Brain hemispheres develop rather symmetrically except in the case of pathology or intense training. As school experience is a form of training, the current study tested the influence of pedagogy on morphological development through the cortical thickness (CTh) asymmetry index (AI). First, we compared CTh AI of 111 students aged 4 to 18 with 77 adults aged > 20. Second, we investigated CTh AI in the students, as a function of schooling background (Montessori or traditional). At the whole-brain level, CTh AI was not different between the adult and student groups, even when controlling for age. However, the pedagogical experience was found to impact CTh AI in the temporal lobe, within the parahippocampal (PHC) region. The PHC has a functional lateralization, with the right PHC having a stronger involvement in spatiotemporal context encoding, while the left PHC is involved in semantic encoding. We observed CTh asymmetry toward the left PHC for participants enrolled in Montessori schools and toward the right for participants enrolled in traditional schools. As these participants were matched on age, intelligence, home life, and socioeconomic conditions, we interpret this effect found in memory-related brain regions to reflect differences in learning strategies. Pedagogy modulates how new concepts are encoded, with possible long-term effects on knowledge transfer.

Objective A trained T1 class Convolutional Neural Network (CNN) model will be used to examine its ability to successfully identify motor imagery when fed pre-processed electroencephalography (EEG) data. In theory, and if the model has been trained accurately, it should be able to identify a class and label it accordingly. The CNN model will then be restored and used to try and identify the same class of motor imagery data using much smaller sampled data in an attempt to simulate live data. Approach PyCharm, a Python platform, will be used to house and process the CNN. The raw data used for the training of the CNN will be sourced from the PhysioBank website. The EEG signal data will then be pre-processed using Brainstorm software that is a toolbox used in conjunction with MATLAB. The sample data used to validate and test the trained CNN, will be also be extracted from Brainstorm but in a much smaller size compared to the training data which is comprised of thousands of images. The sample size would be comparable to a person wearing a Brain Computer Interface (BCI), offering approximately 20 seconds of motor imagery signal data. Results The raw EEG data was successfully extracted and pre-processed. The deep learning model was trained using the extracted image data along with their corresponding labels. After training, it was able to accurately identify the T1 class label at 100 percent. The python coding was then modified to restore the trained model and feed it test sample data in which it was found to recognise 6 out of 10 lines of T1 signal image data. The result suggested that the initial training of the model required a different, more varying approach, so that it would be able to detect varying sample signal image data. The outcome of which could mean that the model could be used in applications for multiple patients wearing the same BCI hardware to control a device or interface.

Research conducted on individuals with depression reveals that major depressive disorders (MDDs) coincide with diminished levels of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) in the brain, as well as modifications in the subunit composition of the primary receptors (GABAA receptors) responsible for mediating GABAergic inhibition. Furthermore, there is substantial evidence supporting the significant role of GABA in regulating stress within the brain, which is a pivotal vulnerability factor in mood disorders. Although there is substantial evidence indicating that GABA may be affecting GABA receptors in peripheral tissues, there is comparatively less evidence supporting its direct action within the brain. Emerging evidence highlights that GABA may exert beneficial effects on the brain and psyche through the gut-brain axis. GABA is readily available and approved as a food supplement in many countries. While GABA enjoys wide consumer acceptance in Eastern Asian markets, with many consumers reporting favorable effects on stress regulation, mood, and sleep, rigorous independent research is still largely lacking. Basic research, coupled with initial clinical findings, makes GABA an intriguing neuro-nutritional compound deserving of clinical studies in individuals with depression and other psychological problems.

Glioblastoma (GBM) is the most aggressive brain cancer. To model GBM in research, orthotopic brain tumor models, including syngeneic models like GL261 and genetically engineered mouse models like TRP, are used. In longitudinal studies, tumor growth and treatment response are typ-ically tracked with in vivo imaging, including bioluminescence imaging (BLI), which is quick, cost-effective, and easily quantifiable. However, BLI requires luciferase-tagged cells, and recent studies indicate that the luciferase gene can elicit an immune response, leading to tumor rejection and experimental variation. We sought to optimize the engraftment of two luciferase-expressing GBM models, GL261 Red-FLuc and TRP-mCherry-FLuc, showing differences in tumor take, with GL261 Red-FLuc cells requiring immunocompromised mice for 100% engraftment. Immuno-histochemistry and MRI revealed distinct tumor characteristics: GL261 Red-FLuc tumors were well-demarcated with densely packed cells, high mitotic activity, and vascularization. In con-trast, TRP-mCherry-FLuc tumors were large, invasive, and necrotic, with perivascular invasion. Quantifying tumor volume using the HALO® AI analysis platform yielded results comparable to manual measurements, providing a standardized and efficient approach for reliable high-throughput analysis of luciferase-expressing tumors. Our study highlights the importance of considering tumor engraftment when using luciferase-expressing GBM models, providing in-sights for preclinical research design.

As the name implies, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA virus and a member of the corona virus family, primarily affecting the upper respiratory system and the lungs. Like many other respiratory viruses, SARS-CoV-2 can spread to other organ systems. Apart from causing diarrhea, another most common but debilitating complication caused by the SARS-CoV-2 is neurological symptoms and cognitive difficulties, which occur in up to two thirds of hospitalized covid patients and ranging from shortness of concentration, overall declined cognitive speed to executive or memory function impairment. Neuro-cognitive dysfunction and “brain fog” are frequently present in COVID-19 cases, which can last several months after the infection, leading to disruption of daily life. Cumulative evidence suggests that SARS-CoV-2 affects vasculature in the extra pulmonary systems directly or indirectly, leading to impairment of endothelial function and even multi-organ damage. The post COVID-19 long-lasting neurocognitive impairments have not been studied fully; and the underlying mechanism remains elusive. In this review, we summarize the current understanding of the effects of COVID-19 on vascular dysfunction and how vascular dysfunction leads to cognitive impairment in patients.

Current lines of research into mood disorders indicate that immune mediators participating in the pathophysiology of chronic somatic disorders have potent influences on brain functions, even when these mediators are produced in peripheral tissues. Elevated levels of circulating immune molecules have been consistently associated with depressive symptoms in a number of clinical populations and experimental models, to the extent that major depressive disorder (MDD) is now seen, at least in part, as a disorder of immunity. This paradigm has brought to the fore the use of anti-inflammatory therapies as adjunctive to standard antidepressant therapy with the hope to improve treatment efficacy, particularly in those cohorts that do not respond well to standard medication. Such new practice requires the availability of biomarkers to tailor these new therapies to those most likely to benefit but also clear mechanisms of action describing the interaction between peripheral immunity and brain function. These mechanisms are generally studied in preclinical models that try to recapitulate the human disease through peripherally induced sickness behaviour as the model for immune-induced MDD. After an appraisal of the data in rodent models and their adherence to the data in clinical cohorts, we propose a modified model of periphery-brain interaction that goes beyond the currently established view of interaction between peripheral cytokines and microglia cells as the driver of depression. Instead, we suggest that brain barriers are primary actors in the communication between body and brain and, as a consequence, in the pathophysiology of the disease. This model suggests novel biomarkers, novel targets for therapies as well as a novel mechanism for resistance to standard treatments.

People who suffer a mild traumatic brain injury (mTBI) have heterogeneous symptoms and disease trajectories, which make it difficult to precisely diagnose and assess complications long-term. Insufficient information is available regarding how to precisely diagnose and assess mTBI. This study identified and compared deficits in cognitive, psychosocial, visual functions, and balance performance between college students with and without histories of mTBI. Global DNA methylation ratio (5-mC%) in blood was also compared as a peripheral epigenetic marker. Twenty-five volunteers participated in this pilot study, including 11 mTBI cases (27.3% females; mean age of 28.7 years, SD=5.92) and 14 healthy controls (64.3% females; mean age of 22.0, SD=4.13). All the participants were assessed for cognitive (by NIH toolbox—executive function, memory, and processing speed), psychological (by PROMIS—depression, anxiety, and sleep disturbances), visual function (by King-Devick and binocular accommodative tests), postural balance performance (by a force plate), and blood 5-mC% (global methylation) levels. Students with mTBI reported significantly poorer episodic memory, severe anxiety, and more sleep disturbance problems. They also had higher blood 5-mC% level (all p’s<.05). No significant differences were found in visual function and postural balance. These findings validate changes in cognitive, psychosocial, and global DNA methylation long after mTBI.

Recent research has identified the gut-brain axis as a key mechanistic pathway and potential therapeutic target in depression. In this paper, the potential role of gut hormones as potential treatments or predictors of response in depression is examined, with specific reference to the peptide hormone motilin. This possibility is explored through two methods: (a) a conceptual review of the possible links between motilin and depression, including evidence from animal and human research as well as clinical trials, and (b) an analysis of the relationship between a functional polymorphism (rs2281820) of the motilin (MLN) gene and cross-national variations in the prevalence of depression. It was observed that (a) there are several plausible mechanisms, including interactions with diet, monoamine, and neuroendocrine pathways, to suggest that motilin may be relevant to the pathophysiology and treatment of depression, and (b) there was a significant correlation between rs2281820 allele frequencies and the prevalence of depression after correcting for multiple confounding factors. These results suggest that further evaluation of the utility of motilin and related gut peptides as markers of antidepressant response is required, and that these molecular pathways represent potential future mechanisms for antidepressant drug development.

Brain-stimulation reward, also known as intracranial self-stimulation (ICSS), is a commonly used procedure for studying brain reward function and drug reward. In electrical ICSS, an electrode is surgically implanted into the medial forebrain bundle in the lateral hypothalamus or the ventral tegmental area in the midbrain. Operant lever responding leads to the delivery of electrical pulse stimulation. The alteration in the stimulation frequency-lever response curve is used to evaluate the impact of pharmacological agents on brain reward function. If a test drug induces a leftward or upward shift in the ICSS response curve, it implies a reward-enhancing or abuse-like effect. Conversely, if a drug causes a rightward or downward shift in the functional response curve, it suggests a reward-attenuating or aversive effect. A significant drawback of electrical ICSS is the lack of cellular selectivity in understanding the neural substrates underlying drug reward versus aversion. Excitingly, recent advancements in optical ICSS (oICSS) have facilitated the development of at least three cell type-specific oICSS models – dopamine-, glutamate-, and GABA-dependent oICSS. In these new models, a comparable frequency-rate response curve has been established and employed to study the substrate-specific mechanisms underlying brain reward function and a drug's rewarding versus aversive effects. In this review article, we summarize recent progress in this exciting research area. The findings in these new behavioral models have not only increased our understanding of the neural mechanisms underlying drug reward and addiction but have also introduced a novel experimental approach in preclinical medication development for treating substance use disorders.

In this paper, we propose an imagined speech-based brain wave pattern recognition using deep learning. Multiple features were extracted concurrently from eight-channel Electroencephalography (EEG) signals. To obtain classifiable EEG data with fewer number of sensors, we placed the EEG sensors on carefully selected spots on the scalp. To decrease the dimensions and complexity of the EEG dataset and to avoid overfitting during the deep learning algorithm, we utilized the wavelet scattering transformation. A low-cost 8-channel EEG headset was used with MATLAB 2023a to acquire the EEG data. The Long-Short Term Memory Recurrent Neural Network (LSTM-RNN) was used to decode the identified EEG signals into four audio commands: Up, Down, Left, and Right. Wavelet scattering transformation was applied to extract the most stable features by passing the EEG dataset through a series of filtration processes. Filtration has been implemented for each individual command in the EEG datasets. The proposed imagined speech-based brain wave pattern recognition approach achieved a 92.50% overall classification accuracy. This accuracy is promising for designing a trustworthy imagined speech-based Brain-Computer Interface (BCI) future real-time systems. For better evaluation of the classification performance, other metrics were considered, and we obtained 92.74%, 92.50% and 92.62% for precision, recall, and F1-score, respectively.

Without protective and/or therapeutic agents the SARS-CoV-2 infection known as coronavirus disease 2019 (COVID-19) is quickly spreading worldwide. It has surprising transmissibility potential, since it could infect all ages, gender, and human sectors. It attacks respiratory, gastrointestinal, urinary, hepatic, and endovascular systems and can reach the peripheral nervous system (PNS) and central nervous system (CNS) through known and unknown mechanisms. The reports on the neurological manifestations and complications of the SARS-CoV-2 infection are increasing exponentially. Herein, we enumerate seven candidate routes, which the mature or immature SARS-CoV-2 components could use to reach the CNS and PNS, utilizing the within-body crosstalk between organs. The majority of SARS-CoV-2 infected patients suffer from some neurological manifestations (e.g., confusion, anosmia, and ageusia). It seems that although the mature virus did not reach the CNS or PNS of the majority of patients, its unassembled components and/or the accompanying immune-mediated responses may be responsible for the observed neurological symptoms. The viral particles and/or its components have been specifically documented in endothelial cells of lung, kidney, skin, and CNS. This means that the blood-endothelial-barrier may be considered as the main route for SARS-CoV-2 entry into the nervous system, with the barrier disruption being more logical than barrier permeability, as evidenced by postmortem analyses.

Alzheimer’s disease (AD) and vascular dementia (VaD) together contribute to almost 90% of all dementia cases leading to major health challenges of our time with a substantial global socioeconomic burden. While in Alzheimer’s disease, the improved understanding of Amyloid beta (Aß) mismetabolism and tau hyperphosphorylation as pathophysiological hallmarks has led to significant clinical breakthroughs, similar advances in VaD are lacking. We thus highlight here the importance of shared pathomechanisms found in AD and VaD: Endothelial damage, blood brain barrier (BBB) breakdown and hypoperfusion inducing oxidative stress, inflammation and demyelination and thus trophic uncoupling in the neurovascular unit. A dysfunctional endothelium and BBB lead to the accumulation of neurotoxic molecules and Aß through impaired clearance, which in turn leads to neurodegeneration. In this context we discuss possible neuropathological parameters, which might serve as biomarkers and thus improve diagnostic accuracy or reveal targets for novel therapeutic strategies for both forms of dementia.

Cancer is the second biggest cause of death in children. With the development of chemotherapy, there is a substantial increase in overall survival rate over recent 30 years. However, the overall mortality rate in children with cancer still remains 25%, and many survivors experience a decline in overall quality of life and long-term adverse effects caused by treatments. Although cancer cells share common characteristics, pediatric cancers are different from adult cancers in their prevalence, mutation load, and drug response. Therefore, there is an urgent unmet need to develop therapeutic approaches specifically designed for children with cancer. Nanotechnology can potentially overcome the deficiencies of conventional methods of administering chemotherapy and ultimately improve clinical outcomes. The nanoparticle-based drug delivery systems can decrease the toxicity of therapy, provide a sustained or controlled drug release, improve pharmacokinetic properties of loading contents, and achieve a targeted drug delivery with achievable modifications. Further, therapeutic approaches based on combining nanoformulated drugs with novel immunotherapeutic agents are emerging. In this review, we discuss the recently developed nanotechnology-based strategies for treating blood and solid pediatric cancers.

A frequent co-morbidity of cerebrovascular pathology and Alzheimer's disease pathology has been observed over past decades. Accordingly, much evidence has been reported which indicates that microvascular endothelial dysfunction, due to cerebrovascular risk factors (e.g., atherosclerosis, obesity, diabetes, smoking, hypertension, aging), precedes cognitive decline in Alzheimer's disease and contributes to its pathogenesis. By incorporating appropriate drug(s) into biomimetic (lipid cubic phase) nanocarriers, one obtains a multitasking combination therapeutic which targets certain cell-surface scavenger receptors, mainly class B type I (i.e., SR-BI), and crosses the blood-brain barrier (BBB). Such targeting allows for various Alzheimer's-related cell types to be simultaneously searched out, in vivo, for localized drug treatment. This in vivo targeting advantage may be particularly important for repurposing an FDA-approved drug, especially one which has shown the added ability to restore some cognitive functions in certain animal models of Alzheimer's disease (e.g., the anticancer drug bexarotene); this (candidate repurposing) drug up to now, by itself (i.e, without nanocarrier), displayed poor CNS penetration in human subjects.

In recent years, advancements in brain science and neuroscience have significantly influenced the field of computer science, particularly in the domain of reinforcement learning (RL). Drawing insights from neurobiology and neuropsychology, researchers have leveraged these findings to develop novel mechanisms for understanding intelligent decision-making processes in the brain. Concurrently, the emergence of quantum computing has opened new frontiers in artificial intelligence, leading to the development of quantum machine learning (QML). This study introduces a novel model that integrates Quantum Spiking Neural Networks (QSNN) and Quantum Long Short-Term Memory (QLSTM) architectures, inspired by the complex workings of the human brain. Specifically designed for reinforcement learning tasks in energy-efficient environments, our approach progresses through two distinct stages mirroring sensory and memory systems. In the initial stage, analogous to the brain’s hypothalamus, low-level information is extracted to emulate sensory data processing patterns. Subsequently, resembling the hippocampus, this information is processed at a higher level, capturing and memorizing correlated patterns. We conduct a comparative analysis of our model against existing quantum models such as Quantum Neural Networks and their classical counterparts, elucidating its unique contributions. Through empirical results, we aim to underscore the effectiveness of our approach in optimizing energy consumption in practical scenarios.

Predictive processes and numerous cognitive, motor, and social skills depend heavily on sequence and statistical learning. The visuomotor Serial Reaction Time Task (SRTT) can measure these fundamental cognitive processes. In this review, we sought to answer whether repetitive transcranial magnetic stimulation (rTMS) is suitable for modulating visuomotor sequence learning and which factors mediate its efficacy. We systematically analyzed the eligible records (n = 17) that attempted to modulate the performance of the SRTT with rTMS. The purpose of the analysis was to determine how the following factors affected SRTT performance: (1) stimulated brain areas, (2) rTMS protocols, (3) stimulated hemisphere, (4) timing of the stimulation, (5) SRTT sequence properties, and (6) other methodological features. The primary motor cortex (M1) and the dorsolateral prefrontal cortex (DLPFC) were found to be the most promising stimulation targets. Low-frequency protocols over the M1 usually weaken performance, but the results are less consistent for the DLPFC. These inconsistencies (at least in part) may be due to the current frequency-based heuristics of rTMS effects developed for explaining local stimulation effects in the motor cortex. Although this review cannot provide an ultimate answer about the optimal stimulation and task parameters, it comprehensively discusses the behavioral effects of six factors that are crucial for designing future studies to modulate sequence learning with rTMS. Moreover, we conclude that synergistically combining functional neuroimaging with rTMS could adequately link the rTMS-induced network effects with the behavioral findings that are crucial to develop a unified cognitive model of visuomotor sequence learning.

This article presents a study on brain tumor detection using the VGG-16 model, a convolutional neural network known for its performance in computer vision tasks. The aim of the study is to classify magnetic resonance imaging (MRI) images and accurately identify the presence of brain tumors. The dataset used consists of brain tumor MRI images, categorized into two classes: "NO" (no tumor) and "YES" (tumor). The methodology involves setting up the environment, importing and preprocessing the data, building the VGG-16 model, and evaluating its performance using metrics such as accuracy, precision, and recall. The results demonstrate an accuracy of approximately 88% on the validation set and 80% on the test set, indicating the potential of the VGG-16 model in supporting healthcare professionals in diagnosing brain tumors. The study contributes to the field of medical image analysis and offers insights into the application of deep learning for brain tumor detection.

Background: Several kinds of research say that adjuvant blood glucose and blood pressure are usual, but an efficient solution for medical application count remains. This review analyzes the pandemic blood pressure and blood glucose to identify the publications which tell about the clinical practices and research gaps in systematic research.Methods: A study guides to identify the research of Blood Pressure (BP) and Blood Glucose. In order to analyze the recent innovations and research on BP and Blood glucose, the relevant publications and literature from journals were identified.Results: Co-morbidity of BP and Blood glucose is reported as very high. The commonness of blood pressure is thrice as high in type I diabetes patients and almost two times higher in type II diabetes patients when compared to others without Diabetes. The pervasiveness of getting depression is more in the female when compared with men. A detailed study about the linkage of BP and blood glucose tells that the relationship between them is not exactly clear.Limitations: Nearly all reviews providing the linkage of BP and blood glucose are with some limitations and they are not providing any clear conclusion.Conclusions: Present research tells that people having high blood glucose will have a greater chance of getting high blood pressure. More research is needed to state the linkage between BP, blood glucose, and the growth of diabetes mellitus issues and to provide support for managing Diabetes.

Multi-Alignment method coupled with phylogenetic analysis we disclosed the Nsp9 and Nsp10 non-structural proteins of Corona Virus as rRNA RlmH/K methyltransferases with similarities with bin recombinase and int-core integrase fold. Further, Nsp9 has similarities to S8 ribosomal protein and Nap10 has similarity to S10 ribosomal protein. Previously, we showed Nsp13, Nsp14, Nsp15 and Nsp16 are also different types of rRNA RlmE/N and Cfr-like methyltransferases-ribonuclease with RNA helicase domains. Two domains of Nsp13 astonishingly have similarities to ribosomal proteins L6 and L9. Taken together, Nsp9/10 and Nsp13-16 proteins could mimic host ribosome assembly and also could methylate rRNA of mitobibosome preventing mitochondrial protein synthesis and oxidative phosphorylation. Low ATP synthesis causes lowering blood pressure following coma but very ATP concentration (1-10nM) surely induces platelets aggregation through vWA, collagen and GpIIb/IIIa proteins followed by fibrin formation and blood clotting as recently have seen in the lung of many Corona virus infected patients. We have also postulated that two polyproteins itself resemble like 28S and 38S mitoribosome subunits and compete with rRNAs inhibiting the ribosome turnover and new protein synthesis due to their similarities with many ribosomal proteins. Such finding may be valuable in computer-based novel drug design against Corona virus.

Medical brain image analysis is a necessary step in the Computers Assisted /Aided Diagnosis (CAD) systems. Advancements in both hardware and software in the past few years have led to improved segmentation and classification of various diseases. In the present work, we review the published literature on systems and algorithms that allow for classification, identification, and detection of White Matter Hyperintensities (WMHs) of brain MRI images specifically in cases of ischemic stroke and demyelinating diseases. For the selection criteria, we used the bibliometric networks. Out of a total of 140 documents we selected 38 articles that deal with the main objectives of this study. Based on the analysis and discussion of the revised documents, there is constant growth in the research and proposal of new models of deep learning to achieve the highest accuracy and reliability of the segmentation of ischemic and demyelinating lesions. Models with indicators (Dice Score, DSC: 0.99) were found, however with little practical application due to the uses of small datasets and lack of reproducibility. Therefore, the main conclusion is to establish multidisciplinary research groups to overcome the gap between CAD developments and their complete utilization in the clinical environment.

The central nervous system (CNS) is the final frontier in drug delivery because of the blood-brain barrier (BBB), which poses significant barriers to the access of most drugs to their targets. Kynurenic acid (KYNA), a tryptophan (Trp) metabolite, plays an important role in behavioral functions and abnormal KYNA levels have been observed in neuropsychiatric conditions. The current challenge lies in delivering KYNA to the CNS owing to its polar side chain. Recently, C-3 side chain modified KYNA analogs have been shown to cross the BBB; however, it is unclear whether they retain the biological functions of the parent molecule. This study examined the impact of KYNA analogs, specifically SZR-72, SZR-104, and the newly developed SZRG-21, on behavior. The analogs were administered intracerebroventricularly (i.c.v.), and their effects on the motor domain were compared with those of KYNA. Specifically, open field (OF) and rotarod (RR) tests were employed to assess motor activity and skills. SZR-104 increased horizontal exploratory activity in the OF test at a dose of 0.04 μmol/4 μL, while SZR-72 decreased vertical activity at doses of 0.04 and 0.1 μmol/4 μL. In the RR test, however, neither KYNA nor its analogs showed any significant differences in motor skills at either dose. Side chain modification affects affective motor performance and exploratory behavior, as the results show for the first time. In this study, we showed that KYNA analogs alter emotional components such as motor-associated curiosity and emotions. Consequently, drug design necessitates the development of precise strategies to traverse the BBB while paying close attention to modifications in their effects on behavior.

Survivors of severe brain injury may require care in a neurointensive care unit (neuro-ICU), where the brain is vulnerable to secondary brain injury. Thus, there is a need for noninvasive, bedside, continuous cerebral blood flow monitoring approaches in the neuro-ICU. Our goal is to address this need through combined measurements of EEG and functional optical spectroscopy (EEG-Optical) instrumentation and analysis to provide a complementary fusion of data about brain activity and function. The present case demonstrates in a patient with traumatic brain injury, noninvasive cerebral blood flow transients can be recorded that correlate with gold-standard invasive measurements and with the frequency content changes in the EEG data during clinical care.

Neuroscience has overwhelmingly and understandably focused on the synaptic modality of signal transmission. There is evidence, however, that from an evolutionary perspective, non-synaptic transmission (NST) preceded synaptic signaling. Moreover, in modern nervous systems, NST coexists and extensively interacts with synaptic transmission modifying neuronal dynamics. In fact, NST remains widespread in complex animals, especially within the interoceptive system where the dearth of insulating barriers such as myelin sheaths and the blood-brain barrier enhances the communication between neural and non-neural tissues mediated by NST. We suggest that this physiological arrangement makes a fundamental contribution to interoception¾the process of sensing visceral states¾which is an essential underpinning of the capacity to feel and the foundation of affective processing.

Accurate geometric modeling of blood vessels lumen given their 3D images is a basis for vessel quantification in support of cardiovascular diseases diagnosis, treatment and monitoring. Unlike other approaches, which assume circular or elliptical vessel cross-section, the proposed method employs parametric B-splines combined with the image formation system equations to accurately localize the highly curved lumen boundaries. No image segmentation is involved which might reduce the localization accuracy in effect of spatial discretization. It is shown that the model parameters can be reliably identified by a feedforward neural network which, driven by the cross-section images, predicts the parameter values many times faster than a reference least-squares (LS) model fitting algorithm. Two example applications: modeling the lower extremities artery-vein complexes visualized in steady-state contrast-enhanced magnetic resonance images (MRI) and the coronary arteries pictured in computed tomography angiograms (CTA), are presented and discussed to demonstrate the method potential. Besides application to medical diagnosis, blood-flow simulation and vessel-phantom design, it can serve as a tool for automated annotation of image datasets required to train machine-learning algorithms.

Central Nervous System (CNS) cancers pose a formidable challenge in the medical world, characterized by aggressive behaviors and limited therapeutic options. The emergence of nanomedicine has offered new hope in CNS cancer treatment. The COVID-19 pandemic has further accelerated the need for innovative therapeutic strategies, emphasizing the significance of nanomedicine in this era. This mini review explores the current status of nanomedicine in CNS cancer therapy, with a particular focus on the post-COVID-19 landscape. We discuss the unique challenges presented by CNS cancers, the potential of nanomedicine in overcoming these challenges, and the recent developments in the field. Additionally, we highlight the lessons learned from the pandemic and how they can be applied to improve CNS cancer therapeutics. We also shed light on the evolving regulatory landscape and the prospects of personalized nanomedicine in CNS cancer treatment. The integration of nanomedicine in CNS cancer therapy is becoming increasingly promising, and its role in the post-COVID-19 era is poised to shape the future of neuro-oncology.

Background: High blood pressure (BP) has been implicated as a major risk factor for cardiovascular diseases in several global populations, including in individuals of African ancestry. Despite the elevated burden of high BP-induced cardiovascular diseases in Africa and other global populations with African ancestry, limited genetic studies have been carried out to explore the genetic machinery driving this phenomenon. Methods: We performed univariate and multivariate analyses using Genome-wide association studies (GWAS) and summary statistics data of 77,850 individuals of African ancestry for systolic (SBP) and diastolic blood pressure (DBP) traits. The six independent cohorts used included individuals derived from the African Partnership for Chronic Disease Research (APCDR), the UK Biobank, and the Million Veteran Program (MVP). Subsequently, we annotated, prioritized, visualized, and interpreted our meta-analyses results using FUMA, to gain further insight into the molecular mechanism(s) that contribute to the genetics of BP traits. Finally, loci attaining genome-wide significance, GWS (p<5x10-8) were also followed up with Bayesian fine-mapping to identify potential causal variants. Results: Our meta-analyses altogether identified 350 GWAS SNPs for SBP (166 SNPs) and DBP (184 SNPs, including two novel loci) whilst our multivariate GWAS method identified 166 SNPs (including three novel loci). Interestingly, in FUMA there was significant tissue enrichment of up-regulated differentially expressed genes (DEGs) in the sigmoid and transverse colon for SBP, as well as 10 significant gene sets from MAGMA gene set analyses, However, for DBP, no significant DEGs nor gene sets in MAGMA were found; instead, in DBP for gene property analysis for tissue specificity nine candidates were found to be significant and all nine were in different brain regions. Finally, Bayesian fine-mapping revealed that only 11 variants from the lead SNPs had >50% posterior probability (PP) of being causal and they included novel variant rs562545 (MOBP, PP = 77%) and 10 other previously published variants. Conclusion: Our results demonstrate the importance of performing GWAS in large sample sizes of global populations of African ancestry, including continental Africans; which yield novel insights, from novel loci to novel pathways/tissue expression candidates. Large-scale genomic datasets are required to enhance further discovery and fine-mapping of high-risk loci/variants in highly susceptible groups for cardiovascular disease and other related traits. Our study highlights the need for diversity in genetic research and the importance of expanding large GWASs to include ancestrally diverse populations.

The study aimed to showcase how implementing a patient blood management (PBM) program effectively cut unnecessary red blood cell (RBC) transfusions in a New York City urban community teaching hospital. Analyzing seven years from 2013 to 2019, a retrospective review of RBC transfusions was conducted. Following PBM introduction, considerable improvements were observed annually. These included a drop in mean pretransfusion hemoglobin levels from 7.26g/dL (2013) to 6.58g/dL (2019), a 34% reduction in yearly RBC unit transfusions, and fewer units given to patients with pre-Hgb levels ≥7g/dL (1210 units in 2013 to 310 units in 2019). Furthermore, the study noted a decline in two-unit RBC orders when Hgb levels were ≥7g/dL from 65 orders in 2013 to merely 3 in 2019. The estimated total cost-savings attributed to the six-year PBM program duration after full implementation in 2014 amounted to $2.1 million US dollars. Overall, PBM implementation significantly decreased RBC transfusions and enhanced transfusion practices. The findings emphasize that successful PBM strategies don't always necessitate extensive resources or increased budgets but instead rely on the application of intuitive methods, as evidenced by this study.

The advent of deep learning (DL) has revolutionized medical imaging, offering unprecedented avenues for accurate disease classification and diagnosis. DL models have shown remarkable promise for classifying brain tumor from Magnetic Resonance Imaging (MRI) scans. However, despite their impressive performance, the opaque nature of DL models poses challenges in understanding their decision-making processes, particularly crucial in medical contexts where interpretability is essential. This paper explores the intersection of medical image analysis and DL interpretability, aiming to elucidate the decision-making rationale of DL models in brain tumor classification. Leveraging state-of-the-art DL frameworks with transfer learning, we conduct a comprehensive evaluation encompassing both classification accuracy and interpretability. Using state-of-the-art DL frameworks with transfer learning, we conduct a thorough evaluation covering both classification accuracy and interpretability. We employ adaptive path-based techniques to understand the underlying decision-making mechanisms of these models. Grad-CAM and Grad-CAM++ highlight critical image regions where the tumors are located.

My hypothesis is that the signs and symptoms of Long COVID can be explained by a shortage of blood in the body and a resulting deficient blood flow through nearly all organs. This shortage arises through damage to the blood-producing organs during the acute phase, while the breakdown of blood continues as normal, after an initial increase. In order to ensure the perfusion of organs that are directly necessary for survival, the body takes the emergency measure of diverting blood from other organs and tissues. The perfusion of the blood-producing organs is also affected by this distribution measure, which hinders the smooth recovery of the total blood volume. The body is stuck in this vicious circle: a shortage of circulating blood hinders the recovery of blood production. This explains the long duration of Long COVID. My proposed treatment of Long COVID focuses on the recovery of the correct volume of blood in the body of the right composition by the very careful administration of donor blood products under continuous expert supervision. A trial treatment can be performed in any hospital without much additional preparations, and has a lower associated risk for the patient than analysing the total blood. A diagnosis ex juvantibus, by therapeutic response, is therefore preferable, and will result in the healing process starting earlier. Indications in blood laboratory values of a shortage of blood are a high serum ferritin due to internal breakdown of blood and values for haematocrit and albumin at reciprocal extremes of the reference ranges due to a stagnation of blood production.

The purpose of this work was to evaluate a novel methodology developed by Digital Blood Corporation (DBC) to calculate critical blood values using four non-invasive measured values as input. The values obtained using a point-of-care testing (POCT) device were utilized for comparison and reference. Radial arterial blood was collected for the POCT comparator analysis using the Abbott i-STAT^® device. The non-invasive methodology from DBC requires four parameters to be directly measured: temperature, hemoglobin, pO2, and pCO2. Subsequently, sodium, potassium, chloride, ionized calcium, total carbon dioxide, pH, bicarbonate, and oxygen saturation are calculated using an algorithm. The agreement between the POCT and DBC’s methodology was analyzed using Bland-Altman difference plots. For a second data set, pO2 and pCO2 values collected with the POCT were used as input for DBC’s algorithm to test its robustness. Data from 37 healthy ambulatory individuals, mean age: 42.4 + 13 years; range: 18-64 years, were included in the primary analysis. In the case of the non-invasive gained four input values the greatest variation between POCT and DBC’s approach was observed for pO2 and consequently for algorithm values that depend upon pO2 precision. Replacing transcutaneous pO2 and pCO2 with POCT values demonstrates the principal ability of DBC’s algorithm to predict the additional 8 blood values in sufficient agreement with a standard POCT device in healthy patients. The algorithm developed by DBC appears to be robust in the case of healthy patients but does need the four measured input values with preciseness comparable to a POCT device to give reliable and clinically relevant results. The present study thus serves as a proof of concept to facilitate future study and further development of this methodology into a non-invasive device.

(1) Background: This study aimed to evaluate whether the implementation of a modified blood sampling protocol, which focused on need-based laboratory testing and minimized venous sampling by replacing it with point-of-care testing (POCT) via capillary puncture, successfully reduced iatrogenic blood loss, incidence of anemia, and frequency of blood transfusion in extremely low birth weight infants (ELBWIs) without negatively affecting neonatal outcomes. (2) Methods: A retrospective analysis was conducted on 313 ELBWIs of gestational age (GA) between 23 and 28 weeks, born between 2013 and 2019. The infants were divided into two groups: before (period I) and after (period II) the implementation of the modified blood sampling protocol in January 2016. Propensity score matching was conducted to minimize selection bias. Clinical data, including the frequency and amount of blood sampling, frequency and volume of blood transfusion, and clinical characteristics, such as gestational age, birth weight, and neonatal outcome data, were collected and compared between the two groups. (3) Results: No significant differences in the GA or birth weight between the two periods were observed. The total sampling volume during a month after birth (16.7 ± 4.1 mL vs. 15.6 ± 4.4 mL, P=0.03) and total sampling volume during hospital days (51.4 ± 29.7 mL vs. 44.3 ± 27.5 mL, P=0.04) in period II were significantly lower than that in period I. There were no differences in the mortality or morbidity between the two periods. Although the transfusion frequency and amount did not have significant differences between the periods, we observed a positive correlation between the transfusion frequency and sampling volume (coefficient: 0.09, 95% CI: 0.08–0.11). (4) Conclusions: The modified blood sampling protocol effectively reduced the iatrogenic blood loss without negatively affecting the neonatal outcomes.

Animal models of Alzheimer’s disease amyloidosis that recapitulate cerebral amyloid-beta pathology have been widely used in preclinical research, and have greatly enabled the mechanistic understanding of Alzheimer’s disease and the development of therapeutics. Comprehensive deep phenotyping of the pathophysiological and biochemical features in these animal models are essential. Recent advances in positron emission tomography have allowed the non-invasive visualization of the alterations in the brain of animal models as well as in patients with Alzheimer’s disease, These tools have facilitated our understanding of disease mechanisms, and provided longitudinal monitoring of treatment effect in animal models of Alzheimer’s disease amyloidosis. In this review, we focus on recent positron emission tomography studies of cerebral amyloid-beta accumulation, hypoglucose metabolism, synaptic and neurotransmitter receptor deficits (cholinergic and glutamatergic system), blood-brain barrier impairment and neuroinflammation (microgliosis and astrocytosis) in animal models of Alzheimer’s disease amyloidosis. We further propose the emerging targets and tracers for reflecting the pathophysiological changes, and discuss outstanding challenges in disease animal models and future outlook in on-chip characterization of imaging biomarkers towards clinical translation.

Enzyme replacement therapy (ERT) improves the somatic manifestations in mucopolysaccharidoses (MPS))．However, because intravenously administered enzymes cannot cross the blood brain barrier (BBB), ERT is ineffective against the progressive neurodegeneration and resultant severe central nervous system (CNS) symptoms observed in patients with neuronopathic MPS. Attempts to surmount this problem have been made with intrathecal and intracerebroventricular ERT intend to achieve CNS effects, but the burdens on patients are inimical to long-term multiple administrations. However, after pabinafusp alfa, a human iduronate-2-sulfatase fused with a BBB-crossing anti-transferrin receptor antibody, showed both central and peripheral efficacy in mice model, subsequent clinical trials in a total of 62 patients with MPS-II (Hunter syndrome) in Japan and Brazil substantiated this dual efficacy and provided an acceptable safety profile. To date, pabinafusp alfa is the only approved intravenous ERT effective against both the somatic and CNS symptoms of patients with MPS-II. This article summarizes the hitherto obtained preclinical and clinical evidence associated with this drug, and discusses the preclinical, translational and clinical challenges of evaluating, ameliorating and preventing the neurodegeneration in patients with MPS-II.

As the world endures the coronavirus disease 2019 (COVID-19) pandemic, conditions of 35 million vulnerable individuals struggling with substance use disorders (SUDs) worldwide have not received sufficient attention for their special health and medical needs. Many of these individuals are complicated by underlying health conditions, such as cardiovascular and lung diseases and undermined immune systems. During the pandemic, access to the healthcare systems and support groups is greatly diminished. Current research on COVID-19 has not addressed the unique challenges facing individuals with SUDs, including the heightened vulnerability and susceptibility to the disease. In this systematic review, we will discuss the pathogenesis and pathology of COVID-19, and highlight potential risk factors and complications to these individuals. We will also provide insights and considerations for COVID-19 treatment and prevention in patients with SUDs.

Stroke remains a major cause of death and disability in the United States and around the world. Solid safety and efficacy profiles of novel stroke therapeutics have been generated in the laboratory, but most failed in clinical trials. Investigations into the pathology and treatment of the disease remain a key research endeavor in advancing scientific understanding and clinical applications. In particular, cell-based regenerative medicine, specifically stem cells transplantation, may hold promise as stroke therapy because grafted cells and their components may recapitulate the growth and function of the neurovascular unit, which arguably represents the alpha and omega of stroke brain pathology and recovery. Recent evidence has implicated mitochondria, organelles with a central role in energy metabolism and stress response, in stroke progression. Recognizing that stem cells offer a source of healthy mitochondria, potentially transferrable into ischemic cells, may provide a new therapeutic tool. To this end, deciphering cellular and molecular processes underlying dysfunctional mitochondria may reveal innovative strategies for stroke therapy. Here, we review recent studies capturing the intimate participation of mitochondrial impairment in stroke pathology, and showcase promising methods of healthy mitochondria transfer into ischemic cells, to critically evaluate the potential of mitochondria-based stem cell therapy for stroke.

Combined radiation with hemorrhage (combined injury, CI), exacerbates hematopoietic acute radiation syndrome and mortality compared to radiation alone (RI). We evaluated the effects of RI or CI on blood cell depletion as a biomarker to differentiate the two. Male CD2F1 mice were exposed to 8.75 Gy γ- radiation (60Co). Within 2 h of RI, animals were bled under anesthesia 0% (RI) or 20% (CI) of total blood volume. Blood samples were collected at 4-5 h and days 1, 2, 3, 7, and 15 after RI. CI decreased WBC at 4-5 h and continued to decrease them until day 3; counts then stayed at the nadir up to day 15. CI decreased neutrophils, lymphocytes, monocytes, eosinophils and basophils more than RI on day 1 or day 2. CI decreased RBCs, hemoglobin and hematocrit on days 7 and 15 compared to RI, whereas Hemorrhage alone returned to the baseline on days 7 and 15. RBCs depleted after CI faster than post RI. Hemorrhage alone increased platelet counts on days 2, 3, and 7, which returned to the baseline on day 15. Our data suggest that WBC depletion may be a biomarker within 2 days post-CI and RBC depletion after 3 days post-CI.

Whole-brain radiation therapy and stereotactic radiosurgery are two treatment modalities commonly utilized to treat brain metastases (BMs). The aim of this study is to retrospectively analyze the main radio-oncologic and clinical-demographic aspects of a cohort of BM patients treated with Volumetric Modulated Arc Therapy for radiosurgery (VMAT-RS). This is a cross-sectional observational design study with retrospective review of medical records of patients with brain metastases treated with VMAT- RS between 2012 and 2018. Clinical and demographic data, with special attention to sex, age, primary tumor, brain tumor-related epilepsy (BTRE), number and brain location of BMs, Karnofsky Performance Status (KPS), the updated DS-GPA prognostic index and the survival estimated according to the Kaplan-Meier model from the date of radiosurgery were analyzed. One hundred and twenty-one patients with 229 BMs were treated with VMAT-RS. Patients presented 1-4 BMs, which were treated with 5 non-coplanar VMAT arcs. Sixty-eight percent of the patients had lung cancer and 35% of the BMs were in the frontal lobe. Proportion of local control was 88.5%. BTRE prevalence was 30.6%. The median survival time (MST) was 7.7 months. In the multivariate analysis of the Cox Regression model KPS70 (HRKPS&lt;70=2.59; p=0.001) and higher DS-GPA (HRDS-GPAII =0.55, p=0.022; HRDS-GPAIII-IV =0.38, p=0.006) were associated with improved survival. In the univariate analysis, primary tumor, age and the presence of metastases in the posterior fossa (PFBMs) were also significative. In conclusion, the VMAT-RS is a technique with an overall survival comparable to other radiosurgery techniques. The median survival is significantly longer in those with higher KPS and DS-GPA. Other variables such as the type of primary tumor, age and PFBMs could also influence survival, although further studies are needed.

Traumatic Brain Injury (TBI) remains a leading cause of morbidity and mortality among all ages; despite the advances, understanding pathophysiological responses after TBI is still complex, involving multiple mechanisms. Previous reviews have focused on potential targets; however, the research on potential targets has continuously grown in the last five years, bringing even more alternatives and elucidating previous mechanisms. Knowing the key and updated pathophysiology concepts is vital for adequate management and better outcomes. This article reviews the underlying molecular mechanisms, the latest updates, and future directions for pathophysiology-based TBI management.

Intracortical microelectrodes that can be implanted have the ability to capture fast-changing neuron action potentials in the living brain. Despite this potential, many obstacles must still be overcome for reliable, long-term, high-quality recordings and accurate analysis of brain activity. These challenges include improving recording quality, enhancing recording stability, increasing recording capacity, and adding multi-functional features. One potential approach to enhance implantable microelectrodes involves the advancement of materials, refinement of implantation methodologies, and augmentation of the number of sites for recording. However, these challenges are still being actively researched, and advancements in microelectrode technology are underway. The difficulties with implantable microelectrodes are evaluated, and solutions are presented from different perspectives. The latest advancements in microelectrode technology are reviewed and condensed, and future possibilities are explored.

Along just over a century of research we moved from learning how to cultivate tissues in a dish to grasping the concepts for creating an entire brain in a vat. As we approach the divisive moment in which we can first detect signs of awareness in such artificially developed organoids, we need to lay foundation for what lays ahead. It is crucial that ethical, legal and moral implications of organoid research are clear and that boundaries are set to separate scientific progress from human life preservation. The largest obstacle may be the definition of consciousness itself, which has arguably been historically neglected by philosophy, psychology and neurosciences at large. One reason may be the difficulties posed by the underlying qualities of awareness, such as its subjective and heterogeneous nature. Another reason may lie on the possibly that consciousness is an overarching emergent property of our brain. For the time being, one can see brain organoids as philosophical zombies, physical analogues of the human brain which mimic sentient human reactions but lack experiential properties of sensation (a.k.a. qualia).

Glycosylation is a complex post-translational modification that conveys functional diversity to glycoconjugates. Cell surface glycosylation mediates several biological activities such as induction of intracellular signaling pathway and pathogen recognition. Red blood cell (RBC) membrane N-glycans determine blood type and influence cell lifespan. Although several proteomic studies were carried out, glycosylation of RBC membrane proteins has not been systematically investigated. This work aims at exploring the human RBC N-glycome by high-sensitivity MALDI-MS techniques to outline a fingerprint of RBC N-glycans. To this purpose, MALDI-TOF spectra of healthy subjects harboring different blood groups were acquired. Results showed the predominant occurrence of neutral and sialylated complex N-glycans with bisected N-acetylglucosamine, core- and/or an-tennary fucosylation. In the higher mass region these species presented with multiple N-acetyllactosamine repeating units. Amongst the detected glycoforms, the presence of glycans bearing ABO(H) antigens allowed us to define a distinctive spectrum for each blood group. For the first time, advanced glycomic techniques have been applied to a comprehensive exploration of human RBC N-glycosylation, providing a new tool for the early detection of distinct glycome changes associated with disease conditions as well as to understand pathogens molecular recognition.

This study explored the effects of a comprehensive health care program (CHCP) on blood pressure, blood glucose, body composition, and depression in older adults living alone. We used a quasi-experimental, two-group, pre-posttest design. The CHCP consisted of open lectures, health counseling, exercise classes, nutrition counseling, and self-help group meetings at a local senior welfare center. Fifty-eight subjects participated in this study, with thirty subjects in the experimental group and twenty-eight subjects in the control group. Data were analyzed using the descriptive statistics, χ²-test, and t-test. Comparisons of the pretest and posttest systolic blood pressure (t = - 2.530, p < .016) and blood glucose (t = 3.089, p < .004) between the experimental and control groups showed significant differences. In both the experimental (t = 3.949, p < .001) and control groups (t = 3.816, p < .002), depression symptoms showed a significant decrease post-test, compared with pre-test. Our findings infer that older adults require physical and psychosocial healthcare and that more efforts must be made to improve the general health and wellbeing of this population group.

product transfusions, but clinical practices vary widely. Many very low birth weight (VLBW) infants receive packed red blood cell (RBC) or platelet transfusions during their initial NICU stay, with incidence inversely proportional to gestational age at birth ^1,2. Many critically ill infants are also transfused with plasma or cryoprecipitate to promote coagulation ^3,4. These blood product transfusions are most often prophylactic, with clinical decisions made in response to numerical blood count values, as opposed to therapeutic transfusions in the context of active bleeding.Emerging evidence has shown that some transfusion practices are harmful for certain NICU patients, such as platelet transfusions in preterm infants ^5,6. More broadly, transfusion reactions can occur with virtually all blood products ⁷ and these reactions are likely under-diagnosed, under-estimated, and under-reported in pediatric patients ³. Our intention was to establish optimal transfusion guidelines for our division and neonatal network, including 19 hospitals, based on a review of currently available literature.

Blood has certain significant physical properties, which the authors investigated. This paper provides values of surface tension and viscosity of blood at 37 °C, as well as relationship between them plotted on a cross-plot. By applying Hagen- Poiseuille equation and Jurin's law to the experimentally obtained data, the authors calculated with great accuracy viscosity and surface tension of blood. Evaluating both of the properties using described methods required from the authors to know the density of investigated liquid, which was found to be on average $\rho=1063,56 \frac{kg}{m^3}$. The authors took blood samples from 30 healthy subjects and determined aforementioned physical properties. There has been made a distinction in regard of a sex of the blood donor. Results indicate that both surface tension and viscosity are independent from sex of a subject, as well as indicate that there is no correlation between viscosity and surface tension of blood at 37\degree C. Average values of surface tension and viscosity were found to be $\sigma=5,241\pm 0,262 \cdot 10^{-2}\frac{J}{m^2}$ and $\eta=3,352\pm0,360 \cdot 10^{-3} Pa \cdot s$, respectively.

Background: There is an increasing interest in the role of EEG in neurorehabilitation. We primarily aimed to identify the knowledge base through highly influential studies. Our secondary aims were to imprint the relevant thematic hotspots, research trends, and social networks within the scientific community. Methods: We performed an electronic search in Scopus looking for studies reporting on rehabilitation in patients with neurological disabilities. The most influential papers outlined the knowledge base, while a word co-occurrence analysis imprinted the research hotspots. Likewise, co-citation analyses highlighted collaboration networks between Universities, authors, and countries. The results were presented in summary tables, burst detection plots, and geospatial maps. Finally, a content review based on the top-20 most cited articles completed our study. Results: Our current bibliometric study was based on 874 records from 420 sources. There was a vivid research interest in EEG use for neurorehabilitation, with an annual growth rate as high as 14.3%. The most influential paper was the study titled "Brain-computer interfaces, a review" by Nicolas-Alfonso LF and Gomez-Gill J, with 997 citations, followed by "Brain-computer interfaces in neurological rehabilitation" by Daly J. and Wolpaw JR (708 citations). The USA, Italy, and Germany were among the most productive countries. The research hotspots shifted with time from the use of “functional magnetic imaging” to EEG-based “brain-machine interface”, “motor imagery”, and “deep learning”. Conclusions: EEG constitutes the most significant input in brain-computer interfaces (BCI) and can be successfully used in the neurorehabilitation of patients with stroke, amyotrophic lateral sclerosis, and traumatic brain and spinal injury. EEG-based BCI facilitates training, communication, and control of wheelchair and exoskeletons. However, research is limited to specific scientific groups from developed countries. Evidence is expected to change with the broader availability of BCI and improvement in EEG filtering algorithms.

Recent progress in microfabrication technique allowed the rapid development of neural implants. They are getting categorized as effective tools for clinical practice, especially to treat traumatic and neurodegenerative disorders. Microelectrode arrays already have been used in numerous neural interface devices. Basically, almost all neural implants have been developed based on BCI (Brain Computer Interface) system. When BCI system falls under invasive technique, it is referred as BMI or Brain Machine Interface. BMIs hold promises for neurorehabilitation of motor and sensory function, cognitive state evaluation and treatment of neurological chaos. A directed overview of the field of neural implants is discussed in this article. The aim of this review is to give a brief introduction of neural prosthetics as well as their exciting applications in treating neurological disorders and a deep discussion on their functionality are mentioned. BCI system and their different types, their functionality, their pros and cons, how other neural implants developed, and their present status have been covered. Different possibilities and possible future of deep brain stimulation (DBS), Neuralink, motor and sensory neural prosthetics are further discussed.

Tissues of the brain, especially white matter, are extremely heterogeneous - with constitutive response varying spatially. In this paper, we implement a high-resolution Finite Element (FE) head model where heterogeneities of white matter structures are introduced through Magnetic Resonance Elastography (MRE) experiments. Displacement of white matter under shear wave excitation is captured and the material properties determined though an inversion algorithm are directly used in the FE model. This approach is found to improve model predictions when compared to experimental results. In the first place, responses in the cerebrum near stiff structures such as the corpus callosum and corona radiata are markedly different compared with a homogenized material model. Additionally, the heterogeneities introduce additional attenuation of the shear wave due to wave scattering within the cerebrum.

One of the biggest queries in cognitive sciences is the emergence of consciousness from matter. Modern neurobiological theories of consciousness propose that conscious experience is the result of interactions between large-scale neuronal networks in the brain, traditionally described within the realm of classical physics. Here, we propose a generalized connectionist framework in which the emergence of “conscious networks” is not exclusive of large brain areas, but can be identified in sub-cellular networks exhibiting non-trivial quantum phenomena. The essential feature of such networks is the existence of strong correlations in the system (classical or quantum coherence) and the presence of an optimal point at which the system’s complexity is maximized, expressed either by maximization of the information content in large scale functional networks or by achieving optimal efficiency through the quantum Goldilock effect.

Exposure to traffic-related air pollution is linked with acute alterations in blood pressure (BP). We examined the cumulative short-term effect of black carbon (BC) exposure on systolic (SBP) and diastolic (DBP) BP and assessed effect modification by participant characteristics. SBP and DBP were repeatedly measured on 152 traffic enforcers. Using a linear mixed-effects model with random intercepts, quadratic (QCDL) and cubic (CCDL) constrained distributed lag models were fitted to estimate the cumulative effect of BC concentration on SBP and DBP during the 10-hours (daily exposure) and 7-days (weekly exposure) before the BP measurement. Ambient BC was related to increased BP with QCDL models. An interquartile range change in BC cumulative during the 7-days before the BP measurement was associated with increased BP [1.2% change in mean SBP, 95% confidence interval (CI), 0.1 to 2.3; and 0.5% change in mean DBP, 95% CI, –0.8 to 1.7]. Moreover, the association between the 10-hours cumulative BC exposure and SBP was stronger for females (4.0% change, 95% CI: 2.1–5.9) versus males, and for obese (2.9% change, 95% CI: 1.0–4.8) vs. non-obese traffic enforcers. Short-term cumulative exposure to ambient traffic-related BC could bring about cardiovascular diseases through mechanisms involving increased BP.

A brain tumor is an abnormal mass of tissue found inside the brain that consists of cells that grow and multiply without any control and unchecked by the mechanisms that regulate normal cell growth. It is one of the leading causes of death in many different regions worldwide, affecting various ages, sex, race, or ethnicities. Besides being a life-threatening condition, it can also disrupt normal brain function leading to severe cognitive morbidity. Additionally, the cost associated with active treatment and palliative care of the brain tumor most often proves to be out of reach for many people. Over the past decades, even though we have several published literature showing the epidemiology and characteristics of brain tumors, up-to-date epidemiological data is yet to be published. This review will provide comparable recent statistics regarding the incidence of brain tumors in 3 different regions; - the USA, the UK, and Australia. Also, a focus will be given to brain tumor’s key characteristics, classifications, and treatment protocol.

Cardiotonic steroids (CTS) are a group of steroid compounds derived from certain plants and animals. CTS are selective inhibitors of Na,K-ATPase, so for a long time they were widely used for medical purposes to treat heart failure and some other diseases. However, over time, doctors gradually began to refuse this group of drugs due to their narrow therapeutic range and a number of serious side effects. However, in parallel with the rise and fall of interest in CTS as a drug, interest in them as a single class of high-affinity Na,K-ATPase inhibitors has only increased. Numerous data on the effect of CTS on signaling cascades and cell viability made impelling a search for a rationale for the existence of such a subtle biological regulator. A large number of studies devoted to the potential use of CTS in the treatment of neurodegenerative, oncological, immune and other diseases "revitalized" the already "written off" group of the drugs. If initially the role of exogenous (mainly plant origin) CTS was studied, then by the 90s of the XX century the study of the role of endogenous CTS and their regulatory effects became a popular trend in biology and physiology. The role of endogenous CTS was studied in details in the pathogenesis of cardiovascular diseases [1]. A large number of researchers have unanimously stated that endogenous CTS are very complex regulators of the development of pathological processes; however, the exact cause-and-effect relationship that would unambiguously explain the processes of synthesis, utilization, and the role of endogenous CTS has not yet been established. The effects of CTS in the frame of various regulatory schemes have been described, but the predominant number of studies was devoted to arterial hypertension, heart and renal failure, cancer [2–4], aging [5,6], and neuroinflammation. The effects of both endo- and exogenous CTS on blood cells and have been studied to a much lesser extent.

There is no well-defined threshold for intra-operative blood transfusion (BT) in advanced epithelial ovarian cancer (EOC) surgery. We developed a Machine Learning (ML)-driven prediction algorithm to trigger and explain a communication alert for BT based on anticipated peri-operative events irrespective of BT policies. We analysed prospectively collected data from 403 EOC patients who underwent cytoreductive surgery between 2014 and 2019. We calculated the estimated blood volume (EBV) using the formula EBV = weight x 80 and set off 10%EBV as threshold for individual intervention. Based on the known estimated blood loss (EBL) we identified two groups. We employed Receiver operating characteristic (ROC) curves for performance metrics. The model performance for the above threshold prediction was satisfactory (AUC 0.823, 95% CI 0.76-0.88). The top feature commonly shared between interrogators was operative time (OT). Intra-operative blood loss of at least 10%EBV was associated with OT&gt;250 minutes, primary surgery, serous histology, performance status 0, R2 resection and surgical complexity score &gt;4. Large bowel resection, stoma formation, ileocecal resection/right hemicolectomy, mesenteric resection, bladder and upper abdominal peritonectomy were amongst sub-procedures clearly associated with increased intervention risk. Precise prediction of blood requirements is not possible unless a rough estimate of OT is known in advance.

Familial Exudative Vitreoretinopathy (FEVR), Norrie disease, and persistent fetal vascular syndrome (PFVS) are extremely rare retinopathies that are clinically distinct but are unified by abnormal retinal endothelial cell function – and subsequent irregular retinal vascular development and/or aberrant inner blood-retinal-barrier (iBRB) function. The early angiogenesis of the retina and its iBRB is a delicate process that is mediated by the canonical Norrin Wnt-signaling pathway in retinal endothelial cells. Pathogenic variants in genes that play key roles within this pathway such as NDP, FZD4, TSPAN12, and LRP5, have been associated with the incidence of these retinal diseases. Recent efforts to further elucidate the etiology of these conditions have not only highlighted their multigenic nature but have also resulted in the discovery of pathological variants in additional genes such as CTNNB1, KIF11, and ZNF408, some of which operate outside of the Norrin Wnt-signaling pathway. Recent discoveries of FEVR-linked variants in two other Catenin genes (CTNND1, CTNNA1) and the Endoplasmic Reticulum Membrane Complex Subunit-1 gene (EMC1) suggest that we will continue to find additional genes that impact the neural retinal vasculature, especially in multi-syndromic conditions. The goals of this review are to briefly highlight the current understanding of the roles of their encoded proteins in retinal endothelial cells to understand the essential functional mechanisms that can be altered to cause these very rare pediatric retinal vascular diseases.

The acetylcholinesterase (AChE) inhibitors are the main drugs for symptomatic treatment of neurodegenerative disorders like Alzheimer’s disease. A recently designed, synthesized and tested hybrid compound between the AChE inhibitor galantamine (GAL) and the antioxidant polyphenol curcumin (CU) showed high AChE inhibition in vitro. Here, we describe tests for acute and short-term toxicity in mice as well as antioxidant tests on brain homogenates measured the levels of malondialdehide (MDA) and glutathione (GSH). Haematological and serum biochemical analyses were also performed. In the acute toxicity tests, the novel AChE inhibitor given orally in mice showed LD50 of 49 mg/kg. The short-term administration of 2.5 and 5 mg/kg did not show toxicity. In the ex vivo tests, the GAL-CU hybrid performed better than GAL and CU themselves. In a dose of 5 mg/kg, it demonstrates 25% reduction in AChE activity, 28% and 73% increase in the levels of MDA and GSH, respectively. No significant changes in blood biochemical data were observed. The GAL-CU hybrid is a novel non-toxic AChE inhibitor with high antioxidant activity which makes it a perspective multitarget drug candidate for treatment of Alzheimer’s disease.

Proper nutrition is crucial for normal brain and neurocognitive development. Failure to optimize neurodevelopment early in life can have profound long-term implications for both mental health and quality of life. Although the first 1000 days of life represent the most critical period of neurodevelopment, the central and peripheral nervous systems continue to develop and change throughout life. All this time, development and functioning depend on many factors, including adequate nutrition. In this review, we outline the role of nutrients in cognitive, emotional, and neural development in infants and young children with special attention to the emerging roles of polar lipids and high quality (available) protein. Furthermore, we discuss the dynamic nature of the gut-brain axis and the importance of microbial diversity in relation to a variety of outcomes, including brain maturation/function and behavior are discussed. Finally, the promising therapeutic potential of psychobiotics to modify gut microbial ecology in order to improve mental well-being is presented. Here we show that the individual contribution of nutrients, their interaction with other micro-and macronutrients, and the way in which they are organized in the food matrix are of crucial importance for normal neurocognitive development.

Circulating miRNA-451a has recently emerged as an important biomolecule with potential clinical values as a diagnostic marker for several diseases. However, to be used as such, it is critical to accurately assay miRNA-451a in the clinic. Yet, pre-analytical factors that can affect such an error-free clinical assay of miRNA-451a have not been explored. This study aimed at investigating several of these pre-analytical factors that may affect the accurate quantification of miRNA-451a in human blood samples. We initially evaluated miRNA-451a levels in red blood cells (RBCs), white blood cells (WBCs), platelets, and plasma by droplet digital PCR (ddPCR). Next, we quantified miRNA-451a levels in whole blood or plasma stored at different temperatures for different time periods by ddPCR and used hemolyzed plasma samples to study the effects of hemolysis on plasma miRNA-451a concentration. We found that WBCs and platelets contain trace amounts of miRNA-451a and that about 99.9% of miRNA-451a in the blood are localized in RBCs. Hemolyzed plasma showed 58.5-fold increase in miRNA-451 concentration as compared to non-hemolyzed plasma. Importantly, plasma stored at room temperature (RT) or 4ºC showed a steady statistically significant decrease in miRNA-451a levels over a 7-day period whereas plasma samples stored at -20 or -80ºC for up to 7 days showed stable miRNA-451a levels. Together, our data indicate that hemolysis and blood storage at RT or 4ºC may have significant negative effects on the levels of circulating miRNA-451a.

Objective: To explore three novel fasting blood glucose (FBG)-based novel indicators, including FBG-to-albumin ratio (FAR), FBG-to-lymphocytes ratio (FLR), and FBG-to-hemoglobin ratio (FHR), in predicting prognosis and detecting metastasis for patients with pancreatic neuroendocrine neoplasms after resection. Materials and methods: A total of 178 pNEN patients underwent surgical resection were included in this study. Receiver operating characteristic (ROC) curves were used to evaluate the diagnosis values of FAR, FLR, and FHR, and the cut-off values were obtained for further analyses. Univariate and multivariate analyses were conducted to determine the independent predictors. The Kaplan-Meier method was used to evaluate the progression-free survival (PFS) and overall survival (OS) of the pNEN patients. Results: The optimal cut-off values of FAR, FLR, and FHR were 0.17, 2.85, and 0.028, respectively. As for PFS, the area under the curve (AUC) was 0.693 for FAR, 0.690 for FLR, and 0.661 for FHR, respectively. The AUC was 0.770, 0.692, and 0.715 accordingly for OS. The groups with lower FAR, FLR, and FHR were significantly associated with prolonged PFS and OS (p < 0.05). In patients with metastasis, the lower FAR group was correlated with significantly longer PFS and OS (p = 0.022 and 0.002, respectively). The FLR was an independent predictor of PFS in pNEN patients, and the FAR was a predictor of OS. FAR was an independent indicator of PFS in patients with metastasis. Conclusion: Preoperative FAR, FLR, and FHR are effective in predicting the prognosis of pNEN patients and detecting the synchronous metastases.

Our knowledge on the plastic functions of the serotonin (5-HT) receptor subtype 7 (5-HT7R) in the brain physiology and pathology considerably advanced in the last few years. A wealth of data show that the 5-HT7R is a key player in the establishment and remodeling of neuronal cytoarchitecture during development and in the mature brain, and its dysfunction is linked to neuropsychiatric and neurodevelopmental diseases. The involvement of this receptor in synaptic plasticity is further demonstrated by data showing that its activation allows to rescue long term potentiation (LTP) and long term depression (LTD) deficits in various animal models of neurodevelopmental diseases. In addition, it is becoming clear that the 5-HT7R is involved in inflammatory intestinal diseases, possibly playing a role in the gut-brain axis, and modulates the function of immune cells. In this review, we will mainly focus on recent findings on this receptor’s role in the structural and synaptic plasticity of the mammalian brain, although we will also illustrate novel aspects highlighted in gut and immune system.

This study was conducted to determine the role of pre-operative 2 weeks use of Finasteride in reducing intra-operative blood loss in patients undergoing monopolar TURP. Number of enrolled patients were 120, on the basis of inclusion criteria. Patients who were candidates of monopolar TURP were given 5mg Finasteride for 2 weeks before the surgery. On the 13th day of medicine, they got admitted in ward and prepared for surgery. During surgery intra-operative irrigation fluid was measured and gathered, then tested for Hemoglobin and the blood loss was calculated with equation formula. Blood loss evaluation was done on the basis of irrigation fluid, hemoglobin in irrigation fluid, preoperative hemoglobin and resected tissue weight. Significant reduction in blood loss was observed in interventional group as compared to the control group. Mean blood loss was 296ml in Group-A and 370ml in Group-B while blood loss per gram was 11.7ml/g in Group-A and 14.7 ml/g in Group-B. Mean operative time was measured 42 minutes in Group-A and 49 minutes in Group-B. This research proclaims a clear-cut supremacy of pre-operative use of Finasteride for two weeks. It significantly reduces intraoperative blood loss and blood loss per gram in patients undergoing monopolar TURP.

In this observational study, we compared continuous physiological signals during an active stand test in adults aged 50 years and over, characterized as frail by three different criteria, using data from The Irish Longitudinal Study on Ageing (TILDA). Four independent groups were identified: those characterized as frail only by one of the frailty tools used (the physical Frailty Phenotype (FP), the 32-item Frailty Index (FI), or the Clinical Frailty Scale (CFS) classification tree), and a fourth group where participants were not characterized as frail by any of these tools. Continuous non-invasive physiological signals were collected during an active stand test: systolic (sBP) and diastolic (dBP) blood pressure, as well as heart rate (HR), using digital artery photoplethysmography. Additionally, frontal lobe cerebral oxygenation (Oxy), deoxygenation (Deoxy), and tissue saturation index (TSI) were also non-invasively measured using near-infrared spectroscopy (NIRS). The signals were visualized across frailty groups and statistically compared using one-dimensional statistical parametric mapping (SPM). A total of 1,124 participants (mean age 63.5 years, 50.2% women) were included: 23 were characterized as frail only by FP, 97 by FI, 38 by CFS, and 966 by none of these criteria. SPM analyses revealed that only the group characterized as frail by FI had significantly different signals (p<0.05) compared to the non-frail group. Specifically, they exhibited a lesser increase in HR between 5-15 seconds post-stand and larger deficits in sBP and dBP between 15-40 seconds post-stand, and possibly a lower Delta TSI at 20 seconds post-stand. In this comparison, the FI proved more adept at capturing distinct physiological responses to standing, likely due to its direct inclusion of cardiovascular morbidities in its definition.

Epilepsy is a neurological disorder that affects approximately 1% of the world's population. To diagnose and estimate the occurrence of epilepsy, the analysis of recorded brain activity is performed by a neurologist, which is not only time-consuming and tedious but also occasionally accompanied by human error. Therefore, in recent decades, researchers have aimed to unravel an approach for designing and building an automated method for diagnosing and estimating the occurrence of epilepsy. Accordingly, the present study proposed two new-fangled ways based on brain signals and a convolutional neural network (CNN). Moreover, this research implements a CNN with a sequential three-layer structure. Numerous experiments were performed, and the accuracy of estimating epilepsy using the developed methods was achieved at 95% without feedback and 97% with feedback. The proposed methods were proven to be more accurate than the previous techniques and can be employed as a physician's assistant once entering the field of operation.

New research points to a possible link between Autism Spectrum Disorder and the gut microbiota as many autistic children have co-occurring gastrointestinal problems. This review focuses on specific alterations of gut microbiota mostly observed in autistic patients. Particularly, the mechanisms through which such alterations may trigger the production of the bacterial metabolites or leaky gut in autistic people are described. Various altered metabolite levels were observed in autistic children, many of those were of bacterial origin such as short chain fatty acids (SCFAs), indoles and lipopolysaccharides. A less integrative gut-blood-barrier is abundant in autistic individuals. This explains the leakage of bacterial metabolites into the patients triggering new body responses or altered metabolism. Some other co-occurring symptoms such as mitochondrial dysfunction, oxidative stress in the cells, altered tight junctions in the blood brain barrier and structural changes in cortex, hippocampus, amygdala and cerebellum were detected. Moreover, this paper suggests that autism is associated with an unbalanced gut microbiota (dysbiosis). Although the cause-effect relationship between autism and gut microbiota is not yet well established, consumption of specific probiotics may represent a powerful tool to re-establish gut homeostasis and promote gut health. Diagnostic and therapeutic value of new biomarkers leading to the perturbation in the phenylalanine metabolism will be discussed.

Introduction: Adverse events related to vaccines are reactions that can lead to serious complications, in the present that we live at the publication of this article with the need to generate high rates of vaccination have been presented in the case of vaccine agents against COVID-19 adverse events, with thrombotic events being the most important. Case Presentation: This is a 37-year-old female patient who presents 11 days after ChAdOx1-S vaccination against COVID-19 presents with intense headache associated with symptoms of intracranial hypertension, she was initially taken to simple cranial tomography showing presence of cerebral edema and indirect signs of cerebral venous thrombosis, it is proposed to carry out cerebral angiography which showed the presence of thrombosis of both transverse venous sinuses, no hypercoagulability states were found in the laboratories, the immunological tests carried out for antiphospholipid syndrome were negative, the thrombotic event was associated with the ChAdOx1-S vaccine, later the patient was taken to thrombectomy by Neuroradiology, achieving complete channeling of both transverse venous sinuses. Conclusions: Adverse events associated with vaccination have been described with multiple vaccine agents, this component against COVID-19 is also an event to consider, knowing the pathophysiology of these events is essential to be able to reduce these risks and select the least risky agent. Despite this risk, vaccination remains the only cost-effective measure to reduce the morbidity and mortality associated with COVID-19.

Brain magnetic resonance imaging (MRI) offers a unique lens to study neuroanatomic support of human neurocognition and intelligence. A core mystery is the MRI explanation of individual differences in neurocognition and intelligence. The past four decades have seen great advancement in studying this century-long mystery, but the sample size and population-level studies limit the explanation at the individual level. The recent rise of big data and artificial intelligence offers novel opportunities. Yet, data sources, harmonization, study design, and interpretation need to be carefully considered. This review aims to summarize past work, discuss rising opportunities and challenges, and facilitate further investigations on machine intelligence inferring human intelligence.

Background: Traumatic brain injury (TBI) remains a significant risk factor for post-traumatic epilepsy (PTE). The pathophysiological mechanisms underlying the injury-induced epileptogenesis are under under investigation. The dentate gyrus, a structure highly susceptible to injury, and has been implicated in the evolution of seizure development. Methods: Utilizing the murine unilateral focal control cortical impact (CCI) injury, we evaluated seizure onset using 24/7 EEG video analysis at 2-4 months post-injury. Cellular changes in the dentate gyrus and hilus of the hippocampus were quantified by non-biased stereology and Imaris image analysis to evaluate Prox1-positive cell migration, astrocyte branching and morphology, as well as neuronal loss at four months post-injury. Isolation of region-specific astrocytes and RNA-seq was performed to determine differential gene expression in PTE+ vs. PTE- that may comport with the epileptogenic process. Results: CCI injury resulted in 37% PTE+-incidence, which increased with injury severity and hippocampal damage. Histological assessments uncovered a significant loss of hilar interneurons that coincided with aberrant migration of Prox1-positive granule cells and reduced astroglial branching in PTE+ compared to PTE- mice. We uniquely identified Cst3 as a PTE+-specific gene signature in astrocytes across all brain regions. Conclusions: These findings suggest that epileptogenesis may emerge following TBI due to distinct aberrant cellular remodeling events and key molecular changes in the dentate gyrus of the hippocampus.

We introduce a mission design for an interstellar expedition to nearby earth-like exoplanets, which our analysis determined to be Tau Ceti and Gliese 667C, at the time of analysis in 2013. We review the research problems in propulsion and AGI that must be addressed to launch an AI guided interstellar probe within 100 years. We propose a new semi-autonomous agent approach for intelligent control of the spacecraft. We introduce the concept of a semi-autonomous agent as having built-in safety guarantees that constrain operation. An autonomous agent case study is presented formulating the objective, constraints, AGI implementation of the agent based on Solomono's Alpha architecture, and adding specicity. We discuss the training required to reach human-level and trans-sapient levels of intelligence which corresponds to an entire crew of AI experts specialized in elds such as astrophysics, astromechanics, astrobiology, quantum physics, computer science, molecular biology, and so forth. We project the feasibility of the human-level AI technology based on empirical ndings in neuroscience, and nd that it should be feasible by 2030. We analyze Solomono's innity point hypothesis in light of Koomey's law about energy eciency of computing and nd that the trends in 2013 indicated an early singularity by 2035, which implies that we might encounter physical bottlenecks which will decelerate computing technology improvements signicantly. We recommend thus year 2040 for launching the probe by which date other required technologies will have been developed. We discuss the scenario of a virtual crew made of brain simulations, which is a bio-information based AI approach. We detail the subsystems of command and control, communication, scientic instrumentation, power, propulsion, navigation, and shielding. We propose a variation of ICAN-II/AIMStar propulsion which uses a positron source instead of anti-protons to initiate micro-fusion reactions. We combine the positron initiated fusion pulse propulsion scheme with a miniaturized version of the Daedelus fusion thruster obtaining high performance. We derive two mission proles one for fusion pulse propulsion, and the yet hypothetical Q-Thruster. Fusion thruster requires 132.2 years for Tau Ceti, and 233.2 years for Gliese 667C, while Q-Thruster takes only 42.3 years for Tau Ceti, and 62.5 years for Gliese 667C. We also discuss extended roles for intelligent interstellar probes such as self-reproduction via nanotechnology, refueling, construction, robotic bodies, and transmission of brain simulations.

There is evidence that spaceflight poses acute and late risks on the central nervous system. To explore possible mechanisms, the proteomic changes following spaceflight in mouse brain were characterized. Space Shuttle Atlantis (STS-135) was launched at the Kennedy Space Center on a 13-day mission. Within 3–5 hours after landing, brain tissue was collected to evaluate protein expression profiles using quantitative proteomic analysis. Our results showed that there were 26 proteins that were significantly altered after spaceflight in the grey and/or white matter. While there was no overlap between the white and grey matter in terms of individual proteins, there was overlap in terms of function, synaptic plasticity, vesical activity, protein/organelle transport, and metabolism. Our data demonstrate that exposure to the spaceflight environment induces significant changes in protein expression related to neuronal structure and metabolic function. This might lead to a significant impact on brain structural and functional integrity that could affect the outcome of space missions.

The likelihood of pre-hypertensive young adults developing hypertension has been steadily increasing over the past few years. Despite the fact that aerobic exercise training (AET) has demonstrated positive results in lowering high blood pressure, the efficacy of different types of AET among pre-hypertensive young adults has not been well-established. The objective of this study was to evaluate the effectiveness of high-intensity interval training (HIIT) and continuous moderate-intensity training (CMT) on blood pressure (BP) of physically inactive pre-hypertensive young adults. 32 adults (age 20.0±1.1 years and BMI 21.5±1.8) were randomly assigned into 3 groups: HIIT, CMT and control (CON). HIIT and CMT groups participated in 5 weeks of AET; while the CON group followed a DASH diet plan only. The HIIT protocol consisted of 1:4 minute work to rest ratio of participants 80%-85% heart rate reserve (HR-reserve) and 40%-60% HR-reserve respectively for 20-minutes, CMT group exercised at 40%-60% of HR-reserve continuously for 20-minutes. In both HIIT and CMT groups, systolic blood pressure (SBP) (3.8±2.8 mmHg, P=0.002 VS 1.6±1.5 mmHg, P=0.011) was significantly reduced. While, significant reductions in the diastolic blood pressure (DBP) (2.9±2.2 mmHg, P=0.002) and mean arterial pressure (MAP) (3.1±1.6mmHg, P<0.0005) were noted only in the HIIT group. No significant differences in SBP (-0.4±3.7 mmHg, P=0.718), DBP (0.4±3.4 mmHg, P=0.714), or MAP (0.1±2.5mmHg, P= 0.892) were observed in the CON group. Both HIIT and CMT decreased the BP in physically inactive pre-hypertensive young adults; however, HIIT yielded more beneficial results in terms of reducing the SPB, DBP and MAP.

Traumatic Brain Injury represents a significant public health concern due to its role in traumatic death and disability, often caused by head impacts or rapid accelerations. Despite advancements in Finite Element Head Models, existing models primarily represent adult males, neglecting anatomical and physiological differences between genders and age groups. Additionally, the mechanistic roles of specific intracranial tissues, such as the dura mater, have conventionally been overlooked. To better understand the mechanical behavior of the brain and its injured regions in the context of TBI, including the dura mater, this study proposes the development of a Female Finite Element Head Model. This model, representative of a middle-aged female subject, was developed using medical image-derived geometry and finite element modeling techniques. The validation results demonstrate a similarity between the numerical displacement curves and those obtained experimentally. In the model with dura mater, the numerical results show analogous behavior to the experimental results, despite minimal variations in the amplitude of the curves. These advancements highlight the significance of including the dura mater in biomechanical brain modeling. Incorporating the dura mater in Finite Element Head Models produces more realistic results than models without it. This emphasizes the importance of enhancing biomechanical models to better represent anatomical complexity.

The abnormal accumulation of cells in the human brain, if left untreated, may cause brain damage. Management and treatment of these tumours require an early and accurate diagnosis, while their prognostic characterisation can also be beneficial in the choice of care planning for the patient. CDSSs are being continuously developed and integrated into routine clinical practice as they assist clinicians and radiologists to deal with an enormous amount of medical data, reduce clinical errors, and improve diagnostic capabilities. They assist detection, classification, and grading of brain tumours as well as alerting physicians of requirement of change in treatment plans. The aim of this systematic review is to identify various CDSSs used in brain tumour diagnosis and prognosis, that rely on data captured by any imaging modality. Based on the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, the literature search was conducted in PubMed and Engineering Village Compendex databases. This review examines various CDSS tool types, system features, techniques used, accuracy, and outcome, to provide the latest evidence available in the field of neuro-oncology. An overview of different types of CDSSs used to support clinical decision-making in the management and treatment of brain tumours, along with highlighting their benefits, challenges, and future perspectives has been provided.

Head injury is among the most devastating types of injury, specifically called Traumatic Brain Injury (TBI). There is need to diminish the morbidity related with TBI and to improve the outcome of patients suffering TBI. Among the improvements on the treatment of TBI, neuroprotection is one of the upcoming improvements. Citicoline has been used in the management of brain ischemia related disorders, such as TBI. Citicoline has biochemical, pharmacological, and pharmacokinetic characteristics that make it a potentially useful neuroprotective drug for the management of TBI. A short review of these characteristics is included in this paper. Also, a narrative review of almost all the published or communicated studies performed with this drug in the management of patients with head injury is included. Based on the results obtained in these clinical studies, it is possible to conclude that citicoline was able to accelerate recovery of consciousness and to improve the outcome of this kind of patients, with an excellent safety profile. Thus, citicoline could have a potential role in the management of TBI.

Current hypotheses implicate insulin resistance of the brain as a pathogenic factor in the development of Alzheimer’s disease and other dementias, Parkinson’s disease, type 2 diabetes, obesity, major depression, and traumatic brain injury. A variety of genetic, developmental, and metabolic abnormalities that lead to disturbances in the insulin receptor signal transduction may underlie insulin resistance. Insulin receptor substrate proteins are generally considered to be the node in the insulin signaling system that is critically involved in the development of insulin insensitivity during metabolic stress, hyperinsulinemia, and inflammation. Emerging evidence suggests that lower activation of the insulin receptor (IR) is another common, while less discussed, mechanism of insulin resistance in the brain. This review aims to discuss causes behind the diminished activation of IR in neurons, with a focus on the functional relationship between mitochondria and IR during early insulin signaling and the related roles of oxidative stress, mitochondrial hypometabolism, and glutamate excitotoxicity in the development of IR insensitivity to insulin.

Current hypotheses implicate insulin resistance of the brain as a pathogenic factor in the development of Alzheimer’s disease and other dementias, Parkinson’s disease, type 2 diabetes, obesity, major depression, and traumatic brain injury. A variety of genetic, developmental, and metabolic abnormalities that lead to disturbances in the insulin receptor signal transduction may underlie insulin resistance. Insulin receptor substrate proteins are generally considered to be the node in the insulin signaling system that is critically involved in the development of insulin insensitivity during metabolic stress, hyperinsulinemia, and inflammation. Emerging evidence suggests that lower activation of the insulin receptor (IR) is another common, while less discussed, mechanism of insulin resistance in the brain. This review aims to discuss causes behind the diminished activation of IR in neurons, with a focus on the functional relationship between mitochondria and IR during early insulin signaling and the related roles of oxidative stress, mitochondrial hypometabolism, and glutamate excitotoxicity in the development of IR insensitivity to insulin.

Human language and social cognition are two key disciplines that have traditionally been studied as separate domains. However, emerging research from detailed studies of comparative animal behavior, human social behavior, language acquisition in children, social cognitive neuroscience, and the cognitive neuroscience of language suggest that language and social cognition are two deeply interrelated capacities of the human species. For instance, recent developmental studies on the acquisition of language in infants and young children, draw attention to the important crucial benefits associated with several different aspects of social stimulation for youngsters, including the quantity and quality of linguistic input, dyadic infant/child-to-parent verbal and non-verbal social interactions, and other important social cues integral for facilitating language learning and social bonding. Studies of the adult human brain further suggest a high degree of specialization for sociolinguistic information processing, memory retrieval, and comprehension, suggesting the function of these regions may link language with social cognition and social bonding. In effect, the social brain and social complexity hypotheses may jointly help to explain how neurotypical children and adults learn language, why autistic adults and children exhibit simultaneous deficits in language and social cognition, and why nonhuman primates and other animals with significant computational abilities do not acquire the capacity for language. But perhaps most critically, the following article argues that this and related research will allow scientists to generate a holistic profile and deeper understanding of the healthy adult social brain, while developing more innovative and effective diagnoses, prognoses, and treatments for maladies and deficits also associated with the social brain.

Background: Processing whole-slide images (WSI) to train neural networks can be intricate and laborious. We developed an open-source library covering recurrent tasks in processing of WSI and in evaluating the performance of the trained networks for classification tasks. Methods: Two histopathology use-cases were selected. First we aimed to train a CNN to distinguish H&amp;E-stained slides obtained from neuropathologically classified low-grade epilepsy-associated dysembryoplastic neuroepithelial tumor (DNET) and ganglioglioma (GG). The second project we trained a convolutional neural network (CNN) to predict the hormone expression of pituitary adenoms only from hematoxylin and eosin (H&amp;E) stained slides. In the same approach, we addressed the issue to also predict clinically silent corticotroph adenoma. We included four clinico-pathological disease conditions in a multilabel approach. Results: Our best performing CNN achieved an area under the curve (AUC) of 0.97 for the receiver operating characteristic (ROC) for corticotroph adenoma, 0.86 for silent corticotroph adenoma and 0.98 for gonadotroph adenoma. Our DNET-GG classifier achieved an AUC of 1.00 for the ROC curve. All scores were calculated with the help of our library on predictions on a case basis. Conclusions: Our comprehensive library is most helpful to standardize the work-flow and minimize the work-burden in training CNN. It is also compatible with fastai. Indeed, our new CNNs reliably extracted neuropathologically relevant information from the H&amp;E staining only. This approach will supplement the clinico-pathological diagnosis of brain tumors, which is currently based on cost-intense microscopic examination and variable panels of immunohistochemical stainings.

The tambaqui Colossoma macropomum is the main species of edible fish originating from fish farming in the Amazon region. This study aimed to determine and compare the hematological and biochemical parameters of tambaqui from fish farms in municipalities in the Metropolitan Region of Manaus, Amazonas, Brazil. Two fish farms were sampled in a semi-excavated pond-type breeding system in each of the five towns investigated (Presidente Figueiredo, Manaus, Iranduba, Manacapuru and Novo Airão), totaling ten breeders. On each farm, ten specimens were captured, totaling 100 animals. Blood was collected by caudal puncture, and hematological and biochemical parameters were determined using the methodology described for teleosts fish. For the erythrogram in the variables of hematocrit, hemoglobin concentration and erythrocytes, significant differences were observed in Iranduba and Novo Airão, demonstrating indications of anemic processes and dehydration. For plasma biochemistry, low levels were observed in fish from Iranduba and Novo Airão. High values in lipid compounds were found in tambaqui from Manacapuru. High intraspecific variation was found in the leukogram and thrombogram, which determined similarities between tambaqui from different farms and municipalities. On the other hand, fish from Manacapuru have an inappropriate diet, indicated by the high levels of cholesterol and triglycerides found in the blood.

Adenosine is a multifunctional nucleoside with several roles across various levels in organisms. Beyond its intracellular involvement in cellular metabolism, extracellular adenosine potently influences both physiological and pathological processes. In relation to its blood level, adenosine impacts the cardiovascular system, such as heart beating rate and vasodilation. To exploit the adenosine levels in the blood, we employed the liquid chromatography method coupled with mass spectrometry (LC-MS). Immediately after the collection, a blood sample mixed with acetonitrile solution that is either enriched with 13C-labeled adenosine or a newly generated mixture is transferred into the tubes containing the defined amount of 13C-labeled adenosine. The 13C-enriched isotopic adenosine is used as an internal standard, allowing for more accurate quantification of adenosine. This novel protocol for LC-MS-based estimation of adenosine delivers a rapid, highly sensitive, and reproducible means for quantitative estimation of total adenosine in blood. The method also allows quantification of a few catabolites of adenosine, i.e., inosine, hypoxanthine, and xanthine. This advancement provides the analytical tool that has the potential to enhance our understanding of adenosine's systemic impact and pave the way for further investigations into its intricate regulatory mechanisms.

. Cucurbiturils are a family of macrocyclic oligomers capable of forming host-guest complexes with various molecules. Due to noncovalent binding to drug molecules and low toxicity, cucurbiturils has been extensively investigated as a potential carrier for drug delivery. However, the immune system interactions with different drug carriers, including cucurbiturils, are still under investigation. In this study, we focused on cucurbiturils immunosafety and immunomodulation properties in vivo. We measured blood counts, lymphocyte subpopulations in blood, spleen, and bone marrow, and assessed in vivo toxicity to spleen and bone marrow cells after intraperitoneal administration to mice. We also evaluated the effect of cucurbiturils on cellular and humoral immune responses. Cucurbiturils in high concentrations effect on the immune system in vivo. The action of various cucurbiturils differs in different homologues, which, apparently, is associated with different interactions in the internal environment of the body.

Haemosporidian parasites, including Haemoproteus, Plasmodium, and Leucocytozoon, are intracellular parasites found in the blood and tissues of birds worldwide. The prevalence of these parasites varies depending on bird species and habitats. Humidity, influenced by water availability, is one of the factors affecting their prevalence. In this study, we collected 145 blood samples from wild songbirds in the western region of Iran from April to November 2021-2022. Blood smears were prepared using the push-slide method and stained with Giemsa. The stained smears were examined under a light microscope. Among the seven songbird families sampled, blood parasites were detected in 31 individuals from five families. Of these, 23 individuals (15.86%) were from humid areas, while 8 individuals (5.51%) were from dry areas. The highest infection rates were observed in the Paridae (9.65%) and Motacilliidae (4.82%) families, while the lowest infection rates were found in the Corvidae (1.37%) and Acrocephalidae (1.37%) families. We recorded two new hosts for Leucocytozoon spp. (Motacilla flava and Acrocephalus melanopogon) for the first time in the world and four new host records (Motacilla flava, Pica pica, Acrocephalus melanopogon, and Acrocephalus agricola) for blood parasites in the west of Iran. Our findings highlight the high prevalence of avian blood parasites in songbirds inhabiting humid areas, suggesting that these environments provide suitable conditions for the growth and reproduction of invertebrate hosts.

5-Hydroxytryptamine (5-HT) or serotonin plays a crucial role as a neuromodulator and/or neurotransmitter of several nervous system functions. Its actions are complex and depend on multiple factors, including the type of effector or receptor activated. Briefly, 5-HT can activate: (i) metabotropic (G-protein-coupled) receptors to promote inhibition (5-HT1, 5-HT5) or activation (5-HT4, 5-HT6, 5 HT7) of adenylate cyclase, as well as activation (5-HT2) of phospholipase C; and (ii) ionotropic receptors (5-HT3), which form a ligand-gated Na+/K+ channel. Regarding blood pressure regulation (and beyond the intricacy of central 5-HT effects), this monoamine also exerts direct postjunctional (on vascular smooth muscle and endothelium) or indirect prejunctional (on autonomic and sensory perivascular nerves) effects. At the prejunctional level, 5-HT can facilitate or preclude the release of autonomic (e.g., noradrenaline and acetylcholine) or sensory (e.g., calcitonin gene-related peptide) neurotransmitters facilitating hypertensive or hypotensive effects. Hence, we cannot formulate a specific impact of 5-HT on blood pressure level, since an increase or decrease in neurotransmitter release would be favoured depending on the type of prejunctional receptor involved. This review summarizes and discusses the current knowledge on the prejunctional mechanisms involved in blood pressure regulation by 5-HT and its impact on some vascular-related diseases.

Background of the Study: We investigated the link between hypertension and cancer since it has been suggested that hypertension may raise the long-term risk of cancer. Previous large observational cohort studies found that greater blood pressure (BP) was related to a higher risk of cancer. Mendelian randomization (MR) was utilized to produce less confounded blood pressure estimates (BP) on overall and site-specific malignancies. The study aims to draw conclusions on the relationship between high blood pressure and cancer. Methods: Studies on high blood pressure and various malignancies are inconclusive, except for renal cell carcinoma. However, given that most meta-analyses only contained a limited number of trials, some relative risks had small to moderate magnitudes, and several may have been impacted by residual confounding, careful interpretation is necessary. The study was conducted using the meta-analysis technique. Cochran's Q test and I2 test were used to assess statistical heterogeneity between studies in the current investigation for research involving two or more cause and outcome combinations. Results: Positive correlations were also reported between high blood pressure and esophageal adenocarcinoma, squamous cell carcinoma, liver, and squamous cell carcinoma. However, most studies lacked multivariable adjustments. Physical and numerical risk of cardiovascular disease is linked to bowel cancer but no other cancers. According to a meta-analysis, hypertensive persons could also be at increased danger of gastrointestinal and breast cancer. Most meta-analyses comprised several trials with moderate or mild hazard ratios.ConclusionDifferent types of cancers have been noted to be directly caused by hypertension. In addition, some treatments have also been associated with the side effects of cancer treatments to cause hypertension. Women facing hypertension have an increased risk of getting breast cancer. Although some cancers showed a real relationship with hypertension, others had no connection at all.

The two main chronic obstructive diseases are asthma – affecting 1-18% of adult population – and chronic obstructive pulmonary disease (COPD) prevalent in up to 6% of adults. In both cases the treatment depends on diseases’ severity. In management of these conditions, spirometry and complete blood count are two major monitoring tests. Our aim was to compare blood morphology results and spirometry values between patients in groups of different treatment intensity in asthma and COPD. By measuring that, we expected to study whether asthma/COPD patients have a need of stepping-up their treatment steps. Methods A retrospective analysis of patients admitted in 2013-2019 to an outpatient pulmonology clinic in Łódź (Poland). Spirometry values, complete blood count and information on pharmacological treatment were obtained from archival data. Patients were assigned with disease severity according to present GINA/GOLD recommendations. The study included 125 patients – 47 with COPD (22 females) and 78 with asthma (57 females). Results Among patients with asthma, a positive correlation in white blood cell count (WBC) (r=0,236, p=0.038) and ascending GINA treatment steps was found. Significant negative correlations were shown between ascending GINA treatment steps and FEV1, FEV1%, FVC%, MEF50, MEF50, PEF%. In COPD patients, positive correlations between ascending GOLD treatment groups and white blood cell count, neutrophil count, basophil percentage, platelet count (r=0.346; 0.309; 0.321; 0.401 respectively) were found. Negative correlations were shown between ascending GOLD treatment groups and FEV1, FEV1%, FVC, FVC%, MEF50, MEF50%, PEF, PEF% (r=-0.732; -0.575; -0.705; -0.498; -0.632; -0.558; -0.688; -0.597 respectively). Conclusions Negative correlations between ascending GINA and GOLD treatment steps and spirometry values may suggest that asthma and COPD patients may benefit from stepping-up the treatment steps earlier. Potential advantages of that more intensive treatment needs to be examined in the future

Background: Thousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Also, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed. Methods: To derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including N=229 African American and N=381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, N = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (N = 27,955) and Hispanic/Latino (N = 28,324) ancestry participants. Results: Our results revealed 24 suggestive signals (p < 1×10^(-4)) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (N=802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN. Conclusions: These analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.

Precise association of serum leptin with body mass index (BMI) and blood pressure (BP; both systolic blood pressure (SBP) and diastolic blood pressure (DBP) is not well known for understanding their involvement in health and disease. Hence, the present study was planned to be conducted for investigating the association of BP, BMI and serum leptin levels in young normal weight (NW) and overweight (OW) male Saudi students. The NW (n: 198) and OW male subjects (n: 192) in the age range of 18-20 years were consulted. Blood pressure (BP) was measured with a mercury sphygmomanometer. Leptin Human ELISA Kits were employed for the determination of the serum leptin levels. The mean ± SD values of BMI (kg/m2), serum leptin (ng/ml), SBP (mmHg), and DBP (mmHg) all showed significant difference for young OW vs. NW male university students as: 27.52± 1.42 vs. 21.49± 2.03; 10.70± 4.67 vs. 4.68± 1.91; 121.37±2.59 vs.118.51±1.54 and 81.44±1.97 vs. 78.79±1.44 respectively. All associations (among BMI, leptin, SBP and DBP) showed positive linear and significant correlation except nonsignificant correlation of BMI and SBP for NW group. The present study in the young Saudi male students, presents significant variations for BP and serum leptin levels and significant positive linear association among serum leptin, BMI and BP.

Until recently, no disease-specific health-related quality of life (HRQoL) instrument existed for pediatric traumatic brain injury (TBI). In this revalidation study, the psychometric properties and the validity of the final German version of the 35-item QOLIBRI-KID/ADO questionnaire were examined in 300 children and adolescents. It is the first self-reported TBI-specific instrument for measuring pediatric HRQoL in individuals aged 8–17 years. The six-factor model fits the data adequately. Internal consistencies were excellent for the total score and satisfactory to excellent for the scale scores. Intraclass correlations indicated good test-retest reliability. Construct validity was supported by overlaps between the QOLBRI-KID/ADO and the PedsQL, which measures generic HRQoL. Discriminant validity indicated that HRQoL was significantly lower in older children and girls, and in those with anxiety, depression, and post-concussion symptoms than in comparison groups, replicating the results of the questionnaire’s first development study. Our results suggest that the QOLIBRI-KID/ADO is a valid and reliable multidimensional instrument for assessing disease-specific HRQoL after pediatric TBI in clinical and research settings, which can additionally be used across the lifespan in combination with the adult version. This may help to improve care, treatment, daily functioning and HRQoL after TBI.

The question of what generates conscious experience has mesmerized thinkers since the dawn of humanity, yet its origins remain a mystery. The topic of consciousness has gained traction in recent years, thanks to the development of large language models that now arguably pass the Turing test, an operational test for intelligence. However, intelligence and consciousness are not related in obvious ways, as anyone who suffers from a bad toothache can attest - pain generates intense feelings and absorbs all our conscious awareness yet nothing particularly intelligent is going on. Still, in the hard sciences, this topic is frequently met with skepticism because to date no protocol to measure the content or intensity of conscious experiences in an observer-independent manner has been agreed upon. Here we present a novel proposal: Conscious experience arises whenever a quantum mechanical superposition forms. Our proposal has several implications: First, it suggests that the structure of the superposition determines the qualia of the experience. Second, quantum entanglement naturally solves the binding problem, ensuring the unity of phenomenal experience. Finally, a moment of agency may coincide with the formation of a superposition state. We outline a research program to experimentally test our conjecture via a sequence of quantum biology experiments. Applying these ideas opens up the possibility of expanding human experience through brain-quantum computer interfaces.

Brain models present a viewpoint on the fundamental structural components of the brain and their mutual organization, generally relative to a particular concept of the brain axis. A model may be based on adult brain structure or on developmental morphogenetic aspects. Brain models usually have functional implications, depending on which functional properties derive from the postulated organization. This essay examines the present scenario about brain models, emphasizing the contrast between columnar or other longitudinal models and transverse subdivisional neuromeric models. In each case, the main functional implications and apparent problems are explored and commented. Particular attention is given to the modern molecularly based ‘prosomeric model’, which postulates a set of 20 transverse prosomeres as the developmental units that serve to construct all the cerebral parts and the particular typology of many different neuronal populations within the forebrain and the hindbrain, plus a number of additional spinal cord units. These metameric developmental units (serially repeated, but with unique molecular profiles) confer to this model remarkable functional properties based mainly on its multiplicity and modularity. Many important brain functions can be decomposed into subfunctions attended to by combined sets of neuronal elements derived from different neuromeres. Each neuromere may participate in multiple functions. Most aspects related to creation of precise order in neural connections (axonal navigation and synaptogenesis) and function is due to the influence of neuromeric anteroposterior and dorsoventral positional information. Research on neuromeric functionality aspects is increasing significantly in recent times.

Light is an electromagnetic radiation that has visible and invisible wavelength spectrum. The visible light can only be detected by the eyes through the optic pathways. With the presence of scalp, cranium and meninges, the brain is seen as being protected from direct exposure to light. For that reason, the brain can be viewed as a black body lying inside a black box. In physics, a black body tends to be in thermal equilibrium with its environment and can tightly regulate its temperature via thermodynamics principles. Therefore, a healthy brain inside a black box should not get exposed to light. On the contrary, photobiomodulation, a form of light therapy to the brain has been shown to have beneficial effects for some neurological conditions. The proposed underlying mechanisms are multiple. Herein we present our intraoperative findings of rapid electrocorticographic brainwave changes when the brain was shone directly with different wavelengths of light during awake brain surgery. Our findings provide literature proof on light’s ability to influence human brain energy and function. Our proposed mechanism for these rapid changes is the presence of plasma-like energy inside the brain which causes fast brain activities that are akin to lightning strikes.

Stereotactic radiosurgery (SRS) has become increasingly important in the management of brain metastases due to improving systemic disease control and rising incidence. Initial trials demonstrated SRS with whole brain radiotherapy (WBRT) improved local control rates versus WBRT alone. Concerns with WBRT associated neurocognitive toxicity have contributed to greater use of SRS alone, including for patients with multiple metastases and following surgical resection. Molecular information, targeted agents and immunotherapy have also altered the landscape for the management of brain metastases. This review summarises current and emerging data on the role of SRS in the management of brain metastases.

In CNS drug discovery, estimation of brain exposure of lead compounds is critical for their optimization. Compounds need to cross the blood-brain barrier (BBB) to reach the pharmacological targets in the CNS. The BBB is a complex system involving passive and active mechanisms of transport and efflux transporters such as P-glycoproteins (P-gp) and breast cancer resistance protein (BCRP), which play an essential role in CNS penetration of small molecules. Several in vivo, in vitro and in silico methods are available to estimate human brain penetration. Preclinical species are used as in vivo models to understand the unbound brain exposure by deriving the Kp,uu parameter, the brain/plasma ratio of exposure corrected with the plasma and brain free fraction. MDCK-mdr1 (Madin Darby canine kidney cells transfected with the MDR1 gene encoding for the human P-gp) assay is the most commonly used in vitro assay to estimate compound permeability and human efflux. The in silico methods to predict brain exposure, such as CNS MPO, CNS BBB scores and various Machine Learning models, help save costs and speed up compound discovery and optimization at all stages. These methods enable the screening of virtual compounds and building of a CNS penetrable compounds library as well as optimization of lead molecules for CNS penetration. Therefore, it is crucial to understand these methods' reliability and ability to predict CNS penetration. We review the in silico, in vitro and in vivo data and their correlation with each other and assess published in silico approaches to predict the BBB penetrability of compounds.

Our previous studies showed that in patients with brain diseases neurotrophic factors in lacrimal fluid (LF) may change more prominently than in blood serum (BS). Since glial cell line-derived neurotrophic factor (GDNF) is involved in control of neuronal networks in epileptic brain, we aimed to assess GDNF levels in LF and BS as well as BDNF, hypothalamic-pituitary-adrenocortical and inflammation indices in BS of patients with focal epilepsy (PWFE), epilepsy and comorbid depression (PWFE+MDD) compared with major depressive disorder (PWMDD) and healthy controls (HC). GDNF levels in BS were similar in patients and HC and higher in PWFE taking valproates. GDNF levels in LF were significantly lower in all patient groups compared to controls, and independent of drugs used. LF and BS GDNF concentrations positively correlated in HC, but not patient groups. BDNF level was lower in BS of patients compared with HC and higher in PWFE+MDD taking valproates. Logistic regression models demonstrated that GDNF decrease in LF may be an important predictor of focal epilepsy. Probability of focal epilepsy can be evaluated using GDNF in LF and BDNF in BS; MDD - GDNF in LF, cortisol and TNF-α in BS; epilepsy with MDD - GDNF in LF, TNF-α and BDNF in BS.

We estimated the risk of blood clots after COVID-19 vaccination accounting for the roles of vaccination in reducing the infection rate, and indirectly lowering the risk of blood clots caused by infection. A self-controlled case series method was used to examine the association between blood clots and COVID-19 vaccination. To deal with the bias due to under-reported infection among non-hospitalized subjects, a case-control study was used to compare the risk of blood clots in infected subjects to control subjects who were hospitalized due to physical injury. We found increased risks of blood clots after vaccination (incidence rate ratio is 1.13, 95% confidence interval (CI): [1.03, 1.24] after the first dose and 1.23, 95% CI: [1.13,1.34] after the second dose). Furthermore, vaccination attenuated the increased risk of blood clots associated with infection (odds ratio (OR) = 2.16, 95% CI: [1.93, 2.42] in unvaccinated versus OR=1.46, 95% CI: [1.25, 1.70] in vaccinated). A causal model was used to explain and weigh up possible risk factors for blood clots after COVID-19 vaccination. After accounting for vaccine efficacy against infection and the protection against infection-associated blood clots, receiving the COVID-19 vaccines decreases the risk of blood clots, especially during high infection rate period.

Blood gas analysis plays a central role in modern medicine. Advances in technology have expanded the range of available parameters and increased the complexity of their interpretation. By applying user-centered design principles, it is possible to reduce the cognitive load associated with interpreting blood gas analysis. In this international, multicenter study, we explored anesthesiologists' perspectives on Visual Blood, a novel visualization technique for presenting blood gas analysis results. We conducted interviews with participants following two computer-based simulation studies: the first utilizing Virtual Reality (VR) (50 participants) and the second without VR (70 participants). Employing the template approach, we identified key themes in the interview responses and formulated six statements, which were rated using Likert scales: from 1 (strongly disagree) to 5 (strongly agree) in an online questionnaire. The most frequently mentioned theme was the positive usability features of Visual Blood. The online survey revealed that participants found Visual Blood to be an intuitive method for interpreting blood gas analysis (median 4, IQR 4-4, p<0.001). Participants noted that minimal training was required to effectively learn how to interpret Visual Blood (median 4, IQR 4-4, p<0.001). However, adjustments are necessary to reduce visual overload (median 4, IQR 2-4, p<0.001). Overall, Visual Blood received a favorable response. The strengths and weaknesses derived from these data will help optimize future versions of Visual Blood to improve the presentation of blood gas analysis results.

Blood image intensity has been used to detect erythrocyte sedimentation rate (ESR). However, it does not give an information on biophysical properties of blood sample under continuous ESR. In this study, three physical properties, including, τ₀, ESR_τ, and AI_I, are suggested to quantify mechanical variations of blood under continuous ESR. To demonstrate the proposed method, blood sample is loaded into a driving syringe. The blood flow rate is set in a periodic on–off pattern. Blood sample is then supplied into a capillary chip, and microscopic blood images are captured at specific intervals. Blood shear stress is quantified from the interface of blood stream in the coflowing channel. Both τ₀ and ESR_τ are then obtained by analyzing the blood shear stress. Simultaneously, the AI_I is evaluated by analyzing the image intensity of blood flow. According to the experimental results, the τ₀ exhibits consistent trends with respect to hematocrit as well as diluent. The ESR_τ and AI_I showed a reciprocal relationship each other. Three suggested properties represented substantial differences for suspended blood samples (i.e., hardened red blood cells, different concentration of dextran solution and fibrinogen). In conclusion, the present method can detect variations of blood sample under continuous ESR effectively.

This prospective single-center study was designed to assess the clinical utility of the FilmArray® blood culture identification (BCID) panel for improving the diagnostic accuracy in neonatal sepsis. Results obtained using the FilmArray® BCID panel were correlated with results of blood culture in all consecutive neonates with suspicion of early-onset (EOS) and late-onset sepsis (LOS) attended in our service over a 2-year period. A total of 102 blood cultures from 92 neonates were included, 69 (67.5%) in cases of EOS and 33 (32.3%) in LOS. The FilmArray® BCID panel was performed in negative culture bottles at a median of 10 hours of blood culture incubation (range 7.5-20 hours), without differences by the type of sepsis. The FilmArray® BCID panel showed a 66.7% sensitivity, 100% specificity, 100% positive predictive value, and 95.7% negative predictive value. There were four false-negative cases, three of which of Streptococcus epidermidis in neonates with LOS and one case of Granulicatella adiacens in one neonate with EOS. We conclude that the use of the FilmArray® BCID panel in negative blood cultures from neonates with clinical suspicion of sepsis is useful in decision-making of starting or early withdrawal of empirical antimicrobials because of the high specificity and negative predictive values of this assay.

BACKGROUND&AIMS: Hepatitis B virus (HBV) infection remains a major public health problem. The interaction between HBV and the host inflammatory response is an important factor contributing to liver damage and disease development. We compared the correlation between the subclinical index and PBMCs concentration in two groups of pregnant women (HBsAg positive), which are different in HBV DNA concentration in Vietnam. METHODS: The Hierarchical cluster analysis (HCA) was run with 20 different clustering methods on data collected from 80 Vietnamese pregnant women and their babies (60/80 cord blood). RESULTS: In the high viral load group (HBV DNA ≥ 5x10^7 copies/ml), a strong correlation between CBMCs with serum maternal Haemoglobin concentration and maternal platelet and maternal ALT. Their R values are: -0.88, 0.82, and 0.84 with p=8.97E-03, 2.41E-02 and 1.75E-01, respectively. CONCLUSIONS: We found a significant correlation shift of subclinical index between the two groups, which may be important in diagnosing pregnant women with chronic hepatitis B virus infection.

Despite impressive progress in quantum biology, many questions about perception, cognition, memory, and their relation to processing of information remain unanswered. Here is an attempt to draw a unified picture starting with the basic quantum-mechanical phenomenon of nano-superconductivity in the microtubules and extending it to quantum processing of information, and generation of coherent Josephson radiation. A model for the generation in the axons of neurons is suggested. Like in a symphony, but on frequencies ten orders of magnitude higher, the radiation forms resonant standing electromagnetic waves, which are defined by the anatomy, synchronize all the functions in organism, and are behind the memory, perception, and cognition of a living being. It is true that we are made of atoms, but we are coherent electromagnetic waves.

Oligodendroglioma (OG) is a brain tumor that contributes to < 1% of brain tumor diagnoses in the pediatric population. Unfortunately, pediatric OG remains without definitive molecular characteristics to aid in diagnosis, and little is known about the tumor microenvironment. Tumor cells' metabolism and proliferation rate are generally higher than healthy cells, so their iron demand is also significantly increased. This consideration underlines the great importance of iron for tumor development and progression. In this context, this study aims to evaluate the effect of iron in a cellular in vitro model of human oligodendroglioma brain tumor. Cell morphology, the effect of siderotic medium on cell growth, iron uptake, and the expression of iron metabolism-related genes were evaluated by optic microscopy, ICP-MS, confocal microscopy, and RealTime PCR, respectively. This study underlines the great importance of iron for tumor development and progression, but also the possibility of reducing the available iron concentration to determine an antiproliferative effect on OGs. Therefore, every attempt can be promising to defeat the OGs for which there are currently no long-term curative therapies.

Brain capillary endothelial cell(s) (BECs) have numerous functions including their semipermeable interface-barrier (transfer and diffusion of solutes), trophic (metabolic homeostasis), tonic (vascular hemodynamics), and trafficking (vascular permeability, coagulation, and leukocyte extravasation) functions to provide brain homeostasis. BECs also serve as the brain’s sentinel cell of the innate immune system and are capable of antigen presentation. In metabolic syndrome (MetS) there are two regions resulting in proinflammatory signaling of BECs. Namely, visceral adipose tissue depots supplying excessive peripheral cytokines/chemokines (pCC) and gut microbiota dysbiotic regions supplying excessive soluble lipopolysaccharide (sLPS), small LPS-enriched extracellular vesicle exosomes (lpsEVexos), and pCC. This dual signaling of BECs at their receptor sites results in BEC activation and dysfunction (BECact/dys) and neuroinflammation. sLPS and lpsEVexos signal BECs toll-like receptor four, which then signals translocated nuclear factor kappa B (NFkB). Translocated NFkB promotes the synthesis and secretion of BEC proinflammatory cytokines and chemokines. Specifically, the chemokine CCL5 (RANTES) is capable of attracting microglia cells to BECs. BEC neuroinflammation activates perivascular space(s) (PVS) resident macrophages. Excessive phagocytosis by reactive resident PVS macrophages results in a stagnation-like obstruction, which along with increased capillary permeability due to BECact/dys could expand the fluid volume within the PVS to result in enlarged PVS (EPVS). Importantly, this remodeling may result in pre- and post-capillary EPVS that would contribute to their identification on T2-weighted MRI, which are considered to be biomarkers for cerebral small vessel disease.

During the 90 days following hospitalization for acute heart failure, ejection fraction and type of discharge medications have been shown in clinical trials to have little effect on mortality. We examined the recent literature addressing brain-related etiologies of sudden death following heart failure. Two mechanisms of sudden unexpected death have been suggested to possibly result from 4 significant influences on pathophysiology in the brain. The two causes of death are severe cardiac arrhythmia, and neurogenic pulmonary edema. They are both mediated through the brainstem autonomic nuclei generally, and executed specifically through the dorsal motor nucleus of the vagus nerve. The four significant influences on pathophysiology in the brainstem autonomic nuclei are: 1) Hyper-stimulation of neurons in the solitary tract nucleus, increasing their metabolic requirements; 2) Inadequate blood flow at a vascular watershed terminus; 3) Additionally decreased blood flow following vasoconstriction related to relative hyperventilation and decreased pCO2 levels; 4) Gravitational ischemia in the brain—caused by the weight of the brain mass sitting above the brainstem. Changes in head tilt release gravitational ischemia in the brain. There is no specific head position (relative to gravity) that is considered favorable or unfavorable for an extended period of time (i.e. more than 24 hours). Even a small degree of head elevation, used in managing pulmonary congestion, may increase gravitational ischemia in the posterior fossa and brainstem. In this paper we suggest a new and important research avenue for intervening in cardiac arrhythmias, and preventing their occurrence, through the non-invasive use of head-tilting, and other head repositioning maneuvers. This could potentially help many geriatric patients with heart failure, who have decreased mobility in bed, and who tend to stay in one position longer, thereby increasing gravitational ischemia in the brain.