Spatial relations between tumor cells and host-infiltrating cells are increasingly important in both basic science and clinical research. In this study we have tested the feasibility of using standard methods of immunohistochemistry (IHC) in a multiplex staining system using a newly developed set of chromogenic substrates for the peroxidase and alkaline phosphatase enzymes. Using this approach we have developed a set of chromogens characterized by 1) providing fine cellular detail, 2) non-overlapping spectral profiles, 3) absence of interactions between chromogens, 4) stable upon storage, and 5) compatible with current standard immunohistochemistry practices. When viewed microscopically under brightfield illumination the chromogens yielded the following colors; red, black, blue, yellow, brown, and green. By selecting compatible color combinations we have shown feasibility for four-color multiplex staining. Depending on the particular type of analysis being performed, visual analysis, without the aid of computer assisted image analysis, was sufficient to differentiate up to four different markers.

The article explores the concept of 'synthetic man' (SM) in the context of 'synthetic biology' (SB), analysing the potential, challenges, and ethical implications of these achievements. Through dialogue with ChatGPT 4, an in-depth understanding of the evolution, contributions of SM, ChatGPT's contribution, and concerns associated with SM is sought, providing insight into how this technology could affect our society. Our study uses a structured dialogue framework with ChatGPT that addresses essential SM questions regarding SM history, contributions, challenges, and concerns. ChatGPT responses are analysed to extract relevant information and identify trends and insights. The ChatGPT dialogue reveals that MS is still a theoretical and speculative concept with significant advances in gene therapy and genetic engineering. The potential contributions of SM in addressing global challenges such as health, environment and education are identified. Ethical and social concerns such as health risks and psychological impact are also highlighted. Differences in ChatGPT responses were observed between different sessions or even within the same session, which highlighted the limitations in the replicability of the research and sometimes the need for clarification of the questions. The article is distinguished by its unique approach of using an advanced language model to explore a complex and speculative topic. The LLM Dialogue Framework on Technology (LLM-DFonTech) framework proposal for structured dialogue with ChatGPT on various technological topics related to the original contribution provides an adaptable tool for interdisciplinary research in emerging technologies. This methodology opens up new possibilities for analyzing and developing trends in technology and society.

The theories of Evolution and Big Bang have brought a major impact upon the scientific and societal perception upon the origins, abilities and roles of mankind on Earth. It is conclusively evident that Mother Nature and the physical realm is autonomous and all phenomena in the world occur without an imposition against the “free will” of such events and patterns. Nevertheless, this extent of freedom does not imply that life on Earth represents an accident and has no purpose. By careful analysis of ancient religious texts, it can be suggested even otherwise, that it is especially free will that is offered as a gift from outside of the physical dimensions of existence, with the purpose of a continuous edification and improvement of the overall life conditions and of the human perception. It may be that the multi-generational focus on improvement and progress have been misattributed as a long-term evolution of species, that humans came from animal ancestors and that there is a blurred line associating humans with animals. Furthermore, it may be that scientists based their suggestions that no outside Creator would have brought the Earth into existence on physical perspectives, when the extra-dimensional process of Creation implies that all elements of the physical existence undergo a process of Creation from the outside, where time, space and physical matter do not exist, in spite of such elements possibly reflecting unseen elements of the meta-physical world. Finally, there is the following example that deserves attention within the scientific community; just because all living cells - human, animal and plant - contain DNA chromosomes, ribosomes, mitochondria and a plasma membrane, it does not indicate that humans are animals, just as this does not indicate that plants are animals. In Science, there is a golden statement, that correlation does not imply causation. This example is in complete agreement with the verses of the Book of Genesis in the Holy Scriptures regarding the origins of life; namely, that animals could have been created by an Author of all life on Earth so that man would experience companionship. An improved scientific perception of the timeline of life on Earth may be reached via an approach that combines molecular biology with quantum physics, given that the three layers of Science - Biology, Chemistry and Physics - together with their foundational layer of Mathematics, are in fact situated in a relationship of complete harmony.

Epithelial–mesenchymal transition (EMT) is defined as a cellular process during which epithelial cells acquire mesenchymal phenotypes and behavior following the downregulation of epithelial features. EMT and its reversed process, the mesenchymal-epithelial transition (MET), and the special form of EMT, the endothelial-mesenchymal transition (EndMT), have been thought as a universal dogma controlling developmental and pathological processes. More than half a century of EMT study has made it a large research field and a mainstream concept. However, discrepancies and disputes over EMT and EMT research have also grown over time. Particularly, neither the epithelial and mesenchymal states/properties nor their regulatory networks nor specific markers have been defined, rendering the EMT, MET and EndMT concepts groundless. Moreover, EMT and MET effects should not be a cause, but rather a consequence of or an accompanying effect during developmental and pathological processes. EMT and MET represented by the change in cell shapes or adhesiveness or symbolized by EMT factors are biased interpretation of the overall change in cellular property and regulatory networks during development and cancer progression. The true meaning of EMT effects in some developmental and pathological processes, such as fibrosis, needs re-evaluation. But the core EMT factors are actually a few components of the regulatory networks of neural stemness, which determines tumorigenicity and pluripotency. The EMT effects in cancer progression and neural crest formation are wrong attribution of the role of neural stemness during cancer progression and the cell-intrinsic property of neural crest cells to the unknown mesenchymal state. It is time to reassess the significance of EMT and its related concepts in scientific research.

Uterine pathologies pose a challenge to women’s health on a global scale. Despite extensive research, the causes and origin of some of these common disorders are not well defined yet. This study presents a comprehensive analysis of transcriptome data from diverse datasets encompassing relevant uterine pathologies such as endometriosis, endometrial cancer and uterine leiomyomas. Leveraging the Comparative Analysis of Shapley values (CASh) technique, we demonstrate its efficacy in improving the outcomes of classical differential expression analysis on transcriptomic data derived from microarray experiments. CASh integrates the Microarray game algorithm with Bootstrap resampling, offering a robust statistical framework to mitigate the impact of potential outliers in the expression data. Our findings unveil novel insights into the molecular signatures underlying these gynecological disorders, highlighting CASh as a valuable tool for enhancing the precision of transcriptomics analyses in complex biological contexts. This research contributes to a deeper understanding of gene expression patterns and potential biomarkers associated with these pathologies, offering implications for future diagnostic and therapeutic strategies.

In the absence of a treaty protocol or verification regime, the Biological and Toxin Weapons Convention (BWC) instituted Confidence-Building Measures (CBMs) as a mechanism to increase confidence in compliance, by enhancing transparency and mitigating ambiguities regarding states parties’ biological activities. While a promising tool to support treaty compliance, low participation, concerns regarding the completeness and accuracy of CBM submissions, a dearth of analysis, and restricted access to many submissions have limited CBMs’ value. Through interviews with 53 international experts—38 from BWC delegations and 15 independent experts—we identified concrete opportunities to increase CBMs’ value while mitigating the burden on states parties. This study supports states parties’ efforts in the BWC Working Group on the Strengthening of the Convention, as part of a series of research on BWC assurance that aims to characterize challenges around BWC verification and increase certainty in BWC compliance.

Several pathotypes of enteric E. coli have been identified. The group represented by Shiga toxin-producing E. coli (STEC) is of particular interest. Raw milk and raw milk products are significant sources of STEC infection in humans; therefore, identifying pathogens at the herd level is crucial for public health. Most national surveillance programs focus solely on raw milk and raw milk cheeses that are ready for retail sale, neglecting the possibility of evaluating the source of contamination directly at the beginning of the dairy chain. In order to assess the viability of new molecular methodologies applied to raw milk filters enabling the identification of the presence of STEC serotypes in milk production and apply the same methods to identify the presence of these pathogens in calf feces we analyzed, through a commercial real-time PCR assay, a total of 290 samples coming from 18 different dairy herds; 88 bulk tank milk (BTM), 104 raw milk filters (RMF) and 98 calves’ feces samples. In total 3.4% of BTM, 41.4% of RMF and 73.4% of calves’ feces tested positive for stx presence, supporting our hypothesis that BTM is not a suitable matrix to assess the STEC presence at herd level, underestimating it. Our conclusion is that the surveillance program needs critical and extensive improvements such as RMF and calves’ feces analysis implementation in order to be more efficient in detecting and preventing STEC infections. The epidemiology of these infections and the characteristics of the pathogen clearly show how a One Health approach will be pivotal to improve our capabilities to control the spread of these infections.

Abstract: The SARS-CoV-2 pandemic has reemphasized the urgent need for broad-spectrum antiviral therapies. We developed a computational workflow using scRNA-Seq data to assess cellular metabolism during viral infection. With this workflow we predicted the capacity of cells to sustain SARS-CoV-2 virion production in patients and found a tissue-wide induction of metabolic pathways that support viral replication. Expanding our analysis to influenza A and dengue viruses, we identified metabolic targets and inhibitors for potential broad-45 spectrum antiviral treatment. These targets were highly enriched for known interaction partners of all analyzed viruses. Indeed, phenformin, an NADH:ubiquinone oxidoreductase inhibitor, suppressed SARS-CoV-2 and dengue virus replication. Atpenin A5, blocking succinate dehydrogenase, inhibited SARS-CoV-2, dengue virus, respiratory syncytial virus, and influenza A with high selectivity indices. In vivo, phenformin showed antiviral activity against SARS-CoV-2 in a Syrian hamster model. Our work establishes host metabolism as druggable for broad-spectrum antiviral strategies, providing invaluable tools for pandemic preparedness.

Graph databases (GDBs) are becoming increasingly popular across scientific disciplines, being highly suitable to store and connect complex heterogeneous data. In systems biology, they are used as a backend solution for biological data repositories, ontologies, networks, pathways, and knowledge graph (KG) databases. In this review, we analyse all publications using or mentioning graph databases retrieved from PubMed and PubMed Central full-text search, focusing on the top 16 available GDB technologies. Relevant publications are then categorised according to their domain and application. We detail different approaches and highlight advantages of outstanding resources, such as UniProtKB, Disease Ontology, and Reactome, which provide graph-based solutions. We discuss ongoing efforts of the systems biology community to standardise and harmonise KG creation and the maintenance of integrated resources. Outlining prospects, including the use of GDBs as a way of communication between biological data repositories, we conclude that efficient design, querying, and maintenance of GDBs will be key for knowledge generation in systems biology and other research fields with heterogeneous data.

The Herpotrichiellaceae family is an important group of dematiaceous filamentous fungi, associated with a variety of pathogenic fungal species causing Chromoblastomycosis (CBM) and Phaeohyphomycosis (PHM), both with polymorphic clinical manifestations and worldwide incidence. Currently, the identification of this family and determination of the causative agent is challenging due to the subjectivity of morphological identification methods, necessitating the use of molecular techniques to complement diagnosis. In this context, genetic sequencing of the Internal Transcribed Spacer (ITS) has become the norm due to a lack of alternative molecular tools for identifying these agents. Therefore, this study aimed to develop PCR-Multiplex methodologies to address this gap. Sequences from the ITS and Large subunit (LSU) of ribosomal DNA were used, and after manual curation and in vitro analyses, primers were synthesized for the identification of the aforementioned targets. The primers were optimized and validated in vitro, resulting in two PCR-Multiplex methodologies: one for identifying the Herpotrichiellaceae family and the bantiana clade, and another for determining the species Fonsecaea pedrosoi and Fonsecaea monophora. Ultimately, the assays developed in this study aim to complement other identification approaches for these agents, reducing the need for sequencing, improving the management of these infections, and enhancing the accuracy of epidemiological information.

Spontaneous, unwilled subjective imagery and symbols often emerge in psychotherapy that can appear baffling and confound interpretation. Moreover, early psychoanalytic theories seemed to diverge as often as they agreed on the meaning of such content. Nevertheless, reviewing key findings in the empirical science of spontaneous thought, as well as insights gleaned from neurosciences and especially embodied cognition, it is now possible to construct a more coherent theory of interpretation that is clinically useful. Given that thought is so thoroughly embodied, it is possible to demonstrate that universalities in human physiology yield universalities in thought. Such universalities can then be demonstrated to form a kind of biologically directed universal “code” for understanding spontaneous symbolic expressions that emerge in psychotherapy. An example is given that illustrates how this can be applied to clinical encounters.

DNA barcoding has emerged as a powerful tool in the field of taxonomy, transforming the way we identify and classify species. This review article aims to provide an up-to-date overview of the advancements in DNA barcoding techniques, their applications, and their impact on taxonomy and biodiversity studies. We will explore the evolution of DNA barcoding, the development of standardized barcode regions, and the challenges and limitations associated with this methodology. Additionally, we will delve into the diverse range of taxonomic groups for which DNA barcoding has been applied, highlighting key case studies and their contributions to our understanding of biodiversity. Furthermore, we will discuss the integration of DNA barcoding with other molecular and bioinformatic approaches, such as metabarcoding and machine learning, to enhance species identification and biodiversity assessment. This review aims to provide a comprehensive perspective on how DNA barcoding is reshaping the field of taxonomy and its implications for conservation, ecology, and evolutionary biology.

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.

Trimeresurus albolabris, also known as the white-lipped pit viper or white-lipped tree viper, is a highly venomous snake distributed across Southeast Asia and the cause of many snakebite cases. In this study, we report the first whole genome assembly of T. albolabris obtained with next-generation sequencing from a specimen collected in Mengzi, Yunnan, China. After genome sequencing and assembly, the genome of this male T. albolabris individual was 1.51 Gb in length and included 38.42% repeat-element content. Using this genome, 21,695 genes were identified, and 99.17% of genes could be annotated using gene functional databases. Our genome assembly and annotation process was validated using a phylogenetic tree, which included six species and focused on single-copy genes of nuclear genomes. This research will contribute to future studies on Trimeresurus biology and the genetic basis of snake venom.

Tumor necrosis factor (TNF) is a pleiotropic cytokine regulating many physiological and pathological immune-mediated processes. Although initially described as a tumor-cytotoxic agent, over time, it has also been recognized as an essential pro-inflammatory cytokine implicated in the pathogenesis of different autoimmune diseases, such as multiple sclerosis (MS). Several studies have shown an increase in TNF expression both in acute and chronic active MS brain lesions, as well as its involvement in maintaining a chronic inflammatory intrathecal process known as “compartmentalized inflammation”, which contributes to disease progression and disability accumulation in MS, even more than acute inflammatory activity. Indeed, high TNF levels were observed in the serum and cerebrospinal fluid of subjects with MS and correlated to disease severity, promoting axonal damage and, consequently, neurodegeneration. In this review we discuss the current knowledge of TNF and its receptors involvement in MS progression, focusing on disability progression independent of relapse activity (PIRA), meant as the disability accumulation evident in relapsing MS patients not related to acute inflammatory events.

Microfluidic systems offer precise control over physiological, biochemical, and mechanical stimuli in cell culture, allowing in vitro emulation of tissue or tumor microenvironments. This study aims to advance our understanding of tumor biology and contribute to personalized therapy development. Overcoming challenges in cell culture, including cell density and microfluidic device properties, is essential for this purpose. We designed a microfluidic system to facilitate the interaction of diverse cell lineages, incorporating human brain microvascular endothelial cells (HBEC5i), glioblastoma multiforme cells (U87MG), and astrocytes (ScienceCells 1800). Post-fabrication, we assessed the system's functionality and systematically evaluated cell inoculation conditions. Photographic acquisitions comprehensively captured cell culture and their interactions. The device successfully enabled assessment of cellular proliferation, invasion, and migration, supporting the growth of monolayers and tumor organoids. Importantly, each channel demonstrated independence in study processes while allowing cellular intercommunication, both physically and biochemically. In conclusion, the functional microfluidic device facilitated the study of cell migration, tumor invasion, and organoid growth, faithfully replicating biological features observed in a tumor microenvironment. This research contributes to advancing our understanding of tumor biology for the development of personalized therapies.

Asian giant hornet, Vespa mandarinia, is an invasive species that could potentially destroy local honeybee industry in North America. It has been observed to nest in the coastal regions of British Columbia in Canada and Washington State in USA. What is the source population of the immigrant hornets? The identification of the source population can not only shed light on the route of immigration, but also on the similarity between the native habitat and the potential new habitat in the Pacific Northwest. We analyzed mitochondrial COX1 sequences of specimens sampled from multiple populations in China, South Korea, Japan and the Russian Far East. V. mandarinia exhibits phylogeographic patterns, forming monophyletic clades for 16 specimens from China, six specimens from South Korea and two specimens from Japan. The two mitochondrial COX1 sequences from Nanaimo, British Columbia are identical to the two sequences from Japan. The COX1 sequence from Blaine, Washington State, clustered with those from South Korea, and is identical to one sequence from South Korea (GenBank accession MN716828). Our geophylogeny, which allows visualization of genetic variation over time and space, provides evolutionary insights on the evolution and speciation of three closely related vespine species (V. tropica, V. soror and V. mandarinia). The geophylogeny also highlights a strong insufficiency in sample collection in China. The existing sequenced specimens from mainland China with geographic coordinates were represent only four provinces, missing populations along the coastal regions in East China. One therefore cannot exclude the possibility that the Asian giant hornet found in Canada and USA may also be identical to V. mandarinia in Eastern China. We strongly recommend more extensive DNA barcoding data with geographic information and longer DNA barcode (e.g., the entire mitochondrial genome) so that critical questions on invasive species and environmental conservation can be addressed more accurately than what is possible with existing data.

Abstract The relationship between cancer and neurodegeneration has spurred extensive scientific discourse, challenging their historical classification as distinct disorders. While cancer signifies uncontrolled cellular proliferation and neurodegeneration marks progressive neuronal loss, recent insights highlight intriguing interconnections between these seemingly disparate conditions. Cancer entails perpetual signaling for growth, evasion of growth inhibitors, resistance to cell death, acquisition of replicative immortality, stimulation of blood vessel growth (angiogenesis), and initiation of invasion and metastasis. Conversely, investigations emphasize disrupted cellular energy regulation and evasion of immune surveillance as key traits arising from genome instability, mutations, and inflammation driving tumorigenesis. Neurodegeneration involves neuronal malfunction and depletion, synaptic impairment, and protein abnormalities aggregations contributing to muscle atrophy and cognitive deficits. Varied clinical studies underscore contrasting correlations between cancer and neurodegeneration, hinting at mirrored molecular pathways that foster cell resilience or vulnerability. Research explores cellular signaling in tumorigenesis, shared with neurodegenerative disorders. Aberrant expression or mutations in crucial genes implicated in neurodegeneration also surface in cancer contexts. Debates persist on the nature of the relationship between cancer and neurodegeneration, contemplating inverse associations or shared pathways. Understanding their complex interplay, encompassing genetics, cellular mechanisms, and environmental influences, remains pivotal in unraveling their connections. This review explores the intriguing perspective that neurodegeneration and cancer might share fundamental genetic links, delving into potential implications for their onset and progression.

Аnalysis of small RNA sequencing data across a range of biofluids is a significant research area, given the diversity of RNA types that holds potential diagnostic, prognostic, and predictive value. The intricate task of segregating the complex mixture of small RNAs from both human and other species, including bacteria, fungi, and viruses, poses one of the most formidable challenges in the analysis of small RNA sequencing data, currently lacking satisfactory solutions. This study introduces sRNAflow, a user-friendly bioinformatic tool with a web interface designed for the analysis of small RNAs obtained from biological fluids. Tailored to the unique requirements of such samples, the proposed pipeline addresses various challenges, including filtering potential RNAs from reagents and environment, classifying small RNA types, managing small RNA annotation overlap, conducting differential expression assays, analysing isomiRs, and presenting an approach to identify the sources of small RNAs within samples. sRNAflow also encompasses an alternative alignment-free analysis of RNA-seq data, featuring clustering and initial RNA source identification using BLAST. This comprehensive approach facilitates meaningful comparisons of results between different analytical methods. The source code can be accessed at https://github.com/zajakin/sRNAflow under the GPL3 licence.

Interdisciplinary conferences play a vital role in advancing explainable Artificial Intelligence (AI) within increasingly intersecting healthcare and computational biology arenas. Challenges result-ing from algorithmic bias and the necessity for domain-specific Explainable AI (XAI) techniques underscore the increasing significance of transparent and interpretable AI systems used in patient care. Collaborative efforts between clinicians, data scientists, and various stakeholders are nec-essary to innovate solutions tailored to healthcare needs. Specialized conferences may foster these interdisciplinary interactions, providing platforms for knowledge exchange, networking, and collaborative partnerships. The legal, ethical, and societal dimensions of medical AI advocate for an integrative approach that aligns technological advancements with patient-centered care val-ues. The role of specialized conferences is therefore essential for shaping future directions in ex-plainable AI and computational biology that contribute to improved patient outcomes and healthcare innovations.

23-Hydroxy ursolic acid (23-OH UA) is a potent atheroprotective and anti-obesogenic phytochemical, with anti-inflammatory and inflammation resolving properties. In this study, we examined whether dietary 23-OH UA protects mice against the acute onset and progression of experimental autoimmune encephalomyelitis (EAE), a mouse model of multiple sclerosis (MS). Female C57BL/6 mice were fed either a defined low-calorie maintenance diet (MD) or an MD supplemented with 0.2 % wgt/wgt 23-OH UA for 5 weeks prior to actively inducing EAE and during the 30 days post-immunization. We observed no difference in the onset of EAE between both groups of mice, but ataxia and EAE disease severity were suppressed by 52% and 48%, respectively, and disease incidence was reduced by over 49% in mice that received 23-OH UA in their diet. Furthermore, disease-associated weight loss was strikingly ameliorated in 23-OH UA-fed mice. ELISPOT analysis showed no significant differences in frequencies of T cells producing IL-17 or IFN- between 23-OH UA fed mice and control mice, suggesting that 23-OH UA does not appear to regulate peripheral T-cell responses. In summary, our findings demonstrate that dietary 23-OH UA may represent an effective oral adjunct therapy for the prevention and treatment of relapsing-remitting MS.

Telomeres are specialized structures at the ends of linear chromosomes that protect them from degradation and fusion. Telomere replication is a complex process that involves both DNA polymerases and a specialized enzyme called telomerase. Telomerase is a ribonucleoprotein complex that synthesizes telomeric DNA by using an internal RNA template. However, telomerase alone cannot fully replicate the telomeric DNA, and requires the cooperation of other factors, such as shelterin, CST, and DNA repair proteins. Moreover, telomere replication is tightly regulated by various mechanisms, such as cell cycle checkpoints, telomere length homeostasis, and telomere position effect. Dysregulation of telomere replication can lead to genomic instability, cellular senescence, and cancer. Therefore, understanding the molecular details of telomere replication is crucial for elucidating the role of telomeres in aging and disease.

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

For a number of reasons, a curative treatment for most chronic diseases is still unrealized [2–4] and the incidence of many chronic diseases is rapidly increasing [5–9]. A new model is offered as a solution; that being the individualized diagnosis of homeostasis, leading to the correction of epimutations. Individuals with chronic diseases are increasingly being defined by their epigenetic signatures [10,11]. Modern innovations in toxicogenomic studies are also becoming more accurate in their ability to identify the unique epigenetic signature of each toxin [12–14]. Hormesis studies (over 5,000) [15] suggest a universal principle, that a small dose is always a stimulant [16–18].These three facts present an opportunity; a method to diagnose and reverse chronic disease tendencies. This new model requires a paradigm shift in our understanding of disease origins: that dysfunctions in homeostasis [19,20] are the primary and deepest level of chronic disease causation. This is the level where the diagnosis needs to be made and where the corrections need to take place [21].

The task of conveying scientific research to individuals with varying levels of knowledge and understanding can prove to be quite challenging for a research scientist. The difficulty is further compounded when the exchange of information must be conducted within a limited timeframe. Notwithstanding, the 'elevator pitch' is a valuable tool that enables researchers to navigate these potential obstacles. An effective elevator pitch not only facilitates the communication of a researcher's scientific findings but also highlights the individual's skills and the significance of their research. Moreover, a well-crafted elevator pitch is a critical career development tool, serving as a means of networking and paving the way for future communications, scientific collaborations, and funding opportunities. This article examines the value of a scientific elevator pitch and provides step-by-step guidelines for developing and constructing an impactful pitch. Furthermore, we provide resources and an example of a successful elevator pitch delivered by a Fellow from the NIH-funded Accelerating Career Transitions (ACT) program, a professional development program established and managed by the American Society for Cell Biology (ASCB).

This paper presents a concise exploration of the synthetic biology currently to artificially 1 create life, juxtaposed against natural life’s emergence over Earth’s 4.5-billion-year history. It explores 2 the complexities of life’s origins, sustaining factors, and the consequences of synthetic life creation, 3 addressing key scientific milestones such as the Urey-Miller experiment and Jacques Monod’s pro- 4 posals. The narrative navigates through the roles of energy, Maxwell’s demons, bifurcations, and 5 genetic information in the emergence and evolution of complex biological systems. Despite significant 6 strides in genetic engineering, the challenge of creating life from scratch persists, necessitating a deep 7 understanding of diverse scientific disciplines. While synthetic biology holds promise for medicine 8 and biotechnology, the creation of truly autonomous synthetic life forms raises ethical concerns. The 9 paper also stresses the imperative for careful ethical evaluation of the societal and environmental 10 implications arising from these advancements.

Vector-borne disease (VBD) accounts for more than 17% of the global infectious disease burden, disproportionately affecting developing nations within tropical and subtropical areas. As Aedes aegypti mosquitoes are the principal vector for the transmission of many Public Health pathogens, our study examined their population dynamics within the seasonal context of tropical dry biomes in El Salvador as incidence of VBD in this region has increased in recent years. Species that rely on sexual reproduction must maintain a balanced sex ratio (1:1) to support their population dynamics, however, our phenological analysis of field-collected A. aegypti specimens revealed significant sex ratio variations during dry and wet seasons. Interestingly, we detected a seasonal shift that favored female mosquitoes during the dry season, highlighting the dynamic nature of mosquito populations in highly urbanized environments like El Salvador. By linking sex ratio distortions to anthropogenic factors, our study underscores the importance of comprehensively characterizing the urban ecology of vectors for the development of effective biocontrol strategies. As such, we advocate for more nuanced vector control approaches that consider ecological factors as well as the human behaviors that influence mosquito breeding habitats to effectively combat the rise of VBDs amid global climate changes.

Bacteria are engaged in a constant battle against preying viruses, called bacteriophages (or phag-es). These remarkable nano-machines pack and store their genomes in a capsid and inject it into the cytoplasm of their bacterial prey following specific adhesion to the host cell surface. Tailed phages possessing dsDNA genomes are the most abundant phages in the bacterial virosphere, particularly those with long, non-contractile tails. All tailed phages possess a nano-device at their tail tip that specifically recognizes and adheres to a suitable host cell surface receptor, being pro-teinaceous and/or saccharidic. Adhesion devices of tailed phages infecting Gram-positive bacte-ria are highly diverse and, for the majority, remain poorly understood. Their long, flexible and multi-domain encompassing tail limits experimental approaches to determine their complete structure. We have previously shown that the recently developed protein structure prediction program AlphaFold2 can overcome this limitation by predicting the structures of phage adhesion devices with confidence. Here, we extend this approach and employ AlphaFold2 to determine the structure of a complete phage, the lactococcal P335 phage TP901-1. Herein we report the structures of its capsid and neck, its extended tail, and the complete adhesion device, the baseplate, which was previously partially determined by X-ray crystallography.

Constraint-based metabolic modeling approaches have enhanced our knowledge and understanding of the metabolism of prokaryotes and eukaryotes. This approach highly depends on the reconstruction process of genome-scale metabolic models (Mmodels). M-models can guide effective experimental design and yield new insights into the function and control of biological systems. Despite the recent advances in the automated generation of draft metabolic network reconstructions, the manual curation of these networks remains a labor-intensive and challenging task. Thus, these ten quick tips for the manual curation process are essential for optimizing high-quality metabolic model generation in less time. This collection of tips describes in great detail the resources and methods to ensure successful reconstruction. Furthermore, it increases the scope of other protocols of metabolic modeling by including resources to reconstruct eukaryotic organisms. Thus, all tips are applicable to a wide range of eukaryotic organisms. We believe this manuscript will interest a broad audience and researchers from different disciplines, spanning from microbiology and systems biology to biotechnology.

The methods used to introduce CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)/Cas-mediated genome editing into fruit species, as well as the impacts of the application of this technology to activate and knock out of target genes in different fruit trees species including tree development, yield, fruit quality, and tolerance to biotic and abiotic stresses have been firstly described in this review. The application of this gene editing technology could allow the development of new generations of fruit crops with improved traits by targeting different genetic segments or even could facilitate the introduction of traits in elite cultivars without changing other traits. However, at this moment, the scarcity of efficient regeneration and transformation protocols in some species, the fact that many of those procedures are the genotype-dependent or the convenience of segregating the transgenic parts of the CRISPR system represent the main handicaps limiting the potential of genetic editing techniques for fruit trees. Finally, latest news on the legislation and regulations about the use of plants modified through CRISPR/Cas systems has been also discussed.

This article provides a general overview of the bio-inspired computing method called DNA-Based Computing (DBC), including its theory and applications. The main theme of DBC is the central dogma of molecular biology (once information of DNA/RNA has got into a protein, it can’t get out again), i.e., DNA to RNA (sequences of four types of nucleotides) and DNA/RNA to protein (sequence of twenty types of amino acids) are allowed, not the reverse ones. Thus, DBC transfers few-element information (DNA/RAN-like) to many-element information (protein-like), solving a given cognitive problem. DBC can take many forms; this article elucidates two main forms, denoted as DBC-1 and DBC-2. Using arbitrary numerical examples, it is shown that DBC-1 can solve the following cognitive problems: “similarity indexing between seemingly different but inherently identical objects” and “recognizing regions of an image separated by a complex boundary.” DBC-2 can solve the following cognitive problem: “pattern recognition when the relevant information is insufficient.” Smart manufacturing-based systems (digital twins and big data analytics) must solve the abovementioned problems to make the manufacturing enablers (machine tools and monitoring systems) more self-reliant and autonomous. Consequently, DBC can improve the cognitive problem-solving ability of smart manufacturing-relevant systems and, thereby, can enhance its biologicalization.

The possibility of abrupt transitions threatens to poise ecosystems into irreversibly degraded states. Recently, it has been proposed the use of engineered microbiomes in endangered ecosystems to prevent them to cross tipping points and avoid collapse. Potential targets for such interventions include some of the most prominent life-support systems in the biosphere: drylands and coral reefs. Since engineering can require the introduction of microorganisms not present in resident communities, how can we weight the potential outcomes? One way is to use general models of species interactions where the "synthetic" strain is incorporated into a standard multispecies model. Here we follow this approach by modelling a resource-consumer community where one of the species is a modified one that acts by preserving some key resource. We show how the indirect effect of damping the decay of shared resources results in biodiversity increase, and last but not less, the successful incorporation of the synthetic within the ecological network. Further extensions and implications for future restoration and terraformation strategies are discussed.

Intermolecular interactions are the fabrics underlying almost all processes in living organisms, where two cornerstone concepts, intermolecular binding affinity (K d ) and binding energy (ΔG), have long been established to physically describe the strengths of biomolecular interactions, e.g., drug-target K d and ΔG to describe the strength of drug-target interaction. The past two-three years saw a big step forward in the use of artificial intelligence (AI) in structural biology (e.g., AlphaFold for protein structure prediction) and drug discovery & design. In light of the roles of K d and ΔG in drug discovery & design, the speed of this AI progress raises a question of what’s next for its practical application in the pharmaceutical industry, in addition to a system-wide account of biomolecular structures and motions. Last August, the concept of a general intermolecular binding affinity calculator (GIBAC) was for the first time coined and proposed in an MDPI-published preprint. Here, this article puts forward an updated conceptual and practical framework of GIBAC, including its inception, definition, construction, practical applications, technical challenges and limitations, and future directions. Moreover, this article argues that the time is now ripe for the construction of such an accurate, precise and efficient GIBAC to be on the agenda of the entire drug discovery & design community, to ensure its applicability & reliability, and to enhance its value in drug R&D in future.

Glioblastoma (GBM) is a representative malignant brain tumor characterized by a dismal prognosis, with survival rates of less than 2 years and high recurrence rates. Despite surgical resection and several alternative treatments, GBM remains a refractory disease due to its aggressive invasiveness and resistance to anticancer therapy. In this report, we explore the role of fibronectin type III domain containing 3B (FNDC3B) and its potential as a prognostic and therapeutic biomarker in GBM. GBM exhibited a significantly higher cancer-to-normal ratio compared to other organs, and patients with high FNDC3B expression had a poor prognosis (p < 0.01). In vitro studies revealed that silencing FNDC3B significantly reduced the expression of Survivin, an apoptosis inhibitor, and also reduced cell migration, invasion, extracellular matrix adhesion ability, and stem cell properties in GBM cells. Furthermore, we identified that FNDC3B regulates PTEN/PI3K/Akt signaling in GBM cells using MetaCore integrated pathway bioinformatics analysis and a proteome profiler phospho-kinase array with sequential western blot analysis. Collectively, our findings suggest FNDC3B as a potential biomarker for predicting GBM patient survival and for the development of treatment strategies for GBM.

CagY is the largest and most complex protein from Helicobacter pylori's type IV secretion system (T4SS) and may participate in the modulation of gastric tissue inflammation. A three-dimensional structure has been reported for only two segments of the protein. To build a more complete model, particularly the region that spans between the outer membrane (OM) and the inner membrane (IM), we employed different approaches, including homology modeling, ab initio, and deep learning techniques. For the long-middle repeat region (MRR), modeling was performed using deep learning techniques and Molecular Dynamics. The modeled segments were assembled into a chain of 1595 aa, and a 14-chain CagY multimer structure was composed by structural alignment. The final multimer structure correlated with previously published struc-tures and allows to show how the multimer may form the T4SS channel through which CagA and other molecules are translocated to gastric epithelial cells. The model further confirmed that MRR, the most polymorphic and complex region of CagY, presents numerous cysteine residues forming disulfide bonds that stabilize the protein and suggest this domain probably functions as a contractile region that may play an essential role in the modulatory activity of CagY on tissue inflammation.

Brown-Spotted Pit viper (Protobothrops mucrosquamatus), also known as the Chinese habu, is a widespread and highly venomous snake distributed from from northeastern India to eastern China. Genomics research can help provide much insight in understanding venom components and natural selection in vipers. Here, we collected, sequenced and assembled the genome of a male P. mucrosquamatus individual from China, producing a highly continuous reference genome, with the length of 1.53 Gb and 41.18% repeat element content. From this 24,799 genes were identified, and 97.97% genes could be annotated. Nuclear genome single-copy genes phylogenetic tree including 6 species verified the validity of our genome assembly and annotation process. This research will contribute to further study on Protobothrops biology and the genetic basis of the snake venom.

The generation and maintenance of membrane potential is considered a fundamental element of the cellular machinery. They are based on elements of physics and chemistry. Mathematics is used to validate the equations and evaluate the results. However, this computation process can lead to a misunderstanding of the phenomena involved or to the masking of crucial events. It is even possible that the calculation no longer corresponds to the hypothesis considered. Membrane theory is no exception to these trivial considerations, which are essential for normal theory validation.

There are compelling evidences that the immune system is to confer protection not only against foreign pathogens but also against cancer. But if the immune system can’t detect every malignant cell, and at the same time a suitable tumor microenvironment (TME) is formed by inflammatory processes, a carcinogenesis is not longer to be blocked. Once the tumor cells have found their niche, the tumor cells are trained by immune cells turned inside out in how to deal with the immune system "out there". The TME is a training camp and protected space for tumor cells. The Corona crisis has revived a therapeutic approach that was thought to be almost dead: RNA vaccines. Despite decades of research and many clinical studies, no registered RNA cancer vaccine exists today. But the SARS-CoV-2 RNA vaccines against COVID-19 disease have demonstrated their dangerous weaknesses. RNA vaccines manipulate the innate immunity and make the body susceptible to any viral infection. There is also the possibility of integration into the genome. The few approved therapeutic cancer vaccines show little effect. Despite some successes, immunotherapies remain ineffective for most patients with cancer. Powerful therapeutic cancer vaccines remain an unfulfilled dream, a misconception.

While it is well known that 98-99% of the human genome do not encode proteins, but are nevertheless transcriptionally active and give rise to a broad spectrum of noncoding RNAs (ncRNAs) with complex regulatory and structural functions, specific functions have so far been assigned to only a tiny fraction of all known transcripts. On the other hand, the striking observation of an overwhelmingly growing fraction of ncRNAs, in contrast to an only modest increase in the number of protein-coding genes, during evolution from simple organisms to humans, strongly suggests critical but so far essentially unexplored roles of the noncoding genome for human health and disease pathogenesis. Research into the vast realm of the noncoding genome during the past decades thus lead to a profoundly enhanced appreciation of the multi-level complexity of the human genome. Here, we address a few of the many huge remaining knowledge gaps and consider some newly emerging questions and concepts of research. We attempt to provide an up-to-date assessment of recent insights obtained by molecular and cell biological methods, and by the application of systems biology approaches. Specifically, we discuss current data regarding two questions: (1) By which mechanisms could evolutionary recent ncRNAs with critical regulatory functions in a broad spectrum of cell types (neural, immune, cardiovascular) constitute novel thera-peutic targets in human diseases ? (2) Since noncoding genome evolution is causally linked to brain evolution, and given the pro-found interactions between brain and immune system, could human-specific brain-expressed ncRNAs play a direct or indirect (immune-mediated) role in human diseases? Synergistic with the remarkable recent progress regarding delivery, efficacy, and safety of nu-cleic acid-based therapies, the ongoing large-scale exploration of the noncoding genome for human-specific therapeutic targets is encouraging to proceed with the development and clinical evaluation of novel therapeutic pathways suggested by these research fields.

Membrane potential generation and maintenance are fundamental parts of membrane theory. However, since its inception, theories and assumptions have remained simple, whereas the amount of knowledge available has only grown. Unfortunately, this simplification and reductionism lead to its loss of validity on both microscopic and macroscopic scales. This article shows that assumptions made outside the context of factual reality lead to contradictions that cannot be compared with science. Membrane theory must be thoroughly revised, taking into account all forgotten and unanswered assumptions and questions to conform to facts and science to maintain credibility.

Single-particle cryo-electron microscopy (cryo-EM SPA) has recently emerged as an exceptionally well-suited technique for determining the structure of membrane proteins (MPs). Indeed, in the last years, it was observed a huge increase in the number of MPs solved by cryo-EM SPA at a resolution better than 3.0 Å in the Protein Data Bank (PDB). However, sample preparation remains a significant challenge in the field. Here, we evaluated in the MPs solved by cryo-EM SPA deposited in the PDB in the last two years at a resolution below 3.0 Å the most critical parameters for sample preparation: i) the surfactant used for protein extraction from the membrane, ii) the surfactant, amphiphiles, nanodiscs or other molecules present in the vitrification step, iii) the vitrification method employed, and iv) the type of grids used. The aim is not to provide a definitive answer on the optimal sample conditions for cryo-EM SPA of MPs, but rather assess the current trends in the MP structural biology community towards obtaining high-resolution cryo-EM structures.

This study investigates the impact of temperature-induced quantum proton tunneling probability on DNA amplification during polymerase chain reactions (PCR). Using a simulation model based on a Gaussian wavefunction and finite-difference time-domain method, quantum tunneling of protons across square potential barriers is examined. The results unveil consistent probability distributions for quantum tunneling across various PCR temperatures, with distinct oscillation patterns emerging post-barrier crossing. Acknowledging limitations in initial conditions due to temperature-dependent proton energy, the study highlights the need for refined models and experimental validation. These findings accentuate the potential interplay between quantum mechanics and biological systems, prompting further research to understand quantum tunnelling’s comprehensive effect on genetic variations and molecular processes.

Coronavirus Disease 2019 (COVID-19) is an infectious respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease, first identified in the Chinese city of Wuhan in November 2019 and has since spread worldwide, is the latest human pandemic, and has officially infected over 800 million people and has caused nearly seven million deaths to date. Although SARS-CoV-2 belongs to the large family of coronaviruses, it has some unique biological characteristics in its interplay with the human host. Therefore, this narrative review aims to provide an up-to-date overview of the structure of the virus, incubation and shedding in the human host, infectivity and biological evolution over time, as well as the main mechanisms for invading human host cells and replicating within. We also proffer that ongoing epidemiological surveillance of newly emerged variants must always be accompanied by biological studies aimed at deciphering new advantageous traits that may contribute to increasing virulence and pathogenicity, such that the most appropriate strategies for establishing a (relatively) safe coexistence with the human host can be implemented.

A wide panel of microtubule-associated proteins and kinases is involved in coordinated regula-tion of the microtubule cytoskeleton and may thus represent valuable molecular markers contrib-uting to major cellular pathways deregulated in cancer. We previously identified a panel of 17 microtubule-related (MT-Rel) genes that are differentially expressed in breast tumors showing resistance to taxane-based chemotherapy. In the present study, we evaluated the expression, prognostic value and functional impact of these genes in breast cancer. We show that 14 MT-Rel genes (KIF4A, ASPM, KIF20A, KIF14, TPX2, KIF18B, KIFC1, AURKB, KIF2C, GTSE1, KIF15, KIF11, RACGAP1, STMN1) are up-regulated in breast tumors compared with adjacent normal tissue. Six of them (KIF4A, ASPM, KIF20A, KIF14, TPX2, KIF18B) are overexpressed by more than 10-fold in tumor samples and four of them (KIF11, AURKB, TPX2 and KIFC1) are essential for cell survival. Overexpression of all 14 genes, and underexpression of 3 other MT-Rel genes (MAST4, MAPT and MTUS1) are associated with poor breast cancer patient survival. A Systems Biology approach highlighted three major functional networks connecting the 17 MT-Rel genes and partners, which are centered on spindle assembly, chromosome segregation and cytokinesis. Together our studies identified mitotic Aurora kinases and their substrates as major targets for therapeutic approaches against breast cancer.

Due to the variation of the body coloration and the similarity of the related species, there are still some unresolved problems and debates in the taxonomic study of the genus Sycanus in China. We conducted the inter-specific phylogenetic analyses and the species delimitation for Sycanus in China based on DNA barcoding dataset of the mitochondrial cytochrome c oxidase subunit I gene of 81 samples and partial 28S rDNA sequences of 34 samples. The result showed that all the samples were divided into twelve species by integrating the results of DNA barcoding and morphological comparison. In the present paper, the genus Sycanus in China was reviewed systematically, all species were described or re-described, keyed, illustrated and photographed, among them, Sycanus taiwanensis Zhao & Cai sp. nov., Sycanus flavicorius Li & Cai sp. nov. and Sycanus hainanensis Wang & Cai sp. nov. were described as new to science. The biological informations of Sycanus falleni Stål, 1863 and Sycanus croceus Hsiao, 1979 were briefly recorded.

With an ever increasing amount of research data available, it becomes constantly more important to possess data literacy skills to benefit from this valuable resource. An integrative course was developed to teach students the fundamentals of data literacy through an engaging genome sequencing project. Each cohort of students performed planning of the experiment, DNA extraction, nanopore sequencing, genome sequence assembly, prediction of genes in the assembled sequence, and assignment of functional annotation terms to predicted genes. Students learned how to communicate science through writing a protocol in the form of a scientific paper, providing comments during a peer-review process, and presenting their findings as part of an international symposium. Many students enjoyed the opportunity to own a project and to work towards a meaningful objective.

The accumulation of loss of function mutations in the uricase gene well explains the high urate levels in hominoids (apes and humans) compared to other mammals. The loss of human uricase activity may have allowed humans to survive environmental stressors, evolution bottlenecks, and life-threatening pathogens. While high urate levels may contribute to developing cardiometabolic disorders such as hypertension and insulin resistance, low urate levels may increase the risk for neurodegenerative diseases. The double-edged sword effect of uric acid has resurrected a growing interest in the antioxidant role of urate and the role of the uricase gene in modulating the risk of obesity. Characterizing both the effect of uric acid levels and the uricase gene in different animal models may provide new insights into the potential therapeutic benefits of uric acid and novel uricase-based therapy.

The Oriental ratsnake Ptyas mucosa is a common non-venomous snake of the colubrid family, with a wide geographic range spanning much of South and Southeast Asia. P. mucosa is widely cultivated dut to it used in traditional medicine, scientific research, and handicrafts. Therefore, genome resources could play an important role in the efficacy of traditional medicine and the analysis of the living environment of the species. We collected a snake sample in Hezhou, Guangxi, China, which was identified as P. mucosa by morphological identification. Here we present a highly continuous P. mucosa genome with a genome size of 1.74Gb. The scaffold N50 length is 9.57Mb and the maximal length of scaffold is 78.3Mb, the P. mucosa genome has a CG content of 37.9% and the integrity of the gene reached 86.6%.Assembled using long-reads, the total length of the repeat sequence in the genome reached 735 Mb, and its repeat content was as high as 42.19%. A total of 24,869 functional genes were annotated. This study will assist in the understanding of the P. mucosa, and also provide a basis for medicinal research.

Chat generative pre-trained transformer (ChatGPT) is a developed language model and a subgroup of artificial intelligence (AI) which has demonstrated noticeable innovation in interactions between computer models and human studies. The release of ChatGPT in November 2022 attracted over 100 million users in a short time. It has unlimited applications in different fields of studies such as technology and science. ChatGPT utilizes deep learning and internet text to produce responses that resemble human language, although their accuracy is not always guaranteed. ChatGPT and GPT-4 can make a huge revolution in biology, medical, dental research, and health care. However, it's important to acknowledge the limitations of ChatGPT such as limitation in accessing the latest data. ChatGPT has generated both excitement and concern regarding its potential misuse. Its utilization in scientific publications has sparked debates and prompted the development of policies to govern the use of it. Although ChatGPT has certain limitations, it could impact on many different fields of study. There are challenges associated with using ChatGPT in the field of laboratory medicine and biology, particularly in the interpretation of test results. In this article, we review some of the applications of ChatGPT and GPT-4 in biology, dental and medical studies, and concerns about ChatGPT. Despite ChatGPT's conversational abilities are impressive, there are important considerations regarding its use in different fields of research and academic public.

This paper discusses complexity theory, that is, the many theories that have been proposed for emergence of complexity from the underlying physics. Our aim is to identify which aspects have turned out to be the more fundamental ones as regards the emergence of biology, engineering, and digital computing, as opposed to those that are in fact more peripheral in these contexts. In the cases we consider, complexity arises via adaptive modular hierarchical structures that are open systems involving broken symmetries. Each emergent level is causally effective because of the meshing together of upwards and downwards causation that takes place consistently with the underlying physics. Various physical constraints limit the outcomes that can be achieved. The underlying issue concerns the origin of consciousness and agency given the basis of life in physics, which is structured starting from symmetries and variational principles with no trace of agency. A possible solution is to admit that consciousness is an irreducible emergent property of matter.

Diminished ovarian reserve can be regarded as a sentinel indicator to foreshadow severe follicular loss and, ultimately, systemic aging. The negative slope of human ovulatory fidelity begins with a robust follicular endowment which gradually declines over time. In contrast, the youthful ovarian phenotype requires the coordinated work of endothelial, granulosa, immune, perivascular, stromal and possibly germline stem cells. Such a diverse tissue matrix can, in general, be influenced by platelet (PLT)-derived factors but this has not yet been specifically confirmed in the ovary after platelet-rich plasma (PRP). How could a comparable response be validated? Here a prospective, experimental study is proposed whereby eligible patients already undergoing scheduled laparoscopy provide ovarian tissue via biopsy submitted for co-culture with autologous Ca⁺² activated PRP. Recognizing the interlocking, central roles of nuclear factor κB (NF-κB) and tumor necrosis factor-α (TNF-α), incubated samples would be assessed for these in vitro before vs. after PRP exposure, in addition to stereomicroscopy. A mathematical model is available to track NF-κB oscillations and estimate gene expression, cell development, growth, apoptosis, and key immune and inflammatory actions. Since NF-κB and TNF-α are discharged in activated PLT releasate (or react to its cargo proteins) this audit permits extraction of response markers observed post-stimulus, thus linking discrete signals to transcriptional output, cellular fitness, and ovarian cytoarchitecture. From this, a hypothesis could emerge where intraovarian PRP is found to make no direct impact on follicles, although modified ovarian field function and curtailed local entropy incidentally favor optimized oocyte competence as a secondary effect.

The study of the currently known >3,000 species of snakes can provide valuable insights into the evolution of their genomes. Deinagkistrodon acutus, also known as Sharp-nosed Pit Viper, one hundred-pacer viper or five-pacer viper, is a venomous snake with significant economic, medicinal and scientific importance. Widely distributed in southeastern China and South-East Asia, D. acutus has been primarily studied for its venom. Here, we employed next-generation sequencing to assemble and annotate a highly continuous genome of D. acutus. The genome size is 1.46 Gb; its scaffold N50 length is 6.21 Mb, the repeat content is 42.81%, and 24,402 functional genes were annotated. This study helps to further understand and utilize D. acutus and its venom at the genetic level.

Aim: Streptococcus pneumoniae and influenza H1N1 virus are common organisms associated with human infections. These infections could play a significant role in immune regulation. The study was performed to analyse the genome sequences of these organisms with human genome and study its functional significance. Methods: The study was performed to analyse the overlapping of genome sequences in Streptococcus pneumoniae and Influenza (H1N1) virus against human genome sequences by BLASTn sequence analysis. The alignments are studied against the corresponding genes for their functional significance with DAVID and NDEx software.Results: Several hits or overlapping nucleotide segments were identified. Between streptococcus and homo sapiens 287 overlaps were identified, and among influenza and homo sapiens 124 hits were identified. A wide range of functional significance of these genes were identified, and the results are presented in this study. The results show insights into functional pathways and biological activities associated with the respective vaccinations or infections by these microorganisms. Conclusion: The common organisms like Streptococcus pneumoniae and Influenza H1N1 virus actively interact with the immune system and result in a wide range of immune regulations.

Living beings are composite thermodynamic systems in non-equilibrium conditions. Within this context, there are a number of thermodynamic potential differences (forces) between them and the surroundings, as well as internally. These forces lead to flows, which, ultimately, are essential to life itself. Living beings are under the pressures of natural selection, thus are biological flows as well. At the same time, the maintenance of homeostatic conditions, the tenet of physiology, demands regulation of these flows by control of variables. However, due to the very nature of these systems, regulation of flows and control of variables become entangled in closed loops. Therefore, the search for adaptation in flows takes a different path than the search for adaptation in morphological traits. Being at the roots of transfer processes, thermodynamic criteria turn out to be as natural physical candidates. Likewise, being at the roots of physiology, control turns out to be as a natural biological candidate in that path. Here we show how to combine entropy generation, with respect to a generalized process, and control of parameters (in such a generalized process) in order to create a criterium of optimal ways to regulate changes in generalized flows.

The idea that the Earth system self-regulates in a habitable state was proposed in the 1970s by James Lovelock, who conjectured that life plays a self-regulatory role on a planetary-level scale. A formal approach to such hypothesis was presented afterwards under a toy model known as the Daisyworld. The model showed how such life-geosphere homeostasis was an emergent property of the system, where two species with different properties adjusted their populations to the changing external environment. So far, this ideal world exists only as a mathematical or computational construct, but it would be desirable to have a real, biological implementation of Lovelock's picture beyond our one Biosphere. Inspired in the exploration of synthetic ecosystems using genetic engineering and recent cell factory designs, here we propose such a living, microbial Daisyworld. This is based on a synthetic microbial ecosystem using pH as the external, abiotic control parameter. Several case studies are considering, including two, three and multiple species assemblies. Despite that oscillatory dynamics and chaos emerge in the latter case, it is shown that global regulation is also achieved in most cases as species diversity increases. The alternative implementations and their implications of this model in other synthetic biology scenarios, including ecosystem engineering, are outlined.

RNA polymerase III (RNAP III) holoenzyme activity and its products processing have been linked to several metabolic dysfunction in lower and in higher eukaryotes. Alterations in the activity of RNAP III driven synthesis of non-coding RNA, causes extensive changes in the glucose metabo-lism. Increased RNAP III activity in S.cerevisiae maf1Δ strain, manifests with lethality when grown on non-fermentable carbon source. This lethal phenotype is suppressed by reducing tRNA syn-thesis. The cause for the lack of growth neither the underlying molecular mechanism has not been deciphered and has been awaiting a scientific explanation for a decade. Our previous proteomics data suggested mitochondrial dysfunction of the strain. Using model mutant strains maf1Δ (with increased tRNA abundance) and rpc128-1007 (with reduced tRNA abundance) we collected data showing major changes in TCA cycle metabolism of the mutants that explain the phenotypic ob-servations. The present study, based on 13C flux data and analysis of TCA enzymes activities, identifies the flux constraints in the mitochondrial metabolic network. The lack of growth is associated with the de-crease in TCA cycle activity and downregulation of the flux towards glutamate, aspartate and phosphoenolopyruvate (PEP), the metabolic intermediate feeding gluconeogenic pathway. rpc128-1007, the strain that is unable to increase tRNA synthesis due to a mutation in C128 subunit, has increased activity of TCA cycle under non-fermentable conditions. To summarize, cells with non-optimal activity of RNAP III, undergo substantial adaptation to a new metabolic state, that make them vulnerable under specific growth conditions. Our results strongly suggest that balanced, non-coding RNA synthesis that is coupled to glucose signaling is a fundamental requirement to sustain cell’s intracellular homeostasis and flexibility under changing growth conditions. Presented results provide insight into the possible role of RNAP III in mito-chondrial metabolism of other cell types.

As cancer remains resistant to several modes of treatment, novel therapeutics are still under active investigation to overcome treatment inefficacy in cancer. Given the high attrition rate of de novo drug discovery, drug screening, and drug repurposing have offered time- and cost-effective alternative strategies for the identification of potentially effective therapeutics. In contrast to large-scale drug screens, computational approaches for drug repurposing leverage the increasing amounts of biomedical data to predict candidate therapeutic agents prior to testing in biological models. Current studies in drug repurposing for cancer therapy prediction have increasingly focused on the prediction of combination therapies, as combination therapies have numerous advantages over monotherapies. These include increased effect from synergistic interactions, reduced toxicity from lowered drug doses, and a reduced risk of resistance due to multiple non-overlapping mechanisms of action. This review provides a summary of several classes of computational methods used for drug combination therapy prediction in cancer research, including networks, regression-based machine learning, classifier machine learning models, and deep learning approaches, with the goal of presenting current progress in the field, particularly to non-computational cancer biologists. We conclude by discussing the need for further advancements in technologies that incorporate disease mechanisms, drug characteristics, multi-omics data, and clinical considerations to generate effective patient-specific drug combinations, as holistic data integration will inevitably result in optimal targeted therapeutics for cancer.

As recently as 2002 programmed aging in mammals was widely thought to be theoretically impossible based on generally accepted concepts regarding the evolution process. However, as described in this article, genetics discoveries, results of selective breeding, and other direct evidence strongly support the idea that aging creates an evolutionary advantage and that therefore complex biological mechanisms evolved that control mammal aging. Like similar life-cycle programs that control reproduction, growth, and menopause the aging program can adjust the aging trait during an individual’s life to compensate for temporary or local changes in external conditions that alter the optimum lifespan for a particular species population. In addition, genetics discoveries strongly support the evolvability concept to the effect that sexually reproducing species can evolve design features that increase their ability to evolve, and that aging is one such feature.

Angiotensin II (Ang II) plays a role in several inflammatory diseases and is capable of inducing the release of inflammatory mediators in several cell types. The objective was to investigate the potential of Ang II to induce mRNA expression of inflammatory mediators by cultured primary human periodontal cells. A synergistic effect of a co-treatment with Ang II and IL1β on mRNA expression of inflammatory mediators was also explored. Primary cultures of human fibroblast-like cells isolated from gingival and periodontal ligament tissues from 3 subjects were established using explant techniques. Immunophenotyping of STRO-1, Ang II type 1 receptor (AT1R) and Ang II type 2 receptor (AT2R) was performed by flow cytometry analysis. Cell cultures were challenged with Ang II (1M) for 3, 6 and 24h with or without a co-treatment with IL1β (0.1ng/mL) for 24h. mRNA expression of inflammatory mediators was performed by real time quantitative polymerase chain reaction (RT-qPCR). We present, for the first time, a precise quantification for AT1R and AT2R on human gingival and periodontal fibroblast-like cell types; the percentage of positive immunostaining compared to the total population of cells varied from 3.35% through 5.29% for AT1R and 2.97% through 4.57% for AT2R. Ang II slightly upregulated mRNA expression of IL6 and CCL2/MCP1 in gingival cells and IL8 and PTGS2/COX2 in periodontal ligament cells. IL1β induced upregulation of IL8, IL6 CCL2/MCP1, PTGS2/COX2 and IL1β mRNA in both cell types. Co-treatment with Ang II and IL1β did not show a synergistic effect under these experimental conditions. Ang II shows a low potential to induce mRNA upregulation of inflammatory mediators in cultured primary human gingival and periodontal ligament cells, most likely due to the low percentage of Ang II receptors in such cells, and no synergistic effect with the co-treatment with IL1β.

Organophosphate pesticides (OPs) are toxic substances that contaminate aquatic environments, interfere with the development of the nervous system, and induce Neurodevelopmental Toxicity (NDT) in animals and humans. The canonical mechanism of OP neurotoxicity involves the inhibi-tion of acetylcholinesterase (AChE), but other mechanisms non-AChE are also involved and not fully understood. We used network toxicology and molecular docking to identify molecular targets and toxicity mechanisms common to OPs. Targets related to diazinon-oxon, chlorpyrifos oxon, and paraoxon OPs were predicted using the Swiss Target Prediction and PharmMapper databases. Targets related to NDT were compiled from GeneCards and OMIM databases. In order to construct the protein-protein interaction (PPI) network, the common targets between OPs and NDT were imported into the STRING. Networks topological analyses identified EGFR, MET, HSP90AA1, and SRC as hub nodes common to the three OPs. Using Reactome pathway and gene ontology we found that signal transduction, axon guidance, cellular responses to stress, and glutamatergic signaling activation play key roles in OP-induced NDT.

Atrial fibrillation (AF), the most prevalent type of sustained cardiac dysrhythmia globally, confers strikingly enhanced risks for cognitive dysfunction, stroke, chronic cardiac failure, and sudden cardiovascular demise. Aggregating studies underscore the crucial roles of inherited determinants in the occurrence and perpetuation of AF. However, due to conspicuous genetic heterogeneity, the inherited defects accounting for AF remain largely indefinite. Here, via the whole-genome genotyping with genetic markers and linkage assay in a family suffering AF, a new AF-causative locus was located at human chromosome 7p14.2-p14.3, a ~4.89-cM (~4.43-Mb) interval between the markers D7S526 and D7S2250. Exome-wide sequencing assay unveiled that at the defined locus, solely the mutation in the TBX20 gene, NM_001077653.2: c.695A&gt;G; p.(His232Arg), co-segregated with AF in the family. Additionally, Sanger sequencing assay of TBX20 in another family suffering AF uncovered a novel mutation, NM_001077653.2: c.862G&gt;C; p.(Asp288His). Neither of the two mutations was observed in 600 unrelated control individuals. Functional investigations demonstrated that the two mutations both significantly reduced the transactivation of the target gene KCNH2 (a well-established AF-causing gene) and the ability to bind the promoter of KCNH2, while without effect on the nuclear distribution of TBX20. Conclusively, these findings reveal a new AF-causative locus at human chromosome 7p14.2-p14.3 and strongly indicate TBX20 as a novel AF-causative gene, shedding light on the mechanism underlying AF and suggesting clinical significance for allele-specific treatment of AF patients.

We consider new insights into the origin and nature of pointer states and their role in wave function collapse in macroscopic quantum coherence. The work includes new theory of quantum coherence underpinned by turbulence, generated by a field of pointer states in the form of recirculating vortices (toroids), interconnected via a vortex cascade. Decoherence occurs when the interconnected field of vortices between pointer states is disrupted by external forces, leading to their localisation. The applicability of this work is considered in addressing unresolved questions in high temperature superconductivity and macroscopic quantum processes in biological systems. We also consider its implications for our understanding of intrinsic spin and pointer states within the standard "point source" representation of a quantum particle, which intuitively requires a more complexed description.

Microbial fuel cells (MFCs) offer sustainable solutions for various biotechnological applications and are a crucial area of research in biotechnology. MFCs can effectively treat wastewater and biodiesel waste by decomposing organic matter and generating electricity. Certain Pseudomonas species possess extracellular electron transfer (EET) pathways, enabling them to transfer electrons from organic compounds to the MFC's anode. Moreover, Pseudomonas species can grow under low oxygen conditions, which is advantageous considering that the electron transfer process in an MFC typically leads to reduced oxygen levels at the anode. This study focuses on evaluating MFCs inoculated with a new Pseudomonas species, grown with 1 g.L-1 glycerol, a common byproduct of biodiesel production. Pseudomonas sp. BJa5 exhibited a maximum power density of 39 mW.m-2. Also, the observed voltammograms and genome analysis indicate the potential production of novel redox mediators by BJa5. Additionally, we investigated the bacterium's potential as a synthetic biology non model chassis. Through testing various genetic parts, including constitutive promoters, replication origins, and cargos using pSEVA vectors as a scaffold, we assessed the bacterium's suitability. Overall, our findings offer valuable insights into utilizing Pseudomonas spp. BJa5 as a novel chassis for MFCs. Synthetic biology approaches can further enhance the performance of this bacterium in MFCs, providing avenues for improvement.

Peroxiredoxins play central roles in the detoxification of reactive oxygen species and have been modelled across multiple organisms using a variety of kinetic methods. However, the peroxiredoxin dimer-to-decamer transition has been underappreciated in these studies despite the 100-fold difference in activity between these forms. This is due to the lack of available kinetics and theoretical framework for modelling this process. Using published isothermal titration calorimetry data, we obtained association and dissociation rate constants of 93.0 µM-4·s-1 and 102 s-1, respectively, for the dimer-decamer transition of human PRDX1. We developed an approach that greatly reduces the number of reactions and species needed to model the peroxiredoxin decamer oxidation cycle. Using these data, we simulated horse radish peroxidase competition and NADPH-oxidation linked assays and found that the dimer-decamer transition had an inhibition-like effect on peroxidase activity. Further, we incorporated this dimer-decamer topology and kinetics into a published and validated in vivo model of PRDX2 in the erythrocyte and found that it almost perfectly reconciled experimental and simulated responses of PRDX2 oxidation to hydrogen peroxide insult. By accounting for the dimer-decamer transition of peroxiredoxins, we were able to resolve several discrepancies between experimental data and available kinetic models.

Background. The molecular mechanisms underlying de novo metastasis of luminal breast cancer (dnMBC) remain largely unknown. Materials & Methods. Newly diagnosed dnMBC patients (grade 2/3, ER+, PR+/-, HER2-), with available core needle biopsy (CNB), collected from the primary tumor, were selected from our clinical-pathological database. Tumors from dnMBC patients were 1:1 pairwise matched (n=32) to tumors from newly diagnosed patients who had no distant metastases at baseline (eBC group). RNA was extracted from 5 x 10µm sections of FFPE CNBs. RNA sequencing was performed using the Illumina platform. Differentially expressed genes (DEG)s were assessed using EdgeR, deconvolution was performed using CIBERSORTx to assess immune cell fractions. Paired Wilcoxon test was used to compare dnMBC and eBC groups, and corrected for false discovery rate (FDR). Results. Many regulatory DEGs were significantly downregulated in dnMBC compared to eBC. Also, immune-related and hypoxia-related signatures were significantly upregulated. Paired Wilcoxon analysis showed that CCL17 and neutrophils fraction were significantly upregulated, whereas the memory B-cell fraction was significantly downregulated in the dnMBC group. Conclusion. Primary luminal tumors of dnMBC patients display significant transcriptomic and immunological differences compared to comparable tumors from eBC patients.

The global malaria community has picked up the theme of malaria elimination in greater than 90 % of the world’s population in the next decade. The recent reports of P. vivax in all sub-Saharan Africa, including Duffy negative individuals, threaten the efforts to achieve elimination. This is not only in view of strategies that are tailored only to P. falciparum elimination, but also due to currently revealed biological characteristics of P. vivax concerning the relapse patterns of hypnozoites and conservation of a large biomass at cryptic sites in the bone marrow and spleen. A typical scenario has been observed in Botswana from the period between 2008 to 2018, which palpably projects how P. vivax could endanger efforts at malaria elimination where the two parasites co-exist. The need for the global malaria community, NMPs, funding agencies and relevant stakeholders to engage in a forum to discuss and recommend clear pathways for sub-Saharan Africa regarding malaria elimination including P. vivax, is warranted.

Based on the eventual destruction of the solar system and the critical need for human continuation, this article suggests sending synthetic biology- and AI-created plant-like astronauts to the closest habitable exoplanet, Teegarden's Star b. Here we show that these astronauts will have green skin, blue blood, and the ability to perform photosynthesis. They could withstand cosmic radiation and extremely low temperatures in space while generating energy through photosynthesis. This groundbreaking interdisciplinary approach may provide a solution to the survival challenges faced by humans on their eternal interstellar journey. As long as plant-like astronauts possess human consciousness, it does not matter whether they are even a hybrid of carbon-based and silicon-based life. They will be a continuation of humanity on exoplanets. Human faces two options for survival. The first is the Mars migration program led by Elon Reeve Musk, which remains within the solar system and may not protect against the Sun's future scorching all life on the solar system during its red giant phase. The second option involves a more daring approach: the frantic escape of plant-like astronauts from the solar system. Should we consider both options simultaneously, much like how humans use their two legs to walk?

The Lagrangian formalism is developed for the population dynamics of interacting species that are described by several well-known models. The formalism is based on standard Lagrangians, which represent differences between the physical kinetic and potential energy-like terms. A method to derive these Lagrangians is presented and applied to selected theoretical models of the population dynamics. The role of the derived Lagrangians and the energy-like terms in the population dynamics is investigated, and it is shown that the obtained standard Lagrangians can be used to study oscillatory behavior of the models and the period of their oscillations, which may have ecological and environmental implications. These and other physical and biological insights gained from the derived standard Lagrangians are discussed.

Arterial hypertension is a common condition worldwide and an important risk factor for cardio- and cerebrovascular events, renal diseases as well as microvascular eye diseases. Established hypertension leads to chronic vasoconstriction of small arteries as well as to decreased lumen diameter and thickening of the arterial media or wall with a consequent increased media-to-lumen ratio (MLR) or wall-to-lumen ratio (WLR). This process, defined as vascular remodeling, was first demonstrated in small resistance arteries isolated from subcutaneous biopsies and measured by micromyography, and this is still considered the gold-standard method for the assessment of structural alteration in small resistance arteries; however microvascular remodeling seems to represent a generalized phenomenon. An increased MLR may impair organ flow reserve, being relevant in the maintenance and, probably, also in the progressive worsening of hypertensive disease, as well as in the development of hypertension-mediated organ damage/cardiovascular events, possessing, therefore, a prognostic relevance. New, non-invasive techniques, such as Scanning Laser Doppler Flowmetry or Adaptive Optics, are presently under development, focusing mainly on the evaluation of WLR in retinal arterioles; recently, also retinal microvascular WLR was demonstrated to have a prognostic impact in term of cardio- and cerebrovascular events. A rarefaction of capillary network has also been reported in hypertension which may contribute to flow reduction and impairment in oxygen delivery to different tissues. These microvascular alterations seem to represent an early step in hypertension-mediated organ damage since they might concur to microvascular angina, stroke, and renal dysfunction. In addition, they could be a marker useful in monitoring the beneficial effect of antihypertensive treatment. Also conductance arteries may be affected by a remodeling process in hypertension, and a cross-talk may exist between structural changes in the small and large arteries. The review will address the possible relations between structural microvascular alterations and hypertension-mediated organ damage and their potential improvement with antihypertensive treatment.

Epigenetic alterations are heritable and enduring modifications in gene expression that play a pivotal role in immune evasion. These include alterations to noncoding RNA, DNA methylation, and histone modifications. DNA methylation plays a crucial role in normal cell growth and development but alterations in methylation patterns such as hypermethylation or hypomethylation can enable tumor and viral cells to evade host immune responses. Histone modifications can also inhibit immune responses by promoting the expression of genes involved in suppressing normal immune function. In the case of T-cell lymphoma, adult T-cell Lymphomas (ALT) also undergo immune evasion through the exceptional function of its accessory and regulatory genes. Epigenetic therapies are emerging as a promising adjunct to traditional immunotherapy and chemotherapy regimens. Clinical trials are currently investigating the use of epigenetic therapies in combination with immunotherapies and chemotherapies for more effective treatment of ATL and other cancers. This review highlights epigenetic alterations that are widely found in T cell malignancies.

Snakes are a vital component of wildlife resources and are widely distributed across the globe. Bungarus multicinctus, a highly venomous snake, is found in central and southern China. B. multicinctus is a highly venomous snake and is distributed in central and southern China. Snakes are an ancient group of reptiles, and their genome resources can provide important clues for understanding the evolutionary history of reptiles. Meanwhile, genomic resources play a crucial role in comprehending the evolution of species. So far, the genomic resources of snakes are a rarity. In 2021, a snake sample was collected from Beiliu Longgukeng, Guangxi, which was identified as B. multicinctus through morphological identification. In this study, we present a highly contiguous genome of B. multicinctus with a size of 1.51 Gb. The genome contains a repeat content of 40.15%, with a total length exceeding 620 Mb. Additionally, we annotated a total of 24,869 functional genes. This research is of great significance for comprehending the evolution of B. multicinctus and provides a genomic basis for the genes involved in venom gland function.

Blood-based circulating cell free DNA(cfDNA) detection offers a non-invasive and easily accessible way for early cancer detection. Despite the extensive utility of cfDNA, there are still many challenges to develop the clinical biomarkers. For example, cfDNA with genetic alterations often compose a small portion of the DNA circulating in plasma, which can be confounded by cfDNA contributed by normal cells. Therefore, filtering out the potential false-positive cfDNA mutations from health population will be important for the cancer-based biomarkers. Additionally, many low-frequency genetic alterations are easily overlooked in small amount of cfDNA-based cancer test. We hypothesize that, the combination of diverse types of cancer studies on cfDNA can provide us a new insight to identify low-frequency genetic variant across cancer types for early clinical detection of cancers. By building a standardized computational pipeline for 1358 cfDNA samples across seven cancer types, we prioritize 129 shard genetic variants in the major cancer types. Further functional analysis of the 129 variants found that they are mainly enriched in ribosome pathways such as cotranslational protein targeting to membrane, some of which are tumor suppressor, oncogene and related to cancer initiation. In summary, our integrative analysis revealed the important roles of ribosome proteins as the common biomarkers in early cancer diagnosis.

Enteric protozoan pathogenic infections significantly contribute to the global burden of gastrointestinal illnesses. Their occurrence is considerable within remote and indigenous communities and regions due to reduced access to clean water and adequate sanitation. The robustness of these pathogens means requirement of harsh treatment methods such as medicinal drugs or antibiotics. However, such treatments impact the gut microbiome, and create dysbiosis, often leading to opportunistic pathogens, anti-microbial resistance, or functional gastrointestinal disorders (FGIDs) such as irritable bowel syndrome (IBS). Recent studies have shown that these impacts do not remain confined to gut, and are reflected across the gut-brain, gut-liver, and gut-lung axes, among others. Therefore, apart from the medicinal treatment, nutritional supplementation is also a key aspect of providing the recovery from this dysbiosis. Future proteins, prebiotics, probiotics, synbiotics, and food formulations offer a good solution to remedy this dysbiosis. Furthermore, the nutritional supplementation also helps to build a resilience against the opportunistic pathogens and potential future infections and disorders that may arise due to the dysbiosis. Systems biology techniques have shown to be highly effective tools to understand the biochemistry of these processes. Systems biology techniques characterises the fundamental host-pathogen interaction biochemical pathways, at various infection and recovery stages. This same mechanism also allows to track the impact of abovementioned treatment methods of gut microbiome remediation. This manuscript is organised in sections delving into system biology approaches and upcoming developments to understand (1) Infection mechanism and current global status; (2) Cross-organ impacts of dysbiosis, particularly within gut-liver and gut-lung axes; (3) Nutritional interventions. It highlights the impact of antimicrobial resistance (AMR) and Multi-drug resistance (MDR) from a perspective of protozoal infections. It also highlights the role of nutritional interventions to add resilience against the chronic problems caused by these phenomena.

With the exponential growth of machine learning and development of Artificial Neural Network (ANNs) in recent years, there is great opportunity to leverage this approach and accelarate bio-logical discoveries through applications on the analysis of bioinformatics data. Various types of datasets including for example protein or gene interaction networks, molecular structures and cellular signalling pathways, have already been used for machine learning by training ANNs for inference and pattern classification. However, unlike regular data structures that are commonly used in the computer science and engineering fields, bioinformatics datasets present challenges that require unique algorithmic approaches. The recent development of the geometric and deep learning approach within the machine learning field, is very promising towards accelerating analysis complex bioinformatics datasets. The principles of ANNs and their importance for bio-informatics machine learning is demonstrated herein, through presentation of the undelying mathematical and statistical foundations from group theory, symmetry, linear algebra. Further-more, the structure and functions of ANN algorithms that form the core principles of artificial intelligence are explained, in relation to the bioinformatics data domain. Overall, the manuscript provides guidance for researchers to understand the principles required for practicing machine learning and artificial intelligence, with the special considerations towards bioinformatics applications.

Knowledge about pharmacological benefits of different seeds is an important factor for cultivation and application of medicinal herbs and plants. The seeds of medicinal plants are stores of valuable and active secondary metabolites that have been commercially and economically beneficial and helpful for medicine and pharmacy. The major parameter of reproduction and preservation of plants are also seeds which have a functional role in the distribution and establishment of plant in different regions. Five important seeds which have tremendous medicinal and pharmacological benefits are anise, basil, borage, cilantro and chamomile. Anise seed is used as a spice, either whole or ground, and its essential oil and extract are also obtained from the seeds. Basil seeds have a long history of usage in Chinese and Ayurvedic medicine, which are the good source of minerals, high in fiber including pectin, rich is flavonoids and other polyphenols. Borage seed oil is used for skin disorders such as seborrheic dermatitis, atopic dermatitis, and neurodermatitis. Cilantro is an annual herb that is part of the Apiaceae family. The seeds are rich in iron, zinc, copper and essential minerals which can decrease bad cholesterol and improves good cholesterol in the body. Chamomile can be considered for treatment of insomnia, hemorrhoids, anxiety, diarrhea and may help with wound healing and skin irritation. The keyword searches for Anise, Seed, Basil, Borage, Cilantro, Chamomile, Seed biology, Traditional medicinal science and seed anatomy were performed by using Scopus, Web of Science, PubMed and Google scholar. The aim of this article review is to survey the pharmacological and health benefits of seeds of five important medicinal plants.

Base excision repair (BER) is a cellular process that removes damaged bases arising from exogenous and endogenous sources including reactive oxygen species, alkylation agents, and ionizing radiation. BER is mediated by the actions of multiple proteins that work in a highly concerted manner to resolve DNA damage efficiently to prevent toxic repair intermediates. During the initiation of BER, the damaged base is removed by one of 11 mammalian DNA glycosylases resulting in abasic sites. Many DNA glycosylases are product inhibited by binding to the abasic site more avidly than the damaged base. Traditionally apurinic/apyrimidinic endonuclease, APE1, was believed to help turnover the glycosylases to undergo multiple rounds of damaged base removal. However, in a series of papers from our laboratory we have demonstrated that UV-damaged DNA binding protein (UV-DDB) stimulates the glycosylase activities of human 8-oxoguanine glycosylase (OGG1), MUTY DNA glycosylase (MUTYH), alkyladenine glycosylase/N-methylpurine DNA glycosylase (AAG/MPG), and single-strand selective monofunctional glycosylase (SMUG1), between three-to-five-fold. Moreover, we have shown UV-DDB can assist chromatin decompaction facilitating access of OGG1 to 8-oxoguanine damage in telomeres. This review summarizes the biochemistry, single-molecule, and cell biology approaches that our group used to directly demonstrate the essential role of UV-DDB in BER.

Antibiotic therapy is a cornerstone of modern medicine, yet the development of antibiotic re-sistance threatens to render these therapies ineffective. The gut microbiota, a complex ecosystem of microorganisms residing in the gastrointestinal tract, plays a critical role in modulating anti-biotic efficacy and resistance. This review delves into the intricate relationship between gut mi-crobiota, antibiotic therapy, and resistance, and discusses the potential applications of gut mi-crobiota research in guiding personalized antibiotic therapy and resistance mitigation strategies. Recent advancements in metagenomics, metatranscriptomics, and metabolomics have demon-strated the potential for tailored antibiotic regimens that minimize collateral damage to com-mensal bacteria and reduce the risk of resistance. Adjuvant therapies such as probiotics, prebi-otics, and synbiotics have shown promise in restoring gut microbial balance and mitigating the adverse effects of antibiotic therapy. We address the challenges associated with this emerging field including the need for standardized methodologies, ethical considerations, and interdisci-plinary collaboration. With continued interdisciplinary collaboration and the implementation of standardized methodologies, gut microbiota research can contribute to the global fight against antibiotic resistance and improve patient outcomes.

In T. gondii, as well as in other model organisms, gene knock-out using CRISPR-Cas9 is a suitable tool to identify the role of specific genes. The general consensus implies that only the gene of interest is affected by the knock-out. Is this really the case? In a previous study, we have generated knock-out (KO) clones of TgRH88_077450 (SRS29B; SAG1) which differed in the numbers of integrated dihydrofolate-reductase-thymidylate-synthase (MDHFR-TS) drug-selectable marker. Clones 18 and 33 had a single insertion of MDHFR-TS within SRS29B. Clone 6 was disrupted by the insertion of a short unrelated DNA-sequence, but the marker was integrated elsewhere. In clone 30, the marker was inserted into SRS29B and several other MDHFR-TS copies were found in the genome. KO and wild-type (WT) tachyzoites had similar shape, dimensions and vitality. This prompted us to investigate the impact of the genetic engineering as such on the overall proteome patterns of the four clones as compared to the respective WT. Comparative shotgun proteomics of the five strains was performed. Overall, 3236 proteins were identified. Principal component analysis of the proteomes revealed five distinct clusters corresponding to the five strains by both iTop3 and iLFQ algorithms. Detailed analysis of the differentially expressed proteins revealed that the target of the KO, srs29B, was lacking in all KO clones. Besides this protein, twenty other proteins were differentially expressed between KO clones and WT or between different KO clones. The protein exhibiting the highest variation between the five strains was srs36D encoded by TgRH_016110. The deregulated expression of SRS36D was further validated by quantitative PCR. Moreover, the transcript levels of three other selected SRS genes, namely SRS36B, SRS46, and SRS57 exhibited significant differences between individual strains. These results indicate that knocking out a given gene may affect the expression of other genes. Therefore, care must be taken when specific phenotypes are regarded as a direct consequence of the KO of a given gene.

Parathyroid-hormone-related protein (PTHrP) is encoded by PTHLH gene which, by alternative promoter usage and splicing mechanisms, can give rise to at least three isoforms of 139, 141 and 173 amino acids with distinct C-terminals. PTHrP is subjected to different post-translational processing that generates smaller bioactive forms, comprising amino terminus, midregion (containing a nuclear/nucleolar targeting signal) and carboxy terminus peptides. Both the full-length protein and the discrete peptides are key controllers of viability, proliferation, differentiation and apoptosis in diverse normal and pathological biological systems via the reprogramming of gene expression and remodulation of PKA or PKC-mediated signalization mechanisms. The aim of this review is to pick up selected studies on PTHrP-associated signatures as revealed by molecular profiling assays, focusing on the available data about exemplary differentiating, differentiated or non-tumoral cell and tissue models. In particular, the data presented relate to adipose, bone, dental, cartilaginous and skin tissues, and also intestinal, renal, hepatic, pulmonary and pancreatic epithelia, with a focus on hepatic fibrosis-, pancreatitis- and diabetes-related changes as diseased states. Whether reported, the biochemical and/or physiological aspects associated with the specific molecular modulation of gene expression and signal transduction pathways in the target model systems under examination will be also briefly commented.

Our understanding of the diversity of life on our planet and the possibility of finding or sustaining life elsewhere in the universe plays a central role in supporting human space settling and exploration. Astrobiology and its outcomes require a multidisciplinary and comprehensive approach, in which the microbial, geological, chemical, astronomical, and physical domains of research are interlinked. An example of the applications of astrobiology and space microbiology is the use of extremophiles for in-situ resource utilization through biomining and bioleaching. To better understand the multidisciplinary research landscape in this area, we have quantitatively reviewed the global scientific literature on astrobiology with a focus on biomining and bioleaching through bibliometric network analysis, investigating patterns and trends in its development over time. The network analysis of the keywords co-occurrence highlights different connecting and overlapping clusters, illustrating the multidisciplinary character of astrobiology. Temporal analyses show a recent focus on topics related to microbiology and geomicrobiology, emphasizing the role that these fields will play in future astrobiology research. In conclusion, astrobiology, biomining, and bioleaching research are timely responding to the identification of these techniques as tools for biotechnological applications, expected to play a crucial role in long-term human space exploration.

Non-standard Lagrangians do not display any discernible energy-like terms, yet they give the same equations of motion as standard Lagrangians, which have easily identifiable energy-like terms. A new method to derive non-standard Lagrangians for second-order nonlinear differential equations with damping is developed and the limitations of this method are explored. It is shown that the limitations do not exist only for those nonlinear dynamical systems that can be converted into linear ones. The obtained results are applied to selected population dynamics models for which non-standard Lagrangians and their corresponding null Lagrangians and gauge functions are derived, and their roles in the population dynamics are discussed.

Angiotensin II (Ang II) plays a role in several inflammatory diseases and is capable of inducing the release of inflammatory mediators in several cell types. The objective was to investigate the potential of Ang II to induce mRNA expression of inflammatory mediators by cultured primary human periodontal cells. A synergistic effect of a co-treatment with Ang II and IL1β on mRNA expression of inflammatory mediators was also explored. Primary cultures of human fibroblast-like cells isolated from gingival and periodontal ligament tissues from 3 subjects were established using explant techniques. Immunophenotyping of STRO-1, AT1 and AT2 receptors was performed by flow cytometry analysis. Cell cultures were challenged with Ang II (1M) for 3, 6 and 24h with or without a co-treatment with IL1β (0.1ng/mL) for 24h. mRNA expression of inflammatory mediators was performed by real time quantitative polymerase chain reaction (RT-qPCR). We present, for the first time, a precise quantification for AT1 and AT2 receptors on human gingival and periodontal fibroblast-like cell types; the percentage of positive immunostaining compared to the total population of cells varied from 3.35% through 5.29% for AT1 and 2.97% through 4.57% for AT2. Ang II slightly upregulated mRNA expression of IL6 and CCL2/MCP1 in gingival cells and IL8 and PTGS2/COX2 in periodontal ligament cells. IL1β induced upregulation of IL8, IL6 CCL2/MCP1, PTGS2/COX2 and IL1β mRNA in both cell types. Co-treatment with Ang II and IL1β did not show a synergistic effect under these experimental conditions. Ang II shows a low potential to induce mRNA upregulation of inflammatory mediators in cultured primary human gingival and periodontal ligament cells, most likely due to the low percentage of Ang II receptors in such cells, and no synergistic effect with the co-treatment with IL1β.

Spodoptera frugiperda is a new invasive and highly polyphagous pest that attacks corn in Indonesia. The availability of abundant plant species allows pests to switch to other host plants to maintain their population. This research aims to examine the development, reproduction, nutritional indices, and life table of S. frugiperda in several plant species. The plants tested were corn, rice, broccoli, oil palm, and baby corn as controls. Ten individual insects were used and repeated five times for each plant species. The test results show that different types of plant feed affect the development time, imago life span, fecundity, and fertility of S. frugiperda. The types of plant feed, that were baby corn fruit and broccoli had higher net reproduction value (R0), intrinsic growth rate (r), gross reproduction rate (GRR), shorter mean generation period (T), and population doubling time (DT) than in corn and rice leaves. On oil palm leaf feed no population parameters can be determined because no larvae developed into adults and had the lowest nutritional indices parameters, so that could not be exploited as a host plant. Also, the nutritional indices of several feed plant species tested provided information that broccoli could be a suitable host when there was no corn in the field.

Biocontainment techniques for genetically modified yeasts (GMYs) are pivotal due to the importance of these organisms for biotechnological processes and also due to the design of new yeast strains by using synthetic biology tools and technologies. Due to the large genetic modifications that many yeast strains display, it is highly desirable to avoid the leakage of GMY cells into natural environments and, consequently, the spread of synthetic genes and circuits by horizontal or vertical gene transfer mechanisms within the microorganisms. Moreover, it is also desirable to avoid that patented yeast gene technologies spread outside the production facility. In this review, it was evaluated the different biocontainment technologies currently available for GMYs. Interestingly, uniplex-type biocontainment approaches (UTBAs), which relies on nutrient auxotrophies induced by gene mutation or deletion, or the expression of simple kill switches apparatus, are still the major biocontainment approaches still in use with GMY. While bacteria like Escherichia coli account for advanced biocontainment technologies based on synthetic biology and multiplex-type biocontainment approaches (MTBAs), GMYs are distant from this scenario due to many reasons. Thus, a comparison of different UTBAs and MTBAs applied for GMY and genetically engineered microorganisms (GEMs) was made, indicating the major advances of biocontainment techniques for GMYs.

Dynamic variables in the non-equilibrium systems of life are determined by catalytic activities. These relate to the expression of the genome. The extent to which such a variable depends on the catalytic activity defined by a gene has become more and more important in view of the possibilities to modulate gene expression or intervene with enzyme function through the use of medicinal drugs. With all the complexity of cellular systems biology, there are still some very simple principles that guide the control of variables such as fluxes, concentrations, and half-times. Using time-unit invariance we here derive a multitude of laws governing the sums of the control coefficients that quantify the control of multiple variables by all the catalytic activities. We show that the sum of the control coefficients of any dynamic variable over all catalytic activities is determined by the control of the same property by time. When the variable is at a maximum, minimum or steady, this limits the sums to simple integers like 0, -1, 1, and -2, depending on the variable under consideration. Some of the implications for biological control are discussed as is the dependence of these results on the precise definition of control.

Kinetic modeling is an essential tool in systems biology research, enabling the quantitative analysis of biological systems and predicting their behavior. However, the development of kinetic models is a complex and time-consuming process. In this article, we propose a novel approach called KinModGPT, which generates kinetic models directly from natural language text. KinModGPT employs GPT-3 as a natural language interpreter and Tellurium as an SBML generator. We demonstrate the effectiveness of KinModGPT in creating SBML models from complex natural language descriptions of biochemical reactions. KinModGPT successfully generates valid SBML models from a range of natural language model descriptions of metabolic pathways, protein-protein interaction networks, and heat shock response. This article demonstrates the potential of KinModGPT in kinetic modeling automation.

Dysfunction of the WW domain-containing adaptor with coiled-coil, WAC, gene underlies a rare autosomal dominant disorder, DeSanto-Shinawi syndrome (DESSH). DESSH is associated with facial dysmorphia, hypotonia, and cognitive alterations, including attention deficit hyperactivity disorder and autism. How the WAC protein localizes and functions in neural cells is critical to understanding its role during development. To understand the genotype-phenotype role of WAC, we developed a knowledgebase of WAC expression, evolution, human genomics, and structural/motif analysis combined with human protein domain deletions to assess how conserved domains guide cellular distribution. Then assessed in a cell type implicated in DESSH, cortical GABAergic neurons. WAC contains conserved charged amino acids, phosphorylation signals, and enriched nuclear motifs, suggesting a role in cellular signaling and gene transcription. Human DESSH variants are found within these regions. We also discovered and tested a nuclear localaization domain that impacts the cellular distribution of the protein. These data provide new insights into the potential roles of this critical developmental gene, establishing a platform to assess further translational studies, including the screening of missense genetic variants in WAC. Moreover, these studies are essential for understanding the role of human WAC variants in more diverse neurological phenotypes, including autism spectrum disorder.

Transmembrane protein 100 (TMEM100) plays an important role in angiogenesis, vascular morphogenesis, integrity and cardiovascular development. TMEM100 is a downstream target of the BMP9/10 and BMPR2/ALK1 signaling pathways. Our recent study demonstrates TMEM100 is a lung endothelium enriched gene. Endothelial-specific deletion of Tmem100 impairs lung endothelial cells regeneration. Activation of Tmem100 signaling represents a novel strategy for lung vascular repair and regeneration. It is interesting and important to understand the roles of TMEM100 in the physiological and pathological conditions. In this review, we summarized the current knowledge of TMEM100.

The number and size of computational models in biology have drastically increased over the past years and continue to grow. Modeled networks are becoming more complex, and reconstructing them from the beginning in an exchangeable and reproducible manner is challenging. Using precisely defined ontologies enables the encoding of field-specific knowledge and the association of disparate data types. In computational modeling, the medium for representing domain knowledge is the set of orthogonal structured controlled vocabularies named Systems Biology Ontology ( SBO). The SBO terms enable modelers to explicitly define and unambiguously describe model entities, including their roles and characteristics. Here, we present the first standalone tool that automatically assigns SBO terms to multiple entities of a given SBML model, named the SBOannotator. The main focus lies on the reactions, as the correct assignment of precise SBO annotations requires their extensive classification. Our implementation does not consider only top-level terms but examines the functionality of the underlying enzymes to allocate precise and highly specific ontology terms to biochemical reactions. Transport reactions are examined separately and are classified based on the mechanism of molecule transport. Pseudo-reactions that serve modeling purposes are given reasonable terms to distinguish between biomass production and the import or export of metabolites. Finally, other model entities, such as metabolites and genes, are annotated with appropriate terms. Including SBO annotations in the models will enhance the reproducibility, usability, and analysis of biochemical networks. Availability: The open-source project SBOannotator is freely available under the terms of LGPL version 3.0 from https://github.com/draeger-lab/SBOannotator/.

In this paper we propose a computational framework that merges mechanistic modeling with deep neural networks obeying the Systems Biology Markup Language (SBML) standard. Over the last 20 years, the systems biology community has developed a large number of mechanistic models in SBML that are currently stored in public databases. With the proposed framework, existing SBML mechanistic models may be upgraded to hybrid systems through the incorporation of deep neural networks into the model core, using a freely available python tool. The so-formed hybrid mechanistic/neural network models are trained with a deep learning algorithm based on the adaptive moment estimation method (ADAM), stochastic regularization and semidirect sensitivity equations. The trained hybrid models are encoded in SBML and stored back in model databases, where they can be further analyzed as regular SBML models. The application of this approach is illustrated with three well-known case studies: the threonine synthesis model in Escherichia coli, the P58IPK signal transduction model, and the Yeast glycolytic oscillations model. The proposed framework is expected to greatly facilitate the widespread use of hybrid modeling techniques for systems biology applications.

Milk is a complex liquid, and the concentrations of many of its components are under genetic control. Many genes and pathways are known to regulate milk compositon, and the purpose of this review is to highlight how the discoveries of quantitative trait loci (QTL) for milk phenotypes can elucidate these pathways. The main body of this review focusses primarily on QTL discovered in cattle (Bos taurus) as a model species for lactation biology, with occasional references to other ruminant species, and some comparisons with human milk composition are also presented. The following section describes a range of techniques that can be used to help identify the causative genes underlying QTL when the underlying mechanism involves the regulation of gene expression. As genotype and phenotype data bases continue to grow and diversify, new QTL will continue to be discovered, and, although proving the causality of underlying genes and variants remains difficult, these new data sets will further enhance our understanding of lactation biology.

Candida boidinii NAD+-dependent formate dehydrogenase (CbFDH) has gained significant attention for its potential applications in the production of biofuels and various industrial chemicals from inorganic carbon dioxide. In this study, we present an atomic X-ray crystal structure of the apo CbFDH to 1.4 Å resolution determined at cryogenic temperature at the Turkish Light Source, “Turkish DeLight”. This structure offers a comprehensive view of the apo enzyme's dynamics, filling the gaps in our understanding from previous studies. Also, comparison of our high-resolution apo and previously available holo enzyme structures reveals major conformational changes of this dynamic enzyme in the absence and presence of the coenzyme and substrate/inhibitor complexes. Collectively all these information may provide invaluable insights into future protein engineering efforts that could enhance enzymatic activity and stability, potentially increasing its efficiency and effectiveness of CbFDH in industrial processes.

As a conceptual model of disease mechanisms, a disease map integrates available knowledge and is applied for data interpretation, predictions and hypothesis generation. It is possible to model disease mechanisms on different levels of granularity and adjust the approach to the goals of a particular project. This rich environment together with requirements for high-quality network reconstruction makes it challenging for new curators and groups to be quickly introduced to the development methods. In this review, we offer a step-by-step guide for developing a disease map within its mainstream pipeline that involves using the CellDesigner tool for creating and editing diagrams and the MINERVA Platform for online visualisation and exploration. We also describe how the Neo4j graph database environment can be used for managing and querying efficiently such a resource. For assessing the interoperability and reproducibility we apply FAIR principles.

Apicomplexan infections, such as giardiasis and cryptosporidiosis, negatively impact a considerable proportion of human and commercial livestock populations. Despite this, the molecular mecha-nisms of disease, particularly the effect on the body beyond the gastrointestinal tract, are still poorly understood. To highlight host-parasite-microbiome biochemical interactions, we utilised integrated metabolomics-16S rRNA genomics and metabolomics-proteomics approaches in a C57BL/6J mouse model of giardiasis and compared these to Cryptosporidium and uropathogenic Escherichia coli (UPEC) infections. Comprehensive samples (faeces, blood, liver, and luminal contents from duo-denum, jejunum, ileum, caecum and colon) were collected 10 days post infection and subjected to proteome and metabolome analysis by liquid and gas chromatographic mass-spectrometry, re-spectively. Microbial populations in faeces and luminal washes were examined using 16S rRNA metagenomics. Proteome-metabolome analyses indicated that 12 and 16 key pathways were sig-nificantly altered in the gut and liver, respectively, during giardiasis with respect to other infections. Energy pathways including glycolysis and supporting pathways of glyoxylate and dicarboxylate metabolism, and redox pathway of glutathione metabolism, were upregulated in small intestinal luminal contents and the liver during giardiasis. Metabolomics-16S rRNA genetics integration in-dicated that populations of three bacterial families –Autopobiaceae (Up), Desulfovibrionaceae (Up) and Akkermanasiaceae (Down) – were most significantly affected across the gut during giardiasis, causing upregulated glycolysis and short-chained fatty acid (SCFA) metabolism. In particular, the perturbed Akkermanasiaceae population seemed to cause oxidative stress responses along the gut-liver axis. Overall, the systems biology approach applied in this study highlighted that the effects of host-parasite-microbiome biochemical interactions extended beyond the gut ecosystem to the gut-liver axis. These findings form the first steps in a comprehensive comparison to ascertain the major molecular and biochemical contributors of host-parasite interactions and contribute towards the development of biomarker discovery and precision health solutions for apicomplexan infections.

The Golgi apparatus (GA) dysfunctions in Parkinson’s Disease (PD), neurodevelopmental disorders (NDDs), cancer, and organelle structural biology (OSB) can provide insights into therapeutic targets, gene therapy, and drug design. Primary defects and fragmentation within the GA are implicated in a wide range of neurodegenerative diseases. GA defects typically result in mislocation of proteins, accumulation of undegraded proteins, and impaired glycosylation of proteins. Inhibition of vesicular trafficking by α-synuclein (aSyn) may affect the dopamine-producing neurons and neuromodulators. GA regulates apoptosis during pathological mechanisms of neurological diseases and could provide new avenues in treatments through translation research. PD patients bearing the hereditary E46K disease mutation manifest the clinical picture of parkinsonism. How do we provide high resolution nanoimages of the GA during disease to capture dysfunction? Could we visualize the aSyn traffic jam between vesicles in the organelles ER and GA? OSB is emerging as a field as more technology advances and is more accessible. Structural studies of the GA will advance the field of neurological disease forward with an in depth understanding of dysfunction, fragmentation, and defects. Discoveries of the GA in PD, NDDs, and cancer would break new ground and provide translational medicine data of these diseases. Future research could be visualizing high angle annular dark field-STEM (HAADF-STEM) tomograms, cryogenic electron tomography (cryo-ET), multiplex correlative light and electron microscopy (cryo-CLEM), nanobody-assisted tissue immunostaining for volumetric EM (NATIVE) and using soft X-ray tomography (SXT) and computational reconstruction of the GA.

The endothelium is a monolayer of cells lining the inner blood vessels. Endothelial cells (ECs) play indispensable roles in angiogenesis, homeostasis, and immune response under normal physiological conditions, and their dysfunction is closely associated with pathologies such as cardiovascular diseases. Abnormal EC metabolism, especially fatty acid (FA) dysfunctional metabolism, contributes to the development of many diseases including pulmonary hypertension (PH). In this review, we focus on discussing the latest advances in FA metabolism in ECs under normal and pathological conditions with an emphasis on PH. We also highlight areas of research that warrant further investigation.

During the past few years unexpected developments have driven studies in the field of clinical immunology. One driver of immense impact was the outbreak of a pandemic caused by the novel virus SARS-CoV-2. Excellent recent reviews address diverse aspects of immunological re-search into cardiovascular diseases. Here, we specifically focus on selected studies taking ad-vantage of advanced state-of-the-art molecular genetic methods ranging from genome-wide epi/transcriptome mapping and variant scanning to optogenetics and chemogenetics. First, we discuss emerging clinical relevance of advanced diagnostics for cardiovascular diseases - includ-ing those associated with COVID-19 - with a focus on the role of inflammation in cardiomyopa-thies and arrhythmias. Second, we consider newly identified immunological interactions at or-gan and systems level which affect cardiovascular pathogenesis. Thus, studies into immune in-fluences arising from the intestinal system are moving towards therapeutic exploitation. Fur-ther, powerful new research tools have enabled novel insight into brain – immune system inter-actions at unprecedented resolution. This latter line of investigation emphasizes the strength of influence of emotional stress - acting through defined brain regions - upon viral and cardiovas-cular disorders. Several challenges need to be overcome before the full impact of these far-reaching new findings will hit the clinical arena.

: Cancer metastasis is the lethal developmental step in cancer, responsible for the majority of cancer deaths. To metastasize, cancer cells must acquire the ability to disseminate systemically and to escape an activated immune response. Here, we endeavoured to investigate if metastatic dissemination reflects acquisition of genomic traits that are selected for. We acquired mutation and copy number data from 8,332 tumours representing 19 cancer types acquired from The Cancer Genome Atlas and the Hartwig Medical Foundation. A total of 827,344 non-synonymous mutations across 8,332 tumour samples representing 19 cancer types were timed as early or late relative to copy number alterations, and potential driver events were annotated. We found that metastatic cancers had significantly higher proportion of clonal mutations and a general enrichment of early mutations in p53 and RTK/KRAS pathways. However, while individual pathways demonstrated a clear time-separated preference for specific events, the relative timing did not vary between primary and metastatic cancers. These results indicate that the selective pressure that drives cancer development does not change dramatically between primary and metastatic cancer on a genomic level, and is mainly focused on alterations that increase proliferation.

During the last 50 years, an interdisciplinary approach in research in various scientific fields has become widely spread. This process significantly deepens and widens our scientific knowledge, but on the other hand makes more difficult choosing a discipline to be used by students and young researchers. The dynamic development of science makes this choice even harder. There is a widely spread opinion that thermodynamics uses a rigorous mathematical apparatus. This paper describes that knowledge of the fundamental principles of thermodynamics is required for deep understanding of crucial biological processes. Thus the effort put into learning classical and nonequilibrium thermodynamics does not make harder, but easier gaining a better knowledge of biological processes. This essay is an attempt to convey personal experience in using thermodynamics to describe biological systems and processes they perform.

Drones equipped with thermal cameras have recently become readily available, broadening the possibilities for monitoring wildlife. The European hare (Lepus europaeus) is a nocturnal mammal that is closely monitored in Denmark due to populations declining since the mid-1900s. The limitations of current population assessment methods, such as spotlight counts and hunting game statistics, could be overcome by relying on drone surveys with thermal imaging for population counts. The aim of this study was to investigate the use of a DJI Mavic 2 Enterprise Advanced drone with thermal imaging as a tool for monitoring the Danish hare population. Multiple test flights were conducted over agricultural areas in Denmark in spring 2022, testing various flight altitudes, camera settings, and recording methods. The test flights were used to suggest a method for identifying and counting hare. The applied use of this methodology was then evaluated through a case survey that had the aim of identifying and counting hare over an agricultural area of 242 ha. Hare could be detected with thermal imaging at flight altitudes up to 80 m and it was possible to fly as low as 40 m without observing direct behavior changes. Thermal images taken at these altitudes also provided enough detail to differentiate between species and animal body size proved to be a good species indicator. The case study confirmed the use of thermal imaging based drone surveys to identify hare and conduct population counts, thus, indicating the suggested methodology as a viable alternative to traditional counting methods.