Climate change is likely to have a complex effect on the growth of plants, their phenology, plant-pollinator interactions, and reproductive success. Therefore, we tested the impact of three key factors (temperature, water, and nitrogen supply) on traits, pollination, and seed production in Sinapis alba (Brassicaceae). We grew the plants in different combinations of temperature, water, and nitrogen supplementation, measured multiple vegetative and floral traits, and assessed the response of pollinators in the field. We also evaluated the effect of growing conditions on seed set in plants exposed to pollinators and hand-pollinated plants. Our results show that water stress impaired vegetative growth, decreased flower production, reduced visitation by pollinators and seed set, while nitrogen availability played an important role in nectar production. Temperature modulated the effect of water and nitrogen availability on vegetative and floral traits and strongly affected flowering phenology and flower production. We demonstrated that changes in temperature, water, and nitrogen availability induce changes in plant vegetative and floral traits which impact flower visitation and consequently plant reproduction. Climate change, particularly increasing temperature combined with reduced precipitation, thus may impact plant-pollinator interactions with negative consequences for the reproduction of wild plants and insect-pollinated crops.

FeIFeI Fe2(S2C3H6)(CO)6(µ-CO) (1a-CO) and its FeIFeII cationic species (2a+-CO) are the simplest model of the CO-inhibited [FeFe] hydrogenase active site, which is known to undergo CO photolysis within a temperature- dependent process whose products and mechanism are still a matter of debate. Using Density Functional Theory (DFT) and Time-Dependent Density Functional Theory (TDDFT) computations, the ground state and low-lying excited state potential energy surfaces (PESs) of 1a-CO and 2a+-CO have been explored aimed at elucidating the dynamics of the CO photolysis yielding Fe2(S2C3H6)(CO)6 (1a) and Fe2(S2C3H6)(CO)6+ (2a+), two simple models of the catalytic site of the enzyme. Two main results came out from these investigations. First, a-CO and 2a+-CO are both bound with respect to any CO dissociation with lowest free energy barriers around 10 kcal mol-1, suggesting that at least 2a+-CO might be synthetized. Second, focusing on the cationic form, we found at least two clear excited state channels along the PESs of 2a+-CO that are unbound with respect to equatorial CO dissociation.

Polychlorinated phenoxathiins (PCPTs), polychlorinated dibenzothiophenes (PCDTs), and polychlorinated thianthrenes (PCTAs) are sulfur analogues of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/DFs). Chlorothiophenols(CTPs) and chlorophenols (CPs) are key precursors to form PCTA/PT/DTs, which can form chloro(thio)phenoxy radical, sulfydryl/hydryl-substituted phenyl radical and (thio)phenoxyl diradicals. The available radical/radical PCTA/DT formation mechanism failed to explain the higher concentration of PCDTs than that of PCTAs under the pyrolysis or combustion conditions. Thus in this work, a detailed thermodynamics and kinetic calculations were carried out to investigate the pre-intermediates formation for PCTA/PT/DTs from radial/molecule coupling of 2-C(T)P with their key radical species. Our study found that the radial/molecule mechanism can thermodynamically and kinetically contribute to the gas-phase formation of PCTA/PT/DT/s. The S/C coupling modes to form thioether-(thio)enol intermediats are preferable over the O/C coupling modes to form ether-(thio)enol intermediats. Thus, although the radial/molecule coupling of chlorophenoxy radical with 2-C(T)P have no effect on the PCDD/PTs formation, the radial/molecule coupling of chlorothiophenoxy radical with 2-C(T)P play an important role in the PCDT/PT formation. Most importantly, the pre-PCDT intermediates formation pathways from the coupling of sulfydryl/hydryl-substituted phenyl radical with 2-C(T)P and the coupling of (thio)phenoxyl diradicals with 2-C(T)P are more favorable to pre-PCTA/PT intermediates formation pathways from the coupling of chlorothiophenoxy radical with 2-C(T)P, which can give reasonable explanation for the high PCDT-to-PCTA ratio in the environment.

Hydrological connectivity plays a major role in solving water resource and eco-environmental problems. However, this phenomenon has not been afforded the attention it deserves. Detailed analysis of connectivity in river systems could provide considerable insight into structural and functional attributes of riverine landscapes. The current study used graph theory approach and associated connectivity indicators to explore the characteristics and evolution of river systems and hydrological connectivity in a large catchment (Poyang Lake, China). The results revealed that the structure of the river system tended to be complex during 1990-2020, characterized by a dynamic evolution of tributaries in certain northern areas. Both river density and complexity exhibited an increasing trend by up to 15%, with the change rate after 2000 approximately twice as high as that of the preceding period. Overall, human activities across the catchment are more likely to play a key role in leading to significant changes in the quantity, morphometric, and structure characteristics of the river system. Additionally, the functional connectivity analysis indicated that the index of connectivity (IC) in the downstream catchment is stronger than that of the upstream vegetation areas, suggesting a strong contribution to the runoff-sediment transport (r=0.6-0.7). This study highlights the spatial and temporal evolution of both the structural and functional connectivity in the large Poyang Lake catchment. The findings of this work will bene-fit future water resource management and applications by providing a strategy for protecting the surface hydrology and mass transport of large river basins under climate and land-use changes.

Network neuroscience delves into comprehending the intricate arrangement and interactions within the neural networks of the brain. By merging insights from both neuroscience and network theory, it investigates the brain's structure and function through the lens of interconnected nodes (symbolizing brain regions) and edges (symbolizing the connections among these regions) forming a dynamic network. Graph metrics play a pivotal role in neuroscience by providing quantifiable insights into the intricate connectivity patterns within the brain's neural networks. Frequently, nodes are extracted from functional or structural atlases, which can lead to diverse shapes and sizes. Nevertheless, our understanding of how these differing node characteristics and definitions impact the computed graph metrics in neuroimaging data remains limited. This study adopts a data-driven methodology to delineate functional nodes, subsequently examining the influence of their sizes on resultant graph metrics. By employing the Neuromark framework, an entirely automated independent component analysis (ICA) is applied to resting state fMRI data. Through this, functional network connectivity (FNC) matrices are computed—capturing Pearson correlations between component-time courses—while employing a proportional threshold to streamline node connections based on these correlations. Subsequently, various global and local graph metrics are computed, offering insights into network characteristics. Global metrics provide an overarching summary of the network structure, while local measures delve into structural intricacies at the individual component level. Node sizes are computed based on voxel counts surpassing a designated threshold. Next, we calculated the Pearson correlation between the obtained node sizes and the graph metrics, which we term 'node-metric coupling' (NMC). Our findings revealed consistent and noteworthy correlations between the values of graph metrics and the dimensions of brain nodes. To delve deeper into the implications of this correlation, we examined the node-metric coupling within a dataset comprising Alzheimer's disease, mild cognitive impairment, and control subjects. The disparities observed in node-metric coupling among these groups underscore the necessity of accounting for this factor during analysis. The two principal outcomes of this study are as follows: Firstly, the substantial interplay between varying node sizes within a given atlas and the resultant graph metrics; and secondly, the potential utility of node-metric coupling as a viable biomarker for brain disorders. These discoveries hold significant ramifications. While comparing studies employing diverse atlases is already a challenge, our work highlights an additional, critical source of variability: accounting for node sizes. Consequently, the association between intra-atlas node size and graph metric should be thoughtfully acknowledged in future neuroimaging investigations.

Nutraceuticals comprise dietary supplements, functional foods, medicinal foods, and pharmaceuticals. However, to date all these concepts are interpreted in different ways with the rapid increasing knowledge on nutrition, medicine, and plant biotechnology changing the concepts about food, health and agriculture. What matters are the bioactive elements conveyed by foodstuffs as nutrients or non-nutrients, which interfere with human metabolism and have impact on health, aging and well-being. Food, not nutrients, is the fundamental unit in nutrition and edible mushrooms, are fungi that supply unique biological compounds, different from plant or animal origin, which significantly impact on health status. Their influence on medicinal interventions has been known and studied for many years. The role on neurodegenerative disorders has been recently investigated and their significance on many other diseases has been well demonstrated. On this note it is synthesized the more recent knowledge of some edible mushrooms and preparations on Ménière’s disease, a lifelong condition it can develop at any age, but most commonly appearing between 40 and 60 years of age.

The aim of the presents study is to further expand the model of translational cross-validation by investigating the brain circuits or networks which underpin the same tasks by means of group independent component analysis for FMRI toolbox (GIFT). We hypothesized that there will be neural network patterns of activation and deactivation, which correspond to real time performance on clinical self-evaluation scales. We recruited 42 subjects: 20 healthy controls and 22 patients with major depressive episode. All subjects underwent functional MRI scanning using paradigm comprised of diagnostic clinical self-assessment depression scale contrasted to neutral scale. The data were processed with group independent component analysis for functional MRI toolbox and statistical parametric mapping. The results have demonstrated that there exist positively or negatively modulated brain networks during processing of diagnostic specific task questions for major depressive disorder. There have also been confirmed differences in the networks processing diagnostic versus off blocks between patients and controls in anterior cingulate cortex and middle frontal gyrus. Diagnostic conditions (depression scale) when contrasted to neutral conditions demonstrate differential activity of right superior frontal gyrus and right middle cingulate cortex in the comparison of patients with healthy controls. It is for the first time when potential neuroimaging state dependent biomarker has been directly linked with clinical assessment self-evaluation scale, administered as stimuli simultaneously with the fMRI acquisition. It may be regarded as further evidence in support of the ability of both methods to concordantly distinguish groups by means of incremental translational cross-validation.

Many insights into human disease have been built on experimental results in Drosophila, and research in fruit flies is often justified on the basis of its predictive value for questions related to human health. Additionally, there is now a growing recognition of the value of Drosophila for the study of rare human genetic diseases, either as a means of validating the causative nature of a candidate genetic variant found in patients, or as a means of obtaining functional information about a novel disease-linked gene when there is little known about it. For these reasons, funders in the US, Europe, and Canada have launched targeted programs to link human geneticists working on discovering new rare disease loci with researchers who work on the counterpart genes in Drosophila and other model organisms. Several of these initiatives are described here, as are a number of output publications that validate this new approach.

High-Intensity Functional Training (HIFT) is a novel exercise intervention that may test body systems in a balanced and integrated fashion by challenging individuals’ abilities to complete mechanical work. However, research has not previously determined if physical work capacity is unique to traditional physiologic measures of fitness. Twenty-five healthy men and women completed a six-week HIFT intervention with physical work capacity and various physiologic measures of fitness assessed pre- and post-intervention. At baseline, these physiologic measures of fitness (e.g., aerobic capacity) were significantly associated with physical work capacity and this relationship was even stronger at post-intervention assessment. Further, there were significant improvements across these physiologic measures in response to the delivered intervention. However, the change in these physiologic measures failed to predict the change in physical work capacity induced via HIFT. These findings point to the potential utility of HIFT as a unique challenge to individuals’ physiology beyond traditional resistance or aerobic training. Elucidating the translational impact of increasing work capacity via HIFT may be of great interest to health and fitness practitioners ranging from strength/conditioning coaches to physical therapists.

1) Background: Patients with neurological disorders are particularly at risk of falling and requiret functional rehabilitation. HUBER® is a motorised rotating platform that allows simultaneous work on balance, stability and strength with continuous adaptation and immediate feedback. This study aimed to measure the impact of rehabilitation with the HUBER® on the physical performance and quality of life of patients with neurological diseases requiring functional rehabilitation. 2) Methods: 32 subjects were enrolled in CHU Liège CNRF and randomly divided into 2 groups. The first group received classical rehabilitation combined with two training sessions per week on the HUBER® for 8 weeks. The second group received their usual treatment. This randomized control trial has been registered on clinicaltrials.gov under the number NCT04687293. Physical performance and quality of life were evaluated at different time. 3) Results: There was no significant difference between the 2 groups after enrolment. In terms of physical performance, an improvement in SPPB chair stand test (p=0.021) and total SPPB (p=0.003) was observed in the HUBER® group. In terms of quality of life, a higher improvement was observed overall in the HUBER® group (p<0.05 between groups). 4) Conclusion: The HUBER® showed promising results in functional rehabilitation of patients with neurological pathologies, as a complement to classical rehabilitation management by physiotherapy.

Functional ankle instability (FAI) results from multiple ankle sprains, causing a perceived sense of joint instability due to muscle and ligament imbalances. Neuromuscular training (NMT) is employed to enhance ankle stability in individuals with FAI. The study included 24 male university students with FAI, who underwent ankle NMT on three surfaces. OpenSim musculoskeletal model analyzed the effects on ankle muscle activity, kinetics, and kinematics. Utilizing repeated measures analysis of variance (ANOVA) and one-dimensional statistical non-parametric mapping (SNPM1d) to identify distinctions between training surfaces. NMT on foam cushion (FC) significantly enhanced tibialis anterior (TA) and gastrocnemius medial (GM) activation during walking compared to level-ground (LG) and artificial turf (AT) (p<0.05). However, no differences observed for peroneus longus (PL), gastrocnemius lateral (GL), and peak ankle plantarflexion (PF). During jogging and fast running, post FC training increased TA, PL, GM, GL activation, and peak ankle PF moment (p<0.05). Additionally, post FC training, subtalar mobility was significantly reduced (p<0.05), and ankle joints exhibited greater dorsiflexion (DF) angles during jogging and fast running (p<0.05). Consequently, selecting FC for short-term ankle NMT proves more advantageous in enhancing ankle stability among individuals with FAI, yielding a more positive impact on FAI improvement.

In this work, we treat a prediction problem via the conditional hazard function of a scalar response variable Y given a functional random variable X by using the local linear technique. The main purpose of this paper is to investigate the asymptotic normality of the nonparametric estimator of the conditional hazard function, under some general conditions. A simulation study, conducted to assess finite sample behavior, demonstrates the superiority of our method than the standard kernel method

Obesity represents a worldwide epidemic disorder, increasing the overall morbidity and mortality rate. In this study we investigated the impact of obesity on peri-operative and long-term functional outcomes of Robotic assisted simple prostatectomy (RASP). Baseline flowmetry parameters and validated questionnaires’ scores were prospectively recorded. Follow-up assessments included Flowmetry and validated questionnaires. Composite outcomes (Trifecta) was defined as combination of: post-operative Q-max>15 ml/sec, IPSS score<8 and absence of complications. Pentafecta included also post-operative ejaculation persistence (MSHQ score>0) and the Erectile function maintenance (∆IEEF<6). Data were stratified by BMI (<30 or ≥30). 81 patients underwent RASP in our Institution. Baseline demographics and clinical features, questionnaires score and baseline flowmetry results were comparable between obese and non-obese cohorts. At follow-up, obese patients reported lower subjective improvement in IPSS (p=0.02) and OABQ scores (p<0.001) and higher incidence of stress incontinence requiring Duloxetin (p<0.001). Flowmetry outcomes, were also worse in this cohort (p=0.02 and p=0.03, respectively). At comprehensive outcomes assessment, obese patients had comparable Trifecta (67% vs 54%, p=0.39) and pentafecta achievement rate (p=0.76). Our prelimirary results proved that obesity is associated with worse functional outcomes (storage LUTS and incontinence rate) after RASP, but doesn’t affect trifecta and pentafecta achievement rate.

Background: Modern computational solutions enabling evaluation of the global neuronal network arrangement seem to be particularly valuable for research on neuronal disconnection in schizophrenia. However, a vast number of algorithms used in these analyzes may be an uncontrolled source of results inconsistency. Objective: Our study aimed to verify whether the comparison of schizophrenia patients with healthy controls, in terms of indexes describing the organization of the neural network, will give analogous results when these parameters are calculated using two different functional connectivity measures. Methods: Resting-state EEG recordings from schizophrenia patients and healthy controls were collected. Based on these data, Minimum Spanning Tree (MST) graphs were computed two times using two different functional connectivity measures (phase lag index, PLI, and phase locking value, PLV). Results: Two series of be-tween-group comparisons regarding MST parameters calculated based on PLI or PLV gave contradictory results, in many cases the values of a given MST index based on PLI were higher in patients, and the results based on PLV were lower in patients than in the controls. Additionally, within the patients' group, selected network measures were significantly different when calculated from PLI or PLV. Conclusions: The selection of FC measures significantly affects the parameters of MST-based neural networks and might be a source of disagreement between the results of network studies on schizophrenia.

The objective of this study was to assess the impact of different inoculation technologies on the aerobic biological semi-decomposition process of bokashi-type biofertilizer formulations. We examined their effects on the chemical and biological quality of the product, as well as their influence on the agronomic and nutritional characteristics of red-beet and cabbage crops in the field. The highest yields of field-grown beet crops were obtained from seedlings produced using the following treatments: bokashi biofertilizer + biodynamic preparations 502-507 BPB (62.6 Mg ha-1), bokashi + Chamomilla 12CH (60.2 Mg ha-1), and bokashi + Carbo vegetabilis 12 CH (56.3 Mg ha-1). These results corresponded to an increase of 60.9%, 54.7%, and 44.7%, respectively, compared to the yield of the control treatment (38.9 Mg ha-1). The increase in productivity of cabbage plants was higher in the treatment bokashi + Calcarea carbônica 12 CH (35.8 Mg ha-1), being 148.6% higher than the control (14.4 Mg ha-1).The content of moisture, carbon, nitrogen, C/N ratio, and pH H2O in the majority of the evaluated formulations, comply with the standards outlined in IN Nº 61, 2020, by Ministry of Agriculture, Fisheries and Supply, qualifying them as class "A" solid organic compound fertilizers.

To explore the expression characteristics and biological functions of related genes of medicago terrestris under long day conditions, and to lay a foundation for revealing the molecular mechanism of medicago terrestris under long day conditions. The leaves of 'R108' tribulus Medicago sativa at branch stage (A), bud stage (B), initial flowering stage (C) and full flowering stage (D) were sequenced by RNA-Seq technology. The genome of Medicago sativa, a related species of Tribulus tribulus, was used as a reference genome for sequence comparison. The transcriptomes of three adjacent periods (A vs B, B vs C, C vs D) were analyzed for differentially expressed genes and photoperiod related differentially expressed genes were screened. A total of 6875 differentially expressed genes were detected. GO functional analysis showed that differentially expressed genes were mainly involved in biological processes, cell components and molecular functions, among which the most differentially expressed genes were involved in cell components. KEGG enrichment analysis showed that differentially expressed genes were mainly involved in circadian rhythm, photosynthesis - antenna protein, ribosome metabolism and other pathways. The number of single nucleotide variants detected by cSNP analysis was 312875, and the frequency of A/G and C/T were the highest. The function of eggNOG was divided into 23 categories, with a total of 26745 genes having similarities, 9008 genes were classified as function unknown, 2669 genes were classified as signal transduction mechanism, 2194 genes were classified as transcription, etc. In different developmental stages (A vs B, B vs C, C vs D), 3463 up-regulated and 3412 down-regulated differentially expressed genes were found. The difference between up-regulated and down-regulated genes was the most obvious between bud stage and initial flowering stage. In addition, a total of 79 flowering genes were found, of which 51 differential genes were screened out to participate in photoperiodic regulation pathway, 23 differential genes were up-regulated, and 28 differential genes were down-regulated. The ratio of gene-LOC11410562(GI), gene-LOC11435974(CO), gene-LOC11422615(TOC1) and gene-LOC11432385(LHY) was higher than that of gene-LOC25500742(PHYA) and gene-LOC11 431402(ELF3), gene-LOC11434778(Col13), gene-LOC25498015(Col6), and gene-LOC11415514(Col9) were preexpressed. The above differentially expressed genes were significantly expressed in different development stages of Terrestris alfalfa, which laid a foundation for further study of the molecular mechanism of Terrestris alfalfa.

Background: Aging rate is affected by genetic changes, epigenetic modifications, oxidative stress, inflammation, lifestyle and environmental factors. In accelerated aging (AA), biological age exceeds the chronological one. Objective: To undertake a critical reappraisal of the AA concept and to reveal its weaknesses and limitations. Methods: We reviewed over 300 recent articles dealing with physiology of brain aging and pathophysiology of neurodegeneration. Results: (1) Organ systems age at different rates, which interferes with application of the AA concept to individual organs. (2) Aging rate can be decelerated due to individual structure–functional reserves built with cognitive, physical training or pharmacological interventions. (3) The AA concept lacks standardised terminology and methodology. (4) Specific molecular biomarkers (MBM) reflect aging. To consolidate the AA theory, researchers should validate numerous MBM candidates. (5) Aging factors, mechanisms and the exact nature of their biological outcomes are not well understood. Conclusion: Although considered as a perspective theory, the AA concept has serious limitations and it requires an update.

Background: Single nucleotide polymorphisms (SNPs) in the SLC10A1 gene, coding for a functional receptor of hepatitis B virus (HBV), sodium taurocholate co-transporting polypeptide (NTCP), may influence the susceptibility, the outcome, and disease course of HBV infection in some populations. Aim: to determine the prevalence of SNPs of NTCP gene, rs2296651 and rs943277, and their relationship with chronic HBV infection in a group of Egyptian patients. Methods: 137 patients with HBV and 65 healthy controls were enrolled, and the patients were divided into two groups; group I chronic HBV infection (68 patients with normal ALT and minimal or no liver necroinflammation or fibrosis) and group II chronic hepatitis B (69 patients with elevated ALT and moderate or severe liver necroinflammation). They were subjected to full history taking, clinical examination, laboratory investigations, abdominal ultrasound, and liver stiffness measurement using both Echosens® Fibroscan and acoustic radiation force impulse (ARFI). Real time PCR TaqMan 5’ allelic discrimination assay was applied to detect the SNPs in NTCP gene, rs2296651 and rs943277. Results: On studying the rs2296651 variant, all controls and patients had genotype GG without any significant association with HBV infection or disease progression. However, the rs943277 variant in all controls and 98% of patients had genotype GA, except for two chronic HBV infection patients who had genotype AA, but no significant difference between patients and controls was found. The non-invasive methods for liver fibrosis assessment ARFI, AST/platelet's ratio (APRI), and fibrosis-4 score (FIB-4) could predict the stages of fibrosis in agreement with Fibroscan with AUCOR 0.8, 0.79, and 0.76, respectively. Conclusion: These findings may suggest that there is no relation between these SNPs of the NTCP gene and susceptibility or chronicity of HBV infection in the Egyptian population. We also suggest that the use of the non-invasive methods for liver fibrosis assessment, ARFI, FIB-4, and APRI may decrease the need for liver biopsies in prediction of significant hepatic fibrosis in chronic HBV patients.

This paper investigates reachable set estimation and state-feedback controller design for linear time-delay control system with bounded disturbances. First, by constructing an appropriate Lyapunov-Krasovskii functional, we obtained a delay-dependent condition, which determed the admissible bounding ellipsoid for the reachable set of the system we considered. Then, a sufficient condition in form of liner matrix inequalities is given to solve the problem of controller design with reachable set estimation. Finally, by minimizing the volume of the ellipsoid and solving the liner matrix inequality, we obtain the desired ellipsoid and controller gain. A comparative numerical example is given to verify the usefulness of our result.

The production of plants and crops is influenced by environmental stress, which is a serious scientific issue. Cotton is an essential crop for producing natural fibers that are used to make biofuel and edible oils. Salinity is the main element that influences cotton growth during the beginning of germination. The type of salt and the growth stage affects how sensitive a plant is to salt stress. Developing ways to enhance cotton performance in salty circumstances can be aided by an understanding of the response of cotton to salt, its mechanism of resistance, and its management methods. Osmotic and ionic imbalances originate due to the deposition of soluble salts under salinity stress in the plant's root zone. Soil salinity significantly reduces plant growth due to several factors, such as nutritional ion imbalance, which reduces K+, PO4-, and NO- absorption, excessive salt chloride concentrations, and osmotic stress, which hinders water availability. Research has revealed that compared to subsequent stages, the germination, emergence, and seedling phases are more vulnerable to salinity stress, which ultimately affects the seed cotton yield by delaying blooming, reducing fruiting positions, shedding fewer fruits, and reducing boll weight. The morphology, growth of cotton roots, shoots, yield, and fiber quality are all strongly impacted by salinity stress. It slows down plant feeding, cellular metabolism, and photosynthesis. The soil, water, and climate all affect how the plant responds to salinity stress. During salt stress, excessive exclusion of sodium or its compartmentalization is the key adaptation process in cotton. A major adaptive potential to create cotton types that can withstand salt is provided by the up-regulation of both physicochemical and non-enzymatic antioxidant genes. A successful strategy to increase cotton germination in saline soils is seed priming. Moreover, the transgenic strategy might be a viable choice for improving cotton yield in saline environments. Our review focuses on the impacts of salinity on cotton productivity as well as how plants react to salt stress. It also clarifies recent genetic advancements and molecular breeding for cotton's resistance to soil salt. To create salt-tolerant cultivars, a combination of traditional breeding and novel molecular approaches will be useful.

The hexaploid bread wheat Triticum aestivum L. (2n = 6x = 42) and the tetraploid durum wheat Triticum durum (2n = 4x = 28) are two commercially the most important wheat species worldwide. These two species are components of the same gene pool, which evolved under different conditions, which made it possible to acquire different adaptations to a wider range of environmental conditions. Identification and characterization of introgressed fragments of one species in the genome of another can help in the search for new loci responsible for economically valuable traits. SNP microarrays provide information on the genotypes of thousands of positions throughout the genome. This information can be used to obtain the distribution of alleles of one species in the genome of another and to determine the location of introgressed fragments. In our work, we used genotyping data from the SNP microarray to identify durum wheat chromosome fragments containing bread wheat alleles in the offspring from crossing bread and durum wheat. We have studied the distribution of the genetic material of bread wheat in 15 combinations from crosses of bread and durum wheat. Introgressed fragments of bread wheat into the durum wheat genome were identified on chromosomes 1A, 1B, 4A, 5B, 6B, and 7A. The introgressed fragments showed polymorphism in different breeding lines. A functional enrichment analysis of genes in the introgression fragments was performed, which showed the presence of statistically significant enrichment of genes responsible for various molecular functions, biological processes and cellular components. The obtained data can be used to identify new QTL of economically valuable traits for obtaining durum wheat varieties with improved agronomic traits.

The focus of recent research shifts towards complex ‘whole organism’ responses (i.e., in multiple functional traits) in adaptation to or to defend against stressors under complex environmental conditions. This increasing complexity is challenging to analyse and demands sophisticated tools to drive meaningful conclusions from those data. Trait-based regression models, multivariate analyses, like principal component analyses, and plasticity indices can be used to tackle challenges with those complex investigations. But those methods have substantial limitations, like the need for high sample size, multi-dimensionality of results or the need for trait coordination in high-dimensional space, or the calculation on the population level, which might buffer or cover the de facto occurring individual effects. To improve and simplify studies on ‘whole organism’ responses, analyses, and their interpretation, we developed the Index for Adaptive Responses. This straightforward framework can unite all traits of an organism in one number. A newly developed transformation method, included in this framework, comprises a normalisation and standardisation to a baseline or control without changing the data or variance structure of the original data. We assessed the performance and accuracy of the framework with an application in an extensive predator-prey case study, with simulations and application examples using literature data. We show that the Index for Adaptive Responses respects adaptations as well as maladaptations and outperforms established approaches. The framework is robust against outliers and non-gaussian distribution. We further show that the qualitative prediction of the adaptiveness of included traits is highly accurate, even under challenging conditions, e.g., low replicate numbers. Functions and algorithms of the framework are provided with an R package but can easily be translated into other programming languages. The Index for Adaptive Responses will simplify future research on complex adaptive responses and improves our understanding of these responses’ ecological as well as evolutionary implications.

In this study, Raman spectroscopy is employed to investigate the chemical compounds of kumquat peels and compared that of orange. Kumquat is a citrus fruit belonging to the genus Fortunella in family Rutaceae. It is observed that kumquat peel has 3 main Raman active characteristic vibration modes specified to carotenoids, which is dominated by β-carotene at 1007, 1158 and 1526 cm-1, as it is well known for orange. The carotenoid distribution within the cross-section of kumquat is also investigated. The carotenoid-related Raman vibration modes are relatively stronger on the peel of kumquat, which is an important finding especially for the fruits that can be eaten with its peel. Our results pave the way to take an attention for the importance of kumquat as being a fruit that can be grown up in different climates compared to orange, which grow in warm climates.

This article reports the two-step synthesis of NiFeO_x nanomaterials, their characterisation and bifunctional electrocatalytic activity measurements in alkaline electrolyte for metal-air batteries. The samples were mostly in layered double hydroxide at the initial temperature, but upon heat treatment, they were converted to NiFe₂O₄ phases. The electrochemical behaviour of the different samples was studied by linear sweep voltammetry and cyclic voltammetry on the glassy carbon electrode. The OER catalyst activity was observed for low mass loadings (0.125 mg cm⁻²), whereas high catalyst loading exhibited the best performance on the ORR side. The sample heat treated at 250 °C delivered the highest bi-functional oxygen evolution and reduction reaction activity (OER/ORR) thanks to its thin-holey nanosheet like structure with higher nickel oxidation state at 250 °C. This work further helps to develop low-cost electrocatalyst development for metal-air batteries.

Magnesium, as one of the most abundant cation in the human body, plays an important role in both physiological and pathological processes. In this study, it was shown that a promising biomedical material Mg-substituted hydroxyapatite (Mg-HA) can be synthesized via fast mechanochemical method. For this method, the nature of magnesium-contained carriers was shown to be important. When using magnesium oxide as a source of magnesium, the partial insertion of magnesium cations into the apatite structure occurs. In contrast, when magnesium hydroxide or monomagnesium phosphate is used, a single-phase Mg-HA is formed. Both experimental and theoretical investigations showed that an increase in the Mg content leads to a decrease in the lattice parameters and unit cell volume of Mg-HA. Density functional theory calculations showed the high sensitivity of the lattice parameters towards the crystallographic position of the calcium site substituted by magnesium. It was shown experimentally that insertion of magnesium cations decreases the thermal stability of the hydroxyapatite. The thermal decomposition of Mg-HA leads to the formation of a mixture of stoichiometric HA, magnesium oxide and Mg-substituted tricalcium phosphate phases.

Flowering in cassava is crucial for generation of botanical seed for breeding. However, most farmer preferred genotypes are poor at flowering, exhibit great disparity in time and amount of flowering or never flower. To elucidate the genetic basis of such a flowering behaviour, 293 diverse cassava accessions were evaluated for flowering traits under two locations and seasons in Uganda. Genotyping by the Diversity Array Technology Pty Ltd. (DArTseq) platform identified 24,040 single-nucleotide polymorphisms (SNPs) distributed on the 18 cassava chromosomes. Population structure analysis using principal components (PC) and kinships showed clustering, the first five PCs accounted for 49.2% of the observed genetic variation. Linkage disequilibrium (LD) estimation was averagely 0.32 at a distance of ~2850kb (kilo base pairs). Polymorphism information content (PIC) and minor allele frequency (MAF) were 0.25 and 0.23, respectively. Genome-wide association study (GWAS) analysis uncovered 53 significant marker-trait associations (MTA) with flowering traits involving 27 loci. Two loci, SNPs S5_29309724 and S15_11747301 were associated with all the flowering traits. Using five of the 27 SNPs with Phenotype_Variance_Explained (PVE) ≥ 5%, 37 candidate genes were identified in the peak SNP sites located within 50kb upstream or downstream, most were associated with branching traits. Eight of the genes, orthologous to Arabidopsis and other plant species, had known functional annotations related to flowering, e.g. eukaryotic translation initiation factor and myb family transcription factor. This study identified genomic regions associated with flowering in cassava, the identified SNPs could be useful in marker-assisted selection to overcome hybridization challenges like unsynchronized flowering, and candidate gene validation.

Polygonatum cyrtonema Hua. is an important medicinal and edible food in China and the traditional processing method of nine-steaming and nine-drying has been used to process its rhizome. However, the global dynamic changes in secondary metabolites during the processing and whether this method could enhance the accumulation of functional components remain unclear. This study aimed to explore the processing-induced mechanisms involved in the accumulation of secondary metabolites and provide theoretical support for the pharmacological study on P. cyrtonema. Results showed the first 6 processing cycles induced drastic changes in the accumulation of secondary metabolites, while the last 3 did not induce further changes. The accumulation of most secondary metabolites significantly increased after the first 3 cycles and stabilized after 6 cycles. The first 3 cycles led to numerous newly added metabolites while the last 6–9 cycles led to a small number of disappeared metabolites. Processing enhanced the biosynthesis of various secondary metabolites and significantly affected the metabolisms of amino acids. Together, a short period of processing was helpful for enhancing the biosynthesis of secondary metabolites. However, the enhancing effects will be reversed or weakened under continuous processing. The processing cycles should be reduced to 3–6 to maintain the enhancing effects.

Lead-free ferroelectric perovskite N-methyl-N'-diazabicyclo[2.2.2]octonium)–ammonium triio-dide, MDABCO-NH₄I₃, nanocrystals are embedded in three different polymer fibers fabricated by the electrospinning technique. The nanofibers, which are very flexible and have a high Young modulus, behave as active piezoelectric energy harvesting sources that produce a piezoelectric voltage coefficient up to geff = 3.6 VmN-1 and show a blue intense luminescence band at 325 nm. In this work, the pyroelectric coefficient is reported for the MDABCO-NH₄I₃ perovskite inserted in electrospun fibers. At the ferroelectric-paraelectric phase transition, the embedded nanocrystals display a pyroelectric coefficient as high as 194×10-6 Cm-2k-1, within the same order of magnitude as that reported for the state-of-the-art bulk ferroelectric triglycine sulfate (TGS). The perovskite nanocrystals embedded into the polymer fibers remain stable, and no degradation is caused by oxidation.

Prebiotic organic synthesis reactions catalyzed by Earth-abundant metal sulfides are key processes for understanding the evolution of biochemistry from inorganic molecules, yet the catalytic functions of sulfides have remained poorly explored in the context of the origins of life. Past studies on prebiotic chemistry have mostly focused on a few types of metal sulfide catalysts, such as FeS or NiS, which form limited types of products with inferior activity and selectivity. To explore the potential of metal sulfides on catalyzing prebiotic chemical reactions, here, the chemical diversity (variations in chemical composition and phase structure) of 304 natural metal sulfide minerals in a mineralogy database was surveyed and approaches to rationally predict the catalytic functions of metal sulfides are discussed based on advanced theories and analytical tools of electrocatalysis such as proton-coupled electron transfer, structural comparisons between enzymes and minerals, and in-situ spectroscopy. To this end, we introduce a model of geo-electrochemistry driven prebiotic synthesis for chemical evolution, as it helps us to predict kinetics and selectivity of targeted prebiotic chemistry under “chemically messy conditions”. We expect that combining the data-mining of mineral databases with experimental methods and theories developed in the field of electrocatalysis will facilitate the prediction and verification of catalytic performance under a wide range of pH and Eh conditions, and aid in the rational screening of mineral catalysts involved in the origins of life.

Drought is one of the leading abiotic factors limiting morphological and physiological activities in blackberry cultivation. We investigated the effect of silver nanoparticles (AgNPs) on morphological and physiological processes in the boysenberry crop (Rubus ursinus Chamisso &amp; Schlenhtendal) under drought stress. The experiment was performed with three drought stress levels (0% PEG, 4% PEG and 8% PEG) and three AgNPs treatments (0, 0.1, 0.2 mg L−1) invitro conditions. The results showed that drought stress induced by PEG, reduced root and shoot development of boysenberry plants grown invitro. The addition of AgNPs is significantly alleviated the adverse effect of drought stress and increased the plant growth parameters. Antioxidant activity of SOD and CAT enzymes increased in boysenberry leaves when treated with AgNPs under drought conditions, while the amount of MDA decreased. Therefore, the results obtained in this study suggest that 0.1 mg L-1 AgNPs added to the medium improve the growth and development of invitro boysenberry plants under drought stress.

The involved components of formulated blending, CNF and CuO NPs, were individually obtained by using a biorefinery strategy for agricultural waste valorization together with an optimized chemical precipitation, assisted by ultrasounds. The optimization of synthesis parameters for CuO NPs have avoided the presence of undesirable species which usually requires of later thermal treatment with associated costs. The aerogels-based structure, obtained by conventional freeze-drying, acted as 3D support for CuO NPs providing a good dispersion within the cross-linked structure of the nanocellulose and facilitating direct contact of the antibacterial phase against undesirable microorganisms. All samples showed a positive response against Escherichia coli and Staphylococcus aureus. An increase of the antibacterial response of the aerogels, measured by agar disk diffusion test, has been observed with the increase of CuO NPs incorporated, obtaining width of the antimicrobial “halo” (nwhalo) from 0 to 0.6 and 0.35 for S. aureus and E. coli, respectively. Furthermore, the aerogels have been able to deactivate S. aureus and E. coli in less than 5 hours when the antibacterial assays have been analyzed by broth dilution method. From CNF-50CuO samples, an overlap nanoparticles effect produced a decrease of the antimicrobial kinetic.

We show that combining vibrational spectroscopy with signal processing can result in a scheme for ultrasensitive detection of molecules. We consider the vibrational spectrum as a signal on the energy axis and apply a matched filter on that axis. On the example of a nerve agent molecule, we show that this allows detecting a molecule by its vibrational spectrum even when the recorded spectrum is completely buried in noise, when conventional spectroscopic detection is impossible. Detection is predicted to be possible with signal-to-noise ratios in recorded spectra as low as 0.1. We study the importance of spectral range used for detection as well as of the quality of the computed spectrum used to program the filter, specifically, the role of anharmonicity, of the exchange correlation functional, and of the basis set. The use of the full spectral range rather than of a narrow spectral window with key vibrations is shown to be advantageous, as well as accounting for anharmonicity.

To investigate the intricate dynamics of brain activity when interacting with a dynamic environment, it is imperative to continuously generate and update expectations regarding forthcoming events and their corresponding sensory and motor responses. This study aims to explore the interconnectivity in time perception across predictable and unpredictable conditions. The necessary data for this study were acquired from EEG signals, sourced from an existing database that involved an experiment conducted on a group of healthy participants. The individuals were subjected to two distinct conditions, predictable and unpredictable, encompassing various time delays. The functional connectivity between brain regions was estimated using a method known as the phase lag index. This method was employed to discern disparities in time perception between the two conditions. A comprehensive comparison of the two conditions across different delays demonstrated noteworthy variations, particularly in the gamma, beta, and theta frequency bands. The differences between delays were more pronounced in the predictable condition. Subsequently, an in-depth analysis was conducted to scrutinize the dissimilarities between the conditions within each delay. Notably, significant differences were observed across all delays. In the unpredictable condition, an increase in connectivity was detected within the alpha band during the 400-ms delay, specifically between occipital and temporal regions. Moreover, the mean connectivity in the unpredictable condition surpassed that of the predictable condition. In the delta band, distinct connectivity patterns were observed across different delays, involving connections between central and frontal regions. Specifically, a heightened connectivity between central and prefrontal regions was noted during the 83-ms delay. Notably, the right hemisphere of the prefrontal cortex played a vital role in time perception. Furthermore, a decline in connectivity across the delta, theta, and beta bands was observed in both conditions during the longest delay (800 ms) when compared to other delays

In the study of materials and macromolecules by first-principle methods, the bond order is a useful tool to represent molecules, bulk materials and interfaces in terms of simple chemical concepts. Despite the availability of several methods to compute the bond order, most applications have been limited to small systems because a high spatial resolution of the wave function and an all-electron representation of the electron density are typically required. Both limitations are critical for large-scale atomistic calculations, even within approximate density-functional theory (DFT) approaches. In this work we describe our methodology to quickly compute delocalization indices for all atomic pairs, while keeping the same representation of the wave function used in most compute-intensive DFT calculations on high-performance computing equipments. We describe our implementation into a post-processing tool, designed to work with Quantum ESPRESSO, a popular open-source DFT package. In this way we recover a description in terms of covalent bonds from a representation of wave function containing no explicit information about atomic types and positions.

Data dealing with the assessment of heavy metal pollution in road dusts in Jeddah, Saudi Arabia and its implication to human health risk of human exposure to heavy metals, are scarce. Road dusts were collected from five different functional areas (traffic areas TA, parking areas PA, residential areas RA, mixed residential commercial areas MCRA and suburban areas SA) in Jeddah and one in rural area (RUA) in Hada Al Sham. We aimed to measure the pollution levels of heavy metals and estimate their health risk of human exposure applying risk assessment models described by USEPA. Using geo-accumulation index (I_geo), the pollution level of heavy metals in urban road dusts was in the following order Cd > As > Pb > Zn > Cu > Ni > Cr > V > Mn > Co > Fe. Urban road dust was found to be moderately to heavily contaminated with As, Pb and Zn, and heavily to extremely contaminated with Cd. Calculation of enrichment factor (EF) revealed that heavy metals in TA had the highest values compared to that of the other functional areas. Cd, As, Pb, Zn and Cu were severely enriched, while Mn, V, Co, Ni and Cr were moderately enriched. Fe was consider as a natural element and consequently excluded. The concentrations of heavy metals in road dusts of functional areas were in the following order: TA > PA > MCRA > SA > RA > RUA. The study revealed that both children and adults in all studied areas having health quotient (HQ) < 1 are at negligible non-carcinogenic risk. The only exception was for children exposed to As in TA. They had an ingestion health quotient (HQ_ing) 1.18 and a health index (HI) 1.19. The most prominent exposure route was ingestion. The cancer risk for children and adults from exposure to Pb, Cd, Co, Ni, and Cr was found to be negligible (< 1 x 10^-6).

The thermal stabilizers, lubricant, and plasticizers are three crucial additives for processing poly (vinyl chloride) (PVC). In this study, a new mannitol stearate ester-based aluminum alkoxides (MSE-Al) was designed and synthesized as a novel additive for PVC. The thermal stability and processing performance of PVC stabilized by MSE-Al were evaluated by Congo red test, conductivity measurement, thermal aging test, ultravioletevisible (UV-vis) spectroscopy test, and torque rheometer test. Results showed that the addition of MSE-Al can not only markedly improve the long-term thermal stability of PVC, but also greatly accelerate the plasticizing and decrease the balance torque which demonstrated that MSE-Al possesses the lubricating property. Thus, MSE-Al was demonstrated to be able to provide tri-functional additive roles, e.g., thermal stabilizer, plasticizer, and lubricant. The test results for the thermal stability of PVC indicated that the initial whiteness of PVC stabilized with MSE-Al was not good enough, thus the synergistic effect of MSE-Al with zinc stearates (ZnSt₂) on the thermal stability of PVC was also investigated. The results showed that there exhibited an appreciable synergistic effect between MSE-Al and ZnSt₂. The thermal stabilization mechanism and synergism effect of MSE-Al with ZnSt₂ were then discussed.

(1) Background : Low dietary intake of calcium, vitamin D, vitamin C and magnesium has been associated with increased risk of osteoposrosis. The purpose was to evaluate changes in biomarkers of bone metabolism, and cardiometabolic health in postmenopausal women, with high risk of osteoporosis, followed by a nutritional intervention program. (2) Method: It was a prospective randomized controlled trial. A sample of 115 apparently healthy postmenopausal women(45 -75 years of age) randomized into four groups: (I) nutritional intervention group(n=40) received daily 1000mg vitamin C, 500mg vitamin D3, 500mg calcium(Ca) and 300mg magnesium (Mg); (II) control group(n=42) received daily 500mg vitamin D3, 500mg Ca and 300mg Mg; (III) nutritional intervention group (n=18) received daily 150mg bisphosphonates, 500mg vitamin D3, 500mg Ca and 300mg Mg; and (IV) nutritional intervention group (n=15) received daily about 364 mg polyphenols via an innovative functional food (50g olive paste enriched with mountain tea extract) along with 500mg vitamin D3, 500mg Ca and 300mg Mg. Groups I -III received supplementation for a year whereas group IV for 5 months. Changes in calciregulatory hormone parathormone (PTH) were evaluated at the beginning of the study as well as at 5 and 12 months intervals. Blood levels of vitamin D, vitamin C, Ca, Mg and the lipid profile were assessed at the beginning and at the end of the study. Anthropometric indices (weight, body fat(Kg), Body Mass Index(BMI) and bone mineral density(BMD) were evaluated at the beginning and at the end of the study. Statistical analysis was performed with IBM-SPSS Statistics-21. The level of statistical significance was set at p<0.05. (3) Results: 25(OH)D3 levels were improved, in groups II, III and IV (+3,71% and +1.45% and +5.62% respectively). PTH levels were increased at the end of the intervention period, for groups I and IV. Significant positive changes recorded, in total BMD, in all four study groups. Significant beneficial changes for total cholesterol was observed in group IV (-2.07%, P<0.05) and positive changes in group I for HDL biomarker (+61.62%, P<0.05) (4) Conclusions:. Additional larger-scale clinical trials and intervention studies are considered essential, in order to fully investigate and elucidate associations between dietary components and biochemical indices of bone metabolism.

This work reports the first nanocrystalline SnON (7.6 % Nitrogen content) n-type nanosheet Field-Effect Transistor (nFET) with transistor’s effective mobility (µeff) as high as 357 and 325 cm2/V-s at electron density (Qe) of 5×1012 cm-2 and ultra-thin body thickness (Tbody) of 7 and 5 nm, respectively. At the same Tbody and Qe, these µeff values are significantly higher than single crystalline Si, InGaAs, thin-body Si-on-Insulator (SOI), two-dimensional (2D) MoS2 and WS2. New discovery of slower µeff decay rate at high Qe than SiO2/bulk-Si universal curve was found, owing to one order of magnitude lower effective field (Eeff) by more than 10 times higher dielectric constant () in channel material, which keeps the electron wave-function away from the gate-oxide/semiconductor interface and lowers the gate-oxide surface scattering. In addition, the high µeff is also due to the overlapped large radius s-orbitals, low 0.29 mo effective mass (me*) and low polar optical phonon scattering. SnON nFETs with record-breaking µeff and quasi-2D thickness enable potential monolithic three-dimensional (3D) integrated circuit (IC) and embedded memory for 3D biological brain-mimicking structures.

For a nonzero normed linear space X‎, ‎we will define some different classes of fuzzy norms on X generated by linear and bounded linear functionals‎. ‎Also separate continuity of the elements of each class are investigated‎. ‎The aim of this research is to introduce a source of examples and counterexamples in the field of fuzzy normed spaces‎.

In recent years, functional fluidic electrohydrodynamic (EHD) pumps have attracted considerable attention due to their remarkable features, such as simple structure, quiet operation, and energy-efficient utilization. EHD liquid pumps can be used in various industrial applications, like flow transfer, thermal management, and actuator drive. In this paper, the author reviewed EHD liquid pump research in these specific aspects: the first observation of the EHD effect, its mathematical modeling, and the choice of pump structure, electrode configuration, and working medium. Based on the review, a summary of the development and latest research on EHD pumps can be provided for the readers.

Prostate cancer (PCa) is one of the most prevalent cancers among men in India. Although studies on PCa have dealt with the genetics, genomics, and the environmental influence in causality of PCa, not many studies employing the next generation sequencing (NGS) approaches of PCa have been carried out. In our previous study, we have identified some causal genes and mutations specific to Indian PCa using Whole-Exome Sequencing (WES). In the recent past, with the help of different cancer consortiums such as The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), along with differentially expressed genes (DEGs), many cancer-associated novel non-coding RNAs have been identified as biomarkers. In this work, we attempt to identify DEGs as well as long non-coding RNAs (lncRNAs) associated with signature pathways from an Indian PCa cohort using RNA-sequencing (RNA-seq) approach. From a cohort of 60, we screened 6 patients who underwent prostatectomy; we performed a whole transcriptome shotgun sequencing (WTSS)/RNA-sequencing to decipher the DEGs. We further normalized the read counts using fragments per kilobase of transcript per million mapped reads (FPKM) and analyzed the DEGs using a cohort of downstream regulatory tools, viz. GeneMANIA Stringdb, Cytoscape-Cytohubba, cbioportal to map the inherent signatures associated with PCa. By comparing the RNA-seq data obtained from the pairs of normal and PCa tissue samples using our benchmarked in-house cuffdiff pipeline, we observed some important genes specific to PCa such as STEAP2, APP, PMEPA1, PABPC1, NFE2L2, HN1L and some other important genes known to be involved in different cancer pathways such as, COL6A1, DOK5, STX6, BCAS1, BACE1, BACE2, LMOD1, SNX9, CTNND1 etc. We also identified a few novel lncRNAs such as LINC01440, SOX2OT, ENSG00000232855, and ENST00000647843.1 that need to be characterized further. Deregulation of SOX2OT is observed in various tumors, including lung cancer, gastric cancer, esophageal cancer, breast cancer, hepatocellular carcinoma, ovarian cancer, pancreatic, laryngeal squamous cell carcinoma, osteosarcoma, nasopharyngeal carcinoma, and glioblastoma. It would be interesting to characterize its function in PCa as well. In comparison with publicly available datasets, we have identified characteristic DEGs and novel lncRNAs implicated in signature PCa pathways in an Indian PCa cohort which have perhaps not been reported. As a pilot study, this has set a precedent for us to validate further experimentally, and we firmly believe this will pave a way towards discovery of biomarkers and development of novel therapies.

Background/Objectives: The purpose of the proposed study is disclosure of correlations between the dynamics of the Breathe Rate (BR) and Heart Rate (HR) when performing the intermittent physical operation at maximum power on a cycle ergometer.Methods: The stage on the study of the General functional athlete readiness (GFAR) performed using the sports standard “Red Engine” and the cycle ergometer in 16 volunteers (10 men, 6 women) whose average age was 21±1.17 years. To determine the sports potential of the volunteers in this study, we used own Coefficient of Anaerobic Capacity (CANAC Q, beats). Continuous recording of the heart rate and respiratory rate of volunteers in the maximum power sports test was carried out by the “RheoCardioMonitor” device with an athlete functional readiness module based on the method of Transthoracic electrical impedance rheography (TEIRG).Results: The degree of correlation of functional indicators (M, HR_M, GFAR) with CANAC Q for the group in full (n=80) occurred at a very high level, which confirmed the effectiveness of using the Coefficient of Anaerobic Capacity (CANAC Q) in assessing the general functional athlete readiness of the volunteers. Conclusions: CANAC Q measured in “beats” of the heart and recorded very accurately using the method of transthoracic electrical impedance rheography (TEIRG). For this reason as promising sports PSM-system, CANAC Q can replace the methods for determining the functional athlete readiness by blood lactate concentration and maximum oxygen consumption.

In this paper, the concept of fuzzy locally convex spaces generated by a family of fuzzy seminorms is introduced. We prove that a Minkowski functional of zero neighborhoods generates a seminorm and finally deduce that the topology generated by the family of seminorms coincides with that of the Minkowski functional.

(1) Background: Chronic musculoskeletal pain (CMP) in adolescents can negatively affect physical, psychological and social functioning, resulting in functional disability. This study aims to evaluate the effectiveness of an outpatient rehabilitation program based on graded exposure in vivo (EP) compared with care as usual (CAU) in a RCT. The aim of the interventions (EP and CAU) is to improve functional ability in adolescents with CMP, CAU is interdisciplinary outpatient rehabilitation care, based on graded activity. (2) Methods: A pragmatic multicenter randomized clinical trial with a 12-month follow-up was used. Adolescents (12-21 years) with musculoskeletal pain were invited to participate. Primary outcome was functional disability (Functional Disability Inventory). Most important secondary measures: perceived harmfulness, pain catastrophizing and intensity. Data analysis was performed by intention-to-treat linear mixed model analysis. (3) Results: Sixty adolescents were randomized to EP or CAU and data of 53 adolescents (93% female) could be analyzed (25 EP, 28 CAU). Mean age was 16.0 years (SD=1.87). Adolescents in EP showed a clinically relevant and statistically significant decrease in functional disability (estimated mean difference at least -8.81,p-values≤0.01) compared with CAU at all time points. Significant differences in favor of EP were found for perceived harmfulness at all time points (p-values≤0.002), for pain catastrophizing (PCS) at 2 months follow-up (p-value=0.039) and for pain intensity at 4 and 10 months follow-up (p-values≤0.028). (4) Conclusion: The effectiveness of the trial is in favor of the EP and leads to a significant and clinically relevant decrease in functional disability compared to usual care.

Prostanoids modulate the pathogenesis of vascular diseases such as atherosclerosis, in which inflammation has an important role. It is well known that inducible Ciclooxygenase-2 (COX-2) is responsible for prostanoid production associated with inflammation. Angiotensin II may be implicated through the expression of COX-2 in the vascular wall. The purpose of this study was to examine in angiotensin II-stimulated adventitial fibroblasts the anti-inflammatory activity of different food peptides by inhibiting COX-2 expression, and the production of pro-inflammatory prostanoids. Fibroblasts from aorta of Sprague-Dawley rats were incubated with different food derived peptides followed by incubation with Angiotensin II. COX-2 expression was determined by western blot, transcriptional activity by luciferase assays and prostaglandin E2 by enzyme immunoassay. COX-2 expression was inhibited in the presence of Val-Pro-Pro (bovine β-casein 84–86), Arg-Asp-Ile-Leu-Asn-Gln (ovalbumin 84–89) and Tyr-Arg-Gly-Gly-Leu-Glu-Pro-Ile-Asn-Phe (ovalbumin 125–134). Angiotensin II-induced prostaglandin E2 production was also reduced by all the above-mentioned sequences. The incubation with ovalbumin-derived peptides displayed a significant reduction of COX-2 promoter activity compared to the stimuli with Angiotensin II in transiently transfected cells. These three sequences could potentially be used as functional food ingredients to reduce inflammation related to cardiovascular diseases.

Background and Aims: We aimed to investigate cross-sectional relationships of relative handgrip strength (RHGS) with presence of diabetes and hypertension in a community setting. Methods and Results: Between 2016 and 2018, we enrolled 601 consecutive women with an average age of 70.7 ± 6.9 years (mean ± SD). Nutritional status was evaluated by the Mini Nutritional Assessment (MNA) score. Muscular strength and level of fitness were assessed by handgrip strength (HGS) and other standardized physical functional tests. The majority of participants were overweight or obese (80% with BMI > 25). Prevalence of diabetes and hypertension was 13 and 60%, respectively. Participants in the lowest quartile of HGS adjusted for BMI (RHGS) had significantly higher prevalence of diabetes and hypertension compared with those in the lower quartile (20.7 vs. 5.3% and 49.3 vs. 39.3%, respectively, p < 0.01 for both), whereas differences in nutritional status were not observed. Likelihood of having diabetes was significantly reduced in women with higher RHGS values (OR 0.77; 0.59–0.86 CI95%; p=0.002), independently of age, abdominal adiposity and presence of hypertension. RHGS was positively correlated with most of the physical functional tests performed. Conclusion: RHGS is an easy-to-obtain and inexpensive measure of muscular strength, independently associated with presence of diabetes in overweight elderly women. Prospective studies are required to assess its predictive value in individuals at risk of new onset or progression of diabetes.

Background and aims: Only one cohort study exists on the incidence of the risk of malnutrition (RM) in older adults, though numerous cross-sectional –and that cohort research– have reported several risk factors associated with the prevalence and incidence of this condition. However, alterations of body composition and impaired physical performance as exposition variables of RM have not been explored. This study assessed the incidence of RM and determined its association with excess fat mass, low total lean tissue, gait speed, and handgrip strength as exposition variables for RM in community-dwelling older adults. Methods: This is a secondary analysis in older adults (≥60 years old) derived from the study “Frailty, dynapenia, and sarcopenia in Mexican adults (FraDySMex)” a prospective cohort project conducted from 2014 to 2019 in Mexico City. At baseline, volunteers underwent body composition analysis and physical performance tests. Several covariates were identified through comprehensive geriatric assessment. At baseline and follow-up, RM was assessed using the long form of the mini nutritional assessment (MNA-LF) scale. Associations between the exposition variables and RM were assessed by multiple logistic regression. Results: The cohort included 241 subjects. Average age was 75.6±7.8 years; 83.4% were women. The mean follow-up period was 4.1 years, during which 28.6% of subjects developed RM. This condition was less likely to occur in subjects with excess fat mass index, even after adjusting for several covariates. RM was also more likely to occur in subjects with low total lean tissue index, according to both an unadjusted model and after adjusting for the corresponding variables. Regarding the association between RM and gait speed, RM was also more likely to occur in subjects with low gait speed according to both the unadjusted and adjusted models. Similar results were found for RM in relation to low handgrip strength; however, after adjusting for the associated covariates, models 1 and 2 no longer reached the level of significance. Conclusion: The risk of malnutrition diagnosed by MNA-LF was significantly less likely to occur among subjects with excess fat mass, but possibility was significantly higher in those with low total lean tissue and low gait speed after 4.1 years of follow-up in community-dwelling older adults. These results highlight that excess fat mass, low total lean tissue, and low gait speed are first than risk of malnutrition and not vice versa.

Functional Data Analysis (FDA) is a relatively new field of statistics dealing with data expressed in the form of functions. FDA methodologies can be easily extended to the study of imaging data, an application proposed in Wang et al. (2020), where the authors settle the mathematical groundwork and properties of the proposed estimators. This methodology allows for the estimation of mean functions and simultaneous confidence corridors (SCC), also known as simultaneous confidence bands, for imaging data and for the difference between two groups of images. This is especially relevant for the field of medical imaging, as one of the most extended research setups consists on the comparison between two groups of images, a pathological set against a control set. FDA applied to medical imaging presents at least two advantages compared to previous methodologies: it avoids loss of information in complex data structures and avoids the multiple comparison problem arising from traditional pixel-to-pixel comparisons. Nonetheless, computing times for this technique have only been explored in reduced and simulated setups (Arias-López et al., 2021). In the present article, we apply this procedure to a practical case with data extracted from open neuroimaging databases and then measure computing times for the construction of Delaunay triangulations, and for the computation of mean function and SCC for one-group and two-group approaches. The results suggest that previous researcher has been too conservative in its parameter selection and that computing times for this methodology are reasonable, confirming that this method should be further studied and applied to the field of medical imaging.

The functional capacity of the cervical spine plays a central role in healthy living. This study evaluated and created a comprehensive strength, range of motion (ROM), and musculoskeletal pain profile of the cervical spine in young adults. 60 physically active individuals (30 males/30 females; 19-24 year-old) participated in the study. Cervical ROM (forward flexion, extension, lateral flexion, and rotation), maximal isometric strength (forward flexion, extension, lateral flexion), and musculoskeletal pains were assessed using an electronic goniometer, a handheld dynamometer, and the Nordic questionnaire, respectively. Data analysis revealed that: a) fe-males had higher ROM values, during extension and lateral flexion, than males (p<0.05), b) males had higher absolute strength values than females in all movement directions, higher rela-tive strength values/body mass (at forward flexion) and flexion/extension ratio values (p<0.05), c) ROM and strength values were not significantly different between right-left sides (p>0.05), d) a great proportion (43.3%) of the participants had cervical pains (no sex-related differences) and e) cervical strength showed significant small negative correlation with pains (p<0.05; r=-0.225 to -0.345). The reference values created may be used by health and fitness professionals to exten-sively evaluate the cervical spine and to design specific exercise programs for injury prevention and rehabilitation.

In the research, we studied the typical functional plant traits and life forms of plants that colonize forest gaps. In the research, we analysed functional plant traits of plant species growing on five forest gaps in the Dinaric fir-beech forest in Slovenia. The forest gaps were created as a result of natural disturbances. We selected 18 functional plant traits, whose values were obtained from the BiolFlor database. With the help of the JUICE program, we calculated the frequency of its occurrence on individual forest gap for each functional plant trait. Then we calculated Sperman's correlation coefficient at p&lt;0.05, between the occurrence of individual functional plant traits and single forest gap. We found out that forest gaps are mainly colonized by perennials and herbaceous perennials and hamephytes. These are plant species that begin to flower in June and July, bloom for two or three months and are pollinated by insects, mainly hover flys and wild bees. Characteristic of colonizing plant species is also that, in addition to reproducing by seeds and spores, they also reproduce vegetatively. Besides that, birds and forest mammals are the vectors of fruit and seed dispersal of colonizing plant species.

The livestock sector can be a major contributor to the mitigation of greenhouse (GHG) emissions. Within the sector, beef production produces the largest proportion of the livestock sector’s direct emissions. The objective of this study was to assess the on-farm GHG emissions in semi-arid rangelands in Argentina and to identify the relationships between emissions and current farm management practices. A survey recorded detailed information on farm management and characteristics. Assessments of GHG emissions were based on the IPCC Tier 2 protocols [1]. The relationships between farm management and GHG emissions were identified using General Linear Models. Cluster analysis was used to identify groups of farms that differed from others in emissions and farm characteristics. Emissions per product sold were low on farms that had improved livestock care management, rotational grazing, received technical advice, and had high animal and land productivities. Emissions per hectare of farmland were low on farms that had low stocking rates, low number of grazing paddocks, little or no land dedicated to improved pastures and forage crops, and low land productivity. Our results suggest that the implementation of realistic, relatively easy-to-adopt farming management practices has considerable potential for mitigating GHG emissions in semi-arid rangelands of central Argentina.

Low dietary intake of calcium, vitamin D, vitamin C and magnesium has been associated with increased risk of osteoporosis. The purpose of the study was to evaluate changes in several bone health indicators and metabolic biomarkers in postmenopausal women, with high osteopenia or osteoporosis, followed by a nutritional intervention program. 115 apparently healthy postmenopausal women (52±8 years old) were randomized into four groups: group I (n=40) received daily 1000 mg vitamin C, 100 mcg vitamin D3, 500 mg calcium(Ca) and 300 mg magnesium (Mg); group II (n=42) received daily 100 mcg vitamin D3, 500 mg Ca and 300 mg Mg; group III (n=18) received daily 5 mg bisphosphonates, 100 mcg vitamin D3, 500 mg Ca and 300 mg Mg; and group IV (n=15) received daily about 364 mg polyphenols via an innovative functional food (50 g olive paste enriched with mountain tea extract) along with 100 mcg vitamin D3, 500 mg Ca and 300 mg Mg. Groups I -III received supplementation for a year whereas group IV for 5 months. Changes in bone health indicators and metabolic biomarkers were assessed at the beginning and at the end of the study. Anthropometric indices and whole-body bone mineral density (BMD) were also evaluated at the beginning and at the end of the intervention period. The results revealed improved elevated levels of 25(OH)D3, in groups II, III and IV (+3,71% and +1.45% and +5.62% respectively). Significant positive changes were recorded, for whole-body BMD, in all four study groups. Significant beneficial changes for total cholesterol were observed in group IV (-2.07%, P&lt;0.05) and positive changes in group I for HDL biomarker (+61.62%, P&lt;0.05). Additional larger-scale clinical trials and intervention studies are considered essential, to fully investigate and elucidate associations between dietary components and biochemical indices of bone health.

We here investigate the dynamical behavior of a fractional-order predator-prey system with anti-predator behavior and Holling IV type functional response. First we study the non-negativity, existence, uniqueness, and boundedness of solutions to the system from a mathematical analysis perspective. Then, we analyze the stability of its equilibrium points and the possibility of bifurcations using stability analysis methods and bifurcation theory, and prove the existence of a supercritical Hopf bifurcation in the system. After providing numerical simulations to illustrate the conclusions theoretically derived, by summarizing those various analytical results obtained, we finally present three interesting conclusions that can contribute to better understanding and preservation of ecological systems.

Insufficient physical activity (PA) is associated with low cardiorespiratory fitness, which favors cardiovascular and other non-communicable diseases. Besides, it evidentially affects mental health. Considering the WHO PA guidelines, CrossFit® represents a versatile exercise program, combining aerobic and resistance training with mobility and could help lowering disease incidences among sedentary people. Yet, long-term CrossFit research is sparse. We conducted a nine-months intervention (≥ 2 CrossFit workouts/week) in sixteen beginners (14 males, 35  6.8 years, 180  8.6 cm, 85. 5  19.1 kg). As primary endpoint, VO2max was assessed at baseline, after four, and nine months. A repeated-measures ANOVA and pearson correlation were conducted. Well-being was investigated by WHO-5-index pre- and post-intervention. For exploratory purpose, body composition was tracked. Main outcome was an 11.5 % VO2max improvement with large effect (p < .01, η_p^2 = .27). Strong negative correlations between baseline VO2max and its progression after nine months (p = .006, r = -.654) were found. Well-being increased by 8.7 % (p = .024, d = .51). Body composition improved without statistical significance. Resting metabolic rate increased by 2.2 % (p = .042). This study reveals the potential of CrossFit to enhance physiological and psychological health in beginners. For more robust results, bigger sample sizes with higher proportion of women are needed.

The road traffic injuries risk factors such as driving offenses and average speed are concerns for health organizations to reduce the number of injuries. Without any comprehensive view of each road, one cannot decide about the effective policy. In this manner, the data-driven policy will help to improve and assess the decisions. The count data near the road of two airports is surveyed for investigating the time-varying speed zones. The descriptive statistics, ANOVA, and functional data analysis were used. The hourly data of traffic counts for four different locations at the entrance of the two airports, international and domestics, were collected for one the year 2018 to 2019.The hourly pattern of driving offenses for each road was assessed and the to and from airport roads had different peaks (<0.05). The hour, weekdays, type of airport, direction and their interactions were statistically significant (<0.05) for the chance of driving offenses. The speed average during the day was statistically different (<0.5) by the number of different types of vehicles. The traffic count data is a great resource for decision making in safe driving subjects such as driving offenses. With functional data analysis, we can analyze them to get the most of the characteristics of this data. The airports are public places with high traffic demand in all countries that yields the different pattern of traffic transportation, therefore we extract the factors that affect the driving offenses. Finally, we conclude that conducting a time-varying speed zone near the airports seems vital.

SARS-CoV-2 is mutating and creating divergent variants across the world. An in-depth investigation of the amino acid substitution in the genomic signature of SARS-CoV-2 proteins is highly essential for understanding its host adaptation and infection biology. A total of 9587 SARS-CoV-2 structural protein sequences collected from 49 different countries are used to characterize protein-wise variants, substitution pattern (type and location), and major substitution changes. The majority of the substitutions are distinct, occurred mostly in a particular location, and leads to a change in amino acid's biochemical properties. In terms of mutational changes, Envelope (E) and Membrane (M) proteins are relatively stable than Nucleocapsid (N) and Spike (S) proteins. Several co-occurrence substitutions are observed, particularly in S and N proteins. Substitution specific to active sub-domains reveals that Heptapeptide Repeat, Fusion peptides, Transmembrane in S protein, and N-terminal and C-terminal domains in N protein are remarkably mutated, and also found few deleterious mutations in these domains.

RNA editing involves the insertion, deletion or substitution of single nucleotides within a RNA molecule, without altering the DNA sequence. Adenosine to inosine (A-to-I) editing consists of an RNA modification where single adenosines along the RNA sequence are converted into inosines. Such a biochemical transformation is catalyzed by enzymes belonging to the family of adenosine deaminases acting on RNA (ADARs) and occurs either co- or post-transcriptionally. Initially, the A-to-I RNA editing phenomenon was discovered and studied in messenger RNAs (mRNAs), where it can influence RNA splicing and cause the recoding of codon sequences. The employment of more powerful, high-throughput detection methods has recently revealed that A-to-I editing widely occurs in non-coding RNAs, including microRNAs (miRNAs). MiRNAs are a class of small regulatory non-coding RNAs (ncRNAs) acting as translation inhibitors, known to exert relevant roles in controlling cell cycle, proliferation, and cancer development. Indeed, a growing number of recent researches have evidenced the importance of miRNA editing in cancer biology by exploiting various detection and validation methods. Herein, we briefly overview early and currently available A-to-I miRNA editing detection and validation methods and discuss the significance of A-to-I miRNA editing in human cancer.

Understanding the role of risk regions identified by genome-wide association studies (GWAS) have made considerable progress lately referred to the post-GWAS era. Annotation of the genes to the GWAS and fine-mapped functional variants, and understanding their biological pathway/gene networks enrichments is expected to give rich dividend by elucidating the mechanisms underlying prostate cancer. To this aim, we compiled and analysed currently available post-GWAS data on genes identified through GWAS and validated through experimental studies in prostate cancer to investigate molecular biological pathways enriched for assigned functional genes. The results highlight some well-known cancer signalling pathways, antigen presentation process and enrichment in cell growth and development gene networks suggesting prostate cancer may result from the accumulation of the effects of functional variants through multiple gene sets and pathways. The upstream analysis identifies critical transcription factors, which supplements the results regarding the regulatory role of the post-GWAS genes. We also identified the common genes between post-GWAS and three well-annotated prostate cancer Oncomine data in patient samples in order to uncover possible main genes in prostate cancer development/progression. Post-GWAS generated knowledge of gene networks and pathways, if analysed further and targeted appropriately, will have an important impact on clinical management of the disease.

In the neuroscience research field, specific for medical imaging analysis, how to mining more latent medical information from big medical data is significant for us to find the solution of diseases. In this review, we focus on neuroimaging data that is functional Magnetic Resonance Imaging (fMRI) which non-invasive techniques, it already becomes popular tools in the clinical neuroscience and functional cognitive science research. After we get fMRI data, we actually have various software and computer programming that including open source and commercial, it's very hard to choose the best software to analyze data. What's worse, it would cause final result imbalance and unstable when we combine more than software together, so that's why we want to make a pipeline to analyze data. On the other hand, with the growing of machine learning, Python has already become one of very hot and popular computer programming. In addition, it is an open source and dynamic computer programming, the communities, libraries and contributors fast increase in the recent year. Through this review, we hope that can make neuroimaging data analysis more easy, stable and uniform base the one platform system.

AbstractIn the evolving modern era of neuromodulation for movement disorders in adults and children, much progress has been made recently characterizing the human motor network (MN) with potentially important treatment implications. Herein is a focused review of relevant resting state fMRI functional and effective connectivity of the human motor network across the lifespan in health and disease. The goal is to examine how the transition from static functional to dynamic effective connectivity may be especially informative of network-targeted movement disorder therapies, with hopeful implications for children.Impact StatementWhile functional connectivity has elucidated much MN properties with relation to age, disease, and behavior, effective connectivity has been shown to be useful in MN-informed therapies in adults. Thus, effective connectivity may have potential to impact childhood movement disorder therapies, given the lower to no patient demand.

With a large number of annotated non-coding RNAs (ncRNAs), repetitive sequences are found to constitute functional components (termed as repetitive elements) in ncRNAs that perform specific biological functions. Bioinformatics analysis is a powerful tool for improving our understanding of the role of repetitive elements in ncRNAs. This chapter summarizes recent findings that reveal the role of repetitive elements in ncRNAs. Furthermore, relevant bioinformatics approaches are systematically reviewed, which promises to provide valuable resources for studying the functional impact of repetitive elements on ncRNAs.

Over the past decade and a half, dynamic functional imaging has revolutionized the neuroimaging field. Since 2009, it has revealed low dimensional brain connectivity measures, has identified potential common human spatial connectivity states, has tracked the transition patterns of these states, and has demonstrated meaningful alterations in these transition and spatial patterns in neurological disorders, psychiatric disorders, and over the course of development. Recently, researchers have begun to analyze this data from the perspective of dynamic system and information theory in the hopes of understanding how these dynamics support less easily quantified processes, such as information processing, cortical hierarchy, and consciousness. Consciousness, in particular, appears to be strongly linked to entropy production in the brain. Little attention has been paid to the effects of psychiatric disease on entropy production in the human brain, however. Even disorders characterized by substantial changes in conscious experience have not been widely analyzed from this perspective. We begin to rectify this by examining the complexity of subject trajectories in state space through the lens of information theory. Specifically, we identify a basis for the dynamic functional connectivity state space and track subject trajectories through this space over the course of the scan. The dynamic complexity of these trajectories is assessed along each dimension of the proposed basis space. Using these estimates, we demonstrate that schizophrenia patients display substantially simpler trajectories than demographically matched healthy controls, and that this drop in complexity concentrates along specific dimensions. We also demonstrate that entropy generation in at least one of these dimensions is linked to cognitive performance. Overall, results suggest great value in applying dynamic systems theory to problems of neuroimaging and reveal a substantial drop in the complexity of schizophrenia patients’ brain function.

Cempo Ireng (Oryza sativa L. var. Cempo Ireng) is one of the black rice variety in Indonesia that consumed as functional food, not as a staple food because of the black rice contains anthocyanin pigment which has beneficial to human health. High concentration of anthocyanin reaching 393.93 ppm cause black color in the pericarp layer of Cempo Ireng which make this variety as an antioxidant source, low glycemic index, and free of gluten, leading to have higher price in the rice market. However, most of the farmers are not cultivate Cempo Ireng due to the longer vegetative phase up to 150 days compared to the white rice varieties which only takes 90 days, the taller phenotype of Cempo Ireng cause problems in cultivation, and also the purple color of Cempo Ireng attract birds and earhead bug (Leptocorisa oratorius) to feed on black rice caryopsis that cause severe yield loss. Transgenic methods, mutation technique, intensification systems, and physical treatment have been applied in Cempo Ireng to overcome those lack characteristics. In the future, Cempo Ireng also has a big potential to become a parent in cross breeding program because of the positive characters. The aim of this review is to describe the potential of Cempo Ireng in rice breeding program for improving food sustainability.

Efforts to quantify and reduce greenhouse gas (GHG) emissions of the built environment often neglect embodied emissions, instead focusing on reducing emissions from building operations. Utilizing sustainably sourced mass timber offers low embodied carbon alternatives to traditional concrete and steel structural systems, however the variability in embodied carbon for different mass timber approaches remains understudied. In this study, we used life cycle assessment (LCA) to compare the whole building embodied carbon of nine mass timber design options and two typical concrete and steel reference cases for an eight-story mixed-use building, ensuring structural, acoustic, thermal, programmatic, and fire-rating equivalence between the designs. The study found that the mass timber designs vary significantly, ranging between a 14-52% reduction in whole building embodied carbon from the most impactful reference case, and a 31-73% reduction when considering the structural systems alone. This study demonstrates the value that whole building LCA (WBLCA) provides as a primary driver for low-carbon structural system design and architectural development of mass timber buildings, beyond that of single material comparisons using environmental product declarations (EPDs).

Studies in the area of cross-linguistic influence (CLI) have attracted the focus of multi-linguistic learners. However, little research on CLI deals with Asian learners, particularly Chinese-speaker with knowledge of two or more foreign languages. The present study explores CLI in L1 Chinese learners with both English (L2) and Spanish (L3) as foreign languages who are studying in Madrid, a Spanish-speaking community; their studies coincided with data collection. English learners were instructed to speak for analysis purposes, with the following aims: (i) to observe the most frequent category (functional transfer, code-switching, borrowing and coinage) in the CLI instances; (ii) to determine the source language of CLI; (iii) to investigate whether CLI factors, including language distance, L2 status, proficiency and recency of use, intervene in the appearance of CLI instances in the participants. Data was gathered from 16 female Chinese students at Complutense University of Madrid (UCM). These were master students aged 22 to 26, who visited Spain for more than 5 months when they participated in the present study. The instrument used was an English semi-structured interview. Results primarily reveal that (a) borrowing is the most prevalent category, accounting for 70% of the CLI instances; (b) Spanish is the main source language of CLI while Chinese plays a functional role in the transfer process; (c) language distance proves to be the strongest predictor of CLI.

The prevalence of autism has been increasing at an alarming rate. Even accounting for the expansion of autism spectrum disorder diagnostic (ASD) criteria throughout the 1990’s, there has been an over 300% increase in ASD prevalence since the year 2000. The often debilitating personal, familial, and societal sequelae of autism are generally believed to be lifelong. However, there have been several encouraging case reports demonstrating reversal of autism diagnoses with a therapeutic focus on addressing the environmental and modifiable lifestyle factors believed to be largely underlying the condition. This case report describes the reversal of autism among dizygotic, female twin toddlers and provides a review of related literature describing associations between modifiable lifestyle factors, environmental exposures, and various clinical approaches to treating autism. The twins were diagnosed with Level 3 severity ASD “requiring very substantial support” at approximately 20 months of age following concerns of limited verbal and non-verbal communication, repetitive behaviors, rigidity around transitions, and extensive gastrointestinal symptoms, among other common symptoms. A parent-driven, multidisciplinary, therapeutic intervention involving a variety of licensed clinicians focusing primarily on addressing environmental and modifiable lifestyle factors was personalized to each of the twin’s symptoms, labs, and other outcome measures. Dramatic improvements were noted within several months in most domains of the twins’ symptoms, which was manifested in reductions of Autism Treatment Evaluation Checklist (ATEC) scores from 76 to 32 in one of the twins and from 43 to 4 in the other twin. The improvement in symptoms and ATEC scores has remained relatively stable for six months at last assessment. While prospective studies are required, this case offers further encouraging evidence of ASD reversal through a personalized, multidisciplinary approach focusing predominantly on addressing environmental and lifestyle risk factors.

Prebiotic oligosaccharides are widely used as human and animal feed additives for their beneficial effects on the gut microbiota. However, there are limited data to assess the direct effect of such functional foods on the transcriptome of intestinal epithelial cells. The purpose of this study is to describe the differential transcriptomes and cellular pathways of colonic cells directly exposed to galacto-oligosaccharides (GOS) and fructo-oligosaccharides (FOS). We have examined the differential gene expression of polarized Caco-2 cells treated with GOS or FOS and their respective mock-treated cells using mRNA sequencing (RNA-seq). A total of 89 significant differentially expressed genes were identified between GOS and mock-treated groups. For FOS treatment, a reduced number of 12 significant genes were observed to be differentially expressed relative to the control group. KEGG and Gene Ontology functional analysis revealed that genes up-regulated in the presence of GOS were involved in digestion and absorption processes, fatty acids and steroids metabolism, potential antimicrobial proteins, energy-dependent and -independent transmembrane trafficking of solutes and amino acids. Using our data, we have established complementary non-prebiotic modes of action for these frequently used dietary fibers.

Transcutaneous nerve stimulation has several neuromodulatory applications, including pain management, sensory restoration, and motor recovery. Transcutaneous stimulation delivered via electrode arrays offers ease of use and reconfigurability through non-invasive means. Also, employing electrode arrays allows regulation of the permeated electric fields for greater control over the stimulation performance. Field shaping involves the regulation of permeated electric fields and is a well-established practice for deep brain stimulation; however, its applicability to peripheral nerve stimulation still needs exploration. Adopting such techniques can help to overcome current limitations with transcutaneous stimulation, like poor targetability, early onset of fatigue, and perceived discomfort. This article provides a perspective on the applicability of field-shaping techniques in improving the overall stimulation outcome.

A system to evaluate several facets of hand function for neuroprostheses-mediated tasks is proposed. It includes a platform that serves as a test bench, sensors for dynamometry, electromyography, sensorized glove, and interactive objects. The system methodically locates and assesses the motor points along the forearm, evaluates stimulation-induced fatigue, measures digit motion and forces exerted during ADL grasps, and evaluates nerve excitability to advance electrode designs. While the system is exclusively designed for neuroprostheses-mediated grasp, it can also be extended to generic grasp and object manipulation-based research.

The possibility of using graphane monolayer crystals as the electrode material is becoming popular. Graphane is stable at room temperature and has large surface area, but its chemical inertness hinders its direct interactions with Li ions. In this study, we performed density functional theory calculations to study the energetic stability, structural and electronic properties of Li on graphane with various CH divacancy configurations (v12, v13 and v14 ). The results show that adsorption of Li atom reduces the formation energy of the CH divacancy configurations. The Li-v12 is most stable with the highest binding energy of 3.25 eV/Li and relaxes to in-plane with other C atoms. Altering the Li charge state to have Li−1-v12 or Li+1 -v12 affects the energetic stability and electronic characters of Li-v12 . The Li−1-v12 (Li +1-v 12 ) enhances (reduces) the binding force between Li and v 12 configuration, and furthermore it improves (deteriorates) the conductivity of the structure. Further investigation of graphane with vacancies is encouraged due to these intriguing observations, as it holds promise for potential utilization as an electrode material.

Measurements of systems taken along a continuous functional dimension, such as time or space, are ubiquitous in many fields, from the physical and biological sciences to economics and engineering. Such measurements can be viewed as realisations of an underlying smooth process sampled over the continuum. However, traditional methods for independence testing and causal learning are not directly applicable to such data, as they do not take into account the dependence along the functional dimension. By using specifically designed kernels, we introduce statistical tests for bivariate, joint, and conditional independence for functional variables. Our method not only extends the applicability to functional data of the Hilbert-Schmidt independence criterion (HSIC) and its d-variate version (d-HSIC), but also allows us to introduce a test for conditional independence by defining a novel statistic for the conditional permutation test (CPT) based on the Hilbert-Schmidt conditional independence criterion (HSCIC), with optimised regularisation strength estimated through an evaluation rejection rate. Our empirical results of the size and power of these tests on synthetic functional data show good performance, and we then exemplify their application to several constraint- and regression-based causal structure learning problems, including both synthetic examples and real socio-economic data.

Plant-derived diterpene synthases (PdiTPSs) play a critical role in the formation of structurally and functionally diverse diterpenoids. However, the specificity or promiscuity of PdiTPSs remains unclear. In order to gain more understanding of this, the sequences of 199 functionally characterized PdiTPSs and their corresponding 3D structures were collected and manually corrected. Then, the correlations among sequences, domains, structures and their corresponding products were comprehensively analyzed. However, those features alone was insufficient for ef-fective product-specific classification of PdiTPSs as these methods could not establish a clear mapping between the enzymes and products. Nevertheless, local structural analysis can identify residues that have been experimentally proven to influence product outcomes through mutagenesis, and these residues exhibit conservation in spatial positioning and physicochemical properties. And aromatic residues surrounding the substrate exhibited selectivity towards its chemical structure. Specifically, tryptophan (W) was preferentially located around the linear substrate geranylgeranyl pyrophosphate (GGPP), while phenylalanine (F) and tyrosine (Y) were preferentially located around the initial cyclized diterpene intermediate. This analysis revealed the functional space of residues surrounding the substrate of PdiTPSs, most of which have not been experimentally explored. These findings provide guidance for screening specific residues for mutation studies to change the catalytic products of PdiTPSs.

The electrochemical CO2 reduction reaction can lead to high value-added molecules production while helping decrease anthropogenic CO2 emissions. Copper can reduce CO2 to more than thirty different hydrocarbons and oxygenates, but it lacks the required selectivity. We present a computational investigation of the role of nano-structuring and alloying in Cu-based catalysts on the activity and selectivity of CO2 reduction to one-carbon products: carbon monoxide, formic acid, formaldehyde, methanol, and methane. The adsorption, activation, and conversion of CO2 were computed on monometallic and bimetallic (decorated and core-shell) 55-atom Cu-based clusters. The dopant metals considered were Ag, Cd, Pd, Pt, and Zn, located at different coordination sites. The relative binding strength of the intermediates at different applied potentials were used to identify the optimal catalyst for the selective CO2 conversion to one carbon products. It was discovered that single atom doping with Cd and Zn is optimal for the CO2 to carbon monoxide conversion. The core-shell models with Ag, Pd, and Pt provided higher selectivity for formic acid and formaldehyde. The Cu-Pt and Cu-Pd showed lowest overpotential for methane formation.

N,N-dimethyl-4-nitroaniline (NNDM4NA, C8H10O2N2), is a superelastic and superplastic charge-transfer molecular crystal with a high molecular dipole moment, µ=7.95 D, which crystal-lizes in the acentric polar point group 2. Highly aligned poly-l-lactic acid (PLLA) polymer micro-fibers with embedded NNDM4NA nanocrystals were fabricated using the electrospinning tech-nique. The composite fibers display an extraordinarily high piezoelectric output response, where for a small stress of 5.0x103 Nm-2, an effective piezoelectric voltage coefficient of geff=3.6 VmN-1 was obtained. The fibers were found to display solid state blue fluorescence with a long (147 ns) life-time decay. Furthermore, the composite fibers exhibit an average increase of 67% on the Young modulus reaching 55 MPa, while the tensile strength reaches 2.8 MPa when compared with solely PLLA fibers. The results show that nanocrystals, from small organic molecules, with elastic and piezoelectric properties form hybrid functional 2-dimensional luminescent array which are me-chanical strong and generate high output voltages making them promising for applications in energy harvesting and as solid-state blue emitters.

Complex colloidal fluids, depending on particulates’ shapes and packing fractions, may have a wide range of shear thinning and thickening behaviors. A particular interesting way to transition between different types of such behavior is by infusing functional complex particles that can be manufactured using modern techicques such as 3D printing. In this paper, we display 2D molecular dynamics simulations of such fluids with infused star-shaped functional particles, with variable leg length and number of legs, as they are infused in a non-interacting, coarse-grained fluid. We vary the packing fraction (ϕ) of the system, and for each different system we apply shear with various strain rate that turns the fluid into a jammed state and rise the apparent viscosity of fluid. We demonstrate the dependence of viscosity with the particles’ packing fraction. We show the role of shape and design dependence of the functional particles towards the transition to a shear thickening fluid .

Many marine species use different habitats at different stages of their life cycle. Functional connectivity, the degree to which the seascape facilitates or impedes movement between habitat patches, is poorly studied in marine systems. We reviewed the scientific literature to explore the various barriers preventing functional connectivity between marine habitats and how the removal of these barriers may restore connectivity. To our knowledge, this is the first systematic review to investigate functional connectivity between life cycle habitats for a range of marine species. A total of 4,499 records were identified and screened, leaving 69 publications eligible for review. The results highlighted a range of distances between nursery and adult habitats that limited functional connectivity for a number of species, predominantly reef fishes. For some species, adults were absent on reefs >9km from the closest nursery habitat, suggesting a threshold for connectivity. Similarly, increased distance between spawning and settlement habitats decreased settling success of larvae of various taxa. Pelagic larval duration, seascape topography and climate change were also shown to impact functional connectivity during the larval phase. The removal and mitigation of barriers preventing functional connectivity, including dams and habitat fragmentation, restored connectivity between disconnected life cycle habitats, but the efficacy of these approaches differed between species and studies. The results of this review deepen our understanding of marine functional connectivity between life cycle habitats via larval, juvenile, and adult dispersal. These findings have implications for the design and management of marine reserve networks.

β-dicalcium silicate (β-Ca₂SiO₄, or β-C₂S in cement chemistry notation) is one of the most important minerals in cement. An improvement of its hydration rate would be the key point for developing environmentally friendly cements with lower energy consumption and CO₂ emissions. However, there is a lack of fundamental understanding on the water/β-C₂S surface interactions. In this work we aim to evaluate the water adsorption on three β-C₂S surfaces at the atomic scale using density functional theory (DFT) calculations. Our results indicate that thermodynamically favorable water adsorption takes place in several surface sites, with a broad range of adsorption energies (−0.78 to −1.48 eV), depending on the particular mineral surface and adsorption site. To clarify the key factor governing the adsorption, the electronic properties of water at the surface were analyzed. The partial density of states (DOS), charge analysis, and electron density difference analyses suggest a dual interaction of water with β-C₂S (100) surface: a nucleophilic interaction of the water oxygen lone pair with surface calcium atoms, and an electrophilic interaction (hydrogen bond) of one water hydrogen with surface oxygen atoms. Despite the elucidation of the adsorption mechanism, no correlation was found between the electronic structure and the adsorption energies.

Given its exceptional attributes, aerogel is viewed as a material with immense potential. Being a natural polymer, cellulose offers the advantage of being both replenishable and capable of breaking down naturally. Cellulose-derived aerogels encompass the replenish ability, biocompatible nature, and ability to degrade naturally inherent in cellulose, along with additional benefits like minimal weight, extensive porousness, and expansive specific surface area. Even with increasing appreciation and acceptance, the undiscovered possibilities of aerogels within the textile sphere continue to be predominantly uninvestigated. In this context, we outline the latest advancements in the study of cellulose aerogel formulation and their diverse impacts on textile formations. Drawing from the latest studies, we reviewed the materials used for the creation of various kinds of cellulose-focused aerogels and their properties, analytical techniques, and multiple functionalities in relation to textiles. This comprehensive analysis extensively covers the diverse strategies employed to enhance the multi-functionality of cellulose-based aerogels in the textile industry. Additionally, we focused on the global market size of bio-derivative aerogels, companies in the industry producing goods, and prospects moving forward.

NiO-based nanomaterials have attracted a great deal of interest in view of various applications, that have stimulated the implementation of various synthetic approaches to control their chemico-physical properties as a function of the desired end-use. In this regard, their bottom-up preparation starting from suitable precursors plays an important role, but a molecular level in-sight into their reactivity remains an open challenge. In this study, we focus on the fragmentation of Ni(II) diketonate-diamine adducts, of interest as precursors for Ni(II) oxide systems, by com-bined electrospray ionization mass spectrometry (ESI-MS) with multiple collisional experiments (ESI-MSn) and theoretical calculations. The joint analyses revealed common features in the frag-mentation pattern of the target compounds: i) in the first-fragmentation, all three complexes form analogous base-peak cations by losing a negatively charged diketonate; in these cations, Ni-O and Ni-N interactions are stronger and the Ni positive charge is lower than in the neutral complexes; ii) the tendency of ligand electronic charge to migrate towards Ni further increases in the subsequent fragmentation processes, leading to the formation – in all three cases – of a tetracoordinated Ni environment involving an interesting cation-π intramolecular interaction.

The aim of this study was to evaluate the effect of dietary supplementation with Olea europaea L. extract on the animal welfare and milk quality of lactating Italian Holstein-Friesian dairy cows at different calving orders. Cows in mid lactation phase received, for 60 days, the natural olive extract Phenofeed Dry® (500 mg/cow/day) with high antioxidant power. Hormonal and metabolic parameters were determined through ELISA assays, the milk fatty acid profile through gas chromatography, chemical-nutritional and hygienic-sanitary parameters through ultrasonic analyses. The milk lysozyme content was measured through a specific ELISA assay. The administration of the enriched feed did not alter the hormonal balance. Primiparous cows were more sensitive to the treatment and showed a better general health status compared to other calving orders. The enriched feed resulted in a reduction of saturated fatty acids (SFAs) and an increase of monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs), ensuring an adequate nutritional content and, above all, a significantly higher content of the antibacterial protein, lysozyme. Overall, our study demonstrate that the inclusion of natural bioactive molecules such as Olea europaea L. polyphenols contributes to improving the welfare status of dairy cows and ensuring high nutritional and functional quality of animal productions.

A concise proof of the Riemann Hypothesis is presented by clarifying the Hadamard product expansion over the zeta zeros, demonstrating that the Riemann Hypothesis is true.

For a long time, there has been interest in the relationship between personality traits and life satisfaction. However, many previous studies suffer from small sample sizes or selective sampling, sometimes leading to biased or imprecise results. The current study, which focuses on the trait of extraversion, attempts to overcome these limitations by using a large-scale German survey of more than 40,000 individuals aged 10 to 72. As the descriptive and regression results clearly show, there is a statistically significant relationship between extraversion and several dimensions of current life satisfaction. Depending on the type of satisfaction, the unstandardized regression coefficients range from 0.18 to 0.33. To gain further insight, age is added as an explanatory variable to test whether these associations change as a person ages. The results show that the effect sizes sometimes differ by age but remain robust and statistically significant. In conclusion, the study adds to the literature by providing convincing evidence that extraversion and life satisfaction are positively associated, at least in Western and industrialized countries, and that there are interaction effects with age.

The paper proves a theorem about the structure of the distribution function on which the extremum of fractionally linear functional is reached in the presence of an uncountable number of linear constraints. The problem of finding an extremal distribution function arises when determining the optimal control strategy in a class of Markov homogeneous randomized control strategies. The structure of extremal functions is described by a finite number of parameters, hence the problem is greatly simplified since it is reduced to the search for an extremum of some function.

Plants and plant-derived food products have been used for medicinal purposes since the ancient. Medicinal Plant-based functional foods or plant-based dietary compounds are a re-emerged interest for their therapeutic benefits and nutritive supports which has implicated in healthcare systems across the world. Neurological disorders are one of the greatest threats to public health and according to the World Health Organization, about 100 million people are affected globally by several neurological and mental ailments. In a traditional medication system, medicinal plants have been applied as both neuro-therapeutic purposes and micro-macro nutrients provider for the wellbeing of psychological states e.g. anti-depressant, anti-anxiety, anti-convulsions, anti-dementia, anti-psychotic, etc. Herein, it is a topic of great interest to present a conceptual aspect by reviewing relevant scientific literature about the plant-based functional foods or bioactive phytochemicals for the prevention and treatment of mental and neurological disorders. From the literature assessment, we have found that nutritional neuroscience is becoming an advanced research discipline and there has been a growing pile of evidence concerning the therapeutic use of plant-based functional foods and/or plant-derived food compounds for the management of neurologic health, evolving with promising impact over the time.

Titanium dioxide nanoparticles have risen concerns about their possible toxicity and the European Food Safety Authority recently banned the use of TiO2 nano-additive in food products. Following the intent of relating nanomaterials atomic structure with their toxicity without having to conduct large scale experiments on living organisms, we investigate the aggregation of titanium dioxide nanoparticles using a multi-scale technique: starting from ab initio Density Functional Theory to get an accurate determination of the energetics and electronic structure, we switch to classical Molecular Dynamics simulations to calculate the Potential of Mean Force for the connection of two identical nanoparticles in water; the fitting of the latter by a set of mathematical equations is the key for the upscale. Lastly, we perform Brownian Dynamics simulations where each nanoparticle is a spherical bead. This coarsening strategy allows studying the aggregation of a few thousand nanoparticles. Applying this novel procedure, we find three new molecular descriptors, namely, the aggregation free energy and two numerical parameters used to correct the observed deviation from the aggregation kinetic described by the Smoluchowski theory. Molecular descriptors can be fed into QSAR models to predict the toxicity of a material knowing its physicochemical properties, without having to conduct large scale experiments on living organisms.

Variability in traits forming the Leaf Economics Spectrum (LES) among and within crop species play a key role in governing agroecosystem processes. However, studies evaluating the extent, causes, and consequences of within-species variation in LES traits for some of the world’s most common crops remain limited. We quantified variation in nine leaf traits measured across 90 vines of five wine grape (Vitis vinifera) varieties at two ontogenetic stages. Grape traits covary along an intraspecific LES, in patterns similar to those documented in wild plants. Across varieties, high rates of photosynthesis (A), and leaf nitrogen (N) concentrations, are coupled with low leaf mass per area (LMA), while the opposite suite of traits defines the “resource conserving end” of this intraspecific LES in grape. Variety identity predicted of leaf physiological (A) and morphological traits (i.e., leaf area and leaf mass), while leaf chemical traits and LMA were best explained by ontogenetic stage. All varieties expressed greater resource conserving trait syndromes (i.e., higher LMA, lower N, lower Amass) later in the growing season. Traits related to leaf hydraulics, including instantaneous water-use efficiency (WUE), were unrelated to LES and other resource capture traits, and were better explained by spatial location. Our results highlight the relative contributions of genetic vs. phenotypic factors in structuring this variation and point to a key role of domestication in governing trait relationships in the world’s crops.

While appropriate nutrient intake is important for older adults, various oral problems cause de-creased masticatory function. This cross-sectional study aimed to identify the factors associated with decreased masticatory performance in older adults. Oral examinations were performed on 80 participants (mean age: 75.10 ± 5.64 years) to determine the number of functional tooth units (FTUs). Symptoms of periodontal and temporomandibular diseases were evaluated via a ques-tionnaire. The tone, elasticity, and dynamic stiffness of the masseter muscle were measured using the Myoton® PRO device. The mixing ability test was used to assess the masticatory performance and the mixing ability index (MAI) was calculated. The analysis of covariance test was performed to adjust for confounding factors and multiple logistic regression analysis was performed to identify the risk factors affecting MAI. A lower MAI was significantly associated with higher tone (p = 0.006) and lower elasticity (p = 0.013). The number of FTUs (adjusted odds ratio [OR] = 0.724, p = 0.029), tone (adjusted OR = 1.215, p = 0.016), and elasticity (adjusted OR = 4.789, p = 0.038) were independently associated with the MAI. Muscle function training and prosthetic treatments may help increase masticatory performance in older adults, which will improve overall health.

Incidence of autoimmune diseases increases. Antinuclear antibodies (ANA) testing is a critical tool for their diagnosis. However, ANA prevalence in health increased over last decades, especially among young people. ANA in health occur in low concentrations, with prevalence up to 50% in some populations, which demands a cutoff revision. The review deals with origin and probable physiological or compensatory function of ANA in health, according to the concept of immunological clearance, theory of autoimmune regulation of cell functions and the concept of functional autoantibodies. Considering ANA titers ≤1:320 as a serological marker of autoimmune diseases seems inappropriate. The role of anti-DFS70/LEDGFp75 autoantibodies is highlighted as possible anti-risk biomarker for autoimmune rheumatic disorders. ANA prevalence in health is different in various regions due to several underlying causes discussed in the review, all influencing in additive combinations according to the concept of the mosaic of autoimmunity. Not only titer, but the HEp-2 IFA staining patterns, like AC-2, is also important. Accepting autoantibodies as a kind of bioregulators, not only upper, but also lower borders of their normal range should be determined. Not only their excess, but also lack of them or “autoimmunodeficiency” could be a reason of disorders.

During its first month, the recently emerged 2019 Wuhan novel coronavirus (SARS-CoV-2) has already infected many thousands of people in mainland China and worldwide and took hundreds of lives. However, the swiftly spreading virus also caused an unprecedentedly rapid response from the research community facing the unknown health challenge of potentially enormous proportions. Unfortunately, the experimental research to understand the molecular mechanisms behind the viral infection and to design a vaccine or antivirals is costly and takes months to develop. To expedite the advancement of our knowledge we leverage the data about the related coronaviruses that is readily available in public databases, and integrate these data into a single computational pipeline. As a result, we provide a comprehensive structural genomics and interactomics road-maps of SARS-CoV-2 and use these information to infer the possible functional differences and similarities with the related SARS coronavirus. All data are made publicly available to the research community at http://korkinlab.org/wuhan .

The total enthalpies of the 16 different spin configurations that can be realized in the unit cell of the archetype spin crossover complex [Fe(phen)₂(NCS)₂] (phen=1,2-phenanthroline) were calculated applying periodic density functional theory combined with the Hubbard model and the Grimme-D2 dispersion correction (DFT+U/D2). The obtained enthalpy differences between the individual spin configurations were used to determine spin couplings of an Ising-like model and subsequent Monte Carlo simulations for this model allowed to estimate the phenomenological interaction parameter Г of the Slichter-Drickamer model, which is commonly used to describe the cooperativity of the spin transition. The calculational procedure described here, which led to an estimate of about 3 kJ/mol⁻¹ for Г, in good agreement with experiment, may be used to predict from first principles how modifications of spin crossover complexes can change the character of the spin transition from gradual to abrupt and vice versa.

The proliferation of SARS-COV-2 through enhanced viral replication and its subsequent triggering of cytokine storm, are some of the hallmark phenotypes in severe COVID-19 patient cases. Cyclosporine, an immunosuppressant drug and Selinexor, an inhibitor of nuclear transporter protein, both have been successfully demonstrated to be effective against SARS-COV-2 infection by targeting those functions individually. However, the highly multifactorial pathology of SARS-COV-2 infection hinders any mono-therapeutic strategy to become an optimal option. In this study, we assess the potential efficacy of the Cyclosporine-Selinexor combination on an integrated interactome by adopting a network-medicine-based repositioning technique, where disease proximity, functional proximity and their topological separation are evaluated, followed by a robust statistical significance test. Results have shown that both drug target modules are highly proximal to the SARS-COV-2 disease modules in terms of network topology and functional associations, in a statistically significant manner, individually. Functional enrichment of both drug modules and SARS-COV-2 infected modules has shown that two drugs target the functions related to viral replication and cytokine storm during infection. Moreover, a high degree of network separation been those two drug target modules has been observed, revealing ``complementary exposure`` patterns, rendering this drug combination as an effective one against SARS-COV-2 infection. We hope that our results will encourage researchers to further investigate the potency of Cyclosporine and Selinexor combination in vivo or in vitro, and ultimately lead that up to clinical trials to treat SARS-COV-2 patients.

G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Much has been learned about the molecular mechanisms of ligand-GPCR complexes from Molecular Dynamics (MD) simulations. However, to explore ligand-specific differences in the response of a GPCR to diverse ligands, as is required to understand ligand bias and functional selectivity, necessitates creating very large amounts of data from the needed large-scale simulations. This becomes a Big Data problem for the high dimensionality analysis of the accumulated trajectories. Here we describe a new machine learning (ML) approach to the problem that is based on transforming the analysis of GPCR function-related, ligand-specific differences encoded in the MD simulation trajectories into a representation recognizable by state-of-the-art deep learning object recognition technology. We illustrate this method by applying it to recognize the pharmacological classification of ligands bound to the 5-HT2A and D2 subtypes of class A GPCRs from the serotonin and dopamine families. The ML-based approach is shown to perform the classification task with high accuracy, and we identify the molecular determinants of the classifications in the context of GPCR structure and function. This study builds a framework for the efficient computational analysis of MD Big Data collected for the purpose of understanding ligand-specific GPCR activity.

In recent decades, given the important role of gamma-aminobutyric acid (GABA) in human health, scientists have paid great attention to the enrichment of this chemical compound in food using various methods, including microbial fermentation. Moreover, GABA or GABA-rich products have been successfully commercialized as food additives or functional dietary supplements. Several microorganisms can produce GABA, including bacteria, fungi, and yeasts. Among GABA-producing bacteria, lactic acid bacteria (LAB) are commonly used in the production of many fermented foods. Lactiplantibacillus plantarum (previously Lactobacillus plantarum) has a long history of natural occurrence and safe use in a variety of food products. This LAB species provides functional properties to various fermented foods by producing a variety of bioactive compounds, including GABA. The present review aims, after a preliminary excursus on the function and biosynthesis of GABA, to provide an overview on the current uses of microorganisms and in particular of L. plantarum in the production of GABA, with a detailed focus on fermented foods.

In an era of unparalleled technical advancement, the pharmaceutical industry is struggling to transform data into increased research and development efficiency, and as a corollary, new drugs for patients. Here, we briefly review some of the commonly discussed issues around this counterintuitive innovation crisis. Looking at both industry and science related factors, we posit that traditional preclinical research is front-loading the development pipeline with data and drug candidates that are unlikely to succeed in patients. Applying a first principles analysis, we highlight the critical culprits and provide suggestions as to how these issues can be rectified through pursuit of a Human Data-driven Discovery (HD3) paradigm. Consistent with other examples of disruptive innovation, we propose that new levels of success are not dependent on new inventions, but rather the strategic integration of existing data and technology assets. In support of these suggestions, we highlight the power of HD3, through recently published proof-of-concept applications in the areas of drug safety analysis and prediction, drug repositioning, rational design of combination therapies and the global response to the Covid19 pandemic. We conclude that innovators must play a key role in expediting the path to a largely human focused, systems-based approach to drug discovery and research.

In forests, the microbial populations living in the soil can directly affect the carbon decomposed by the surface plants, and promote carbon storage and stability. In this study, 3 plots of 25.82 m×25.82 m were set up in 5 stand types, respectively. Soil samples were collected from 0~20 cm, 20~40 cm and 40~60 cm layers. Soil microbial composition, organic carbon component, pH, water content, bulk density, nitrogen, phosphorus, potassium and other physicochemical indexes and correlations were determined, and the correlations between soil carbon components and soil microbial functional modules in different mixed modes were analyzed. The results showed that: (1) The SOC of the same soil layer varied significantly, which also showed significant differences on the composition of soil bacteria and fungal microbial communities. Moreover, the bacterial community was more sensitive to the vegetation change environment, and the fungal community structure was more resistant to the influence of soil environment changes. (2) Fun_mod 1,6 and Bac_mod 7 were the microbial functional modules that played a decisive role in the process of soil carbon pool change, and the diversity and composition of bacterial community had more positive effects on soil organic carbon than that of fungal community. (3) Linear fitting and RDA results showed that POC in soil had the strongest correlation with SOC content, indicating that soil microorganisms affected the storage and stability of soil carbon mainly by regulating the conversion of surface plants (carbon sources) into POC. The soil environment of different mixed modes has different effects on soil carbon accumulation. Soil microorganisms affect soil carbon storage and stability mainly by regulating the conversion of surface plants (carbon sources) into POC forms.

In this study, we created a series of N, S, and P-doped and co-doped carbon catalysts using a single graphene nanoribbon (GNR) matrix and thoroughly evaluated the impact of doping on ORR activity and selectivity in acidic, neutral, and alkaline conditions. The results obtained showed no significant changes in the GNR structure after the doping process, though changes were observed in the surface chemistry in view of the heteroatom insertion and oxygen depletion. Of all the dopants investigated, nitrogen (mainly in the form of pyrrolic-N and graphitic-N) was the most easily inserted and detected in the carbon matrix. The electrochemical analyses conducted showed that doping impacted the performance of the catalyst in ORR through changes in the chemical composition of the catalyst, as well as in the double-layer capacitance and electrochemically accessible surface area. In terms of selectivity, GNR doped with phosphorus and sulfur favored the 2e- ORR pathway, while nitrogen favored the 4e- ORR pathway. These findings can provide useful insights into the design of more efficient and versatile catalytic materials for ORR in different electrolyte solutions, based on functionalized carbon.

Background: This study investigated the incidence, characteristics and functional outcomes associated with unplanned Acute Care Unit Readmissions (ACUR) during inpatient traumatic brain injury (TBI) rehabilitation in an Asian cohort. Methods: Retrospective review of electronic medical records from single rehabilitation unit was conducted from 1 Jan 2012 to 31 Dec 2014. Inclusion criteria were first TBI, aged &gt;18 years, admitted &lt; 6 months of TBI. ACUR were characterized into either of neurological, medical or neurosurgical subtypes. The main outcome measure was discharge Functional Independence Measure (FIM). Secondary outcomes included rehabilitation length of stay (RLOS). Results: Of 121 eligible TBI records, the incidence of ACUR was 14% (n=17), comprising neurologic (76.5%) and medical (23.5%) subtypes, occurring at median of 13 days (IQR 6, 28.5) after rehabilitation admission. Patients without ACUR had significantly higher admission mean (SD) FIM score compared to those with ACUR (FIM ACUR-negative 63.4 (21.1) vs FIM ACUR-positive 50.53(25.4), P =0.026). Significantly lower discharge FIM was noted in those with ACUR compared to those without. (FIM ACUR-positive 65.8(31.4) vs FIM ACUR-negative 85.4 (21.1), P = 0.023) Furthermore, a significant near-doubling of RLOS was noted in ACUR patients compared to non-ACUR counterparts [ACUR-positive median 55 days (IQR 34.50, 87.50) vs ACUR-negative median 28 days (IQR 16.25, 40.00), P = 0.002]. Conclusion: This study highlights the significant negative functional impact and lengthening of rehabilitation duration of ACUR on inpatient rehabilitation outcome for TBI.

The behavioral variant of frontotemporal dementia (bvFTD) has a devastating effect on multiple domains of daily living. The purpose of this PRISMA-compliant systematic review is to summarize the most important factors associated with functional impairment in this clinical group by critically analyzing the existing literature spanning the period from 2000 to 2023. To be included in the review, the study had to investigate any kind of correlates of functional status in bvFTD patients, using a previously validated instrument of functional assessment. Out of 40 articles assessed for eligibility, 18 met the inclusion criteria. The anatomical pattern of cerebral atrophy at baseline appeared to be the strongest predictor of the rate of functional decline over time, with the frontal-dominant anatomical subtype being associated with a faster rate of functional impairment. Additionally, executive dysfunction as well as apathy appeared to contribute significantly to functional disability in bvFTD patients. A comparative examination of bvFTD in relation to other clinical subtypes of FTD and other types of dementia in general suggests that it’s the predominant atrophy of the frontal lobes along with the subsequent unique combination of cognitive and neuropsychiatric manifestations that account for the pronounced functional limitations observed in these individuals, even from the early stages of the disease.

Accurate and efficient determination of excited-state polarizabilities (α) is an open problem both experimentally and computationally. Following our previous work, [Phys. Chem. Chem. Phys. 2023, 25, 2131−2141], where one can employ simple ground-state density-based functions from the information-theoretic approach (ITA) to accurately and efficiently predict the macromolecular polarizabilities, we aim to predict the lowest excited-state polarizabilities in this work. The philosophy is to use density-based functions to depict the excited-state polarizabilities. As a proof-of-principle application, employing 2-(2′-hydroxyphenyl)benzimidazole and its derivatives as model systems, we have verified that either with the ground-state (S0) or excited-state (S1) densities as input, ITA quantities can be strongly correlated with the excited-state polarizabilities. When the transition densities are considered, both S0 and S1 polarizabilities are in good relationships with some ITA quantities. Furthermore, excitation and emission energies can be predicted based on multivariant linear regression equations of ITA quantities.

Description of redox reactions is critically important for understanding and rational design of materials for electrochemical technologies including metal-ion batteries, catalytic surfaces, or redox-flow cells. Most of these technologies utilize redox-active transition metal compounds due to their rich chemistry and their beneficial physical and chemical properties for these types of applications. A century since its introduction, the concept of formal oxidation states (FOS) is still widely used for rationalization of the mechanisms of redox reactions, but there exists a well-documented discrepancy between FOS and the electron density-derived charge states of transition metal ions in their bulk and molecular compounds. We summarize our findings and those of others which suggest that density-driven descriptors are in certain cases better suited to characterize the mechanism of redox reactions, especially when anion redox is involved, which is the blind spot of the FOS ansatz.