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IntroductionKidney diseases pose a serious healthcare problem because of their high prevalence, worsening of patients’ quality of life, and high mortality. Patients with kidney diseases are often asymptomatic until disease progression starts. Expensive renal replacement therapy options, such as dialysis or kidney transplant, are required for end-stage kidney disease. Early diagnosis of kidney pathology is crucial for slowing down or curbing further damage. This study aimed to analyze the features of the protein composition of blood plasma in patients with the most common kidney pathologies: kidney calculus, kidney cyst, and kidney cancer.MethodsThe study involved 75 subjects. Proteins associated with kidney pathologies (CFB, SERPINA3, HPX, HRG, SERPING1, HBB, ORM2, and CP) were proposed. These proteins are important participants of complement and coagulation cascade activation and lipid metabolism.ResultsThe revealed phosphorylated proteoforms (CFB, C4A/C4B, F2, APOB, TTR, and NRAP) were identified. For them, modification sites were mapped on 3D protein models, and the potential role in formation of complexes with native partner proteins was assessed.DiscussionThe study demonstrates that the selected kidney pathologies have a similar proteomic profile, and patients can be classified into kidney pathology groups with an accuracy of (70–80)%.

Abstract The primary objective of analyzing the data obtained in a mass spectrometry-based proteomic experiment is peptide and protein identification, or correct assignment of the tandem mass spectrum to one amino acid sequence. Comparison of empirical fragment spectra with the theoretical predicted one or matching with the collected spectra library are commonly accepted strategies of proteins identification and defining of their amino acid sequences. Although these approaches are widely used and are appreciably efficient for the well-characterized model organisms or measured proteins, they cannot detect novel peptide sequences that have not been previously annotated or are rare. This study presents PowerNovo tool for de novo sequencing of proteins using tandem mass spectra acquired in a variety of types of mass analyzers and different fragmentation techniques. PowerNovo involves an ensemble of models for peptide sequencing: model for detecting regularities in tandem mass spectra, precursors, and fragment ions and a natural language processing model, which has a function of peptide sequence quality assessment and helps with reconstruction of noisy sequences. The results of testing showed that the performance of PowerNovo is comparable and even better than widely utilized PointNovo, DeepNovo, Casanovo, and Novor packages. Also, PowerNovo provides complete cycle of processing (pipeline) of mass spectrometry data and, along with predicting the peptide sequence, involves the peptide assembly and protein inference blocks.

Abstract Climate‐induced shifts in mosquito phenology and population structure have important implications for the health of humans and wildlife. The timing and intensity of mosquito interactions with infected and susceptible hosts are a primary determinant of vector‐borne disease dynamics. Like most ectotherms, rates of mosquito development and corresponding phenological patterns are expected to change under shifting climates. However, developing accurate forecasts of mosquito phenology under climate change that can be used to inform management programs remains challenging despite an abundance of available data. As climate change will have variable effects on mosquito demography and phenology across species it is vital that we identify associated traits that may explain the observed variation. Here, we review a suite of modeling approaches that could be applied to generate forecasts of mosquito activity under climate change and evaluate the strengths and weaknesses of the different approaches. We describe four primary life history and physiological traits that can be used to constrain models and demonstrate how this prior information can be harnessed to develop a more general understanding of how mosquito activity will shift under changing climates. Combining a trait‐based approach with appropriate modeling techniques can allow for the development of actionable, flexible, and multi‐scale forecasts of mosquito population dynamics and phenology for diverse stakeholders.

Abstract Although numerous studies have projected changes in freezing rain under future climate conditions, the internal variability of freezing rain remains poorly quantified. Here, we introduce a framework utilizing a novel machine‐learning algorithm to diagnose freezing rain in reanalysis and climate model simulations. By employing multivariate quantile mapping, we decompose the projected freezing rain trend into contributions from changes in temperature, relative humidity, and precipitation, which helps separate the forced response from internal climate variability. Our finding reveals a notable decrease in freezing rain occurrence in most areas. Despite a substantial temperature increase, internal variability overshadows climate forcing across a large portion of the eastern United States until about 2050. This insight has implications for practitioners, suggesting that the observed freezing rain frequency climatology continues to provide a relevant baseline for decision‐making in the near term. However, longer‐term design and adaptation plans should consider the projected changes in these regions.

IntroductionThe high prevalence of schizophrenia worldwide makes it necessary to proceed from subjective assessment of patient’s clinical symptoms in diagnosis making to searching for circulating blood biomarkers. On the one hand, searching for molecular markers and targets for therapeutics will make it possible to refine and detail the molecular mechanisms of pathology development, while on the other hand, it will offer new opportunities for elaborating novel approaches to disease diagnosis and enhance efficacy and timeliness of drug therapy.MethodsIn this study, we performed an extended-range proteomic analysis of plasma samples collected from 48 study subjects with confirmed diagnosis of schizophrenia and 50 healthy volunteers. The high-resolution tandem mass spectra recorded in the data-dependent acquisition mode were analyzed using the MaxQuant algorithm for the library of known protein sequences and the PowerNovo algorithm for de novo protein sequencing.ResultsIt was demonstrated that both strategies show similar results for high-abundance proteins (≥1 μg/mL). For mid-abundance (10 ng/mL – 1 μg/mL) and low-abundance (

Abstract Despite of multiple systematic studies of schizophrenia based on proteomics, metabolomics, and genome-wide significant loci, reconstruction of underlying mechanism is still a challenging task. Combination of the advanced data for quantitative proteomics, metabolomics, and genome-wide association study (GWAS) can enhance the current fundamental knowledge about molecular pathogenesis of schizophrenia. In this study, we utilized quantitative proteomic and metabolomic assay, and high throughput genotyping for the GWAS study. We identified 20 differently expressed proteins that were validated on an independent cohort of patients with schizophrenia, including ALS, A1AG1, PEDF, VTDB, CERU, APOB, APOH, FASN, GPX3, etc. and almost half of them are new for schizophrenia. The metabolomic survey revealed 18 group-specific compounds, most of which were the part of transformation of tyrosine and steroids with the prevalence to androgens (androsterone sulfate, thyroliberin, thyroxine, dihydrotestosterone, androstenedione, cholesterol sulfate, metanephrine, dopaquinone, etc.). The GWAS assay mostly failed to reveal significantly associated loci therefore 52 loci with the smoothened p

To understand the biological relevance and mode of action of artificial protein ligands, crystal structures with their protein targets are essential. Here, we describe and investigate all known crystal structures that contain a so-called “molecular tweezer” or one of its derivatives with an attached natural ligand on the respective target protein. The aromatic ring system of these compounds is able to include lysine and arginine side chains, supported by one or two phosphate groups that are attached to the half-moon-shaped molecule. Due to their marked preference for basic amino acids and the fully reversible binding mode, molecular tweezers are able to counteract pathologic protein aggregation and are currently being developed as disease-modifying therapies against neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease. We analyzed the corresponding crystal structures with 14-3-3 proteins in complex with mono- and diphosphate tweezers. Furthermore, we solved crystal structures of two different tweezer variants in complex with the enzyme Δ1-Pyrroline-5-carboxyl-dehydrogenase (P5CDH) and found that the tweezers are bound to a lysine and methionine side chain, respectively. The different binding modes and their implications for affinity and specificity are discussed, as well as the general problems in crystallizing protein complexes with artificial ligands.

Proteomic and metabolomic research enables quantitation of the molecular profile of athletes. Multiomic profiling was conducted using plasma samples collected from 18 male athletes performing aerobic activity (running) at high altitude. Metabolomic profiling detected changes in the levels of 4-hydroxyproline, methionine, oxaloacetate, and tyrosine during the recovery period. Furthermore, proteomic profiling revealed changes in expression of proteins contributing to the function of the immune system, muscle damage, metabolic fitness and performance, as well as hemostasis. Further research should focus on developing metabolic models to monitor training intensity and athlete adaptation.

High exercise loading causes intricate and ambiguous proteomic and metabolic changes. This study aims to describe the dataset on protein and metabolite contents in plasma samples collected from highly trained athletes across different sports disciplines. The proteomic and metabolomic analyses of the plasma samples of highly trained athletes engaged in sports disciplines of different intensities were carried out using HPLC-MS/MS. The results are reported as two datasets (proteomic data in a derived mgf-file and metabolomic data in processed format), each containing the findings obtained by analyzing 93 mass spectra. Variations in the protein and metabolite contents of the biological samples are observed, depending on the intensity of training load for different sports disciplines. Mass spectrometric proteomic and metabolomic studies can be used for classifying different athlete phenotypes according to the intensity of sports discipline and for the assessment of the efficiency of the recovery period.

Abstract Introduction: Midcareer research faculty are a vital part of the advancement of science in U.S. medical schools, but there are troubling trends in recruitment, retention, and burnout rates. Methods: The primary sampling frame for this online survey was recipients of a single R01 or equivalent and/or K-award from 2013 to 2019. Inclusion criteria were 3–14 years at a U.S. medical school and rank of associate professor or two or more years as assistant professor. Forty physician investigators and Ph.D. scientists volunteered for a faculty development program, and 106 were propensity-matched controls. Survey items covered self-efficacy in career, research, work-life; vitality/burnout; relationships, inclusion, trust; diversity; and intention to leave academic medicine. Results: The majority (52%) reported receiving poor mentoring; 40% experienced high burnout and 41% low vitality, which, in turn, predicted leaving intention (P < 0.0005). Women were more likely to report high burnout (P = 0.01) and low self-efficacy managing work and personal life (P = 0.01) and to be seriously considering leaving academic medicine than men (P = 0.003). Mentoring quality (P < 0.0005) and poor relationships, inclusion, and trust (P < 0.0005) predicted leaving intention. Non-underrepresented men were very likely to report low identity self-awareness (65%) and valuing differences (24%) versus underrepresented men (25% and 0%; P < 0.0005). Ph.D.s had lower career advancement self-efficacy than M.D.s (P < .0005). Conclusions: Midcareer Ph.D. and physician investigators faced significant career challenges. Experiences diverged by underrepresentation, gender, and degree. Poor quality mentoring was an issue for most. Effective mentoring could address the concerns of this vital component of the biomedical workforce.

Abstract Introduction:Midcareer is a critical transition point for biomedical research faculty and a common dropout point from an NIH-funded career. We report a study to assess the efficacy of a group peer mentoring program for diverse biomedical researchers in academic medicine, seeking to improve vitality, career advancement, and cross-cultural competence. Methods:We conducted a stratified randomized controlled trial with a waitlist control group involving 40 purposefully diverse early midcareer research faculty from 16 states who had a first-time NIH R01 (or equivalent) award, a K training grant, or a similar major grant. The yearlong intervention (2 to 3 days quarterly) consisted of facilitated, structured, group peer mentoring. Main study aims were to enhance faculty vitality, self-efficacy in achieving research success, career advancement, mentoring others, and cultural awareness and appreciation of diversity in the workplace. Results:Compared to the control group, the intervention group’s increased vitality did not reach statistical significance (P = 0.20), but perceived change in vitality was 1.47 standard deviations higher (D = 1.47, P = 0.03). Self-efficacy for career advancement was higher in the intervention group (D = 0.41, P = 0.05) as was self-efficacy for research (D = 0.57, P = 0.02). The intervention group also valued diversity higher (D = 0.46, P = 0.02), had higher cognitive empathy (D = 0.85, P = 0.03), higher anti-sexism/racism skills (D = 0.71, P = 0.01), and higher self-efficacy in mentoring others (D = 1.14, P = 0.007). Conclusions:The mentoring intervention resulted in meaningful change in important dimensions and skills among a national sample of diverse early midcareer biomedical faculty. This mentoring program holds promise for addressing the urgencies of sustaining faculty vitality and cross-cultural competence.

Abstract Post-translational processing leads to conformational changes in protein structure that modulate molecular functions and change the signature of metabolic transformations and immune responses. Some post-translational modifications (PTMs), such as phosphorylation and acetylation, are strongly related to oncogenic processes and malignancy. This study investigated a PTM pattern in patients with gender-specific ovarian or breast cancer. Proteomic profiling and analysis of cancer-specific PTM patterns were performed using high-resolution UPLC-MS/MS. Structural analysis, topology, and stability of PTMs associated with sex-specific cancers were analyzed using molecular dynamics modeling. We identified highly specific PTMs, of which 12 modified peptides from eight distinct proteins derived from patients with ovarian cancer and 6 peptides of three proteins favored patients from the group with breast cancer. We found that all defined PTMs were localized in the compact and stable structural motifs exposed outside the solvent environment. PTMs increase the solvent-accessible surface area of the modified moiety and its active environment. The observed conformational fluctuations are still inadequate to activate the structural degradation and enhance protein elimination/clearance; however, it is sufficient for the significant modulation of protein activity.

Background: United States military Veterans from recent conflicts are experiencing symptoms related to posttraumatic stress disorder (PTSD). Many Veterans are resistant to conventional health and mental health interventions (e.g., medication, psychotherapy). Alternative treatment approaches are needed. An underlying feature of PTSD is exaggerated inflammation, both peripherally and in the central nervous system. This inflammation is thought to play an important role in the vulnerability to, aggravation of, and persistence of PTSD symptoms. Therefore, an innovative intervention strategy would be the use of immunoregulatory/anti-inflammatory probiotics to reduce inflammation. Here we describe the rationale, design, and methods of a randomized placebo-controlled trial (RCT) of Lactobacillus rhamnosus GG (LGG; ATCC 53103) for posttraumatic stress disorder (PTSD). Methods: This is a Phase IIa trial of LGG for United States military Veterans with PTSD, using a longitudinal, double-blind, randomized placebo-controlled design. The primary outcome measure is plasma concentration of high-sensitivity C-reactive protein. Conclusion: Despite the fact that symptoms associated with PTSD can be disabling, individuals living with this trauma-related disorder have limited options in terms of evidence-based interventions. Recent research efforts aimed at highlighting the biological mechanisms of PTSD suggest that increased inflammation and altered autonomic nervous system activity may be treatment targets, and that immunoregulatory probiotics, such as LGG, have the potential to decrease trauma-induced inflammatory responses, as well as associated symptoms. This manuscript describes the best powered human subjects Phase IIa trial, to date, of a probiotic intervention for those living with PTSD.

Abstract Background In contrast to intoxications in toddlers which can be due to accidental ingestions, many intoxications in infants are due to medication errors. To our knowledge, this is the first case report of a citalopram intoxication in an infant, and may offer new insight on possible screening methods for intoxication as well as pharmacokinetics of citalopram in small infants. Case presentation This case report describes an unintentional citalopram intoxication in a 4 week old infant due to a vitamin D drops ‘look alike’ error. The infant showed extreme jitteriness and opisthotonus at presentation, as well as prolonged signs of gastro-oesophageal reflux. No cardiac rhythm disturbances or convulsions were seen. The clinical course combined with Finnegan scores was correlated to and supported by pharmacokinetic and pharmacokinetic data of citalopram in the patient. Conclusions Using Finnegan scores in general pediatric practice could help objectify follow-up of acute intoxications in young infants with neurological symptoms.

ABSTRACT Regionalization is an important technique for estimating the flow of hydrographic sections with a lack of data. First, it is necessary to identify hydrologically homogeneous regions (HHRs), which are commonly validated via statistical analyses. Because this step is understood to be subjective, studies that contribute to a greater reliability in identifying regions are needed. In this context, the objective was to evaluate the inclusion of a physical analysis of the average regionalized flow rates as an aid to identify HHRs. The groupings were defined on the basis of geographical convenience methods and cluster analysis. For the assessment of regionalized flows, six statistical indices were used with a physical analysis that was performed via a comparison of the runoff coefficient to the spatial distribution of precipitation values. It was concluded that the physical analysis reduced the subjectivity in the identification of HHRs.

The paper describes the Web platform built within the project “Contro l’Odio”, for monitoring and contrasting discrimination and hate speech against immigrants in Italy. It applies a combination of computational linguistics techniques for hate speech detection and data visualization tools on data drawn from Twitter.It allows users to access a huge amount of information through interactive maps, also tuning their view, e.g. visualizing the most viral tweets and interactively reducing the inherent complexity of data. Educational courses for high school students have been developed which are centered on the platform and focused on the deconstruction of negative stereotypes against immigrants, Rom and religious minorities, and on the creation of positive narratives. The data collected and analyzed by the platform are also currently used for benchmarking activities within an evaluation campaign, and for paving the way to new projects against hate.

Abstract Objective Most eukaryotic cells contain microtubule filaments, which play central roles in intra-cellular organization. However, microtubule networks have a wide variety of architectures from one cell type and organism to another. Nonetheless, the sequences of tubulins, of Microtubule Associated proteins (MAPs) and the structure of microtubules are usually well conserved throughout the evolution. MAPs being known to be responsible for regulating microtubule organization and dynamics, this raises the question of the conservation of their intrinsic properties. Indeed, knowing how the intrinsic properties of individual MAPs differ between organisms might enlighten our understanding of how distinct microtubule networks are built. End-Binding protein 1 (EB1), first described as a MAP in yeast, is conserved in plants and mammals. The intrinsic properties of the mammalian and the yeast EB1 proteins have been well described in the literature but, to our knowledge, the intrinsic properties of EB1 from plant and mammals have not been compared thus far. Results Here, using an in vitro assay, we discovered that plant and mammalian EB1 purified proteins have different intrinsic properties on microtubule dynamics. Indeed, the mammalian EB1 protein increases microtubules dynamic while the plant EB1 protein stabilizes them.

Abstract Background Left atrial appendage occlusion (LAAO) represents a treatment alternative to anticoagulation in patients with atrial fibrillation. We evaluate a novel device for epicardial LAAO in a translational canine model. Methods Nine hounds (n = 9) were used to assess usability, safety, and efficacy of the TigerPaw Pro (TPP) device for epicardial LAAO. Following baseline imaging (intra-cardiac echocardiography (ICE) and angiography) and intraoperative visual inspection, usability was tested via a ``closure/re-opening`` maneuver followed by deployment of a total of twenty TPP devices (n = 20) on the left and right atrial appendages respectively. Procedural safety was evaluated by assessing for adverse-events via direct Epicardial inspection and endocardial imaging. Efficacy evaluation included assessment of device positioning, presence of residual stumps and completeness of closure. Post-mortem evaluation was performed to confirm safety and efficacy. Results Usability testing of all TPP devices was successful (n = 20;100%, delivery-time range 22–120 s) without any procedural adverse-events (tissue damage or tears, bleeding, vessel-impingement, structural impact). All devices fully traversed the ostium (n = 18) or appendage body (n = 2), and conformed smoothly to adjacent cardiac anatomy. In nineteen deployments (n = 19;95%), all device connector pairs were fully engaged, while in one TPP device the most distal pair remained unengaged. ICE and post-mortem inspections revealed complete closure of all appendage ostia (n = 18;100%) and only in one case a small residual stump was detected. Intraoperative safety findings were further confirmed post-mortem. Devices created a nearly smooth line of closure via symmetric endocardial tissue-coaptation. Conclusions In this preclinical model, the TPP demonstrated good ease of use for ostial access, ability to re-position (after engagement) and rapid deployment, while achieving safe and effective LAAO.

Reduction in tumor necrosis factor (αTNF) and interleukin-6 (IL-6) activities is a widely utilized strategy for the treatment of rheumatoid arthritis (RA) with a high success rate. Despite both schemes targeting the deprivation of inflammatory reactions caused by the excessive activity of cytokines, their mechanisms of action and the final output are still unequal. This was a comparative longitudinal study that lasted for 24 weeks and aimed to find the answer to why the two schemes of therapy can pass out of proportion in attitude of their efficiency. What are the differences in metabolic and proteomic responses among patients who were being treated by either the anti-TNF or anti-IL-6 strategy? We found increased levels of immunoglobulins A and G (more than 2-fold in anti-IL-6 and more than 4-5-fold in anti-TNF groups) at the final stage (24 weeks) of monitoring but the most profound increase was determined for µ-chains of immunoglobulins in both groups of study. Metabolomic changes displayed main alterations with regard to arginine metabolism and collagen maintenance, where arginine increased 8.86-fold (p < 0.001) in anti-TNF and 5.71-fold (p < 0.05) in anti-IL-6 groups but patients treated by the anti-TNF scheme suffered a higher depletion of arginine before the start of therapy. Some indicators of matrix and bone tissue degradation also increased 4-hydroxyproline (4-HP) more than 6-fold (p < 0.001) in anti-TNF and more than 2-fold (p < 0.05) in the anti-IL-6 group, but the growth dynamics in the anti-IL6 group was delayed (gradually raised at week 24) compared to the anti-TNF group (raised at week 12) following a smooth reduction. The ELISA analysis of IL-6 and TNFα concentration in the study population supported proteomic and metabolomic data. A positive correlation between ΔCDAI and ΔDAS28 indicators and ESR and CRP was established for the majority of patients after 24 weeks of treatment where ESR and CRP reduced by 20% and 40% finally, respectively. A regression model using the Forest Plot was estimated to elucidate the impact of the most significant clinical, biochemical, and anthropometric indicators for the evaluation of differences between considered anti-TNF and anti-IL-6 schemes of therapy.

The aim of this study was to determine the influence of high-intensity training under extreme conditions (T = 40 °C) on the metabolism and immunological reactions of athletes. Male triathletes (n = 11) with a high level of sports training performed load testing to failure (17 ± 2.7 min) and maximum oxygen consumption (64.1 ± 6.4 mL/min/kg). Blood plasma samples were collected before and immediately after exercise. Mass spectrometric metabolomic analysis identified 30 metabolites and 6 hormones in the plasma, of which 21 and 4 changed after exercise, respectively. Changes in the intermediate products of tricarboxylic and amino acids were observed (FC > 1.5) after exercise. The obtained data can be associated with the effect of physical activity on metabolism in athletes. Therefore, constant monitoring of the biochemical parameters of athletes can help coaches identify individual shortcomings in a timely manner and track changes, especially as the volume of training increases. In addition, it was revealed that the immunological reaction (manifestation of a hyperactive reaction to food components) is personalized in nature. Therefore, it is important for coaches and sports doctors to analyze and control the eating behavior of athletes to identify food intolerances or food allergies in a timely manner and develop an individual elimination diet.

Abstract Background Non-host resistance (NHR) presents a compelling long-term plant protection strategy for global food security, yet the genetic basis of NHR remains poorly understood. For many diseases, including stem rust of wheat [causal organism Puccinia graminis (Pg)], NHR is largely unexplored due to the inherent challenge of developing a genetically tractable system within which the resistance segregates. The present study turns to the pathogen’s alternate host, barberry (Berberis spp.), to overcome this challenge. Results In this study, an interspecific mapping population derived from a cross between Pg-resistant Berberis thunbergii (Bt) and Pg-susceptible B. vulgaris was developed to investigate the Pg-NHR exhibited by Bt. To facilitate QTL analysis and subsequent trait dissection, the first genetic linkage maps for the two parental species were constructed and a chromosome-scale reference genome for Bt was assembled (PacBio + Hi-C). QTL analysis resulted in the identification of a single 13 cM region (~ 5.1 Mbp spanning 13 physical contigs) on the short arm of Bt chromosome 3. Differential gene expression analysis, combined with sequence variation analysis between the two parental species, led to the prioritization of several candidate genes within the QTL region, some of which belong to gene families previously implicated in disease resistance. Conclusions Foundational genetic and genomic resources developed for Berberis spp. enabled the identification and annotation of a QTL associated with Pg-NHR. Although subsequent validation and fine mapping studies are needed, this study demonstrates the feasibility of and lays the groundwork for dissecting Pg-NHR in the alternate host of one of agriculture’s most devastating pathogens.

Abstract Background In the present work, an electrochemical sensor for detection of paracetamol was fabricated by modifying a glassy carbon electrode (GCE) using multiwalled carbon nanotube (MWCNT) decorated with bismuth oxide (Bi2O3) based on using the drop dry technique. Methods The prepared composite electrode was characterized by scanning electron microscopy–energy dispersive X-ray spectroscopy (SEM–EDS), Fourier transform infrared spectroscopy (FT-IR), and cyclic voltammetry (CV). Electrochemical techniques such as cyclic voltammetry, chronoamperometry, and square wave voltammetry (SWV) were used to study the behavior of paracetamol. Results The modification process improved the redox kinetics of paracetamol as shown by increased peak currents. The peak current varied linearly with increment of paracetamol concentration in the range of 0.02 to 28 μM with a sensitivity of 1.133 μA μM−1. A detection limit of 0.0052 μM was obtained. Conclusion The proposed method was successfully applied to determination of paracetamol in biological samples with recoveries in the range 94.3–98.7%.

A comprehensive analysis of indicators of the state of the body between training and recovery allows a comprehensive evaluation of various aspects of health, athletic performance, and recovery. In this pilot study, an assessment of the metabolomic profile of athletes was performed, and the immunological reaction of the athlete’s body to food before exercise and 48 h after exercise was studied. As a result, 15 amino acids and 3 hormones were identified, the plasma levels of which differed between the training and recovery states. In addition, immunological reactions or hyperreactivity to food allergens were assessed using an enzyme immunoassay. It is likely that for the athletes in the study sample, 48 h is not enough time for the complete recovery of the body.

A highly sensitive method for the qualitative and quantitative determination of amino- and carboxylic acids, as well as a number of urea and methionine cycle metabolites in the studied solutions, is presented. Derivatives (esterification) were obtained for amino acids by their reaction in a solution of 3 N of hydrochloric acid in n-butanol for 15 min at 65 °C and for carboxylic acids by their reaction with phenol in ethyl acetate with 3 N of hydrochloric acid for 20 min at 65 °C. Experimental work on the determination of individual metabolites was carried out using the HPLC-MS/MS method and included the creation of a library of spectra of the analyzed compounds and their quantitative determination. Multiplex methods have been developed for the quantitative analysis of the desired metabolites in a wide range of concentrations of 3–4 orders of magnitude. The approach to the analysis of metabolites was developed based on the method of the dynamic monitoring of multiple reactions of the formation of fragments for a mass analyzer with a triple quadrupole (QQQ). The effective chromatographic separation of endogenous metabolites was carried out within 13 min. The calibration curves of the analyzed compounds were stable throughout the concentration range and had the potential to fit below empirical levels. The developed methods and obtained experimental data are of interest for a wide range of biomedical studies, as well as for monitoring the content of endogenous metabolites in biological samples under various pathological conditions. The sensitivity limit of the methods for amino acids was about 4.8 nM and about 0.5 μM for carboxylic acids. Up to 19 amino- and up to 12 carboxy acids and about 10 related metabolites can be tested in a single sample.

Training and competitive periods can temporarily impair the performance of an athlete. This disruption can be short- or long-term, lasting up to several days. We analyzed the health indicators of 3661 athletes during an in-depth medical examination. At the time of inclusion in the study, the athletes were healthy. Instrumental examinations (fluorography, ultrasound examination of the abdominal cavity and pelvic organs, echocardiography, electrocardiography, and stress testing “to failure”), laboratory examinations (general urinalysis and biochemical and general clinical blood analysis), and examinations by specialists (ophthalmologist, otolaryngologist, surgeon, cardiologist, neurologist, dentist, gynecologist (women), endocrinologist, and therapist) were performed. This study analyzed the significance of determining the indicators involved in the implementation of the “catabolism” and “anabolism” phenotypes using the random forest and multinomial logistic regression machine learning methods. The use of decision forest and multinomial regression models made it possible to identify the most significant indicators of blood and urine biochemistry for the analysis of phenotypes as a characterization of the effectiveness of recovery processes in the post-competitive period in athletes. We found that the parameters of muscle metabolism, such as aspartate aminotransferase, creatine kinase, lactate dehydrogenase, and alanine aminotransferase levels, and the parameters of the ornithine cycle, such as creatinine, urea acid, and urea levels, made the most significant contribution to the classification of two types of metabolism: catabolism and anabolism.

A defining component of agroforestry parklands across Sahelo-Sudanian Africa (SSA), the shea tree (Vitellaria paradoxa) is central to sustaining local livelihoods and the farming environments of rural communities. Despite its economic and cultural value, however, not to mention the ecological roles it plays as a dominant parkland species, shea remains semi-domesticated with virtually no history of systematic genetic improvement. In truth, shea’s extended juvenile period makes traditional breeding approaches untenable; but the opportunity for genome-assisted breeding is immense, provided the foundational resources are available. Here we report the development and public release of such resources. Using the FALCON-Phase workflow, 162.6 Gb of long-read PacBio sequence data were assembled into a 658.7 Mbp, chromosome-scale reference genome annotated with 38,505 coding genes. Whole genome duplication (WGD) analysis based on this gene space revealed clear signatures of two ancient WGD events in shea’s evolutionary past, one prior to the Astrid-Rosid divergence (116–126 Mya) and the other at the root of the order Ericales (65–90 Mya). In a first genome-wide look at the suite of fatty acid (FA) biosynthesis genes that likely govern stearin content, the primary determinant of shea butter quality, relatively high copy numbers of six key enzymes were found (KASI, KASIII, FATB, FAD2, FAD3, and FAX2), some likely originating in shea’s more recent WGD event. To help translate these findings into practical tools for characterization, selection, and genome-wide association studies (GWAS), resequencing data from a shea diversity panel was used to develop a database of more than 3.5 million functionally annotated, physically anchored SNPs. Two smaller, more curated sets of suggested SNPs, one for GWAS (104,211 SNPs) and the other targeting FA biosynthesis genes (90 SNPs), are also presented. With these resources, the hope is to support national programs across the shea belt in the strategic, genome-enabled conservation and long-term improvement of the shea tree for SSA.

This paper reports on the design, and implementation of piezoelectric-on-silicon MEMS resonators installed within a portable experimental setup for sensing nanoparticles in a laboratory environment. MEMS oscillators with a center frequency of approximately 5.999 MHz are employed for sensing 50 nm size-selected silver nanoparticles generated in the laboratory. The same experimental setup is then assembled to sense indoor particles that are present in the laboratory environment. The challenges associated with particle deposition as a result of assembling the portable experimental setup is highlighted. Furthermore, the MEMS oscillators demonstrate that the total mass of silver nanoparticles deposited onto the MEMS resonator surface using the inertial impaction technique-based experimental setup is approximately 7.993 nanograms. The total indoor particle mass accumulated on the MEMS resonator surface is estimated to be approximately 1.732 nanograms and 26.9 picograms for two different runs. The frequency resolution of the MEMS oscillator is estimated to be approximately 32 ppb and, consequently, the minimum detectable particle mass is approximately 60 femtograms for a 9.2 s integration time.

Abstract The Weather Research and Forecasting model (WRF) was used to produce both 9 and 3 km resolution ensemble forecasts from the deterministic Global Forecast System (GFS) model for microclimatic, agricultural regions in New York State. The forecasts were then statistically post‐processed to generate probabilistic forecasts for surface temperature (T), specific humidity (q), incoming solar radiation (SR) and precipitation (P). T was post‐processed with non‐homogeneous Gaussian regression (NGR), q and SR with truncated NGR, and P with extended logistic regression. A comparison of forecast skill was conducted between these post‐processed forecasts, the raw WRF output, the GFS forecasts and forecasts from the National Weather Service's deterministic National Digital Forecast Database (NDFD). Overall, significant improvement was observed in post‐processed WRF forecasts over all other methods for all locations and variables. Furthermore, raw WRF ensembles were found to outperform deterministic NDFD, so that if observational data are unavailable for post‐processing, dynamically downscaled WRF should be selected over deterministic, human‐altered NDFD forecasts. Finally, the 9 km post‐processed WRF had the same forecast skill as the 3 km post‐processed WRF, except for precipitation, rendering the 3 km WRF unnecessary if observational data are available, saving computational cost.

Influence of vitamins C and E supplementation on flesh yields and proximate compositions of Clarias gariepinus fed diets contaminated with increasing doses of fumonisin B1 (FB1), an environmental mycotoxin produced by Fusarium verticillioides, was evaluated. A total of 780 juvenile fish were randomly stocked in completely randomized design into 13 groups. Fusarium verticillioides inoculated diets containing FB1 were used to formulate 12 diets containing approximately 2.5, 5.0, and 7.5 mg FB1/kg feed constituting diets 2, 3, and 4, respectively and nine other diets constituting diets 5–13 with the same varied dietary FB1 concentrations but supplemented with 0.6 g of vitamin C or E or vitamins C and E. The flesh and waste yields for the fish ranged from 54.35 ± 0.89 to 60.40 ± 3.40 and 32.60 ± 8.20 to 40.15 ± 1.11 respectively and were significantly influenced (P > 0.05) by the levels of FB1 contamination. The results of the proximate composition of crude protein (68.13 ± 0.32) and fat (12.74 ± 0.34) of fish fed diet 3 and control, respectively were significantly different (P

Abstract Background The accurate determination of parent-progeny relationships within both in situ natural populations and ex situ genetic resource collections can greatly enhance plant breeding/domestication efforts and support plant genetic resource conservation strategies. Although a range of parentage analysis tools are available, none are designed to infer such relationships using genome-wide single nucleotide polymorphism (SNP) data in the complete absence of guiding information, such as generational groups, partial pedigrees, or genders. The R package (‘apparent’) developed and presented here addresses this gap. Results ‘apparent’ adopts a novel strategy of parentage analysis based on a test of genetic identity between a theoretically expected progeny (EPij), whose genotypic state can be inferred at all homozygous loci for a pair of putative parents (i and j), and all potential offspring (POk), represented by the k individuals of a given germplasm collection. Using the Gower Dissimilarity metric (GD), genetic identity between EPij and POk is taken as evidence that individuals i and j are the true parents of offspring k. Significance of a given triad (parental pairij + offspringk) is evaluated relative to the distribution of all GDij|k values for the population. With no guiding information provided, ‘apparent’ correctly identified the parental pairs of 15 lines of known pedigree within a test population of 77 accessions of Actinidia arguta, a performance unmatched by five other commonly used parentage analysis tools. In the case of an inconclusive triad analysis due to the absence of one parent from the test population, ‘apparent’ can perform a subsequent dyad analysis to identify a likely single parent for a given offspring. Average dyad analysis accuracy was 73.3% in the complete absence of pedigree information but increased to 100% when minimal generational information (adults vs. progeny) was provided. Conclusions The ‘apparent’ R package is a fast and accurate parentage analysis tool that uses genome-wide SNP data to identify parent-progeny relationships within populations for which no a priori knowledge of family structure exists.

Inhibitory impairments may persist after abstinence in individuals with alcohol use disorder (AUD). Using traditional statistical parametric mapping (SPM) fMRI analysis, which requires data to satisfy parametric assumptions often difficult to satisfy in biophysical system as brain, studies have reported equivocal findings on brain areas responsible for response inhibition, and activation abnormalities during inhibition found in AUD persist after abstinence. Research is warranted using newer analysis approaches. fMRI scans were acquired during a Go/NoGo task from 30 abstinent male AUD and 30 healthy control participants with the objectives being (1) to characterize neuronal substrates associated with response inhibition using a rigorous nonparametric permutation-based fMRI analysis and (2) to determine whether these regions were differentially activated between abstinent AUD and control participants. A blood oxygen level dependent contrast analysis showed significant activation in several right cortical regions and deactivation in some left cortical regions during successful inhibition. The largest source of variance in activation level was due to group differences. The findings provide evidence of cortical substrates employed during response inhibition. The largest variance was explained by lower activation in inhibition as well as ventral attentional cortical networks in abstinent individuals with AUD, which were not found to be associated with length of abstinence, age, or impulsiveness.

Individuals with alcohol use disorder (AUD) may manifest an array of neural and behavioral abnormalities, including altered brain networks, impaired neurocognitive functioning, and heightened impulsivity. Using multidomain measures, the current study aimed to identify specific features that can differentiate individuals with AUD from healthy controls (CTL), utilizing a random forests (RF) classification model. Features included fMRI-based resting-state functional connectivity (rsFC) across the reward network, neuropsychological task performance, and behavioral impulsivity scores, collected from thirty abstinent adult males with prior history of AUD and thirty CTL individuals without a history of AUD. It was found that the RF model achieved a classification accuracy of 86.67% (AUC = 93%) and identified key features of FC and impulsivity that significantly contributed to classifying AUD from CTL individuals. Impulsivity scores were the topmost predictors, followed by twelve rsFC features involving seventeen key reward regions in the brain, such as the ventral tegmental area, nucleus accumbens, anterior insula, anterior cingulate cortex, and other cortical and subcortical structures. Individuals with AUD manifested significant differences in impulsivity and alterations in functional connectivity relative to controls. Specifically, AUD showed heightened impulsivity and hypoconnectivity in nine connections across 13 regions and hyperconnectivity in three connections involving six regions. Relative to controls, visuo-spatial short-term working memory was also found to be impaired in AUD. In conclusion, specific multidomain features of brain connectivity, impulsivity, and neuropsychological performance can be used in a machine learning framework to effectively classify AUD individuals from healthy controls.

Renalase (RNLS) is a recently discovered protein involved in blood pressure regulation. It exists both as an intracellular catalytically active flavoprotein (EC 1.6.3.5 dihydro-NAD(P):oxygen oxidoreductase) and an extracellular protein that demonstrates various cell protecting effects. Using a twenty-membered peptide corresponding to the residues 220–239 of the renalase sequence (RP-220) and the HK-2 cell line Wang et al. identified a renalase-binding protein, which was considered as a receptor for extracellular renalase crucial for MAPK signaling (Wang et al., 2015) [1]. In this study we have investigated profiles of renalase binding proteins in HEK293 cells by using affinity based proteomic profiling with full-length recombinant human RNLS-1 and human RNLS-2 as affinity ligands followed by analysis of bound proteins by liquid chromatography-mass spectrometry. Both renalases (RNLS-1 and RNLS-2) contain the RP-220 sequence (residues 220–239) but differ in their C-terminal region (residues 293–342 and 293–325, respectively). Profiling of HEK293 proteins resulted in identification of two different sets of proteins specifically bound to RNLS-1 and RNLS-2, respectively. We thus demonstrate that the C-terminal region is crucial for specific binding of renalase to its targets and/or receptors. Keywords: Renalase, Renalase-binding protein, RP-220 peptide, Affinity-based proteomic profiling, LC–MS

Despite the interwoven nature of platelet activation and the coagulation system in thrombosis, few studies relate both analysis of protein and cellular parts of coagulation in the same population. In the present study, we use matched ex vivo samples to determine the influences of standard antiplatelet therapies on platelet function and use advanced rheological analyses to assess clot formation. Healthy volunteers were recruited following fully informed consent then treated for 7 days with single antiplatelet therapy of aspirin (75 mg) or prasugrel (10 mg) or with dual antiplatelet therapy (DAPT) using aspirin (75 mg) plus prasugrel (10 mg) or aspirin (75 mg) plus ticagrelor (90 mg). Blood samples were taken at day 0 before treatment and at day 7 following treatment. We found that aspirin plus prasugrel or aspirin plus ticagrelor inhibited platelet responses to multiple agonists and reduced P-selectin expression. Significant platelet inhibition was coupled with a reduction in fractal dimension corresponding to reductions in mean relative mass both for aspirin plus prasugrel (−35 ± 16% change, p = 0.04) and for aspirin plus ticagrelor (−45 ± 14% change, p = 0.04). Aspirin alone had no effect upon measures of clot structure, whereas prasugrel reduced fractal dimension and mean relative mass. These data demonstrate that platelets are important determinants of clot structure as assessed by fractal dimension (df) and that effective platelet inhibition is associated with a weaker, more permeable fibrin network. This indicates a strong association between the therapeutic benefits of antiplatelet therapies and their abilities to reduce thrombus density that may be useful in individual patients to determine the functional relationship between platelet reactivity, eventual clot quality, and clinical outcome. df could represent a novel risk stratification biomarker useful in individualizing antiplatelet therapies.

Nutrition is considered one of the foundations of athletic performance, and post-workout nutritional recommendations are fundamental to the effectiveness of the recovery and adaptive processes. Therefore, at present, new directions in dietetics are being formed, focused on the creation of personalized diets. To identify the probable risk of somatic and allergic reactions upon contact with food antigens, we used the method of enzyme-linked immunosorbent assay (ELISA) for the quantitative determination of IgG antibodies in the blood plasma of athletes against protein–peptide antigens accommodated in food. The study enrolled 40 athletes of boating and fighting sport disciplines. We found that the majority of the studied participants were characterized by an elevated IgG level against one or two food allergens (barley, almond, strawberry, etc.). Comparative analysis of the semiquantitative levels of IgG antibodies in athletes engaged in boating and fighting did not reveal significant differences between these groups. As a result, foods that are likely to cause the most pronounced immune response amongst the studied participants can be identified, which may indicate the presence of food intolerances. An athlete’s diet is influenced by both external and internal factors that can reduce or worsen the symptoms of a food intolerance/allergy associated with exercise. The range of foods is wide, and the effectiveness of a diet depends on the time, the place, and environmental factors. Therefore, during the recovery period (the post-competition period), athletes are advised to follow the instructions of doctors and nutritionists. An effective, comprehensive recovery strategy during the recovery period may enhance the adaptive response to fatigue, improving muscle function and increasing exercise tolerance. The data obtained may be useful for guiding the development of a new personalized approach and dietary recommendations covering the composition of athletes’ diet and the prevalence of food intolerance.

Post-translational modification (PTM) leads to conformational changes in protein structure, modulates the biological function of proteins, and, consequently, changes the signature of metabolic transformations and the immune response in the body. Common PTMs are reversible and serve as a mechanism for modulating metabolic trans-formations in cells. It is likely that dysregulation of post-translational cellular signaling leads to abnormal proliferation and oncogenesis. We examined protein PTMs in the blood samples from patients with kidney cancer. Conformational changes in proteins after modification were analyzed. The proteins were analyzed using ultra-high resolution HPLC-MS/MS and structural analysis was performed with the AMBER and GROMACS software packages. Fifteen proteins containing PTMs were identified in blood samples from patients with kidney cancer. For proteins with PDB structures, a comparative analysis of the structural changes accompanying the modifications was performed. Results revealed that PTMs are localized in stable and compact space protein globule motifs that are exposed to a solvent. The phenomenon of modification is accompanied, as a rule, by an increase in the area available for the solvent of the modified amino acid residue and its active environment.

Background Existing data on predictors of late mortality and prevention of sudden cardiac death after atrial switch repair surgery for D‐transposition of the great arteries (D‐TGA) are heterogeneous and limited by statistical power. Methods and Results We conducted a systematic review and meta‐analysis of 29 observational studies, comprising 5035 patients, that reported mortality after atrial switch repair with a minimum follow‐up of 10 years. We also examined 4 additional studies comprising 105 patients who reported rates of implantable cardioverter‐defibrillator therapy in this population. Average survival dropped to 65% at 40 years after atrial switch repair, with sudden cardiac death accounting for 45% of all reported deaths. Mortality was significantly lower in cohorts that were more recent and operated on younger patients. Patient‐level risk factors for late mortality were history of supraventricular tachycardia (odds ratio [OR] 3.8, 95% CI 1.4–10.7), Mustard procedure compared with Senning (OR 2.9, 95% CI 1.9–4.5) and complex D‐TGA compared with simple D‐TGA (OR 4.4, 95% CI 2.2–8.8). Significant risk factors for sudden cardiac death were history of supraventricular tachycardia (OR 4.7, 95% CI 2.2–9.8), Mustard procedure (OR 2.2, 95% CI 1.1–4.1), and complex D‐TGA (OR 5.7, 95% CI 1.8–18.0). Out of a total 124 implantable cardioverter‐defibrillator discharges over 330 patient‐years in patients with implantable cardioverter‐defibrillators for primary prevention, only 8% were appropriate. Conclusions Patient‐level risk of both mortality and sudden cardiac death after atrial switch repair are significantly increased by history of supraventricular tachycardia, Mustard procedure, and complex D‐TGA. This knowledge may help refine current selection practices for primary prevention implantable cardioverter‐defibrillator implantation, given disproportionately high rates of inappropriate discharges.

Since its inception in 1983, NOAA&apos;s Regional Climate Center (RCC) Program has been providing timely, customized climate services for decision making across all climate-sensitive sectors. Through this 40-yr period, the RCC Program has not only seen but also has played an active role in, the evolution of climate services from the days of climate data libraries--where books of data were consulted to fulfill simple data requests--to coproduced tools that can calculate sectoral-specific, on-the-fly climate analyses in a matter of seconds. With new technologies emerging, the RCC Program is poised to build on its reputation as a trusted climate service provider by incorporating advanced methods for climate service delivery to continue to meet the needs of the nation. This publication will provide a look back at the evolution of regional climate services over the past 40 years, along with a vision for the future. KEYWORDS: Climate services; Decision support; History, 1. Celebrating 40 years of the Regional Climate Center Program The Regional Climate Center (RCC) Program has its roots in the National Climate Program Act of 1978, which recognized the [...]