Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of mDurance, A Wearable Surface Electromyography System for Muscle Activity Assessment

The mDurance® system is an innovative digital tool that combines wearable surface electromyography (sEMG), mobile computing and cloud analysis to streamline and automatize the assessment of muscle activity. The tool is particularly devised to support clinicians and sport professionals in their daily routines, as an assessment tool in the prevention, monitoring rehabilitation and training field. This study aimed at determining the validity of the mDurance system for measuring muscle activity by comparing sEMG output with a reference sEMG system, the Delsys® system. Fifteen participants were tested during isokinetic knee extensions at three different speeds (60, 180, and 300 deg/s), for two muscles (rectus femoris [RF] and vastus lateralis [VL]) and two different electrodes locations (proximal and distal placement). The maximum voluntary isometric contraction was carried out for the normalization of the signal, followed by dynamic isokinetic knee extensions for each speed. The sEMG output for both systems was obtained from the raw sEMG signal following mDurance's processing and filtering. Mean, median, first quartile, third quartile and 90th percentile was calculated from the sEMG amplitude signals for each system. The results show an almost perfect ICC relationship for the VL (ICC > 0.81) and substantial to almost perfect for the RF (ICC > 0.762) for all variables and speeds. The Bland-Altman plots revealed heteroscedasticity of error for mean, quartile 3 and 90th percentile (60 and 300 deg/s) for RF and at mean and 90th percentile for VL (300 deg/s). In conclusion, the results indicate that the mDurance® sEMG system is a valid tool to measure muscle activity during dynamic contractions over a range of speeds. This innovative system provides more time for clinicians (e.g., interpretation patients' pathologies) and sport trainers (e.g., advising athletes), thanks to automatic processing and filtering of the raw sEMG signal and generation of muscle activity reports in real-time.
Estimation of Major Adverse Cardiovascular Events in Patients With Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: A Risk Prediction Score Model From a Derivation and Validation Study

Background: The population with myocardial infarction (MI) undergoing primary percutaneous coronary intervention (PPCI) is growing, but validated models to guide their clinical management are lacking. This study aimed to develop and validate prognostic models to predict major adverse cardiovascular events (MACEs) in patients with MI undergoing PPCI. Methods and Results: Models were developed in 4,151 patients with MI who underwent PPCI in Fuwai Hospital between January 2010 and June 2017, with a median follow-up of 698 days during which 544 MACEs occurred. The predictors included in the models were age, a history of diabetes mellitus, atrial fibrillation, chronic kidney disease, coronary artery bypass grafting, the Killip classification, ejection fraction at admission, the high-sensitivity C-reactive protein (hs-CRP) level, the estimated glomerular filtration rate, the d-dimer level, multivessel lesions, and the culprit vessel. The models had good calibration and discrimination in the derivation and internal validation with C-indexes of 0.74 and 0.60, respectively, for predicting MACEs. The new prediction model and Thrombolysis in Myocardial Infarction (TIMI) risk score model were compared using the receiver operating characteristic curve. The areas under the curve of the new prediction model and TIMI risk score model were 0.806 and 0.782, respectively (difference between areas = 0.024 < 0.05; z statistic, 1.718). Conclusion: The new prediction model could be used in clinical practice to support risk stratification as recommended in clinical guidelines.
Determinants of Host Range Specificity in Legume-Rhizobia Symbiosis

Leguminous plants possess the almost unique ability to enter symbiosis with soil-resident, nitrogen fixing bacteria called rhizobia. During this symbiosis, the bacteria physically colonize specialized organs on the roots of the host plant called nodules, where they reduce atmospheric nitrogen into forms that can be assimilated by the host plant and receive photosynthates in return. In order for nodule development to occur, there is extensive chemical cross-talk between both parties during the formative stages of the symbiosis. The vast majority of the legume family are capable of forming root nodules and typically rhizobia are only able to fix nitrogen within the context of this symbiotic association. However, many legume species only enter productive symbiosis with a few, or even single rhizobial species or strains, and vice-versa. Permitting symbiosis with only rhizobial strains that will be able to fix nitrogen with high efficiency is a crucial strategy for the host plant to prevent cheating by rhizobia. This selectivity is enforced at all stages of the symbiosis, with partner choice beginning during the initial communication between the plant and rhizobia. However, it can also be influenced even once nitrogen-fixing nodules have developed on the root. This review sets out current knowledge about the molecular mechanisms employed by both parties to influence host range during legume-rhizobia symbiosis.
Progress in the Pathogenesis, Diagnosis, and Treatment of TSH-Secreting Pituitary Neuroendocrine Tumor

TSH-secreting pituitary neuroendocrine tumor (PitNET) is one of the causes of central hyperthyroidism. The incidence of TSH PitNET is far lower than that of other PitNETs. The clinical manifestations of TSH PitNETs mainly include thyrotoxicosis or thyroid goiter, secretion disorders of other anterior pituitary hormones, and mass effect on the pituitary gland and its surrounding tissues. The application of high-sensitivity TSH detection methods contributes to the early diagnosis and timely treatment of TSH PitNETs. Improvements in magnetic resonance imaging (MRI) have advanced the noninvasive visualization of smaller PitNETs. Treatments for TSH PitNETs include surgery, drugs, and radiotherapy. This review focuses on the progress in pathogenesis, diagnosis, and treatment of TSH PitNETs to provide more information for the clinician.
Environmental Gradients and Spatial Patterns of Calanoid Copepods in the Southeast Pacific

Understanding the mechanisms maintaining the biodiversity of plankton communities in marine ecosystems subject to a strongly variable ocean has become a critical issue for modern oceanography. Here, we used data on distribution of calanoid copepods in the upper layer of the ocean (0–500 m), a widely distributed taxonomic group in the pelagic realm, to assess the effects of changing oceanographic conditions on their diversity patterns and family and species richness. Copepods abundance and occurrence were evaluated from 2002 to 2015 covering the region extended between the coastal upwelling zone (CUP-Z) and the offshore region of Chile at subtropical and temperate areas. We used spatial analyses of community structure descriptors, such as abundance and diversity (family and species richness), multivariate analysis and General Additive Models (GAMS) in order to study the effect of surface temperature and its gradients, mixed layer depth, salinity and Chlorophyll-a on copepod diversity. Seventeen families were identified comprising 151 species distributed in 3 predefined zones in the onshore-offshore gradient covering the coastal upwelling, the coastal transition and the oligotrophic zones, whereas over the alongshore gradient, same families were majorly linked to the northern and southern portions of the sampled area (20–40°S). Families and species were significantly structured over the zonal gradient, revealing the dominant habitat for each of the families. Spatial patterns revealed the presence of transitional zones comprised by mixed taxa. Over the alongshore gradient this transition zone was linked to the subtropical convergence (30°S). The spatial variation of sea surface temperature (SST) revealed strong environmental zonation of temperature gradients across onshore-offshore and alongshore dimensions. Mean SST combined with mean mixed layer depth explained about 40% and about 29% of variation in family and species richness, respectively over the onshore-offshore axis. We thus conclude that the environmental zonation imposed by SST and its spatial gradients, considered as ecological barriers, is the key driver for maintaining diversity of copepods in the southeast Pacific.
Effects of IL-1β and TNF-α on the Expression of P311 in Vascular Endothelial Cells and Wound Healing in Mice

Objective This study aimed to define the role of interleukine-1β (IL-1β) and tumor necrosis factor-α (TNF-α) in the expression of P311 in vascular endothelial cells (VECs) and in wound healing. Methods DAPI staining, a CCK-8 assay, cell migration assay, and an angiogenesis assay were used to assess the effects exerted by TNF-α and IL-1β at various concentrations on morphology, proliferation, migration, and angiogenesis of VECs. Western blot (WB) and reverse transcription-polymerase chain reaction (RT-PCR) models were employed to observe the effects exerted by proteins related to the nuclear factor-kappa B (NF-κB) signaling pathway and P311 mRNA expression. Bioinformatics analysis was performed on the binding sites of P311 and NF-κB. Finally, to investigate the effects of IL-1β and TNF-α on wound healing and the length of new epithelium in mice, we established a full-thickness wound defect model in mice. Immunohistochemistry was used to measure changes in P311, proliferating cell nuclear antigen (PCNA), vascular endothelial growth factor (VEGF), CD31 (platelet endothelial cell adhesion molecule-1, PECAM-1/CD31), as well as other related proteins. Results When levels of TNF-α and IL-1β were both 20 ng/ml, their effects on cell proliferation, cytoskeleton protein expression, cell migration, and angiogenesis were the greatest (P < 0.05). IL-1β and TNF-α at moderate concentrations effectively promoted P311 mRNA and p-NF-κB protein expression (P < 0.05), while p-NF-K b protein expression was decreased (P < 0.05). Luciferase assays showed that P311 expression was also relatively greater when stimulated at moderate concentrations (P < 0.05), while relative expression was significantly lower when the p-NF-K b inhibitor CAPE was added (P < 0.05). On 7-day wound healing rate comparison, the control, IL-1β, IL-1βab, TNF-α, and TNF-αab groups were 18, 37, 35, 39, and 36%, respectively, while control group + P311 siRNA was 31% (P < 0.05). New epithelial length, granulation tissue thickness, and number of blood vessels trends were also the same. In the control group, P311 showed lower relative expression levels than the others (P < 0.05). P311 relative expression levels trended as follows: control group > IL-1βab > IL-1β > TNF-αab > TNF-α (P < 0.05). Conclusion When IL-1β and TNF-α concentrations are moderate, they effectively promote the proliferation, expression, migration, and angiogenesis of VECs, possibly by promoting the expression of the NF-K b pathway and thereby promoting the expression of P311. In vitro experiments on mice suggest that P311 effectively promotes wound healing, and its mechanism may be closely related to PCNA, CD31, and VEGF.
The female (XX) and male (YY) genomes provide insights into the sex determination mechanism in spinach

Sexual reproduction is the primary means of reproduction for the vast majority of macroscopic organisms, including almost all animals and plants. Sex chromosomes are predicted to play a central role in sexual dimorphism. Sex determination in spinach is controlled by a pair of sex chromosomes. However, the mechanisms of sex determination in spinach remain poorly understand. Here, we assembled the genomes of both a female (XX) and a male (YY) individual of spinach, and the genome sizes were 978 Mb with 28,320 predicted genes and 926 Mb with 26,537 predicted genes, respectively. Based on reported sex-linked markers, chromosomes 4 of the female and male genome were defined as the X and Y chromosomes, and a 10 Mb male-specific region of the Y chromosome (MSY) from approximately 95– 105 Mb, was identified that contains abundant transposable elements (92.32%). Importantly, a large-scale inversion of about 13 Mb in length was detected on the X chromosome, corresponding to ~9 Mb and ~4 Mb on the Y chromosome, which were located on both sides of the MSY with two distinct evolutionary strata. Almost all sex-linked/Y-specific markers were enriched on the inversions/MSY, suggesting that the flanked inversions might result in recombination suppression between the X and Y chromosomes to maintain the MSY. Forty-nine genes within the MSY had functional homologs elsewhere in the autosomal region, suggesting movement of genes onto the MSY. The X and Y chromosomes of spinach provide a valuable resource for investigating spinach sex chromosomes evolution from wild to cultivated spinach and also provide a broader understanding of the sex determination model in the Amaranthaceae family.
Three-dimensional ATUM-SEM reconstruction and analysis of hepatic endoplasmic reticulum‒organelle interactions

The endoplasmic reticulum (ER) is a contiguous and complicated membrane network in eukaryotic cells, and membrane contact sites (MCSs) between the ER and other organelles perform vital cellular functions, including lipid homeostasis, metabolite exchange, calcium level regulation, and organelle division. Here, we establish a whole pipeline to reconstruct all ER, mitochondria, lipid droplets, lysosomes, peroxisomes, and nuclei by automated tape-collecting ultramicrotome scanning electron microscopy (ATUM-SEM) and deep-learning techniques, which generates an unprecedented 3D model for mapping liver samples. Furthermore, the morphology of various organelles is systematically analyzed. We found that the ER presents with predominantly flat cisternae and is knitted tightly all throughout the intracellular space and around other organelles. In addition, the ER has a smaller volume-to-membrane surface area ratio than other organelles, which suggests that the ER could be more suited for functions that require a large membrane surface area. Moreover, the MCSs between the ER and other organelles are explored. Our data indicate that ER-mitochondrial contacts are particularly abundant, especially for branched mitochondria. In addition, ER contacts with lipid droplets, lysosomes, and peroxisomes are also plentiful. In summary, we design an efficient method for obtaining a 3D reconstruction of biological structures at a nanometer resolution. Our study also provides the first 3D reconstruction of various organelles in liver samples together with important information fundamental for biochemical and functional studies in the liver.
DELocal: Chromosomal neighbourhoods having genes of diverse functions allow improved identification of differentially expressed genes

Exploration of genetically modified organisms, developmental processes, diseases or responses to various treatments require accurate measurement of changes in gene expression. This can be done for thousands of genes using high throughput technologies such as microarray and RNAseq. However, identification of differentially expressed (DE) genes poses technical challenges due to limited sample size, few replicates, or simply very small changes in expression levels. Consequently, several methods have been developed to determine DE genes, such as Limma, RankProd, SAM, and DeSeq2. These methods identify DE genes based on the expression levels alone. As genomic co-localization of genes is generally not linked to co-expression, we deduced that DE genes could be detected with the help of genes from chromosomal neighbourhood. Here, we present a new method, DELocal, which identifies DE genes by comparing their expression changes to changes in adjacent genes in their chromosomal regions. Our results show that DELocal provides distinct benefits in the identification of DE genes. Furthermore, our comparative analysis of the dispersal of genes with related functions suggests that DELocal is applicable to a wide range of developmental systems. With increasing availability of genomic data, gene neighbourhood can become a powerful tool to detect differential expression.
Microglia: A Potential Therapeutic Target for Sepsis-Associated Encephalopathy and Sepsis-Associated Chronic Pain

Neurological dysfunction, one of the severe manifestations of sepsis in patients, is closely related to increased mortality and long-term complications in intensive care units, including sepsis-associated encephalopathy (SAE) and chronic pain. The underlying mechanisms of these sepsis-induced neurological dysfunctions are elusive. However, it has been well established that microglia, the dominant resident immune cell in the central nervous system, play essential roles in the initiation and development of SAE and chronic pain. Microglia can be activated by inflammatory mediators, adjacent cells and neurotransmitters in the acute phase of sepsis and then induce neuronal dysfunction in the brain. With the spotlight focused on the relationship between microglia and sepsis, a deeper understanding of microglia in SAE and chronic pain can be achieved. More importantly, clarifying the mechanisms of sepsis-associated signaling pathways in microglia would shed new light on treatment strategies for SAE and chronic pain.
Wrangling Shape-Shifting Morpheeins to Tackle Disease and Approach Drug Discovery

Homo-multimeric proteins that can come apart, change shape, and reassemble differently with functional consequences have been called morpheeins and/or transformers; these provide a largely unexplored context for understanding disease and developing allosteric therapeutics. This article describes such proteins within the context of protein structure dynamics, provides one detailed example related to an inborn error of metabolism and potential herbicide development, and describes the context for applying these ideas for understanding disease and designing bioactive molecules, such as therapeutics.
NeuroGPU: Accelerating multi-compartment, biophysically detailed neuron simulations on GPUs

The membrane potential of individual neurons depends on a large number of interacting biophysical processes operating on spatial-temporal scales spanning several orders of magnitude. The multi-scale nature of these processes dictates that accurate prediction of membrane potentials in specific neurons requires utilization of detailed simulations. Unfortunately, constraining parameters within biologically detailed neuron models can be difficult, leading to poor model fits. This obstacle can be overcome partially by numerical optimization or detailed exploration of parameter space. However, these processes, which currently rely on central processing unit (CPU) computation, often incur exponential increases in computing time for marginal improvements in model behavior. As a result, model quality is often compromised to accommodate compute resources. Here, we present a simulation environment, NeuroGPU, that takes advantage of the inherent parallelized structure of graphics processing unit (GPU) to accelerate neuronal simulation. NeuroGPU can simulate most of biologically detailed models 800x faster than traditional simulators when using multiple GPU cores, and even 10-200 times faster when implemented on relatively inexpensive GPU systems. We demonstrate the power of NeuoGPU through large-scale parameter exploration to reveal the response landscape of a neuron. Finally, we accelerate numerical optimization of biophysically detailed neuron models to achieve highly accurate fitting of models to simulation and experimental data. Thus, NeuroGPU enables the rapid simulation of multi-compartment, biophysically detailed neuron models on commonly used computing systems accessible by many scientists.
Genetic sensitivity analysis: Adjusting for genetic confounding in epidemiological associations

Associations between exposures and outcomes reported in epidemiological studies are typically unadjusted for genetic confounding. We propose a two-stage approach for estimating the degree to which such observed associations can be explained by genetic confounding. First, we assess attenuation of exposure effects in regressions controlling for increasingly powerful polygenic scores. Second, we use structural equation models to estimate genetic confounding using heritability estimates derived from both SNP-based and twin-based studies. We examine associations between maternal education and three developmental outcomes – child educational achievement, Body Mass Index, and Attention Deficit Hyperactivity Disorder. Polygenic scores explain between 14.3% and 23.0% of the original associations, while analyses under SNP- and twin-based heritability scenarios indicate that observed associations could be almost entirely explained by genetic confounding. Thus, caution is needed when interpreting associations from non-genetically informed epidemiology studies. Our approach, akin to a genetically informed sensitivity analysis can be applied widely. Author summary An objective shared across the life, behavioural, and social sciences is to identify factors that increase risk for a particular disease or trait. However, identifying true risk factors is challenging. Often, a risk factor is statistically associated with a disease even if it is not really relevant, meaning that even successfully improving the risk factor will not impact the disease. One reason for the existence of such misleading associations stems from genetic confounding. This is when genetic factors influence both the risk factor and the disease, which generates a statistical association even in the absence of a true effect of the risk factor. Here, we propose a method to estimate genetic confounding and quantify its effect on observed associations. We show that a large part of the associations between maternal education and three child outcomes - educational achievement, body mass index and Attention-Deficit Hyperactivity Disorder-is explained by genetic confounding. Our findings can be applied to better understand the role of genetics in explaining associations of key risk factors with diseases and traits.
Inhibition of SARS-CoV-2 main protease by allosteric drug-binding

The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous health problems and economical challenges for mankind. To date, no effective drug is available to directly treat the disease and prevent virus spreading. In a search for a drug against COVID-19, we have performed a massive X-ray crystallographic screen of two repurposing drug libraries against the SARS-CoV-2 main protease (Mpro), which is essential for the virus replication and, thus, a potent drug target. In contrast to commonly applied X-ray fragment screening experiments with molecules of low complexity, our screen tested already approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds binding to Mpro. In subsequent cell-based viral reduction assays, one peptidomimetic and five non-peptidic compounds showed antiviral activity at non-toxic concentrations. We identified two allosteric binding sites representing attractive targets for drug development against SARS-CoV-2.