Miracle-dz/UniFAR-FTUs huggingface dataset:
The Inclusion of Water Molecules in Residue Interaction Networks Identifies Additional Central Residues

The relevance of water molecules for the recognition and the interaction of biomolecules is widely appreciated. In this paper we address the role that water molecules associated to protein complexes play for the functional relevance of residues by considering their residue interaction networks (RINs). These are commonly defined on the basis of the amino acid composition of the proteins themselves, disregarding the solvation state of the protein. We determine properties of the RINs of two protein complexes, colicin E2/Im2 and barnase/barstar, with and without associated water molecules, using a previously developed methodology and its associated application RINspector. We find that the inclusion of water molecules in RINs leads to an increase in the number of central residues which adds a novel mechanism to the relevance of water molecules for protein function.
Sex- and Age-Specific Optimal Anthropometric Indices as Screening Tools for Metabolic Syndrome in Chinese Adults

Objectives To compare the predictive ability of six anthropometric indices for identification of metabolic syndrome (MetS) and to determine their optimal cut-off points among Chinese adults. Methods A total of 59,029 participants were enrolled. Body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), and conicity index (CI) were measured. Receiver-operating characteristic curves analyses were performed to determine the discriminatory power of these indices for the identification of cardiometabolic risks and diagnosis of MetS. The differences in the area under the curve (AUC) values among the indices were evaluated. The Youden index was used to determine the optimal cut-off points. Results WHtR and BRI exhibited the highest AUC values for identifying MetS and most cardiometabolic risk factors in both sexes, whereas ABSI showed the lowest AUC value. The general optimal cut-off points in women were 23.03 kg/m2 for BMI, 77.25 cm for WC, 0.490 for WHtR, and 3.179 for BRI; those in men were 24.64 kg/m2 for BMI, 87.25 cm for WC, 0.510 for WHtR, and 3.547 for BRI. The AUC values and cut-off points of the indices were also analyzed in each age and BMI category. Conclusions In Chinese adults, WHtR and BRI showed a superior predictive power for MetS in both sexes, which can be used as simple and effective screening tools for cardiometabolic risks and MetS in clinical practice.
RiboProP: a probabilistic ribosome positioning algorithm for ribosome profiling

MOTIVATION Ribosome profiling has been widely used to study translation in a genome-wide fashion. It requires deep sequencing of ribosome protected mRNA fragments followed by mapping of fragments to the reference genome. For applications such as identification of ribosome pausing sites, it is not enough to map a fragment to a given gene, but the exact position of the ribosome represented by the fragment must be identified for each mRNA fragment. The assignment of the correct ribosome position is complicated by the broad length distribution of the ribosome protected fragments caused by the known sequence bias of micrococcal nuclease (MNase), the most widely used nuclease for digesting mRNAs in bacteria. Available mapping algorithms suffer from either MNase bias or low accuracy in characterizing the ribosome pausing kinetics. RESULTS In this paper, we introduce a new computational method for mapping the ribosome protected fragments to ribosome locations. We first develop a mathematical model of the interplay between MNase digestion and ribosome protection of the mRNAs. We then use the model to reconstruct the ribosome occupancy profile on a per gene level. We demonstrate that our method has the capability of mitigating the sequence bias introduced by MNase and accurately locating ribosome pausing sites at codon resolution. We believe that our method can be broadly applied to ribosome profiling studies on bacteria where codon resolution is necessary. AVAILABILITY AND IMPLEMENTATION Source code implementing our approach can be downloaded under GPL3 license at http://bioserv.mps. ohio-state.edu/RiboProP. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Coupling of oxidative stress responses to tricarboxylic acid cycle and prostaglandin E2 alterations in Caenorhabditis elegans under extremely low-frequency electromagnetic field

Abstract Purpose: With all-pervasive presence of extremely low-frequency electromagnetic field (ELF-EMF) in modern life, ELF-EMF has been regarded as an essential factor which may induce changes in many organisms. The objective of the present study was to investigate the physiological responses of Caenorhabditis elegans (C. elegans) to 50 Hz, 3 mT ELF-EMF exposure. Materials and methods: Worms were exposed to ELF-EMF from the egg stage until reaching the fourth larva (L4) stage. After exposure, expressions of the tricarboxylic acid (TCA) cycle enzymes were examined by qRT-PCR and western blot analysis. Two lipid metabolites were detected by GC-MS. Reactive oxygen species (ROS) level was detected by dichlorofluorescein staining and worm antioxidant system was investigated by enzymatic activity analysis, including detection of the superoxide dismutase and catalase (CAT) activity and the total antioxidant capacity (T-AOC). Results: The TCA cycle enzyme, fumarase was found with decreased expression under ELF-EMF exposure. And arachidonic acid (ArA) and prostaglandin E2(PGE2) showed elevated concentrations, with increased expression of prostaglandin E2 synthase (PGES-2) in ELF-EMF exposed worms. Significant elevation of ROS level was identified accompanied with the significant depression of T-AOC in response to ELF-EMF. Conclusions: Our results suggested that exposure to 50 Hz, 3 mT ELF-EMF in C. elegans can elicit disruptions of the TCA cycle metabolism and PGE2 formation, coupling ELF-EMF-induced oxidative stress responses. Our study probably will attract increasing attentions to the controllable application of ELF-EMF associated with health and disease.
Validity and reliability of a novel optoelectronic device to measure movement velocity, force and power during the back squat exercise

ABSTRACT This study analysed the validity and reliability of a new optoelectronic device (Velowin) for the measurement of vertical displacement and velocity as well as to estimate force and mechanical power. Eleven trained males with Mean (SD) age = 27.4 (4.8) years, completed an incremental squat exercise test with 5 different loads (<30–90% of their 1−repetition maximum) while displacement and vertical velocity of the barbell were simultaneously measured using an integrated 3D system (3D motion capture system + force platform) and Velowin. Substantial to almost perfect correlation (concordance correlation coefficient = 0.75–0.96), root mean square error as coefficient of variation ±90% confidence interval ≤10% and good to excellent intraclass correlation coefficient = 0.84–0.99 were determined for all the variables. Passing and Bablock regression methods revealed no differences for average velocity. However, significant but consistent bias were determined for average or peak force and power while systematic and not proportional bias was found for displacement. In conclusion, Velowin, in holds of some potential advantages over traditionally used accelerometer or linear transducers, represents a valid and reliable alternative to monitor vertical displacement and velocity as well as to estimate average force and mechanical power during the squat exercise.
Embryonic myosin is a regeneration marker to monitor utrophin-based therapies for DMD

Abstract Duchenne muscular dystrophy (DMD) is a lethal, X-linked muscle-wasting disease caused by lack of the cytoskeletal protein dystrophin. Constitutive utrophin expression, a structural and functional paralogue of dystrophin, can successfully prevent the dystrophic pathology in the dystrophin-deficient mdx mouse model. In dystrophic muscles, utrophin is increased as part of the repair process and localized at the sarcolemma of regenerating myofibers. The presence of developmental myosin such as embryonic myosin (MyHC-emb) and neonatal represents a useful marker of muscle regeneration and a meaningful indicator of muscle damage, which correlates with the clinical severity of milder Becker muscular dystrophy and DMD patients. In the present study, we demonstrate that MyHC-emb is a robust marker of regeneration at different ages and in different skeletal muscles. We also evaluate the correlation between utrophin, dystrophin and MyHC-emb in wild-type (wt) and regenerating dystrophic muscles. Restoration of dystrophin significantly reduced MyHC-emb levels. Similarly, overexpression of utrophin in the transgenic mdx-Fiona mice reduced the number of MyHC-emb positive fibers to wt level, prevented the regenerative process and rescued the muscle function. In contrast, the absence of utrophin in the dystrophin-deficient double-knockout mice resulted in a higher MyHC-emb content and in a more severe dystrophic pathophysiology than in mdx mice. These data illustrate the importance of monitoring utrophin and MyHC-emb levels in the preclinical evaluation of therapies and provide translational support for the use of developmental myosin as a disease biomarker in DMD clinical trials.
Modification of unscented Kalman filter using a set of scaling parameters

This work, based on the standard unscented Kalman filter (UKF), proposes a modified UKF for highly non-linear stochastic systems, assuming that the associated probability distributions are normal. In the standard UKF with 2n + 1 sample points, the estimated mean and covariance match the true mean and covariance up to the third order, besides, there exists a scaling parameter that plays a crucial role in minimising the fourth-order errors. The proposed method consists of a computationally efficient formulation of the unscented transform that incorporates N − 1 , N ≥ 2 , constant parameters to scale 2 n ( N − 1 ) + 1 sample points such that the 2 N th order errors are minimised. The scaling parameters are obtained by solving a set of algebraic equations. Through rigorous analytical processes and numerical simulations, it is demonstrated that the new filter provides consistent estimates and the estimation error of the modified UKF is smaller than that of the standard UKF. With the help of a well-studied case, univariate non-stationary growth model, the authors evaluate the estimation performance of the new technique using 4n + 1 sample points over 100 independent runs.
Association Between Environmental Factors and Oral Epstein-Barr Virus DNA Loads: A Multicenter Cross-sectional Study in China

Background Oral Epstein-Barr virus (EBV) status reflects host EBV activity and potentially links to EBV-associated diseases, however, factors influencing oral EBV loads or reactivation, such as environmental exposures or host factors, are not fully understood. Methods A 2-stage, multicenter, cross-sectional study of 6558 subjects from 21 administrative cities of southern China and 3 populations from representative geographical areas in China (referred to as the south, north, and northeastern populations) was performed. The relationships between demographical factors and environmental exposures to EBV loads were analyzed by logistic regression models. Results Current smoking, with a dose-response effect, was found to be strongly associated with higher oral EBV loads in the pooled data, with an odds ratio of 1.58 (95% confidence interval, 1.39-1.79), as well as in each of the separate populations. The odds ratio increased to 3.06 when current smokers in southern China were compared to never smokers in northern China. Additionally, higher oral EBV loads tended to be detected in older participants, male participants, and participants in southern China. Conclusions This study provided evidence linking the effect of host-environmental factors, particularly smoking, to oral EBV activity. It could strengthen our understanding of the possible causal roles of EBV-related diseases, which may help to prevent or mitigate EBV-associated diseases.
Organic–Inorganic Hybrid Passivation Enables Perovskite QLEDs with an EQE of 16.48%

Perovskite quantum dots (QDs) with high photoluminescence quantum yields (PLQYs) and narrow emission peak hold promise for next‐generation flexible and high‐definition displays. However, perovskite QD films often suffer from low PLQYs due to the dynamic characteristics between the QD's surface and organic ligands and inefficient electrical transportation resulting from long hydrocarbon organic ligands as highly insulating barrier, which impair the ensuing device performance. Here, a general organic–inorganic hybrid ligand (OIHL) strategy is reported on to passivate perovskite QDs for highly efficient electroluminescent devices. Films based on QDs through OIHLs exhibit enhanced radiative recombination and effective electrical transportation properties compared to the primal QDs. After the OIHL passivation, QD‐based light‐emitting diodes (QLEDs) exhibit a maximum peak external quantum efficiency (EQE) of 16.48%, which is the most efficient electroluminescent device in the field of perovskite‐based LEDs up to date. The proposed OIHL passivation strategy positions perovskite QDs as an extremely promising prospect in future applications of high‐definition displays, high‐quality lightings, as well as solar cells.
Selenium Analysis and Speciation in Dietary Supplements Based on Next-Generation Selenium Ingredients

Selenium is essential for humans and the deficit of Se requires supplementation. In addition to traditional forms such as Se salts, amino acids, or selenium-enriched yeast supplements, next-generation selenium supplements, with lower risk for excess supplementation, are emerging. These are based on selenium forms with lower toxicity, higher bioavailability, and controlled release, such as zerovalent selenium nanoparticles (SeNPs) and selenized polysaccharides (SPs). This article aims to focus on the existing analytical systems for the next-generation Se dietary supplement, providing, at the same time, an overview of the analytical methods available for the traditional forms. The next-generation dietary supplements are evaluated in comparison with the conventional/traditional ones, as well as the analysis and speciation methods that are suitable to reveal which Se forms and species are present in a dietary supplement. Knowledge gaps and further research potential in this field are highlighted. The review indicates that the methods of analysis of next-generation selenium supplements should include a step related to chemical species separation. Such a step would allow a proper characterization of the selenium forms/species, including molecular mass/dimension, and substantiates the marketing claims related to the main advantages of these new selenium ingredients.
Faster Hamiltonian Monte Carlo by Learning Leapfrog Scale

Hamiltonian Monte Carlo samplers have become standard algorithms for MCMC implementations, as opposed to more basic versions, but they still require some amount of tuning and calibration. Exploiting the U-turn criterion of the NUTS algorithm (Hoffman and Gelman, 2014), we propose a version of HMC that relies on the distribution of the integration time of the associated leapfrog integrator. Using in addition the primal-dual averaging method for tuning the step size of the integrator, we achieve an essentially calibration free version of HMC. When compared with the original NUTS on several benchmarks, this algorithm exhibits a significantly improved efficiency.
Regulatory Efficacy of the Polyunsaturated Fatty Acids from Microalgae Spirulina platensis on Lipid Metabolism and Gut Microbiota in High-Fat Diet Rats

Ultra-high performance liquid chromatography coupled with photo-diode array detector and electrospray ionization-mass spectrometry was employed to analyze the major fatty acids in Spirulina platensis 95% ethanol extract (SPL95). The effects of SPL95 on hepatoprotection were evaluated, including liver tissue histopathology, liver, and serum biochemical analysis. The active principle of SPL95 revealed a hypolipidemic effect, as indicated by down-regulating the mRNA and protein levels of sterol regulatory element-binding transcription factor-1c, 3-hydroxy-3-methyl glutaryl coenzyme A reductase, acetyl CoA carboxylase pathway, and upregulating adenosine 5′-monophosphate-activated protein kinase-α in liver. SPL95 enriched the beneficial bacteria, including Prevotella, Alloprevotella, Porphyromonadaceae, Barnesiella, and Paraprevotella. Treatment with SPL95 led to a decrease in microbes, such as Turicibacter, Romboutsia, Phascolarctobacterium, Olsenella, and Clostridium XVIII, which were positively correlated with serum triglyceride, total cholesterol, and low-density-lipoprotein cholesterol levels, but negatively correlated with the serum high-density-lipoprotein cholesterol levels. These results provide evidence that the fatty acid from SPL95 may be used as a novel adjuvant therapy and functional food to regulate gut microbiota in obese and diabetic individuals.
Multimodal Speech Emotion Recognition Using Audio and Text

Speech emotion recognition is a challenging task, and extensive reliance has been placed on models that use audio features in building well-performing classifiers. In this paper, we propose a novel deep dual recurrent encoder model that utilizes text data and audio signals simultaneously to obtain a better understanding of speech data. As emotional dialogue is composed of sound and spoken content, our model encodes the information from audio and text sequences using dual recurrent neural networks (RNNs) and then combines the information from these sources to predict the emotion class. This architecture analyzes speech data from the signal level to the language level, and it thus utilizes the information within the data more comprehensively than models that focus on audio features. Extensive experiments are conducted to investigate the efficacy and properties of the proposed model. Our proposed model outperforms previous state-of-the-art methods in assigning data to one of four emotion categories (i.e., angry, happy, sad and neutral) when the model is applied to the IEMOCAP dataset, as reflected by accuracies ranging from 68.8% to 71.8%.
Validity of Garmin Vívofit 1 and Garmin Vívofit 3 for School-Based Physical Activity Monitoring.

PURPOSE Activity trackers are useful tools for physical activity promotion in adolescents, but robust validity evaluations have not been done under free-living conditions. This study evaluated the validity of the Garmin Vívofit 1 (G1) and Garmin Vívofit 3 (G3) in different settings and contexts. METHODS The participants (girls: 52%, age: 15.9 [1.9] y) wore the G1 and G3 on their nondominant wrist and the Yamax pedometer on their right hip for a period of 1 week. Validity was examined in 4 discrete segments (before school, in school, after school, and whole day). The criterion method was the Yamax pedometer. RESULTS Both the G1 and G3 could be considered equivalent to the Yamax pedometer regarding the before school, in school, and whole day segments. The G1 showed wider limits of agreement than G3. CONCLUSIONS The G1 and G3 trackers exhibited acceptable validity for 3 of the 4 segments (before school, in school, and whole day measurements). The results were less accurate during the after-school segment. The evidence that the validity of the monitors varied depending on the setting and context is an important consideration for research on adolescent activity patterns.
Security and Privacy Preservation in Mobile Crowdsensing

Mobile CrowdSensing (MCS) is a compelling paradigm that enables a crowd of individuals to cooperatively collect and share data to measure phenomena or record events of common interest using their mobile devices. Pairing with inherent mobility and intelligence, mobile users can collect, produce and upload large amounts of data to service providers based on crowdsensing tasks released by customers, ranging from general information, such as temperature, air quality and traffic condition, to more specialized data, such as recommended places, health condition and voting intentions. Compared with traditional sensor networks, MCS can support large-scale sensing applications, improve sensing data trustworthiness and reduce the cost on deploying expensive hardware or software to acquire high-quality data. Despite the appealing benefits, however, MCS is also confronted with a variety of security and privacy threats, which would impede its rapid development. Due to their own incentives and vulnerabilities of service providers, data security and user privacy are being put at risk. The corruption of sensing reports may directly affect crowdsensing results, and thereby mislead customers to make irrational decisions. Moreover, the content of crowdsensing tasks may expose the intention of customers, and the sensing reports might inadvertently reveal sensitive information about mobile users. Data encryption and anonymization techniques can provide straightforward solutions for data security and user privacy, but there are several issues, which are of significantly importance to make MCS practical. First of all, to enhance data trustworthiness, service providers need to recruit mobile users based on their personal information, such as preferences, mobility pattern and reputation, resulting in the privacy exposure to service providers. Secondly, it is inevitable to have replicate data in crowdsensing reports, which may possess large communication bandwidth, but traditional data encryption makes replicate data detection and deletion challenging. Thirdly, crowdsensed data analysis is essential to generate crowdsensing reports in MCS, but the correctness of crowdsensing results in the absence of malicious mobile users and service providers become a huge concern for customers. Finally yet importantly, even if user privacy is preserved during task allocation and data collection, it may still be exposed during reward distribution. It further discourage mobile users from task participation. In this thesis, we explore the approaches to resolve these challenges in MCS. Based on the architecture of MCS, we conduct our research with the focus on security and privacy protection without sacrificing data quality and users’ enthusiasm. Specifically, the main contributions are, i) to enable privacy preservation and task allocation, we propose SPOON, a strong privacy-preserving mobile crowdsensing scheme supporting accurate task
Roles of TGF β and FGF Signals in the Lens: Tropomyosin Regulation for Posterior Capsule Opacity

Transforming growth factor (TGF) β and fibroblast growth factor (FGF) 2 are related to the development of posterior capsule opacification (PCO) after lens extraction surgery and other processes of epithelial–mesenchymal transition (EMT). Oxidative stress seems to activate TGF β1 largely through reactive oxygen species (ROS) production, which in turn alters the transcription of several survival genes, including lens epithelium-cell derived growth factor (LEDGF). Higher ROS levels attenuate LEDGF function, leading to down-regulation of peroxiredoxin 6 (Prdx6). TGF β is regulated by ROS in Prdx6 knock-out lens epithelial cells (LECs) and induces the up-regulation of tropomyosins (Tpms) 1/2, and EMT of LECs. Mouse and rat PCO are accompanied by elevated expression of Tpm2. Further, the expression of Tpm1/2 is induced by TGF β2 in LECs. Importantly, we previously showed that TGF β2 and FGF2 play regulatory roles in LECs in a contrasting manner. An injury-induced EMT of a mouse lens as a PCO model was attenuated in the absence of Tpm2. In this review, we present findings regarding the roles of TGF β and FGF2 in the differential regulation of EMT in the lens. Tpms may be associated with TGF β2- and FGF2-related EMT and PCO development.