Miracle-dz/UniFAR-FTUs huggingface dataset:
A High-Protein/Low-Fat Diet May Interact with Vitamin D-Binding Protein Gene Variants to Moderate the Risk of Depression in Apparently Healthy Adults

Background: Recent studies have shown that depression is inversely correlated with high protein and low fat intake and positively correlated with vitamin D-binding protein (VDBP). Therefore, the aim of this study was to examine the interaction between protein/fat dietary patterns and VDBP genotypes with regard to the risk of depression in apparently healthy adults who have not been diagnosed with any chronic disease. Methods: In this study, 265 individuals (126 males and 139 females) aged 18–55 years were recruited from the communities of central and west Tehran based on convenience sampling. Body composition was measured with a body composition analyzer and depression symptoms were categorized as normal, moderate depression, or severe depression using the Depression Anxiety Stress Scales 21 (DASS-21) questionnaire. Dietary patterns were determined by a semiquantitative food frequency questionnaire to assess typical food intake during the 12-month period. Blood samples were collected from and biochemical measurements performed on all participants. An analysis of two polymorphisms (rs7041 and rs4588) in the GC gene, which encodes VDBP, was performed by polymerase chain reaction-restriction fragment length polymorphism. Results: A statistically significant association was found between depression and diet (p = 0.03) after having categorized the participants into three groups: a high-protein/low-fat (HP/LF) group, a moderate-protein/moderate-fat (MP/MF) group, and a low-protein/high-fat (LP/HF) group. Moreover, the findings demonstrated that depression was related to both the rs7041 and the rs4588 polymorphism (p = 0.05 and p = 0.02, respectively). We next used multinomial logistic modeling to investigate the risk of depression. A significant interaction was observed between HP/LF diet and the rs7041 polymorphism in the moderate- and severe-depression groups (β = –0.30, p = 0.05, and β = –0.48, p = 0.01, respectively). Conclusion: This study showed that an HP/LF diet interacts with the rs7041 polymorphism, with T allele carriers having a greater prevalence of moderate and severe depression.
Enhanced ER proteostasis and temperature differentially impact the mutational tolerance of influenza hemagglutinin

We systematically and quantitatively evaluate whether endoplasmic reticulum (ER) proteostasis factors impact the mutational tolerance of secretory pathway proteins. We focus on influenza hemaggluttinin (HA), a viral membrane protein that folds in the host’s ER via a complex pathway. By integrating chemical methods to modulate ER proteostasis with deep mutational scanning to assess mutational tolerance, we discover that upregulation of ER proteostasis factors broadly enhances HA mutational tolerance across diverse structural elements. Remarkably, this proteostasis network-enhanced mutational tolerance occurs at the same sites where mutational tolerance is most reduced by propagation at fever-like temperature. These findings have important implications for influenza evolution, because influenza immune escape is contingent on HA possessing sufficient mutational tolerance to evade antibodies while maintaining the capacity to fold and function. More broadly, this work provides the first experimental evidence that ER proteostasis mechanisms define the mutational tolerance and, therefore, the evolution of secretory pathway proteins.
An Electrophysiological Investigation of Attentional Bias in a PTSD Population

Objective: Evidence relying on probe detection tasks suggests that anxious individuals exhibit an enhanced selective attentional bias toward emotional or threating stimuli, characterized by attentional vigilance or avoidance of threat. Method: Amplitude of P100 and P300 event-related potentials and behavioral measures of target detection were assessed during presentation of a dot-probe task in 18 posttraumatic stress disorder patients and 18 healthy controls to elucidate the effects of attentional bias toward threatening facial expressions. Results: Perceptual (P100) processing of threat-face pairs revealed no evidence of attentional bias in posttraumatic stress disorder (PTSD) patients. PTSD patients exhibited larger P100 and P300 amplitude to probes replacing neutral rather than angry faces, indicating an increased allocation of early perceptual and later strategic processing away from anger-related stimuli. Conclusion: The present study provided no support for facilitated engagement in this sample of patients. Possible interpretations of the results related to differential processing of target probes replacing angry-neutral face pairs are discussed.
Optimal Mechanical Design of Electronic Devices for Shock Protection

Handheld electronic devices are subject to mechanical shocks, which is one of the primary sources of failures. When a device is dropped onto a hard surface, an impact sequence triggers vibrations in various components or subsystems of the device. The time history of the excitation and thus the response of the component depends sensitively on the initial conditions of dropping and on the physical properties of the device and the underlying surface. In this paper, we explore how the response of a component is affected by its position in the device and by its physical parameters including mass distribution of the device and degree of energy absorption during impacts. An event-based numerical simulation of falling motion is used to determine the excitation of the component, which is modeled as a damped, linear oscillator. The maximal displacement of the oscillator is used as a measure of impact shock. Our results suggest that the appropriate design may decrease the mechanical shock by at least a factor of five.
HealthDep: An Efficient and Secure Deduplication Scheme for Cloud-Assisted eHealth Systems

In this paper, we analyze the inherent characteristic of electronic medical records (EMRs) from actual electronic health (eHealth) systems, where we found that first, multiple patients would generate large amounts of duplicate EMRs and second, cross-patient duplicate EMRs would be generated numerously only in the case that the patients consult doctors in the same department. We then propose the first efficient and secure encrypted EMRs deduplication scheme for cloud-assisted eHealth systems (HealthDep). With the integration of our analysis results, HealthDep allows the cloud server to efficiently perform the EMRs deduplication, and enables the cloud server to reduce storage costs by more than 65% while ensuring the confidentiality of EMRs. Security analysis shows that HealthDep provides a stronger security guarantee than Marforio et al.'s scheme (NDSS 2014) and Bellare et al.'s scheme (USENIX Security 2013). Algorithm implementation and performance analysis demonstrate the feasibility and high efficiency of HealthDep.
Look before we leap: reinforced active sampling framework for image classification

Abstract. We aim to improve the negative-accelerated sampling framework and construct a more reasonable and effective active sampling framework by introducing the technique of reinforcement learning. Compared with traditional uncertainty-based active sampling strategy, the proposed sample selection framework consists of both a certainty metric and sample postprocessing for more precise evaluation. The certainty metric is measured by the visual classifying model, and the postprocessing module is implemented by the Q-learning algorithm to construct a compact training set for the visual module to further improve the effectiveness and efficiency of classification. Meanwhile, the parameters of the whole sampling framework are calculated adaptively instead of being set manually to improve the adaptiveness of the whole framework. Experimental results on real-world datasets show the effectiveness of the proposed framework.
Molecular interactions connecting the function of the serine-arginine–rich protein SRSF1 to protein phosphatase 1

Splicing generates many mRNA strands from a single precursor mRNA, expanding the proteome and enhancing intracellular diversity. Both initial assembly and activation of the spliceosome require an essential family of splicing factors called serine-arginine (SR) proteins. Protein phosphatase 1 (PP1) regulates the SR proteins by controlling phosphorylation of a C-terminal arginine-serine–rich (RS) domain. These modifications are vital for the subcellular localization and mRNA splicing function of the SR protein. Although PP1 has been shown to dephosphorylate the prototype SR protein splicing factor 1 (SRSF1), the molecular nature of this interaction is not understood. Here, using NMR spectroscopy, we identified two electrostatic residues in helix α2 and a hydrophobic residue in helix α1 in the RNA recognition motif 1 (RRM1) of SRSF1 that constitute a binding surface for PP1. Substitution of these residues dissociated SRSF1 from PP1 and enhanced phosphatase activity, reducing phosphorylation in the RS domain. These effects lead to shifts in alternative splicing patterns that parallel increases in SRSF1 diffusion from speckles to the nucleoplasm brought on by regiospecific decreases in RS domain phosphorylation. Overall, these findings establish a molecular and biological connection between PP1-targeted amino acids in an RRM with the phosphorylation state and mRNA-processing function of an SR protein.
Psychiatric and psycho-social characteristics of suicide completers: a comprehensive evaluation of psychiatric case records and postmortem findings

Objectives To explore the demographic, psychosocial and clinical characteristics of individuals known to the mental health services, who died by probable suicide in the West of Ireland. Methods Postmortem reports between January 2006 and May 2012 detailed 153 individuals who died by probable suicide, 58 of whom attended the mental health services. Relevant socio-demographic and clinical data was extracted from individuals’ lifetime case notes. Results Recurrent depressive disorder (44%) was the most common diagnosis and hanging the most common method of death (58%). Of individuals who died by hanging, 79% previously attempted suicide by the same method. For individuals with a documented history of depression, only 32% had antidepressants detected in their toxicology reports. Similarly, only one individual (20%) with schizophrenia had antipsychotics detected in their toxicology report. Conclusions Individuals who died by probable suicide, most commonly died by hanging and drowning; with previous attempts of hanging particularly prevalent in the group who subsequently died by hanging. At the time of death, less than one-third of individuals according to toxicology reports were taking the medication that was last prescribed to them by the mental health services suggesting a high rate of treatment non-concordance in individuals who died by probable suicide.
A Stepwise Spatio-Temporal Flow Clustering Method for Discovering Mobility Trends

Massive flows that represent the individual level of movements and communications can be easily obtained in the age of big data. Generalizing spatial and temporal flow patterns from such data is essential to demonstrate spatial connections and mobility trends. Clustering approaches provide effective methods to handle data sets that contain massive individual-level flows. However, existing flow clustering studies obscure the geometric properties of flow data, such as direction and length, which significantly indicate movement trends. In addition, temporal information is often ignored because previous approaches have mainly focused on the perspective of spatial clusters of flow data, resulting in a loss of temporal patterns. In this paper, we introduce new spatial and temporal similarity measurements between flows and propose a new clustering approach of flow data based on a stepwise strategy. This method can identify clusters from distinct flow distributions and discover significant spatio-temporal trends from large flow data. Simulated experiments with synthetic flows and a case study using Beijing taxi trip data are conducted to validate the usefulness of the proposed method.
Family Support: A Possible Buffer Against Disruptive Events for Individuals With and Without Remitted Depression

The current study sought to test the role of family support as a buffer of life stress for depressive symptoms in a sample of young adults at low- and high-risk for depression based on a previous history of depression. Ninety-seven young adults, 54 with remitted depression and 43 without prior history of depression, completed reports of family relationships, disruptive life events, and depressive symptoms at baseline and every 2 months for 10 months. Results revealed significant interactions between family environment and life events predicting Beck Depressive Inventory (BDI) scores at baseline, such that individuals with better family support were buffered from risk associated with life stress, and this was true even after accounting for a previous history of depression. Longitudinal analyses utilizing the Patient Health Questionnaire-9 (PHQ-9) as a depressive symptom measure did not find significant associations with family environment, but did find that more stressful events at baseline were associated with increasing levels of symptoms over time. Exploratory analyses suggest that discrepant findings for baseline versus longitudinal analyses may be due to differences in symptom measurement and to associations between family environment and cognitive features of depression. These findings provide qualified support for the continued relevance of families as stress buffers in young adulthood across a spectrum of risk for depression.
The importance of commutability in material used for quality control purposes

External Quality Assessment (EQA) is an important part of laboratory quality assurance. Spiking of normal plasma is sometimes employed to mimic clinical samples. It is important that spiked material gives similar results to clinical samples (ie, is commutable) to ensure appropriate conclusions can be drawn from EQA exercises. We describe here data from UK National External Quality Assessment Scheme for Blood Coagulation (NEQAS BC) exercises where spiked samples were tested alongside samples from patients to explore commutability of artificial material. Normal plasma was spiked with unfractionated heparin (UFH), low molecular weight heparin (LMWH), Dabigatran or Rivaroxaban. Factor VIII (FVIII) deficient plasma was spiked with FVIII concentrate. Spiked samples and ex vivo patient material were sent to laboratories for testing. For LMWH, good agreement was seen between results for samples from patient plasma and plasma spiked with heparin. For UFH, APTT ratios differed between spiked and patient samples for the same drug concentration, with no correlation in ranking of reagents. Precision for patient and spiked material for Rivaroxaban and Dabigatran assays was comparable. However, the pattern of results for some Dabigatran assay kits differed between spiked and patient samples. For FVIII assays, results obtained with spiked and postinfusion samples gave comparable results. Spiked material is suitable for EQA if commutability is demonstrated. Our data show commutability for plasma spiked with Rivaroxaban, LWMH and some FVIII concentrates. For some tests, notably APTT for UFH, marked differences between patient and spiked samples indicate not all tests can be evaluated using artificial samples.
RNNs as psycholinguistic subjects: Syntactic state and grammatical dependency

Recurrent neural networks (RNNs) are the state of the art in sequence modeling for natural language. However, it remains poorly understood what grammatical characteristics of natural language they implicitly learn and represent as a consequence of optimizing the language modeling objective. Here we deploy the methods of controlled psycholinguistic experimentation to shed light on to what extent RNN behavior reflects incremental syntactic state and grammatical dependency representations known to characterize human linguistic behavior. We broadly test two publicly available long short-term memory (LSTM) English sequence models, and learn and test a new Japanese LSTM. We demonstrate that these models represent and maintain incremental syntactic state, but that they do not always generalize in the same way as humans. Furthermore, none of our models learn the appropriate grammatical dependency configurations licensing reflexive pronouns or negative polarity items.
Functionality-Oriented Microservice Extraction Based on Execution Trace Clustering

The main task of microservice extraction is to find which software entities (e.g., methods, classes) should be grouped together from existing monolithic software as candidate microservices, responsible for specific functionalities and evolving independently. Current methods extract microservices by analyzing source code and following the assumption that "classes with strong relation should be in the same service", which originates from software structure analysis. We find that 1) many program behaviors cannot be explicitly reflected in the source code, and 2) the relation at code-level is not equivalent to the same functionality. Thus, we propose a functionality-oriented microservice extraction (FoME) method in this study by monitoring program dynamic behavior and clustering execution traces. Instead of source code analysis, the execution traces of a program are applied to group source code entities that are dedicated to the same functionality. We also construct a systematic measurement of microservice by integrating five complementary metrics of service cohesion and coupling. These metrics measure Functional Independence of microservices. That is, it qualifies whether a microservices can have its own responsibilities independently. In the experiment, our method is compared with three state-of-the-art methods on four open-source projects. The microservice candidates generated using our method present similar functional cohesion to the services produced using the other methods, but have considerably looser coupling measurements (dramatically reducing measurements of IRN and OPN).
Serum exosomal miR-328, miR-575, miR-134 and miR-671-5p as potential biomarkers for the diagnosis of Kawasaki disease and the prediction of therapeutic outcomes of intravenous immunoglobulin therapy

The present study was conducted to screen serum exosomal microRNAs (miRNAs) for the early diagnosis of Kawasaki disease (KD) and to investigate their underlying mechanisms by analyzing microarray data under accession numbers GSE60965 [exosomal miRNA, including three pooled serum samples from 5 healthy children, 5 patients with KD and 5 patients with KD following intravenous immunoglobulin (IVIG) therapy] and GSE73577 (mRNA, including peripheral blood mononuclear cell samples from 19 patients with KD prior to and following IVIG treatment) from the Gene Expression Omnibus database. Differentially expressed miRNAs (DE-miRNAs) and genes (DEGs) were identified using the Linear Models for Microarray data method, and the mRNA targets of DE-miRNAs were predicted using the miRWalk 2.0 database. The functions of the target genes were analyzed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). As a result, 65 DE-miRNAs were identified with different expression patterns between the healthy children and patients with KD and between patients with KD and patients with KD following IVIG therapy. The target genes of 15 common DE-miRNAs were predicted. Following overlapping the target genes of DE-miRNAs with 355 DEGs, 28 common genes were identified and further screened to construct a network containing 30 miRNA-mRNA regulatory associations. Of these associations, only miR-328-spectrin α, erythrocytic 1, miR-575-cyclic AMP-responsive element-binding protein 5/b-1,4-galactosyltransferase 5/WD repeat and FYVE domain-containing 3/cystatin-A/C-X-C motif chemokine receptor 1/protein phosphatase 1 regulatory subunit 3B, miR-134-acyl-CoA synthetase long chain family member 1/C-type lectin domain family 1 member A and miR-671-5p-tripartite motif containing 25/leucine rich repeat kinase 2/kinesin family member 1B/leucine rich repeat neuronal 1 were involved in the negative regulation of gene expression. Functional analysis indicated that the identified target genes may be associated with inflammation. Accordingly, serum exosomal miR-328, miR-575, miR-134 and miR-671-5p may act as potential biomarkers for the diagnosis of KD and the prediction of outcomes of the IVIG therapy by influencing the expression of inflammatory genes.
Pool size estimations for dense‐core vesicles in mammalian CNS neurons

Neuropeptides are essential signaling molecules transported and secreted by dense‐core vesicles (DCVs), but the number of DCVs available for secretion, their subcellular distribution, and release probability are unknown. Here, we quantified DCV pool sizes in three types of mammalian CNS neurons in vitro and in vivo. Super‐resolution and electron microscopy reveal a total pool of 1,400–18,000 DCVs, correlating with neurite length. Excitatory hippocampal and inhibitory striatal neurons in vitro have a similar DCV density, and thalamo‐cortical axons in vivo have a slightly higher density. Synapses contain on average two to three DCVs, at the periphery of synaptic vesicle clusters. DCVs distribute equally in axons and dendrites, but the vast majority (80%) of DCV fusion events occur at axons. The release probability of DCVs is 1–6%, depending on the stimulation. Thus, mammalian CNS neurons contain a large pool of DCVs of which only a small fraction can fuse, preferentially at axons.
Scalar Differential Equations for Transversely Varying Thickness Modes in Doubly Rotated Quartz Crystal Sensors

For time-harmonic motions, we generalize the 2-D scalar differential equation by Stevens and Tiersten for transversely varying thickness-shear vibrations of doubly rotated quartz plate sensors to include the effects of surface acoustic loadings. Starting from the 3-D equations of piezoelectricity, the governing equations are first transferred into a new coordinate system formed by the three eigenvibration directions; then, by neglecting the terms pertaining to the third and higher order in-plane wavenumbers, which are considered to be small compared to the thickness wavenumber, a scalar differential equation for the quasi-thickness shear modes is derived. The surface impedance tensor was introduced to represent the mechanical effects of surface mass layers and viscous fluid. Both unelectroded and electroded plates are treated. For electroded plates, both free and electrically forced vibrations under a time-harmonic driving voltage are analyzed. In addition to the fast thickness variation, which was considered in conventional 1-D models such as Sauerbrey's equation and Kanazawa's equation, the new equations properly accounted for the slow transverse variation of the finite sensors. Numerical examples for partially electroded fluid viscosity sensors are presented to show practical applications of the new equations for design and analysis of quartz crystal sensors.