Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated Segmentation of Midbrain Structures in High-Resolution Susceptibility Maps Based on Convolutional Neural Network and Transfer Learning

Background Accurate delineation of the midbrain nuclei, the red nucleus (RN), substantia nigra (SN) and subthalamic nucleus (STN), is important in neuroimaging studies of neurodegenerative and other diseases. This study aims to segment midbrain structures in high-resolution susceptibility maps using a method based on a convolutional neural network (CNN). Methods The susceptibility maps of 75 subjects were acquired with a voxel size of 0.83 × 0.83 × 0.80 mm3 on a 3T MRI system to distinguish the RN, SN, and STN. A deeply supervised attention U-net was pre-trained with a dataset of 100 subjects containing susceptibility maps with a voxel size of 0.63 × 0.63 × 2.00 mm3 to provide initial weights for the target network. Five-fold cross-validation over the training cohort was used for all the models’ training and selection. The same test cohort was used for the final evaluation of all the models. Dice coefficients were used to assess spatial overlap agreement between manual delineations (ground truth) and automated segmentation. Volume and magnetic susceptibility values in the nuclei extracted with automated CNN delineation were compared to those extracted by manual tracing. Consistencies of volume and magnetic susceptibility values by different extraction strategies were assessed by Pearson correlation coefficients and Bland-Altman analyses. Results The automated CNN segmentation method achieved mean Dice scores of 0.903, 0.864, and 0.777 for the RN, SN, and STN, respectively. There were no significant differences between the achieved Dice scores and the inter-rater Dice scores (p > 0.05 for each nucleus). The overall volume and magnetic susceptibility values of the nuclei extracted by the automatic CNN method were significantly correlated with those by manual delineation (p < 0.01). Conclusion Midbrain structures can be precisely segmented in high-resolution susceptibility maps using a CNN-based method.
T Cell Recognition of Tumor Neoantigens and Insights Into T Cell Immunotherapy

In cancer, non-synonymous DNA base changes alter protein sequence and produce neoantigens that are detected by the immune system. For immune detection, neoantigens must first be presented on class I or II human leukocyte antigens (HLA) followed by recognition by peptide-specific receptors, exemplified by the T-cell receptor (TCR). Detection of neoantigens represents a unique challenge to the immune system due to their high similarity with endogenous ‘self’ proteins. Here, we review insights into how TCRs detect neoantigens from structural studies and delineate two broad mechanistic categories: 1) recognition of mutated ‘self’ peptides and 2) recognition of novel ‘non-self’ peptides generated through anchor residue modifications. While mutated ‘self’ peptides differ only by a single amino acid from an existing ‘self’ epitope, mutations that form anchor residues generate an entirely new epitope, hitherto unknown to the immune system. We review recent structural studies that highlight these structurally distinct mechanisms and discuss how they may lead to differential anti-tumor immune responses. We discuss how T cells specific for neoantigens derived from anchor mutations can be of high affinity and provide insights to their use in adoptive T cell transfer-based immunotherapy.
Human Herpesvirus 6A Is a Risk Factor for Multiple Sclerosis

The role for human herpesvirus (HHV)-6A or HHV-6B in multiple sclerosis (MS) pathogenesis has been controversial. Possibly because the damage of the virus infection may occur before onset of clinical symptoms and because it has been difficult to detect active infection and separate serological responses to HHV-6A or 6B. Recent studies report that in MS patients the serological response against HHV-6A is increased whereas it is decreased against HHV-6B. This effect seems to be even more pronounced in MS patients prior to diagnosis and supports previous studies postulating a predomination for HHV-6A in MS disease and suggests that the infection is important at early stages of the disease. Furthermore, HHV-6A infection interacts with other factors suspected of modulating MS susceptibility and progression such as infection with Epstein-Barr virus (EBV) and Cytomegalovirus (CMV), tobacco smoking, HLA alleles, UV irradiation and vitamin D levels. The multifactorial nature of MS and pathophysiological role for HHV-6A in inflammation and autoimmunity are discussed.
Temporospatial Alterations in Upper-Limb and Mallet Control Underlie Motor Learning in Marimba Performance

Sound-producing movements in percussion performance require a high degree of fine motor control. However, there remains a relatively limited empirical understanding of how performance level abilities develop in percussion performance in general, and marimba performance specifically. To address this issue, nine percussionists performed individualised excerpts on marimba within three testing sessions spaced 29 days apart to assess early, intermediate, and late stages of motor learning. Motor learning was quantified via analyses of both the temporal control of mallet movements, and the spatial variability of upper-limb movements. The results showed that temporal control of mallet movements was greater in the intermediate compared to the early learning session, with no significant additional improvements revealed in the late learning session. In addition, spatial variability in the left and right elbows decreased within the intermediate compared to the early learning session. The results suggest that temporal control of mallet movements may be driven by reductions in spatial variability of elbow movements specifically. As a result, this study provides novel evidence for kinematic mechanisms underlying motor learning in percussion which can be applied towards enhancing musical training.
Visceral Adiposity, Inflammation, and Testosterone Predict Skeletal Muscle Mitochondrial Mass and Activity in Chronic Spinal Cord Injury

Background Mitochondrial health is an important predictor of several health-related comorbidities including obesity, type 2 diabetes mellitus, and cardiovascular disease. In persons with spinal cord injury (SCI), mitochondrial health has been linked to several important body composition and metabolic parameters. However, the complex interplay of how mitochondrial health is affected has yet to be determined in this population. Objective In this study, we examined the contribution of visceral adiposity, inflammatory biomarkers, testosterone and circulating serum growth factors as predictors of mitochondrial health in persons with chronic SCI. Participants Thirty-three individuals with chronic SCI (n = 27 Males, n = 6 Females, age: 40 ± 13.26 years, level of injury: C4-L1, BMI: 23 ± 5.57) participated in this cross-sectional study. Methods Visceral adipose tissue (VAT) was measured via magnetic resonance imaging (MRI). After an overnight fast, serum testosterone, inflammatory biomarkers [interleukin 6 (IL-6), tumor necrosis factor alpha (TNF-α), c-reactive protein (CRP)], and anabolic growth factors [insulin-like growth factor 1 (IGF-1), insulin-like growth factor binding protein 3 (IGFBP-3)] were measured. Skeletal muscle biopsies were obtained from the vastus lateralis muscle to measure citrate synthase (CS) and Complex III activity. Regression analyses were used to examine predictors of mitochondrial mass and activity. Results CS activity was negatively associated with VAT (r2 = 0.360, p < 0.001), CRP (r2 = 0.168, p = 0.047), and positively associated with testosterone (r2 = 0.145, p = 0.042). Complex III activity was negatively associated with VAT relative to total lean mass (VAT:TLM) (r2 = 0.169, p = 0.033), trended for CRP (r2 = 0.142, p = 0.069), and positively associated with testosterone (r2 = 0.224, p = 0.010). Multiple regression showed CS activity was significantly associated with VAT + CRP (r2 = 0.412, p = 0.008) and VAT + Testosterone (r2 = 0.433, p = 0.001). Complex III activity was significantly associated with VAT relative to total trunk cross-sectional area (CSA) + CRP (VAT:total trunk CSA + CRP; r2 = 0.286, p = 0.048) and VAT + Testosterone (r2 = 0.277, p = 0.024). Conclusion Increased visceral adiposity and associated inflammatory signaling (CRP) along with reduced testosterone levels predict mitochondrial dysfunction following SCI. Specifically, lower VATCSA and higher testosterone levels or lower VATCSA and lower CRP levels positively predict mitochondrial mass and enzyme activity in persons with chronic SCI. Future research should investigate the efficacy of diet, exercise, and potentially testosterone replacement therapy on enhancing mitochondrial health in chronic SCI. Clinical Trial Registration [www.ClinicalTrials. gov], identifier: [NCT02660073].
Self-Serving Bias in Performance Goal Achievement Appraisals: Evidence From Long-Distance Runners

While working with a long-distance running event organizer, the authors of this study observed considerable differences between event participants’ official finish time (i.e., bib time) and their self-reported finish time in the post-event survey. Drawing on the notion of self-serving bias, we aim to explore the source of this disparity and how such psychological bias influences participants’ event experience at long-distance running events. Using evidence of 1,320 marathon runners, we demonstrated how people are more likely to be subject to a biased self-assessment contingent upon achieving their best finish time at the event. The study samples were split into record-high-achieved and record-high-missed groups, and the self-serving biases of each group were explored. Results from the t-test comparing record-high-achieved and -missed groups showed that runners in the record-high-missed group were significantly more likely to report a positively biased finish time than runners in the record-high-achieved group (p < 0.01). Additionally, results from logistic regression showed that as runners missed their best finish time by a wider margin, the probability of reporting a positively biased incorrect finish time increased. Lastly, we conducted an additional t-test and revealed that runners who are subject to self-serving bias showed a lower level of overall event satisfaction. The current study suggests one way to bypass the adverse effects of participant sport event participants’ worse-than-expected athletic performance. We specifically suggest that the event organizers target runners who had worse-than-expected performance and make extra efforts on non-race service attributes (e.g., finish line experience, rest and recovery area, and transportation after the event) because these runners are more likely to be unsatisfied with the event.
Effects of Integrative Neuromuscular Training Combined With Regular Tennis Training Program on Sprint and Change of Direction of Children

Objective The aim of this study was to investigate the effects of integrative neuromuscular training (NMT) on sprint and the ability to change direction for children who are between the ages of 7 and 8 and beginning to play tennis. Methods Thirty-two participants were randomized into a training group (TG; n = 16) and a control group (CG; n = 16). All participants attended tennis classes twice a week for a continuous 8 weeks. In addition, the TG received NMT (e.g., 20-m sprints, running at four corners, rope ladder drills, etc.), which progressed in difficulty every 2 weeks. Pre-intervention and post-intervention measurements, including a 30-m sprint test, a 5–10–5 test, and a 3 × 10 m shuttle run test, were assessed by a Smartspeed laser timing gate system, while the spider agility test was evaluated with a stopwatch. Results Two-way repeated measures ANOVA found significant differences in the interaction between time and group among variables measured. Results were as follows: time in the 30 m sprint (F = 13.467, 95% CI = 7.163–7.506, p = 0.001, η2p = 0.310, Δ = 0.42 s); 5–10–5 test (F = 13.975, 95% CI = 8.696–9.017, p = 0.001, η2p = 0.318, Δ = 0.78 s); 3 × 10 m shuttle run (F = 7.605, 95% CI = 11.213–11.642, p = 0.01, η2p = 0.202, Δ = 0.77 s); and spider agility test (F = 34.555, 95% CI = 28.258–29.670, p < 0.001, η2p = 0.535, Δ = 3.96 s). The results demonstrated a greater decrease in sprint and change of direction (COD) time among the TG than the CG from pre-intervention to post-intervention. Conclusion A regular tennis training combined with NMT program could produce greater improvement in a player’s sprint and ability to change direction when introduced to childhood tennis beginners in a sensitive period, compared to tennis class intervention only.
Functional Network Changes After High-Frequency rTMS Over the Most Activated Speech-Related Area Combined With Speech Therapy in Chronic Stroke With Non-fluent Aphasia

Objective High-frequency repetitive transcranial magnetic stimulation (HF-rTMS) to the lesional hemisphere requires prudence in selecting the appropriate stimulation spot. Functional near-IR spectroscopy (fNIRS) can be used in both selecting the stimulation spot and assessing the changes of the brain network. This study aimed to evaluate the effect of HF-rTMS on the most activated spot identified with fNIRS and assess the changes of brain functional network in the patients with poststroke aphasia. Methods A total of five patients received HF-rTMS to the most activated area on the lesional hemisphere, followed by 30 min of speech therapy for 10 days. The Korean version of the Western aphasia battery (K-WAB) and fNIRS evaluation were done 1 day before the treatment, 1 day and 1 month after the last treatment session. Changes of K-WAB and paired cortical interaction and brain network analysis using graph theory were assessed. Results Aphasia quotient in K-WAB significantly increased after the treatment (P = 0.043). The correlation analysis of cortical interactions showed increased connectivity between language production and processing areas. Clustering coefficients of the left hemisphere were increased over a sparsity range between 0.45 and 0.58 (0.015 < p < 0.031), whereas the clustering coefficients of the right hemisphere, decreased over a sparsity range 0.15–0.87 (0.063 < p < 0.095). The global efficiency became lower over a network sparsity range between 0.47 and 0.75 (0.015 < p < 0.063). Conclusion Improvement of language function and changes of corticocortical interaction between language-related cortical areas were observed after HF-rTMS on the most activated area identified by fNIRS with combined speech therapy in the patients with poststroke aphasia.
Friend of the Devil: Negative Social Influences Driving Substance Use Disorders

Substance use disorders in humans have significant social influences, both positive and negative. While prosocial behaviors promote group cooperation and are naturally rewarding, distressing social encounters, such as aggression exhibited by a conspecific, are aversive and can enhance the sensitivity to rewarding substances, promote the acquisition of drug-taking, and reinstate drug-seeking. On the other hand, withdrawal and prolonged abstinence from drugs of abuse can promote social avoidance and suppress social motivation, accentuating drug cravings and facilitating relapse. Understanding how complex social states and experiences modulate drug-seeking behaviors as well as the underlying circuit dynamics, such as those interacting with mesolimbic reward systems, will greatly facilitate progress on understanding triggers of drug use, drug relapse and the chronicity of substance use disorders. Here we discuss some of the common circuit mechanisms underlying social and addictive behaviors that may underlie their antagonistic functions. We also highlight key neurochemicals involved in social influences over addiction that are frequently identified in comorbid psychiatric conditions. Finally, we integrate these data with recent findings on (±)3,4-methylenedioxymethamphetamine (MDMA) that suggest functional segregation and convergence of social and reward circuits that may be relevant to substance use disorder treatment through the competitive nature of these two types of reward. More studies focused on the relationship between social behavior and addictive behavior we hope will spur the development of treatment strategies aimed at breaking vicious addiction cycles.
Automated Detection of Vaping-Related Tweets on Twitter During the 2019 EVALI Outbreak Using Machine Learning Classification

There are increasingly strict regulations surrounding the purchase and use of combustible tobacco products (i.e., cigarettes); simultaneously, the use of other tobacco products, including e-cigarettes (i.e., vaping products), has dramatically increased. However, public attitudes toward vaping vary widely, and the health effects of vaping are still largely unknown. As a popular social media, Twitter contains rich information shared by users about their behaviors and experiences, including opinions on vaping. It is very challenging to identify vaping-related tweets to source useful information manually. In the current study, we proposed to develop a detection model to accurately identify vaping-related tweets using machine learning and deep learning methods. Specifically, we applied seven popular machine learning and deep learning algorithms, including Naïve Bayes, Support Vector Machine, Random Forest, XGBoost, Multilayer Perception, Transformer Neural Network, and stacking and voting ensemble models to build our customized classification model. We extracted a set of sample tweets during an outbreak of e-cigarette or vaping-related lung injury (EVALI) in 2019 and created an annotated corpus to train and evaluate these models. After comparing the performance of each model, we found that the stacking ensemble learning achieved the highest performance with an F1-score of 0.97. All models could achieve 0.90 or higher after tuning hyperparameters. The ensemble learning model has the best average performance. Our study findings provide informative guidelines and practical implications for the automated detection of themed social media data for public opinions and health surveillance purposes.
The Efficacy of Nitrates for Bone Health: A Systematic Review and Meta-Analysis of Observational and Randomized Controlled Studies

Background Although some studies have found that nitrates were beneficial for bone health, the findings are inconsistent. To assess the efficacy of nitrates for bone health, we conducted a meta-analysis. Methods PubMed, EMBASE databases, Cochrane Library for relevant articles published before December 2021 were searched. All observational and randomized controlled studies that reporting bone mineral density (BMD), fractures with nitrates use were included. A meta-analysis was performed to calculate risk ratios (RRs) for fractures, change differences for bone mineral density. Results Four cohort studies and two case-control studies examining the association between nitrates use and fractures were identified. The nitrates use was not associated with any fracture risk (RR = 0.97; 95% CI, 0.94–1.01; I 2 = 31.5%) and hip fracture (RR = 0.88; 95% CI, 0.76–1.02; I 2 = 74.5%). Subgroup analyses revealed no differences in fracture risk, whereas two cohort studies revealed a reduced risk of hip fracture (RR = 0.71, 95% CI, 0.58–0.86, I 2 = 0.0%). There were no statistically significant differences in BMD percent changes at lumbar spine (WMD = -0.07, 95% CI,-0.78–0.65; I 2 = 0.0%), total hip (WMD = -0.42, 95% CI,-0.88–0.04; I 2 = 0.0%), femoral neck (WMD = -0.38, 95% CI,-1.02–0.25; I 2 = 0.0%), or total body (WMD = -0.17, 95% CI,-0.51–0.17; I 2 = 0.0%) in two randomized controlled trials (RCTs) compared with a placebo. Another two RCTs compared nitrates with alendronate. Nitrates were comparable to alendronate in increasing bone mineral density at lumbar spine (WMD = 0.00, 95% CI,-0.01–0.02; I 2 = 0.0%). Besides, the most common adverse effect was headache, contributing to low adherence to therapy. Conclusion Our meta-analysis showed no association between nitrates use and fractures in observational studies. The results of RCTs on the usage of nitrates and their effects on BMD were inconsistent. High-quality, long-term studies are needed to clarify the efficacy of nitrates for bone health.
Chemical Composition and Potential Biological Activity of Melanoidins From Instant Soluble Coffee and Instant Soluble Barley: A Comparative Study

In this work a comparative study of the chemical composition and potential biological activity of high molecular weight (HMW) melanoidins isolated from instant soluble coffee (ISC) and instant soluble barley (ISB) was performed. ISB HMW melanoidins were almost exclusively composed by an ethanol soluble (EtSn) melanoidin fraction composed by glucose (76% w/w) partially susceptible to in vitro digestion, whereas ISC was composed mainly by arabinogalactans (~41% w/w) and lower amounts of galactomannans (~14% w/w) presenting a range of ethanol solubilities and resistant to in vitro digestion. Melanoidins from ISC presented a significantly higher content of condensed phenolic compounds (17/100 g) when compared to ISB (8/100 g) showing also a higher in vitro scavenging of ABTS•+ (329 mmol Trolox/100 g vs. 124 mmol Trolox/100 g) and NO radicals (inhibition percentage of 57 and 26%, respectively). Nevertheless, ISB EtSn melanoidins presented, on average a higher inhibitory effect on NO production from LPS-stimulated macrophages. ISB melanoidins, up to 1 mg/mL, did not induce toxicity in Caco-2, HepG2 and RAW 264.7 cell lines while at the highest concentration ISC slightly reduced cell viability. Thus, consumption of a diet rich in ISC and ISB melanoidins may reduce the oxidative stress, the inflammatory levels and increase the protective effects against chronic inflammatory diseases.
Design of Time-Mode PI Controller for Switched-Capacitor DC/DC Converter Using Differential Evolution Algorithm—A Design Methodology

This work presents an automated design methodology for time-mode proportional and integral (PI) controllers aimed for an on-chip switched-capacitor (SC) dc/dc converter system. The basis of this design is the use of evolutionary optimization algorithms to find the near-optimal set of sizings for the time-mode PI controller. It is motivated due to the difficulty faced when tuning the controller parameters at a circuit level, which arise as a result of the presence of modeling inaccuracies and the small region for the linearized model where it is defined. Moreover, this design proposes the required modifications for the original design presented for the inductor-based dc/dc converter. These modifications are necessary to operate the SC dc/dc converter in slow switching limit (SSL). The addition of a pulse-width-modulated (PWM)-to-pulse frequency-modulated (PFM) conversion block is presented and elaborated in this article. The controller is codesigned using the differential evolution algorithm for the circuit level implementation to mitigate the issues prior mentioned. The optimized controller is then tested in a simulation environment using TSMC $0.18~\mu \text{m}$ technology. The results of the optimized controller were superior to those of a conventional controller. The optimized system achieved an overall efficiency of 79.1%.