bluuebunny/crossref_metadata_2025_split huggingface dataset:
Virtually delivered Mindfulness-Oriented Recovery Enhancement (MORE) reduces daily pain intensity in patients with lumbosacral radiculopathy: a randomized controlled trial
Authors: Wexler Ryan S. , Fox Devon J. , ZuZero Danielle , Bollen Melissa , Parikshak Anand , Edmond Hannah , Lemau Johnny , Montenegro Diane , Ramirez Jillian , Kwin Sophia , Thompson Austin R. , Carlson Hans L. , Marshall Lynn M. , Kern Thomas , Mist Scott D. , Bradley Ryan , Hanes Douglas A. , Zwickey Heather , Pickworth Courtney K. 
Published: March 2024

Abstract

Introduction:
Lumbosacral radiculopathy (LR), also known as sciatica, is a common type of radiating neurologic pain involving burning, tingling, and numbness in the lower extremities. It has an estimated lifetime prevalence as high as 43%.

Objectives:
The objective of this randomized controlled trial was to evaluate the impact of virtually delivered Mindfulness-Oriented Recovery Enhancement (MORE) on patients with LR during the COVID-19 pandemic.

Methods:
Potentially eligible patients were identified using electronic health record queries and phone screenings. Participants were then randomized to MORE or treatment-as-usual (TAU) for 8 weeks, with pain intensity assessed daily. At baseline and follow-up visits, participants completed questionnaires assessing the primary outcome, disability, as well as quality of life, depression, mindful reinterpretation of pain, and trait mindfulness.

Results:
In our study, patients undergoing virtual delivery of MORE had greater improvements in daily pain intensity (P = 0.002) but not in disability (P = 0.09), depression (P = 0.26), or quality of life (P = 0.99 and P = 0.89, SF-12 physical and mental component scores, respectively), relative to TAU patients. In addition, patients in MORE experienced significantly greater increases in mindful reinterpretation of pain (P = 0.029) and trait mindfulness (P = 0.035).

Conclusion:
Among patients with lumbar radiculopathy, MORE significantly reduced daily pain intensity but did not decrease disability or depression symptoms. Given the long duration of symptoms in our sample, we hypothesize the discrepancy between changes in daily pain intensity and disability is due to fear avoidance behaviors common in patients with chronic pain. As the first trial of a mindfulness intervention in patients with LR, these findings should inform future integrative approaches to LR treatment, particularly when considering the increasing use of virtual interventions throughout the COVID-19 pandemic.
Social health in young women with chronic pain
Authors: Boggero Ian A. , Sangalli Linda , Brasch Lauryn , King Christopher D. 
Published: March 2024

Abstract

Introduction:
Chronic pain may negatively affect social functioning, but no study to date has examined the specific social impact of different chronic pain conditions in young women, and whether living with multiple chronic overlapping pain conditions (COPCs) differently influences social domains.

Objectives:
This study aimed to assess social functioning (social isolation, hostility, informational support satisfaction, social roles, emotional support, friendships, and family relationships) among young women with chronic pain compared with pain-free controls and to test whether the number of COPCs influenced the extent of social burden.

Methods:
Participants aged 18 to 30 years with a physician-confirmed diagnoses of migraine, fibromyalgia, or temporomandibular disorder (TMD) and pain-free controls were invited to participate from across the United States. After confirming eligibility, participants completed a 1-hour REDCap online questionnaire assessing social functioning.

Results:
One hundred four participants (mean age 24.54 ± 3.35 years) were included (n = 26 with TMD, n = 25 with fibromyalgia, n = 25 with migraine, and n = 28 controls). All 3 chronic pain groups combined reported worse functioning than controls on friendship (P = 0.038), social isolation (P = 0.002), and social roles (P < 0.001). There were no differences on social variables between the 3 chronic pain groups (all P's > 0.05). Compared with those with 3 COPCs, participants with 1 condition reported better family relationships (P = 0.024).

Conclusions:
Experience of chronic pain—regardless of the specific pain condition—may negatively affect some areas of social functioning in young women.
The impact of urbanization on youth mental health in Hong Kong
Authors: Cheung Teris , Fong Kwan Hin , Xiang Yu-Tao 
Published: March 2024

Purpose of review
Urbanization is a multifaceted process that can have both positive and negative effects on mental health, especially in adolescents. This paper attempts to summarize the impact of urbanization on youth mental health in Hong Kong.

Recent findings
Several studies have shown that urbanization is associated with an increased risk of youth mental health problems in Hong Kong. Psychosocial factors like perceived stress, social isolation, and exposure to environmental pollutants may contribute to a negative association between urbanization and mental health issues. Academic pressure, poor transparency and accessibility to mental health services in Hong Kong further exacerbate youth's mental health wellbeing. Environmental factors like housing conditions, green spaces, and visible urban greenery have been found to influence mental health outcomes. Existing empirical studies have found a positive association between urbanization and mental health problems, while others have found no association or even a negative association.

Summary
Further research is warranted to investigate the complex relationship between urbanization and youth mental health in Hong Kong. Exploration of effective interventions is necessary to mitigate the negative impacts of urbanization on youth mental health. Understanding this relationship can inform health policy-making and formulate interventions to promote youth's mental health well being in the short-and long run.
Relationship between body regional fat and cardiovascular disease in middle-aged and young adults: Results from NHANES 2011–2018 and Mendelian randomization meta-analysis
Authors: Liu Zheng , Shu Wenqi , Liu Meisi , Chong Wei 
Published: March 2024

ABSTRACTBACKGROUNDTo assess the correlation between regional body fat and cardiovascular diseases in middle-aged and young adults.METHODSInformation on the regional body fat, including the mass and percentage of fat in the head, arms, trunk, and legs, was collected. Data for the observational study were derived from the National Health and Nutrition Examination Survey 2011–2018. The relationship between exposure and outcomes was primarily assessed using restricted cubic splines (RCS), weighted multivariable logistic regression, and subgroup analysis. In the Mendelian randomization (MR) analysis, the outcome was precisely defined as coronary heart disease (CHD), and the data primarily originated from the IEU OpenGWAS project.RESULTSA total of 10,158 participants aged 20–59 years were included, with a prevalence of cardiovascular diseases at 3.4%. Regional body fat was primarily associated with heart disease rather than with stroke. The RCS indicated a positive linear correlation between all body fat masses and the percentage of heart disease. After adjusting for confounding factors, logistic regression analysis revealed significant associations between heart disease and head fat mass (unit: 0.1 kg, odds ratio [OR] = 1.31, p = 0.002), head fat percentage (unit: 1%, OR = 1.37, p = 0.018), arm fat mass (unit: 1 kg, OR = 1.18, p = 0.047), and trunk fat mass (unit: 2.5 kg, OR = 1.14, p = 0.027). Leg fat mass and percentage of fat in the arms, trunk, and legs showed no significant correlation with heart disease (p > 0.05). The IEU OpenGWAS database does not include head-fat information. MR meta-analysis indicated that the fat mass and percentage in the arms, trunk, and legs were all causally related to CHD.CONCLUSIONHead fat mass, head fat percentage, arm fat mass, and trunk fat mass were all associated with heart disease and were likely causally related.WHAT IS KNOWNTrunk fat mass is positively associated with certain cardiovascular risk factors, while leg fat mass is the opposite.Dual-Energy X-ray Absorptiometry measures regional body fat, characterized by its speed, low radiation exposure, and cost-effectiveness, making it suitable for community settings.WHAT THE STUDY ADDSIn middle-aged and young adults, regional body fat mass and percentage are not associated with stroke.Head fat mass, head fat percentage, arm fat mass, and trunk fat mass are all associated with heart disease and are likely causally related.Measurement of fat in the head, arms, and trunk may contribute to early screening forheart diseases in middle-aged and young adults.
Validation of RT-qPCR primers and probes for new and old variants of SARS-CoV-2 in a world scale
Authors: Almeida Alderrosy Fragoso Rodrigues , Almeida Weriskiney Araújo , Pereira Wvelton Mendes , Silva Renato de Santana , Venancio Larissa Paola Rodrigues , Fabres-Klein Mary Hellen , Lima Jonilson Berlink , Klein Raphael Contelli , Araújo-Santos Théo 
Published: March 2024

AbstractIntroductionThe demand for molecular diagnosis of pathogens has surged dramatically since the onset of the COVID-19 pandemic. In this context, different diagnostic tests have been developed to identify SARS-CoV-2 in patient samples. The emergence of new variants of SARS-CoV-2 raises questions about whether the molecular tests available for diagnosis continue to be effective in detecting the virus in biological samples.ObjectiveThis study analyzed the viability of molecular targets directed to N, E and RdRp genes available against the new variants of SARS-CoV-2.MethodologyFor this, we used bioinformatics tools to analyze SARS-CoV-2 genomic data of different variants deposited in GSAID and NCBI virus genomic databases to assess the accuracy of molecular tests available for the diagnosis of COVID-19. We also developed software for analyzing mutation frequencies in different molecular targets from the mutation database.ResultsMutation frequency analysis revealed a high rate of mutations in the N, E and RdRp genes and targets, although the target regions were more conserved. Only three SNPs were recurrent in the sequences of the variants identified in different continents and all in different targets. On the other hand, the registered mutations are not consistent and do not appear frequently in isolates of the same variant in all regions of the world.ConclusionOur data suggest that the molecular targets designed for the first SARS-CoV-2 variants remain valid for the identification of new virus variants despite the large number of identified haplotypes. However, false negative test failures can be identified by using more than one molecular target for the same sample. Genomic regions that are under evolutive selective pressure should be avoided in the use of the diagnostic, once the emergence of new variants may affect the efficiency of molecular testing on a global scale.
Antibiotics damage the colonic mucus barrier in a microbiota-independent manner
Authors: Sawaed Jasmin , Zelik Lilach , Levin Yehonatan , Feeney Rachel , Naama Maria , Gordon Ateret , Zigdon Mor , Rubin Elad , Telpaz Shahar , Modilevsky Sonia , Ben-Simon Shira , Awad Aya , Harshuk-Shabso Sarina , Nuriel-Ohayon Meital , Werbner Michal , Schroeder Bjoern O , Erez Amir , Bel Shai 
Published: March 2024

AbstractAntibiotic use is a risk factor for development of inflammatory bowel diseases (IBDs). IBDs are characterized by a damaged mucus layer, which does not properly separate the host intestinal epithelium from the microbiota. Here, we hypothesized that antibiotics might affect the integrity of the mucus barrier. By systematically determining the effects of different antibiotics on mucus layer penetrability we found that oral antibiotic treatment led to breakdown of the mucus barrier and penetration of bacteria into the mucus layer. Using fecal microbiota transplant, RNA sequencing followed by machine learning andex vivomucus secretion measurements, we determined that antibiotic treatment induces ER stress in the colonic tissue which inhibits colonic mucus secretion in a microbiota-independent manner. This mucus secretion flaw led to penetration of bacteria into the colonic mucus layer, translocation of microbial antigens into circulation and exacerbation of ulcerations in a mouse model of IBD. Thus, antibiotic use might predispose to development of intestinal inflammation by impeding mucus production.
Batch correction methods used in single cell RNA-sequencing analyses are often poorly calibrated
Authors: Emmanúel Antonsson Sindri , Melsted Páll 
Published: March 2024

AbstractAs the number of experiments that employ single-cell RNA-sequencing (scRNA-seq) grows it opens up the possibility of combining results across experiments or processing cells from the same experiment assayed in separate sequencing runs. The gain in the number of cells that can be compared comes at the cost of batch effects that may be present. Several methods have been proposed to combat this for scRNA-seq datasets.We compared seven widely used method used for batch correction of scRNA-seq datasets. We present a novel approach to measure the degree to which the methods alter the data in the process of batch correction, both at the fine scale comparing distances between cells as well as measuring effects observed across clusters of cells. We demonstrate that many of the published method are poorly calibrated in the sense that the process of correction creates measurable artifacts in the data.In particular, MNN, SCVI and LIGER performed poorly in our tests, often altering the data considerably. Batch correction with Combat, BBKNN and Seurat introduced artifacts that could be detected in our setup. However, we found that Harmony was the only method that consistently performed well, in all the testing methodology we present. Due to these result Harmony is the only method we can safely recommend using when performing batch correction of scRNA-seq data.
Investigating demic versus cultural diffusion and sex bias in the spread of Austronesian languages in Vietnam
Authors: Thao Dinh Huong , Dinh Tran Huu , Mitsunaga Shige , Duy La Duc , Phuong Nguyen Thanh , Anh Nguyen Phuong , Anh Nguyen Tho , Duc Bui Minh , Thi Thu Hue Huynh , Ha Nguyen Hai , Ton Nguyen Dang , Hübner Alexander , Pakendorf Brigitte , Stoneking Mark , Inoue Ituro , Duong Nguyen Thuy , Hai Nong Van 
Published: March 2024

AbstractAustronesian (AN) is the second-largest language family in the world, particularly widespread in Island Southeast Asia (ISEA) and Oceania. In Mainland Southeast Asia (MSEA), groups speaking these languages are concentrated in the highlands of Vietnam. However, our knowledge of the spread of AN-speaking populations in MSEA remains limited; in particular, it is not clear if AN languages were spread by demic or cultural diffusion. In this study, we present and analyze new data consisting of complete mitogenomes from 369 individuals and 847 Y-chromosomal single nucleotide polymorphisms (SNPs) from 170 individuals from all five Vietnamese Austronesian groups (VN-AN) and five neighboring Vietnamese Austroasiatic groups (VN-AA). We found genetic signals consistent with matrilocality in some, but not all, of the VN-AN groups. Population affinity analyses indicated connections between the AN-speaking Giarai and certain Taiwanese AN groups (Rukai, Paiwan, and Bunun). However, overall, there were closer genetic affinities between VN-AN groups and neighboring VN-AA groups, suggesting language shifts. Our study provides insights into the genetic structure of AN-speaking communities in MSEA, characterized by some contact with Taiwan and language shift in neighboring groups, indicating that the expansion of AN speakers in MSEA was a combination of cultural and demic diffusion.
Optimizing sequential gene expression modulation for cellular reprogramming - Coupled Boolean modeling and Reinforcement Learning based method
Authors: Singh Vivek 
Published: March 2024

AbstractRegenerative medicine entails regenerating damaged cells and tissues from healthy cells through the process of cellular reprogramming. The most common method to achieve reprogramming of cells of one type to another is by modulating the activity of specific genes. However, identifying the most suitable genes for reprogramming is a challenge due to their large number in humans and their complex interactions.This study describes a computational method to predict sequential gene expression modulation for reprogramming a starting cell type to a target cell type. The proposed method integrates: (1) a Boolean model of the concerned gene regulatory network (GRN); and (2) a reinforcement learning (RL) based model for optimization. The Boolean model is used to capture the dynamic behavior of the GRN and to understand how the gene expression modulation alters its behavior. RL model is used to optimize sequential decision-making of predicting the suitable sequence of gene expression modulation.Coupling of the Boolean model and RL plays a crucial role in the proposed computational method. Boolean model captures the GRN dynamics, and thereby, constrains the combinatorially large state space. The RL model operates in this constrained state space and uses the Boolean model to evaluate the effect of modulations on GRN dynamics to predict the sequence of suitable gene expression modulations.Applicability of the proposed method is demonstrated using a toy network of 4 genes, and a biological network of heart development representing the dynamics of 15 genes.
Cancer-Associated Hypercalcemia Signals Through the Hindbrain to cause Anorexia
Authors: Grinman Diego Y. , Takyar Farzin M. , Dann Pamela , Shanabrough Marya , Brown Stacey , Clemenceau Alisson , Hens Julie R. , Stutz Bernardo , Chodosh Lewis A. , Chang Wenhan , Shulman Gerald I. , Horvath Tamas L. , Wysolmerski John J. 
Published: March 2024

ABSTRACTHypercalcemia, caused by tumor secretion of parathyroid hormone-related protein (PTHrP), is associated with anorexia and weight loss. We demonstrate that overexpression of PTHrP by tumor cells in a transgenic model of breast cancer causes anorexia and rapid weight loss. These changes are accompanied by activation of neurons in the area postrema (AP), the nucleus tractus solitarius (NTS) and the parabrachial nucleus (PBN), a hindbrain circuit regulating food intake. Blocking hypercalcemia prevents anorexia and activation of these brain centers in tumor bearing mice, whereas injecting calcium activates the same circuit in wild-type mice. Neurons in the AP express the calcium-sensing receptor (CaSR) and the same AP/NTS/PBN circuit is stimulated by treating WT mice with cinacalcet, an allosteric activator of the CaSR. Finally, treating diet-induced obese mice with cinacalcet reduces food intake and causes weight loss. These results suggest that CaSR-expressing neurons in the AP might be a pharmacologic target for obesity.
Identifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures
Authors: Ellis Charles A. , Lapera Sancho Martina , Miller Robyn L. , Calhoun Vince D. 
Published: March 2024

AbstractDeep learning methods are increasingly being applied to raw electro-encephalogram (EEG) data. However, if these models are to be used in clinical or research contexts, methods to explain them must be developed, and if these models are to be used in research contexts, methods for combining explanations across large numbers of models must be developed to counteract the inherent randomness of existing training approaches. Model visualization-based explainability methods for EEG involve structuring a model architecture such that its extracted features can be characterized and have the potential to offer highly useful insights into the patterns that they uncover. Nevertheless, model visualization-based explainability methods have been underexplored within the context of multichannel EEG, and methods to combine their explanations across folds have not yet been developed. In this study, we present two novel convolutional neural network-based architectures and apply them for automated major depressive disorder diagnosis. Our models obtain slightly lower classification performance than a baseline architecture. However, across 50 training folds, they find that individuals with MDD exhibit higher β power, potentially higher δ power, and higher brain-wide correlation that is most strongly represented within the right hemisphere. This study provides multiple key insights into MDD and represents a significant step forward for the domain of explainable deep learning applied to raw EEG. We hope that it will inspire future efforts that will eventually enable the development of explainable EEG deep learning models that can contribute both to clinical care and novel medical research discoveries.
srahunter: a user-friendly tool to speed up and simplify data downloading from NCBI SRA
Authors: Bortoletto Enrico , Frizzo Riccardo , Venier Paola , Rosani Umberto 
Published: March 2024

AbstractEasy access and use of vast datasets are paramount for advancing scientific discovery in steadily expanding studies based on high-throughput sequencing (HTS). The Sequence Read Archive (SRA) is a publicly accessible repository currently holding a huge amount of HTS reads, as part of the International Nucleotide Sequence Database Collaboration (INSDC). However, accessing, downloading, and managing data and metadata efficiently can be challenging. Here, we introducesrahunter, a tool designed to simplify data and metadata acquisition from SRA. Developed with Python,srahunterleverages the core functionalities ofSRA ToolkitandEntrez Direct, to enable automated downloading, smart data management, and user-friendly metadata integration through an interactive HTML tablehttps://github.com/GitEnricoNeko/srahunter. Compared to existing tools,srahunterincreases the efficiency of metadata retrieval by reducing the technical barriers to SRA data and streamlining the handling of SRA datasets, and can therefore accelerate the development of genomics and multiple ‘omics research.