bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Mediating Effect of Uncertainty in Illness on Cancer Coping in Patients With Primary Malignant Brain Tumors
Authors: Hong Soomin , Lee JuHee , Lee Jiyeon , Chang Jong Hee , Park Chang Gi , Kim Tae Hee 
Published: December 2022

Background
Patients with primary malignant brain tumors (PMBTs) experience uncertainty in illness (UI) because of the high recurrence rate and symptoms that occur during treatment.

Objective
To develop and test a model based on the Uncertainty in Illness Theory to predict the UI and cancer coping experienced by PMBT patients.

Methods
This was a cross-sectional study using path analysis. The participants were adults diagnosed with PMBT who completed a questionnaire about demographic and disease-related characteristics, UI, cancer coping, brain tumor symptoms, and social support. Clinical data (eg, the diagnosis, tumor location, and grade) were obtained from electronic health records. Data were analyzed using SPSS 26.0 and the MVN, psych, and lavaan packages in R 4.1.0.

Results
This study included 203 PMBT patients. The hypothesized model satisfied all statistical criteria (comparative fit index = 0.998, root mean square error of approximation = 0.044, standardized root mean square residual = 0.016). The indirect and direct associations of UI in the path from social support to cancer coping were all significant with a 95% bootstrapping confidence interval. Although the indirect and direct associations of UI in the path of brain tumor symptoms and cancer coping did not have direct or total effects, the indirect effect was statistically significant.

Conclusions
Uncertainty in illness mediated brain tumor symptoms and social support to predict cancer coping.

Implications for Practice
A nurse-led intervention for cancer coping among PMBT patients can be developed by considering symptoms and social support and UI as a mediator.
A Uniform Chart of Accounts: Strengthening Public Health Practice and Research Through Standardized Financial Data
Authors: Bekemeier Betty , Heitkemper Elizabeth , Zaichkin Dana L. , Whitman Greg , Singh Simone R. , Leider Jonathon P. 
Published: December 2022

Context:
The COVID-19 pandemic made the long-standing need for a national uniform financial reporting standard for governmental public health agencies clear, as little information was available to quantify state and local public health agencies' financial needs during the pandemic response. Such a uniform system would also inform resource allocation to underresourced communities and for specific services, while filling other gaps in practice, research, and policy making. This article describes lessons learned and recommendations for ensuring broad adoption of a national Uniform Chart of Accounts (UCOA) for public health departments.

Program:
Leveraging previous efforts, the UCOA for public health systems was developed through collaboration with public health leaders. The UCOA allows state and local public health agencies to report spending on activities and funding sources, along with practice-defined program areas and capabilities.

Implementation:
To date, 78 jurisdictions have utilized the UCOA to crosswalk financial information at the program level, enabling comparisons with peers.

Evaluation:
Jurisdictions participating in the UCOA report perceptions of substantial up-front time investment to crosswalk their charts of accounts to the UCOA standard but derive a sense of valuable potential for benchmarking against peers, ability to engage in resource allocation, use of data for accountability, and general net positive value of engagement with the UCOA.

Implications for Policy and Practice:
The UCOA is considered a need among practice partners. Implementing the UCOA at scale will require government involvement, a reporting requirement and/or incentives, technical assistance, financial support for agencies to participate, and a means of visualizing the data.
The Management of Upper Limb Amputation Rehabilitation: Synopsis of the 2022 U.S. Department of Veterans Affairs and U.S. Department of Defense Clinical Practice Guideline for Acquired Amputation
Authors: Crunkhorn Andrea , Andrews Erin , Fantini Christopher , Highsmith M. Jason , Loftsgaarden Megan , Randolph Billie , Sall James , Webster Joseph 
Published: December 2022

Abstract
Upper limb amputation (ULA) can result in significant functional impairment necessitating a comprehensive rehabilitation approach throughout the continuum of care. In 2022, the Departments of Veteran Affairs (VA) and Defense (DOD) completed an updated clinical practice guideline (CPG) for the management of ULA rehabilitation. This practice guideline was developed by a workgroup of subject-matter experts from a variety of disciplines. Twelve key questions were developed by the workgroup using the PICOTS (population, intervention, comparator, outcomes, timing of outcomes measurement, and setting) format to establish the scope of the literature review. Eighteen recommendations were developed through extensive review of the available literature and use of the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) criteria. The strength of each recommendation was determined based upon the quality of the research evidence and the additional domains of the GRADE criteria. Of the 18 recommendations, 4 were found to have sufficient evidence to suggest for use of a particular rehabilitation management strategy. Thus, the 2022 VA/DOD CPG provides updated, evidence-based information on the care and rehabilitation of persons with ULA. However, a significant lack of high-quality evidence in ULA rehabilitation limited evidence-based clinical guidance to assist healthcare providers in managing this population.
Menstruation Hygiene Management among Secondary School Students of Chitwan, Nepal- Pre-Post Study Design
Authors: Khanal Gayatri , Shrestha Niki , Adhikari Kishor , Ghimire Usha 
Published: December 2022

AbstractIntroductionDespite of significant progress towards reproductive health, still in many societies menstruation is treating as negative, shameful or dirty consequences which may increases the incidence of reproductive tract infection leading to significant negative impact to a women’s health. To manage menstruation hygienically and with dignity, it is essential that women and girls have sufficient knowledge on menstruation hygiene management to manage it. Thus, this study aim to identify the knowledge and practice of menstruation hygiene and effectiveness of a health educational intervention on MHM.MethodsA school-based cross-sectional study was conducted between August 2021 to April 2022 among 400 secondary school girls studying in grades 9 and 10 in Chitwan District, Nepal. A total of 20 schools out of 250 schools were selected through lottery method. A further 400 girls were selected from selected schools by using systematic random method. Logistic regression analysis and Wilcoxon rank test were employed to identify predictors and evaluate effectiveness of health educational intervention on Menstrual Hygiene ManagementResultsOverall, 57.7% of the girls had unsatisfactory level of knowledge. Around two third (61.4%) missed schools days. Almost 99.5% had experienced any form of cultural restrictions. After health education intervention, level of knowledge about menstruation hygiene had significantly improved (z= 17.129, p=<0.001) in satisfactory level of knowledge compared to baseline (42.3% vs 92.5%). During multivariate analysis, studied in public schools (AoR= 1.7, p= 0.026), No or one close female friend (AoR= 2.2, p= 0.011), other than Brahmin/Chhetri caste (AoR= 1.4, p= 0.05), lived in joint family (AoR= 1.6, p= 0.048) were significantly associated with unsatisfactory level of knowledge on Menstruation hygiene management.ConclusionGirls had unsatisfactory level of knowledge. School absenteeism and cultural restriction is very high. Ethnicity status, Types of family, Number of close female friends, types of schools and mothers’ education were associated with MHM.. Educational program conducted brings significant change in level of knowledge. Hence the education intervention demonstrate the suitability and feasibility of implementing a health educational intervention on MHM.
Dysfunctional analysis of the pre-training model on nucleotide sequences and the evaluation of different k-mer embeddings
Authors: Zhang Yao-zhong , Bai Zeheng , Imoto Seiya 
Published: December 2022

AbstractPre-training has attracted much attention in recent years. Although significant performance improvements have been achieved in many downstream tasks using pre-training, the mechanism of how a pre-training method works for downstream tasks is not fully illustrated. In this work, focusing on nucleotide sequences, we decompose a pre-training model of Bidirectional Encoder Representations from Transformers (BERT) into embedding and encoding modules to illustrate what a pre-trained model learns from pre-training data. Through dysfunctional analysis on both data and model level, we demonstrate that the context-consistent k-mer representation is the primary product that a typical BERT model learns in the embedding layer. Surprisingly, single usage of the k-mer embedding pre-trained on the random data can achieve comparable performance to that of the k-mer embedding pre-trained on actual biological sequences. We further compare the learned k-mer embeddings with other commonly used k-mer representations in downstream tasks of sequence-based functional predictions and propose a novel solution to accelerate the pre-training process.Contactyaozhong@ims.u-tokyo.ac.jporimoto@hgc.jpSupplementary informationThe source code and relevant data are available athttps://github.com/yaozhong/bert_investigation.
Expanded olfactory system in fishes capable of terrestrial exploration
Authors: Burguera Demian , Dionigi Francesco , Kverková Kristina , Winkler Sylke , Brown Thomas , Pippel Martin , Zhang Yicheng , Shafer Maxwell , Nichols Annika L.A. , Myers Eugene , Němec Pavel , Musilova Zuzana 
Published: December 2022

AbstractSmell abilities differ greatly among vertebrate species, as reflected by the exceptional size variability of gene families and brain regions involved in odour detection. However, key environmental factors shaping the molecular and phenotypic evolution of the olfactory sensory system remain mostly unknown. Here, we investigate the association between diverse ecological traits and the number of olfactory chemoreceptors in the genomes of more than two hundred ray-finned fishes. We found independent expansions producing large gene repertoires in nocturnal amphibious fishes, generally able to perform active terrestrial exploration. Furthermore, we reinforced this finding with an additional analysis of a clariid species (Channallabes apus), a fish lineage with chemosensory-based aerial orientation. Importantly, we also detected an augmented information-processing capacity in the olfactory bulb of examined nocturnal amphibious species. Overall, we report a convergent magnification of the olfactory system in amphibious fishes potentially enhancing terrestrial orientation, revealing the likelihood of an analogous event in tetrapod ancestors during the water-to-land transition.
Extensive immune receptor repertoire diversity in disease-resistant rice landraces
Authors: Gladieux Pierre , van Oosterhout Cock , Fairhead Sebastian , Jouet Agathe , Ortiz Diana , Ravel Sebastien , Shrestha Ram-Krishna , Frouin Julien , He Xiahong , Zhu Youyong , Morel Jean-Benoit , Huang Huichuan , Kroj Thomas , Jones Jonathan D G 
Published: December 2022

AbstractPlants have powerful defence mechanisms, and extensive immune receptor repertoires, yet crop monocultures are prone to epidemic diseases. Rice is susceptible to many diseases, such as rice blast caused byMagnaporthe oryzae. Varietal resistance of rice to blast relies on intracellular nucleotide binding, leucine-rich repeat (NLR) receptors that recognize specific pathogen molecules and trigger immune responses. In the Yuanyang terraces in south-west China, rice landraces rarely show severe losses to disease whereas commercial inbred lines show pronounced field susceptibility. Here, we investigate within-landrace NLR sequence diversity of nine rice landraces and eleven modern varieties ofindica, japonicaandaususing complexity reduction techniques. We find that NLRs display high sequence diversity in landraces, consistent with balancing selection, and that balancing selection at NLRs is more pervasive in landraces than modern varieties. Notably, modern varieties lack many ancient NLR haplotypes that are retained in some landraces. Our study emphasises the value of standing genetic variation that is maintained in farmer landraces as resource to make modern crops and agroecosystems less prone to disease.
Boosting wheat functional genomics via indexed EMS mutant library of KN9204
Authors: Wang Dongzhi , Li Yongpeng , Wang Haojie , Xu Yongxin , Yang Yiman , Zhou Yuxin , Chen Zhongxu , Zhou Yuqing , Gui Lixuan , Guo Yi , Zhou Chunjiang , Tang Wenqiang , Zheng Shuzhi , Wang Lei , Guo Xiulin , Zhang Yingjun , Cui Fa , Lin Xuelei , Jiao Yuling , He Yuehui , Li Junming , He Fei , Liu Xigang , Xiao Jun 
Published: December 2022

SummaryA better understanding of wheat functional genomics could facilitate the targeted breeding for agronomic traits improvement and environmental adaptation. With the release of reference genomes and extensive re-sequencing data of wheat and relatives, wheat functional genomics enters a new era. However, limited transformation efficiency in wheat hampers in-depth gene functional study and genetic manipulation for breeding. Here, we generated an EMS mutagenesis library of KN9204, a widely grown elite wheat variety in northern China, with available reference genome, transcriptome, and epigenome of various tissues. The library harbors enormous developmental diversity covering important tissues and transition stages. Exome capture sequencing of 2,090 mutant lines, with probes designed by KN9204 genome, revealed that 98.79% of coding genes have mutations and 1,383 EMS-type SNPs per line averagely. Novel allelic variations for important agronomic trait-related genes, such asRht-D1, Q, TaTB1, andWFZP, were identified. We tested 100 lines with severe mutations in 80 NAC TFs under drought and salinity stresses, and found 13 lines with altered sensitivity. Three lines were further analyzed for the regulation insight of NAC TFs in stress response by combing transcriptome and available chromatin accessibility data. Hundreds of direct targets of NAC with altered transcriptional pattern in mutant lines under salt or drought stress induction were identified, includingSNAC1, DREB2B, CML16andZFP182, knowing factors in abiotic stresses response. Thus, we have generated and indexed KN9204 EMS mutant library which would facilitate functional genomics study and provide resources for genetic manipulation in wheat.
Fast and accurate protein function prediction from sequence through pretrained language model and homology-based label diffusion
Authors: Yuan Qianmu , Xie Junjie , Xie Jiancong , Zhao Huiying , Yang Yuedong 
Published: December 2022

AbstractProtein function prediction is an essential task in bioinformatics which benefits disease mechanism elucidation and drug target discovery. Due to the explosive growth of proteins in sequence databases and the diversity of their functions, it remains challenging to fast and accurately predict protein functions from sequences alone. Although many methods have integrated protein structures, biological networks or literature information to improve performance, these extra features are often unavailable for most proteins. Here, we propose SPROF-GO, a Sequence-based alignment-free PROtein Function predictor which leverages a pretrained language model to efficiently extract informative sequence embeddings and employs self-attention pooling to focus on important residues. The prediction is further advanced by exploiting the homology information and accounting for the overlapping communities of proteins with related functions through the label diffusion algorithm. SPROF-GO was shown to surpass state-of-the-art sequence-based and even network-based approaches by more than 14.5%, 27.3% and 10.1% in AUPR on the three sub-ontology test sets, respectively. Our method was also demonstrated to generalize well on non-homologous proteins and unseen species. Finally, visualization based on the attention mechanism indicated that SPROF-GO is able to capture sequence domains useful for function prediction.Key pointsSPROF-GO is a sequence-based protein function predictor which leverages a pretrained language model to efficiently extract informative sequence embeddings, thus bypassing expensive database searches.SPROF-GO employs self-attention pooling to capture sequence domains useful for function prediction and provide interpretability.SPROF-GO applies hierarchical learning strategy to produce consistent predictions and label diffusion to exploit the homology information.SPROF-GO is accurate and robust, with better performance than state-of-the-art sequence-based and even network-based approaches, and great generalization ability on non-homologous proteins and unseen species
Design of MEG-Based Brain-Machine Interface Control Methodology Through Time-Varying Cortical Neural Connectivity & Extreme Learning Machine
Authors: Uyulan Caglar 
Published: December 2022

AbstractHuman-machine interfaces contribute to the improvement of the life quality of physically disabled users. In this study, a non-invasive brain-machine interface (BMI) design methodology was proposed to control a robot arm through magnetoencephalography (MEG) based on directionally modulated MEG activity that was acquired during the user’s imagined wrist movements in four various directions. The partial directed coherence (PDC) measure derived from functional connectivity between cortical brain regions was utilized in the feature extraction process. The time-varying parameters were estimated based on a time-varying multivariate adaptive autoregressive (AAR) model, that can detect task-dependent features and non-symmetric channel relevance for mental task discrimination. An extreme learning machine (ELM), that utilizes Moore-Penrose (MP) generalized inverse to set its weights and does not necessitate a gradient-based backpropagation algorithm was employed to generate a model with the extracted feature set. The output of the task classification model was embedded into the robotic arm model for realizing control-based tasks. The classification results dictate that the proposed BMI methodology is a feasible solution for rehabilitation or assistance systems that are devised to help motor-impaired people. The proposed methodology provides very satisfactory classification performance at a fast learning speed.
HLA-Glyco: A large-scale interrogation of the glycosylated immunopeptidome
Authors: Bedran Georges , Polasky Daniel A. , Hsiao Yi , Yu Fengchao , Veiga Leprevost Felipe da , Alfaro Javier A. , Cieslik Marcin , Nesvizhskii Alexey I. 
Published: December 2022

AbstractMHC-associated peptides (MAPs) bearing post-translational modifications (PTMs) have raised intriguing questions regarding their attractiveness for targeted therapies. Here, we developed a novel computational glyco-immunopeptidomics workflow that integrates the ultrafast glycopeptide search of MSFragger with a glycopeptide-focused false discovery rate (FDR) control. We performed a harmonized analysis of 8 large-scale publicly available studies and found that glycosylated MAPs are predominantly presented by the MHC class II. We created HLA-Glyco, a resource containing over 3,400 human leukocyte antigen (HLA) class II N-glycopeptides from 1,049 distinct protein glycosylation sites. Our comprehensive resource reveals high levels of truncated glycans, conserved HLA-binding cores, and differences in glycosylation positional specificity between classical HLA class II allele groups. To support the nascent field of glyco-immunopeptidomics, we include the optimized workflow in the FragPipe suite and provide HLA-Glyco as a free web resource.
Detection of rare mutations, copy number variation, and DNA methylation in the same template DNA molecules
Authors: Wang Yuxuan , Douville Christopher , Cohen Joshua D. , Mattox Austin , Curtis Sam , Silliman Natalie , Popoli Maria , Ptak Janine , Dobbyn Lisa , Nehme Nadine , Dudley Jonathan C. , Summers Mahmoud , Zhang Ming , Bettegowda Chetan , Papadopoulos Nickolas , Kinzler Kenneth W. , Vogelstein Bert 
Published: December 2022

ABSTRACTThe analysis of cell-free DNA (cfDNA) from plasma offers great promise for the earlier detection of cancer. At present, changes in DNA sequence, methylation, or copy number are the most sensitive ways to detect the presence of cancer. To further increase the sensitivity of such assays with limited amounts of sample, it would be useful to be able to evaluate the same template molecules for all these changes. Here we report an approach, called MethylSaferSeqS, that achieves this goal, and can be applied to any standard library preparation method suitable for massively parallel sequencing. The innovative step was to copy both strands of each DNA-barcoded molecule with a primer that allows the subsequent separation of the original strands (retaining their 5-methylcytosine residues) from the copied strands (in which the 5-methylcytosine residues are replaced with unmodified cytosine residues). The epigenetic and genetic alterations present in the DNA molecules can then be obtained from the original and copied strands, respectively. We applied this approach to plasma from 265 individuals, including 198 with cancers of the pancreas, ovary, lung and colon, and found the expected patterns of mutations, copy number alterations, and methylation. Furthermore, we could determine which original template DNA molecules were methylated and/or mutated. MethylSaferSeqS should be useful for addressing a variety of questions relating genetics and epigenetics in the future.