bluuebunny/crossref_metadata_2025_split huggingface dataset:
Magmatism Controls Global Oceanic Transform Fault Topography
Authors: Tian Xiaochuan , Behn Mark , Ito Garrett , Schierjott Jana , Kaus Boris , Popov Anton 
Published: September 2023

Abstract
Oceanic transform faults are fundamental features of plate tectonics, accommodating strike-slip motion between two adjacent mid-ocean ridge segments. The continuations of these faults form tectonically inactive fracture zones, creating the longest ‘scars’ on the Earth’s surface. Yet, despite the relatively simple kinematic and thermal structures, oceanic transform faults display an enigmatic continuum of morphologies ranging from deep valleys to small ridges. Here, through three-dimensional numerical modeling of two mid-ocean ridge segments separated by a transform fault, we find that the rate of magma intrusion within the transform domain exerts a first-order control on transform topography. Low-rate magmatism results in transform-parallel tectonic stretching, generating deep transform valleys and fracture zones. Intermediate-rate magmatism fully accommodates far-field stretching, but strike-slip motion induces across-transform tension, producing shallow valleys whose depth increases with the shear strength of the fault. High-rate magmatism leads to local compression that generates fault-parallel ridges. The models not only reproduce the observed global transform valley depths but also predict the observation that fracture zones are consistently shallower than their adjacent transform valleys. These results suggest that plate motion changes are not a necessary condition for generating oceanic transform topography and that oceanic transform faults are not simple conservative strike-slip plate boundaries.
From remains to results: assessing the feasibility of free DNA for disaster victim identification and forensic applications
Authors: Worrapitirungsi Wikanda , Sathirapatya Tikumphorn , Sukawutthiya Poonyapat , Vongpaisarnsin Kornkiat , Varrarthyarom Pagparpat 
Published: September 2023

Abstract
In tropical disaster victim identification (DVI) scenarios, challenging environmental conditions lead to accelerated DNA degradation in remains. To further enhance the utilization of leached DNA from tissue in the preservative solution (termed "free DNA") as an alternative source, we incorporated new results by assessing its integrity in postmortem and decomposing cadavers preserved in DNA/RNA Shield™ and modified TENT, with silica-based purification (QIAquick®) for faster processing. The psoas muscle tissues of one decomposed and ten cadavers were preserved in each solution at 25°C and 35°C for three months. Free DNA efficiency was compared with individual reference samples for reliable results in quantity, quality, and STR profiles. The findings revealed that DNA/RNA Shield™ effectively preserves free DNA integrity for extended storage, while modified TENT is more suitable for short-term storage due to higher degradation levels. Moreover, the use of free DNA samples with massive parallel sequencing displays potential for forensic DNA analysis. Successful amplification of the mtDNA control region enables variant calling and heteroplasmy analysis, while also serving for quality control using ACTB and enabling differentiation within the 16S rRNA region for microbiome analysis. The simplicity of handling free DNA for PCR-based forensic analysis adds to its potential for various applications, including DVI and field-based analysis of biological evidence.
Ensemble of Self-supervised Learning Methods for Robust Skin Disease Image Diagnosis Leveraging Unlabeled Data
Authors: Kojima Kaname , Tadokoro Ryu , Kinoshita Kengo , Asano Yoshihide , Yamasaki Kenshi , Shido Kosuke 
Published: September 2023

Abstract
Deep learning technologies have led to remarkable improvements in medical image analysis, but the collection and annotation of medical data remain challenging. This study leverages self-supervised learning and unlabeled images from the National Skin Disease Database of Japan (NSDD) to enhance skin disease classification. By generating pre-trained models using three self-supervised learning methods, and comparing them to a baseline pre-trained model on ImageNet, we found that pre-training with unlabeled images increased transfer learning performance by 1-2% on labeled images in the NSDD. We also demonstrated the effectiveness of the pre-trained models across four public dermatological image datasets. We further implemented a hybrid pre-training approach that combines self-supervised and supervised learning, and observed accuracy improvements in certain datasets. Since the optimal strategy is task and dataset-specific, we proposed an ensemble of transfer learned models from diverse pre-training methods for robust classification. The ensemble approach consistently enhanced accuracy across various datasets, with an improvement by up to 8.3% from the baseline, confirming the effectiveness of self-supervised pre-training with unlabeled dermatological images even when the images are mainly from one ethnic group.
Impact of familiarity with the format of the exam on performance in the OSCE of 5th undergraduate medical students – an interventional study
Authors: Neuwirt Hannes , Eder Iris Elisabeth , Gauckler Philipp , Horvath Lena , Koeck Stefan , Noflatscher Maria , Schaefer Benedikt , Simeon Anja , Petzer Venera , Prodinger Wolfgang , Berendonk Christoph 
Published: September 2023

Abstract

Background: Assessments aim to verify whether students have acquired the necessary competencies. These assessments are typically carried out as summative structured examinations. It is important not only to establish a constructive alignment between teaching and assessment but also to familiarize students with the examination format prior to the assessment. The latter point is intended to ensure that true competency is measured. Regarding practical examinations such as objective structured clinical examinations (OSCEs), this is often not the case. Therefore, it is unclear whether students can demonstrate their true potential or possibly perform less effectively due to the unfamiliar examination format. Hence, we questioned whether a 10-minute active familiarization in the form of simulation improved medical students´ OSCE performance. Next, we wanted to elucidate whether the effect depends on whether the familiarization procedure is active or passive. Methods: We implemented an intervention consisting of a 10-minute active simulation to prepare the students for the OSCE setting. We compared the impact of this intervention on performance to no intervention in 5th-year medical students (n=1284) from 2018 until 2022. Recently, a passive lecture, in which the OSCE setting is explained without active participation of the students, was introduced as a comparator group. Students who participated in neither the intervention nor the passive lecture group formed the control group. The OSCE performance between the groups and the impact of gender was assessed using X2, nonparametric tests and regression analysis (total n=362). Results: We found that active familiarization of students in the exam setting yields significantly better performance compared to the passive comparator (Cohen´s d=0.857, p<0.001)) and control group (Cohen´s d=0.473, p<0.001). In multivariate regression analysis, active intervention remained the only significant variable with a 2.945-fold increase in the probability of passing the exam (p=0.018). Conclusions: A short 10-minute active intervention to familiarize students with the OSCE setting significantly improved student performance. We suggest that curricula should include simulations on the exam setting in addition to courses that increase knowledge or skills to mitigate the negative effect of nonfamiliarity with the OSCE exam setting on the student.
Coupling normothermic machine perfusion with mesenchymal stem cell bioreactors: benefits exerted on the rat liver
Authors: Lonati Caterina 
Published: September 2023

Abstract

Administration of mesenchymal-stem-cells (MSCs) during Normothermic-Machine-Perfusion (NMP) reduces ischemia/reperfusion injury, but the strategy to apply cell-based therapies ex-situ can hamper their effectiveness. To fully harness MSCs potential, we developed an advanced perfusion system equipped with a MSCs-bioreactor and investigated its benefits on the rat liver.
The study involved two work packages: 1) Development: bioreactors seeded with 2x107 human adipose tissue-derived MSCs were connected to the NMP circuit and subjected to 4h-liverless perfusion (Liverless-NMP,n=5); 2) MSCs-bioreactor-based liver NMP: rat livers were perfused for 4h on the NMP circuit coupled with the MSCs-bioreactor (NMP+bioreactor,n=5) or without it (NMP,n=5).
MSCs remained metabolically active during liverless-NMP and showed a preserved expression of stemness-related markers. When used for liver NMP, MSCs changed their secretome in a liver-tailored manner. Organs exposed to the MSCs-bioreactor-based perfusion produced more bile, released less damage biomarkers, and showed higher ATP content with reduced succinate accumulation than those subjected to NMP alone. A lower release of pro-inflammatory mediators and the induction of factors involved in resolution/regeneration were also observed.
This proof-of-concept study provides a novel MSCs-based protocol for liver NMP, thereby creating a modern perfusion platform able to preserve mitochondrial function, sustain hepatic cell viability, reduce inflammation, and trigger healing processes.
Synthetic rescue of XPC phenotype via PIK3C3 downregulation
Authors: Gidrol Xavier , Kobaisi Farah , Sulpice Eric , Nasrallah Ali , Fayyad-kazan Hussein , Rachidi Walid 
Published: September 2023

Abstract

Xeroderma Pigmentosum C is a dermal hereditary disease. It is caused by a mutation in the DNA damage recognition protein XPC that belongs to the Nucleotide excision repair pathway. XPC patients exhibit a photosensitive phenotype and fail to repair UV induced DNA lesions leading to their accumulation and ultimate conversion to mutations and carcinomas. In an attempt to normalize this phenotype, we screened a library of siRNAs targeting the human kinases, given their role in different DNA repair pathways. WT and XPC immortalized patient fibroblasts were transfected with the library then irradiated with UVB to induce DNA damage. XPC phenotypic reversal was monitored by the quantification of decreased photosensitivity and increased DNA damage repair. Out of the 1292 kinase siRNAs tested, twenty-eight were selected cellular survival compared to cells transfected with non-targeting siRNA in XP-C irradiated cells. Out of the selected hits, two kinases, PIK3C3 and LATS1, induce more than 20% repair of 6-4PP DNA lesions. The down regulation of autophagy-related protein PIK3C3 alone had an exclusive photo protective effect on XP-C irradiated cells validated these effects also on primary XP-C patient fibroblasts and CRISPR-Cas9 generated XPC-KO keratinocytes. PIK3C3 knock down in XP-C cells ameliorated in UVB dose response analysis, decreased apoptosis and lowered phosphorylation of P53 with no effect on proliferation. More importantly, PIK3C3 knock down induced an increase in UVRAG expression, a previously reported cDNA conveying lower photosensitivity in XP-C cells. Attempts to improve the XPC photosensitive and deficient repair phenotype using PIK3C3 inhibitors could thus pave a way for new therapeutic approaches delaying or preventing tumor initiation.
Prediction of Adverse Events Risk in Patients with Comorbid Post- Traumatic Stress Disorder and Alcohol Use Disorder Using Electronic Medical Records by Deep Learning Models
Authors: Miranda Oshin , Fan Peihao , Qi Xiguang , Wang Haohan , Brannock M Daniel , Kosten Thomas , Ryan Neal David , Kirisci Levent , Wang LiRong 
Published: September 2023

Abstract

Background Prediction of high-risk events in mental disorder patients is crucial. In our previous study, we developed a deep learning model: DeepBiomarker by using electronic medical records (EMR) to predict suicide related event (SRE) risk in post-traumatic stress disorder (PTSD) patients. Methods We applied DeepBiomarker2 through data integration of multimodal information: lab test, medication, co-morbidities, and social determinants of health. We analyzed EMRs of 5,565 patients from University of Pittsburgh Medical Center with a diagnosis of PTSD and alcohol use disorder (AUD) on risk of developing an adverse event (opioid use disorder, SREs, depression and death). Results DeepBiomarker2 predicted whether a PTSD + AUD patient will have a diagnosis of any adverse events (SREs, opioid use disorder, depression, death) within 3 months with area under the receiver operator curve (AUROC) of 0.94. We found piroxicam, vilazodone, dronabinol, tenofovir, suvorexant, empagliflozin, famciclovir, veramyst, amantadine, sulfasalazine, and lamivudine to have potential to reduce risk. Conclusions DeepBiomarker2 can predict multiple adverse event risk with high accuracy and identify potential risk and beneficial factors. Our results offer suggestions for personalized interventions in a variety of clinical and diverse populations.
Assessment of outdoor thermal human comfort over Houche Al-Oumara, North Lebanon
Authors: ELCHAAR ALI ADNAN , Hewehy Mahmoud Ahmed , Abbas Ismail Ibrahim , Robaa El-Sayed Mohamed Abdel-Hamid , Mostafa Mohammed Salah El-din Mostafa Mohammed Salah El-din Mostafa 
Published: September 2023

Abstract
This study investigated thermal discomfort in Houche Al-Oumara from 1994 to 2021 using different discomfort indices and analyzed data on temperatures, relative humidity, and rainfall. It was found that July and August had significantly higher mean temperatures compared to other months, with the highest temperature occurring in July. Conversely, January was the coldest month. The study observed a linear increase in mean air temperature from January to July, followed by a linear decrease from July to December. Similar patterns were observed for relative humidity, but in the opposite direction. Less than half of the population experienced thermal discomfort during July and August. The study emphasized the importance of understanding long-term thermal discomfort trends, considering global warming, urbanization, and population growth. Rainfall data analysis revealed significant variability in the annual average rainfall over the years, without a clear trend. Periods of consecutive years with above-average or below-average rainfall were identified. These findings are valuable for policymakers in managing human thermal comfort in rural areas. They provide insights into the influence of environmental factors such as air temperature, relative humidity, and rainfall. The results can assist in developing strategies to address heat stress-related health risks and plan for sustainable development in North Lebanon.
Free particles beyond fermions and bosons
Authors: Wang Zhiyuan , Hazzard Kaden 
Published: September 2023

Abstract

It is commonly believed that there are only two types of particle exchange statistics in quantum mechanics, fermions and bosons, with the exception of anyons in two dimension [1-4]. In principle, a second exception known as parastatistics, which extends outside of two dimensions, has been considered [5] but was believed to be physically equivalent to fermions and bosons [6, 7]. In this paper we show that nontrivial parastatistics inequivalent to either fermions or bosons can exist in physical systems. These new types of identical particles obey generalized exclusion principles, leading to exotic free-particle thermodynamics distinct from any system of free fermions and bosons. We formulate our theory by developing a second quantization of paraparticles, which naturally includes exactly solvable non-interacting theories, and incorporates physical constraints such as locality. We then construct a family of one-dimensional quantum spin models where free parastatistical particles emerge as quasiparticle excitations. This demonstrates the possibility of a new type of quasiparticle in condensed matter systems, and, more speculatively, the potential for previously unconsidered types of elementary particles.
Near full-length genome analysis of two novel HIV second recombinant forms in Hebei, China.
Authors: FENG YUXIN , Lu Jianhua , Wang LiJing , Han Jingwan , Wang Yuling , Li Chen , Wang Xiaolin , Li Beilei , Liu Yongjian , Xiaojing Qu , Jia Lei , Chen Qian , Yao Ru , Li Yingxia , Feng Fumin , Li Jingyun , Li Hanping , Li Lin , DAI ERHEI 
Published: September 2023

Abstract
Individuals infected with HIV-1 among men who have sex with men (MSM) rose rapidly in recent years in China, and such subtypes as CRF01_AE, CRF07_BC, B, and some novel URFs were prevalent among them. Co-circulation of strains among MSM populations allows the development of CRFs and URFs. In the study, we reported two new URFs from two HIV-1-positive subjects infected through homosexual contact routes in Hebei, China. Two URFs originated from CRF01_AE, CRF07_BC, and B through analysis of near full-Length genome (NFLG) using phylogenetic tree and recombinant analysis, and CRF01_AE segments in the backbone of URFs derived from cluster 4 of CRF01_AE. The CRF07_BC segments of two URFs were clustered with 07BC_N. The development of novel URFs with complicated genomic structures continually indicated that it was necessary to strengthen the survey of the HIV-1 prevalence and new URFs among the MSM populations in this region.
Genetically encoded transcriptional plasticity underlies stress adaptation in Mycobacterium tuberculosis
Authors: Liu Qingyun , Bei Cheng , Zhu Junhao , Culviner Peter , Rubin Eric , Fortune Sarah , Gao Qian 
Published: September 2023

Abstract
Transcriptional regulation is a critical adaptive mechanism that allows bacteria to respond to changing environments, yet the concept of transcriptional plasticity (TP) remains largely unexplored. In this study, we investigate the genome-wide TP profiles of Mycobacterium tuberculosis (Mtb) genes by analyzing 894 RNA sequencing samples derived from 73 different environmental conditions. Our data reveal that Mtb genes exhibit significant TP variation that correlates with gene function and gene essentiality. We also found that critical genetic features, such as gene length, GC content, and operon size independently impose constraints on TP, beyond trans-regulation. By extending our analysis to include two other Mycobacterium species -- M. smegmatis and M. abscessus -- we demonstrate a striking conservation of the TP landscape. This study provides a comprehensive understanding of the TP exhibited by mycobacteria genes, shedding light on this significant, yet understudied, genetic feature encoded in bacterial genomes.
Diagnostic value of cuproptosis-related genes in sepsis: A novel model based on bioinformatics screening
Authors: Jia Xuan , Tian Yuan , Zhang Dian , Chen Siqia , Meng Dongmei 
Published: September 2023

Abstract

Background: Sepsis is a life-threatening functional disorder of the organs resulting from a dysregulated host immune response to infection and is a leading cause of death and critical illness worldwide. Genetic diagnosis combined with big data analysis of existing biomarkers has great potential in the diagnosis and prognosis prediction of sepsis, and there is an urgent need to construct prognostic models that will improve the effectiveness of treatment decisions. Methods: We used data from the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) database to perform a comprehensive analysis of differential gene expression profiles associated with cuproptosis in sepsis. Combining the sepsis datasets (GSE131761 and GSE54514) as test sets, a total of 208 sepsis samples and 69 normal samples were used for the analysis of cuproptosis-related differentially expressed genes (CRDEGs), weighted gene co-expression network analysis (WGCNA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The gene sets from the Molecular Signatures Database (MSigDB) and were used to perform GSVA (Gene Set Variation Analysis) and GSEA (Gene-set Enrichment Analysis). The prognostic performance of the hub genes in the CRDEGs diagnostic model was examined in the validation set (GSE25504 and GSE26378), and receiver operating characteristic curves (ROC) were plotted. We constructed a Cox regression model and drew a nomogram based on the final screened CRDEGs. The prognostic Calibration and decision curve analysis were used to evaluate the model. Finally, we constructed a protein-protein interaction network (PPI network) and performed ceRNA network analysis and immune cell infiltration abundance correlation analysis. Results: We obtained two sepsis disease subtype groups based on clustering analysis of differentially expressed cuproptosis hub genes (LIPT1, PDHB, MTF1, GLS, SLC31A1). GO and KEGG analyses indicated that sepsis-related cuproptosis alterations were primarily enriched in cellular copper ion homeostasis, regulation of respiratory gaseous exchange by neurological system process, suckling behavior, protein-cofactor linkage. WGCNA yielded six cuproptosis-related gene co-expression modules and 202 CRDEGs between subgroups of sepsis. A total of 32 CRDEGs were extracted additionally based on LASSO analysis calculations, of which 23 CRDEGs were included in the optimized diagnostic gene labels used for constructing Cox regression models and plotting nomogram. Finally, in the immune infiltration analysis, there was a statistically significant relationship between the abundance of immune infiltration of 16 immune cells and the expression of CRDEGs. Conclusions: The diagnostic model we constructed on CRDEGs has promising predictive power, paving the way for further exploration of the mechanisms related to cuproptosis in sepsis and providing new ideas for discovering potential biomarkers and diagnostic patterns for sepsis.