bluuebunny/crossref_metadata_2025_split huggingface dataset:
SEXUAL MISCONDUCT AMONG HIGH SCHOOL STUDENTS IN VIETNAM
Authors: Tran Kim Tu , Leone Ruschelle M. , Swartout Kevin M , Tran Minh Hung , Trinh Oanh , Yount Kathryn M. 
Published: January 2025

AbstractBackgroundSexual misconduct is a global problem. Adolescents 15-19 years face the highest risk of sexual misconduct, however, studies on school-based sexual misconduct in low and middle-income countries (LMICs) are limited. We aimed to determine the prevalence of sexual misconduct, including sexual harassment, stalking, dating violence, and sexual violence experiences among students at three high schools in Vietnam since their enrollment.MethodsBetween February and May 2023, 754 students in three high schools in Ho Chi Minh City completed the adapted Administrator-Researcher Campus Climate Collaborative online.ResultsOverall, 54.5% of students reported any sexual misconduct since enrolling in high school. The prevalence of sexual harassment victimization was 40.2% perpetrated by staff and 30.2% perpetrated by students. Stalking prevalence was 18.3%, and 13.1% of students reported experiencing dating violence. Nearly 1 in 10 (8.7%) of students reported sexual violence victimization. Sexual coercion prevalence was highest in the middle-ranked school (6.2%) and lowest in the high-ranked school (1.6%) (p=0.028). Compared to girls, boys reported a higher prevalence of unwanted sexual attention (18.7% vs. 10.9%) and sexual coercion (10.1% vs 4.6%) by staff (p=0.001). Girls reported a higher prevalence of dating violence victimization than boys (14.9% vs. 9.9%, p=0.029).ConclusionSexual misconduct prevalence among high school students in Ho Chi Minh City is high with notable gender differences in victimization. Awareness raising among parents, school administrators, and youth is needed to develop contextually appropriate preventive and response programs to address sexual misconduct in high schools across Vietnam.HighlightsWe assessed sexual misconduct among students in three high schools in South VietnamWe assessed experiences of sexual harassment, stalking, dating violence, and sexual violenceBoys experienced higher sexual harassment victimization by faculty/staff than girlsGirls experienced a higher prevalence of dating violence victimization than boysFindings inform future research and prevention efforts for high schools in South Vietnam
Towards Metacognitive Clinical Reasoning: Benchmarking MD-PIE Against State-of-the-Art LLMs in Medical Decision-Making
Authors: Esteitieh Yasma , Mandal Shaurjya , Laliotis George 
Published: January 2025

AbstractThe ability of large language models (LLMs) to perform clinical reasoning and cognitive tasks within medicine remains a critical measure of their overall capabilities in decision-making, with significant implications for patient outcomes and healthcare efficiency. Current AI models often face limitations in real-world clinical environments, including variability in performance, a lack of domain-specific knowledge, and black-box reasoning processes. In this study, we introduce a novel PIE framework, named MD-PIE, which emulates cognitive and reasoning abilities in medical reasoning and decision-making. We benchmark our framework and baseline methods both quantitatively and qualitatively using state-of-the-art LLMs, comparing them against OpenAI’s o1, Gemini 2.0 Flash Thinking, and DeepSeek V3 across diverse benchmarks. Our results demonstrate that MD-PIE surpasses existing models in differential diagnosis and reasoning accuracy across diverse medical benchmarks. This study underscores its potential to improve clinical decision-making through adaptive and collaborative design. Future research should focus on larger benchmarks and real-world validation to confirm its reliability and effectiveness in varied clinical scenarios.
The Utility of Ultra-Deep RNA sequencing in Mendelian Disorder Diagnostics
Authors: Zhao Sen , Sinson Jefferson C. , Li Shenglan , Rosenfeld Jill A. , Zapata Gladys , Macakova Kristina , Pena Mezthly , Maywald Becky , Worley Kim C. , Burrage Lindsay , Hubshman Monika Weisz , Ketkar Shamika , Craigen William , Emrick Lisa ,   Undiagnosed Diseases Network, Clark Tyson , Lithwick Gila Yanai , Shipony Zohar , Eng Christine , Lee Brendan , Liu Pengfei 
Published: January 2025

AbstractClinical RNA-seq has become an essential tool for resolving variants of uncertain significance (VUS), particularly those affecting gene expression and splicing. However, most reference data and diagnostic protocols employ relatively modest sequencing depths (∼50-150 million reads), which may fail to capture low-abundance transcripts and rare splicing events critical for accurate diagnoses. We evaluated the diagnostic and translational utility of ultra-high-depth (up to ∼one billion unique reads) RNA-seq in four clinically accessible tissues (blood, fibroblast, LCL, and iPSC) using Ultima sequencing platform. After validating the performance of Ultima RNA-seq, we investigated how increasing depth affects gene and isoform detection, splicing variant discovery, and clinical interpretation of VUS. Deep RNA-seq substantially improved sensitivity for detecting lowly-expressed genes and isoforms. At ∼1 billion reads, near-saturation was achieved for gene-level detection, although isoform-level coverage continued to benefit from even deeper sequencing. In two clinical cases with VUS, pathogenic splicing abnormalities were undetected at ∼50 million reads but emerged at 200 million reads, becoming even more pronounced at ∼one billion reads. Using deep RNA-seq data, we constructed a novel resource, MRSD-deep, to estimate the minimum required sequencing depth to achieve desired coverage thresholds. MRSD-deep provided gene- and junction-level guidelines, aiding labs in selecting suitable coverage targets for specific applications. Leveraging deep RNA-seq data on fibroblast, we also built an expanded splicing-variation reference that successfully identified rare splicing events missed by standard-depth data. Our findings underscore the diagnostic and research benefits of deep RNA-seq for Mendelian disease investigations. By capturing rare transcripts and splicing events, ultra-high-depth RNA-seq can facilitate more definitive variant interpretations and enrich splicing-reference databases. We anticipate that cost-effective deep sequencing technologies and robust reference cohorts will further advance RNA-based diagnostics in precision medicine.
Divergent morphologies with convergent performance in the mandible of pelagiarian fishes
Authors: Knapp Andrew , Lazaro Gizeh Rangel-de , Friedman Matt , Johanson Zerina , Evans Kory M , Giles Sam , Beckett Hermione T , Goswami Anjali 
Published: January 2025

AbstractMandibles represent a key evolutionary innovation that enabled jawed vertebrates to adapt and diversify in response to a range of food sources. Using a phylogenetic comparative approach, we explore the phenotypic disparity and mechanical properties of the lower jaw in Pelagiaria, a morphologically diverse but relatively small clade of open-ocean fishes which are hypothesized to have radiated near the Cretaceous/Paleogene (K/Pg) mass extinction event. We found that body elongation and diet are not significantly correlated with jaw shape, but that habitat depth and tooth type are. Mechanical advantage (MA) is significantly correlated with mandible shape, with jaw-closing MA being most strongly correlated. Pelagiarian jaw shapes fall broadly into six morphotypes, of which two show significantly higher closing MA than other groups, despite differing substantially in shape. The high morphological disparity of pelagiarian mandible shape was established very early in their evolutionary history, and high levels of disparity have been maintained over tens of millions of years; this is consistent with the hypothesis that Pelagiaria represents an ancient adaptive radiation. Our results demonstrate both the mechanical and morphological diversity of the pelagiarian mandible and highlight the crucial role that morphological diversification has played in the trophic radiation of this clade.
Tensor analysis of animal behavior by matricization and feature selection
Authors: Wang Beichen , Cai Jiazhang , Fang Luyang , Ma Ping , Leung Yuk Fai 
Published: January 2025

AbstractContemporary neurobehavior research often collects multi-dimensional tensor (MDT) data, consisting of time-series measurements for multiple features from multiple animals subjected to various perturbations. Proper analysis of the MDT data can facilitate the dissection of the underlying neural circuitry driving the behavior. However, many common approaches for MDT analysis, such as tensor decomposition, often yield results that are difficult to interpret and not directly compatible with standard multivariate analysis (MVA), which is designed for simpler, lower-dimensional data structures. To address this issue, dimensionality reduction techniques, including matricization methods such as Index Construction and Feature Concatenation, are applied to transform all or a subset of the features in the MDT into a lower-dimensional tensor, commonly a 2-dimensional tensor (2DT), that is compatible with MVA. However, the matricization methods may exclude information from the MDT features or create too many 2DT features that introduce spurious noise to the downstream analyses. Their impacts on the downstream MVA performance remain elusive. In this study, we systematically evaluated different approaches for matricization and feature selection and their impacts on MVA performance using an MDT dataset of zebrafish visual- motor response collected from wild-types (WTs) and visually-impaired mutants. We matricized the MDT dataset using various Index Construction and Feature Concatenation methods, then identified informative 2DT features using the filter and embedded methods. To evaluate these feature-selection approaches, we conducted a classification task distinguishing WT and visually-impaired zebrafish by multiple classifiers. We then assessed classification performance with cross-validation and holdout validation. We found that most classifiers performed the best when using all 2DT features matricized by Feature Concatenation and selected by the embedded method. The results also revealed unique behavioral differences between the WTs and visually-impaired mutants that were not identified by standard MVA or MDT analysis. Our results demonstrate the utility of analyzing MDT behavioral data by matricization and feature selection.
Leveraging Neural Network Models for Drug Repurposing: A case study on Cardiac Hypertrophy
Authors: Magnusson Rasmus , Johansson Markus , Hagvall Sepideh , Synnergren Jane 
Published: January 2025

AbstractBackgroundDrug repurposing has emerged as an attractive strategy in contemporary pharmaceutical research, presenting an opportunity to expedite drug discovery, minimize developmental costs, and mitigate risks associated with developing new pharmaceuticals. In this study, we investigated a novel approach based on deep learning of human transcriptomic mechanisms for systematic identification of additional therapeutic potential in preexisting drugs.MethodWe trained a composite feedforward neural network model using gene expression data sourced from the ARCHS4 compilation of the GEO, encompassing extensive human datasets. Subsequently, disease-associated gene expression data were generated from our stem cell-derivedin vitromodel of cardiac hypertrophy induced by Endothelin-1 stimulation. These data were employed to identify latent variables associated with genes showing differential expression due to Endothelin-1 stimulation. By examining the differential expression profiles within the model’s latent space, we successfully correlated the disease signal with known drug targets found in pharmaceutical compounds cataloged in DrugBank.ResultsThe model accurately encoded additional disease-related genes beyond the curated gene set, demonstrating its ability to generalize disease associations. Leveraging the model, we identified potential drug candidates, such as lapatinib and amiodarone showing promise in mitigating proBNP concentration associated with cardiac hypertrophy.ConclusionThis study demonstrates the power of deep learning of human transcriptomic mechanisms in swiftly identifying new therapeutic potentials for existing drugs, highlighting the pivotal role of artificial intelligence technologies in accelerating drug development for other complex medical conditions.HighlightsAn interpretable neural network model for identification of candidate drugs for drug repurposingEncoding expression data from our cardiac hypertrophy model highlights important disease mechanismsLapatinib and amiodarone experimentally validated as candidate drugs for cardiac hypertrophy therapies
Biophysical Basis of thein vivoElectroretinogram of the Mouse: 4-Shell Current Source Density Model
Authors: Peinado Allina Gabriel , Kumar Ratheesh , Yao Vincent , Calkins David J. , FitzGerald Paul , Schiesser William E. , Pugh Edward N. 
Published: January 2025

ABSTRACTA goal of contemporary physiology is to translate the knowledge obtainedex vivoof the molecular structure and function of ionic mechanisms into tools for quantitative,in vivomeasurement of that function in humans, and in animal models of disease and therapeutic intervention. Non-invasive field potentials such as ECGs, EMGs, EEGs, and ERGs hold great promise in efforts to achieve this goal, but their full translation is challenging due to the multiplicity of cells with distinct ionic mechanisms and distributions of membrane current sources and sinks, and the requirement of adequate characterization of volume conduction in the relevant tissue(s). The molecular identities and subcellular distributions of the ionic mechanisms of mouse rod photoreceptors and the adjacent retinal pigment epithelium (RPE) have been thoroughly characterized, and are associated with two major components of the ERG, thea-wave and thec-wave, respectively. To develop a molecular-biophysical description of these components of the ERG, we have pharmacologically and genetically isolated rod photoreceptor-driven currents, created a 3D “4-shell” model of volume conduction in the mouse eye and extraocular tissue, and solved the Equation of Continuity for trans-photoreceptor layer and trans-RPE layer sources. Corneal and intraocular measurements ofa- andc-waves are shown to reject the classic Rodieck-Ford electrical circuit model of the ERG, but found consistent with a 4-shell model having realistic values for extracellular conductivity in the eye and extraocular tissues. Our results and analysis explain the large variation across studies in maximala-wave amplitudes and show howa-wave amplitudes exceeding 1 mV can be achieved.
A super-enhancer actuated by heterodimerization of a specific YAP1 isoform, YAP1-2α, with TAZ endows cancer stemness and drug resistance
Authors: Ooki Takuya , Hayashi Takeru , Yamamoto Yui , Hatakeyama Masanori 
Published: January 2025

SUMMARYMolecular targeted drugs are frequently used in precision cancer therapies. However, the prolonged administration of these agents can result in drug resistance. Cancer cells exhibiting defects in homologous recombination are particularly susceptible to genotoxic stress, such as that induced by PARP inhibitors (PARPi), resulting in synthetic lethality. Here, we show that sustained treatment of such cancer cells with PARPi selectively upregulates YAP1-2α, a minor isoform of YAP1. Elevated YAP1-2α heterodimerizes with TAZ to induce liquid-liquid phase separation (LLPS) in the nucleus. This LLPS-driven process generates nuclear condensates that activate a super-enhancer comprising YAP1-2α, TAZ, TEAD, and BRD4. The super-enhancer reconfigures transcriptional networks to enhance cancer stem-like malignant properties, thereby potentiating cell resilience and augmenting cell resistance to adverse conditions, including precision cancer therapies. Our study reveals the presence of a super-enhancer that promotes malignant tumor progression. Targeting the YAP1-2α/TAZ-induced super-enhancer is a promising strategy for overcoming resistance to anticancer modalities.
Expression profile of the ADHD risk geneADGRL3during human neurodevelopment and the effects of genetic variation
Authors: McNeill Rhiannon Victoria , Nieberler Matthias , Schickardt Zora , Radtke Franziska , Chiocchetti Andreas , Kittel-Schneider Sarah 
Published: January 2025

AbstractAttention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders, affecting ∼5.3 % children, with symptoms including hyperactivity, inattention and impulsivity. Moreover, ADHD persists into adulthood in ∼50 % cases, significantly affecting quality of life. Currently, the complex aetiology of ADHD remains unclear, although it has been shown that it is a highly heritable disorder. Single nucleotide polymorphisms (SNPs) in the adhesion G protein-coupled receptor isoform L3 gene (ADGRL3/LPHN3) have been consistently associated with ADHD development, symptom severity and treatment response, with the rs1397547 SNP previously shown associated with alteredADGRL3transcription. Animal models have revealed an essential role of ADGRL3 in glutamatergic synapse development. However, ADGRL3 function has not been investigated in humans. We used human induced pluripotent stem cell (hiPSC)-derived cortical neurons to characterise ADGRL3 expression during human neurogenesis in vitro, and found that expression peaks early in neurodevelopment, consistent with in vivo data. ADGRL3 protein was found primarily expressed in glutamatergic neurons, and localised to growth cone-like structures, supporting a role in neurite outgrowth and glutamatergic synapse development. Lastly, using hiPSC-derived cortical neurons from healthy controls and ADHD patients, we investigated whether the rs1397547 SNP could affect ADGRL3 expression in cortical neurons. We found the rs1397547 SNP was associated with significantly increasedADGRL3transcription in early neurodevelopmental stages. Moreover, single-cell RNA sequencing of maturing cortical neurons revealed a unique transcriptional profile in SNP carriers. Our results further implicate ADGRL3 in ADHD development and suggest that genetic variation may result in dysregulated glutamatergic neuron development.
Canalization of circuit assembly by δ-protocadherins in the zebrafish optic tectum
Authors: Biswas Sayantanee , Emond Michelle R. , Philip Grace S. , Jontes James D. 
Published: January 2025

AbstractNeurons are precisely and reproducibly assembled into complex networks during development. How genes collaborate to guide this assembly remains an enduring mystery. In humans, large numbers of genes have been implicated in neurodevelopmental disorders that are characterized by variable and overlapping phenotypes. The complexity of the brain, the large number of genes involved and the heterogeneity of the disorders makes understanding the relationships between genes, development and neural function challenging. Waddington suggested the concept of canalization to describe the role of genes in shaping developmental trajectories that lead to precise outcomes1. Here, we show that members of the δ-protocadherin family of homophilic adhesion molecules, Protocadherin-19 and Protocadherin-17, contribute to developmental canalization of visual circuit assembly in the zebrafish. We provided oriented visual stimuli to zebrafish larvae and performedin vivo2-photon calcium imaging in the optic tectum. The latent dynamics resulting from the population activity were confined to a conserved manifold. Among different wild type larvae, these dynamics were remarkably similar, allowing quantitative comparisons within and among genotypes. In both Protocadherin-19 and Protocadherin-17 mutants, the latent dynamics diverged from wild type. Importantly, these deviations could be averaged away, suggesting that the loss of these adhesion molecules leads to stochastic phenotypic variability and introduced disruptions of circuit organization that varied among individual mutants. These results provide a specific, quantitative example of canalization in the development of a vertebrate neural circuit, and suggest a framework for understanding the observed variability in complex brain disorders.
Crystal structure and doping in synthetic enstatite: an analysis of Li/Fe3+-doped single-crystal samples
Authors: Ballirano Paolo , Celata Beatrice , Pacella Alessandro , Bloise Andrea , Bosi Ferdinando 
Published: January 2025

A series of Li+/Fe3+-doped enstatite crystals of composition Mg(2–2x)Li
x
Fe
x
Si2O6 were synthesized and structurally characterized. Under the selected experimental conditions, we grew three crystals of Pbca orthopyroxene (OPX: x = 0.270–0.313) and two crystals of Pbcn protopyroxene (PPX: x = 0.156–0.164) using the flux-growth technique. The observed variation in the polyhedral volume and distortion of the M2 octahedron as a function of Li/Fe3+ doping suggests the presence of an upper limit, at least for the OPX samples. The same linear relation was observed between the polyhedral volume and 〈M1—O〉 bond length across all analysed samples, including the endmembers protoenstatite (PEN), orthoenstatite (OEN) and LiFe3+Si2O6. It seems that the M2 octahedron plays a crucial role in stabilizing the pyroxene topology in either the PEN or the OEN form, because the PPX and OPX samples show two distinct linear relations between the M2O6 polyhedral volume and 〈M2—O〉, with the PPX trend converging toward the parameters of the LiFe3+Si2O6 endmember, whereas the OPX trend, including OEN, diverges largely from these parameters.
Pathways for green building acceleration in fast-growing countries: a case study on Nigeria
Authors: Ikudayisi Ayodele Emmanuel , Adegun Olumuyiwa Bayode 
Published: January 2025

PurposeGreen building (GB) development is attracting interest globally, yet many fast-growing countries (FGCs) are underperforming in GB delivery, particularly in Africa and Southeast Asia. This study aims to identify pathways for accelerating GB development in FGCs, using Nigeria as a case study.Design/methodology/approachThree-fold research data was employed. First, seven policy documents that are relevant for GB development in Nigeria were sourced, reviewed and analyzed based on content analysis. Second, a systematic literature review (SLR) of thirty-five research articles sourced from the Scopus database was conducted to underscore key research outcomes. Third, an exploratory case study of sixteen GBs was conducted to contextualize the current practice status in Nigeria.FindingsThe findings revealed that the few policy efforts in Nigeria skewed largely towards energy efficiency. The challenges associated with GB growth include low level of competency, low investment in the GB market, the dearth of technological enablers and the scarcity of GB project cases. Current project initiatives are diminutive, revealing low certification achievement and scanty public sector participation.Practical implicationsThis paper presents a unique position for accelerating sustainable architecture and construction based on policy pathways (development of novel codes and sectorial policies, harmonization of standards and performance monitoring), research pathways (development of models, technological enablers and knowledge management) and practice pathways (capacity building, public investment and sectorial collaborations).Originality/valueThe paper developed an integrated three-pathway framework for bringing Nigeria’s construction industry up to speed in GB delivery, noting areas where other FGCs need to explore.