bluuebunny/crossref_metadata_2025_split huggingface dataset:
OQA : A question-answering dataset on orthodontic literature
Authors: Rousseau Maxime , Zouaq Amal , Huynh Nelly 
Published: July 2024

AbstractBackgroundThe near-exponential increase in the number of publications in orthodontics poses a challenge for efficient literature appraisal and evidence-based practice. Language models (LM) have the potential, through their question-answering fine-tuning, to assist clinicians and researchers in critical appraisal of scientific information and thus to improve decision-making.MethodsThis paper introduces OrthodonticQA (OQA), the first question-answering dataset in the field of dentistry which is made publicly available under a permissive license. A framework is proposed which includes utilization of PICO information and templates for question formulation, demonstrating their broader applicability across various specialties within dentistry and healthcare. A selection of transformer LMs were trained on OQA to set performance baselines.ResultsThe best model achieved a mean F1 score of 77.61 (SD 0.26) and a score of 100/114 (87.72%) on human evaluation. Furthermore, when exploring performance according to grouped subtopics within the field of orthodontics, it was found that for all LMs the performance can vary considerably across topics.ConclusionOur findings highlight the importance of subtopic evaluation and superior performance of paired domain specific model and tokenizer.
Large Language Models forecast Patient Health Trajectories enabling Digital Twins
Authors: Makarov Nikita , Bordukova Maria , Rodriguez-Esteban Raul , Schmich Fabian , Menden Michael P. 
Published: July 2024

AbstractBackgroundGenerative artificial intelligence (AI) accelerates the development of digital twins, which enable virtual representations of real patients to explore, predict and simulate patient health trajectories, ultimately aiding treatment selection and clinical trial design. Recent advances in forecasting utilizing generative AI, in particular large language models (LLMs), highlights untapped potential to overcome real-world data (RWD) challenges such as missingness, noise and limited sample sizes, thus empowering the next generation of AI algorithms in healthcare.MethodsWe developed the Digital Twin - Generative Pretrained Transformer (DT-GPT) model, which utilizes biomedical LLMs using rich electronic health record (EHR) data. Our method eliminates the need for data imputation and normalization, enables forecasting of clinical variables, and preliminary explainability through a human-interpretable interface. We benchmarked DT-GPT on RWD including long-term US nationwide non-small cell lung cancer (NSCLC) and short-term Intensive Care Unit (ICU) datasets.FindingsDT-GPT surpassed state-of-the-art machine learning methods in patient trajectory forecasting on mean absolute error (MAE) for both the long-term (3.4% MAE improvement) and the short-term (1.3% MAE improvement) dataset. Additionally, DT-GPT was capable of preserving cross-correlations of clinical variables (average R2of 0.98), handling data missingness and noise. Finally, we discovered the ability of DT-GPT to provide insights into a forecast’s rationale and to perform zero-shot forecasting on variables not used during fine-tuning, outperforming even fully trained task-specific machine learning models on 13 clinical variables.InterpretationDT-GPT demonstrates that LLMs can serve as a robust medical forecasting platform, empowering digital twins which virtually replicate patient characteristics beyond their training data. We envision that LLM-based digital twins will enable a variety of use cases, including clinical trial simulations, treatment selection and adverse event mitigation.
Investigating associations between physical multimorbidity clusters and subsequent depression: cluster and survival analysis of UK Biobank data
Authors: DeLong Lauren Nicole , Fleetwood Kelly , Prigge Regina , Galdi Paola , Guthrie Bruce , Fleuriot Jacques D. 
Published: July 2024

AbstractBackgroundMultimorbidity, the co-occurrence of two or more conditions within an individual, is a growing challenge for health and care delivery as well as for research. Combinations of physical and mental health conditions are highlighted as particularly important. The aim of this study was to investigate associations between physical multimorbidity and subsequent depression.Methods and FindingsWe performed a clustering analysis upon physical morbidity data for UK Biobank participants aged 37-73 years at baseline data collection between 2006-2010. Of 502,353 participants, 142,005 had linked general practice data with at least one physical condition at baseline. Following stratification by sex (77,785 women; 64,220 men), we used four clustering methods (agglomerative hierarchical clustering, latent class analysis,k-medoids andk-modes) and selected the best-performing method based on clustering metrics. We used Fisher’s Exact test to determine significant over-/under-representation of conditions within each cluster. Amongst people with no prior depression, we used survival analysis to estimate associations between cluster-membership and time to subsequent depression diagnosis.Thek-modes models consistently performed best, and the over-/under-represented conditions in the resultant clusters reflected known associations. For example, clusters containing an overrepresentation of cardiometabolic conditions were amongst the largest clusters in the whole cohort (15.5% of participants, 19.7% of women, 24.2% of men). Cluster associations with depression varied from hazard ratio (HR) 1.29 (95% confidence interval (CI) 0.85-1.98) to HR 2.67 (95% CI 2.24-3.17), but almost all clusters showed a higher association with depression than those without physical conditions.ConclusionsWe found that certain groups of physical multimorbidity may be associated with a higher risk of subsequent depression. However, our findings invite further investigation into other factors, like social ones, which may link physical multimorbidity with depression.
The Prevalence and Factors Associated with Utilisation of Malaria Preventive Measures among Long Distance Travellers at Maunyamo Harbour in Mongu, Western Province of Zambia. A Cross-Sectional Study
Authors: Chingumbe Inambao , Mooka Larry Lubinda , Nawa Mukumbuta 
Published: July 2024

AbstractIntroductionMalaria is a significant public health concern in Zambia. Travelling is associated with exposure to different strains of malaria parasites whilst the use of preventive measures is not well documented among Zambia travellers. The Barotse flood plains in the upper Zambezi region with its swampy areas play a significant role in malaria transmission in the Western Province of Zambia. This study assessed the prevalence and factors associated with the utilisation of malaria preventive measures among long-distance travellers at Maunyamo harbour in Mongu district of Western Province.MethodsThis was a cross-sectional study design which targeted long-distance travellers from the Barotse flood plains who come to Mongu the capital and central business hub of Western Province. A sample size of 171 participants was selected using simple random sampling. Data was collected through a structured questionnaire with closed questions. Data was summarised using descriptive statistics such as frequency, percentages, and cross-tabulations with comparisons using Chi-Square or Fisher’s Exact test. Further, associations between the outcome variable and dependent variables were tested using univariate and multivariable logistic regression. A P-value of 0.05 was significant.ResultsA total of 171 respondents were included in the study, males 50.9% (87/171) and females 49.1% (84/171) were equally represented. A majority 74% (126/171) of participants were aware of malaria preventive measures, however, few actually used the conventional preventive measures such as mosquito repellents (43%), ITNs (19%), IRS (12%), and mosquito coils (5%) while a sizable number used unconventional means such as cutting and burning shrubs (18%). Factors associated with the use of conventional preventive measures included awareness of mosquito repellents as a preventive measure aOR 1.97 (P value < 0.001), whilst the younger age group of 21 – 25 years aOR 0.21 (P value 0.022) were significantly associated with less use of preventive measures compared to those aged 26 years and older. Factors such as sex, education levels and duration in business were not statistically significant.ConclusionAwareness of malaria preventive measures among long-distance travellers was relatively high but utilisation was much lower indicating a mismatch between knowledge and utilisation. Awareness of specific preventive measures such as mosquito repellents was associated with a higher utilisation rate whilst the younger age group was associated with lower utilisation. Socioeconomic factors like sex, education and duration were not statistically significant.
Validation of the Hospital Anxiety and Depression Scale in Patients with Decompensated Cirrhosis
Authors: Zeng Chengbo , Donlan John , Indriolo Teresa , Li Lucinda , Zhu Enya , Zhou Joyce C. , Armstrong Malia E. , Pintro Kedie , Horick Nora , Chung Raymond T. , EI-Jawahri Areej , Edelen Maria O. , Ufere Nneka N. 
Published: July 2024

AbstractBackgroundThe Hospital Anxiety and Depression Scale (HADS) demonstrates strong psychometric properties in many populations of patients with serious illness. However, its psychometric performance among patients with decompensated cirrhosis (DC) has not been examined. We investigated the reliability, validity, and responsiveness of the HADS for patients with DC.MethodsThis observational study utilized data from patients with DC at enrollment and week 6 follow-up. Two hundred eighteen outpatients with DC were recruited from a liver transplant center, with 145 completing week 6 assessment. We evaluated psychological distress using HADS and Patient Health Questionnaire 9 (PHQ-9). Patients’ health-related quality of life (HRQOL) was assessed using the Short-Form Liver Disease Quality of Life questionnaire. We examined reliability, floor/ceiling effects, structural validity, and known-groups validity for anxiety (HADS-Anxiety) and depression (HADS-Depression) subscales. We assessed the convergent validity with the PHQ-9. We predicted the change in HRQOL using the change in depression and anxiety. We also evaluated the internal responsiveness to changes in HRQOL for both HADS-Anxiety and HADS-Depression from baseline to week 6.ResultsThe HADS-Anxiety and HADS-Depression subscales showed strong internal consistency (Cronbach’s alpha>0.8), adequate floor/ceiling effects (<15%), and excellent convergent validity with PHQ-9 (r>0.7). Both domains significantly predicted the changes in HRQOL longitudinally. Both HADS-Anxiety (1.8 [95% confidence interval [CI]: 0.5, 3.2]) and HADS-Depression (2.2 [95%CI: 1, 3.4]) showed responsiveness in patients with decreased HRQOL.ConclusionsThe HADS is a reliable, valid, responsive tool for assessing anxiety and depression among patients with DC.
Machine learning is more accurate and biased than risk scoring tools in the prediction of postoperative atrial fibrillation after cardiac surgery
Authors: Ho Joyce C , Joshi Shalmali , Valverde Eduardo , Wood Kathryn , Grubb Kendra , Leal Miguel , Hertzberg Vicki Stover 
Published: July 2024

AbstractIncidence of postoperative atrial fibrillation (POAF) after cardiac surgery remains high and is associated with adverse patient outcomes. Risk scoring tools have been developed to predict POAF, yet discrimination performance remains moderate. Machine learning (ML) models can achieve better performance but may exhibit performance heterogeneity across race and sex subpopulations. We evaluate 8 risk scoring tools and 6 ML models on a heterogeneous cohort derived from electronic health records. Our results suggest that ML models achieve higher discrimination yet are less fair, especially with respect to race. Our findings highlight the need for building accurate and fair ML models to facilitate consistent and equitable assessment of POAF risk.
MENSA, a Media Enriched with Newly Synthesized Antibodies, to Identify SARS-CoV-2 Persistence and Latent Viral Reactivation in Long-COVID
Authors: Haddad Natalie S. , Morrison-Porter Andrea , Quehl Hannah , Capric Violeta , Lamothe Pedro A. , Anam Fabliha , Runnstrom Martin C. , Truong Alex D. , Dixit Adviteeya N. , Woodruff Matthew C. , Chen Anting , Park Jiwon , Nguyen Doan C. , Hentenaar Ian , Kim Caroline Y. , Kyu Shuya , Stewart Brandon , Wagman Elizabeth , Geoffroy Hannah , Sanz Daniel , Cashman Kevin S. , Ramonell Richard P. , Cabrera-Mora Monica , Alter David N. , Roback John D. , Horwath Michael C. , O’Keefe James B. , Dretler Alexandra W. , Gripaldo Ria , Yeligar Samantha M. , Natoli Ted , Betin Viktoria , Patel Rahulkumar , Vela Kennedy , Hernandez Mindy Rodriguez , Usman Sabeena , Varghese John , Jalal Anum , Lee Saeyun , Le Sang N. , Toby Amoss R. , Daiss John L. , Sanz Ignacio , Lee F. Eun-Hyung 
Published: July 2024

ABSTRACTPost-acute sequelae of SARS-CoV-2 (SARS2) infection (PASC) is a heterogeneous condition, but the main viral drivers are unknown. Here, we use MENSA, Media Enriched with Newly Synthesized Antibodies, secreted exclusively from circulating human plasmablasts, to provide an immune snapshot that defines the underlying viral triggers. We provide proof-of-concept testing that the MENSA technology can capture the new host immune response to accurately diagnose acute primary and breakthrough infections when known SARS2 virus or proteins are present. It is also positive after vaccination when spike proteins elicit an acute immune response. Applying the same principles for long-COVID patients, MENSA is positive for SARS2 in 40% of PASC vs none of the COVID recovered (CR) patients without any sequelae demonstrating ongoing SARS2 viral inflammation only in PASC. Additionally, in PASC patients, MENSAs are also positive for Epstein-Barr Virus (EBV) in 37%, Human Cytomegalovirus (CMV) in 23%, and herpes simplex virus 2 (HSV2) in 15% compared to 17%, 4%, and 4% in CR controls respectively. Combined, a total of 60% of PASC patients have a positive MENSA for SARS2, EBV, CMV, and/or HSV2. MENSA offers a unique antibody snapshot to reveal the underlying viral drivers in long-COVID thus demonstrating the persistence of SARS2 and reactivation of viral herpes in 60% of PASC patients.Graphical abstract
Trends in Violence Against Women in Morocco: An Analysis of National Surveys from 2009 to 2020
Authors: Wafqui Fatima-Ezzahraa , Yahyane Abdelhakim , Bouaddi Oumnia , Rhajbal Zineb , Khalis Mohamed 
Published: July 2024

AbstractViolence Against Women (VAW) remains a significant challenge in Morocco despite major advances in legislative framework and policy initiatives.ObjectiveThis study aims to investigate the trends of VAW in Morocco including its forms, contexts in which it occurs and the socio-demographic characteristics of victims over a 10-year period from 2009 to 2020.MethodsWe conducted an online search for official publicly available, open access national reports and surveys about VAW in Morocco, published in the period between 2009-2020. We identified Five official reports. We collected data on prevalence of VAW, profiles of the victims, its forms and contexts.ResultsFrom 2009 to 2020, the overall prevalence of VAW has consistently exceeded the 50% mark with 62.80% in 2009 vs 58.2% in 2020. Although it has seen a decrease, the highest prevalence of VAW was reported among married females belonging to younger age groups, with high levels of education 75.3% in 2009 vs 62.7% in 2019. Intimate partner violence, both marital and extra-marital was the most common context where VAW occurred across the ten-year period (55% and 47.4% in 2009 respectively vs 52,5% for marital violence in 2020 and 27.7% for extra marital violence in 2019). Marital or spousal violence ranged from 38.4% among non-single women to more than 80% among victims admitted to integrated care units in 2011, 2012, and 2013. Psychological violence stood out as the most common form of violence across the years, while violence in public spaces has seen a steady decrease over the years. Electronic or cyber violence was only studied in one survey and was estimated at 4.5%.ConclusionDespite legislative advancements, VAW remains a complex issue in Morocco, with significant prevalence requiring sustained efforts to address this issue comprehensively. Education and empowerment initiatives, alongside strengthening the implementation of the law and addressing barriers to reporting, are crucial for combating VAW effectively in Morocco.
Accurate diagnosis achieved via super-resolution whole slide images by pathologists and artificial intelligence
Authors: Wang Kuansong , Liu Ruijie , Chen Yushi , Wang Yin , Gao Yanhua , Qiu Yanning , Zhou Maoxu , Bai Bingqian , Zhang Mingxing , Sun Kai , Deng Hongwen , Xiao Hongmei , Yu Gang 
Published: July 2024

AbstractBackgroundDigital pathology significantly improves diagnostic efficiency and accuracy; however, pathological tissue sections are scanned at high resolutions (HR), magnified by 40 times (40X) incurring high data volume, leading to storage bottlenecks for processing large numbers of whole slide images (WSIs) for later diagnosis in clinic and hospitals.MethodWe propose to scan at a magnification of 5 times (5X). We developed a novel multi-scale deep learning super-resolution (SR) model that can be used to accurately computes 40X SR WSIs from the 5X WSIs.ResultsThe required storage size for the resultant data volume of 5X WSIs is only one sixty-fourth (less than 2%) of that of 40X WSIs. For comparison, three pathologists used 40X scanned HR and 40X computed SR WSIs from the same 480 histology glass slides spanning 47 diseases (such tumors, inflammation, hyperplasia, abscess, tumor-like lesions) across 12 organ systems. The results are nearly perfectly consistent with each other, with Kappa values (HR and SR WSIs) of 0.988±0.018, 0.924±0.059, and 0.966±0.037, respectively, for the three pathologists. There were no significant differences in diagnoses of three pathologists between the HR and corresponding SR WSIs, with Area under the Curve (AUC): 0.920±0.164 vs. 0.921±0.158 (p-value=0.653), 0.931±0.128 vs. 0.943±0.121 (p-value=0.736), and 0.946±0.088 vs. 0.941±0.098 (p-value=0.198). A previously developed highly accurate colorectal cancer artificial intelligence system (AI) diagnosed 1,821 HR and 1,821 SR WSIs, with AUC values of 0.984±0.016 vs. 0.984±0.013 (p-value=0.810), again with nearly perfect matching results.ConclusionsThe pixel numbers of 5X WSIs is only less than 2% of that of 40X WSIs. The 40X computed SR WSIs can achieve accurate diagnosis comparable to 40X scanned HR WSIs, both by pathologists and AI. This study provides a promising solution to overcome a common storage bottleneck in digital pathology.
Developmental encoding of ultrasound vocalizations in the mouse auditory cortex
Authors: Zucca Stefano , La Rosa Chiara , Fellin Tommaso , Peretto Paolo , Bovetti Serena 
Published: July 2024

AbstractMice communicate through high-frequency ultrasound vocalizations (USVs), which are crucial for social interactions such as courtship and aggression. Although USV representation has been found in adult brain areas along the auditory pathway, including the auditory cortex (ACx), no evidence is available on the neuronal representation of USVs early in life. Using in vivo two-photon calcium imaging, we analyzed ACx layer 2/3 neuronal responses to USVs, pure tones (4-90 kHz), and high-frequency modulated sweeps from postnatal day 12 (P12) to P21. We found that ACx neurons are tuned to respond to USV syllables as early as P12-P13, with an increasing number of responsive cells as the mouse age. By P14, while pure tone responses showed a frequency preference, no syllable preference was observed. Additionally, at P14, USVs, pure tones, and modulated sweeps activate clusters of largely non-overlapping responsive neurons. Finally, we show that while cell correlation decreases with increasing processing of peripheral auditory stimuli, neurons responding to the same stimulus maintain highly correlated spontaneous activity after circuits have attained mature organization, forming neuronal sub-networks sharing similar functional properties.
Spatial organization of PI3K-PI(3,4,5)P3-AKT signaling by focal adhesions
Authors: Wang Jing , An Zhengyang , Wu Zhongsheng , Zhou Wei , Sun Pengyu , Wu Piyu , Xue Rui , Dang Song , Bai Xue , Wang Wenxu , Chen Rongmei , Du Yongtao , Huang Pei , Lam Sin Man , Ai Youwei , Liu Suling , Shui Guanghou , Zhang Zhe , Liu Zheng , Huang Jianyong , Fang Xiaohong , He Kangmin 
Published: July 2024

SUMMARYThe class I PI3K-AKT signaling pathway is the master regulator of cell survival, growth, and proliferation, and among the most frequently mutated pathways in cancer. However, where and how the PI3K-AKT signaling is spatially activated and organized in mammalian cells remain poorly understood. Here, we identified focal adhesions (FAs) as the subcellular signaling hubs organizing the activation of PI3K-PI(3,4,5)P3-AKT signaling in mammalian cells. We found that class IA PI3Ks are preferentially and dynamically recruited to FAs for activation, resulting in localized production of the critical signaling lipid PI(3,4,5)P3around FAs. As the effector protein of PI(3,4,5)P3, AKT molecules are dynamically recruited around FAs for activation. Mechanistically, the spatial recruitment/activation of PI3K-PI(3,4,5)P3-AKT cascade are regulated by the activated FAK. Furthermore, combined inhibition of class I PI3K and FAK results in a more potent inhibitory effect on cancer cells. Thus, our results unveil a growth-factor independent, compartmentalized organization mechanism for PI3K-PI(3,4,5)P3-AKT signaling.
“Target-and-release” nanoparticles for effective immunotherapy of metastatic ovarian cancer
Authors: Pires Ivan S. , Covarrubias Gil , Gomerdinger Victoria F. , Backlund Coralie , Shanker Apoorv , Gordon Ezra , Wu Shengwei , Pickering Andrew J. , Melo Mariane B. , Suh Heikyung , Irvine Darrell J. , Hammond Paula T. 
Published: July 2024

ABSTRACTImmunotherapies such as checkpoint inhibitors (CPI) are effective in treating several advanced cancers, but these treatments have had limited success in metastatic ovarian cancer (OC). Here, we engineered liposomal nanoparticles (NPs) carrying a layer-by-layer (LbL) polymer coating that promotes their binding to the surface of OC cells. Covalent anchoring of the potent immunostimulatory cytokine interleukin-12 (IL-12) to phospholipid headgroups of the liposome core enabled the LbL particles to concentrate IL-12 in disseminated OC tumors following intraperitoneal administration. Shedding of the LbL coating and serum protein-mediated extraction of IL-12-conjugated lipids from the liposomal core over time enabled IL-12 to disseminate in the tumor bed following rapid NP localization in tumor nodules. Optimized IL-12 LbL-NPs promoted robust T cell accumulation in ascites and tumors in mouse models, extending survival compared to free IL-12 and remarkedly sensitizing tumors to CPI, leading to curative treatments and immune memory.