bluuebunny/crossref_metadata_2025_split huggingface dataset:
The attenuation of activity-based anorexia by obese adipose tissue transplant is AgRP neuron-dependent
Authors: Yoon Dongmin J. , Zhang Jie , Zapata Rizaldy C. , Ulivieri Martina , Libster Avraham M. , McMurray Matthew S. , Osborn Olivia , Dulawa Stephanie C. 
Published: April 2024

ABSTRACTAnorexia nervosa (AN) is an eating disorder observed primarily in girls and women, and is characterized by a low body mass index, hypophagia, and hyperactivity. The activity-based anorexia (ABA) paradigm models aspects of AN, and refers to the progressive weight loss, hypophagia, and hyperactivity developed by rodents exposed to time-restricted feeding and running wheel access. Recent studies identified white adipose tissue (WAT) as a primary location of the ‘metabolic memory’ of prior obesity, and implicated WAT-derived signals as drivers of recidivism to obesity following weight loss. Here, we tested whether an obese WAT transplant could attenuate ABA-induced weight loss in normal female mice. Recipient mice received a WAT transplant harvested from normal chow-fed, or HFD-fed obese mice; obese fat recipient (OFR) and control fat recipient (CFR) mice were then tested for ABA. During ABA, OFR mice survived longer than CFR mice, defined as maintaining 75% of their initial body weight. Next, we tested whether agouti-related peptide (AgRP) neurons, which regulate feeding behavior and metabolic sensing, mediate this effect of obese WAT transplant. CFR and OFR mice received either control or neonatal AgRP ablation, and were assessed for ABA. OFR intact mice maintained higher body weights longer than CFR intact mice, and this effect was abolished by neonatal AgRP ablation; further, ablation reduced survival in OFR, but not CFR mice. In summary, obese WAT transplant communicates with AgRP neurons to increase body weight maintenance during ABA. These findings encourage the examination of obese WAT-derived factors as potential treatments for AN.
A regression based approach to phylogenetic reconstruction from multi-sample bulk DNA sequencing of tumors
Authors: Schmidt Henri , Raphael Benjamin J. 
Published: April 2024

AbstractMotivationDNA sequencing of multiple bulk samples from a tumor provides the opportunity to investigate tumor heterogeneity and reconstruct a phylogeny of a patient’s cancer. However, since bulk DNA sequencing of tumor tissue measures thousands of cells from a heterogeneous mixture of distinct sub-populations, accurate reconstruction of the tumor phylogeny requires simultaneous deconvolution of cancer clones and inference of ancestral relationships, leading to a challenging computational problem. Many existing methods for phylogenetic reconstruction from bulk sequencing data do not scale to large datasets, such as recent datasets containing upwards of ninety samples with dozens of distinct sub-populations.ResultsWe develop an approach to reconstruct phylogenetic trees from multi-sample bulk DNA sequencing data by separating the reconstruction problem into two parts: a structured regression problem for a fixed tree 𝒯, and an optimization over tree space. We derive an algorithm for the regression sub-problem by exploiting the unique, combinatorial structure of the matrices appearing within the problem. This algorithm has both asymptotic and empirical improvements over linear programming (LP) approaches to the problem. Using our algorithm for this regression sub-problem, we developfastBE, a simple method for phylogenetic inference from multi-sample bulk DNA sequencing data. We demonstrate on simulated data with hundreds of samples and upwards of a thousand distinct sub-populations thatfastBEoutperforms existing approaches in terms of reconstruction accuracy, sample efficiency, and runtime. Owing to its scalability,fastBEalso enables phylogenetic reconstruction directly from indvidual mutations without requiring the clustering of mutations into clones. On real data from fourteen B-progenitor acute lymphoblastic leukemia patients,fastBEinfers similar phylogenies to the existing, state-of-the-art method, but with fewer violations of a widely used evolutionary constraint and better agreement to the observed mutational frequencies. Finally, we show that on two patient-derived colorectal cancer models,fastBEalso infers phylogenies with less violation of a widely used evolutionary constraint compared to existing methods, and leads to distinct interpretations of the intra-tumor heterogeneity.AvailabilityfastBEis implemented in C++and is available at: github.com/raphael-group/fastBE.
Twin study provides heritability estimates for 2,321 plasma proteins and assesses missing SNP heritability
Authors: Drouard Gabin , Hagenbeek Fiona A. , Ollikainen Miina , Zheng Zhili , Wang Xiaoling ,   FinnGen, Ripatti Samuli , Pirinen Matti , Kaprio Jaakko 
Published: April 2024

AbstractAssessing how much of the variability in blood plasma proteins is due to genetic or environmental factors is essential for advancing personalized medicine. While large-scale studies have established SNP-based heritability (SNP-h2) estimates for plasma proteins, less is known about the proportion of total genetic effects on protein variability. We applied quantitative genetic twin models to estimate the heritability of 2,321 plasma proteins and to assess the proportion of heritability accounted for by SNP-h2estimates. Olink proteomics data were generated for 401 twins aged 56-70, including 196 complete same-sex twin pairs. On average, 40% of protein variability was attributable to genetic effects. Twin-based heritability estimates were highly correlated with published SNP-h2estimates from the UK Biobank (Spearman coefficient: r=0.80). However, on average, only half of the total heritability was covered by SNP-h2, and the other half, representing one-fifth of total protein phenotypic variability, remains missing.
No-code machine learning in radiology: implementation and validation of a platform that allows clinicians to train their own models
Authors: Elton Daniel C. , Dasegowda Giridhar , Sato James Y. , Frias Emiliano G. , Bridge Christopher P. , Mamonov Artem B. , Walters Mark , Ziemelis Martynas , Schultz Thomas J. , Bizzo Bernardo C. , Dreyer Keith J. , Kalra Mannudeep K. 
Published: April 2024

ABSTRACTMachine learning models can assist clinicians and researchers in many tasks within radiology such as diagnosis, triage, segmentation/measurement, and quality assurance. To better leverage machine learning we have developed a platform that allows users to label data and train models without requiring any programming knowledge. The technology stack consists of a TypeScript web application running on .NET for user interaction, Python, PyTorch, and MONAI for machine learning, DICOM WADO-RS to retrieve data from clinical systems, and Docker for model management. As a first trial of the system, researchers used it to train a model for clavicle fracture detection as part of an IRB-approved retrospective study. The researchers labeled 4,135 clavicle radiographs from 2,039 patients across 13 sites. The platform automatically split the data into training, validation, and test sets and trained a model until the validation loss plateaued. The system then returned a receiver operating characteristic curve, AUC, F1, and other metrics. The resulting model identifies clavicle fractures with 90% sensitivity, 87% specificity, and 88% accuracy with an AUC of 0.95. This model performance is equivalent to or better than similar models reported in the literature. More recently, our system was used to train a model to identify if ultrasound frames that contain personally identifiable information (PII). After validation, the model was used to help de-identify a large dataset that was to be used for research. This first-of-its-kind system streamlines model development and deployment and opens up an exciting new pathway for the use of AI within healthcare.
Adenosine deficiency facilitates CA1 synaptic hyperexcitability in the presymptomatic phase of a knock in mouse model of Alzheimer’s disease
Authors: Bonzanni Mattia , Braga Alice , Saito Takashi , Saido Takaomi C. , Tesco Giuseppina , Haydon Philip G. 
Published: April 2024

SummaryThe disease’s trajectory of Alzheimer’s disease (AD) is associated with and worsened by hippocampal hyperexcitability. Here we show that during the asymptomatic stage in a knock in mouse model of Alzheimer’s disease (APPNL-G-F/NL-G-F; APPKI), hippocampal hyperactivity occurs at the synaptic compartment, propagates to the soma and is manifesting at low frequencies of stimulation. We show that this aberrant excitability is associated with a deficient adenosine tone, an inhibitory neuromodulator, driven by reduced levels of CD39/73 enzymes, responsible for the extracellular ATP-to-adenosine conversion. Both pharmacologic (adenosine kinase inhibitor) and non-pharmacologic (ketogenic diet) restorations of the adenosine tone successfully normalize hippocampal neuronal activity. Our results demonstrated that neuronal hyperexcitability during the asymptomatic stage of a KI model of Alzheimer’s disease originated at the synaptic compartment and is associated with adenosine deficient tone. These results extend our comprehension of the hippocampal vulnerability associated with the asymptomatic stage of Alzheimer’s disease.Abstract FigureSynaptic hyperexcitability spreads to the soma and manifests at low frequencies of stimulationSynaptic hyperexcitability is associated with reduced adenosine tonein vitroandin vivoReduced adenosine tone is driven by reduced ATP-to-adenosine extracellular conversionRestoration of adenosine tone successfully normalizes neuronal excitability in the AD model
Modulating Cardiac Energetics in Cardio-Metabolic Syndromes: A mechanistic, hyperpolarized MR Trial of Ninerafaxstat Treatment
Authors: Hundertmark Moritz. J. , Siu Adrienne. G. , Matthews Violet , Lewis Andrew J. , Grist James , Patel Jai , Chamberlin Paul , Sarwar Rizwan , Yavari Arash , Dehbi Hakim-Moulay , Rao Prashant , Shi Xu , Zheng Shuning , Robbins Jeremy M. , Gerszten Robert E. , Frenneaux Michael P. , Valkovič Ladislav , Miller Jack J.J.J , Neubauer Stefan , Tyler Damian J. , Rider Oliver J. 
Published: April 2024

AbstractBackgroundType 2 diabetes (T2D) and obesity are key contributors for heart failure (HF)- development, especially for HF with a preserved ejection fraction (HFpEF). On a molecular basis, excessive use of fatty acids (FA) induces lipotoxicity which in turn promotes inflammation, reduces mitochondrial pyruvate dehydrogenase (PDH) activity and impairs myocardial energetics and -function. Harnessing in-vivo, real time measurement of cellular metabolism via hyperpolarized pyruvate MR, we aimed to assess the effects of ninerafaxstat, a selective FA oxidation inhibitor, on cardiac energetics, metabolism & diastolic function in patients with cardio-metabolic syndromes.MethodsIMPROVE-DiCE was an open-label, mechanistic phase 2a trial. 21 participants received 200mg ninerafaxstat twice daily for four (n=5) or eight weeks (n=16). Myocardial energetics (phosphocreatine to adenosine triphosphate ratio, PCr/ATP), metabolism and function were assessed pre-& post-treatment using magnetic resonance imaging (MRI),31P- and1H-MR spectroscopy (MRS). We utilised hyperpolarized [1-13C]pyruvate MRS to assess in-vivo PDH-flux (n=9) and plasma metabolomics and proteomics to assess whole body metabolism.ResultsPatients presented with impaired PCr/ATP, (median 1.6 [IQR 1.4, 2.1]), myocardial steatosis (2.2 % [IQR 1.5, 3.2]) and LV diastolic dysfunction (peak circumferential diastolic strain rate 0.86/s [IQR 0.82, 1.06]) at baseline. Ninerafaxstat treatment improved myocardial energetics by 32% (p<0.01), reduced myocardial triglyceride content by 34% (p=0.03) and showed a trend towards improved PDH-flux (mean 45% increase,p=0.08). Diastolic function was significantly improved post-treatment (peak diastolic strain rate by 10%, peak LV filling rate by 11%, bothp<0.05).ConclusionsMetabolic modulation with ninerafaxstat significantly improved myocardial energetics, reduced myocardial steatosis and improved LV diastolic filling. Combining hyperpolarized MRS and metabolomics, is a powerful approach to examine the mechanism of action of novel metabolic modulators.REGISTRATIONURL:https://clinicaltrials.gov;Unique identifier:NCT04826159Abstract Figure
HIV and Pregnancy among Adolescents in Sub-Saharan Africa: A Scoping Review
Authors: Akinsolu Folahanmi Tomiwa , Adewole Ifeoluwa Eunice , Lawale Abisola , Olagunju Mobolaji Timothy , Abodunrin Olunike Rebecca , Ola Oluwabukola Mary , Chukwuemeka Abel Nnamdi , Gambari Aisha Oluwaseun , Eleje George Uchenna , Ezechi Oliver Chukwujekwu 
Published: April 2024

ABSTRACTThe interaction of adolescent pregnancy with HIV is a complex and crucial public health issue worldwide. This is evident in sub-Saharan Africa, where the co-occurrence of HIV and adolescent pregnancies represents a high risk for additional health and social consequences for both adolescent mothers and their children. This study aims to explore literature to provide a clear synthesis of data related to pregnancies among adolescents living with HIV in Sub-Saharan Africa.A literature search was conducted in July 2023 using PubMed, Scopus, CINAHL, Cochrane Library, African Journals Online, and World Health Organization Global Index Medicus. Two authors screened potential studies. Articles selected were those published in or translated into the English language between 2002 and 2022.Among 1,560 identified results, 25 peer-reviewed publications on pregnancy among adolescents living with HIV in Sub-Saharan Africa were included after screening. The studies, included both qualitative and quantitative data, with a total of 178,227 participants in the age range of 12-18 years. The majority of the studies reported quantitative data, while a few presented qualitative or mixed-methods findings.This scoping review highlights disparities in pregnancy prevalence, revealing varied rates among different age groups. The underrepresentation of adolescents in demographic studies suggests diverse vulnerabilities and access to healthcare. The study also emphasizes the need for tailored healthcare services and comprehensive interventions addressing HIV risk, mental health challenges, and socio-economic barriers.
Automating Responses to Patient Portal Messages Using Generative AI
Authors: Kaur Amarpreet , Budko Alex , Liu Katrina , Eaton Eric , Steitz Bryan , Johnson Kevin B. 
Published: April 2024

ABSTRACTBackgroundPatient portals serve as vital bridges between patients and providers, playing an increasing role in healthcare communication. The rising volume and complexity of these messages is exacerbating physician and nursing burnout. Recent studies have demonstrated that AI chatbots can generate message responses that are viewed favorably by healthcare professionals; however, these studies have not included the diverse range of messages typically found in patient portals. Our goal is to investigate the quality of GPT-generated message responses across the spectrum of message types within a patient portal.MethodsWe used novel prompt engineering techniques to craft synthetic responses tailored to adult primary care patients. We enrolled a sample of primary care providers in a cross-sectional study to compare authentic with synthetic patient portal message responses, generated by GPT-4. The survey assessed each message’s empathy, relevance, medical accuracy, and readability on a scale from 0 to 5. Respondents were asked to identify messages that were GPT-generated vs. provider-generated. Mean scores for all metrics were computed for subsequent analysis.ResultsA total of 49 health care providers participated in the survey (59% completion rate), comprising 16 physicians and 32 advanced practice providers (APPs). When presented with GPT vs. authentic message response pairs, participants correctly identified GPT-generated responses 73% of the time and correctly identified authentic responses 50% of the time. In comparison to messages generated by physicians, GPT-4 generated messages exhibited higher mean scores for empathy (3.57 vs. 3.07, p < 0.001), relevance (3.94 vs. 3.81, p = 0.08) accuracy (4.05 vs. 3.95, p= 0.12) and readability (4.5 vs. 4.13, p < 0.001).LimitationsThe study is a single site, single-specialty study, limited due to the use of synthetic data.ConclusionOur findings affirm the potential of GPT-generated patient portal message responses to achieve comparable levels of empathy, relevance, and readability to those found in typical responses according to the health care providers and indicates promising prospects for their integration in the healthcare sector. Additional studies should be done within provider workflows and with careful evaluation of patient attitudes and concerns related to the ethics as well as the quality of generated patient portal message responses in all settings.
Evaluating the causal relationships between urate, blood pressure, and kidney function in the general population: a two-sample Mendelian Randomization study
Authors: Tang Haotian , Walker Venexia M , Gaunt Tom R 
Published: April 2024

AbstractBackgroundAssociations between blood urate levels, blood pressure (BP), and kidney function have previously been reported in observational studies. However, causal inference between these three traits is challenging due to potentially bidirectional relationships. Method: We applied bidirectional univariable Mendelian randomization (UVMR) to assess the causal relationships between urate levels, BP, and kidney function, proxied by estimated glomerular filtration rate (eGFR), using genetic associations from UK Biobank and CKDGen. We performed multivariable MR (MVMR) to assess the independent effects of urate and BP on eGFR. Effect estimates are presented as standard deviation (SD) change in outcome (95% confidence interval) per SD increase in exposure.ResultsThe UVMR analysis showed a bidirectional causal effect between urate and eGFR [urate on log(eGFR): beta=-0.10 (−0.22 to 0.02); log(eGFR) on urate: beta=−0.11 (−0.17 to −0.04)]. We also found bidirectional causal effects between urate and SBP [urate on SBP: beta=0.08 (0.04 to 0.11); SBP on urate: beta=0.13 (0.08 to 0.18)] and urate and DBP [urate on DBP: beta=0.09 (0.05 to 0.14); DBP on urate: beta=0.13 (0.08 to 0.18)]. However, there was weak evidence of a causal effect between BP and eGFR. MVMR results suggested the causal effect of urate on eGFR was independent of BP.ConclusionOur results provide evidence for bidirectional causal effects between urate and both eGFR and BP, suggesting urate control as a potential intervention to reduce BP and decline in kidney function in the general population, but little evidence of a causal relationship between BP and eGFR.
Cerebral perivascular spaces as predictors of dementia risk and accelerated brain atrophy
Authors: Barisano Giuseppe , Iv Michael , Choupan Jeiran , Hayden-Gephart Melanie 
Published: April 2024

AbstractCerebral small vessel disease, an important risk factor for dementia, lacks robust,in vivomeasurement methods. Perivascular spaces (PVS) on brain MRI are surrogates for small parenchymal blood vessels and their perivascular compartment, and may relate to brain health. We developed a novel, robust algorithm to automatically assess PVS count and size on MRI, and investigated their relationship with dementia risk and brain atrophy. We analyzed 46,478 clinical measurements of cognitive functioning and 20,845 brain MRI scans from 10,004 participants (71.1±9.7 years-old, 56.6% women). Fewer PVS and larger PVS diameter at baseline were associated with higher dementia risk and accelerated brain atrophy. Longitudinal trajectories of PVS markers were significantly different in non-demented individuals who converted to dementia compared with non-converters. In simulated placebo-controlled trials for treatments targeting cognitive decline, screening out participants less likely to develop dementia based on our PVS markers enhanced the power of the trial. These novel radiographic cerebrovascular markers may improve risk-stratification of individuals, potentially reducing cost and increasing throughput of clinical trials to combat dementia.
Adenovirus-specific T cells in adults are frequent, cross-reactive to common childhood adenovirus infections and boosted by adenovirus-vectored vaccines
Authors: Mukhopadhyay Rookmini , Lambisia Arnold W. , Hoang Jennifer P. , Ravenhill Benjamin J. , Agoti Charles N. , Krishna Benjamin A.C. , Houldcroft Charlotte J. 
Published: April 2024

AbstractHuman adenoviruses (HAdVs) cause diverse disease presentations as pathogens, and are also used as viral vectors for vaccines and gene therapy products. Preexisting adaptive immune responses to HAdV are known to influence symptom severity, viral clearance and the success of viral vectored products. Of note, approximately 50% of the UK’s adult population has received at least one dose of a chimpanzee adenovirus vectored SARS-CoV-2 vaccine (ChAdOx1) since January 2021.We used FluoroSpot analysis to quantify the interferon gamma (IFNγ) and interleukin-2 (IL2) responses of healthy blood donors to HAdV species A, B, C, D and F and chimpanzee adenovirus Y25, related to HAdV species E. We find that cellular immune responses to multiple species of human adenovirus are ubiquitous among healthy adult blood donors, and that stimulating PBMC with whole hexon peptide libraries induces a significantly greater IFNγ and IL2 response than using selected peptide pools alone. We then compared the cellular immune responses of ChAdOx1 recipients and control donors using PBMC collected in 2021, and found that homotypic and heterotypic IFNγ responses were significantly boosted in ChAdOx1 recipients but not controls. Finally, we show that in PBMC derived from blood donors, IFNγ responses are made to both conserved and variable regions of the hexon protein.Future vaccination campaigns using adenoviral vectored vaccines will need to account for the pre-existing exposure of recipients to both circulating HAdVs and vaccines such as ChAdOx1, which convey polyfunctional antiviral T cell responses to even low seroprevalence HAdV types.