bluuebunny/crossref_metadata_2025_split huggingface dataset:
Proposing a Weight-Based Expectation-Maximization Algorithm for Estimating Discrete-Time Markov Transition Probability Matrices with a Proof-of-Concept Example in Health Technology Assessment
Authors: Bollée Marc , Majumdar Abhirup Dutta 
Published: January 2025

AbstractDiscrete-time Markov cohort-state transition models are now well-established as the preferred choice of analysts across application areas including health technology assessment. This preference arises out of its relative intuition and its capability to strike a fine balance between complex disease pathways, statistical precision, and parsimony although being criticized by a wide variety of stakeholders. Transition probability matrices (TPMs) are the “heart and soul” of such models responsible for estimating patient dispositions. However, estimating such TPMs comes with its own set of challenges. In some situations, the transition data may be censored such that the health state of a patient is unknown for multiple time steps before the next observation or data immaturity especially in rare diseases. Craig and Sendi proposed the expectation-maximization (EM) algorithm using uniform weights as a solution for unequal estimation intervals for partially observed data. However, this typically comes at the cost of increased within-state output variations with no optimization technique available in the literature.The objective of this paper is to explore an optimized weighted version of the original EM algorithm, that aims to estimate the set of weights which minimizes the uncertainty of the estimated TPM against a target objective function. The weighting reduces the uncertainty of the estimate by considering the difference in temporal sparsity of the data when there are missing time steps. Further, we demonstrate the applicability of this weighting method using a fictitious cost-effectiveness model with our approach, showing a fine but definitive change over the original approach.
The atypical filament assembly underpins the inflammasome-independent functions of IFI16
Authors: Garg Archit , Niedzialkowska Ewa , Zhou Jeffrey J. , Moh Jasper , Egelman Edward H. , Sohn Jungsan 
Published: January 2025

AbstractInflammasomes trigger cell death upon sensing various intracellular maladies. These supra-structures relay upstream signals by sequentially assembling architecturally congruent filaments via their pyrin domains (PYDs). Interferon Inducible Protein 16 (IFI16) is an innate immune sensor that detects dysregulated nucleic acids. Once presumed as an inflammasome receptor due to its PYD, the role of IFI16 has been much more appreciated in other innate immune pathways such as regulating interferon production and viral replication restriction. Here, a cryo-EM structure of the filament assembled by the PYD of IFI16(PYD)shows a helical architecture distinct from inflammasome PYD filaments.In silico Rosettainteraction energy calculations suggest that the helical architecture of the IFI16PYDfilament is incompatible with those assembled by the central inflammasome adaptor ASC and its interacting partners. Cellular experiments further support that IFI16 fails to interact with ASC. Together, we provide the structural basis for the inflammasome-independent functions of IFI16.
The Biorepository and Integrative Genomics resource for inclusive genomics: insights from a diverse pediatric and admixed cohort
Authors: Buonaiuto Silvia , Marsico Franco , Mohammed Akram , Chinthala Lokesh K , Amos−Abanyie Ernestine K , Center Regeneron Genetics , Prins Pjotr , Mozhui Kyobeni , Rooney Robert J , Williams Robert W , Davis Robert L , Finkel Terri H , Brown Chester W , Colonna Vincenza 
Published: January 2025

AbstractThe Biorepository and Integrative Genomics (BIG) Initiative in Tennessee has developed a pioneering resource to address gaps in genomic research by linking genomic, phenotypic, and environmental data from a diverse Mid-South population, including underrepresented groups. We analyzed 13,152 exomes from BIG and found significant genetic diversity, with 50% of participants inferred to have non-European or several types of admixed ancestry. Ancestry within the BIG cohort is stratified, with distinct geographic and demographic patterns, as African ancestry is more common in urban areas, while European ancestry is more common in suburban regions. We observe ancestry-specific rates of novel genetic variants, which are enriched for functional or clinical relevance. Disease prevalence analysis linked ancestry and environmental factors, showing higher odds ratios for asthma and obesity in minority groups, particularly in the urban area. Finally, we observe discrepancies between self-reported race and genetic ancestry, with related individuals self-identifying in differing racial categories. These findings underscore the limitations of race as a biomedical variable. BIG has proven to be an effective model for community-centered precision medicine. We integrated genomics education, and fostered great trust among the contributing communities. Future goals include cohort expansion, and enhanced genomic analysis, to ensure equitable healthcare outcomes.
Development and Validation of a Nutrient Profiling Model for Shopping Baskets: The Grocery Basket Score (GBS)
Authors: Marcon Sandro , Naef André , Faeh David , Windisch Paul 
Published: January 2025

AbstractBackgroundRating someone’s diet as a whole as opposed to rating individual food items could help to better inform people about their nutrition and its health properties, e.g. by considering possible deficiencies. The goal of this project was to develop an automated rating of shopping baskets based on their health properties that can be deployed on top of existing loyalty or digital shopping basket programs by retailers without knowing for how long a basket will last or how many people consume it.MethodsWe developed a model that uses nutrient densities as opposed to absolute quantities based on self-reported food intake from the National Health and Nutrition Examination Survey (NHANES) as well as mortality follow-up data and conducted a validation against the Nutri-Score as well as the Alternate Healthy Eating Index (AHEI).ResultsThe model we obtained punishes consuming calories from sugar and saturated fats, high salt intake, as well as consuming calories from beverages. Furthermore, a penalty is applied to a nutrition that is deficient in protein, vitamin C, or iron. Fiber consumption is rewarded. The model showed a high degree of correlation with the Nutri-Score (Pearson correlation coefficient: 0.60) and the AHEI (Pearson correlation coefficient: -0.62 for the AHEI without the protective effect of moderate alcohol consumption and -0.60 with it).ConclusionsThe proposed model is aligned with the recommendations formulated in nutritional guidelines, which is indicated by a high degree of correlation with the AHEI. Product-level profiling systems such as the Nutri-Score also exhibit a correlation with the model and can be used in combination.
Quantifying Device Type and Handedness Biases in a Remote Parkinson’s Disease AI-Powered Assessment
Authors: Tumpa Zerin Nasrin , Shahriar Zawad Md Rahat , Sollis Lydia , Parab Shubham , Chen Irene , Washington Peter 
Published: January 2025

AbstractEarly detection of Parkinson’s Disease (PD) can enable early access to care, improving patient outcomes. We investigate the use of machine learning to predict PD using data recorded from a web application measuring structured mouse and keypress data through tests assessing finger and hand movement patterns. We evaluate the impact of demographic bias and bias related to device type and handedness, which are particularly relevant to our application. We collected data from 251 participants (99 PD, 152 Non-PD). Using a random forest model, we observed an 84% F1 score, 86% sensitivity, and 92% specificity. When examining only F1-score differences across groups, no significant bias appears. However, conducting a more in-depth analysis using algorithmic fairness metrics uncovers bias regarding the positive prediction and error rates. In particular, we found that sex and ethnicity have no statistically significant impact on receiving a PD prediction. However, we observe biases regarding device type and dominant hand in terms of receiving a PD diagnosis, as evidenced by disparate impact and equalized odds fairness metrics. This work demonstrates that remote digital health diagnostics using consumer devices like desktops or laptops can exhibit nontraditional yet significant biases concerning understudied factors in algorithmic fairness such as device type and handedness.
Freeze-drying as a novel concentrating method for wastewater detection of SARS-CoV-2
Authors: Dong Rui , Noriega Landa Elizabeth , Ouellet Hugues , Lee Wen-Yee , Xiao Chuan 
Published: January 2025

AbstractExtracting and detecting viral RNA in wastewater has proven to be a rapid and cost-effective approach for community-level monitoring during the recent global Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Various sample concentrating methods, such as centrifugal ultrafiltration, have been utilized in wastewater SARS-CoV-2 detection studies. However, freeze drying, a promising technique commonly used for concentrating and preserving various biological samples, has yet to be explored in this field. This study compared the performance of freeze-drying and the widely used centrifugal ultrafiltration method in terms of recovery rate, detection limit, and other key parameters for concentrating 72 wastewater samples collected from four facilities in El Paso, TX. Statistical analyses revealed that the freeze-drying method demonstrated higher overall recovery efficiency (20.33% vs 13.00%), a superior detection ratio (68.4% vs. 31.6%), and lower detection limits (0.06copies/mL vs 0.35copis/mL) than centrifugal ultrafiltration, particularly during the early stages of the pandemic. Despite its longer processing time than centrifugal ultrafiltration, freeze-drying offers several notable advantages, including eliminating pretreatment steps, providing flexible sample storage options, preventing signal loss and sample degradation, and reducing labor and exposure risks. Freeze-drying also does not require intensive training for concentrating sewage water. These benefits, combined with its efficient capture of viral RNA, position freeze-drying as a promising alternative for wastewater virus detection, especially in resource-constrained lab settings at local wastewater treatment plants. The protocol and findings reported here provide a baseline for further development of freeze-drying-based methods for enabling community-level early warning and surveillance against emerging viral threats in the future.
Postprandial glycaemic response to white and wholemeal bread consumption between normal weight and overweight/obese healthy adults
Authors: Dong Honglin , Colosimo Abbie , Xu Yizhi 
Published: January 2025

AbstractObesity and the increased postprandial glycaemic response (PPGR) are risk factors for type 2 diabetes. Few studies have explored the association of body weight with PPGRs. The study aimed to investigate the PPGR between healthy adults with normal weight and overweight/obesity to two commercially available breads (white and wholemeal) with different dietary fibre contents. In this acute randomised crossover trial, 20 healthy adults (10 normal weight, 10 overweight/obese) consumed two slices of white (100 g, fibre 3.6 g) or wholemeal bread (88 g, fibre 5.6 g) alongside 150 ml of orange juice and 10 g butter on separate visits in random order after fasting for 8-12 hours. The blood glucose concentration was measured fasted, 30 min, 60 min, 90 min and 120 min postprandially by finger pricks. Information on age, gender, ethnicity, body mass index (BMI), and body fat percentage were collected. Two-way repeated measures ANCOVA was used for controlling for age, gender, ethnicity and body fat percentage, and results showed no significant difference was observed in fasting blood glucose concentrations (F(1, 14)=2.968, P=0.107), incremental areas under the curve (iAUCs) (F (1, 14) = 0.702, P=0.416) and peak values (PVs) (F (1, 14) = 0.507, P=0.488) between participants with normal weight and overweight/obesity, or in fasting blood glucose concentrations (F(1, 14)=0.007, P=0.964), iAUCs (F (1, 14) = 0.008, P=0.929) and PVs (F (1, 14) = 0.036, P=0.851) between white and wholemeal bread consumption. The BMI or body fat percentage was not associated with iAUCs or PVs regardless of bread type adjusted by age, gender and ethnicity. Our results did not find that body weight is associated with PPGR in healthy adults, and the wholemeal bread used in the current study did not deliver the health benefit of attenuating PPGR compared with white bread consumption despite the higher dietary fibre content.
An Enhanced Conditional Variational Autoencoder-Based Normative Model for Neuroimaging Analysis
Authors: Ho Mai P. , Song Yang , Sachdev Perminder S. , Jiang Jiyang , Wen Wei 
Published: January 2025

AbstractNormative modelling in neuroimaging provides a powerful framework for quantifying individual deviations from expected brain measures as a function of relevant covariates. While most established approaches have focused on analysing distinct variables in isolation, there is a growing need for deep learning-based methods capable of handling multiple response variables simultaneously. Conditional variational autoencoders (cVAEs) have previously been applied in this context; however, existing inference methods still face challenges in providing reliable probabilistic predictions.In this study, we introduce an enhanced cVAE-based framework for normative modelling of neuroimaging data. Our key contribution is the development of a novel inference method that integrates latent space sampling and bootstrapping. This method directly leverages the generative nature of cVAEs to estimate the conditional distributions of brain measures. We demonstrate the effectiveness of this approach using white matter hyperintensity (WMH) volumes as a test case for developing, testing, and validating the model. Our dataset includes 8,551 normotensive and 18,180 hypertensive participants from the UK Biobank. We evaluated our method against three well-established and popular normative modelling techniques, including Generalised Additive Models for Location, Scale, and Shape (GAMLSS), Multivariate Fractional Polynomial Regression (MFPR), and Hierarchical Bayesian Regression (HBR).Our results indicate that the proposed cVAE-based framework achieves comparable performance across various metrics, while capturing individual deviations that correlate with the severity of hypertension. The model is particularly well-suited for high-dimensional, non-linear data, making it a robust tool for assessing individual deviations in brain structure. This enhanced normative modelling architecture paves the way for more nuanced and reliable assessments of brain health, with potential implications for personalised medicine and early detection of neurological disorders.
MISO Regulates Mitochondria Dynamics and mtDNA Homeostasis by Establishing Inner Membrane Subdomains
Authors: Zhang Yue , Xia Yuchen , Wang Xinhui , Wu Shang , Li Jianshuang , Guo Xuan , Zhou Qinghua , He Li 
Published: January 2025

AbstractMitochondrial dynamics and mtDNA homeostasis are critical in various biological processes, including cell fate determination, metabolism, and aging. Although specialized mitochondrial membrane subdomains linking these two aspects have recently been reported, their structural and molecular characteristics have remained elusive. In this study, we discover MISO (MitochondrialInner membraneSubdomainOrganizer), a novel protein that initiates the formation of distinctMISO-EnrichedMitochondrialSubdomains (MEMS) within the inner mitochondrial membrane. Our data demonstrate that MISO is an evolutionary conserved protein that regulates mitochondrial dynamics inDrosophilaintestinal stem cells (ISCs)in vivoand various human and mouse cell linesin vitro. The functions of MISO depend on the formation of MEMS, which promote mitochondrial fission while inhibiting fusion, likely through the modulation of FIS1-DRP1 and OPA1 respectively. Further investigation reveals that MEMS recruit mtDNA nucleoids, facilitating their degradation via peripheral mitochondrial division. Additionally, we show that MISO orchestrates the assembly of MEMS through oligomerization mediated by its C-terminal domain, which drives contact between inner mitochondrial membranes to generate locally multilayered structures. Our findings collectively elucidate the molecular identity and functional mechanisms of specific mitochondrial subdomains bothin vivoandin vitro, revealing a structural link between the regulation of mitochondrial dynamics and mtDNA homeostasis.
Manipulating Environmental Affordances via Intrinsic Measurement: Evidence from Sensorimotor Brain Dynamics
Authors: Wang Sheng 
Published: January 2025

AbstractAccording to the view of ecological psychology, affordances are perceived directly through the interaction between the observer and the environment, and thus body-scaled. Considering the actions from different object-agent distances, Tosoni and colleagues have provided a conceptual distinction concerning two types of affordances: macro affordances (also called environmental affordance) and micro affordances. Both of these two types of affordances have been investigated in psychological research since the beginning of this century. However, most of the environmental affordances have not yet been manipulated with a body-scaled setting in the prior research protocol. Inspired by the intrinsic measurement introduced by ecological psychologist Warren (1984) and focusing on environmental affordances, the present study adapted the task of Djebbara et al. (2019) by defining transitional affordance as the body-door height ratios. The current results from subjective data, EEG data and behavioral data showed that affordance can be manipulated intrinsically and covaried with agents’ experience, perception and motor interaction. The perception of environmental affordances was based on intrinsic optical information for the relationship between environmental properties and capacities of the observer’s own action system. It thus provides empirical support for the need to link ecological psychology and neuro-architecture in experimental protocols.
Irinotecan-induced mucositis is associated with variation in the expression of regulatory compounds associated with goblet cells
Authors: Thorpe Daniel W , Mayo Bronwen , Bresland John , Stringer Andrea 
Published: January 2025

AbstractAlimentary mucositis (AM) is a common side effect of antineoplastic treatment and a key reason for cessation of treatment, compromising the chance of remission. Gastrointestinal mucin secretion is associated with regulatory compounds nitric oxide and its respective synthases inducible, epithelial and neural nitric oxide synthase (iNOS, eNOS and nNOS, respectively), vasoactive intestinal polypeptide (VIP), and prostaglandin E2 (PGE2). Changes in secretion during mucositis have been demonstrated in numerous studies, however no secretory regulatory signals have been associated in mucositis induced secretory change. The aim of this study is to investigate regulator factors in the gastrointestinal tract involved in mucin secretion, VIP, NOS, and PGE2, which are suspected of being involved in mucositis, specifically through alteration of neural or goblet cells. Tumour-bearing Dark Agouti rats received a single dose of 175 mg/kg of irinotecan (i.p.) and 0.01mg/kg atropine. (s.c.). Rats were killed post treatment at 6, 24, 48, 72, 96 and 120 hours. Samples were collected, immunohistochemistry and real time PCR were performed to analyse the expression of iNOS, eNOS, nNOS, VIP, and PGE2. Following irinotecan treatment, staining intensity for iNOS positive goblet cells in the crypts of the jejunum decreased significantly at 48 h (p < 0.05). VIP, and PGE2 positive goblet cell numbers showed no change. mRNA expression in iNOS, eNOS, and nNOS showed no change. Irinotecan-induced mucositis is associated with altered secretory regulatory compounds; this may affect mucin secretion increasing the severity of irinotecan induced mucositis.
Enhanced yield and subtype identity of hPSC-derived midbrain dopamine neuron by modulation of WNT and FGF18 signaling
Authors: Kim Tae Wan , Piao Jinghua , Bocchi Vittoria D , Koo So Yeon , Choi Se Joon , Chaudhry Fayzan , Yang Donghe , Cho Hyein S , Hergenreder Emiliano , Perera Lucia Ruiz , Joshi Subhashini , Mrad Zaki Abou , Claros Nidia , Donohue Shkurte Ademi , Frank Anika K. , Walsh Ryan , Mosharov Eugene V. , Betel Doron , Tabar Viviane , Studer Lorenz 
Published: January 2025

AbstractWhile clinical trials are ongoing using human pluripotent stem cell-derived midbrain dopamine (mDA) neuron precursor grafts in Parkinson’s disease (PD), current protocols to derive mDA neurons remain suboptimal. In particular, the yield of TH+ mDA neurons afterin vivografting and the expression of some mDA neuron and subtype-specific markers can be further improved. For example, characterization of mDA grafts by single cell transcriptomics has yielded only a small proportion of mDA neurons and a considerable fraction of contaminating cell populations.Here we present an optimized mDA neuron differentiation strategy that builds on our clinical grade (“Boost”) protocol but includes the addition of FGF18 and IWP2 treatment (“Boost+”) at the mDA neurogenesis stage. We demonstrate that Boost+ mDA neurons show higher expression of EN1, PITX3 and ALDH1A1. Improvements in both mDA neurons yield and transcriptional similarity to primary mDA neurons is observed both in vitro and in grafts. Furthermore, grafts are enriched in authentic A9 mDA neurons by single nucSeq. Functional studiesin vitrodemonstrate increased dopamine production and release and improved electrophysiological properties.In vivoanalyses show increased percentages of TH+ mDA neurons resulting in efficient rescue of amphetamine induced rotation behavior in the 6-OHDA rat model and rescue of some motor deficits in non-drug induced assays, including the ladder rung assay that is not improved by Boost mDA neurons. The Boost+ conditions present an optimized protocol with advantages for disease modeling and mDA neuron grafting paradigms.