bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a Research Program Focused on Non-Invasive Brain Stimulation for Peripheral Neuropathy in Minoritized Communities
Authors: Wong Marlon L. , McTeague Lisa M. , Miller Chelsea A. , Gonzalez Gabriel , Tovin Melissa M. , Penedo Frank J. , Widerstrom-Noga Eva 
Published: January 2025

ABSTRACTBlack and Hispanic/Latino communities experience disproportionate chronic pain and are underrepresented in pain research. Transcutaneous auricular vagus nerve stimulation (taVNS) and transcranial magnetic stimulation (TMS) are promising tools for pain management. Therefore, it is critical to ensure that research using these tools engages underrepresented communities to make research findings more generalizable and reach all who may benefit. Lack of diversity in the research workforce itself is a key barrier to improving Black and Hispanic/Latino representation in pain research, and video-enhanced recruitment and consenting may be a useful tool to better engage minoritized communities.Using community participatory research principles in an iterative process, we engaged key stakeholders, including neuromodulation researchers and minoritized community members, to create and test informational videos on taVNS and TMS. These videos were designed for Black English-speaking, Hispanic/Latino Spanish-speaking, and Haitian-Creole speaking people with chronic pain. Study 1 involved iterative feedback from stakeholders to develop test videos, which were then refined based on community member input. Study 2 was a pilot randomized controlled trial assessing the impact of these videos on participant expectations for pain relief with taVNS.Results indicated that the videos were well-received, and there was no significant difference in expectancy scores between those who viewed the videos and those who received traditional brochures. This suggests that while videos may improve engagement, they do not unduly influence expectations, potentially making them valuable tools for improving research participation in underrepresented populations. These videos will be freely available to help researchers to engage people from minority communities.PERSPECTIVEThis article presents the process of developing culturally sensitive informational videos on taVNS and TMS, and provides the field with these videos in English, Spanish, and Haitian-Creole language. These videos could potentially help researchers to engage people from minority communities to enhance the diversity and reach of research using noninvasive brain stimulation for pain.
HaptiKart: An engaging videogame reveals elevated proprioceptive vs. visual bias in individuals with autism spectrum disorder
Authors: Lidstone Daniel E. , Singhala Mohit , Wang Liam J. , Brown Jeremy D. , Mostofsky Stewart H. 
Published: January 2025

AbstractAn overreliance on proprioceptive (intrinsic) sensory input from the body, compared to visual (extrinsic) input from the environment, may underpin core features of autism spectrum disorder (ASD). We developed an engaging videogame (“HaptiKart”) as a tool to examine differences in proprioceptive vs. visual bias in children and adults with ASD and whether bias correlates with age, core autism features, and intellectual ability. Eighty-one participants (33 ASD, 48 typically-developing, TD) aged 8 to 31 years played “HaptiKart,” a driving videogame with a force-feedback steering wheel that provided “steering assist” during gameplay. In separate trials, proprioceptive and visual feedback were selectively delayed, and differences in driving error between the conditions were used to calculate perceptual bias scores. Effects of autism diagnosis and age on perceptual (proprioceptive vs. visual) bias scores were examined, controlling for sex, as were associations of perceptual bias with autism symptom severity (ADOS-2, SRS-2), attention-deficit symptom severity (Conners4 ADHD Total Scores) ratings, and IQ (general ability index, GAI). The ASD group exhibited significantly higher proprioceptive bias than did the TD group (p=0.002). There was a trend for decreasing proprioceptive bias with age, but no significant diagnosis-by-age interaction. Increased proprioceptive bias correlated with higher autism severity and with lower IQ, but not ADHD symptoms. HaptiKart provides a highly scalable approach for measuring sensory-motor bias, revealing that individuals with ASD show elevated proprioceptive bias, correlating with autism severity. HaptiKart’s sensory-motor bias measure may thereby serve as a digital biomarker for addressing autism heterogeneity in ways that can improve targeted intervention.Author SummaryIn this study, we explored how people with autism spectrum disorder (ASD) may rely more on body-based (proprioceptive) senses than on visual information when interacting with their surroundings. Using a custom video game,HaptiKart, we designed a fun and engaging driving task to measure this sensory preference. Players drove a virtual car using a steering wheel that could be set to delay either visual or proprioceptive feedback, allowing us to observe how each type of feedback affects driving accuracy.Our results showed that individuals with ASD had a stronger preference for proprioceptive feedback than those without ASD. This sensory preference was linked to greater autism symptom severity and lower IQ, suggesting that heightened reliance on body-centered feedback may contribute to learning and skill differences often seen in autism. These findings support the potential ofHaptiKartas a simple, accessible tool to help clinicians better understand and address sensory biases in ASD, tailoring interventions to improve learning from visual information.
Modeling the microbial contribution to human Energy Balance using the Digestion, Absorption, and Microbial Metabolism (DAMM) model
Authors: Davis Taylor L. , Dirks Blake , Carnero Elvis A. , Corbin Karen D. , Smith Steven R. , Marcus Andrew , Krajmalnik-Brown Rosa , Rittmann Bruce E 
Published: January 2025

AbstractColonic microorganisms have been linked to human health and disease, specifically metabolic disease states such as obesity, but causal relationships remain to be established. Previous work demonstrated that interactions between the host’s diet and intestinal microbiome were associated with human energy balance by affecting the human’s energy absorption, quantified by metabolizable energy. We developed the Digestion, Absorption and Microbial Metabolism (DAMM) model, which explicitly accounts for the energy contributions of the colonic microbial community by: 1) breaking down the diet composition into the gross energy of the individual macronutrients, 2) calculating direct absorption in the upper gastrointestinal tract, 3) using microbial stoichiometry to estimate the consumption of the remaining unabsorbed nutrients by microbes in the large intestine, and 4) quantifying predicted production of microbial products (short-chain fatty acids (SCFA) and methane) in the colon and estimating absorption from the colonic tract to the host. When used to predict the results from a clinical study that compared two distinctly different diets, the DAMM model captured the directionality and magnitude of change in measured metabolizable chemical oxygen demand (which can be converted to metabolizable energy), improved on the accuracy of predictions compared to the Atwater factors by reducing systematic bias on one of the diets, and estimated substrate availability within the colon and rate of production of microbially derived short-chain fatty acids. Measured methane concentrations, combined with findings from the DAMM model, support the hypothesis that methanogens accumulated in mucosal biofilms in participants harboring methanogens. Model outputs also support that colonic transit time directly influenced SCFA absorption rates. The DAMM model now can be linked to existing human models that predict changes in body energy stores to extend our understanding of how microbial metabolic processes affect macronutrient absorption and metabolizable energy.
Social Compliance with NPIs, Mobility Patterns, and Reproduction Number: Lessons from COVID-19 in Europe
Authors: Baccega Daniele , Aguilar Jose , Baquero Carlos , Fernández Anta Antonio , Ramirez Juan Marcos 
Published: January 2025

AbstractNon-pharmaceutical interventions (NPIs), including measures such as lockdowns, travel limitations, and social distancing mandates, play a critical role in shaping human mobility, which subsequently influences the spread of infectious diseases. Using COVID-19 as a case study, this research examines the relationship between restrictions, mobility patterns, and the disease’s effective reproduction number (Rt) across 13 European countries. Employing clustering techniques, we uncover distinct national patterns, highlighting differences in social compliance between Northern and Southern Europe. While restrictions strongly correlate with mobility reductions, the relationship between mobility and Rtis more nuanced, driven primarily by the nature of social interactions rather than mere compliance. Additionally, employing XGBoost regression models, we demonstrate that missing mobility data can be accurately inferred from restrictions, and missing infection rates can be predicted from mobility data. These findings provide valuable insights for tailoring public health strategies in future crisis and refining analytical approaches.
Evaluation of age groupings used for syndromic surveillance
Authors: Morbey R. A. , Todkill D. , Hughes H. E. , Charlett A. , Elliot A. J. 
Published: January 2025

AbstractPublic health surveillance stratifies populations into age groups to help identify threats and provide appropriate responses. However, there is considerable variation in the age groupings used for epidemiology both between and within countries.We evaluate the age groups (under 1, 1-4, 5-14, 15-44, 45-64, over 65 years) used for syndromic surveillance in England. Comparing the existing age grouping with alternatives and using syndromic data to suggest new age groupings that maximise the homogeneity within groups and heterogeneity between groups. Data between November 2011 and March 2024 was extracted from four syndromic systems including 79 different syndromic indicators.Correlations between time series for individual ages in years were used to calculate homogeneity of specific age groups and age groupings (collections of age groups that completely span 0 to 90 years). Young adolescents were identified as a specific age group with distinct trends different to younger children or older adolescents. The current age group of 5 to 14 years was found to be more heterogeneous that over age groups, even those with a much wider span. Also, the age group over 65 years was assessed to be too broad and would benefit from being split into those over 90 years and below. Thus, our recommendation is a new age grouping for syndromic surveillance consisting of under 1s, 1 to 4, 5 to 8, 9 to 17, 18 to 33, 34 to 50, 51 to 67, 68 to 89 and over 90 years.
Systematic Exploration of Hospital Cost Variability: A Conformal Prediction-Based Outlier Detection Method for Electronic Health Records
Authors: Grolleau François , Goh Ethan , Ma Stephen P. , Masterson Jonathan , Ross Ted , Milstein Arnold , Chen Jonathan H. 
Published: January 2025

AbstractMarked variability in inpatient hospitalization costs poses significant challenges to healthcare quality, resource allocation, and patient outcomes. Traditional methods like Diagnosis-Related Groups (DRGs) aid in cost management but lack practical solutions for enhancing hospital care value. We introduce a novel methodology for outlier detection in Electronic Health Records (EHRs) using Conformal Prediction. This approach identifies and prioritizes areas for optimizing high-value care processes. Unlike conventional predictive models that neglect uncertainty, our method employs Conformal Quantile Regression (CQR) to generate robust prediction intervals, offering a comprehensive view of cost variability. By integrating Conformal Prediction with machine learning models, healthcare professionals can more accurately pinpoint opportunities for quality and efficiency improvements. Our framework systematically evaluates unexplained hospital cost variations and generates interpretable hypotheses for refining clinical practices associated with atypical costs. This data-driven approach offers a systematic method to generate clinically sound hypotheses that may inform processes to enhance care quality and optimize resource utilization.
Phase 2b clinical study evaluating efficacy of RTS,S/AS01EinPlasmodium falciparum-exposed Kenyan adults treated with antimalarial chemopreventive drugs
Authors: Copeland Nathanial K. , Otieno Lucas , Otieno June Doryne , Otieno Solomon , Chira Salome , Ivinson Karen , Onyango Irene , Wasuna Ruth , Akala Hoseah , Onditi Amos , Sifuna Peter , Andagalu Ben , Oyugi Roselyne , Omondi Mary , Amoit Stellah , Locke Emily , Gregory Scott , Bergmann-Leitner Elke S. , Pindolia Hema , Raine Mike , Gast Chris , Mercer Laina D. , Aponte John J. , Lievens Marc , Ockenhouse Christian F. , Lee Cynthia K. 
Published: January 2025

ABSTRACTBackgroundRTS,S/AS01 vaccine efficacy (VE) was previously shown to be lower in African adults than in malaria-naïve US adults, potentially due to concurrentPlasmodium falciparum(Pf) infections. We investigated whether treatment of infection prior to vaccination would lead to improved VE and immunogenicity.MethodsA Phase 2b study in Kenyan adults evaluated the efficacy of RTS,S/AS01Ein conjunction with antimalarial chemopreventive drugs. Participants, grouped by baseline presence or absence ofPfinfections, were randomized to receive RTS,S/AS01Eor rabies vaccine. Four groups received antimalarial drugs prior to immunization and were followed for six months to assessPfinfection. We included an additional group of adults not treated with antimalarial drugs for immunological assessment.ResultsVE (RTS,S/AS01Eversus rabies vaccine) was 34.8% (8.9%, 53.4%) and −24.0% (−97%, 22.4%) in baselinePf-positive and baselinePf-negative participants, respectively. In RTS,S/AS01Erecipients, there were no statistical differences in anti-circumsporozoite (CS) antibody titers in baselinePf-positive orPf-negative participants, or in susceptibility to infection during the post-vaccination follow-up period. Drug treatment did not improve anti-CS antibody titers.ConclusionsTreatingPfinfections during vaccination does not result in increased VE. Anti-CS antibody responses to vaccination do not differ with baselinePfinfection status, drug treatment, or susceptibility toPfinfections.Clinical Trial RegistrationNCT04661579; PACTR202006896481432
Impact of SGLT2 Inhibitors on Survival in Gastrointestinal Cancer Patients Undergoing Chemotherapy and/or Radiotherapy: A Real-World Data Retrospective Cohort Study
Authors: Flausino Lucas E. , Murillo Carrasco Alexis Germán , Furuya Tatiane Katsue , Tuan Wen-Jan , Chammas Roger 
Published: January 2025

AbstractBackgroundThe role of sodium-glucose co-transporter 2 inhibitor (SGLT2i) drugs in the management of diabetes and cardiovascular disease is well-established, but emerging evidence suggests potential effects on cancer outcomes, including gastrointestinal (GI) cancers. We conducted an extensive, sex-oriented, real-world data analysis to investigate whether SGLT2i can enhance GI cancer outcomes when used alongside standard therapies such as chemotherapy and radiotherapy.MethodsThe study applied a retrospective cohort design with data from the TriNetX research database (https://trinetx.com), examining GI cancer patients treated with chemotherapy and/or radiotherapy between 2013 and 2023. The intervention cohort consisted of Gl cancer patients who received SGLT2i, while the control cohort did not. A 5-year follow-up period was used, and baseline characteristics were balanced using a 1:1 propensity score matching technique. Cox proportional-hazards and logistic regression models assessed mortality and morbidity risks between the cohorts.ResultsThe study included 6,389 male and 3,457 female patients with GI cancer (ICD-10: C15-C25). The use of SGLT2i was significantly associated with improved survival for both male (HR 0.568; 95% CI 0.534-0.605) and female (HR 0.561; 95% CI 0.513-0.614) patients undergoing chemotherapy and/or radiotherapy. SGLT2i use also correlated significantly with lower hospitalisation rates both in male (OR 0.684; 95% CI 0.637-0.734) and female (OR, 0.590; 95% CI 0.536-0.650) patients. The analysis of GI cancer subtypes also demonstrated similar benefits, without significant adverse effects.ConclusionsRepurposing SGLT2 inhibitors for cancer treatment could potentially improve outcomes for GI cancer patients without causing significant side effects. Further clinical trials are needed to confirm these findings and establish the optimal condition for its application in GI cancer treatment.
The correlations of outcomes and vascular morphology with infarct patterns in middle cerebral arterial trunk occlusion
Authors: Cai ZhiRong , Chen Yuan , Pei ShaoQing , He Yue , Zhu YaNan , Zhang Rui , Lin JingWei , Yang Yi , Zhu Ying 
Published: January 2025

AbstractBackground and purposeThe large vessel occlusion (LVO) in middle cerebral artery (MCA) trunk (i.e., M1segment) caused by intracranial atherosclerotic disease (ICAD) could introduce with different infarct patterns. We aimed to compare the clinical outcomes among these patterns and investigate the associations between the morphological parameters of contralateral MCA (cMCA) M1segment and infarct patterns.MethodsPatients with stroke attributed to M1-ICAD-LVO were enrolled. The infarct patterns were categorized into artery-artery embolism (AAE), large infarct, borderzone infarct (BZI) and perforating artery infarction (PAI). The morphological parameters of cMCA-M1segment consisted of proximal diameter, distal diameter, arc length and chord length were measured. The tortuosity index of cMCA-M1segment was calculated by (arc length/chord length-1) × 100%.ResultsA total of 171 subjects were enrolled. Compared to AAE, the risk of poor outcome significantly increased in BZI (odds ratio [OR]= 5.51, 95% confidence interval [CI] = 1.71–17.78,p= 0.004) and large infarct (OR= 10.92, 95% CI = 2.01–59.27,p= 0.006), and was comparable in PAI. The tortuosity index (OR= 2.85, 95% CI = 1.13–7.18,p= 0.026) and arc length (OR= 2.47, 95% CI = 1.02–5.97,p= 0.045) significantly elevated in BZI and were identical in other three patterns. Subjects other than BZI were categorized into large infarct (n = 32) and non-large-infarct (n = 46) groups, and the proximal diameter (OR= 0.22, 95% CI = 0.07–0.72,p= 0.012), arc length (OR= 0.88, 95% CI = 0.78–0.98,p= 0.018) and chord length (OR= 0.87, 95% CI = 0.77–0.995,p= 0.042) were all negatively associated with the onset of large infarct.ConclusionFor patients with M1-ICAD-LVO, the outcomes of large infarct and BZI were poorer than AAE and PAI. The cMCA-M1segment with elevated tortuosity and arc length was associated with BZI, whereas a thin and short M1segment was correlated with large infarct in patients with a cMCA trunk of low tortuosity.
Ivabradine and Atrial Fibrillation Incidence: A Nested Matching Study
Authors: Kim Kibum , Keur Jasmeen , Anderson Halie , Radwański Przemysław B. , Munger Mark A. 
Published: January 2025

ABSTRACTObjectiveThe objective of this real-world study was to quantify and project the cumulative incidence of atrial fibrillation (AF) associated with exposure to ivabradine (IVB) in naïve-AF heart failure (HF) patients.MethodsA retrospective observational comparative study was performed using a health plan claims database. The new diagnosis of AF was compared between adult HF patients receiving IVB versus no IVB controls (CTRs) over 180-day follow-up period. Eligible IVB subjects were free from AF diagnosis before the IVB index date, which should be longer than 6 months. Incidence-density sampling was performed to select matched CTRs based on clinical characteristics, AF naïve status and time to be selected as a CTRs corresponding to the time to receive IVB from the initial HF diagnosis. The measure of IVB-AF association was tested using Cox Proportional Hazards Regression model.ResultsOf the 153 IVB and 4,494,305 CTRs meeting the AF-naïve HF status, the analytic cohort of 107 IVB and 321 matched controls were created. The groups were well matched for age: 52.9±11.3 (IVB) vs. 53.5±11.8, gender: 57% male, HFrEF diagnosis: 66.4%, co-morbidities: hypertension 81.3% and coronary artery disease event 38.3%, and goal-directed medical therapy: ß-adrenergic blockers 89.7%, ACEi/ARB/sacubitril/valsartan 79.4%, mineral corticoid antagonists 39.3%. The adjusted HR [95% CI] estimates was 7.293 [4.985-10.668]. The only variable that predicted AF incidence was the IVB prescription.ConclusionsIn HF AF-naive patients, analysis of healthcare claims point to a significant risk of AF receiving IVB.
Deep Learning–Based Early Detection of Major Adverse Cerebral Injuries in Cardiothoracic and Vascular Surgery
Authors: Yoo Dongjoon , Tae Yunwon , Cho Kyungjae , Je Hyunggon , Kim Dohyung , Son Bongsoo , Ju Minho , Lee Cheehoon , Lee Sangsu , Kim Taehwa , Cho Woo Hyun , Kim Young A. , Lee Narae , Ahn Sung-Ho 
Published: January 2025

AbstractBackgroundDespite advances in central nervous system (CNS)-protective anesthetic and surgical strategies, perioperative stroke remains a significant concern in high-risk cardiothoracic and vascular surgery (CTVS). Early detection, facilitating timely and prompt intervention, is often hindered by sedation and mechanical ventilation (MV) in the immediate postoperative period. This study aimed to develop and validate a deep learning (DL)-based artificial intelligence (AI) program for early detection of severe, surgery-related major adverse cerebral injury (sMACI), encompassing fatal CNS and systemic insults in high-risk CTVS patients.MethodsWe retrospectively analyzed data from 4,455 patients who underwent seven types of CTVS (2010–2021), requiring postoperative ICU admission and ongoing MV. Continuous vital signs (heart rate, blood pressures, respiratory rate, pulse oximetry saturation, temperature) were extracted from the operating room (OR) and intensive care unit (ICU), along with demographic and laboratory data. sMACI was defined as significant postoperative CNS injury (modified Rankin Scale ≥3 at 1 month) or 1-month mortality. Two-tier DL models were constructed: Model 1 using ICU data alone, and Model 2 integrating pre-ICU and ICU data. Performance in detecting sMACI within 24 hours of ICU admission was assessed using the area under the receiver operating characteristic curve (AUROC) and precision-recall curve (AUPRC).ResultsAmong 4,455 patients, 5% experienced sMACI. Model 1 achieved an AUROC of 0.809 (95% CI: 0.759–0.858) and an AUPRC of 0.275 (0.195–0.375). Model 2 showed improved detection (AUROC 0.826 [0.781–0.871]; AUPRC 0.322 [0.233–0.423]). Both models outperformed conventional early warning scores and other machine learning algorithms, demonstrating robust performance as early as 4 hours after ICU admission. Key contributors included systolic blood pressure, heart rate, diastolic blood pressure, mean arterial pressure, and pulse oximetry saturation.ConclusionsA DL-based AI program leveraging continuous vital signs enables effective early detection of severe surgery-related CNS and systemic injury in high-risk CTVS patients, outperforming established scoring systems and other machine learning approaches.