bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of exercise training on the brain and cognition in T2DM, and its physiological mediators: a systematic review
Authors: Vandersmissen Jitske , Dewachter Ilse , Cuypers Koen , Hansen Dominique 
Published: September 2024

AbstractBackgroundType 2 diabetes (T2DM) affects brain structure and function, and is associated with an increased risk of dementia and mild cognitive impairment. It is known that exercise training has a beneficial effect on cognition and the brain, at least in healthy people, but the impact of exercise training on cognition and the brain remains to be fully elucidated in patients with T2DM.MethodsThis paper systematically reviews studies that evaluate the effect of exercise training on cognition in T2DM, and aims to indicate the most beneficial exercise modality for improving or preserving cognition in this patient group. In addition, the possible physiological mediators and targets involved in these improvements are narratively described in the second part of this review. Papers published up until the end of June 2024 were searched by means of the electronic database PubMed. Studies directly investigating the effect of any kind of exercise training on the brain or cognition in patients with T2DM, or animal models thereof, were included, with the exception of human studies assessing cognition only at one time point, and studies combining exercise training with other interventions (e.g. dietary changes, cognitive training, etc.).ResultsFor the systematic part of the review, 24 papers were found to be eligible. 20 out of 24 papers (83.3%) showed a significant positive effect of exercise training on cognition in T2DM, of which four studies only showed a moderate significant effect. Four papers (16.7%) did not show a significant effect of exercise on cognition in T2DM, but two of them did show a positive trend. Similar effects were found for resistance and endurance exercise, with both possibly requiring a minimal intensity to reach cognitive improvement. In addition, BDNF, lactate, leptin, adiponectin, GSK3β, GLP-1, the AMPK/SIRT1 pathway, and the PI3K/Akt pathway were identified as plausible mediators directly from studies investigating the effect of exercise training on the brain in T2DM.ConclusionOverall, exercise training beneficially affects cognition and the brain in T2DM, with resistance and endurance exercise having similar effects. However, additional studies comparing the effect of different exercise intensities are needed to determine the optimal exercise intensity for cognitive improvement. Furthermore, we were able to define several mediators involved in the effect of exercise training on cognition in T2DM, but further research is necessary to unravel the entire process.This review demonstrates a positive effect of exercise training on the brain in T2DM, but simultaneously emphasizes the need for additional studies on this topic. BDNF, lactate, leptin, adiponectin, GSK3β, GLP-1, the AMPK/SIRT1 pathway, and the PI3K/Akt pathway were identified as factors mediating the effect of exercise on the brain in T2DM.
A survey of Paediatric Radiology Artificial Intelligence
Authors: Kelly Brendan S , Clifford Simon M , Judge Conor S , Bollard Stephanie M , Healy Gerard M , Hughes Hannah , Colleran Gabrielle C , Rod J.E. , Lee Edward H , Prolo Laura M , Yeom Kristen W , Lawlor Aonghus , Killeen Ronan P 
Published: September 2024

ABSTRACTBackgroundArtificial intelligence (AI) applications in paediatric radiology present unique challenges due to diverse anatomy and physiology across age groups. Advancements in AI algorithms, particularly deep learning techniques, show promise in improving diagnostic accuracy.ObjectivesTo survey trends in AI research in paediatric radiology. To evaluate use cases, tasks, research methodologies and underlying data. To identify potential biases and future directions.MethodsA systematic search of paediatric radiology AI studies published from 2015 to 2021 was conducted following the PRISMA guidelines and the Cochrane Collaboration Handbook. The search included papers utilizing AI techniques for radiological diagnosis or intervention in patients aged under 18. Narrative synthesis was used due to methodological heterogeneity.ResultsA total of 292 articles were included, with an increasing annual trend in the number of published articles. Neuroradiology and musculoskeletal radiology were the most common subspecialties. MRI was the dominant imaging modality, with segmentation and classification as the most common tasks. Retrospective cohort studies constituted the majority of research designs. Data quality and quantity varied, as did the choice of research design, data sources, and evaluation metrics.ConclusionsAI literature in paediatric radiology shows rapid growth, with advancements in various subspecialties and tasks. However, potential biases and data quality issues highlight the need for rigorous research design and evaluation to ensure the generalisability and reliability of AI models in clinical practice. Future research should focus on addressing these biases and improving the robustness of AI applications in paediatric radiology.
COVID-19 prevention with alternate vaccine boosting frequencies for multiple-sclerosis patients undergoing therapy with beta-interferon, dimethyl fumarate, natalizumab, or teriflunomide
Authors: Dornburg Alex , Hassler Hayley B. , Townsend Jeffrey P. 
Published: September 2024

AbstractMultiple-sclerosis patients undergoing treatment with disease-modifying therapies exhibit diverse immune responses to COVID-19 vaccinations. However, guidance on how specific treatments influence infection risks and optimal vaccination schedules remains limited. This study integrates data on vaccine-induced and infection-derived antibody responses to predict cumulative probabilities of breakthrough infections in untreated multiple-sclerosis patients and those treated with interferon, dimethyl fumarate, natalizumab, or teriflunomide. Using antibody dynamics and augmented logistic regression models, we evaluated the effectiveness of different Pfizer-BioNTech BNT162b2 booster schedules.Our findings reveal that annual boosters effectively reduce infection risks for untreated multiple-sclerosis patients, lowering their cumulative risk by more than half over two years. Among treated patients, booster vaccinations generally provide protection comparable to that of untreated patients, although treatment-specific variations in immunity are evident. For patients on interferon, annual boosters yield an even greater reduction in risk. Patients treated with dimethyl fumarate or natalizumab benefit significantly from boosters, though they experience moderately higher risks compared to untreated patients.This study underscores the importance of tailored booster schedules for MS patients, taking into account disease-modifying-therapy-specific effects on immunity. Our analysis provides actionable insights for mitigating SARS-CoV-2 risks in this vulnerable population until broader long-term infection data are available. These findings aim to guide clinicians in optimizing care for multiple-sclerosis patients in the context of ongoing COVID-19 vaccination strategies.Practice PointsTailor Booster Schedules:Annual COVID-19 boosters are recommended for untreated MS patients and those on interferon, dimethyl fumarate, natalizumab, or teriflunomide; Bi-annual boosters would further reduce infection risk.Address Risks for Immunosuppressed Patients:For patients on highly immunosuppressive treatments (e.g., fingolimod, ocrelizumab, rituximab), recognize diminished vaccine efficacy and consider supplemental measures for risk mitigation.Promote Booster Adherence and Education:Encourage timely booster adherence and educate patients on the benefits of tailored vaccination schedules, while keeping in mind the potential antiviral properties of specific therapies.
Secular trends of incidence and prevalence of parkinsonism and subtypes: A cohort study in the United Kingdom
Authors: Chen Xihang , Barclay Nicola L. , Pineda-Moncusí Marta , Sabaté Martí Català , Molina-Porcel Laura , Man Wai Yi , Delmestri Antonella , Prieto-Alhambra Daniel , Jödicke Annika M. , Newby Danielle 
Published: September 2024

AbstractBackgroundWhile summarized under the umbrella term “Parkinsonism”, several subtypes with different etiologies exist, including Parkinson’s Disease, Vascular Parkinsonism and Drug-induced Parkinsonism. However, evidence on their incidence and prevalence remains limited.ObjectivesTo evaluate secular trends of incidence and prevalence of parkinsonism, Parkinson’s Disease, Vascular Parkinsonism, and Drug-induced Parkinsonism from 2007 to 2021 in the United Kingdom.MethodsWe used primary care data, Clinical Practice Research Datalink GOLD, from the United Kingdom. Individuals were included if they were registered from January 2007 to December 2021 with at least one year of prior observation. Incidence and prevalence were calculated on a yearly basis with 95% confidence intervals and then stratified by age and sex.ResultsFrom 2007 to 2019, the incidence of parkinsonism and Parkinson’s Disease decreased, with Parkinson’s Disease incidence dropping from 35.86 (95% confidence interval: 34.22 – 37.56) to 31.40 (29.40 – 33.50) per 100,000 person-years. The prevalence of parkinsonism and Parkinson’s Disease increased from 0.22% (0.22% - 0.23%) and 0.21% (0.21% - 0.22%) in 2007 to peak in 2016 with 0.25% (0.25% - 0.26%) and 0.23% (0.23% - 0.24%) respectively. The number of Vascular Parkinsonism diagnoses have increased from 2010, whereas incidence and prevalence of Drug-induced Parkinsonism remained stable. Incidence and prevalence increased with age and were generally higher in males, except for Drug-induced Parkinsonism, which was slightly higher in females.ConclusionsGiven its association with aging, parkinsonism and these subtypes continue to present an increasing challenge to our aging society.
RiskPath: Explainable deep learning for multistep biomedical prediction in longitudinal data
Authors: de Lacy Nina , Ramshaw Michael , Lam Wai Yin 
Published: September 2024

HighlightsMany diseases are increasingly conceptualized as multifactorial, progressive processesRobust prediction of progressive disease courses can advance risk stratification and treatment targetingRiskPath provides optimizable timeseries AI to predict progressive disease with longitudinal cohort dataEnhanced explainability and functionality facilitates risk pathway mapping and compact modelsThe Bigger PictureIdentifying persons at elevated risk for a disease outcome is a key prerequisite for targeting interventions to improve health. Current risk stratification tools for common diseases are aging and achieve only moderate performance. Moreover, many diseases are increasingly recognized to be complex outcomes where individual risk is determined not by a single effect modifier but by time-dependent interactions among many contributory factors over the lifecourse. There is an urgent need to improve individual-level prediction for progressive diseases and understand how multifactorial risks interact over time so that risk stratification and accompanying prevention and intervention strategies can be targeted earlier and more effectively in the disease course.SummaryMany diseases are the end outcomes of multifactorial risks that interact and increment over months or years. Timeseries AI methods have attracted increasing interest given their ability to operate on native timeseries data to predict disease outcomes. Instantiating such models in risk stratification tools has proceeded more slowly, in part limited by factors such as structural complexity, model size and explainability. Here, we present RiskPath, an explainable AI toolbox that offers advanced timeseries methods and additional functionality relevant to risk stratification use cases in classic and emerging longitudinal cohorts. Theoretically-informed optimization is integrated in prediction to specify optimal model topology or explore performance-complexity tradeoffs. Accompanying modules allow the user to map the changing importance of predictors over the disease course, visualize the most important antecedent time epochs contributing to disease risk or remove predictors to construct compact models for clinical applications with minimal performance impact.
Combining evidence from human genetic and functional screens to identify pathways altering obesity and fat distribution
Authors: Baya Nikolas A. , Sur Erdem Ilknur , Venkatesh Samvida S. , Reibe Saskia , Charles Philip D. , Navarro-Guerrero Elena , Hill Barney , Lassen Frederik Heymann , Claussnitzer Melina , Palmer Duncan S. , Lindgren Cecilia M. 
Published: September 2024

AbstractOverall adiposity and body fat distribution are heritable traits associated with altered risk of cardiometabolic disease and mortality. Performing rare variant (minor allele frequency<1%) association testing using exome-sequencing data from 402,375 participants in the UK Biobank (UKB) for nine overall and tissue-specific fat distribution traits, we identified 19 genes where putatively damaging rare variation associated with at least one trait (Bonferroni-adjustedP<1.58×10-7) and 52 additional genes at FDR≤1% (P≤4.37×10-5). These 71 genes exhibited higher (P=3.58×10-18) common variant prioritisation scores than genes not significantly enriched for rare putatively damaging variation, with evidence of monotonic allelic series (dose-response relationships) among ultra-rare variants (minor allele count≤10) in 22 genes. Five of the 71 genes have cognate protein UKB Olink data available; all five associated (P<3.80×10-6) with three or more analysed traits. Combining rare and common variation evidence, allelic series and proteomics, we selected 17 genes for CRISPR knockout in human white adipose tissue cell lines. In three previously uncharacterised target genes, knockout increased (two-sidedt-testP<0.05) lipid accumulation, a cellular phenotype relevant for fat mass traits, compared to Cas9-empty negative controls:COL5A3(fold change [FC]=1.72,P=0.0028),EXOC7(FC=1.35,P=0.0096), andTRIP10(FC=1.39,P=0.0157); furthermore, knockout ofSLTMresulted in reduced lipid accumulation (FC=0.51,P=1.91×10-4). Integrating across population-based genetic andin vitrofunctional evidence, we highlight therapeutic avenues for altering obesity and body fat distribution by modulating lipid accumulation.
Hypothalamic Gliosis is Associated With Multiple Cardiovascular Disease Risk Factors
Authors: Lo Justin , Melhorn Susan J , Kee Sarah , Olerich Kelsey LW , Huang Alyssa , Yeum Dabin , Beiser Alexa , Seshadri Sudha , De Carli Charles , Schur Ellen A 
Published: September 2024

AbstractBackgroundHypothalamic gliosis is mechanistically linked to obesity and insulin resistance in rodent models. We tested cross-sectional associations between radiologic measures of hypothalamic gliosis in humans and clinically relevant cardiovascular disease risk factors, as well as prevalent coronary heart disease.MethodsUsing brain MRI images from Framingham Heart Study participants (N=867; mean age, 55 years; 55% females), T2 signal intensities were extracted bilaterally from the region of interest in the mediobasal hypothalamus (MBH) and reference regions in the amygdala (AMY) and putamen (PUT). T2 signal ratios were created in which greater relative T2 signal intensity suggests gliosis. The primary measure compared MBH to AMY (MBH/AMY); a positive control ratio (MBH/PUT) also assessed MBH whereas a negative control (PUT/AMY) did not. Outcomes were BMI, HDL-C, LDL-C, fasting triglycerides, and the presence of hypertension (n=449), diabetes mellitus (n=66), metabolic syndrome (n=254), or coronary heart disease (n=25). Dietary risk factors for gliosis were assessed in a prospective analysis. Statistical testing was performed using linear or logistic regression.ResultsGreater MBH/AMY T2 signal ratios were associated with higher BMI (β = 21.5 [95% CI, 15.4– 27.6];P<0.001), higher fasting triglycerides (β = 1.1 [95% CI, 0.6–1.7];P<0.001), lower HDL-C (β = –20.8 [95% CI, –40.0 to –1.6];P=0.034), and presence of hypertension (odds ratio, 1.2 [95% CI, 1.1–1.4];P=0.0088), and the latter two were independent of BMI. Findings for diabetes mellitus were mixed and attenuated by adjusting for BMI. Metabolic syndrome was associated with MBH/AMY T2 signal ratios (odds ratio, 1.3 [95% CI, 1.1–1.6];P<0.001). Model results were almost uniformly confirmed by the positive control ratios, whereas negative control ratios that did not test the MBH were unrelated to any outcomes (allP≥0.05). T2 signal ratios were not associated with prevalent coronary heart disease (allP>0.05), but confidence intervals were wide. Self-reported percentages of macronutrient intake were not consistently related to future T2 signal ratios.ConclusionsUsing a well-established study of cardiovascular disease development, we found evidence linking hypothalamic gliosis to multiple cardiovascular disease risk factors, even independent of adiposity. Our results highlight the need to consider neurologic mechanisms to understand and improve cardiometabolic health.
High Seroprevalence toAedes-borne arboviruses in Ethiopia: a Cross-sectional Survey in 2024
Authors: Parker Daniel M. , Haileselassie Werissaw , Hailemariam Temesgen Sisay , Workenh Arsema , Workineh Salle , Wang Xiaoming , Lee Ming-Chieh , Yan Guiyun 
Published: September 2024

ABSTRACTAedes-borne diseases infect millions of people each year. In the last decade several arbovirus outbreaks have been reported in Ethiopia. Arbovirus diagnosis and surveillance is lacking and the true burden is unknown. In this study we conducted a seroprevalence survey using a commercially available test kit that that tests for immunological responses to IgM and IgG for dengue (DENV), Zika (ZIKV), and chikungunya (CHIKV) viruses in Dire Dawa city, eastern Ethiopia. We found a high IgG seroprevalence for DENV (76%), CHIKV (44%), and ZIKV (38%), and <20% IgM seropositivity across all viruses. As a comparison, we conducted serosurveillance in Addis Ababa, the national capital with no reported history of arbovirus outbreaks. The highest seropositivity we found was to IgM for DENGV at approximately 3%. Our results suggest both past and recent widespread exposure to these arboviruses, underscoring the need for improved surveillance and public health interventions in Ethiopia.
End Stage Kidney Disease in Cystic Fibrosis
Authors: Stevanovic Mirjana , MacKenzie Todd A , Zimmerman Asha , Graber Martha L 
Published: September 2024

AbstractBackgroundCystic fibrosis (CF) is a multisystem autosomal recessive disease caused by mutations in the cystic fibrosis transduction regulator (CFTR). The CFTR is expressed in all renal tubular segments. Tubular functional abnormalities as well as renal histologic changes are recognized in people with cystic fibrosis (CF). Chronic kidney disease (CKD) occurs in CF at greater frequency than in the non-CF population. The prevalence and characteristics of end stage kidney disease (ESKD) in the cystic fibrosis population have not previously been described.MethodsWe used data supplied by the US Renal Data System (USRDS) to compare persons with ESKD and CF with those with ESKD who did not have a diagnosis of CF. We used linear and logistic regression, propensity score-matched Kaplan-Meier survival curves, and log-rank tests.ResultsThe prevalence of ESKD was approximately thirty times higher than predicted in the general US population. Diabetes was more frequently a diagnosis in people with CF, but was approximately half as frequently the primary cause of ESKD than in those without CF. Complications of transplantation, particularly of lung, were rarely the cause of ESKD in those without CF but were the second most frequent etiology of ESKD in people with CF. Drugs and medications, interstitial nephritis and acute kidney injury (AKI) were more frequent primary causes in those with CF. Hypertension, cystic kidney disease, and glomerulonephritis were less frequent in those with CF. Mortality and survival with ESKD were not significantly different between those with CF and ESKD and those with ESKD who did not have CF. Diabetes mellitus and complications of lung transplantation as the primary cause of ESKD, but not lung transplant status, were associated with significantly shorter survival with ESKD in people with CF.ConclusionsPeople living with CF have a markedly higher prevalence of ESKD than the general United States population. The profile of primary causes of ESKD differed significantly from that of the non-CF population. Diabetes mellitus was approximately half as frequently the primary cause of ESKD in those with CF. Complications of solid organ transplant, particularly lung, were the second most frequent primary cause of ESKD in people with CF. Survival with ESKD was not significantly different between those who did and did not have CF. The diagnosis of diabetes mellitus, and complications of lung transplantation as the primary cause of ESKD, but not lung transplant status, were associated with significantly shorter survival with ESKD in people with CF. It is our aim that these findings will promote awareness of kidney disease in persons living with CF and will encourage prevention of acute kidney injury (AKI), early detection and intervention in CKD, and preemptive referral to nephrology and transplant centers.
The central response of electroacupuncture for anxiety in people with obesity based on resting-state functional magnetic resonance imaging: a protocol for a randomized, blinded, sham-controlled trial
Authors: Shu Qi , Peng Qiumei , Duan Wenxiu , Zhang Fan , Yu Qing , Cai Ronglin 
Published: September 2024

IntroductionObesity is a problem that is increasing worldwide and anxiety is a major psychological disorder associated with obesity. Electroacupuncture (EA) has been proved to be a feasible treatment for obesity and anxiety respectively in clinical practice. However, to date, there are no data on EA’s effectiveness on anxiety for people with obesity. Therefore, this study aims to evaluate the efficacy and safety of EA for anxiety in people with obesity, and to observe the brain functional status of patients and the intervention effects of EA on brain function by functional magnetic resonance imaging (fMRI).Methods and analysisThis study is a randomized, blinded, sham-controlled and clinical trial. 72 obesity patients from two hospitals with anxiety will be randomly divided into EA group and control group in 1:1 ratio by using a random number table. Patients in EA group will receive EA treatment at specific acupoints with penetrating needling for 8 weeks. The control group will receive Park’s acupuncture with non- penetrating needling. Weight, waist, BMI (Body Mass Index), SAS (Self-rating Anxiety Scale), STAI (State-Trait Anxiety Inventory) and PSQI (Pittsburgh Sleep Quality Index) will be performed before, after 8-week treatments and at one-month follow-up in patients. Objective metabolic parameters such as triglyceride, total cholesterol, fasting blood glucose, ghrelin, leptin, cortisol and adrenocorticotropic hormone will also be detected before and after 8-week intervention. 20 patients will be randomly selected from EA group and control group, respectively, before treatment, and 20 paired healthy participants will be recruited at the same time. The 20 patients will be scanned by fMRI before and after treatment while the other 20 healthy participants will be scanned only at baseline. Regional homogeneity, amplitude of low-frequency fluctuation and resting-state-functional-connectivity will be carried out to compare the dysfunctional brain regions between patients and healthy participants, as well as the differences between two groups of patients after treatment.Ethics and disseminationThe study protocol has been approved by the Hospital Ethics Committee of Second Affiliated Hospital of Anhui University of Chinese Medicine (2023-zj-42). Informed consent will be obtained prior to starting study- ralated procedures. The results will be disseminated in peer-reviewed journals and at scientific conferences.Trail Registration numberChinese Clinical Trail Registry. ChiCTR2400083594, registered 29 April 2024.