bluuebunny/crossref_metadata_2025_split huggingface dataset:
Meditation attenuates Default-mode activity: a pilot study using ultra-high strength MRI
Authors: Ganesan Saampras , Moffat Bradford , Van Dam Nicholas T. , Lorenzetti Valentina , Zalesky Andrew 
Published: January 2023

AbstractObjectivesMapping the neurobiology of meditation using 3 Tesla functional MRI (fMRI) has burgeoned recently. However, limitations in signal quality and neuroanatomical resolution have impacted reliability and precision of extant findings. Although ultra-high strength 7 Tesla MRI overcomes these limitations, investigation of meditation using 7 Tesla fMRI is still in its infancy.MethodsIn this feasibility study, we scanned 10 individuals who were beginner meditators using 7 Tesla fMRI while they performed focused attention meditation and non-focused rest. We also measured and adjusted the fMRI signal for key physiological differences between meditation and rest. Finally, we explored the 2-week impact of the single fMRI meditation session on mindfulness, anxiety and focused attention attributes.ResultsGroup-level task fMRI analyses revealed significant reductions in activity during meditation relative to rest in Default-mode network hubs, i.e., antero-medial prefrontal and posterior cingulate cortices, precuneus, as well as visual and thalamic regions. These findings survived stringent statistical corrections for fluctuations in physiological responses which demonstrated significant differences (p < 0.05/n, Bonferroni controlled) between meditation and rest. Compared to baseline, State Mindfulness Scale (SMS) scores were significantly elevated (F = 8.16, p<0.05/n, Bonferroni controlled) following the fMRI meditation session, and were closely maintained at 2-week follow up.ConclusionsThis pilot study establishes the feasibility and utility of investigating focused attention meditation using ultra-high strength (7 Tesla) fMRI, by supporting widespread evidence that focused attention meditation attenuates Default-mode activity responsible for self-referential processing. Future functional neuroimaging studies of meditation should control for physiological confounds and include behavioural assessments.
An outbreak of Salmonella Typhimurium following an Eid al-Adha celebration barbecue in Wales (UK), July 2021
Authors: Adamson James , Sawyer Clare , Hobson Gemma , Clark Emily , Fina Laia , Orife Oghogho , Smith Robert , Williams Christopher , Hughes Harriet , Jones Allyson , Swaysland Sarah , Somoye Oluwaseun , Phillips Ryan , Iqbal Junaid , Mohammed Israa , Karani George , Thomas Daniel Rh 
Published: January 2023

AbstractBackgroundOn a Friday evening in July 2021, Public Health Wales received notification of two cases of salmonella gastroenteritis. Both cases reported attending an Eid al-Adha celebration barbecue in a public park in Cardiff, UK two days earlier. Case finding over the weekend indicated further cases in those who had attended this event and an outbreak investigation was initiated.MethodsCases were defined as an individual with diarrhoea and/or vomiting with date of onset on the day of the barbecue, with an epidemiological link to the Eid-al Adha celebration meal. We undertook a cohort study in 36 people attending the barbecue and an associated lunchtime event, and a nested case-control study using Firth logistic regression. A communication campaign that was sensitive towards cultural practices was developed in collaboration with the community, community liaison staff and the Public Health Wales communications team.ResultsConsumption of a traditional raw liver dish, ‘marrara’, at the barbecue was the most likely vehicle for infection (Firth logistic regression, aOR: 49.99, 95%CI 1.71-1461.54, p=0.02). Meat came from two local butchers with the same supplier and food samples yielded identical whole genome sequences to those from cases. This outbreak highlights the need for appropriate food hygiene advice in communities preparing traditional dishes.ConclusionsThis outbreak identified a new vehicle of interest, a traditional raw offal dish. Future outbreak investigations, particularly where cultural events are associated with particular foods, should consider dishes beyond those on routine questionnaires to those which may be relevant to the community in question.
SARS-CoV-2 Reinfection is Preceded by Unique Biomarkers and Related to Initial Infection Timing and Severity: an N3C RECOVER EHR-Based Cohort Study
Authors: Hadley Emily , Yoo Yun Jae , Patel Saaya , Zhou Andrea , Laraway Bryan , Wong Rachel , Preiss Alexander , Chew Rob , Davis Hannah , Chute Christopher G , Pfaff Emily R , Loomba Johanna , Haendel Melissa , Hill Elaine , Moffitt Richard ,   the N3C and RECOVER consortia
Published: January 2023

AbstractAlthough the COVID-19 pandemic has persisted for over 2 years, reinfections with SARS-CoV-2 are not well understood. We use the electronic health record (EHR)-based study cohort from the National COVID Cohort Collaborative (N3C) as part of the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection. We validate previous findings of reinfection incidence (5.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present novel findings that Long COVID diagnoses occur closer to the index date for infection or reinfection in the Omicron BA epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between first infection and reinfection (chi-squared value: 9446.2, p-value: 0) with a medium effect size (Cramer’s V: 0.18, DoF = 4).
Classification of Hyper-scale Multimodal Imaging Datasets
Authors: MacFadyen Craig , Duraiswamy Ajay , Harris-Birtill David 
Published: January 2023

AbstractAlgorithms that can classify hyper-scale multi-modal datasets, comprising of millions of images, into constituent modality types can help researchers quickly retrieve and classify diagnostic imaging data, accelerating clinical outcomes. This research aims to demonstrate that a deep neural network that is trained on a hyper-scale dataset (4.5 million images) composed of heterogeneous multi-modal data, can be used to obtain significant modality classification accuracy (96%). By combining 102 medical imaging datasets, a dataset of 4.5 million images was created. A ResNet-50, ResNet-18 and VGG16 were trained to classify these images by the imaging modality used to capture them (Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and X-ray) across many body locations. The classification accuracy of the models was then tested on unseen data.The best performing model achieved classification accuracy of 96% on unseen data. The model achieved a balanced accuracy of 86%.This research shows it is possible to train Deep Learning (DL) Convolutional Neural Networks (CNNs) with hyper-scale multimodal data-sets, composed of millions of images. The trained model can be used to classify images by modality, with the best performing model achieving a classification accuracy of 96%. Such models can find use in real-world applications with volumes of image data in the hyper-scale range, such as medical imaging repositories, or national healthcare institutions. Further research can expand this classification capability to include 3D-scans.
Survey Design and Geospatial Analysis using Data on Baseline Prevalence, Environmental Risk-Factors and Treatment History Drastically Reduces the Cost of STH Impact Surveys
Authors: Fronterrè Claudio , Johnson Olatunji , Giorgi Emanuele , Montresor Antonio , Diggle Peter J 
Published: January 2023

AbstractSoil-transmitted helminth (STH) infections are among the most common neglected tropical diseases worldwide, causing high morbidity and mortality rates in endemic areas. STH impact assessment surveys provide information on the changing epidemiological situation so that control programme managers can adapt the frequency of any continuing preventive chemotherapy (PC). The cost associated with conducting these surveys is an important factor, especially in developing countries with severely limited financial resources. Using three case studies based on historical data on baseline prevalence, environmental risk-factors and treatment history from Kenya, Sierra Leone and Zimbabwe, we show that a model-based geostatistics approach drastically reduces the cost of STH impact surveys by comparison with a survey conducted according to the current WHO guidelines, whilst maintaining the same overall accuracy. The framework that we develop is disease-agnostic and could easily be repurposed for use with other NTDs.
The relationship between diabetes, obesity and cardiovascular disease phenotypes: a UK Biobank cohort study
Authors: Brown Oliver I , Drozd Michael , McGowan Hugo , Giannoudi Marilena , Conning-Rowland Marcella , Gierula John , Straw Sam , Wheatcroft Stephen B , Paradine Katherine , Roberts Lee D , Levelt Eylem , Ajjan Ramzi , Griffin Kathryn J , Bailey Marc A , Kearney Mark T , Cubbon Richard M 
Published: January 2023

AbstractIntroductionObesity and diabetes mellitus (DM) frequently co-exist, yet their individual contributions to cardiovascular risk remain debated. We explored cardiovascular disease biomarkers, events and mortality in a large cohort stratified by body mass index (BMI) and DM.Methods451,355 UK Biobank participants were stratified by ethnicity-specific BMI categories (normal, overweight, obese) and DM status. We examined cardiovascular biomarkers including: carotid intima-media thickness (CIMT); arterial stiffness; left ventricular ejection fraction (LVEF) and cardiac contractility index (CCI). Poisson regression models estimated adjusted incidence rate ratios (IRR) for myocardial infarction, ischaemic stroke and cardiovascular death, with normal weight non-DM as comparator.Results5% of participants had DM (10% normal weight, 34% overweight and 55% obese; versus 34%, 43% and 23%, respectively, in non-DM). In the non-DM group, overweight/obesity was associated with higher CIMT, arterial stiffness and CCI, and lower LVEF (p<0.05); these relationships were diminished in the DM group. Within BMI classes, DM was associated with adverse cardiovascular phenotype (p<0.05), particularly in the normal weight group. After 5,323,190 person-years follow-up, incident myocardial infarction, ischaemic stroke and cardiovascular mortality all rose across increasing BMI categories in the DM and non-DM groups (p<0.05). However, normal weight DM had higher cardiovascular mortality than obese non-DM (IRR 2.81 [95% confidence interval: 2.24-3.54] vs IRR 1.84 [1.70-1.98]).ConclusionsObesity and DM are additively associated with adverse cardiovascular biomarkers and mortality risk. Whilst adiposity metrics are more strongly correlated with cardiovascular biomarkers than diabetes-oriented metrics, both correlate weakly, suggesting other factors underpin the high cardiovascular risk of normal-weight diabetes.
OpenChart-SE: A corpus of artificial Swedish electronic health records for imagined emergency care patients written by physicians in a crowd-sourcing project
Authors: Berg J , Aasa CO , Appelgren Thorell B , Aits S 
Published: January 2023

AbstractElectronic health records (EHRs) are a rich source of information for medical research and public health monitoring. Information systems based on EHR data could also assist in patient care and hospital management. However, much of the data in EHRs is in the form of unstructured text, which is difficult to process for analysis. Natural language processing (NLP), a form of artificial intelligence, has the potential to enable automatic extraction of information from EHRs and several NLP tools adapted to the style of clinical writing have been developed for English and other major languages. In contrast, the development of NLP tools for less widely spoken languages such as Swedish has lagged behind. A major bottleneck in the development of NLP tools is the restricted access to EHRs due to legitimate patient privacy concerns. To overcome this issue we have generated a citizen science platform for collecting artificial Swedish EHRs with the help of Swedish physicians and medical students. These artificial EHRs describe imagined but plausible emergency care patients in a style that closely resembles EHRs used in emergency departments in Sweden. In the pilot phase, we collected a first batch of 50 artificial EHRs, which has passed review by an experienced Swedish emergency care physician. We make this dataset publicly available as OpenChart-SE corpus (version 1) under an open-source license for the NLP research community. The project is now open for general participation and Swedish physicians and medical students are invited to submit EHRs on the project website (https://github.com/Aitslab/openchart-se). Additional batches of quality-controlled EHRs will be released periodically.
Diminished responses to mRNA-based SARS-CoV-2 vaccines in individuals with rheumatoid arthritis on immune modifying therapies
Authors: Klebanoff Samuel D. , Rodda Lauren B. , Morishima Chihiro , Wener Mark H. , Yuzefpolskiy Yevgeniy , Bettelli Estelle , Buckner Jane H. , Speake Cate , Pepper Marion , Campbell Daniel J. 
Published: January 2023

AbstractRheumatoid arthritis (RA) is a chronic inflammatory autoimmune disorder that causes debilitating swelling and destruction of the joints. People with RA are treated with drugs that actively suppress one or more parts of their immune system, and these may alter their response to vaccination against SARS-CoV-2. In this study, we analyzed blood samples from a cohort of RA subjects after receiving a 2-dose mRNA COVID-19 vaccine regimen. Our data show that individuals on the CTLA4-Ig therapy abatacept have reduced levels of SARS-CoV-2-neutralizing antibodies after vaccination. At a cellular level, these subjects show reduced activation and class-switching of SARS-CoV-2-specific B cells, as well as reduced numbers and impaired helper cytokine production by SARS-CoV-2-specific CD4+T cells. Individuals on methotrexate showed similar but less severe defects in vaccine response, whereas individuals on the B cell-depleting therapy rituximab had a near-total loss of antibody production after vaccination. These data define a specific cellular phenotype associated with impaired response to SARS-CoV-2 vaccination in RA subjects on different immune-modifying therapies, and help inform efforts to improve vaccination strategies in this vulnerable population.
Expression profiling of the learning striatum
Authors: Lousada E , Kliesmete Z , Janjic A , Burguière E , Enard W , Schreiweis C 
Published: January 2023

AbstractDuring cortico-basal ganglia dependent learning, relevant environmental information is associated with certain outcomes; such learning is essential to generate adaptive behaviour in a continuously changing environment. Through repetitive trial-and-error experiences, actions are optimized and cognitive associative load can be relieved through consolidation and automatization. Although the molecular basis of learning is well studied, region-specific genome-wide expression profiles of the striatum, the major input region of cortico-basal ganglia circuits, during learning are lacking. Here we combined an automated operant conditioning paradigm with an efficient RNA-sequencing protocol to compare expression profiles among three learning stages in three striatal regions per hemisphere in a total of 240 striatal biopsies. Notably, the inclusion of matched yoked controls allowed reliably identifying learning-related expression changes. With 593 differently expressed genes (3.3% of all detected genes), we find the strongest effect of learning at an early, goal-directed stage across all three striatal region and identify a total of 921 learning-related expression changes. Our dataset provides a unique resource to study molecular markers of striatal learning.
The use of newborn foot length to identify low birth weight and preterm babies in Papua New Guinea: A diagnostic accuracy study
Authors: Mengi Alice , Vallely Lisa M , Laman Moses , Jally Eunice , Kulimbao Janeth , Warel Sharon , Enman Regina , Aipit Jimmy , Low Nicola , Riddell Michaela 
Published: January 2023

AbstractLow birth weight (LBW, <2.50 kg) and preterm birth (PTB, <37 completed weeks of gestation) are important contributors to neonatal death. Newborn foot length has been assessed to identify LBW and PTB babies in Asia and Africa. The objectives of this observational study were to determine the diagnostic accuracy of foot length to identify LBW and PTB and to compare foot length measurements of a researcher with those of trained volunteers in Papua New Guinea. Newborn babies were enrolled prospectively with written informed consent from their mothers, who were participating in a clinical trial in Madang Province. The reference standards were birth weight, measured by electronic scales and gestational age at birth, based on ultrasound scan and last menstrual period at the first antenatal visit. Newborn foot length was measured within 72 hours of birth with a firm plastic ruler. Optimal foot length cut-off values for LBW and PTB were derived from receiver operating characteristic curve analysis. Bland-Altman analysis was used to assess inter-observer agreement between researcher and volunteer. From 12 October 2019 to 6 January 2021, we enrolled 342 newborns (80% of those eligible); 21.1% (72/342) were LBW and 7.3% (25/342) were PTB. The area under the curve for LBW was 87.0% (95% confidence intervals 82.8-90.2) and for PTB 85.6% (81.5-89.2). The optimal foot length cut-off was <7.7 cm for both LBW (sensitivity 84.7%, 74.7-91.2, specificity 69.6%, 63.9-74.8) and PTB (sensitivity 88.0% (70.0-95.8), specificity 61.8% (56.4-67.0). In 123 babies with paired measurements, the mean difference between the researcher and volunteer measurements was 0.07 cm (95% limits of agreement −0.55 to +0.70) and 7.3% (9/123) of the pairs were outside the 95% limits of agreement. When birth at a health facility is not possible, foot length measurement can identify LBW and PTB in newborns but needs appropriate training for community volunteers and evaluation of its impact on healthcare outcomes.
Peculiar morphologic characteristics of adrenal veins and similarity to fibromuscular dysplasia of artery: implication of pathogenesis
Authors: Zhang Peilin , Rafii Daniel , Arenas Minerva Romero 
Published: January 2023

AbstractBackgroundFibromuscular dysplasia (FMD) is a peculiar abnormality of arterial wall with characteristic bead-like features on angiogram that commonly occurs in renal arteries and carotid arteries. The morphologic features of FMD of arteries share significant similarities to those described for adrenal veins. The pathogenic mechanism of FMD remains largely unknown and genetic susceptibility appears important.MethodsWe examined the morphologic characteristics of adrenal vessels to compare with fibromuscular dysplasia and segmental arterial mediolysis. We have retrospectively reviewed 30 cases of adrenalectomy specimens associated with or without adrenal neoplasms including cortical adenomas and pheochromocytomas regarding the histomorphologic features of adrenal vessels within the normal tissue and the tumors.ResultsAdrenal veins showed characteristically asymmetrical muscle bundles in normal adrenal glands in all cases except for one adrenal cortical adenoma in which normal adrenal gland was absent. These morphologic features shared significant similarities with those of FMD of arteries. A spectrum of vascular changes including hyalinization, intimal fibroplasia, myxoid degeneration and atherosis was observed in 10 of the 15 cases of adrenal cortical adenomas and 5 of the 10 cases of pheochromocytomas. Most common complications were hemorrhage/hematoma and thrombosis. There is no statistically significant differences in patients’ baseline characteristics including race/ethnicity, marital status, blood pressure and body mass index (BMI).ConclusionThe unique vascular changes in adrenal glands and adrenal neoplasms suggests the importance of tissue specific milieu likely related to adrenal hormones/hormone receptors, providing direction of further investigation of pathogenic mechanisms and potentially management of FMD and similar diseases.
Oxytocin administration enhances pleasantness and neural responses to gentle stroking but not moderate pressure social touch by increasing peripheral concentrations
Authors: Chen Yuanshu , Zou Haochen , Hou Xin , Lan Chunmei , Wang Jing , Qing Yanan , Chen Wangjun , Yao Shuxia , Kendrick Keith M 
Published: January 2023

AbstractBackgroundSocial touch constitutes a key component of human social relationships although in some conditions with social dysfunction, such as autism, it can be perceived as unpleasant. We have previously shown that intranasal administration of oxytocin facilitates the pleasantness of social touch and activation of brain reward and social processing regions, although it is unclear if it influences responses to gentle stroking touch mediated by cutaneous C-touch fibers or pressure touch mediated by other types of fibers. Additionally, it is unclear whether endogenous oxytocin acts via direct entry into the brain or by increased peripheral blood concentrations.MethodsIn a randomized controlled design, we compared effects of intranasal (direct entry into the brain and increased peripheral concentrations) and oral (only peripheral increases) oxytocin on behavioral and neural responses to social touch targeting C-touch (gentle-stroking) or other (medium pressure without stroking) cutaneous receptors.ResultsAlthough both types of touch were perceived as pleasant, intranasal and oral oxytocin equivalently enhanced pleasantness ratings and responses of reward, orbitofrontal cortex, and social processing, superior temporal sulcus, regions only to gentle-stroking not medium pressure touch. Furthermore, increased blood oxytocin concentrations predicted the pleasantness of gentle stroking touch. The specificity of neural effects of oxytocin on C-touch targeted gentle stroking touch were confirmed by time-course extraction and classification analysis.ConclusionsIncreased peripheral concentrations of oxytocin primarily modulate its behavioral and neural responses to gentle social touch mediated by C-touch fibers. Findings have potential implications for using oxytocin therapeutically in conditions where social touch is unpleasant.FundingKey Technological Projects of Guangdong Province grant 2018B030335001.Clinical trial numberNCT05265806
Evolution takes multiple paths to evolvability when facing environmental change
Authors: Kumawat Bhaskar , Lalejini Alexander , Acosta Monica , Zaman Luis 
Published: January 2023

AbstractLiving systems are surprisingly effective at exploiting new opportunities, as evidenced by the rapid emergence of antimicrobial resistance and novel pathogens. How populations attain this level ofevolvabilityand the various ways it aids their survival are major open questions with direct implications for human health. Here, we use digital evolution to show that particular kinds of environments facilitate the simultaneous evolution of high mutation rates and a distribution of mutational effects skewed towards beneficial phenotypes. The evolved mutational neighborhoods allow rapid adaptation to previously encountered environments, whereas higher mutation rates aid adaptation to completely new environmental conditions. By precisely tracking evolving lineages and the phenotypes of their mutants, we show that evolving populations localize on phenotypic boundaries between distinct regions of genotype space. Our results demonstrate how evolution shapes multiple determinants of evolvability concurrently, fine-tuning a population’s adaptive responses to unpredictable or recurrent environmental shifts.