bluuebunny/crossref_metadata_2025_split huggingface dataset:
Demography, hygiene and previous disease prevalence as plausible risk factors associated with Covid-19 deaths across Indian states
Authors: Chatterjee Bithika , Mande Shekhar C. 
Published: June 2023

AbstractSeverity of Covid-19 diseases has been disproportionate with higher case-fatality ratio affecting developed nations. In India, states with higher income have reported more number of deaths compared to lower income states. The global burden of diseases India 2019 and the National Health Profile 2019 data was used to draw correlations with Covid-19 mortality at two different dates of peak Covid-19 cases in India. We explored correlation of mortality in different states of India with prevalence of different diseases, demography, development, sanitation etc. The study found a positive correlation with known demographic parameters such as percentage of elderly population(spearman correlation coefficient(rho) =0.44 and 0.46 with 1stand 2ndpeak respectively). Similarly, percentage urbanization was seen to correlate well with mortality(rho=0.71 and 0.57) suggesting Covid-19 to be a predominantly urban disease. Prevalence of Autoimmune diseases, and Cancer show higher correlation with deaths. A surprising positive correlation emerged between improved sanitation parameters, such as closed drainage and indoor toilets, with COVID-19 deaths. Overall the multivariate regression model achieved by combining demography, sanitation, autoimmune diseases and cancer gave us the best prediction for Covid-19 mortality(adjusted R square value of 0.71 with peak 1 and 0.85 with peak 2). Analysis of the Covid-19 related data seems to indicate that as the wealth of a state increases, the state’s urban landscape changes often leading to better sanitation facilities. The lifestyle and prevalence to autoimmune diseases as well as cancer also increases. However, this may affect the state’s ability to fight pandemics due to lower exposure to pathogens and immune training.
Dual-energy computed tomography imaging with megavoltage and kilovoltage x-ray spectra
Authors: Jadick Giavanna , Schlafly Geneva , La Rivière Patrick J. 
Published: June 2023

AbstractPurposeSingle-energy computed tomography (CT) often suffers from poor contrast, yet it remains critical for effec-tive radiotherapy treatment. Modern therapy systems are often equipped with both megavoltage (MV) and kilovoltage (kV) x-ray sources and thus already possess the hardware needed for dual-energy (DE) CT. There exists an unexplored potential for enhanced image contrast using MV-kV DE-CT in radiotherapy contexts.ApproachA toy model comprising a single-line integral through a two-material object was designed for computing basis material signal-to-noise ratio (SNR) using estimation theory. Five dose-matched spectra (three kV, two MV) and three variables were considered: spectral combination, spectral dose allocation, and object material composition. The single-line model was extended to a simulated fan-beam CT acquisition of an anthropomorphic phantom with and without a metal implant. Basis material sinograms were computed and synthesized into virtual monoenergetic images (VMIs). MV-kV and kV-kV VMIs were compared with single-energy images.ResultsThe 80kV-140kV pair typically yielded the best SNRs, but for bone thicknesses greater than 8 cm, the detunedMV-80kV pair surpassed it. Peak MV-kV SNR was achieved with approximately 90% dose allocated to the MV spectrum. For the CT simulations, MV-kV VMIs yielded a higher contrast-to-noise ratio (CNR) than single-energy CT at specific monoenergies. With the metal implant, MV-kV produced a higher maximum CNR and lower minimum root-mean-square-error than kV-kV.ConclusionsThis work quantitatively analyzes MV-kV DE-CT imaging and assesses its potential advantages. This technique may yield improved contrast and accuracy relative to dose-matched single-energy CT or kV-kV DE-CT, depending on object composition.
SOCIAL MEDIA AS AN INFORMATION, EDUCATION, AND COMMUNICATION TOOL FOR RABIES PREVENTION: AN INTERVENTIONAL STUDY
Authors: Verma Jay , Agarwal Anurag 
Published: June 2023

ABSTRACTIntroductionRabies is a fatal disease that can be avoided by treating animal bites promptly. Hence, post-exposure prophylaxis is critical. As a result, the National Rabies Control Program was approved under the 12th five-year plan. One of its strategies is to engage in Information, Education and Communication activities. Social media provides an opportunity for the quick and easy dissemination of research but is constrained by a lack of peer review and the risk of misinterpretation. The efficacy of a novel social media-based knowledge dissemination strategy for rabies prevention was tested in this study.MethodsAn experimental study design was followed, wherein 144 preclinical medical students were included in each control and test group. The test group was administered the intervention, which exposed the participants to health education material via social media across a span of 30 days. Participants’ knowledge, attitude, and practices were observed before and after the study duration.ResultsThere was no significant change in the responses of the control (chi-square statistic = 2.46, p-value = 0.96) and test (chi-square statistic = 1.64, p-value = 0.98) groups across the study duration. A comparison of the change in responses between the two groups revealed an insignificant difference (chi-square statistic = 1.29, p-value = 0.73).ConclusionSocial media is an ineffective strategy for improvements in health literacy over a short duration. Such strategies need further validation for longer durations. Moreover, the effectiveness of the health education material itself needs to be assessed.
The pattern of antidiabetic drugs and glycaemic control among type 2 diabetes patients in an Endocrinology Clinic in Lagos, Nigeria
Authors: Azeez Taoreed Adegoke 
Published: June 2023

AbstractBackgroundDiabetes mellitus is highly prevalent in Nigeria. In addition to lifestyle changes, hypoglycaemic agents are of crucial importance in providing optimal care. The study aimed to study the pattern of hypoglycaemic agents and glycaemic control.MethodsIt is a retrospective study. Parameters of interest were obtained from the electronic medical records of 248 type 2 diabetes patients.ResultsThe mean age of the patients was 59.6 ± 12.7 years. Biguanides (85.5%) and DPP-IV inhibitors (60.9%) were the most commonly used antidiabetic drugs, while thiazolidinediones (1.2%), α-glucosidase inhibitors (0.8%), and meglitinides (0%) were the least prescribed. In addition, SGLT-2 inhibitors, insulins, GLP-1 agonists, and sulphonylureas were prescribed to 31.0%, 17.1%, 15.3%, and 14.9%, respectively. On average, about 2-3 hypoglycaemic agents were prescribed. The number of drugs used and HbA1c were significantly negatively correlated. Biguanide, insulins, and DPP-IV inhibitors were associated with a significantly lower HbA1c.ConclusionsMetformin is the drug of choice. Combining 2 to 3 drugs is very common. Glycaemic control is better in the present study, compared with prior studies, and it could be due to the pattern of drugs used in this study.
Combined cerebrospinal fluid metabolomic and cytokine profiling in tuberculosis meningitis reveals robust and prolonged changes in immunometabolic networks
Authors: Tomalka Jeff , Sharma Ashish , Smith Alison G.C. , Avaliani Teona , Gujabidze Mariam , Bakuradze Tinatin , Sabanadze Shorena , Jones Dean P. , Avaliani Zaza , Kipiani Maia , Kempker Russell R. , Collins Jeffrey M. 
Published: June 2023

AbstractMuch of the high mortality in tuberculosis meningitis (TBM) is attributable to excessive inflammation, making it imperative to identify targets for host-directed therapies that reduce pathologic inflammation and mortality. In this study, we investigate how cytokines and metabolites in the cerebral spinal fluid (CSF) associate with TBM at diagnosis and during TBM treatment. At diagnosis, TBM patients demonstrate significant increases versus controls of cytokines and chemokines that promote inflammation and cell migration including IL-17A, IL-2, TNFα, IFNγ, and IL-1β. Inflammatory immune signaling was strongly correlated with immunomodulatory metabolites including kynurenine, lactic acid, carnitine, tryptophan, and itaconate. Inflammatory immunometabolic networks were only partially reversed with two months of effective TBM treatment and remained significantly different versus control CSF. Together, these data highlight a critical role for host metabolism in regulating the inflammatory response to TBM and indicate the timeline for restoration of immune homeostasis in the CSF is prolonged.
The brain’s sensitivity to sensory error can be modulated by altering perceived variability
Authors: Tang Ding-lan , Parrell Benjamin , Beach Sara D. , Niziolek Caroline A. 
Published: June 2023

AbstractWhen individuals make a movement that produces an unexpected outcome, they learn from the resulting error. This process, essential in both acquiring new motor skills and adapting to changing environments, critically relies on error sensitivity, which governs how much behavioral change results from a given error. Although behavioral and computational evidence suggests error sensitivity can change in response to task demands, neural evidence regarding the flexibility of error sensitivity in the human brain is lacking. Critically, the sensitivity of the nervous system to auditory errors during speech production, a complex and well-practiced motor behavior, has been extensively studied by examining the prediction-driven suppression of auditory cortical activity. Here, we tested whether the nervous system’s sensitivity to errors, as measured by this suppression, can be modulated by altering speakers’ perceived variability. Our results showed that error sensitivity was increased after exposure to an auditory perturbation that increased participants’ perceived variability, consistent with predictions generated from previous behavioral data and state-space modeling. Conversely, we observed no significant changes in error sensitivity when perceived variability was unaltered or artificially reduced. The current study establishes the validity of behaviorally modulating the nervous system’s sensitivity to errors. As sensitivity to sensory errors plays a critical role in sensorimotor adaptation, modifying error sensitivity has the potential to enhance motor learning and rehabilitation in speech and, potentially, more broadly across motor domains.Significance StatementThe process of learning from error is essential for both the acquisition of new skills and successful adaptation to changing environments. Such error-based learning critically relies on error sensitivity, which determines how much we learn from a given error. Although evidence from behavioral studies suggests error sensitivity is malleable, neural evidence regarding the flexibility of error sensitivity in the human brain is lacking. Here, we showed that the nervous system’s sensitivity to errors can be modulated by altering perceived variability. The present study establishes the validity of behaviorally modulating neural sensitivity to sensory errors. Improving our ability to learn from error can play a critical role in applied settings such as rehabilitation.
ASSAY OF THE DREEM DEVICE ON SLEEP METRICS AND AN EXPLORATION OF SLEEP STAGING IN CHRONIC SHORT SLEEPERS DURING TIME IN BED EXTENSION
Authors: Mallender Zachary , Depner Christopher M. 
Published: June 2023

ABSTRACTDespite clear research findings showing that sleeping less than seven hours per night has an array of health consequences, over 1 in 3 American adults report sleeping less than seven hours per night. Many studies exploring the consequences of insufficient sleep are restricted to small sample sizes and are of relatively short duration due to a significant cost of gold-standard polysomnography in terms of participant burden, expense, time, and reliance on trained sleep technicians. Additionally, many studies of short sleep duration use a paradigm of experimental sleep restriction on otherwise healthy sleepers, which excludes people who chronically obtain short sleep duration over months to years. Here, we explore possible solutions to these issues by implementing a sleep extension protocol in 14 adults (average age 20.6±2.5y; +/- SD) with self-reported habitual sleep duration less than 6.5h/night. Participants completed 2 weeks of baseline monitoring (habitual short sleep duration) and then were instructed to increase time in bed to ≥8h/night for four weeks. Sleep was monitored using wrist-actigraphy and the Dreem 2 headband, a wireless dry electrode consumer electroencephalography (EEG) device. Compared to wrist-actigraphy, the Dreem 2 shows minimal systemic skew for nights with data quality over 75% (as assigned by the Dreem algorithm). However, Bland Altman analysis shows significant random error with limits of agreement approximately +/- 70 minutes between actigraphy and the Dreem. Exploration of sleep metrics from the Dreem 2 during baseline short sleep versus sleep extension revealed an increase in total sleep time; increase in all recorded sleep stages; and no significant changes in sleep onset latency, wakefulness after sleep onset, or sleep efficiency. Although several limitations of producing high quality data were identified, the Dreem 2 headband shows promise as a home environment sleep research device. With an improvement in data quality, the Dreem headband, or another wireless consumer sleep device, has the potential to help advance the sleep field in ways that were previously inaccessible with clinical PSG.
An Epidemic Model for Multi-Intervention Outbreaks
Authors: Schaber Kathryn L. , Kumar Sagar , Lubwama Baker , Desai Angel , Majumder Maimuna S. 
Published: June 2023

AbstractModeling is an important tool to utilize at the beginning of an infectious disease outbreak, as it allows estimation of parameters—such as the basic reproduction number, R0—that can be used to postulate how the outbreak may continue to spread. However, there exist many challenges that need to be accounted for, such as an unknown first case date, retrospective reporting of ‘probable’ cases, changing dynamics between case count and death count trends, and the implementation of multiple control efforts and their delayed or diminished effects. Using the near-daily data provided from the recent outbreak of Sudan ebolavirus in Uganda as a case study, we create a model and present a framework aimed at overcoming these aforementioned challenges. The impact of each challenge is examined by comparing model estimates and fits throughout our framework. Indeed, we found that allowing for multiple fatality rates over the course of an outbreak generally resulted in better fitting models. On the other hand, not knowing the start date of an outbreak appeared to have large and non-uniform effects on parameter estimates, particularly at the beginning stages of an outbreak. While models that did not account for the decaying effect of interventions on transmission underestimated R0, all decay models run on the full dataset yielded precise R0estimates, demonstrating the robustness of R0as a measure of disease spread when examining data from the entire outbreak.
Encoding manual dexterity through modulation of intrinsic alpha band connectivity
Authors: Maddaluno O. , Della Penna S. , Pizzuti A. , Spezialetti M. , Corbetta M. , de Pasquale F. , Betti V. 
Published: June 2023

AbstractUsing hands proficiently implies consolidated motor skills, yet malleable to task demands. How the brain realizes this balance between stability and flexibility is unknown. At rest, in absence of overt input or behavior, the communication within the brain may represent a neuralpriorof stored memories. This magnetoencephalography study addresses how the modulation of such stable connectivity, induced by motor tasks, relates to proficient behavior. To this aim, we estimated functional connectivity from 51 participants of the Human Connectome Project during rest and finger tapping in alpha and beta bands. We identified two groups of participants characterized by opposite patterns of connectivity strength and topology.High and low performersshowed distributed decreases and increases of connectivity, respectively. However, while dexterous individuals also show modulations of the motor network,low performersexhibited a stability of such connections. Furthermore, in dexterous individuals, an increased segregation was observed through an increment of network modularity and decrease of nodal centrality. Instead,low performersshow a dysfunctional increased integration. Our findings reveal that the balance between stability and flexibility is not fixed; rather it constrains proficient behavior.
Neural representation dynamics reveal computational principles of cognitive task learning
Authors: Mill Ravi D. , Cole Michael W. 
Published: June 2023

AbstractDuring cognitive task learning, neural representations must be rapidly constructed for novel task performance, then optimized for robust practiced task performance. How the geometry of neural representations changes to enable this transition from novel to practiced performance remains unknown. We hypothesized that practice involves a shift from compositional representations (task-general activity patterns that can be flexibly reused across tasks) to conjunctive representations (task-specific activity patterns specialized for the current task). Functional MRI during learning of multiple complex tasks substantiated this dynamic shift from compositional to conjunctive representations, which was associated with reduced cross-task interference (via pattern separation) and behavioral improvement. Further, we found that conjunctions originated in subcortex (hippocampus and cerebellum) and slowly spread to cortex, extending multiple memory systems theories to encompass cognitive task learning. The strengthening of conjunctive representations hence serves as a computational signature of learning, reflecting cortical-subcortical dynamics that optimize task representations in the human brain.HighlightsLearning shifts multi-task representations from compositional to conjunctive formatsCortical conjunctions uniquely associate with improved behavior and pattern separationThese conjunctions strengthen over separated learning events and index switch costsSubcortical regions are critical for cross-region binding of task rule information
Uncovering Language Disparity of ChatGPT in Healthcare: Non-English Clinical Environment for Retinal Vascular Disease Classification
Authors: Liu Xiaocong , Wu Jiageng , Shao An , Shen Wenyue , Ye Panpan , Wang Yao , Ye Juan , Jin Kai , Yang Jie 
Published: June 2023

AbstractObjectiveTo evaluate the effectiveness and reasoning ability of ChatGPT in diagnosing retinal vascular diseases in the Chinese clinical environment.Materials and MethodsWe collected 1226 fundus fluorescein angiography reports and corresponding diagnosis written in Chinese, and tested ChatGPT with four prompting strategies (direct diagnosis or diagnosis with explanation and in Chinese or English).ResultsChatGPT using English prompt for direct diagnosis achieved the best performance, with F1-score of 80.05%, which was inferior to ophthalmologists (89.35%) but close to ophthalmologist interns (82.69%). Although ChatGPT can derive reasoning process with a low error rate, mistakes such as misinformation (1.96%), and hallucination (0.59%) still exist.Discussion and ConclusionsChatGPT can serve as a helpful medical assistant to provide diagnosis under non-English clinical environments, but there are still performance gaps, language disparity, and errors compared to professionals, which demonstrates the potential limitations and the desiration to continually explore more robust LLMs in ophthalmology practice.
Knowledge of COVID-19 prevention in Eastern Ethiopia
Authors: Dheresa Merga , Madewell Zachary J. , Muir Jonathan A. , Getachew Tamirat , Daraje Gamachis , Mengesha Gezahegn , Whitney Cynthia G. , Assefa Nega , Cunningham Solveig A. 
Published: June 2023

ABSTRACTObjectivesAs of May 2023, over 500,000 COVID-19 cases and over 7,500 deaths have been reported in Ethiopia. Understanding community members’ knowledge and perception of SARS-CoV-2 prevention is essential for directing public health interventions to reduce transmission and improve vaccination coverage. Here, we aimed to describe factors associated with knowledge of COVID-19 prevention among community residents in Eastern Ethiopia.MethodsWe conducted a cross-sectional survey among a random sample of 880 participants in a Health and Demographic Surveillance System in the Harari Region, Ethiopia, from August to September 2021. Principal components analysis was used to create a score representing knowledge of COVID-19 prevention. Quasi-Poisson regression was used to examine associations between demographic characteristics and knowledge of COVID-19 prevention. Our survey also included information regarding knowledge of community or government measures to prevent COVID-19, healthcare services for children under five, and healthcare services for pregnant women.ResultsThe most cited individual measures to reduce the risk of contracting COVID-19 were washing hands with soap (91.5%) and wearing a facemask (89.2%), whereas least mentioned were avoiding domestic and international travel (22.2%) and wearing medical gloves (20.3%). The most recognized community or government measures to prevent SARS-CoV-2 transmission were closure of schools and universities (77.0%), advice to avoid gatherings (75.2%), and advice to stay home (62.3%). Adjusted analyses demonstrated that knowledge of COVID-19 prevention was higher among participants from rural areas than urban areas, those aged ≥65 years (<25 years as reference), with secondary education (no formal education as reference), with monthly income of ≥2,001 Birr (0-1,200 as reference), and were farmers or domestic/subsistence workers or government employees (unemployed as reference). Knowledge was lower among households with ≥5 household members (1-2 as reference). Of households with children under five and pregnant women, 9.4% and 12.3% missed at least one medical care visit since mid-March 2020 consequent to the pandemic, respectively.ConclusionsPublic health interventions to reduce infectious disease transmission depend on perceptions of risk and knowledge. The survey found that most adults had good knowledge of methods for reducing risks of COVID-19, although knowledge differed between groups. A substantial number of respondents reported missing important healthcare visits. Understanding these factors may help Ethiopian authorities plan effective health education programs to control community and household transmission of SARS-CoV-2.