bluuebunny/crossref_metadata_2025_split huggingface dataset:
Contextual modulation of primary visual cortex by temporal predictability during motion extrapolation
Authors: Agostino Camila Silveira , Hinrichs Herman , Noesselt Toemme 
Published: December 2023

ABSTRACTPredicting future events is a fundamental cognitive ability which often depends on the volatility of the environment. Previous studies on apparent motion reported that when the brain is confronted with low levels of predictability, activity in low-level sensory areas is increased, including primary visual cortex. However, other studies on temporal predictability reported opposite effects potentially due to the influence of attention. It remains unclear, however, how temporal predictability modulates brain responses in a more ecologically valid real motion paradigm. Our study investigated whether motion extrapolation in high and low predictable contexts would differently modulate fMRI-responses in subject-specific primary visual cortex during visible and partially occluded stimulation. To this end, participants performed a modified version of the interception paradigm in visible and occluded phases, in which they observed a stimulus moving horizontally, then vertically at two different velocities. They were instructed to press when and where the stimulus would reach a given point-of-contact. In high predictable context, the velocity was identical during horizontal and vertical (occluded) movement; whereas, in low predictable context, the velocity could change during the vertical trajectory. MVPA results revealed accuracies above chance for all classification analyses carried out with low and highly predictable context data. Moreover, trial-history analysis showed that a change in trial type (constant velocity after change in velocity and vice versa) increased BOLD-responses in V1. This pattern of results suggests motion extrapolation can enhance activity in primary visual cortex, regardless of trial-specific predictability, but it is affected by recent trial history.Highlights* Ignoring trial history high and low temporal predictability similarly enhance response in V1* In recent trial-history analysis, low temporal predictability enhanced responses in V1 compared to high temporal predictability* Shared regions inside primary visual cortex encode visible and partially occluded information
Sensitivity, specificity and avoidable workload of using a large language models for title and abstract screening in systematic reviews and meta-analyses
Authors: Tran Viet-Thi , Gartlehner Gerald , Yaacoub Sally , Boutron Isabelle , Schwingshackl Lukas , Stadelmaier Julia , Sommer Isolde , Aboulayeh Farzaneh , Afach Sivem , Meerpohl Joerg , Ravaud Philippe 
Published: December 2023

AbstractImportanceSystematic reviews are time-consuming and are still performed predominately manually by researchers despite the exponential growth of scientific literature.ObjectiveTo investigate the sensitivity, specificity and estimate the avoidable workload when using an AI-based large language model (LLM) (Generative Pre-trained Transformer [GPT] version 3.5-Turbo from OpenAI) to perform title and abstract screening in systematic reviews.Data SourcesUnannotated bibliographic databases from five systematic reviews conducted by researchers from Cochrane Austria, Germany and France, all published after January 2022 and hence not in the training data set from GPT 3.5-Turbo.DesignWe developed a set of prompts for GPT models aimed at mimicking the process of title and abstract screening by human researchers. We compared recommendations from LLM to rule out citations based on title and abstract with decisions from authors, with a systematic reappraisal of all discrepancies between LLM and their original decisions. We used bivariate models for meta-analyses of diagnostic accuracy to estimate pooled estimates of sensitivity and specificity. We performed a simulation to assess the avoidable workload from limiting human screening on title and abstract to citations which were not “ruled out” by the LLM in a random sample of 100 systematic reviews published between 01/07/2022 and 31/12/2022. We extrapolated estimates of avoidable workload for health-related systematic reviews assessing therapeutic interventions in humans published per year.ResultsPerformance of GPT models was tested across 22,666 citations. Pooled estimates of sensitivity and specificity were 97.1% (95%CI 89.6% to 99.2%) and 37.7%, (95%CI 18.4% to 61.9%), respectively. In 2022, we estimated the workload of title and abstract screening for systematic reviews to range from 211,013 to 422,025 person-hours. Limiting human screening to citations which were not “ruled out” by GPT models could reduce workload by 65% and save up from 106,268 to 276,053-person work hours (i.e.,66 to 172-person years of work), every year.Conclusions and RelevanceAI systems based on large language models provide highly sensitive and moderately specific recommendations to rule out citations during title and abstract screening in systematic reviews. Their use to “triage” citations before human assessment could reduce the workload of evidence synthesis.
Single voxel autocorrelation reflects hippocampal function in temporal lobe epilepsy
Authors: Bouffard Nichole R. , Audrain Sam , Golestani Ali M. , Barense Morgan D. , Moscovitch Morris , McAndrews Mary Pat 
Published: December 2023

AbstractWe have previously shown that analyses of autocorrelation of BOLD signal applied to single voxels in healthy controls can identify gradients of temporal dynamics throughout the hippocampal long-axis that are related to behavior. A question that remains is how changes in functional and structural integrity in the brain affect single voxel autocorrelation. In this study we investigate how hippocampal autocorrelation is affected by structural and functional hippocampal dysfunction by investigating a population of patients with unilateral temporal lobe epilepsy (TLE). Many patients with TLE have mesial temporal sclerosis (MTS), characterized by scarring and neuronal loss particularly in the anterior hippocampus. Here we compared patients with left and right TLE, some with and without MTS, to healthy controls. We applied our single voxel autocorrelation method and data-driven clustering approach to segment the hippocampus based on the autocorrelation. We found that patients with left TLE had slower signal dynamics (i.e., higher autocorrelation) compared to controls, particularly in the anterior-medial portion of the hippocampus. This was true for both the epileptogenic and non-epileptogenic hemispheres. We also evaluated the extent of cluster preservation (i.e., spatial overlap with controls) of patient autocorrelation clusters and the relationship to verbal and visuospatial memory. We found that patients with greater cluster preservation in the anterior-medial hippocampus had better memory performance. Surprisingly, we did not find any effect of MTS on single voxel autocorrelation, despite the structural changes associated with the condition. These results suggest that single voxel autocorrelation may be related to functional, rather than structural, integrity.
Assessing the usability of the new automated medication dispensation device for patients and the adherence dashboard for real-time medication monitoring for healthcare providers: a study protocol
Authors: Patel Tejal , Laeer Christoph , Darabi Hamed , Lachance Maxime , Anawati Michelle , Chomienne Marie-Hélène 
Published: December 2023

AbstractBackgroundNon-adherence to prescribed medication regimens can lead to suboptimal control of chronic health conditions and increased hospitalizations. Older adults may find it particularly challenging to self-manage medications due to physical and cognitive limitations resulting in medication non-adherence. While automated medication dispensing technologies may offer a solution for medication self-management among older adults, these technologies must demonstrate usability before effectiveness can be investigated and products made available for widespread use.ObjectivesThis study will aim to measure usability, workload, and unassisted task completion rates of an automated medication dispenser and medication adherence dashboard on the Medipense portal with older adults and their clinicians, respectively.MethodsThis study is designed as convergent parallel mixed methods observational study with older adults and their clinicians. Usability will be examined with the use the System Usability Scale while NASA-TLX will be utilized to assess the workload of both the device and the adherence monitoring platform. Cognitive walkthrough will be utilized prior to usability testing to identify series of steps required to use the automated dispenser and adherence dashboard. The study will assess the unassisted task completion rates to successfully operate the device. Semi-structured interviews with both types of participants will provide qualitative data with which to comprehensively gauge user experience with the automated dispenser.ResultsThe results of this study will allow us to examine usability of both the automated medication dispensing system and the adherence monitoring dashboard from older adult and heath care provider perspectives. The results of this study will highlight and address the challenges with usability that older adults and healthcare providers may face with this device and dashboard.Conclusions:The results of this study will be used to optimize the usability of both the automated medication dispenser and the adherence dashboard.
Multidimensional evaluation of the early emergence of executive function and development in Bangladeshi children using nutritional and psychosocial intervention: A randomized controlled trial protocol
Authors: Shama T. , O’Sullivan J.M. , Rahman N. , Kakon S.H. , Tofail F. , Hossain M.I. , Zeilani M. , Haque R. , Gluckman P. , Forrester T. , Nelson C.A. 
Published: December 2023

AbstractIntroductionReversing malnutrition-induced impairment of cognition and emotional regulation is a critical global gap. We hypothesize that brain-targeted micronutrient supplemented nutritional rehabilitation in children with moderate acute malnutrition, followed by 2 years micronutrient supplementation will impact on the cognition and emotion regulation of these children.MethodsThe primary outcome of this prospective, randomized controlled trial is to study the development of executive functions (EFs) and emotion regulation (ER) in this cohort.Moderate acute malnourished (MAM; WLZ/WHZ <-2 and ≥-3 z-score, and/or 11.5 cm ≤ MUAC < 12.5cm; n=140)children aged around one year (11m-13m) in Mirpur, Dhaka, Bangladesh will be randomized (1:1) to receive either locally produced Ready to Use Supplementary Food (RUSF) or Enhanced Ready to Use Supplementary Food (E-RUSF) until anthropometric recovery (WLZ/WHZ > -1SD), or for 3 months after enrollment (whichever is earlier). The randomized MAMs groups will be given either Small Quantity Lipid Based Nutrient Supplement (SQLNS) or Enhanced Small Quantity Lipid Based Nutrient Supplement (E-SQLNS), respectively until the end of the 2-year follow up period. Standard psychosocial stimulation will be provided to the MAMs intervention groups. Biological samples will be collected, anthropometric and neurocognitive assessments will be performed at 2 (22m-26m) and 3 (34m-38m) years of age.Two control groups will be recruited: 1), non-malnourished one-year (11m-13m) old children (WLZ/WHZ score>-1SD; n=70); and 2) three –year (34m-38m) old children (n=70) with untreated MAM (WHZ <-2 and ≥-3 z-score, and/or 11.5≤MUAC<12.5 cm). The 3-year-old MAM reference group will be assessed once and provided with 2 months of nutritional rehabilitation support (RUSF Nutriset’s Plumpy’SupTM).Ethics and disseminationThe study protocol has been reviewed and approved by all the relevant ethical review boards at each research site (icddr,b Bangladesh; University of the West Indies, Kingston Jamaica; and University of Auckland, New Zealand). The results will be disseminated through peer-reviewed publications and national and international scientific conferences.Protocol version 1 (1/11/2022)Trial registration numberNCT05629624. Registered on November 29, 2022.
Predictors of advanced-stage presentation among breast and cervical cancer patients in Ethiopia
Authors: Shewarega Birtukan , Getachew Sefonias , Assefa Nigussie , Yesufe Abdu Adem , Trabizsch Josephin , Dandena Yonas , Gashawubeza Biruck , Addissie Adamu , Kantelhardt Eva Johanna , Gizaw Muluken 
Published: December 2023

AbstractBreast and cervical cancers are the most common causes of cancer incidence and mortality in women in Africa. Women with breast and cervical cancers in Sub-Saharan Africa (SSA) are frequently diagnosed at advanced stages. Delays in health seeking, diagnosis and treatment are contributing factors to high mortality in Ethiopia. This study aimed to assess predictors of advanced stage presentation among breast and cervical cancer patients attending public hospitals in Addis Ababa, Ethiopia. A cross-sectional study was conducted with a total of 418 patients at Tikur Anbessa specialized hospital and Saint Pauls’ Hospital Millennium Medical College from October to November 2021. Stages III and IV were considered advanced stages. Data were collected by reviewing medical records and in face-to-face interviews with a structured questionnaire. Bivariate and multivariate analyses were performed to examine the association between independent and outcome variables. A total of 269 patients with breast cancer and 149 patients with cervical cancer were included in the study, and the mean age was 44 years (SD = 10.9 years) and 50 years (SD = 11.2) years, respectively. About 66.9% of breast cancers and 71.1% of cervical cancers were diagnosed at an advanced disease stage. Rural residence (AOR = 2.041, 95% CI: 1.108–3.758), indirect referral (AOR = 3.8, 95% CI: 1.485–9.946), financial difficulty (AOR = 10, 95% CI: 1.859–56.495) and no prior advise/awareness about screening (AOR = 4.029 95%CI: 1.658–10.102) were independent predictors of advanced-stage presentation. This study revealed a high prevalence of advanced-stage breast and cervical cancer diagnosis in Ethiopia, similar to data collected 10 years ago, despite the introduction of a cancer control plan in 2015. For better implementation, interventions should aim to improve referral pathways, adapt screening and early detection services and increase cancer awareness at the community level in a culturally accepted way.
Retrospective analysis of Covid-19 hospitalization modelling scenarios which guided policy response in France
Authors: Starck Thomas , Langevin Maxime 
Published: December 2023

AbstractDuring the COVID-19 pandemic, epidemiological modelling has played a key role in public debate and policy making for anticipating the epidemic trajectory, as well as proposing and evaluating non-pharmaceuticals interventions. Despite its importance, evaluations of models’ ability to accurately represent the evolution of the disease remain scarce. Robust and systematic evaluation is needed to assess models. We investigate the following research question : were the COVID-19 scenarios proposed by modellers during the pandemic to policy-makers relevant for decision making ? To answer this, we conduct a retrospective assessment of modelling reports which guided policy response in France in 2020-2022. After systematically verifying the scenarios hypotheses (e.g., exclusion of no-lockdown scenarios when a lockdown was effectively in place), we find that out of 10 reports, reality was below the best-case scenario in 6 reports; within the best-case / worst case scenarios range in 3 reports; above the worst-case scenario in 1 report. Best-case scenarios were the closest to reality, but often came from report with a large span between best-case and worst-case scenarios beyond 2 weeks, precluding certainty about future outcomes at the time of publishing. Our results hint a systematic overestimation bias for these particular models used to anticipate epidemic evolution, which can be of importance if such models are used to contractually estimate the effectiveness of non pharmaceutical interventions. To our knowledge, this is the only national systematic retrospective assessment of COVID-19 pandemic scenarios assessing hospital burden; such an approach should be reproduced in other countries whenever possible.Graphical AbstractReality (black line) compared to prospective scenarios (colored lines) which informed policy during the COVID-19 pandemic in France for Intensive Care Units (top) and New Hospital Admissions (bottom). Colors indicate the error between reality and scenarios, expressed as a percentage of the 1st wave peak (horizontal dashed line).
Determinants of overweight and obesity among children between 5 to 11 years in Ecuador: a secondary analysis from the National Health Survey 2018
Authors: Tello Betzabé , Ocaña José , García-Zambrano Paúl , Enríque-Moreira Betsabé , Dueñas-Espín Iván 
Published: December 2023

AbstractBackgroundDuring the 1990s, global eating habits changed, affecting poorer and middle-income nations, as well as richer countries. This shift, known as the “obesity transition,” led to more people becoming overweight or obese worldwide. In Ecuador, this change is happening, and now, one in three children is affected by overweight or obesity (OW/OB). This study explores the links between social, economic, and demographic factors and childhood obesity in Ecuador, seeking to provide insights for shaping future health policies in response to this intricate shift.MethodsA cross-sectional study using 2018 National Health and Nutrition Survey data from Ecuador. Weighted percentages were computed, and odds ratios for OW/OB unadjusted and adjusted for each category of explanatory variables were estimated using multilevel multivariate logistic regression models.ResultsAmong 10,807 Ecuadorian school children aged 5 to 11, the prevalence of OW/OB was 36.0%. Males exhibited 1.26 times higher odds than females (95% CI: 1.20 to 1.33), and each additional year of age increased the odds by 1.10 times (95% CI: 1.09 to 1.10). Economic quintiles indicated increased odds (1.17 to 1.39) from the 2nd to 5th quintile (the richest) compared with the first quintile (the poorest). Larger household size slightly reduced odds of OW/OB (adjusted odds ratio [aOR]=0.93, 95% CI: 0.91 to 0.95), while regular physical activity decreased odds ([aOR]=0.79, 95% CI: 0.75 to 0.82). The consumption of school-provided meals showed a non-significant reduction (aOR: 0.93, 95% CI: 0.82 to 1.06). Children from families recognizing and using processed food labels had a higher likelihood of being overweight or obese (aOR=1.14, 95% CI: 1.02 to 1.26).ConclusionAge, male gender, and higher economic quintile increase OW/OB in Ecuadorian school children. Larger households and physical activity slightly decrease risks. Ecuador needs policies for healthy schools and homes, focusing on health, protection, and good eating habits.
High-Activity Enhancer Generation based on Feedback GAN with Domain Constraint and Curriculum Learning
Authors: Li Jiahao , Xiao Liwei , Luo Jiawei , Liu Xianliang , Chen Junjie 
Published: December 2023

AbstractEnhancers are important cis-regulatory elements, enhancing the transcription of target genes. De novo design of high-activity enhancers is one of long-standing goals in generated biology for both clinical purpose and artificial life, because of their vital roles on regulation of cell development, differentiation, and apoptosis. But designing the enhancers with specific properties remains challenging, primarily due to the unclear understanding of enhancer regulatory codes. Here, we propose an AI-driven enhancer design method, named Enhancer-GAN, to generate high-activity enhancer sequences. Enhancer-GAN is firstly pre-trained on a large enhancer dataset that contains both low-activity and high-activity enhancers, and then is optimized to generate high-activity enhancers with feedback-loop mechanism. Domain constraint and curriculum learning were introduced into Enhancer-GAN to alleviate the noise from feedback loop and accelerate the training convergence. Experimental results on benchmark datasets demonstrate that the activity of generated enhancers is significantly higher than ones in benchmark dataset. Besides, we find 10 new motifs from generated high-activity enhancers. These results demonstrate Enhancer-GAN is promising to generate and optimize bio-sequences with desired properties.
Single-cell measurement of microbial growth rate with Raman microspectroscopy
Authors: Caro Tristan A. , Kashyap Srishti , Brown George , Chen Claudia , Kopf Sebastian H. , Templeton Alexis S. 
Published: December 2023

AbstractRates of microbial activity and growth are fundamental to understanding environmental geochemistry and ecology. However, measuring the heterogeneity of microbial activity at the single-cell level, especially within complex populations and environmental matrices, remains a forefront challenge. Stable Isotope Probing (SIP) is a standard method for assessing microbial activity and involves measuring the incorporation of an isotopically labeled compound into microbial biomass. Here, we assess the utility of Raman microspectroscopy as a SIP technique, specifically focusing on the measurement of deuterium (2H), a tracer of microbial biomass production. We generate calibrations of microbial biomass2H values and find that Raman microspectroscopy reliably quantifies2H incorporation ranging between 0 and 40 at. %. Applying the results of this calibration to a SIP model, we explicitly parameterize the factors controlling microbial growth quantification, demonstrating how Raman-SIP can measure the growth of microorganisms with doubling times ranging from hours to years. Furthermore, we correlatively compare our Raman-derived measurements with those of nanoscale secondary ion mass spectrometry (nanoSIMS) to compare the relative strengths of nanoSIMS- and Raman-based SIP approaches. We find that Raman microspectroscopy is a robust, accessible methodology that can readily differentiate and quantify the growth of individual microbial cells in complex samples.ImportanceGrowth rate, the rate at which organisms grow and reproduce, is a key metric with which to evaluate microbial physiology and contributions to system-level processes. The heterogeneity of microbial growth across space, time, and populations is often difficult to capture with bulk-scale techniques. Single-cell methods hold promise for measuring the heterogeneity of microbial growth rates and responses to changing conditionsin situ, without the need for cultivation of microbial isolates. In this study, we evaluated the ability of Raman microspectroscopy, a non-destructive and rapid technique, to measure the assimilation of isotopically labeled water into individual microbial cells and thereby calculate their rates of growth. We explicitly parameterize the factors controlling the quantification of microbial growth rate and compare this technique to standard methods. The framework we report allows researchers to couple single-cell and aggregate rate measurements to functional or system-level properties, a forefront challenge in microbiology.