bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Cultural Evolution of Vaccine Hesitancy: Modeling the Interaction between Beliefs and Behaviors
Authors: Anderson Kerri-Ann , Creanza Nicole 
Published: May 2022

AbstractHealth perceptions and health-related behaviors can change at the population level as cultures evolve. In the last decade, despite the proven efficacy of vaccines, the developed world has seen a resurgence of vaccine-preventable diseases (VPDs) such as measles, pertussis, and polio. Vaccine hesitancy, an individual attitude influenced by historical, political, and socio-cultural forces, is believed to be a primary factor responsible for decreasing vaccine coverage, thereby increasing the risk and occurrence of VPD outbreaks. In recent years, mathematical models of disease dynamics have begun to incorporate aspects of human behavior, however they do not address how beliefs and motivations influence these health behaviors. Here, using a mathematical modeling framework, we explore the effects of cultural evolution on vaccine hesitancy and vaccination behavior. With this model, we shed light on facets of cultural evolution (vertical and oblique transmission, homophily, etc.) that promote the spread of vaccine hesitancy, ultimately affecting levels of vaccination coverage and VPD outbreak risk in a population. In addition, we present our model as a generalizable framework for exploring cultural evolution when humans’ beliefs influence, but do not strictly dictate, their behaviors. This model offers a means of exploring how parents’ potentially conflicting beliefs and cultural traits could affect their children’s health and fitness. We show that vaccine confidence and vaccine-conferred benefits can both be driving forces of vaccine coverage. We also demonstrate that an assortative preference among vaccine-hesitant individuals can lead to increased vaccine hesitancy and lower vaccine coverage.
SHIVIR - An Agent-Based Model to assess the transmission of COVID-19 in India
Authors: Narassima M.S. , John Denny , Anbuudayasankar S.P. , Jammy Guru Rajesh , Pant Rashmi , Choudhury Lincoln 
Published: May 2022

AbstractBackgroundCOVID-19 has tormented the global health and economy like no other event in the recent past. Researchers and policymakers have been working strenuously to end the pandemic completely.Methodology/Principal FindingsInfectious disease dynamics could be well-explained at an individual level with established contact networks and disease models that represent the behaviour of the infection. Hence, an Agent-Based Model, SHIVIR (Susceptible, Infected, Admitted, ICU, Ventilator, Recovered, Immune) that can assess the transmission dynamics of COVID-19 and the effects of Non-Pharmaceutical Interventions (NPI) was developed. Two models were developed using to test the synthetic populations of Rangareddy, a district in Telangana state, and the state itself respectively. NPI such as lockdowns, masks, and social distancing along with the effect of post-recovery immunity were tested across scenarios.The actual and forecast curves were plotted till the unlock phase began in India. The Mean Absolute Percentage Error of scenario MD100I180 was 6.41 percent while those of 3 other scenarios were around 10 percent each. Since the model anticipated lifting of lockdowns that would increase the contact rate proportionately, the forecasts exceeded the actual estimates. Some possible reasons for the difference are discussed.ConclusionsModels like SHIVIR that employ a bottom-up Agent-Based Modelling are more suitable to investigate various aspects of infectious diseases owing to their ability to hold details of each individual in the population. Also, the scalability and reproducibility of the model allow modifications to variables, disease model, agent attributes, etc. to provide localized estimates across different places.Author SummaryThe world has witnessed several infectious disease outbreaks from time to time. COVID-19 is one such event that tormented the life of mankind. Healthcare practitioners, policymakers, and governments struggled enormously to handle the influx of infections and devise suitable interventions. Agent-Based Models that use the population data could cater to these requirements better. Hence, we developed a disease model that represents various states acquired by COVID-19 infected individuals. The contact network among the individuals in the population was defined based on which the simulation progresses. The effect of various Non-Pharmaceutical Interventions such as lockdowns, the use of masks and social distancing along with post-recovery immunity were enacted considering two case studies viz. population of Rangareddy district and Telangana state. The capability of these models to adapt to different input data fields and types make them handy to be tailored based on available inputs and desired outputs. Simulating them using local population data would fetch useful estimates for policymakers.
Association of LGBTQ+ Affirming Care With Chronic Disease and Preventive Care Outcomes
Authors: McKay Tara , Tran Nathaniel M. , Barbee Harry , Min Judy K. 
Published: May 2022

IntroductionExperiences of discrimination and bias in health care contribute to health disparities for LGBTQ+ and other minority populations. To avoid discrimination, many LGBTQ+ people go to great lengths to find healthcare providers who they trust and are knowledgeable about their health needs. This study examines whether access to an LGBTQ+ affirming provider may improve health outcomes for LGBTQ+ populations across a range of preventive health and chronic disease management outcomes.MethodsThis cross-sectional study uses Poisson regression models to examine original survey data (n=1,120) from Wave 1 of the Vanderbilt University Social Networks, Aging, and Policy Study (VUSNAPS), a panel study examining older (50□76 years) LGBTQ+ adults’ health and aging, collected between April 2020 and September 2021.ResultsOverall, access to an LGBTQ+ affirming provider is associated with greater uptake of preventive health screenings and improved management of mental health conditions among older LGBTQ+ adults. Compared to participants reporting a usual source of care that is not affirming, participants with an LGBTQ+ affirming provider are more likely to have ever and recently received several types of preventive care, including past year provider visit, flu shot, colorectal cancer screening, and HIV test. Access to an LGBTQ+ affirming provider is also associated with better management of mental health conditions.ConclusionsInclusive care is essential for reducing health disparities among LGBTQ+ populations. Health systems can reduce disparities by expanding education opportunities for providers regarding LGBTQ+ medicine, adopting nondiscrimination policies for LGBTQ+ patients and employees, and ensuring LGBTQ+ care is included in health insurance coverage.
Radiographically Successful Periacetabular Osteotomy Does Not Achieve Optimal Contact Mechanics in Dysplastic Hips
Authors: Aitken Holly D. , Miller Aspen , Rivas Dominic J.L. , Tatum Marcus , Westermann Robert W. , Willey Michael C. , Goetz Jessica E. 
Published: May 2022

ABSTRACTIntroductionOptimal correction of hip dysplasia deformity with periacetabular osteotomy (PAO) that minimizes elevated contact stresses may reduce osteoarthritis (OA) development.Questions/PurposesWe used a computational approach based on discrete element analysis (DEA) to determine (1) if computational optimization can identify patient-specific acetabular corrections that optimize joint contact mechanics, (2) whether a strictly mechanically optimal correction is clinically feasible, and (3) whether the contact mechanics of optimal corrections differ from those of surgically achieved corrections.MethodsPreoperative and postoperative hip models were created from CT scans of a retrospective cohort (n=20) who underwent PAO to treat hip dysplasia. A digitally extracted acetabular fragment was computationally rotated in two-degree increments of lateral and anterior coverage to simulate candidate PAO reorientations. DEA-computed contact stress for each candidate reorientation model was used to select a purely mechanically optimal reorientation that minimized chronic contact stress exposures above damaging thresholds and a clinically optimal reorientation that balanced reducing chronic exposures with achieving clinically realistic acetabular orientations. Radiographic coverage, contact area, peak/mean contact stress, and peak/mean cumulative exposure were compared between preoperative, mechanically optimal, clinically optimal, and surgically achieved acetabular orientations.ResultsComputationally optimal reorientations had significantly (p<0.001) more lateral and anterior coverage than surgically achieved PAO corrections. The mechanically/clinically optimal reorientations also had significantly more contact area (p<0.001/p=0.001) and significantly lower peak contact stress (p<0.001/p<0.001), mean contact stress (p<0.001/p=0.001), peak chronic exposure (p=0.001/p=0.003), and mean chronic exposure (p<0.001/p=0.001) than the surgically achieved corrections.ConclusionsThis computational approach identified patient-specific mechanically optimal and clinically optimal acetabular reorientations. Surgically achieved reorientations did not reduce contact stress exposure to the extent achieved with computed optimal reorientations. However, optimal orientations identified for many patients risk secondary femoroacetabular impingement. Identifying patient-specific corrections that balance optimizing mechanics with clinical reality is necessary to reduce the risk of OA progression after PAO.
Real world external validation of metabolic gestational age assessment in Kenya
Authors: Hawken Steven , Ward Victoria , Bota A. Brianne , Lamoureux Monica , Ducharme Robin , Wilson Lindsay A. , Otieno Nancy , Munga Stephen , Nyawanda Bryan O. , Atito Raphael , Chakraborty Pranesh , Darmstadt Gary L. , Wilson Kumanan 
Published: May 2022

AbstractUsing data from Ontario Canada, we previously developed machine learning-based algorithms incorporating newborn screening metabolites to estimate gestational age (GA). The objective of this study was to evaluate the use of these algorithms in a population of infants born in Siaya county, Kenya.Cord and heel prick samples were collected from newborns in Kenya and metabolic analysis was carried out by Newborn Screening Ontario in Ottawa, Canada. Postnatal GA estimation models were developed with data from Ontario with multivariable linear regression using ELASTIC NET regularization. Model performance was evaluated by applying the models to the data collected from Kenya and comparing model-derived estimates of GA to reference estimates from early pregnancy ultrasound.Heel prick samples were collected from 1,039 newborns from Kenya. Of these, 8.9% were born preterm and 8.5% were small for GA. Cord blood samples were also collected from 1,012 newborns. In data from heel prick samples, our best-performing model estimated GA within 9.5 days overall of reference GA [mean absolute error (MAE) 1.35 (95% CI 1.27, 1.43)]. In preterm infants and those small for GA, MAE was 2.62 (2.28, 2.99) and 1.81 (1.57, 2.07) weeks, respectively. In data from cord blood, model accuracy slightly decreased overall (MAE 1.44 (95% CI 1.36, 1.53)). Accuracy was not impacted by maternal HIV status and improved when the dating ultrasound occurred between 9 and 13 weeks of gestation, in both heel prick and cord blood data (overall MAE 1.04 (95% CI 0.87, 1.22) and 1.08 (95% CI 0.90, 1.27), respectively).Compared to internal validation performance using Ontario data and to our previously published external validations, model performance was diminished in the Kenya cohort, suggesting that reference ultrasound timing is an important factor in model performance. Our study highlights the challenges in reliably estimating GA in low resource settings, even those with access to dating ultrasound, given that the timing of dating ultrasound is critical to develop algorithms for accurate estimation of GA based on metabolic analysis of blood obtained at birth.
Protection against Omicron conferred by mRNA primary vaccine series, boosters, and prior infection
Authors: Chin Elizabeth T. , Leidner David , Lamson Lauren , Lucas Kimberley , Studdert David M. , Goldhaber-Fiebert Jeremy D. , Andrews Jason R. , Salomon Joshua A. 
Published: May 2022

ABSTRACTBackgroundPrisons and jails are high-risk settings for Covid-19 transmission, morbidity, and mortality. We evaluate protection conferred by prior infection and vaccination against the SARS-CoV-2 Omicron variant within the California state prison system.MethodsWe employed a test-negative design to match resident and staff cases during the Omicron wave (December 24, 2021—April 14, 2022) to controls according to a case’s test-week as well as demographic, clinical, and carceral characteristics. We estimated protection against infection using conditional logistic regression, with exposure status defined by vaccination, stratified by number of mRNA doses received, and prior infection, stratified by periods before or during Delta variant predominance.ResultsWe matched 15,783 resident and 8,539 staff cases to 180,169 resident and 90,409 staff controls. Among cases, 29.7% and 2.2% were infected before or during the emergence of the Delta variant, respectively; 30.6% and 36.3% were vaccinated with two or three doses, respectively. Estimated protection from Omicron infection for two and three doses were 14.9% (95% Confidence Interval [CI], 12.3—19.7%) and 43.2% (42.2—47.4%) for those without known prior infections, 47.8% (95% CI, 46.6—52.8%) and 61.3% (95% CI, 60.7—64.8%) for those infected before the emergence of Delta, and 73.1% (95% CI, 69.8—80.1%) and 86.8% (95% CI, 82.1—92.7) for those infected during the period of Delta predominance.ConclusionA third mRNA dose provided significant, additional protection over two doses, including among individuals with prior infection. Our findings suggest that vaccination should remain a priority—even in settings with high levels of transmission and prior infection.
Epidemiology of adverse events attributed to airway management in pediatric anesthesia: A protocol for a Japan Pediatric Difficult Airway in Anesthesia study (J-PEDIA)
Authors: Kojima Taiki , Yamauchi Yusuke , Watanabe Fumio , Ichiyanagi Shogo , Kobayashi Yasuma , Kaiho Yu , Kasuya Shugo , Urayama Kevin Y. , Kuratani Norifumi , Suzuki Yasuyuki 
Published: May 2022

AbstractIntroductionFailure to secure an airway during general anesthesia is a major cause of adverse events (AEs) in children. The safety of peddiatric anesthesia may be improved by identifying the incidence of AEs and their attributed risk factors. However, previous large cohort studies have not been appropriately designed to explore such aspects. Thus, this study aims to deternine the incidence of AEs and the risk factors attributed to airway management under general anesthesia in children.Methods and designThis prospective, multi-center, registry-based, observational study will be conducted in four tertiary care hospitals in Japan from June 2022 to May 2025. Children younger than 18 years of age undergoing surgical and/or diagnostic test procedures under general anesthesia or sedation by anesthesiologists will be enrolled in this study. Data on patient characteristics, discipline of anesthesia providers, and methodology of airway management will be collected through a standardized verification system under monitoring by institutional research leaders among the recruited institutions to minimize the loss of collected data. The primary outcome and exposure are AEs and presence of difficult airway features with potential confounders, which are related to the failure to secure the airway, and the variability in the anesthesia providers’ levels, adjusted using hierarchical multivariable regression models with mixed effects.DiscussionThis study will determine the incidence of AEs and the risk factors related to airway management under general anesthesia in children.Trial registrationThis study is registered as a prospective observational study in the University hospital Medical Information Network (UMIN) (registration number UMIN000047351, April 1, 2022).
Is family social exclusion associated with child psychomotor and social development delay in southeastern Brazil?
Authors: de Oliveira Clariana Vitória Ramos , Nery Teixeira Palombo Cláudia , Jeong Joshua , Solís Cordero Katherine Maria , Fujimori Elizabeth 
Published: May 2022

AbstractThe early years of life are a crucial period for shaping child development. Children from socially excluded families may have less opportunity to attain their full development. The objective was to identify if family social exclusion is associated with child psychomotor and social development delay in Southeastern Brazil. A cross-sectional study was conducted using data from a sample of 348 children under three years. We measured psychomotor and social development delays. An index was used to evaluate social exclusion. The prevalence of child psychomotor and social developmental delay was 27.6% and 17.2%, respectively. Children in the most social excluded group were more likely to have delayed psychomotor development (OR = 3.4; 95% CI = 1.14; 10.55) and social developmental delay (OR = 3.9; 95% CI = 1.05; 9.02) than children in the least social excluded group. The results confirm the association between family social exclusion and child development delay.
Enhanced Direct Joint Attenuation and Scatter Correction of Whole-Body PET Images via Context-Aware Deep Networks
Authors: Izadi Saeed , Shiri Isaac , Uribe Carlos F. , Geramifar Parham , Zaidi Habib , Rahmim Arman , Hamarneh Ghassan 
Published: May 2022

ABSTRACTIn positron emission tomography (PET), attenuation and scatter corrections is necessary steps towards accurate quantitative reconstruction of the radiopharmaceutical distribution. Inspired by recent advances in deep learning, many algorithms based on convolutional neural networks have been proposed for automatic attenuation and scatter correction, enabling applications to CT-less or MR-less PET scanners to improve performance in the presence of CT-related artifacts. A known characteristic of PET imaging is to have varying tracer uptakes for various patients and/or anatomical regions. However, existing deep learning-based algorithms utilize a fixed model across different subjects and/or anatomical regions during inference, which could result in spurious outputs. In this work, we present a novel deep learning-based framework for direct reconstruction of attenuation and scatter corrected PET from non-attenuation-corrected images in absence of structural information. To deal with inter-subject and intra-subject uptake variations in PET imaging, we propose a novel model to perform subject- and region-specific filtering through modulating the convolution kernels in accordance to the contextual coherency within the neighboring slices. This way, the context-aware convolution can guide the composition of intermediate features in favor of regressing input-conditioned and/or region-specific tracer uptakes. We also utilize a large cohort of 910 whole-body studies for training and evaluation purposes, which is more than one order of magnitude larger than previous works. In our experimental studies, qualitative assessments showed that our proposed CT-free method is capable of producing corrected PET images that accurately resemble ground truth images corrected with the aid of CT scans. For quantitative assessments, we evaluated our proposed method over 112 held-out subjects and achieved absolute relative error of 14.30 ± 3.88% and relative error of − 2.11% ± 2.73% in whole-body.
CSR-1 RNA interference pathway restricts holocentromere protein CENP-A/HCP-3 localization in Caenorhabditis elegans
Authors: Yu Wong Charmaine Yan , Yee Yuen Karen Wing 
Published: May 2022

AbstractCSR-1 is an argonaute of a RNA interference pathway that is important for chromosome segregation in C. elegans. Live-cell imaging revealed that CSR-1 depletion slows down spindle pole separation in a kinetochore-dependent manner. In csr-1(RNAi) embryos, the kinetochores may be misattached to the microtubules and chromosome segregation is disrupted. On the holocentromeres, there are increased levels of some kinetochore proteins, including the centromeric epigenetic mark, CENP-A or HCP-3. Without affecting HCP-3 expression level, HCP-3 density is higher on stretched chromatin fibers in CSR-1-depleted embryos. The increased HCP-3 deposition on chromatin after CSR-1 depletion is at least partially independent of HCP-3 loading factors, KNL-2 and LIN-53, suggesting a non-classical, improper HCP-3 loading pathway. Negative regulation of HCP-3 holocentromere loading by CSR-1 required its slicer activity and the b isoform. CSR-1 acts as a HCP-3 repressor for its chromosomal occupancy, shedding light on the role of RNAi pathways in specifying the localization of centromere proteins.
Bridging between mouse and human enhancer-promoter long-range interactions in neural stem cells, to understand enhancer function in neurodevelopmental disease
Authors: D’Aurizio Romina , Catona Orazio , Pitasi Mattia , Li Yang Eric , Ren Bing , Nicolis Silvia K. 
Published: May 2022

Non-coding variation in complex human disease has been well established by genome-wide association studies, and it is thought to involve regulatory elements, such as enhancers, whose variation affects the expression of the gene responsible for the disease. The regulatory elements often lie far from the gene they regulate, or within introns of genes differing from the regulated gene, making it difficult to identify the gene whose function is affected by a given enhancer variation.Enhancers are connected to their target gene promoters via long-range physical interactions (loops). In our study, we re-mapped, onto the human genome, more than 10,000 enhancers connected to promoters via long-range interactions, that we had previously identified in mouse brain-derived neural stem cells by RNApolII-ChIA-PET analysis, coupled to ChIP-seq mapping of DNA/chromatin regions carrying epigenetic enhancer marks. These interactions are thought to be functionally relevant. We discovered, in the human genome, thousands of DNA regions syntenic with the interacting mouse DNA regions (enhancers+connected promoters). We further annotated these human regions regarding their overlap with sequence variants (single nucleotide polymorphisms, SNPs; copy number variants, CNVs), that were previously associated with neurodevelopmental disease in human. We document various cases in which the genetic variant, associated in human to neurodevelopmental disease, affects an enhancer involved in long-range interactions: SNPs, previously identified by genome-wide association studies to be associated with schizophrenia, bipolar disorder, and intelligence, are located within our human syntenic enhancers, and alter transcription factors recognition sites. Similarly, CNVs associated to autism spectrum disease and other neurodevelopmental disorders overlap with our human syntenic enhancers. Some of these enhancers are connected (in mouse) to homologs of genes already associated to the human disease, strengthening the hypothesis that the gene is indeed involved in the disease. Other enhancers are connected to genes not previously associated with the disease, pointing to their possible pathogenetic involvement.Our observations provide a resource for further exploration of neural disease, in parallel with the now widespread genome-wide identification of DNA variants in patients with neural disease.