bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatial prediction of COVID-19 pandemic dynamics in the United States
Authors: Ak Cigdem , Chitsazan Alex D. , Gönen Mehmet , Etzioni Ruth , Grossberg Aaron J. 
Published: April 2022

AbstractBackgroundThe impact of COVID-19 across the United States has been heterogeneous, with some areas demonstrating more rapid spread and greater mortality than others. We used geographically-linked data to test the hypothesis that the risk for COVID-19 is spatially defined and sought to define which features are most closely associated with elevated COVID-19 spread and mortality.MethodsLeveraging geographically-restricted social, economic, political, and demographic information from U.S. counties, we developed a computational framework using structured Gaussian processing to predict county-level case and death counts during both the initial and the nationwide phases of the pandemic. After identifying the most predictive spatial features, we applied an unsupervised clustering algorithm, topic modelling, to identify groups of features that are most closely associated with COVID-19 spread.FindingsWe found that the inclusion of spatial features modeled case counts very well, with overall Pearson’s correlation coefficient (PCC) and R2of 0.96 and 0.84 during the initial phase and 0.95 and 0.87, respectively, during the nationwide phase. The most frequently selected features were associated with urbanicity and 2020 presidential vote margins. When trained using death counts, models revealed similar performance metrics, with the addition of aging metrics to those most frequently selected. Topic modeling showed that counties with similar socioeconomic and demographic features tended to group together, and some feature sets were associated with COVID-19 dynamics. Unsupervised clustering of counties based on these topics revealed groups of counties that experienced markedly different COVID-19 spread.InterpretationSpatial features explained most of the variability in COVID-19 dynamics between counties. Topic modeling can be used to group collinear features and identify counties with similar features in epidemiologic research.
Quickest Way to Less Headache Days: an operational research model and its implementation for Chronic Migraine
Authors: Lo Irene , Zhang Pengfei 
Published: April 2022

Structured AbstractBackgroundChoosing migraine prevention medications often involves trial and error. Operations research methodologies, however, allow us to derive a mathematically optimum way to conduct such trial and error processes.ObjectiveGiven probability of success (defined as 50% reduction in headache days) and adverse events as a function of time, we seek to develop and solve an operations research model, applicable to any arbitrary patient, minimizing time until discovery of an effective migraine prevention medication. We then seek to apply our model to real life data for chronic migraine prevention.MethodsWe develop a model as follows: Given a set of D many preventive medications, for drug i in D, we describe the likelihood of reaching 50% headache day reduction over the course of time, (ti,1 ≤ ti,2 ≤ …) by probability (pi,1 ≤ pi,2 ≤ …). We additionally assume a probability of adverse event(qi,1 ≤ qi,2 ≤ …). We then solve for a sequence of prescription trials that minimizes the expected time until an effective drug is identified.Once we identify the optimal sequence for our model, we estimate p, t and q for topiramate and OnabotulinumtoxinA based on the FORWARD study by Rothrock et al as well as erenumab data published by Barbanti et al. at IHC 2019.ResultsThe solution for our model is to order the drugs by probability of efficacy per unit time. When the efficacy of each drug i is known only for one period ti and there are no adverse effects, then the optimum sequence is to administer drug i for ti periods in decreasing order pi/ti. In general, the optimum sequence is to administer drug i for ti,k* periods in decreasing order of the Gittins index σi,k*Based on the above data, the optimum sequence of chronic migraine prevention medication is a trial of erenumab for 12 weeks, followed by a trial of OnabotulinumtoxinA for 32 weeks, followed by a trial of topiramate for 32 weeks.ConclusionWe propose an optimal sequence for preventive medication trial for patients with chronic migraine. Since our model makes limited assumptions on the characteristics of disease, it can be readily applied also to episodic migraine, given the appropriate data as input.Indeed, our model can be applied to other scenarios so long as probability of success/adverse event as a function of time can be estimated. As such, we believe our model may have implications beyond our sub-specialty.Trial RegistrationNot applicable.
Lymphoid Enhancer-Binding Factor 1 (LEF1) immunostaining as a surrogate of β-catenin (CTNNB1)mutations
Authors: Hewer Ekkehard , Fischer Pascal , Vassella Erik , Knabben Laura , Imboden Sara , Mueller Michael D. , Rau Tilman T. , Dettmer Matthias S. 
Published: April 2022

AbstractBackgroundActivating mutations affecting exon 3 of the β-catenin (CTNNB1) gene result in constitutive activation of WNT signaling and are a diagnostic hallmark of several tumor entities including desmoid-type fibromatosis. They also define clinically relevant tumor subtypes within certain entities such as endometrioid carcinoma. In diagnostics, β-catenin immunohistochemistry is widely used as a surrogate forCTNNB1mutations, but is often difficult to assess in practice, given that the characteristic nuclear translocation may be focal or hard to distinguish from spillover of the normal membranous staining.Study design and methodsWe therefore examined Lymphoid Enhancer-Binding Factor 1 (LEF1) immunostaining, a nuclear marker of WNT activation that serves as a potential surrogate ofCTNNB1mutations.ResultsIn a cohort of endometrial carcinomas (n=255) LEF1 predictedCTNNB1mutations correctly in 85%, while β-catenin was 76% accurate. Across a variety of entities characterized byCTNNB1mutations as putative drivers, we found diffuse and strong expression of LEF1 in 77% of cases. LEF1 immunostaining proved easier to interpret than β-catenin immunostaining in 54% of cases, more difficult in 1% of cases, and comparable in the remaining cases.ConclusionWe conclude that LEF1 immunostaining is a useful surrogate marker forCTNNB1mutations. It favorably complements β-catenin immunohistochemistry and outperforms the latter as a single marker.
Effectiveness of an Inactivated Covid-19 Vaccine with Homologous and Heterologous Boosters against Omicron in Brazil
Authors: Ranzani Otavio T. , Hitchings Matt D.T. , Leite de Melo Rosana , de França Giovanny V. A. , Fernandes Cássia de Fátima R. , Lind Margaret L , Scaramuzzini Torres Mario Sergio , Tsuha Daniel Henrique , David Leticia C. S. , Said Rodrigo F. C. , Almiron Maria , de Oliveira Roberto D. , Cummings Derek A.T. , Dean Natalie E , Andrews Jason R. , Ko Albert I. , Croda Julio 
Published: April 2022

AbstractThe effectiveness of inactivated vaccines (VE) against symptomatic and severe COVID-19 caused by omicron is unknown. We conducted a nationwide, test-negative, case-control study to estimate VE for homologous and heterologous (BNT162b2) booster doses in adults who received two doses of CoronaVac in Brazil in the Omicron context. Analyzing 1,386,544 matched-pairs, VE against symptomatic disease was 8.6% (95% CI, 5.6-11.5) and 56.8% (95% CI, 56.3-57.3) in the period 8-59 days after receiving a homologous and heterologous booster, respectively. During the same interval, VE against severe Covid-19 was 73.6% (95% CI, 63.9-80.7) and 86.0% (95% CI, 84.5-87.4) after receiving a homologous and heterologous booster, respectively. Waning against severe Covid-19 after 120 days was only observed after a homologous booster. Heterologous booster might be preferable to individuals with completed primary series inactivated vaccine.
COVID-19 vaccination coverage by company size and the effects of socioeconomic factors and workplace vaccination in Japan: a cohort study
Authors: Mori Koji , Mori Takahiro , Nagata Tomohisa , Ando Hajime , Hino Ayako , Tateishi Seiichiro , Tsuji Mayumi , Muramatsu Keiji , Fujino Yoshihisa ,   the CORoNa Work Project
Published: April 2022

AbstractBackgroundVaccination is considered the most effective control measure against COVID-19. Vaccine hesitancy and equitable vaccine allocation are important challenges to disseminating developed vaccines. To promote COVID-19 vaccination coverage, the government of Japan established the workplace vaccination program. However, while it appears that the program was effective in overcoming vaccine hesitancy, the program may have hindered the equitable allocation of vaccines because it mainly focused on employees of large companies. We investigated the relationship between company size and COVID-19 vaccination completion status of employees and the impact of the workplace vaccination program on this relationship.MethodsWe conducted an internet-based prospective cohort study from December 2020 (baseline) to December 2021. The data were collected using a self-administered questionnaire survey. Briefly, 27,036 workers completed the questionnaire at baseline and 18,560 at follow-up. After excluding ineligible respondents, we finally analyzed the data from 15,829 participants. At baseline, the participants were asked about the size of the company they worked for, and at follow-up they were asked about the month in which they received their second COVID-19 vaccine dose and the availability of a company-arranged vaccination opportunity.ResultsIn each month throughout the observation period, the odds of having received a second COVID-19 vaccine dose were significantly lower for small-company employees than for large-company employees in the sex- and age-adjusted model. This difference decreased after adjusting for socioeconomic factors, and there was no significant difference after adjusting for the availability of a company-arranged vaccination opportunity.ConclusionsThe workplace vaccination program implemented in Japan to control the COVID-19 pandemic may have been effective in overcoming vaccine hesitancy in workers; however, it may have caused an inequitable allocation of vaccines between companies of different sizes. Because people who worked for small companies were less likely to be vaccinated, it will be necessary to enhance support of vaccination for this population in the event of future infectious disease outbreaks.Trial registrationNot applicable.
Risk models based on non-cognitive measures may identify presymptomatic Alzheimer’s disease
Authors: Yang Jingjing , Oveisgharan Shahram , Liu Xizhu , Wilson Robert S , Bennett David A , Buchman Aron S 
Published: April 2022

ABSTRACTBackgroundAlzheimer’s disease is a progressive disorder without a cure. Developing risk prediction models for detecting presymptomatic Alzheimer’s disease using non-cognitive measures is necessary to enable early interventions.ObjectiveExamine if non-cognitive metrics alone can be used to construct risk models to identify adults at risk for Alzheimer’s dementia and cognitive impairment.MethodsClinical data from older adults without dementia from the Memory and Aging Project (MAP, n=1179) and Religious Orders Study (ROS, n=1103) were analyzed using Cox proportional hazard models to develop risk prediction models for Alzheimer’s dementia and cognitive impairment. Models using only non-cognitive covariates were compared to models that added cognitive covariates. All models were trained in MAP, tested in ROS, and evaluated by the AUC of ROC curve.ResultsModels based on non-cognitive covariates alone achieved AUC (0.800,0.785) for predicting Alzheimer’s dementia (3,5) years from baseline. Including additional cognitive covariates improved AUC to (0.916,0.881). A model with a single covariate of composite cognition score achieved AUC (0.905,0.863). Models based on non-cognitive covariates alone achieved AUC (0.717,0.714) for predicting cognitive impairment (3,5) years from baseline. Including additional cognitive covariates improved AUC to (0.783,0.770). A model with a single covariate of composite cognition score achieved AUC (0.754,0.730).ConclusionRisk models based on non-cognitive metrics predict both Alzheimer’s dementia and cognitive impairment. However, non-cognitive covariates do not provide incremental predictivity for models that include cognitive metrics in predicting Alzheimer’s dementia, but do in models predicting cognitive impairment. Further improved risk prediction models for cognitive impairment are needed.
An investigation of age-related neuropathophysiology in autism spectrum disorder using fixel-based analysis of corpus callosum white matter micro- and macrostructure
Authors: Kirkovski Melissa , Singh Mervyn , Dhollander Thijs , Fuelscher Ian , Hyde Christian , Albein-Urios Natalia , Donaldson Peter H , Enticott Peter G 
Published: April 2022

AbstractBackgroundCorpus callosum anomalies are commonly noted in autism spectrum disorder (ASD). Given the complexity of its microstructural architecture, with crossing fibers projecting throughout, we applied fixel-based analysis to probe white matter micro- and macrostructure within this region. As ASD is a neurodevelopmental condition with noted abnormalities in brain growth, age was also investigated.MethodsData for participants with (N=54) and without (N=50) ASD, aged 5-34 years, were obtained from the Autism Brain Imaging Data Exchange-II (ABIDE-II). Within each site, indices of fiber density (FD), fiber cross-section (FC), and combined fiber density and cross-section (FDC) were compared between those groups.ResultsYoung adolescents with ASD (age = 11.19 ± 7.54) showed reduced macroscopic FC and FDC compared to age-matched neurotypical controls (age = 10.04 ± 4.40). Reduced FD and FDC was noted in a marginally older ASD (age 13.87 ± 3.15) cohort compared to matched controls (age = 13.85 ± 2.90). Among the oldest cohorts, a non-significant trend indicated reduced FD in older adolescents/young adults with ASD (age = 17.07 ± 3.56) compared to controls (age = 16.55 ± 2.95). There was a positive correlation between age and callosal mean FC and FDC in the youngest cohort. When stratified by diagnosis, this finding remained only for the ASD sample.ConclusionWhite matter aberration appears greatest among younger ASD cohorts. In older adolescents and young adults, less of the corpus callosum seems affected. This supports the suggestion that some early neuropathophysiological indicators in ASD may dissipate with age.
Breast and Cervical Cancer Screening Rates in Student-Run Free Clinics: A Systematic Review
Authors: Xiao Sophia Ying , Major Catherine Kendall , O’Connell Katie A. , Lee David , Lin Christine , Sarino Esther , Chen Kevin 
Published: April 2022

AbstractObjectiveTo assess rates of breast and cervical cancer screening at student-run free clinics to better understand challenges and strategies for advancing quality and accessibility of women’s health screening at student-run free clinics.Data sourcesWe performed a systematic search of Ovid MEDLINE, PubMed, Web of Science, and Google Scholar databases from database inception to 2020 using keywords related to student-run clinics, breast cancer screening, and cervical cancer screening.Study eligibility criteriaWe included all English-language publications describing screening rates of breast and/or cervical cancer at student-run free clinics within the United States. Five authors screened abstracts and reviewed full texts for inclusion.Study appraisal and synthesis methodsTwo reviewers extracted data independently for each publication using a structured data extraction table. Disagreements were resolved by group consensus. Two reviewers then assessed for risk of bias for each text using a modified Agency for Healthcare Research and Quality checklist for cross-sectional and prevalence studies. Results were synthesized qualitatively due to study heterogeneity.ResultsOf 3634 references identified, 12 references met study inclusion criteria. The proportion of patients up-to-date on breast cancer screening per guidelines ranged from 45% to 94%. The proportion of patients up-to-date on cervical cancer screening per guidelines ranged from 40% to 88%.ConclusionStudent-run free clinics can match breast and cervical cancer screening rates amongst uninsured populations nationally, though more work is required to bridge the gap in care that exists for the underinsured and uninsured.
Interpretation of non-responders to SARS-CoV-2 vaccines using WHO International Standard
Authors: Zeng Qiang , Yang Xue , Gao Qi , Lin Biao-yang , Li Yong-zhe , Huang Gang , Xu Yang 
Published: April 2022

ABSTRACTSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic with more than 485 millions infected. Questions about non-responders to SARS-CoV-2 vaccines remain unaddressed. Here, we report data from people after administering the complete dose of SARS-CoV-2 vaccines using the World Health Organization International Standard for anti-SARS-CoV-2 immunoglobulin. Our study showed that immune cells such as CD4 cells, CD8 cells, and B cells and anti-spike immunoglobulin G levels were significantly reduced in the elderly. There were 7.5% non-responders among the 18–59 yr group and 11.7% in the ≥60 yr group. A titer of anti-SARS-CoV-2 spike immunoglobulin G is blew 50 BAU/mL to be considered as non-responders at intervals of 30 to 90 days after the last vaccine dose. Booster vaccination may be recommended for non-responders to reduce the disease severity and mortality.
Size matters - the impact of nucleus size on results from spatial transcriptomics
Authors: Mohammadi Elyas , Chojnowska Katarzyna , Bieńkowski Michał , Kostecka Anna , Koczkowska Magdalena , Żmijewski Michał A. , Jąkalski Marcin , Ingelsson Martin , Filipowicz Natalia , Olszewski Paweł , Davies Hanna , Wierzbicka Justyna M. , Hyman Bradley T. , Dumanski Jan P. , Piotrowski Arkadiusz , Mieczkowski Jakub 
Published: April 2022

AbstractVisium Spatial Gene Expression (ST) is a method combining histological spatial information with transcriptomics profiles directly from tissue sections. The use of spatial information has made it possible to discover novel modes of gene expression regulations. However, in the ST experiment, the nucleus size of cells may exceed the thickness of a tissue slice. This may, in turn, negatively affect comprehensive capturing the transcriptomics profile in a single slice, especially for tissues having large differences in the size of nuclei. Here, we defined the effect of Consecutive Slices Data Integration (CSDI) on results from spatial transcriptomic study of human postmortem brains. CSDI can be applied to investigate consecutive sections studied with ST in the human cerebral cortex, avoiding misinterpretation of spot clustering and annotation, increasing accuracy of cell recognition as well as improvement in uncovering the layers of grey matter in the human brain.
Metabolic alkalosis and mortality in COVID-19
Authors: Jiang Zhifeng 
Published: April 2022

AbstractBackgroundAs a new infectious disease affecting the world, COVID-19 has caused a huge impact on countries around the world. At present, its specific pathophysiological mechanism has not been fully clarified. We found in the analysis of the arterial blood gas data of critically ill patients that the incidence of metabolic alkalosis in such patients is high.MethodWe retrospectively analyzed the arterial blood gas analysis results of a total of 16 critically ill patients in the intensive ICU area of Xiaogan Central Hospital and 42 severe patients in the intensive isolation ward, and analyzed metabolic acidosis and respiratory acidosis. Metabolic alkalosis and respiratory alkalosis, and the relationship between metabolic alkalosis and death.ResultAmong the 16 critically ill patients, the incidence of metabolic alkalosis was 100%, while the incidence of metabolic alkalosis in severe patients was 50%; the mortality rate in critically ill patients was 81.3%, and 21.4% in severe patients; The mortality of all patients with metabolic alkalosis is 95.5%,and 4.5% in without metabolic alkalosis.ConclusionThe incidence of metabolic alkalosis in critically ill COVID-19 patients is high, and it is associated with high mortality.
Changes in Apolipoprotein A1 and B, Glucose Metabolism, and Skeletal Muscle Mass in Peripheral Artery Disease after Endovascular Treatment: A Pilot Study
Authors: Ikeda Takeshi , Komiyama Hidenori , Miyakuni Tomoyo , Takano Masamichi , Matsushita Masato , Kobayashi Nobuaki , Asai Kuniya , Shimizu Wataru , Miyauchi Yasushi 
Published: April 2022

AbstractPeripheral artery disease impairs walking and physical activity, resulting in further loss of skeletal muscle. However, peripheral artery disease can be treated with endovascular treatment. The thigh muscle has been shown to correlate with systemic skeletal muscle volume. We assessed the changes in the metabolism of apolipoproteins A1 and B, blood glucose, and thigh muscle mass after endovascular treatment in above-the-knee peripheral artery disease where vessels supply the thigh muscle. Mid-thigh muscle volume was measured with computed tomography before and at 6 months after endovascular treatment. Apolipoproteins A1 and B, fasting blood glucose, post-load (75 g oral glucose tolerance test) 2 h-blood glucose, and glycated hemoglobin A1c (HbA1c) levels were measured concomitantly. The relationships between changes in apolipoproteins A1, apolipoproteins B, blood glucose, post-oral glucose tolerance test 2 h-blood glucose, Rutherford classification, and gain or loss of thigh muscle were investigated. Thigh muscle mass did not correlate with changes in apolipoproteins A1, B, fasting glucose, post-oral glucose tolerance test 2 h-blood glucose, HbA1c, and Rutherford classification. Among patients with muscle gain post-endovascular treatment, apolipoproteins A1 increased significantly, while apolipoproteins B levels were similar. Post-oral glucose tolerance test 2 h-blood glucose levels decreased. Preferable metabolic changes were observed in patients with skeletal muscle gain contrasted with muscle loss.