bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictive Value of Isolated Symptoms for Diagnosis of Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Children Tested During Peak Circulation of the Delta Variant
Authors: Westbrook Adrianna L , Benedit Laura C , Frediani Jennifer K , Griffiths Mark A , Khan Nabeel Y , Levy Joshua M , Morris Claudia R , Rostad Christina A , Stone Cheryl L , Sullivan Julie , Vos Miriam B , Welsh Jean , Wood Anna , Martin Greg S , Lam Wilbur , Pollock Nira R 
Published: March 2022

Abstract

Background
Coronavirus disease 2019 (COVID-19) testing policies for symptomatic children attending US schools or daycare vary, and whether isolated symptoms should prompt testing is unclear. We evaluated children presenting for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing to determine if the likelihood of having a positive SARS-CoV-2 test differed between participants with 1 symptom vs ≥2 symptoms, and to examine the predictive capability of isolated symptoms.

Methods
Participants aged &lt;18 years presenting for clinical SARS-CoV-2 molecular testing in 6 sites in urban/suburban/rural Georgia (July–October, 2021; Delta variant predominant) were queried about individual symptoms. Participants were classified into 3 groups: asymptomatic, 1 symptom only, or ≥2 symptoms. SARS-CoV-2 test results and clinical characteristics of the 3 groups were compared. Sensitivity, specificity, positive predictive values (PPVs), and negative predictive values (NPVs) for isolated symptoms were calculated by fitting a saturated Poisson model.

Results
Of 602 participants, 21.8% tested positive and 48.7% had a known or suspected close contact. Children reporting 1 symptom (n = 82; odds ratio [OR], 6.00 [95% confidence interval {CI}, 2.70–13.33]) and children reporting ≥2 symptoms (n = 365; OR, 5.25 [95% CI, 2.66–10.38]) were significantly more likely to have a positive COVID-19 test than asymptomatic children (n = 155), but they were not significantly different from each other (OR, 0.88 [95% CI, .52–1.49]). Sensitivity and PPV were highest for isolated fever (33% and 57%, respectively), cough (25% and 32%), and sore throat (21% and 45%); headache had low sensitivity (8%) but higher PPV (33%). Sensitivity and PPV of isolated congestion/rhinorrhea were 8% and 9%, respectively.

Conclusions
With high Delta variant prevalence, children with isolated symptoms were as likely as those with multiple symptoms to test positive for COVID-19. Isolated fever, cough, sore throat, or headache, but not congestion/rhinorrhea, offered the highest predictive value.
Seroprevalence of Severe Acute Respiratory Syndrome Coronavirus 2 After the Second Wave in South Africa in Human Immunodeficiency Virus–Infected and Uninfected Persons: A Cross-Sectional Household Survey
Authors: Wolter Nicole , Tempia Stefano , von Gottberg Anne , Bhiman Jinal N , Walaza Sibongile , Kleynhans Jackie , Moyes Jocelyn , Buys Amelia , McMorrow Meredith L , Aitken Sue , Magni Sarah , Yun Jessica , Fellows Tamika , Maakamedi Tetelo , Weiner Renay , Cawood Cherie , Martinson Neil , Lebina Limakatso , Jassat Waasila , Brauer Marieke , Cohen Cheryl 
Published: March 2022

Abstract

Background
Seroprevalence studies are important for quantifying the burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in resource-constrained countries.

Methods
We conducted a cross-sectional household survey spanning the second pandemic wave (November 2020 to April 2021) in 3 communities. Blood was collected for SARS-CoV-2 antibody (2 enzyme-linked immunosorbent assays targeting spike and nucleocapsid) and human immunodeficiency virus (HIV) testing. An individual was considered seropositive if testing positive on ≥1 assay. Factors associated with infection, and the age-standardized infection case detection rate, infection hospitalization rate, and infection fatality rate were calculated.

Results
Overall, 7959 participants were enrolled, with a median age of 34 years and an HIV prevalence of 22.7%. SARS-CoV-2 seroprevalence was 45.2% (95% confidence interval 43.7%–46.7%) and increased from 26.9% among individuals enrolled in December 2020 to 47.1% among those enrolled in April 2021. On multivariable analysis, seropositivity was associated with age, sex, race, being overweight/obese, having respiratory symptoms, and low socioeconomic status. Persons living with HIV with high viral load were less likely to be seropositive than HIV-uninfected individuals. The site-specific infection case detection rate, infection hospitalization rate, and infection fatality rate ranged across sites from 4.4% to 8.2%, 1.2% to 2.5%, and 0.3% to 0.6%, respectively.

Conclusions
South Africa has experienced a large burden of SARS-CoV-2 infections, with &lt;10% of infections diagnosed. Lower seroprevalence among persons living with HIV who are not virally suppressed, likely as a result of inadequate antibody production, highlights the need to prioritize this group for intervention.
Machine learning-based identification of risk-factor signatures for undiagnosed atrial fibrillation in primary prevention and post-stroke in clinical practice
Authors: Schnabel Renate B , Witt Henning , Walker Jochen , Ludwig Marion , Geelhoed Bastian , Kossack Nils , Schild Marie , Miller Robert , Kirchhof Paulus 
Published: March 2022

Abstract

Aims
Atrial fibrillation (AF) carries a substantial risk of ischemic stroke and other complications, and estimates suggest that over a third of cases remain undiagnosed. AF detection is particularly pressing in stroke survivors. To tailor AF screening efforts, we explored German health claims data for routinely available predictors of incident AF in primary care and post-stroke using machine learning methods.

Methods and results
We combined AF predictors in patients over 45 years of age using claims data in the InGef database (n = 1 476 391) for (i) incident AF and (ii) AF post-stroke, using machine learning techniques. Between 2013–2016, new-onset AF was diagnosed in 98 958 patients (6.7%). Published risk factors for AF including male sex, hypertension, heart failure, valvular heart disease, and chronic kidney disease were confirmed. Component-wise gradient boosting identified additional predictors for AF from ICD-codes available in ambulatory care. The area under the curve (AUC) of the final, condensed model consisting of 13 predictors, was 0.829 (95% confidence interval (CI) 0.826–0.833) in the internal validation, and 0.755 (95% CI 0.603–0.890) in a prospective validation cohort (n = 661). The AUC for post-stroke AF was of 0.67 (95% CI 0.651–0.689) in the internal validation data set, and 0.766 (95% CI 0.731–0.800) in the prospective clinical cohort.

Conclusion
ICD-coded clinical variables selected by machine learning can improve the identification of patients at risk of newly diagnosed AF. Using this readily available, automatically coded information can target AF screening efforts to identify high-risk populations in primary care and stroke survivors.
Interplays between drugs and the gut microbiome
Authors: Wan Yating , Zuo Tao 
Published: March 2022

Abstract
The gut microbiota is considered a key ‘metabolic organ’. Its metabolic activities play essential roles complementary to the host metabolic functions. The interplays between gut microbes and commonly used non-antibiotic drugs have garnered substantial attention over the years. Drugs can reshape the gut microorganism communities and, vice versa, the diverse gut microbes can affect drug efficacy by altering the bioavailability and bioactivity of drugs. The metabolism of drugs by gut microbial action or by microbiota–host cometabolism can transform the drugs into various metabolites. Secondary metabolites produced from the gut microbial metabolism of drugs contribute to both the therapeutic benefits and the side effects. In view of the significant effect of the gut microbiota on drug efficiency and clinical outcomes, it is pivotal to explore the interactions between drugs and gut microbiota underlying medical treatments. In this review, we describe and summarize the complex bidirectional interplays between gut microbes and drugs. We also illustrate the gut-microbiota profile altered by non-antibiotic drugs, the impacts and consequences of microbial alteration, and the biochemical mechanism of microbes impacting drug effectiveness. Understanding how the gut microbes interact with drugs and influence the therapeutic efficacy will help in discovering diverse novel avenues of regulating the gut microbes to improve the therapeutic effects and clinical outcomes of a drug in precision.
Assessing the potential of wearable health monitors for health system strengthening in low- and middle-income countries: a prospective study of technology adoption in Cambodia
Authors: Liverani Marco , Ir Por , Perel Pablo , Khan Mishal , Balabanova Dina , Wiseman Virginia 
Published: March 2022

Abstract
Wearable health monitors are a rapidly evolving technology that may offer new opportunities for strengthening health system responses to cardiovascular and other non-communicable diseases (NCDs) in low- and middle-income countries (LMICs). In light of this, we explored opportunities for, and potential challenges to, technology adoption in Cambodia, considering the complexity of contextual factors that may influence product uptake and sustainable health system integration. Data collection for this study involved in-depth interviews with national and international stakeholders and a literature review. The analytical approach was guided by concepts and categories derived from the non-adoption, abandonment, scale-up, spread, and sustainability (NASSS) framework—an evidence-based framework that was developed for studying health technology adoption and the challenges to scale-up, spread and sustainability of such technologies in health service organizations. Three potential applications of health wearables for the prevention and control of NCDs in Cambodia were identified: health promotion, follow-up and monitoring of patients and surveys of NCD risk factors. However, several challenges to technology adoption emerged across the research domains, associated with the intended adopters, the organization of the national health system, the wider infrastructure, the regulatory environment and the technology itself. Our findings indicate that, currently, wearables could be best used to conduct surveys of NCD risk factors in Cambodia and in other LMICs with similar health system profiles. In the future, a more integrated use of wearables to strengthen monitoring and management of patients could be envisaged, although this would require careful consideration of feasibility and organizational issues.
Surviving Art from Terezín: The Satirical Drawings of Pavel Fantl
Authors: Stańczyk Ewa 
Published: March 2022

ABSTRACT
This article examines the art of Pavel Fantl (1903–1945), a Czech Jewish doctor whom the Nazis murdered shortly before the end of the Second World War. Fantl left behind approximately eighty drawings. Despite being created under difficult conditions in the Terezín Ghetto, his art stands out for its use of humor and satire. This article argues that Fantl’s work not only testified to the suffering and persecution of Jews, but also reflected the wider visual conventions of the time, in particular the satirical cartoon and comic strip of the 1920s and 1930s. In addition, by tracing the material practices surrounding Fantl’s art, this paper shows how the creation and survival of drawings from the ghettos hinged on strong interpersonal bonds with non-Jews beyond the ghetto walls.
Universal Quadratic Forms, Small Norms, and Traces in Families of Number Fields
Authors: Kala Vítězslav , Tinková Magdaléna 
Published: March 2022

AbstractWe obtain good estimates on the ranks of universal quadratic forms over Shanks’ family of the simplest cubic fields and several other families of totally real number fields. As the main tool, we characterize all the indecomposable integers in these fields and the elements of the codifferent of small trace. We also determine the asymptotics of the number of principal ideals of norm less than the square root of the discriminant.
Codesigning a community-based participatory research project to assess tribal perspectives on privacy and health data sharing: A report from the Strong Heart Study
Authors: Triplett Cynthia , Fletcher Burgundy J , Taitingfong Riley I , Zhang Ying , Ali Tauqeer , Ohno-Machado Lucila , Bloss Cinnamon S 
Published: March 2022

Abstract
Broad health data sharing raises myriad ethical issues related to data protection and privacy. These issues are of particular relevance to Native Americans, who reserve distinct individual and collective rights to control data about their communities. We sought to gather input from tribal community leaders on how best to understand health data privacy and sharing preferences in this population. We conducted a workshop with 14 tribal leaders connected to the Strong Heart Study to codesign a research study to assess preferences concerning health data privacy for biomedical research. Workshop participants provided specific recommendations regarding who should be consulted, what questions should be posed, and what methods should be used, underscoring the importance of relationship-building between researchers and tribal communities. Biomedical researchers and informaticians who collect and analyze health information from Native communities have a unique responsibility to safeguard these data in ways that align to the preferences of specific communities.
Effects of feeding high oleic soybean oil to growing-finishing pigs on growth performance and carcass characteristics
Authors: Gaffield Katelyn N , Boler Dustin D , Dilger Ryan N , Dilger Anna C , Harsh Bailey N 
Published: March 2022

Abstract
Feeding growing-finishing pigs supplemental fat is a common practice in the swine industry and can result in improved feed efficiency and reduced feed intake; however, dietary lipids also play a key role in determining pork composition. The objectives of the current study were to evaluate the effects of feeding graded levels of high oleic soybean oil (HOSO) on growth performance and carcass characteristics. A total of 288 pigs raised in two separate blocks (144 pigs each) were assigned to one of four diets containing either 25% dried distiller’s grains with solubles (DDGS), 2% high oleic soybean oil (HOSO2), 4% high oleic soybean oil (HOSO4), or 6% high oleic soybean oil (HOSO6). Pigs were housed 4 per pen and fed for 98 d using a 3-phase feeding system. Pigs were individually weighed and feed intake was recorded throughout the trial to calculate average daily feed intake (ADFI) and gain to feed ratio (G:F). A total of 144 pigs were transported to the University of Illinois Meat Science Laboratory and fabricated into primal and subprimal cuts to calculate carcass cutting yields. Differences in growth performance were observed, with pigs fed the DDGS treatment exhibiting greater (P ≤ 0.01) overall ADFI consuming 0.21, 0.18, and 0.28 kg/d more than HOSO2, HOSO4, and HOSO6 diets, respectively. Pigs fed the HOSO6 diet had greater (P ≤ 0.03) overall G:F than pigs fed DDGS and HOSO2 diets but did not differ (P = 0.12) from pigs fed HOSO4. Furthermore, differences in carcass traits were observed. Hot carcass weight was increased (P ≤ 0.03) in pigs fed the HOSO6 diet compared with pigs fed the DDGS and HOSO2 diets, while pigs fed HOSO4 did not differ (P &gt; 0.05) from either extreme. Additionally, pigs fed HOSO4 and HOSO6 produced fatter (P ≤ 0.01) carcasses with reduced (P ≤ 0.01) standardized fat-free lean. Minimal differences were observed in primal weights expressed as a percentage of chilled side including bone-in Boston butt, trimmed loin, and trimmed ham with primal weights decreasing with increasing inclusion of dietary HOSO. Overall, pigs fed HOSO2 had reduced ADFI with similar backfat thickness and standardized fat-free lean compared with pigs fed the DDGS treatment. However, pigs fed HOSO 4% and 6% not only had improvements in ADFI and G:F but also had increased backfat thickness, which resulted in reductions in standardized fat-free lean and primal weights expressed as a percentage of chilled side weight.
Multi-disciplinary Leadership to Mitigate COVID-19 in an Austere West African Military Environment
Authors: Mitchell Stephanie L , Mitchell Thomas A , Horwitz-Willis Nathaniel , Alptunaer Timur N , Gipson Jeffrey A , Shackelford Stacy A 
Published: March 2022

ABSTRACT

Introduction
The COVID-19 pandemic created challenges for forward-deployed military units to Western Africa. Austere military environments afford multiple avenues to transmit COVID-19 amongst service members.

Materials and Methods
A COVID-19 outbreak on a military base in Western Africa spanning over 100 days is statistically analyzed using a Pearson’s correlation coefficient. Furthermore, a COVID-19 reproductive number (R0) is evaluated to examine the relationship between specific command-directed policies to mitigate COVID-19 transmission.

Results
The multidisciplinary partnership of military command, medical, and public health leadership implemented evidence-based and epidemiologically informed COVID-19 preventive base-wide policies, including appropriate isolation/quarantine policies. The R0 for the outbreak was 0.03 and remained &lt;1 for the outbreak duration. This base remained COVID-19 free for multiple weeks after policy implementation.

Conclusions
The implementation of practical mitigating base-wide policies through seamless communication between military command/medical/public health leadership resolved the COVID-19 outbreak while maintaining mission readiness. Weekly COVID-19 testing epidemiological data may be utilized by commanders to direct further decision-making on tightening/loosening base-wide policy restrictions for continued mission-essential operations, e.g., security, food service, or airfield operations.
Comparison of the Parkes and FAST FRB DM distribution
Authors: Arcus W R , James C W , Ekers R D , Wayth R B 
Published: March 2022

ABSTRACT
We model the fast radio burst (FRB) dispersion measure (DM) distribution for the Five-hundred-meter Aperture Spherical Telescope (FAST) and compare this with the four FRBs published in the literature to date. We compare the DM distribution of Parkes and FAST, taking advantage of the similarity between their multibeam receivers. Notwithstanding the limited sample size, we observe a paucity of events at low DM for all evolutionary models considered, resulting in a sharp rise in the observed cumulative distribution function in the region of 1000 pc cm−3 ≲ DM ≲ 2000 pc cm−3. These traits could be due to statistical fluctuations (0.12 ≤ p ≤ 0.22), a complicated energy distribution or break in an energy distribution power law, spatial clustering, observational bias, or outliers in the sample (e.g. an excessive DMHost as recently found for FRB 20190520B). The energy distribution in this regime is unlikely to be adequately constrained until further events are detected. Modelling suggests that FAST may be well placed to discriminate between redshift evolutionary models and to probe the helium ionization signal of the intergalactic medium.
Black hole weather forecasting with deep learning: a pilot study
Authors: Duarte Roberta , Nemmen Rodrigo , Navarro João Paulo 
Published: March 2022

ABSTRACT
In this pilot study, we investigate the use of a deep learning (DL) model to temporally evolve the dynamics of gas accreting on to a black hole in the form of a radiatively inefficient accretion flow (RIAF). We have trained a convolutional neural network (CNN) on a data set that consists of numerical solutions of the hydrodynamical equations for a range of initial conditions. We find that deep neural networks trained on one simulation seem to learn reasonably well the spatiotemporal distribution of densities and mass continuity of a black hole accretion flow over a duration of 8 × 104GM/c3, comparable to the viscous time-scale at r = 400GM/c2; after that duration, the model drifts from the ground truth suffering from excessive artificial mass injection. Models trained on simulations with different initial conditions show some promise of generalizing to configurations not present in the training set, but also suffer from mass continuity issues. We discuss the caveats behind this method and the potential benefits that DL models offer. For instance, once trained the model evolves an RIAF on a single GPU four orders of magnitude faster than usual fluid dynamics integrators running in parallel on 200 CPU cores. We speculate that a data-driven machine learning approach should be very promising for accelerating simulations of accreting black holes.
Gene Regulatory Networks of Epidermal and Neural Fate Choice in a Chordate
Authors: Leon Anthony , Subirana Lucie , Magre Kevin , Cases Ildefonso , Tena Juan J. , Irimia Manuel , Gomez-Skarmeta Jose Luis , Escriva Hector , Bertrand Stéphanie 
Published: March 2022

Abstract
Neurons are a highly specialized cell type only found in metazoans. They can be scattered throughout the body or grouped together, forming ganglia or nerve cords. During embryogenesis, centralized nervous systems develop from the ectoderm, which also forms the epidermis. How pluripotent ectodermal cells are directed toward neural or epidermal fates, and to which extent this process is shared among different animal lineages, are still open questions. Here, by using micromere explants, we were able to define in silico the putative gene regulatory networks (GRNs) underlying the first steps of the epidermis and the central nervous system formation in the cephalochordate amphioxus. We propose that although the signal triggering neural induction in amphioxus (i.e., Nodal) is different from vertebrates, the main transcription factors implicated in this process are conserved. Moreover, our data reveal that transcription factors of the neural program seem to not only activate neural genes but also to potentially have direct inputs into the epidermal GRN, suggesting that the Nodal signal might also contribute to neural fate commitment by repressing the epidermal program. Our functional data on whole embryos support this result and highlight the complex interactions among the transcription factors activated by the signaling pathways that drive ectodermal cell fate choice in chordates.