bluuebunny/crossref_metadata_2025_split huggingface dataset:
Overweight and Obesity in Adult Birth by Cesarean Section: A Systematic Review With Meta-analysis
Authors: Chiavarini Manuela , De Socio Benedetta , Giacchetta Irene , Fabiani Roberto 
Published: January 2023

Context:
Overweight/obesity is one of the most important health problems. Birth by cesarean section has been shown to influence long-term health outcomes including obesity.

Objective:
The aim of this systematic review-meta-analysis is to update acknowledgment of the increased risk of cesarean section on offspring's overweight/obesity.

Methods:
This study follows the PRISMA guidelines. A systematic literature search was conducted on Scopus, PubMed, and Web of Science; we have selected all the articles published until January 2, 2022. For inclusion, studies must have reported either (i) both birth by cesarean section and adult (≥18 years) offspring's body mass index; (ii) cohort or case-control study design; and (iii) a risk estimate. Heterogeneity testing was performed using Cochran's Q and I
2 statistics. Publication bias was assessed by the Egger test and the Begg test. Meta-analysis was performed through a random-effects model.

Results:
Twelve studies with a combined population of 180 065 subjects were included in the meta-analysis. The overall analysis (N = 19) yielded a combined risk estimate for overweight/obesity of 1.19 (95% CI, 1.08-1.30) and the test of heterogeneity resulted into Q = 57.44 (I
2 = 68.67%, P ≤ .001). The risk of offspring obesity is 1.23 (95% CI, 1.09-1.39) and the test of heterogeneity resulted into Q = 39.55 (I
2 = 69.66%, P ≤ .001). Children born by cesarean section have an increased risk of obesity in adulthood.
Near-Miss Events Detected Using the Emergency Department Trigger Tool
Authors: Griffey Richard T. , Schneider Ryan M. , Todorov Alexandre A. 
Published: January 2023

Objectives
Near misses include conditions with potential for harm, intercepted medical errors, and events requiring monitoring or intervention to prevent harm. Little is reported on near misses or their importance for quality and safety in the emergency department (ED).

Methods
This is a secondary evaluation of data from a retrospective study of the ED Trigger Tool (EDTT) at an urban, academic ED (data from October 1, 2014, to October 31, 2015; 92,859 eligible visits). All patients 18 years and older completing a visit were eligible. We ran the EDTT, a computerized query for triggers on 13 months of ED visit data, reviewing 5582 selected records using a 2-tiered approach. Events were categorized by occurrence (ED vs present on arrival [POA]), severity, omission/commission, and type, using a taxonomy with categories, subcategories, and cross-cutting modifiers.

Results
We identified 1458 ED near misses in 1269 of 5582 records (22.7%) and 80 near misses that were POA. Patient care events represented most ED near misses, including delays in diagnosis, treatment, and failure to monitor, primarily driven by ED boarding and crowding. Medication events were second most common (17%), including 80 medication administration errors. Of 80 POA events, 42% were related to overanticoagulation. We estimate that 19.3% of all ED visits include a near miss.

Conclusions
Near-miss events are relatively common (22.7% of our sample, 19.3% in the population) and are associated with an increased risk for an adverse event. Most events were patient care related (77%) involving delays due to crowding and ED boarding followed by medication administration errors. The EDTT is a high-yield approach for detecting important near misses and latent system deficiencies that impact patient safety.
Colorimetric Detector for Hydrogen Sulfide Detection in Industrial Environments Based on Silver Nanoparticles Synthesized in Streptomyces Bacteria
Authors: Souri Nika , Abbaszadeh Maedeh , Ghorbanzadeh Sadegh 
Published: January 2023

AbstractHydrogen sulfide is a colorless, foul-odor pollutant with corrosive properties. This gas is one of the important pollutants released from food factories, fertilizer manufacturing factories, sewage treatment plants, and well drilling. Considering the dangers of being exposed to hydrogen sulfide gas, this article provides a cost-effective, simple, life-saving efficient solution. In this study, Streptomyces bacterium was used for biological production of silver nanoparticles, due to its resistance to the antimicrobial properties of silver. The synthesis and the size range of nanoparticles were confirmed using validation methods. For preparing biocomposite that entraps biological agents, microencapsulation of bacteria was adopted using gellan gum and alginate. In order to validate the final product, the viscosity and porosity of the biocomposite were determined. These tests aimed to investigate the mechanical properties affecting the behaviour and the response time of the final detector. In the end, the detector was exposed to hydrogen sulfide gas, and the color changes of the detector were recorded by time. According to the results, the control sample remained unchanged in all concentrations. However, the color of the test sample, changed faster with the increase in the input gas concentration. Moreover, no color change was observed in concentrations less than 20 mg/l. Therefore, the designed biodetector can be used for qualitative and semi-quantitative measurement of Hydrogen sulfide, in concentrations higher than 20 mg/l.
A Case Report of a COVID-19 Infection with Positive Sputum and Negative Nasopharyngeal Rapid Antigen-Based Testing: A Practical Method to Explore Sputome
Authors: Guzman Norberto A. , Guzman Daniel E. 
Published: January 2023

AbstractCurrent COVID-19 antigen testing is primarily carried out by obtaining a specimen via nasopharyngeal swab and performing a rapid lateral flow immunoassay (LFIA) or related immunoassays. On average, a nasopharyngeal antigen-based LFIA for COVID-19 remains positive for approximately one week from symptom onset, and levels of infectivity and duration of the symptoms may depend primarily on carrying a high viral load enough to infect others. It has been proposed that patients with long-COVID, a syndrome in which patients continue to have complications of COVID with ongoing symptoms, may have occurring viral replication, despite testing negative via rapid COVID antigen testing.We therefore propose a modified antigen-based method that exposes hidden or masked antigenic sites of viral specimens, or lingering fragments of viral proteins, present in sputum using a home-based rapid immunoassay for COVID-19. Almost all protocols for testing were performed according to LFIA kit manufacturer’s instructions for the detection of SARS-CoV-2 nucleocapsid protein antigen, one of the most predominant proteins encoded by the SARS-CoV-2 virus. However, in challenging the manufacturer instructions, one or more digestive enzymes and a detergent were added to the collected biosamples (nasopharyngeal, oropharyngeal, saliva, buccal, gargle, and sputum); this modified procedure expose hidden or masked antigenic sites of the coronavirus or cross-reactant antigenic sites of related or non-related viruses, or some of the plethora of epitopes generated by the sample corresponding microbiota to accomplish an optimal binding to the commercial antibody used in the diagnostic test. The modified protocol can enhance detection sensitivity by making the resultant test band in sputum samples visible, that would otherwise not be seen, and consequently may generate a false negative result, in a nasopharyngeal sample from a patient with mild symptoms of COVID-19 and/or low viral load. Therefore, a need exists for an improved sample pre-treatment extraction procedure that allows optimization of sample preparation to attain a more accurate test result. Although the experiments described here were performed using commercial platforms, with antibodies directed to SARS-CoV-2 nucleocapsid antigen, this method may also be viable for the detection of any other pathogen in sputum by using antibodies directed to the key antigens present in the pathogen of interest. Furthermore, this modified method to expose the content of sputum can be used as a simple protocol to study the sputome, the proteome of sputum, and other omics (sputomics). In summary, this simple method is non-invasive, rapid, inexpensive, accurate, and may provide increased sensitivity and specificity in the detection of COVID-19 antigens for several weeks or even months.
Using Artificial Intelligence to Learn Optimal Regimen Plan for Alzheimer’s Disease
Authors: Bhattarai Kritib , Das Trisha , Kim Yejin , Chen Yongbin , Dai Qiying , Li Xiaoyang , Jiang Xiaoqian , Zong Nansu 
Published: January 2023

ABSTRACTBackgroundAlzheimer’s Disease (AD) is a progressive neurological disorder with no specific curative medications. While only a few medications are approved by FDA (i.e., donepezil, galantamine, rivastigmine, and memantine) to relieve symptoms (e.g., cognitive decline), sophisticated clinical skills are crucial to optimize the appropriate regimens given the multiple coexisting comorbidities in this patient population.ObjectiveHere, we propose a study to leverage reinforcement learning (RL) to learn the clinicians’ decisions for AD patients based on the longitude records from Electronic Health Records (EHR).MethodsIn this study, we withdraw 1,736 patients fulfilling our criteria, from the Alzheimer’s Disease Neuroimaging Initiative(ADNI) database. We focused on the two most frequent concomitant diseases, depression, and hypertension, thus resulting in five main cohorts, 1) whole data, 2) AD-only, 3) AD-hypertension, 4) AD-depression, and 5) AD-hypertension-depression. We modeled the treatment learning into an RL problem by defining the three factors (i.e., states, action, and reward) in RL in multiple strategies, where a regression model and a decision tree are developed to generate states, six main medications extracted (i.e., no drugs, cholinesterase inhibitors, memantine, hypertension drugs, a combination of cholinesterase inhibitors and memantine, and supplements or other drugs) are for action, and Mini-Mental State Exam (MMSE) scores are for reward.ResultsGiven the proper dataset, the RL model can generate an optimal policy (regimen plan) that outperforms the clinician’s treatment regimen. With the smallest data samples, the optimal-policy (i.e., policy iteration and Q-learning) gained a lesser reward than the clinician’s policy (mean -2.68 and -2.76vs. -2.66, respectively), but it gained more reward once the data size increased (mean -3.56 and -2.48vs. -3.57, respectively).ConclusionsOur results highlight the potential of using RL to generate the optimal treatment based on the patients’ longitude records. Our work can lead the path toward the development of RL-based decision support systems which could facilitate the daily practice to manage Alzheimer’s disease with comorbidities.
Assessing eligibility for lung cancer screening: Parsimonious multi-country ensemble machine learning models for lung cancer prediction
Authors: Callender Thomas , Imrie Fergus , Cebere Bogdan , Pashayan Nora , Navani Neal , van der Schaar Mihaela , Janes Sam M 
Published: January 2023

AbstractBackgroundEnsemble machine learning could support the development of highly parsimonious prediction models that maintain the performance of more complex models whilst maximising simplicity and generalisability, supporting the widespread adoption of personalised screening. In this work, we aimed to develop and validate ensemble machine learning models to determine eligibility for risk-based lung cancer screening.MethodsFor model development, we used data from 216,714 ever-smokers in the UK Biobank prospective cohort and 26,616 high-risk ever-smokers in the control arm of the US National Lung Screening randomised controlled trial. We externally validated our models amongst the 49,593 participants in the chest radiography arm and amongst all 80,659 ever-smoking participants in the US Prostate, Lung, Colorectal and Ovarian Screening Trial (PLCO). Models were developed to predict the risk of two outcomes within five years from baseline: diagnosis of lung cancer, and death from lung cancer. We assessed model discrimination (area under the receiver operating curve, AUC), calibration (calibration curves and expected/observed ratio), overall performance (Brier scores), and net benefit with decision curve analysis.ResultsModels predicting lung cancer death (UCL-D) and incidence (UCL-I) using three variables – age, smoking duration, and pack-years – achieved or exceeded parity in discrimination, overall performance, and net benefit with comparators currently in use, despite requiring only one-quarter of the predictors. In external validation in the PLCO trial, UCL-D had an AUC of 0.803 (95% CI: 0.783-0.824) and was well calibrated with an expected/observed (E/O) ratio of 1.05 (95% CI: 0.95-1.19). UCL-I had an AUC of 0.787 (95% CI: 0.771-0.802), an E/O ratio of 1.0 (0.92-1.07). The sensitivity of UCL-D was 85.5% and UCL-I was 83.9%, at 5-year risk thresholds of 0.68% and 1.17%, respectively 7.9% and 6.2% higher than the USPSTF-2021 criteria at the same specificity.ConclusionsWe present parsimonious ensemble machine learning models to predict the risk of lung cancer in ever-smokers, demonstrating a novel approach that could simplify the implementation of risk-based lung cancer screening in multiple settings.
A large-scale machine learning study of sociodemographic factors contributing to COVID-19 severity
Authors: Tumbas Marko , Markovic Sofija , Salom Igor , Djordjevic Marko 
Published: January 2023

AbstractUnderstanding sociodemographic factors behind COVID-19 severity relates to significant methodological difficulties, such as differences in testing policies and epidemics phase, as well as a large number of predictors that can potentially contribute to severity. To account for these difficulties, we assemble 115 predictors for more than 3000 US counties and employ a well-defined COVID-19 severity measure derived from epidemiological dynamics modeling. We then use a number of advanced feature selection techniques from machine learning to determine which of these predictors significantly impact the disease severity. We obtain a surprisingly simple result, where only two variables are clearly and robustly selected - population density and proportion of African Americans. Possible causes behind this result are discussed. We argue that the approach may be useful whenever significant determinants of disease progression over diverse geographic regions should be selected from a large number of potentially important factors.
Influence of soil-transmitted helminth infections on physical activity, physical fitness, and cardiovascular disease risk in primary schoolchildren in Gqeberha, South Africa
Authors: Nqweniso Siphesihle , Walter Cheryl , Randt Rosa du , Adams Larissa , Beckmann Johanna , Coulibaly Jean T. , Degen Jan , Dolley Danielle , Gall Stefanie , Joubert Nandi , Long Kurt Z. , Müller Ivan , Nienaber Madeleine , Pühse Uwe , Seelig Harald , Steinmann Peter , Utzinger Jürg , Gerber Markus , Lang Christin 
Published: January 2023

AbstractObjectiveSchool-aged children in low- and middle-income countries carry the highest burden of intestinal helminth infections, such as soil-transmitted helminths (STH). STH infections have been associated with negative consequences for child physical and cognitive development and wellbeing. Thus, the aim of this study was to determine the association of STH infections in schoolchildren from Gqeberha, focusing on physical activity, physical fitness, and clustered cardiovascular disease (CVD) risk score.MethodsThis cross-sectional study involved 680 schoolchildren (356 girls and 324 boys; mean age 8.19 years, SD±1.4) from disadvantaged communities in Gqeberha (formerly, Port Elizabeth), South Africa. Stool samples were collected and examined for STH infections using the Kato-Katz method. Physical activity (accelerometer) and physical fitness (grip strength, 20 m shuttle run) were measured using standard procedures. Furthermore, anthropometry, blood pressure, as well as glycated haemoglobin and lipid profile from capillary blood samples were assessed. We employed one-way ANOVAs to identify the associations of STH infections in terms of species and infection intensity with physical activity, physical fitness, and clustered CVD risk score.ResultsWe found a low STH infection prevalence (7.2%) in our study, with participants infected with at least one intestinal helminth species. In comparison to their non-infected peers, children infected with STH had lower mean grip strength scores, but higher mean VO2max estimation and higher levels of MVPA (p<.001). When considering type and intensity of infection, a positive association ofA. lumbricoidesinfection and MVPA was found. In contrast, lightT. trichiura-infected children had significantly lower grip strength scores compared to non-infected children. VO2max and MVPA were positively associated with lightT. trichiurainfection. No significant association between the clustered CVD risk score and infection with any STH species was evident.ConclusionsSTH-infected children had lower grip strength scores than their non-infected peers, yet, achieved higher VO2max and MVPA scores. Our study highlights that the type and intensity of STH infection is relevant in understanding the disease burden of STH infections on children’s health. The findings of our study must be interpreted cautiously due to the low infection rate, and more research is needed in samples with higher prevalence rates or case-control designs.
Omicron BA.1/BA.2 infections in triple-vaccinated individuals enhance a diverse repertoire of mucosal and blood immune responses
Authors: Hornsby Hailey , Nicols Alexander R. , Longet Stephanie , Liu Chang , Tomic Adriana , Angyal Adrienn , Kronsteiner Barbara , Tyerman Jessica K. , Tipton Tom , Zhang Peijun , Ramalho Marta Gallis , Supasa Piyada , Selvaraj Muneeswaran , Abraham Priyanka , Neale Isabel , Ali Mohammad , Barratt Natalie A. , Nell Jeremy M. , Gustafsson Lotta , Strickland Scarlett , Grouneva Irina , Rostron Timothy , Moore Shona C. , Hering Luisa M. , Dobson Susan L. , Bibi Sagida , Mongkolsapaya Juthathip , Lambe Teresa , Wootton Dan , Hall Victoria , Hopkins Susan , Dong Tao , Barnes Eleanor , Screaton Gavin , Richter Alex , Turtle Lance , Rowland-Jones Sarah L. , Carroll Miles , Duncan Christopher J.A. , Klenerman Paul , Dunachie Susanna J. , Payne Rebecca P. , de Silva Thushan I. 
Published: January 2023

AbstractPronounced immune escape by the SARS-CoV-2 Omicron variant has resulted in large numbers of individuals with hybrid immunity, generated through a combination of vaccination and infection. Based primarily on circulating neutralizing antibody (NAb) data, concerns have been raised that omicron breakthrough infections in triple-vaccinated individuals result in poor induction of omicron-specific immunity, and that a history of prior SARS-CoV-2 in particular is associated with profound immune dampening. Taking a broader and comprehensive approach, we characterized mucosal and blood immunity to both spike and non-spike antigens following BA.1/BA.2 infections in triple mRNA-vaccinated individuals, with and without a history of previous SARS-CoV-2 infection. We find that the majority of individuals increase BA.1/BA.2/BA.5-specific NAb following infection, but confirm that the magnitude of increase and post-omicron titres are indeed higher in those who were infection-naive. In contrast, significant increases in nasal antibody responses are seen regardless of prior infection history, including neutralizing activity against BA.5 spike. Spike-specific T cells increase only in infection-naive vaccinees; however, post-omicron T cell responses are still significantly higher in previously-infected individuals, who appear to have maximally induced responses with a CD8+ phenotype of high cytotoxic potential after their 3rdmRNA vaccine dose. Antibody and T cell responses to non-spike antigens also increase significantly regardless of prior infection status, with a boost seen in previously-infected individuals to immunity primed by their first infection. These findings suggest that hybrid immunity induced by omicron breakthrough infections is highly dynamic, complex, and compartmentalised, with significant immune enhancement that can help protect against COVID-19 caused by future omicron variants.
Migrant healthcare workers during COVID-19: bringing an intersectional health system-related approach into pandemic protection. A German case study
Authors: Kuhlmann Ellen , Ungureanu Marius-Ionut , Behrens Georg MN , Cossmann Anne , Fehr Leonie Mac , Klawitter Sandra , Mikuteit Marie , Müller Frank , Thilo Nancy , Brînzac Monica Georgina , Dopfer-Jablonka Alexandra 
Published: January 2023

AbstractIntroductionMigrant healthcare workers played an important role during the COVID-19 pandemic, but data are lacking especially for high-resourced European healthcare systems. This study aims to research migrant healthcare workers through an intersectional health system-related approach, using Germany as a case study.MethodsAn intersectional research framework was created and a rapid scoping study performed. Secondary analysis of selected items taken from two COVID-19 surveys was undertaken to compare perceptions of national and foreign-born healthcare workers, using descriptive statistics.ResultsAvailable research is focused on worst-case pandemic scenarios of Brazil and the United Kingdom, highlighting racialised discrimination and higher risks of migrant healthcare workers. The German data did not reveal significant differences between national-born and foreign-born healthcare workers for items related to health status including SARS-CoV-2 infection and vaccination, and perception of infection risk, protective workplace measures, and government measures, but items related to social participation and work conditions with higher infection risk indicate a higher burden of migrant healthcare workers.ConclusionsCOVID-19 pandemic policy must include migrant healthcare workers, but simply adding the migration status is not enough. We introduce an intersectional health systems-related approach to understand how pandemic policies create social inequalities and how the protection of migrant healthcare workers may be improved.
Biochemical deconstruction and reconstruction of Nuclear Matrix reveals the layers of nuclear organization
Authors: Bihani Ashish , Avvaru Akshay K. , Mishra Rakesh K. 
Published: January 2023

ABSTRACTNuclear Matrix (NuMat) is the fraction of the eukaryotic nucleus insoluble to detergents and high-salt extractions that manifests as a pan-nuclear fiber-granule network. NuMat consists of ribonucleoprotein complexes, members of crucial nuclear functional modules, and DNA fragments. Although NuMat captures the organization of non-chromatin nuclear space, very little is known about component organization within NuMat. To understand the organization of NuMat components, we subfractionated it with increasing concentrations of the chaotrope Guanidinium Hydrochloride (GdnHCl) and analyzed the proteomic makeup of the fractions. We observe that the solubilization of proteins at different concentrations of GdnHCl is finite and independent of the broad biophysical properties of the protein sequences. Looking at the extraction pattern of the Nuclear Envelope and Nuclear Pore Complex, we surmise that this fractionation represents easily-solubilized/loosely-bound and difficultly-solubilized/tightly-bound components of NuMat. Microscopic analyses of the localization of key NuMat proteins across sequential GdnHCl extractions ofin situNuMat further elaborate on the divergent extraction patterns. Furthermore, we solubilized NuMat in 8M GdnHCl and upon removal of GdnHCl through dialysis,en masserenaturation leads to RNA-dependent self-assembly of fibrous structures. The major proteome component of the self-assembled fibers comes from the difficultly-solubilized, tightly-bound component. This fractionation of the NuMat reveals different organizational levels within it which may reflect the structural and functional organization of nuclear architecture.