bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fatal cases after Omicron BA.1 and BA.2 infection: Diffuse alveolar damage occurs only in a minority – results of an autopsy study
Authors: Märkl Bruno , Dintner Sebastian , Schaller Tina , Sipos Eva , Kling Elisabeth , Miller Silvia , Farfan Francisco , Grochowski Przemyslaw , Reitsam Nic , Waidhauser Johanna , Hirschbühl Klaus , Spring Oliver , Fuchs Andre , Wibmer Thomas , Boor Peter , Beer Martin , Wylezich Claudia 
Published: October 2022

AbstractCompared with previously prevalent variants of SARS-CoV-2, the Omicron lineages BA.1 and BA.2 are known to be associated with mild clinical courses. In addition, well-established animal models do not develop severe diseases.To address whether the supposedly fatal cases after Omicron-BA.1/2 infection show the known COVID-19 organ alterations, especially in the lungs, 23 full and 3 partial autopsies in the deceased with known Omicron BA.1/2 infections have been consecutively performed. Viral RNA was determined by RT-qPCR and RNA-in situ hybridization. The lineages were analyzed by whole genome sequencing or S-gene analysis.Despite high viral loads in almost all nasopharyngeal swabs and in 13 lung tissue samples, death caused by COVID-19-associated diffuse alveolar damage (DAD) in the acute and organizing stages was found in only eight cases (31%). This rate is significantly lower compared to previous studies, including non-Omicron variants, where rates of 92% and 69% for non-vaccinated and fully vaccinated vaccines were observed. It is of special interest that neither vaccination status nor known risk factors (i.e., age, comorbidities, obesity, immuno-suppression) were significantly associated with a direct cause of death by COVID-19. Only the reason for the hospital admission of the patients due to COVID-19-related symptoms showed a significant correlation with directly COVID-19-caused deaths (P < 0.001).DAD still occurred in the Omicron BA.1/BA.2 era of the SARS-CoV-2 pandemic but at a considerably lower frequency than seen with previous variants of concern. In our study, none of the known risk factors discriminated the cases with COVID-19-caused death from those that had COVID-19 infections but died due to a different disease. Therefore, the host’s genomics might play a key role in this regard. Further studies are urgently needed to elucidate the existence of a genomic mechanism as a risk factor for a fatal course.
Predicting congenital syphilis cases: a performance evaluation of different machine learning models
Authors: Teixeira Igor Vitor , Silva Leite Morgana Thalita da , de Morais Melo Flávio Leandro , Silva Rocha Élisson da , Sadok Sara , da Costa Carrarine Ana Sofia Pessoa , Santana Marília , Rodrigues Cristina Pinheiro , de Lima Oliveira Ana Maria , Gadelha Keduly Vieira , de Morais Cleber Matos , Kelner Judith , Endo Patricia Takako 
Published: October 2022

AbstractBackgroundCommunicable diseases represent a huge economic burden for healthcare systems and for society. Sexually transmitted infections (STIs) are a concerning issue, especially in developing and underdeveloped countries, in which environmental factors and other determinants of health play a role in contributing to its fast spread. In light of this situation, machine learning techniques have been explored to assess the incidence of syphilis and contribute to the epidemiological surveillance in this scenario.ObjectiveThe main goal of this work is to evaluate the performance of different machine learning models on predicting undesirable outcomes of congenital syphilis in order to assist resources allocation and optimize the healthcare actions, especially in a constrained health environment.MethodWe use clinical and sociodemographic data from pregnant women that were assisted by a social program in Pernambuco, Brazil, named Mãe Coruja Pernambucana Program (PMCP). Based on a rigorous methodology, we propose six experiments using three feature selection techniques to select the most relevant attributes, pre-process and clean the data, apply hyperparameter optimization to tune the machine learning models, and train and test models to have a fair evaluation and discussion.ResultsThe AdaBoost-BODS-Expert model, an Adaptive Boosting (AdaBoost) model that used attributes selected by health experts, presented the best results in terms of evaluation metrics and acceptance by health experts from PMCP. By using this model, the results are more reliable and allows adoption on a daily usage to classify possible outcomes of congenital syphilis using clinical and sociodemographic data.
Social and structural determinants of injection drug use-associated bacterial and fungal infections: a qualitative systematic review and thematic synthesis
Authors: Brothers Thomas D. , Bonn Matthew , Lewer Dan , Comeau Emilie , Kim Inhwa , Webster Duncan , Hayward Andrew , Harris Magdalena 
Published: October 2022

ABSTRACTBackgroundInjection drug use-associated bacterial and fungal infections are increasingly common, and social contexts shape individuals’ injecting practices and treatment experiences. We sought to synthesize qualitative studies of social-structural factors influencing incidence and treatment of injecting-related infections.MethodsWe searched PubMed, EMBASE, Scopus, CINAHL, and PsycINFO from January 1, 2000, to February 18, 2021. Informed by Rhodes’ “risk environment” framework, we performed thematic synthesis in three stages: (1) line-by-line coding; (2) organizing codes into descriptive themes, reflecting interpretations of study authors; (3) consolidating descriptive themes into conceptual categories to identify higher-order analytic themes.ResultsWe screened 4,841 abstracts and included 26 qualitative studies on experiences of injecting-related bacterial and fungal infections. We identified six descriptive themes organized into two analytic themes. The first analytic theme, social production of risk, considered macro-environmental influences. Four descriptive themes highlighted pathways through which this occurs: (1) unregulated drug supply, leading to poor drug quality and solubility; (2) unsafe spaces, influenced by policing practices and insecure housing; (3) health care policies and practices, leading to negative experiences that discourage access to care; and (4) harm reduction programs, including structural barriers to effective service provision. The second analytic theme, practices of care among people who inject drugs, addresses protective strategies that people who inject drugs employ within infection risk environments. Associated descriptive themes were: (5) mutual care, including assisted-injecting and sharing sterile equipment; and (6) self-care, including vein health and self-treatment. Within constraining risk environments, some protective strategies for bacterial infections precipitated other health risks (e.g., HIV transmission).ConclusionsInjecting-related bacterial and fungal infections are shaped by modifiable social-structural factors, including unregulated drug quality, criminalization, insufficient housing, limited harm reduction services, and harmful health care practices. Enabling environment interventions that address these factors could further empower people who inject drugs to protect themselves and their community.
Dynamics of Vaccine-Hesitant Parents’ Considerations Regarding Covid-19 Vaccination
Authors: Atad Erga , Netzer Itamar , Peleg Orr , Landsman Keren , Dalyot Keren , Reuven Shanny Edan , Nitzany Eyal , Baram-Tsabari Ayelet 
Published: October 2022

AbstractIntroductionMost studies present a snapshot of hesitant parents’ decisions and thinking concerning COVID-19 vaccination, but for many it is a dynamic rather than a stable process. We examined the considerations of a group of vaccine hesitant parents (VHPs) with respect to COVID-19 vaccinations for their children before, during and after the main vaccination campaign for the 12 to15-year-old age group in Israel, over a six-month period.MethodsDigital surveys were administered to 1118 Israeli parents. After VHPs were identified, three surveys were conducted to evaluate considerations that discourage or encourage vaccination. A logistic regression was carried out on sixteen models; of these, six were found to be statistically significant.Results456 parents’ data were analyzed. Parents’ intentions to vaccinate prior to the vaccination campaign were a good predictor of their actual behavior, (rp=.497, p<.001). We divided the parents into four groups: consistently pro-vaccine (39.4%), consistently anti-vaccine (15.2%), pro-vaccine parents who did not vaccinate (17.6%), and anti-vaccine parents who did vaccinate (27.9%). We identified eight considerations that were significant in VHPs’ vaccination behavior: trust in scientists, doctors and drug companies, children’s preferences, spread of COVID, social responsibility, children’s characteristics, the vaccine’s speed of development and its side effects.DiscussionGreater vaccine uptake for teenagers may depend on the attitudes and perceptions of their parents. We identified encouraging and discouraging considerations that may make potential targets for public health officials when communicating about vaccines.Article SummaryEncouraging and discouraging considerations re COVID-19 vaccination are explored and identified in vaccine hesitant parents.What’s known on this subjectMost studies found that vaccine uptake is improved among well-to-do or highly educated parents. Severity of the disease and safety of the vaccination are the main factors influencing the decision.What this study addsThe dynamics of attitude change toward vaccination among VHPs may be affected by several different factors. Chief are children’s preferences and individual health characteristics, side effects and speed of vaccine development
TACCO: Unified annotation transfer and decomposition of cell identities for single-cell and spatial omics
Authors: Mages Simon , Moriel Noa , Avraham-Davidi Inbal , Murray Evan , Chen Fei , Rozenblatt-Rosen Orit , Klughammer Johanna , Regev Aviv , Nitzan Mor 
Published: October 2022

AbstractRapid advances in single-cell-, spatial-, and multi-omics, allow us to profile cellular ecosystems in tissues at unprecedented resolution, scale, and depth. However, both technical limitations, such as low spatial resolution and biological variations, such as continuous spectra of cell states, often render these data imperfect representations of cellular systems, best captured as continuous mixtures over cells or molecules. Based on this conceptual insight, we build a versatile framework, TACCO (Transfer of Annotations to Cells and their COmbinations) that extends an Optimal Transport-based core by different wrappers or boosters to annotate a wide variety of data. We apply TACCO to identify cell types and states, decipher spatio-molecular tissue structure at the cell and molecular level, and resolve differentiation trajectories. TACCO excels in speed, scalability, and adaptability, while successfully outperforming benchmarks across diverse synthetic and biological datasets. Along with highly optimized visualization and analysis functions, TACCO forms a comprehensive integrated framework for studies of high-dimensional, high-resolution biology.
Exploring causal effects of smoking and alcohol related lifestyle factors on self-report tiredness: a Mendelian randomization study
Authors: Li Heshan , Zhao Junru , Liang Jing , Song Xiaoyu 
Published: October 2022

AbstractSelf-reported tiredness or low energy, often referred to as fatigue, has been linked to lifestyle factors, although data from randomized–controlled trials are lacking. We investigate whether modifiable lifestyle factors including smoking and alcohol intake related exposures (SAIEs) are causal factors for fatigue using Mendelian randomization (MR). A two-sample MR study was performed by using genome-wide association summary results from UK Biobank (UKBB), and each of the sample size is more than 100,000. We used the inverse variance weighted method, and sensitivity analyses (MR Egger, weighted median and penalized median estimators) to account for pleiotropy. The two-sample MR analyses showed inverse causal effect of never-smoking status and positive effect of current smoking status on the risk of fatigue. Similarly, genetically predicted alcoholic intake was positively associated with fatigue. The results were consistent across the different MR methods. Our Mendelian randomization analyses do support that the cessation of smoking and alcohol can decrease the risk of fatigue, and limit alcohol intake frequency can also reduce the risk.Author summaryMany lifestyle factors have been associated with the risk of fatigue, but we cannot ascertain the causality between lifestyle factors and the risk of fatigue; whether the modification of lifestyles will reduce the risk. Another challenge is that fatigue is usually caused by various physiological and pathological factors, so most epidemiological data which examined risk factor modification have not studied the relationship between modifiable risk factors and self-reported tiredness in extensive conditions. SAIEs are the ones of the most influential lifestyle factors for human health and wellbeing. We performed MR analyses to estimate the causal effect of SAIEs on fatigue. In our study, we initially identified genetic variants which are significantly associated with SAIEs. We found SAIEs are causally involved in fatigue. The results could be extremely useful in the context of lifestyle - health relationships.
The Crux toolkit for analysis of bottom-up tandem mass spectrometry proteomics data
Authors: Kertesz-Farkas Attila , Adoquaye Acquaye Frank Lawrence Nii , Bhimani Kishankumar , Eng Jimmy K. , Fondrie William E. , Grant Charles , Hoopmann Michael R. , Lin Andy , Lu Yang Y. , Moritz Robert L. , MacCoss Michael J. , Noble William Stafford 
Published: October 2022

AbstractThe Crux tandem mass spectrometry data analysis toolkit provides a collection of algorithms for analyzing bottom-up proteomics tandem mass spectrometry data. Many publications have described various individual components of Crux, but a comprehensive summary has not been published since 2014. The goal of this work is to summarize the functionality of Crux, focusing on developments since 2014. We begin with empirical results demonstrating our recently implemented speedups to the Tide search engine. Other new features include a new score function in Tide, two new confidence estimation procedures, as well as three new tools: Param-medic for estimating search parameters directly from mass spectrometry data, Kojak for searching cross-linked mass spectra, and DIAmeter for searching data independent acquisition data against a sequence database.
Environmental and genetic predictors of human cardiovascular ageing
Authors: Shah Mit , Inácio Marco H. de A. , Lu Chang , Schiratti Pierre-Raphaël , Zheng Sean L. , Clement Adam , Bai Wenjia , King Andrew P. , Ware James S. , Wilkins Martin R. , Mielke Johanna , Elci Eren , Kryukov Ivan , McGurk Kathryn A. , Bender Christian , Freitag Daniel F. , O’Regan Declan P. 
Published: October 2022

ABSTRACTCardiovascular ageing is a process that begins early in life and leads to a progressive change in structure and decline in function due to accumulated damage across diverse cell types, tissues and organs contributing to multi-morbidity. Damaging biophysical, metabolic and immunological factors exceed endogenous repair mechanisms resulting in a pro-fibrotic state, cellular senescence and end-organ damage, however the genetic architecture of cardiovascular ageing is not known. Here we used machine learning approaches to quantify cardiovascular age from image-derived traits of vascular function, cardiac motion and myocardial fibrosis, as well as conduction traits from electrocardiograms, in 39,559 participants of UK Biobank. Cardiovascular ageing was found to be significantly associated with common or rare variants in genes regulating sarcomere homeostasis, myocardial immunomodulation, and tissue responses to biophysical stress. Ageing is accelerated by cardiometabolic risk factors and we also identified prescribed medications that were potential modifiers of ageing. Through large-scale modelling of ageing across multiple traits our results reveal insights into the mechanisms driving premature cardiovascular ageing and reveal potential molecular targets to attenuate age-related processes.
Role of anti-polyethylene glycol (PEG) antibodies in the allergic reactions and immunogenicity of PEG-containing Covid-19 vaccines
Authors: Kozma Gergely Tibor , Mészáros Tamás , Berényi Petra , Facskó Réka , Patkó Zsófia , Oláh Csaba Zs. , Nagy Adrienne , Fülöp Tamás Gyula , Glatter Kathryn Anne , Radovits Tamás , Merkely Béla , Szebeni János 
Published: October 2022

AbstractThe polyethylene-glycol (PEG)-containing Covid-19 vaccines can cause hypersensitivity reactions (HSRs), or rarely, life-threatening anaphylaxis. A causal role of anti-PEG antibodies (Abs) has been proposed, but not yet proven in humans. The 191 blood donors in this study included 10 women and 5 men who displayed HSRs to Comirnaty or Spikevax Covid-19 vaccines with 3 anaphylaxis. 118 donors had pre-vaccination anti-PEG IgG/IgM values as measured by ELISA, of which >98% were over background regardless of age, indicating the presence of these Abs in almost everyone. Their values varied over 2-3 orders of magnitude and displayed strong left-skewed distribution with 3-4% of subjects having >15-30-fold higher values than the respective median. First, or booster injections with both vaccines led to significant rises of anti-PEG IgG/IgM with >10-fold rises in about ∼10% of Comirnaty, and all Spikevax recipients, measured at different times after the injections. The anti-PEG Ab levels measured within 4-months after the HSRs were significantly higher than those in nonreactors. Serial testing of plasma (n=361 tests) showed the SARS-CoV-2 neutralization IgG to vary over a broad range, with a trend for biphasic dose dependence on anti-PEG Abs. The highest prevalence of anti-PEG Ab positivity in human blood reported to date represents new information which can most easily be rationalized by daily exposure to common PEG-containing medications and/or household items. The significantly higher, HSR-non-coincidental blood level of anti-PEG Abs in hypersensitivity reactor vs. non-reactors, taken together with relevant clinical and experimental data in the literature, suggest that anti-PEG Ab supercarrier people might be at increased risk for HSRs to PEG-containing vaccines, which themselves can induce these Abs via bystander immunogenicity. Our data also raise the possibility that anti-PEG Abs might also contribute to the reduction of these vaccines’ virus neutralization efficacy. Thus, screening for anti-PEG Ab supercarriers may identify people at risk for HSRs or reduced vaccine effectiveness.
Non-specific effects of Bacillus Calmette-Guérin - a systematic review and meta-analysis of randomized controlled trials
Authors: Trunk Gerhard , Davidović Maša , Bohlius Julia 
Published: October 2022

AbstractVaccines induce antigen-specific immunity which provides long-lived protection from the target pathogen. Trials especially from high infectious disease areas indicated that the tuberculosis vaccine Bacillus Calmette-Guérin (BCG) induces in addition non-specific immunity against various pathogens and thereby reduces overall mortality. Although recent trials produced conflicting results, it was suggested that BCG might protect from non-tuberculosis respiratory infections and could be used to bridge time until a specific vaccine against novel respiratory diseases like COVID-19 is available. We performed a systematic search for randomized controlled trials (RCT) published between 2011 and August 5th, 2022 providing evidence about non-specific effects after BCG vaccination, assessed their potential for bias, and meta-analyzed relevant clinical outcomes. We excluded RCTs investigating vaccination with an additional vaccine, unless outcomes from a follow-up period before the second vaccination were reported. Our search identified 15 RCTs including 32160 participants. Vaccination with BCG caused an estimated 49% decrease in risk for respiratory infections (HR 0.51, 95% CI 0.33-0.80) with substantial heterogeneity between trials (I2=80%; p<0.00001). There was evidence for a protective effect on all-cause mortality of 22% if follow-up was restricted to one year (HR 0.78, 95% CI 0.63-0.96); we did not find evidence for an effect when we considered longer follow-up (HR 0.87, 95% CI 0.75-1.02). Infection-related mortality after BCG-vaccination was reduced by 33% (HR 0.67; 95% CI 0.46-0.99), mortality for sepsis by 38% (HR 0.62, 95% CI 0.41-0.93). There was no evidence for a protective effect of BCG vaccination on infections of any origin (HR 0.84, 95% CI 0.71-1.00), COVID-19 (HR 0.83, 95% CI 0.61-1.14), sepsis (HR 0.82, 95% CI 0.62-1.07) or hospitalization (HR 1.02, 95% CI 0.92-1.14). According to these results, depending on the setting, vaccination with BCG provides time-limited partial protection against non-tuberculosis respiratory infections and may reduce mortality. These findings underline BCG’s potential 1) in pandemic preparedness against novel pathogens especially in developing countries with established BCG-vaccination programs but limited access to specific vaccines; 2) in reducing microbial infections, antimicrobial prescriptions and thus the development of antimicrobial resistance. There is a need for additional RCTs to clarify the circumstances under which BCG’s non-specific protective effects are mediated.
Glaucoma Detection and Staging from Visual Field Images using Machine Learning Techniques
Authors: Akter Nahida , Gordon Jack , Li Sherry , Poon Mikki , Perry Stuart , Fletcher John , Chan Thomas , White Andrew , Roy Maitreyee 
Published: October 2022

AbstractPurposeIn this study, we investigated the performance of deep learning (DL) models to differentiate between normal and glaucomatous visual fields (VFs) and classify glaucoma from early to the advanced stage to observe if the DL model can stage glaucoma as Mills criteria using only the pattern deviation (PD) plots. The DL model results were compared with a machine learning (ML) classifier trained on conventional VF parameters.MethodsA total of 265 PD plots and 265 numerical datasets of Humphrey 24-2 VF images were collected from 119 normal and 146 glaucomatous eyes to train the DL models to classify the images into four groups: normal, early glaucoma, moderate glaucoma, and advanced glaucoma. The two popular pre-trained DL models: ResNet18 and VGG16, were used to train the PD images using five-fold cross-validation (CV) and observed the performance using balanced, pre-augmented data (n= 476 images), imbalanced original data (n=265) and feature extraction. The trained images were further investigated using the Grad-CAM visualization technique. Moreover, four ML models were trained from the global indices: mean deviation (MD), pattern standard deviation (PSD) and visual field index (VFI), using five-fold CV to compare the classification performance with the DL model’s result.ResultsThe DL model, ResNet18 trained from balanced, pre-augmented PD images, achieved high accuracy in classifying the groups with an overall F1-score: 96.8%, precision: 97.0%, recall: 96.9%, and specificity: 99.0%. The highest F1 score was 87.8% for ResNet18 with the original dataset and 88.7% for VGG16 with feature extraction. The DL models successfully localized the affected VF loss in PD plots. Among the ML models, the random forest (RF) classifier performed best with an F1 score of 96%.ConclusionThe DL model trained from PD plots was promising in differentiating normal and glaucomatous groups and performed similarly to conventional global indices. Hence, the evidence-based DL model trained from PD images demonstrated that the DL model could stage glaucoma using only PD plots like Mills criteria. This automated DL model will assist clinicians in precision glaucoma detection and progression management during extensive glaucoma screening.