bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of COVID-19 Diagnosis from Healthy and Pneumonia CT scans using Convolutional Neural Networks
Authors: Srirambhatla Rushil , Karim Helmet T. 
Published: October 2022

AbstractBackgroundCurrent methods of COVID-19 detection from other respiratory illnesses using computed tomography (CT) scans are highly inaccurate. However, understanding pathogen-specific immune responses can help reduce inconsistencies and improve the accuracy of COVID-19 and Pneumonia detection. A deep learning model using Relief-based feature selection (RBAs) was developed to detect COVID-19 and Pneumonia. Patient-specific Class Activation Maps (CAMs) were produced to highlight immunopathogenic differences and identify differences between COVID-19 and Pneumonia on CT scans.MethodsTo examine the effect on lung lesions, a COVIDx CT-2 dataset, containing CT scans from 3,745 patients, was examined. We developed an algorithm to convert the 3-D CT scan of each patient into multiple 2-D slices. Altogether, there were 194,344 2-D slices retrieved from 3,745 CT Scans. The distribution of slices was 67%-20%-17% consisting of COVID-19, Pneumonia, and normal CT scan, respectively. An AlexNet architecture was implemented with additional feature extraction layers (containing RBA) and classification layers to perform deep learning. The 2-D slices were divided into 3 groups: Training, Test, and Validation. The training set consisted of 70% of the data, the test set consisted of 20% of the data, and the validation consisted of 10% of the data. After training, unique CAMs were generated on patient CT scans using the immunopathogenic differences to highlight COVID-19 and Pneumonia related abnormalities.ResultsThe model accurately distinguished hyperinflammation in COVID-19 patients from Pneumonia patients and achieved a validation accuracy of 95.60% and a false-positive rate of 4.65%. Additionally, the segmented lung, shown by the patient-specific CAMs, identified higher levels of inflammation in the lung of COVID scans compared to the other two groups.DiscussionThe use of deep learning in disease diagnosis and prevention has provided many avenues to advance current techniques. Likewise, in this analysis, deep learning was shown to successfully predict COVID-19 via CT scan. By providing patient-specific CAMs, the model can be used to not just aid in diagnosis but potentially also to evaluate serial chest CT scans for treatment.
Signs and symptoms associated with a need for supervision in patients with Alzheimer’s disease
Authors: Huey Celia C. , Kociolek Anton , Fernandez Kayri K. , Hernandez Michelle , Gottesman Reena T. , Barker Megan , Cosentino Stephanie , Stern Yaakov 
Published: October 2022

AbstractCaregivers identify the need for continuous supervision of Alzheimer’s disease patients while awake as a “milestone” functional change that has a profound impact on the lives of the caregiver and patient. The specific predictors of this important functional change are not known. We determined specific cognitive, neuropsychiatric, and motor symptoms associated with Alzheimer’s disease patients needing supervision while awake in a longitudinal, ethnically diverse cohort of Alzheimer’s disease patients in Northern Manhattan. At the initial visit, neuropsychiatric and behavioral symptoms, including more hallucinations (OR=3.12) and lower elation (OR=0.13) were associated with the need for supervision while awake, as were poor memory (OR=0.89) and higher letter fluency (OR=1.33) abilities. The findings presented in the current study can aid clinicians and caregivers in prognosis and planning, suggest symptoms to target with non-pharmacological and pharmacological treatments to forestall this important functional “milestone”, and suggest priorities for future research.Significance StatementNeed for supervision while awake is identified by caregivers of AD patients as a “milestone” symptom that greatly changes caregiving needs and quality of lifeSpecific neuropsychiatric and cognitive symptoms, including hallucinations, elation, and memory and executive dysfunction, are associated with a significantly increased or decreased need for supervision while awakeThese patient-centered findings aid prognosis and planning, and indicate symptoms to prioritize for treatment and future research to improve AD patient functioning
Multiple hypervirulent methicillin-sensitiveStaphylococcus aureuslineages contribute towards poor patient outcomes in orthopedic device-related infections
Authors: Post Virginia , Pascoe Ben , Mourkas Evangelos , Calland Jessica K. , Hitchings Matthew D. , Erichsen Christoph , Fischer Julian , Morgenstern Mario , Richards R. Geoff , Sheppard Samuel K. , Moriarty T. Fintan 
Published: October 2022

AbstractStaphylococci are the most common cause of orthopedic device-related infections (ODRIs), withStaphylococcus aureusresponsible for a third or more of cases. This prospective clinical and laboratory study investigated the association of genomic and phenotypic variation with treatment outcomes in ODRI isolates. Eighty-six invasiveS. aureusisolates were collected from patients with ODRI, and clinical outcome was assessed after a follow-up examination of 24 months. Each patient was then considered to have been “cured” or “not cured” based on predefined clinical criteria. Whole genome sequencing and molecular characterization identified isolates belonging to globally circulating community- and hospital-acquired pandemic lineages. Most isolates were phenotypically susceptible to methicillin and lacked the SCCmeccassette (MSSA), but contained several (hyper) virulence genes, including toxins and biofilm genes. While recognizing the role of the host immune response, we identify characteristics of isolate genomes that, with larger datasets, could help contribute to infection severity or clinical outcome predictions. While this and several other studies reinforce the role antibiotic resistance (e.g., MRSA infection) has on treatment failure, it is important not to overlook MSSA that can cause equally destructive infections and lead to poor patient outcomes.ImportanceStaphylococcus aureusis a prominent cause of orthopedic device-associated infections, yet little is known about how the infecting pathogen, and specifically the repertoire of genome-encoded virulence factors can impact treatment outcome. Past studies have focused on distinguishing commensal from invasiveS. aureusisolates but in this study, we aim to investigate traits in infecting isolates that influence patient outcomes. InvasiveS. aureusisolates were collected from orthopedic-device related infection patients and categorized according to the success of subsequent treatment (“cured” /”not cured”), as determined following hospital discharge two years after initial presentation. Several MSSA hypervirulent clones were associated with a “not cured” clinical outcome. Improved understanding of the bacterial traits associated with treatment failure in ODRI will inform the risk assessment, prognosis, and therapy of these infections.
Robust Machine Learning predicts COVID-19 Disease Severity based on Single-cell RNA-seq from multiple hospitals
Authors: Lemsara Amina , Chan Adrian , Wolff Dominik , Marschollek Michael , Li Yang , Dieterich Christoph 
Published: October 2022

AbstractCoronavirus disease 2019 (COVID-19) has a highly variable disease severity. Possible associations between peripheral blood signatures and disease severity have been investigated since the emergence of the pandemic. Although several signatures were identified based on exploratory analyses of single-cell omics data, there are no state-of-the-art validated models to predict COVID-19 severity from comprehensive transcriptome profiling of Peripheral Blood Mononuclear Cells (PBMCs). In this paper, we present a computational workflow based on a Multilayer perceptron network that predicts the necessity of mechanical ventilation from PBMCs single-cell RNA-seq data. The study includes patient cohorts from Bonn, Berlin, Stanford, and three Korean medical centers. Training and model validation are performed using Berlin and Bonn samples, while testing is performed on completely unseen samples from the Stanford and Korean datasets. Our model shows a high area under the receiver operating characteristic (AUROC) curve (Korea: 1 (CI:1-1), Stanford: 0.86 (CI:0.81-0.9)), proving our model’s robustness. Moreover, we explain our model’s performance by identifying gene loci and cell types, which are most critical for the classification task. In summary, we could show that the expression of 15 genes and the cell type proportion of 29 PBMC classes distinguish between COVID-19 disease states.Graphical Abstract
Meta-analysis of genotype-phenotype associations in Alström syndrome
Authors: Bea-Mascato Brais , Valverde Diana 
Published: October 2022

AbstractIntroductionAlström syndrome (ALMS, #203800) is an ultra-rare monogenic recessive disease. This the syndrome is associated with mutations in theALMS1gene, which codes for a centrosome structural protein responsible for centrosome cohesion. The type of mutation associated with ALMS is mostly cLOF (97%) and they are mainly located in exons 8, 10 and 16 of the gene. Other studies in the literature have tried to establish a genotype-phenotype correlation in this syndrome with little success. The difficulty in recruiting a large cohort in rare diseases is the main barrier to conducting this type of study.MethodsIn this study we have collected all cases published to date for ALMS. We have created a database with those patients who had a genetic diagnosis and an individualised clinical history. Finally, we have attempted to establish a genotype-phenotype correlation using the truncation site of the patient’s longest allele as a grouping criterion.ResultsWe collected a total of 357 patients of which 227 had complete clinical information, complete genetic diagnosis and meta information regarding sex and age. We have seen that there are 5 variants in high frequency with p.(Arg2722Ter) being the most common variant with 28 alleles. There are no gender differences in disease progression. Finally, truncating mutations in exon 10 seem to be correlated with a higher prevalence of liver disorders in patients with ALMS.ConclusionThe location of the mutation in theALMS1gene does not have a major impact on the phenotype developed by the patient. Only mutations in exon 10 of theALMS1gene were associated with a higher prevalence of liver disease.
Retina-arrestin is not a CD8+ T-cell autoantigen in HLA-A29-positive birdshot chorioretinitis
Authors: Venema W.J. , Hiddingh S. , Janssen G.M.C. , Ossewaarde J. , van Loon N. Dam , de Boer J.H. , van Veelen P.A. , Kuiper J.J.W. 
Published: October 2022

ABSTRACTBackgroundHLA-A29-positivebirdshot chorioretinitis(BCR) is an inflammatory eye disorder that is generally assumed to be caused by an autoimmune response to HLA-A29-presented peptides from retinal arrestin (SAG), yet the epitopes recognized by CD8+ T cells from patients remain to be identified.ObjectivesThe identification of natural ligands of SAG presented by HLA-A29. To quantify CD8+ T cells reactive to antigenic SAG peptides presented by HLA-A29 in patients and controls.MethodsWe performed mass-spectrometry based immunopeptidomics of HLA-A29 of antigen-presenting cell lines from patients engineered to express SAG. MHC-I Dextramer technology was utilised to identify antigen-specific CD8+ T cells reactive to SAG peptides in complex with HLA-A29 in a cohort of BCR patients, HLA-A29-positive controls, and HLA-A29-negative controls.ResultsWe report on the naturally presented antigenic SAG peptides identified by sequencing the HLA-A29 immunopeptidome of antigen-presenting cells of patients. We show that the N-terminally extended SAG peptide precursors can be trimmedin vitroby the antigen-processing aminopeptidases ERAP1 and ERAP2. Unexpectedly, no antigen engagement by CD8+ T cells upon stimulation with SAG peptides was observed in patients or HLA-A29-positive controls. Multiplexed HLA-A29-peptide dextramer profiling of a case-control cohort revealed that CD8+ T cells specific for these SAG peptides were neither detectable in peripheral blood nor in eye biopsies of patients.ConclusionsCollectively, these findings demonstrate that SAG is not a CD8+ T cell autoantigen and sharply contrast the paradigm in the pathogenesis of BCR. Therefore, the mechanism by which HLA-A29 is associated with BCR does not involve SAG.
Receipt of COVID-19 and seasonal influenza vaccines in California (USA) during the 2021-2022 influenza season
Authors: Andrejko Kristin L. , Myers Jennifer F. , Openshaw John , Fukui Nozomi , Li Sophia , Watt James P. , Murray Erin L. , Hoover Cora , Lewnard Joseph A. , Jain Seema , Pry Jake M. 
Published: October 2022

ABSTRACTBackgroundDespite lower circulation of influenza virus throughout 2020–2022 during the COVID-19 pandemic, seasonal influenza vaccination has remained a primary tool to reduce influenza-associated illness and death. The relationship between the decision to receive a COVID-19 vaccine and/or an influenza vaccine is not well understood.MethodsWe assessed predictors of receipt of 2021–2022 influenza vaccine in a secondary analysis of data from a case-control study enrolling individuals who received SARS-CoV-2 testing. We used mixed effects logistic regression to estimate factors associated with receipt of seasonal influenza vaccine. We also constructed multinomial adjusted marginal probability models of being vaccinated for COVID-19 only, seasonal influenza only, or both as compared with receipt of neither vaccination.ResultsAmong 1261 eligible participants recruited between 22 October 2021 – 22 June 2022, 43% (545) were vaccinated with both seasonal influenza vaccine and ≥1 dose of a COVID-19 vaccine, 34% (426) received ≥1 dose of a COVID-19 vaccine only, 4% (49) received seasonal influenza vaccine only, and 19% (241) received neither vaccine. Receipt of ≥1 COVID-19 vaccine dose was associated with seasonal influenza vaccination (adjusted odds ratio [aOR]: 3.72; 95% confidence interval [CI]: 2.15–6.43); this association was stronger among participants receiving ≥1 COVID-19 booster dose (aOR=16.50 [10.10– 26.97]). Compared with participants testing negative for SARS-CoV-2 infection, participants testing positive had lower odds of receipt of 2021-2022 seasonal influenza vaccine (aOR=0.64 [0.50–0.82]).ConclusionsRecipients of a COVID-19 vaccine were more likely to receive seasonal influenza vaccine during the 2021–2022 season. Factors associated with individuals’ likelihood of receiving COVID-19 and seasonal influenza vaccines will be important to account for in future studies of vaccine effectiveness against both conditions. Participants who tested positive for SARS-CoV-2 in our sample were less likely to have received seasonal influenza vaccine, suggesting an opportunity to offer influenza vaccination before or after a COVID-19 diagnosis.
Applying Machine Learning to Blood Count Data Predicts Sepsis with ICU Admission
Authors: Ahrens Paul C. , Steinbach Daniel , Schmidt Maria , Federbusch Martin , Heuft Lara , Lübbert Christoph , Nauck Matthias , Gründling Matthias , Isermann Berend , Gibb Sebastian , Kaiser Thorsten 
Published: October 2022

AbstractBackgroundDelay in diagnosing sepsis results in potentially preventable deaths. Mainly due to their complexity or limited applicability, machine learning (ML) models to predict sepsis have not yet become part of clinical routines. For this reason, we created a ML model that only requires complete blood count (CBC) diagnostics.MethodsNon-intensive care unit (non-ICU) data from a German tertiary care centre were collected from January 2014 to December 2021. Patient age, sex, and CBC parameters (haemoglobin, platelets, mean corpuscular volume, white and red blood cells) were utilised to train a boosted random forest, which predicts sepsis with ICU admission. Two external validations were conducted using data from another German tertiary care centre and the Medical Information Mart for Intensive Care IV database (MIMIC-IV). Using the subset of laboratory orders also including procalcitonin (PCT), an analogous model was trained with PCT as an additional feature.FindingsAfter exclusion, 1,381,358 laboratory requests (2016 from sepsis cases) were available. The derived CBC model shows an area under the receiver operating characteristic (AUROC) of 0.872 (95% CI, 0.857–0.887) for predicting sepsis. External validations show AUROCs of 0.805 (95% CI, 0.787–0.824) and 0.845 (95% CI, 0.837–0.852) for MIMIC-IV. The model including PCT revealed a significantly higher performance (AUROC: 0.857; 95% CI, 0.836–0.877) than PCT alone (AUROC: 0.790; 95% CI, 0.759–0.821; p<0.001).InterpretationOur results demonstrate that routine CBC results could significantly improve diagnosis of sepsis when combined with ML. The CBC model can facilitate early sepsis prediction in non-ICU patients with high robustness in external validations. Its implementation in clinical decision support systems has strong potential to provide an essential time advantage and increase patient safety.FundingThe study was part of the AMPEL project (www.ampel.care), which is co-financed through public funds according to the budget decided by the Saxon State Parliament under the RL eHealthSax 2017/18 grant number 100331796.
Possible harms ofMomordica charantia L. in humans; a systematic review
Authors: Demmers Armelle , Mes Jurriaan J. , Elbers Roy G. , Pieters Raymond HH 
Published: October 2022

AbstractIntroductionA few cases of serious side effects have been reported of Momordica charantia L. (MC). No comprehensive safety assessment has yet been performed based on human intake.This systematic review aims to evaluate the potential harm of Momordica charantia L. derived products using data from randomized controlled trials.MethodsDatabases Cochrane Library, Pubmed and EMBASE were searched until December 2020. The PRISMA harms checklist was followed. Data extraction was on aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine, adverse effects (AE), reasons for drop out related to the intervention and interaction with other treatment. Two authors independently extracted data and bias was evaluated based on the latest version of the Cochrane risk of Bias Tool (RoB 2). Additional safety data were requested from Health Regulatory Agencies, Herbal Medicine Associations and manufacturers.ResultsSeventeen trials met the inclusion criteria. The IRR was calculated for each study ranging from 0.30 (95% CI = 0.12 to 0.75) to 13.00 (95% CI = 0.73 to 230.76) of any adverse events.ConclusionsUnder a daily dosage of 6g of MC-derived products no evidence was seen of harms in humans. In case reports that showed serious harm, MC was used in a liquid form. The safety of traditional MC-based supplements appears more guaranteed when produced under strict quality standards.
Clinical criteria for genetic testing in pediatric oncology show a low specificity and miss every 4thchild carrying a cancer predisposition
Authors: Friedrich Ulrike Anne , Bienias Marc , Zinke Claudia , Prazenicova Maria , Lohse Judith , Jahn Arne , Menzel Maria , Langanke Jonas , Walter Carolin , Wagener Rabea , Brozou Triantafyllia , Varghese Julian , Dugas Martin , Schröck Evelin , Suttorp Meinolf , Borkhardt Arndt , Hauer Julia , Auer Franziska 
Published: October 2022

AbstractClinical checklists are the current gold standard to determine whether a child with cancer shows indications for genetic testing. Nevertheless, the efficacy of these tests to reliably detect genetic cancer predisposition in children with cancer is still insufficiently investigated. Here, we assessed the validity of clinically recognizable signs to identify cancer predisposition by correlating a state-of-the-art clinical checklist to the corresponding whole exome sequencing analysis in an unselected single-center cohort of 139 child-parent datasets. We applied a strict testing to only include autosomal dominant or compound heterozygous cancer-related variants.Our study reflects a high consent rate for genetic testing (>90%). In total, 1/3rdof patients had a clinical indication for genetic testing according to current recommendations and 10.8% (n=15/139) of children harbored a proven cancer predisposition based on exome sequencing. Out of these only 73.3% (n=11/15) were identified through the clinical checklist. In addition, >2 clinical findings in the applied checklist increased the likelihood to identifying genetic predisposition from 15% to 50%. While our data revealed a high rate of genetic predisposition (50%, n=5/10) in Myelodysplastic Syndrome (MDS) cases, no cancer predisposition variants were identified in the sarcoma and lymphoma group.In summary, our data showed a low checklist specificity of 68.5%, and missed every 4thchild with genetic predisposition. This highlights the drawbacks of sole clinical evaluation to accurately identify all children at risk and underlines the need for routine germline sequencing of pediatric cancers.
An Adjudication Protocol for Severe Bacterial and Viral Pneumonia
Authors: Pickens Chiagozie I. , Gao Catherine A. , Walter James M. , Kruser Jacqueline M. , Donnelly Helen K. , Donayre Alvaro , Clepp Katie , Borkowski Nicole , Wunderink Richard G. , Singer Benjamin D. ,   The NU SCRIPT Study Investigators
Published: October 2022

AbstractRationaleClinical endpoints that constitute successful treatment in severe pneumonia are difficult to ascertain and vulnerable to bias. Utility of a protocolized adjudication procedure to determine meaningful endpoints in severe pneumonia is not well described.ObjectivesTo develop and validate a protocol for classification and adjudication of clinical endpoints in severe bacterial and viral pneumonia in a prospective cohort of critically ill, mechanically ventilated patients.MethodsEach episode of pneumonia was independently reviewed by two of six pulmonary and critical care physician adjudicators. If a discrepancy in at least one critical answer occurred between the two adjudicators, a third adjudicator reviewed the case and answered the specific question(s) for which there was a lack of agreement. If discrepancy remained after all three adjudications, consensus was achieved through committee review.ResultsEvaluation of 784 pneumonia episodes during 593 hospitalizations achieved a 79% crude rate of interobserver agreement defined as agreement between 2 of 3 reviewers. Culture-negative pneumonia was associated with increased interobserver agreement. Multiple episodes of pneumonia and bacterial and viral co-infection in the initial episode of pneumonia were associated with decreased interobserver agreement. For bacterial pneumonia, patients with an adjudicated day 7-8 clinical impression of cure for the initial episode of pneumonia were more likely to be discharged alive compared to patients with a day 7-8 clinical impression of indeterminate (p < 0.01), superinfection (p = 0.03), or a combined impression of persistence and superinfection (p = 0.04). In viral pneumonia, patients with an adjudicated clinical impression of cure for an initial episode of viral pneumonia were more likely to be discharged alive compared to patients with an adjudicated clinical impression of persistence (p < 0.01), indeterminate (p < 0.01), or bacterial superinfection (p < 0.01).ConclusionsWe developed and validated a protocol for classification and adjudication of clinical endpoints in severe pneumonia. This protocol can be applied to cohorts of patients with severe pneumonia to provide uniform assessment of patient-centered endpoints.