bluuebunny/crossref_metadata_2025_split huggingface dataset:
MDITRE: scalable and interpretable machine learning for predicting host status from temporal microbiome dynamics
Authors: Maringanti Venkata Suhas , Bucci Vanni , Gerber Georg K. 
Published: December 2021

AbstractLongitudinal microbiome datasets are being generated with increasing regularity, and there is broad recognition that these studies are critical for unlocking the mechanisms through which the microbiome impacts human health and disease. Yet, there is a dearth of computational tools for analyzing microbiome time-series data. To address this gap, we developed an open-source software package, MDITRE, which implements a new highly efficient method leveraging deep-learning technologies to derive human-interpretable rules that predict host status from longitudinal microbiome data. Using semi-synthetic and a large compendium of publicly available 16S rRNA amplicon and metagenomics sequencing datasets, we demonstrate that in almost all cases, MDITRE performs on par or better than popular uninterpretable machine learning methods, and orders-of-magnitude faster than the prior interpretable technique. MDITRE also provides a graphical user interface, which we show through use cases can readily derive biologically meaningful interpretations linking patterns of microbiome changes over time with host phenotypes.
DNA methylation in transposable elements disrupts the connection between three-dimensional chromatin organization and gene expression upon rice genome duplication
Authors: Sun Zhenfei , Wang Yunlong , Song Zhaojian , Zhang Hui , Ma Min , Wang Pan , Fang Yaping , Cai Detian , Li Guoliang , Fang Yuda 
Published: December 2021

AbstractPolyploidy serves as a major force in plant evolution and domestication of cultivated crops. However, the relationship and underlying mechanism between three-dimensional (3D) chromatin organization and gene expression upon rice genome duplication is largely unknown. Here we compared the 3D chromatin structures between diploid (2C) and autotetraploid (4C) rice by high-throughput chromosome conformation capture analysis, and found that 4C rice presents weakened intra-chromosomal interactions compared to its 2C progenitor. Moreover, we found that changes of 3D chromatin organizations including chromatin compartments, topologically associating domain (TAD) and loops uncouple from gene expression. Moreover, DNA methylations in the regulatory sequences of genes in compartment A/B switched regions and TAD boundaries are not related to their expressions. Importantly, in contrast to that there was no significant difference of methylation levels in TEs in promoters of differentially expressed genes (DEGs) and non-DEGs between 2C and 4C rice, we found that the hypermethylated transposable elements across genes in compartment A/B switched regions and TAD boundaries suppress the expression of these genes. We propose that the rice genome doubling might modulate TE methylation which results in the disconnection between the alteration of 3D chromatin structure and gene expression.
Understanding the source of METTL3-independent m6A in mRNA
Authors: Poh Hui Xian , Mirza Aashiq H. , Pickering Brian F. , Jaffrey Samie R. 
Published: December 2021

ABSTRACTN6-methyladenosine (m6A) is a highly prevalent mRNA modification which promotes degradation of transcripts encoding proteins that have roles in cell development, differentiation, and other pathways. METTL3 is the major methyltransferase that catalyzes the formation of m6A in mRNA. As 30–80% of m6A can remain in mRNA after METTL3 depletion by CRISPR/Cas9-based methods, other enzymes are thought to catalyze a sizable fraction of m6A. Here, we re-examined the source of m6A in the mRNA transcriptome. We characterized mouse embryonic stem cell lines which continue to have m6A in their mRNA after Mettl3 knockout. We show that these cells express alternatively spliced Mettl3 transcript isoforms that bypass the CRISPR/Cas9 mutations and produce functionally active methyltransferases. We similarly show that other reported METTL3 knockout cell lines express altered METTL3 proteins. We find that gene dependency datasets show that most cell lines fail to proliferate after METTL3 deletion, suggesting that reported METTL3 knockout cell lines express altered METTL3 proteins rather than have full knockout. Finally, we reassessed METTL3’s role in synthesizing m6A using a genomic deletion of Mettl3, and found that METTL3 is responsible for >95% of m6A in mRNA. Overall, these studies suggest that METTL3 is responsible for the vast majority of m6A in the transcriptome, and that remaining m6A in putative METTL3 knockout cell lines is due to the expression of altered but functional METTL3 isoforms.
The Omicron variant mutation at position 28,311 in the SARS-CoV-2 N gene does not perturb CDC N1 target detection
Authors: Bei Yanxia , Vrtis Kyle B. , Borgaro Janine G. , Langhorst Bradley W. , Nichols Nicole M. 
Published: December 2021

AbstractThe emergence of new SARS-CoV-2 variants necessitates the reevaluation of current COVID-19 tests to ensure continued accuracy and reliability. The new SARS-CoV-2 variant, Omicron, is heavily mutated, with over 50 mutations within its RNA genome. Any of these mutations could adversely affect the ability of diagnostic assays to detect the virus in patient samples, potentially leading to inconclusive or false negative results. In fact, the U.S. Food and Drug Administration (FDA) has identified over two dozen diagnostic tests that contain a gene target that is expected to have “significantly reduced sensitivity due to a mutation in the SAS-CoV-2 Omicron variant”1. Additionally, one of the U.S. Centers for Disease Control and Prevention (CDC) Emergency Use Authorization (EUA) targets for COVID-19 tests, 2019-nCoV_N1, overlaps an Omicron mutation within the sequence targeted by the fluorescent probe. This target from the CDC has been used in many other EUA assays. Using in vitro transcribed (IVT) N gene RNA representing the wild-type (GenBank/GISAID ID MN908947.3) and Omicron variant (BA.1, GISAID ID EPI_ISL_6752027), we evaluated the performance of two different amplification protocols, both of which include the CDC 2019-nCoV_N1 primer-probe set. Both assays were able to detect the mutant N1 sequence as efficiently as the wild-type sequence. Consequently, these data suggest that diagnostic assays that use the 2019-nCoV-N1 primer-probe set are unlikely to be impacted by currently circulating Omicron lineage viruses.
MIRS: an AI scoring system for predicting the prognosis and therapy of breast cancer
Authors: Huang Chen , Deng Min , Leng Dongliang , Leung Elaine Lai-Han , Sun Baoqing , Zheng Peiyan , Zhang Xiaohua Douglas 
Published: December 2021

AbstractCurrent scoring systems for prognosis of breast cancer are available but usually consider only one prognostic feature. We aim to develop a novel prognostic scoring system based on both immune-infiltration and metastatic features to not only assess the patient prognoses more accurately but also guide therapy for patients with breast cancer. Computational immune-infiltration and gene profiling analysis identified a 12-gene panel firstly characterizing immune-infiltrating and metastatic features. Neural network model yielded a precise prognostic scoring system called metastatic and immunogenomic risk score (MIRS). The influence of MIRS on the prognosis and therapy of breast cancer was then comprehensively investigated. MIRS significantly stratifies patients into high risk-group (MIRShigh) and low risk-group (MIRSlow) in both training and test cohorts. The MIRSlow patients exhibit significantly improved survival rate compared with MIRShigh patients. A series of analyses demonstrates that MIRS can well characterize the metastatic and immune landscape of breast cancer. Further analysis on the usage of MIRS in chemotherapy suggests that MIRShigh patients may benefit from three chemotherapeutic drugs (Cisplatin, Tamoxifen and Vincristine). Higher immune infiltration and significantly prolonged survival are observed in MIRSlow patients, indicating a better response in immune checkpoint inhibitor therapy. Our analysis demonstrates that MIRS could effectively improve the accuracy of prognosis for patients with breast cancer. Also, MIRS is a useful webtool, which is deposited at https://lva85.github.io/MIRS/, to help clinicians in designing personalized therapies for patients with breast cancer.
Mendelian randomization analyses clarify the effects of height on cardiovascular diseases
Authors: Hui Daniel , Sanford Eric , Lorenz Kimberly , Damrauer Scott M. , Assimes Themistocles L. , Thom Christopher S. , Voight Benjamin F. 
Published: December 2021

AbstractAn inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested causal association. However, the extent to which the effect estimated by MR can be explained by established cardiovascular risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized a well-powered set of genetic instruments for human stature, comprising >1,800 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (∼6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 0.02). However, multivariable analyses demonstrated independent effects of height on other cardiovascular traits beyond CAD, consistent with epidemiologic associations and univariable MR experiments. In contrast with published reports, we observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest the impact of height on CAD risk beyond previously established cardiovascular risk factors is minimal and not explained by lung function measures.
Human blood DNA methylation patterns reflect individual lifestyle
Authors: Klemp Ireen , Hoffmann Anne , Müller Luise , Hagemann Tobias , Horn Kathrin , Rohde-Zimmermann Kerstin , Tönjes Anke , Thiery Joachim , Löffler Markus , Burkhardt Ralph , Böttcher Yvonne , Stumvoll Michael , Blüher Matthias , Krohn Knut , Scholz Markus , Baber Ronny , Franks Paul W , Kovacs Peter , Keller Maria 
Published: December 2021

AbstractObesity is driven by modifiable lifestyle factors whose effects may be mediated by epigenetics. Therefore, we investigated lifestyle effects (diet, physical activity, smoking and alcohol) on blood DNA methylation in participants of the LIFE-Adult study, a well-characterized population-based cohort from Germany. Fifty subjects with an extremely healthy and 50 with an extremely unhealthy lifestyle were selected for genome-wide DNA methylation analysis in blood samples. Whereas obesity was only marginally related to variability in DNA methylation pattern, comparisons between lifestyle categories resulted in 145 Differentially Methylated Positions (DMPs) and 4682 Differentially Methylated Regions (DMRs) annotated to 4426 unique genes. Intersection analysis showed that diet, physical activity, smoking and alcohol intake are equally contributing to the observed differences, which particularly affects pathways related to glutamatergic synapse and axon guidance. DNA methylation patterns help discriminate individuals with a healthy vs. unhealthy lifestyle, which may mask subtle methylation differences derived from obesity.
Deficits in hospital care among clinically vulnerable children aged 0 to 4 years during the COVID-19 pandemic
Authors: Etoori David , Harron Katie , Grath-Lone Louise Mc , Verfuerden Maximiliane , Gilbert Ruth , Blackburn Ruth 
Published: December 2021

AbstractObjectiveTo quantify deficits in hospital care for clinically vulnerable children during the COVID-19 pandemic.DesignBirth cohort in Hospital Episode Statistics (HES).SettingNHS hospitals in England.Study populationAll children aged <5 years with a birth recorded in hospital administrative data (January 2010 to March 2021).Main exposureClinical vulnerability defined by a chronic health condition, preterm birth (<37 weeks gestation) or low birthweight (<2500g).Main outcomesDeficits in care defined by predicted rates for 2020, estimated from 2015- 2019, minus observed rates per 1000 child years during the pandemic (March 2020-2021).ResultsOf 3,813,465 children, 17.7% (1 in 6) were clinically vulnerable (9.5% born preterm or low birthweight, 10.3% had a chronic condition). Deficits in hospital care during the pandemic were much higher for clinically vulnerable children than peers: respectively, outpatient attendances (314 versus 73 per 1000 child years), planned admissions (55 versus 10), and unplanned admissions (105 versus 79). Clinically vulnerable children accounted for 50.1% of the deficit in outpatient attendances, 55.0% in planned admissions, and 32.8% in unplanned hospital admissions. During the pandemic, weekly rates of planned care returned to pre-pandemic levels for infants with chronic conditions but not older children. Deficits in care differed by ethnic group and level of deprivation. Virtual outpatient attendances increased from 3.2% to 24.8% during the pandemic.Conclusion1 in 6 clinically vulnerable children accounted for one-third to one half of the deficit in hospital care during the pandemic.
A Machine Learning Ensemble Based on Radiomics to Predict BI-RADS Category and Reduce the Biopsy Rate of Ultrasound-Detected Suspicious Breast Masses
Authors: Interlenghi Matteo , Salvatore Christian , Magni Veronica , Caldara Gabriele , Schiavon Elia , Cozzi Andrea , Schiaffino Simone , Carbonaro Luca Alessandro , Castiglioni Isabella , Sardanelli Francesco 
Published: December 2021

AbstractWe developed a machine learning model based on radiomics to predict the BI-RADS category of ultrasound-detected suspicious breast lesions and support medical decision making towards short-interval follow-up versus tissue sampling. From a retrospective 2015–2019 series of ultrasound-guided core needle biopsies performed by four board-cer-tified breast radiologists using six ultrasound systems from three vendors, we collected 821 images of 834 suspicious breast masses from 819 patients, 404 malignant and 430 benign according to histopathology. A balanced image set of biopsy-proven benign (n = 299) and malignant (n = 299) lesions were used for training and cross-validation of ensembles of ma-chine learning algorithms supervised during learning by histopathological diagnosis as a reference standard. Based on a majority vote (over 80% of the votes to have a valid prediction of benign lesion), an ensemble of support vector machines showed an ability to reduce the biopsy rate of benign lesions by 15% to 18%, always keeping a sensitivity over 94%, when externally tested on 236 images from two image sets: 1) 123 lesions (51 malignant and 72 benign) obtained from the same four ultrasound systems used for training, resulting into a positive predictive value (PPV) of 45.9% (95% confidence inter-val 36.3-55.7%) versus a radiologists’ PPV of 41.5% (p < 0.005), combined with a 98.0% sensitivity (89.6–99.9%); 2) 113 lesions (54 malignant and 59 benign) obtained from two ultrasound systems from vendors different from those used for training, resulting into a 50.5% PPV (40.4–60.6%) versus a radiologists’ PPV of 47.8% (p < 0.005), combined with a 94.4% sensitivity (84.6–98.8%). Errors in BI-RADS 3 category (i.e., assigned by the model as BI-RADS 4) were 0.8% and 2.7% in the Testing set I and II, respectively. The board-certified breast radiologist accepted the BI-RADS classes assigned by the model in 114 masses (92.7%) and modified the BI-RADS classes of 9 breast masses (7.3%). In 6 of 9 cases the model performed better than the radiologist, since it assigned a BI-RADS 3 classification to histopathology-confirmed benign masses that were classified as BI-RADS 4 by the radiologist.
Cash Transfer Programs and HIV-Related Outcomes: an Analysis of 42 Countries from 1996 to 2019
Authors: Richterman Aaron , Thirumurthy Harsha 
Published: December 2021

AbstractBackgroundMany low- and middle-income countries have introduced cash transfer programs as part of their poverty reduction and social protection strategies. These programs have the potential to overcome various drivers of HIV risk behaviors and usage of HIV services, but their overall effects on a broad range of HIV-related outcomes remains unknown.MethodsWe used publicly reported data to determine whether low- and middle-income countries with HIV prevalence >1% and baseline annual incidence >1/1000 had conditional or unconditional cash transfer programs that covered >5% of the impoverished population, and the year in which those programs began and ended. We obtained country- and individual-level data on HIV-related outcomes from UNAIDS and population-representative household surveys, focusing on the period between 1996 and 2019. We conducted difference-in-differences analyses with country and year fixed effects to evaluate the effects of cash transfer programs on country- and individual-level HIV-related outcomes.FindingsForty-two countries across three continents were included. Among these, 21 were in the intervention group, having implemented cash program(s) with impoverished population coverage greater than 5% during the study period. Cash transfer programs were associated with lower probability of reporting sexually transmitted infection within the last 12 months among females (odds ratio [OR] 0.67, 95% confidence interval [CI] 0.50-0.91) and higher probability of an HIV test within the last 12 months among females (OR 2.61, 95% CI 1.15-5.88) and males (OR 3.19, 95% CI 2.45-4.15). For country-level outcomes, cash transfer programs were associated with a reduction in new HIV infections (incidence rate ratio [IRR] 0.94, 95% CI 0.89-0.99), but not with the proportion of people with HIV receiving antiretroviral therapy (5.0%, 95% CI -0.2-10.1) or AIDS-related deaths (IRR 0.99, 95% CI 0.95-1.03), though temporal analyses showed delayed improvements in both antiretroviral coverage and deaths.InterpretationsCash transfer programs, which are being expanded in the context of the COVID-19 pandemic, have the potential to promote ongoing efforts to end HIV as a public health threat. Alongside the already existing focus on expanding biomedical services, these anti-poverty programs can play a greater role in achieving global targets for HIV prevention and treatment.FundingNone
Predictors of SARS-CoV-2 infection in a multi-ethnic cohort of United Kingdom healthcare workers: a prospective nationwide cohort study (UK-REACH)
Authors: Martin Christopher A. , Pan Daniel , Melbourne Carl , Teece Lucy , Aujayeb Avinash , Baggaley Rebecca F. , Bryant Luke , Carr Sue , Gregary Bindu , Gupta Amit , Guyatt Anna L. , John Catherine , McManus I Chris , Nazareth Joshua , Nellums Laura B. , Reza Rubina , Simpson Sandra , Tobin Martin D. , Woolf Katherine , Zingwe Stephen , Khunti Kamlesh , Abrams Keith R. , Gray Laura J. , Pareek Manish 
Published: December 2021

AbstractIntroductionHealthcare workers (HCWs), particularly those from ethnic minority groups, have been shown to be at disproportionately higher risk of infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) compared to the general population. However, there is insufficient evidence on how demographic and occupational factors influence infection risk among ethnic minority HCWs.MethodsWe conducted a cross-sectional analysis using data from the United Kingdom Research study into Ethnicity And COVID-19 Outcomes in Healthcare workers (UK-REACH) cohort study. We used logistic regression to examine associations of demographic, household and occupational predictor variables with SARS-CoV-2 infection (defined by PCR, serology or suspected COVID-19) in a diverse group of HCWs.Results2,496 of the 10,772 HCWs (23.2%) who worked during the first UK national lockdown in March 2020 reported previous SARS-CoV-2 infection. In an adjusted model, demographic and household factors associated with increased odds of infection included younger age, living with other key workers and higher religiosity. Important occupational risk factors associated with increased odds of infection included attending to a higher number of COVID-19 positive patients (aOR 2.49, 95%CI 2.03–3.05 for ≥21 patients per week vs none), working in a nursing or midwifery role (1.35, 1.15– 1.58, compared to doctors), reporting a lack of access to personal protective equipment (1.27, 1.15 – 1.41) and working in an ambulance (1.95, 1.52–2.50) or hospital inpatient setting (1.54, 1.37 – 1.74). Those who worked in Intensive Care Units were less likely to have been infected (0.76, 0.63–0.90) than those who did not. Black HCWs were more likely to have been infected than their White colleagues, an effect which attenuated after adjustment for other known predictors.ConclusionsWe identified key sociodemographic and occupational risk factors associated with SARS-CoV-2 infection amongst UK HCWs, and have determined factors that might contribute to a disproportionate odds of infection in HCWs from Black ethnic groups. These findings demonstrate the importance of social and occupational factors in driving ethnic disparities in COVID-19 outcomes, and should inform policies, including targeted vaccination strategies and risk assessments aimed at protecting HCWs in future waves of the COVID-19 pandemic.Trial registrationISRCTN 11811602