tbuckley/cabot-search huggingface dataset:
Counties with High COVID-19 Incidence and Relatively Large Racial and Ethnic Minority Populations — United States, April 1–December 22, 2020
Authors: Florence C. Lee, Laura Adams, Sierra J. Graves, Greta M. Massetti, Renee M. Calanan, Ana Penman-Aguilar, S. Jane Henley, Francis B. Annor, Michelle Van Handel, Noah Aleshire, Tonji Durant, Jennifer Fuld, Sean Griffing, Laura Mattocks, Leandris Liburd
Journal: MMWR Morbidity and Mortality Weekly Report (2021)

Long-standing systemic social, economic, and environmental inequities in the United States have put many communities of color (racial and ethnic minority groups) at increased risk for exposure to and infection with SARS-CoV-2, the virus that causes COVID-19, as well as more severe COVID-19-related outcomes (1-3). Because race and ethnicity are missing for a proportion of reported COVID-19 cases, counties with substantial missing information often are excluded from analyses of disparities (4). Thus, as a complement to these case-based analyses, population-based studies can help direct public health interventions. Using data from the 50 states and the District of Columbia (DC), CDC identified counties where five racial and ethnic minority groups (Hispanic or Latino [Hispanic], non-Hispanic Black or African American [Black], non-Hispanic Asian [Asian], non-Hispanic American Indian or Alaska Native [AI/AN], and non-Hispanic Native Hawaiian or other Pacific Islander [NH/PI]) might have experienced high COVID-19 impact during April 1-December 22, 2020. These counties had high 2-week COVID-19 incidences (>100 new cases per 100,000 persons in the total population) and percentages of persons in five racial and ethnic groups that were larger than the national percentages (denoted as large). During April 1-14, a total of 359 (11.4%) of 3,142 U.S. counties reported high COVID-19 incidence, including 28.7% of counties with large percentages of Asian persons and 27.9% of counties with large percentages of Black persons. During August 5-18, high COVID-19 incidence was reported by 2,034 (64.7%) counties, including 92.4% of counties with large percentages of Black persons and 74.5% of counties with large percentages of Hispanic persons. During December 9-22, high COVID-19 incidence was reported by 3,114 (99.1%) counties, including >95% of those with large percentages of persons in each of the five racial and ethnic minority groups. The findings of this population-based analysis complement those of case-based analyses. In jurisdictions with substantial missing race and ethnicity information, this method could be applied to smaller geographic areas, to identify communities of color that might be experiencing high potential COVID-19 impact. As areas with high rates of new infection change over time, public health efforts can be tailored to the needs of communities of color as the pandemic evolves and integrated with longer-term plans to improve health equity.
P78.09 Immunotherapy Beyond Progression for Patients with Advanced Non-Small Cell Lung Cancer
Authors: X. Ge, Z. Zhang, X. Yan, F. Zhang, F. Yuan, X. Han, Z. Huang, J. Ma, L. Wang, H. Tao, X. Li, S. Zhang, X. Zhi, Y. Hu, J. Wang
Journal: Journal of Thoracic Oncology (2021)
Uranium Exposure in American Indian Communities: Health, Policy, and the Way Forward
Authors: Nicole Redvers, Ann Marie Chischilly, Donald Warne, Manuel Pino, Amber Lyon-Colbert
Journal: Environmental Health Perspectives (2021)

Background: Uranium contamination of drinking-water sources on American Indian (AI) reservations in the United States is a largely ignored and underfunded public health crisis. With an estimated 40% of the headwaters in the western U.S. watershed, home to many AI reservation communities, being contaminated with untreated mine waste, the potential health effects have largely been unexplored. With AI populations already facing continued and progressive economic and social marginalization, higher prevalence of chronic disease, and systemic discrimination, associations between various toxicant exposures, including uranium, and various chronic conditions, need further examination. Objectives: Uranium's health effects, in addition to considerations for uranium drinking-water testing, reporting, and mitigation in reference to AI communities through the lens of water quality, is reviewed. Discussion: A series of environmental health policy recommendations are described with the intent to proactively improve responsiveness to the water quality crisis in AI reservation communities in the United States specific to uranium. There is a serious and immediate need for better coordination of uranium-related drinking-water testing and reporting on reservations in the United States that will better support and guide best practices for uranium mitigation efforts. https://doi.org/10.1289/EHP7537
Blockade of IL-22 signaling reverses erythroid dysfunction in stress-induced anemias
Authors: Mahesh Raundhal, Shrestha Ghosh, Samuel A. Myers, Michael S. Cuoco, Meromit Singer, Steven A. Carr, Sushrut S. Waikar, Joseph V. Bonventre, Jerome Ritz, Richard M. Stone, David P. Steensma, Aviv Regev, Laurie H. Glimcher
Journal: Nature Immunology (2021)
The first and second waves of the COVID-19 pandemic in Africa: a cross-sectional study
Authors: Stephanie J Salyer, Justin Maeda, Senga Sembuche, Yenew Kebede, Akhona Tshangela, Mohamed Moussif, Chikwe Ihekweazu, Natalie Mayet, Ebba Abate, Ahmed Ogwell Ouma, John Nkengasong
Journal: The Lancet (2021)

Although the first wave of the COVID-19 pandemic progressed more slowly in Africa than the rest of the world, by December, 2020, the second wave appeared to be much more aggressive with many more cases. To date, the pandemic situation in all 55 African Union (AU) Member States has not been comprehensively reviewed. We aimed to evaluate reported COVID-19 epidemiology data to better understand the pandemic's progression in Africa.
Nuisance or necessity? Why robust peer review is critical for medical science
Authors: Jon Patricios, Joanne Kemp, Jane S Thornton, Jonathan Drezner
Journal: British Journal of Sports Medicine (2021)

<h3>Introduction</h3> Currently the Quality of Work Life (QWL) and psychosocial risks are identified as important indicators of health in workers, it is important to carry out studies that can describe the behaviour of them in organisations. The aim was to analyse the relationship between QWL and the presence of symptoms of depression or anxiety in the administrative female employees of a public university in Mexico. <h3>Methods</h3> These study was performed with a universe of 6455 employees and a probabilistic sample of 225 people. They all were applied the CVT-GOHISALO and Goldberg's depression and anxiety questionnaires to measure their QWL and the presence of depression or anxiety symptoms. The Cronbach's Alpha of CVT-GOHISALO is 0.9527 and the Goldberg's depression and anxiety scale is 0.89. <h3>Results</h3> Only in one of the seven dimensions of CVT-GOHISALO instrument, the highest percentage of satisfaction was of high level, 49.3%, in all other dimensions the highest percentage of satisfaction was of low level. As for the presence of depression symptoms, 20.9% of the employees had them and anxiety symptoms occurred in 59.1%. In all dimensions, the higher satisfaction with the QWL and the absence of depression or anxiety symptoms were related. As well as low and medium level of satisfaction with the presence of depression or anxiety symptoms. All crosses were statistically significant, with p values for each dimension ranging between 0.000–0.046. <h3>Conclusions</h3> To the university administrative staff, there is a relationship between being satisfied with the QWL and the absence of depression or anxiety symptoms. High satisfaction with QWL, is a protective factor for not having depression or anxiety symptoms. The risk of developing depression or anxiety symptoms, is four times higher for those with low satisfaction level with their QWL than for those who have high satisfaction level.
Abstract 17367: Propitious Temporal Changes in Clinical Outcomes After Transcatheter Compared to Surgical Aortic Valve Replacement; A Meta-Analysis
Authors: Ankur Panchal, Andreas Kyvernitakis, Mark Doyle, Robert W Biederman
Journal: Circulation (2020)

Introduction: Treatment for severe aortic stenosis has rapidly evolved over the past decade, in both transcatheter aortic valve replacement (TAVR) technique and surgical aortic valve replacement (SAVR), resulting in improved clinical outcomes. We sought to determine and compare the temporal changes and 1-year outcomes between these groups. Methods: We searched the Medline MESH database using the keywords “aortic stenosis”, “atrial fibrillation” and “stroke”. We performed a meta-analysis and created funnel plots to compare TAVR with SAVR population for post-procedural stroke, all-cause and cardiovascular (CV) mortality at 1-year. Results: Out of &gt;50 studies, we included 20 meeting criteria for analysis with total population of &gt;65000 patients, of which 61067 had TAVR and 4162 had SAVR. AFib prevalence was higher in TAVR vs SAVR patients (38% vs 27%; p&lt; 0.0001). By funnel plotting, post-procedural stroke at 1-year was 3.1% in TAVR and 5% in SAVR patients (NS). All-cause mortality at 1 year was 12.5% in TAVR and 10.3 % in SAVR patients, and CV mortality at 1-year was 7.4% in TAVR and 6.2% in SAVR patients (NS for both). Conclusion: While there is a trend over the last 14 years for overall improvement in both SAVR and TAVR outcomes, via meta-analysis, despite a higher prevalence of AFib in TAVR vs SAVR, there is statistical overlap in the confidence intervals supporting no distinct separation in stroke risk, all-cause mortality or adjudicated CV mortality at 1 year between groups. To our knowledge, this represents the largest study over the longest time period that points towards potential benefit at the individual level but as a socio-economic consideration, no distinction between SAVR vs TAVR.
Coffee Consumption and Colorectal Cancer Prognosis
Authors: Irena T. Tan, Albert Y. Lin
Journal: JAMA Oncology (2021)

Our website uses cookies to enhance your experience. By continuing to use our site, or clicking "Continue," you are agreeing to our Cookie Policy | Continue JAMA Oncology HomeNew OnlineCurrent IssueFor Authors Podcast Publications JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry (1919-1959) JN Learning / CMESubscribeJobsInstitutions / LibrariansReprints & Permissions Terms of Use | Privacy Policy | Accessibility Statement 2023 American Medical Association. All Rights Reserved Search All JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Forum Archive JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry Input Search Term Sign In Individual Sign In Sign inCreate an Account Access through your institution Sign In Purchase Options: Buy this article Rent this article Subscribe to the JAMA Oncology journal
ZFTA–RELA Dictates Oncogenic Transcriptional Programs to Drive Aggressive Supratentorial Ependymoma
Authors: Amir Arabzade, Yanhua Zhao, Srinidhi Varadharajan, Hsiao-Chi Chen, Selin Jessa, Bryan Rivas, Austin J. Stuckert, Minerva Solis, Alisha Kardian, Dana Tlais, Brian J. Golbourn, Ann-Catherine J. Stanton, Yuen San Chan, Calla Olson, Kristen L. Karlin, Kathleen Kong, Robert Kupp, Baoli Hu, Sarah G. Injac, Madeline Ngo, Peter R. Wang, Luz A. De León, Felix Sahm, Daisuke Kawauchi, Stefan M. Pfister, Charles Y. Lin, H. Courtney Hodges, Irtisha Singh, Thomas F. Westbrook, Murali M. Chintagumpala, Susan M. Blaney, Donald W. Parsons, Kristian W. Pajtler, Sameer Agnihotri, Richard J. Gilbertson, Joanna Yi, Nada Jabado, Claudia L. Kleinman, Kelsey C. Bertrand, Benjamin Deneen, Stephen C. Mack
Journal: Cancer Discovery (2021)

Abstract More than 60% of supratentorial ependymomas harbor a ZFTA–RELA (ZRfus) gene fusion (formerly C11orf95–RELA). To study the biology of ZRfus, we developed an autochthonous mouse tumor model using in utero electroporation (IUE) of the embryonic mouse brain. Integrative epigenomic and transcriptomic mapping was performed on IUE-driven ZRfus tumors by CUT&amp;RUN, chromatin immunoprecipitation sequencing, assay for transposase-accessible chromatin sequencing, and RNA sequencing and compared with human ZRfus-driven ependymoma. In addition to direct canonical NFκB pathway activation, ZRfus dictates a neoplastic transcriptional program and binds to thousands of unique sites across the genome that are enriched with PLAGL family transcription factor (TF) motifs. ZRfus activates gene expression programs through recruitment of transcriptional coactivators (Brd4, Ep300, Cbp, Pol2) that are amenable to pharmacologic inhibition. Downstream ZRfus target genes converge on developmental programs marked by PLAGL TF proteins, and activate neoplastic programs enriched in Mapk, focal adhesion, and gene imprinting networks. Significance: Ependymomas are aggressive brain tumors. Although drivers of supratentorial ependymoma (ZFTA- and YAP1-associated gene fusions) have been discovered, their functions remain unclear. Our study investigates the biology of ZFTA–RELA-driven ependymoma, specifically mechanisms of transcriptional deregulation and direct downstream gene networks that may be leveraged for potential therapeutic testing. This article is highlighted in the In This Issue feature, p. 2113
Radiotherapy after Oesophageal Cancer Stenting (ROCS): a randomised controlled trial of palliative radiotherapy in preventing post stent dysphagia deterioration in patients with advanced oesophageal cancer
Authors: Douglas Adamson, Anthony Byrne, Catharine Porter, Jane M Blazeby, Gareth Griffiths, Annmarie Nelson, Bernadette Sewell, Mari Jones, Martina Svobodova, Deborah Fitzsimmons, Lisette Nixon, Jim Fitzgibbon, Stephen Thomas, Anthony Millen, Tom Crosby, John Staffurth, Christopher Hurt
Journal: The Lancet. Gastroenterology & hepatology (2020)
Prioritising Para athlete care
Authors: Jon Patricios, Nick Webborn
Journal: British Journal of Sports Medicine (2021)

‘Para’ is derived from the Greek word παράλληλα and is a medical prefix meaning ‘alongside’ (cf. parathyroid). Hence, the Paralympics takes place ‘alongside’ the Olympic Games. Since the first Paralympic Games in Rome 1960, the event has grown from 400 athletes from 23 countries to become the third largest sporting event in the world with over 4328 athletes representing 159 countries in Rio 2016.1 Paralympic Games comprise 22 summer sports and 6 winter sports with participation by athletes with a diverse range of physical, sensory and cognitive impairments. However, the science and medicine needed to support these athletes have evolved more slowly. In 1992, there were just nine articles in a PubMed search of the entire literature relating to ‘Disability or Paralympic Sport’. Over the last decade, that same search reveals 590 articles, and 101 in the last year, but the breadth of authorship and expertise is narrow. As clinicians and scientists, how do we enhance care of the Para athlete, the International Paralympic Committee‘s term for an athlete with a disability, and encourage further expansion of the scientific literature to provide an evidence-based approach?

We propose four key interventions, abbreviated to the acronym CARE, that may elevate the standard of sport and exercise medicine for athletes with disability.

With the emergence of Sport and Exercise Medicine …
Prognostic Value of ER and PgR Expression and the Impact of Multi-clonal Expression for Recurrence in Ductal Carcinoma <i>in situ</i>: Results from the UK/ANZ DCIS Trial
Authors: Mangesh A. Thorat, Pauline M. Levey, J. Louise Jones, Sarah E. Pinder, Nigel J. Bundred, Ian S. Fentiman, Jack Cuzick
Journal: Clinical Cancer Research (2021)

Abstract Purpose: The prognostic value of estrogen receptor (ER)/progesterone receptor (PgR) expression in ductal carcinoma in situ (DCIS) is unclear. We observed multi-clonality when evaluating ER/PgR expression in the UK/ANZ DCIS trial, therefore, we investigated the prognostic role of both uni-clonal and multi-clonal ER/PgR expression in DCIS. Experimental Design: Formalin-fixed paraffin embedded tissues were collected from UK/ANZ DCIS trial participants (n = 755), and ER/PgR expression was evaluated by IHC in 181 cases (with recurrence) matched to 362 controls by treatment arm and age. Assays were scored by the Allred method and by a newly devised clonal method—analyses categorizing multi-clonal DCIS as ER/PgR-positive as per current practice (Standard) and as ER/PgR-negative (clonal) were performed. Results: ER expression was multi-clonal in 11% (39/356) of ER-positive (70.6%, 356/504) patients. Ipsilateral breast event (IBE) risk was similarly higher in ER-multi-clonal and ER-negative DCIS as compared with DCIS with uni-clonal ER expression. ER-negative DCIS (clonal) had a higher risk of in situ IBE [OR 4.99; 95% confidence interval (CI), 2.66–9.36; P &amp;lt; 0.0001], but the risk of invasive IBE was not significantly higher (OR 1.72; 95% CI, 0.84–3.53; P = 0.14), Pheterogeneity = 0.03. ER was an independent predictor in multivariate analyses (OR 2.66; 95% CI, 1.53–4.61). PgR status did not add to the prognostic information provided by ER. Conclusions: ER expression is a strong predictor of ipsilateral recurrence risk in DCIS. ER-positive DCIS with distinct ER-negative clones has a recurrence risk similar to ER-negative DCIS. ER should be routinely assessed in DCIS, and ER scoring should take clonality of expression into account.
Importance of artificial intelligence, machine learning deep learning in the field of medicine on the future role of the physician
Authors: S. Kumar
Journal: Clinical Cancer Research (2021)

There are many ways to define the field of Artificial Intelligence  Here is one way for Artificial Intelligence is  Study of the computations that make it possible to perceive, reason, act and predict the future possible outcomes  Deep learning, which is a popular research area of artificial intelligence (AI), enables the creation of end-to-end models to achieve promised results using input data  Deep learning techniques have been successfully applied in many problems such as arrhythmia detection, skin cancer classification, breast cancer detection, brain disease classification, pneumonia detection, COVID-19 from chest X-ray images, and CT scan images  Almost all hospitals have CT imaging machines;therefore, the chest CT images can be utilized for early classification of diseases  However, the chest CT classification involves a radiology expert and considerable time, which is valuable when any infection is growing at a rapid rate  Therefore, automated analysis of chest CT images is desirable to save the medical professionals precious time that shows the importance of Artificial Intelligence neural networks which is used to classify the infected patients as infected (+ve) or not (-ve)  There is a vital need to detect the disease at an early stage and save the patient from the disease  Convolutional neural networks (CNN) are a powerful tool that comes under the platform of Neural Networks Artificial Intelligence inspired by the human brain, which is extensively utilized for image classification  The hierarchical structure and efficient feature extraction characteristics from an image make CNN a dynamic model for image classification  Initially, the layers are organized into three dimensions: width, height, and depth  The neurons in a given layer do not attach to the entire set of neurons in the later layer, but only to limited neurons of it  Finally, the output is diminished to a single vector of probability scores, coordinated alongside the depth dimension  In a Convolutional Neural Network, the linear function that is used is called a convolutional layer  Each node in the hidden layer extracts different features by using image processing feature detectors  For example, in the first layer, the first node may extract the horizontal edges of an image, the second node may extract vertical edges and etc  These features are extracted using a kernel  The bottom is the original image and the top is the output of the convolutions  It is also worth noting that the output of the convolutions reduces the dimension of the original image, The next step the pooling layer happens tends to be computed after the convolutional layer  The reason why pooling is done is to further reduce the dimensions of the convolutional layer and just extract out the features to make the model more robust  AI could help to rapidly diagnose diseases if proper attention given in collecting the data
Respiratory Support During the COVID-19 Pandemic
Authors: Laveena Munshi, Jesse B. Hall
Journal: JAMA (2021)

Domenico Luca Grieco, MD; Luca S. Menga, MD; Melania Cesarano, MD; Tommaso Rosà, MD; Savino Spadaro, MD, PhD; Maria Maddalena Bitondo, MD; Jonathan Montomoli, MD, PhD; Giulia Falò, MD; Tommaso Tonetti, MD; Salvatore L. Cutuli, MD; Gabriele Pintaudi, MD; Eloisa S. Tanzarella, MD; Edoardo Piervincenzi, MD; Filippo Bongiovanni, MD; Antonio M. Dell'Anna, MD; Luca Delle Cese, MD; Cecilia Berardi, MD; Simone Carelli, MD; Maria Grazia Bocci, MD; Luca Montini, MD; Giuseppe Bello, MD; Daniele Natalini, MD; Gennaro De Pascale, MD; Matteo Velardo, PhD; Carlo Alberto Volta, MD; V. Marco Ranieri, MD; Giorgio Conti, MD; Salvatore Maurizio Maggiore, MD, PhD; Massimo Antonelli, MD; COVID-ICU Gemelli Study Group; Gian Marco Anzellotti; Laura Cascarano; Francesca Ceccaroni; Paolo De Santis; Mariangela Di Muro; Miriana Durante; Nicoletta Filetici; Veronica Gennenzi; Antonio Gullì; Gianmarco Lombardi; Alessio Maccaglia; Riccardo Maviglia; Alessandro Mele; Giovanna Mercurio; Teresa Michi; Tony C. Morena; Martina Murdolo; Mariano Alberto Pennisi; Stefania Postorino; Antonella Potalivo; Francesca Pozzana; Carlotta Rubino; Martina Savino; Roberta Scarascia; Angela Scavone; Donatella Settanni; Serena Silva; Flavia Torrini; Joel Vargas; Carmelina Zaccone