bluuebunny/crossref_metadata_2025_split huggingface dataset:
Statistical framework for studying the spatial architecture of the tumor immune microenvironment
Authors: Wilson Christopher , Thapa Ram , Creed Jordan , Nguyen Jonathan , Segura Carlos Moran , Gerke Travis , Schildkraut Joellen , Peres Lauren , Fridley Brooke L. 
Published: April 2021

AbstractNew technologies, such as multiplex immunofluorescence microscopy (mIF), are being developed and used for the assessment and visualization of the tumor immune microenvironment (TIME). These assays produce not only an estimate of the abundance of immune cells in the TIME, but also their spatial locations; however, there are currently few approaches to analyze the spatial context of the TIME. Thus, we have developed a framework for the spatial analysis of the TIME using Ripley’sK, coupled with a permutation-based framework to estimate and measure the departure from complete spatial randomness (CSR) as a measure of the interactions between immune cells. This approach was then applied to ovarian cancer using mIF collected on intra-tumoral regions of interest (ROIs) and tissue microarrays (TMAs) from 158 high-grade serous ovarian carcinoma patients in the African American Cancer Epidemiology Study (AACES) (94 subjects on TMAs resulting in 259 tissue cores; 91 subjects with 254 ROIs). Cox proportional hazard models were constructed to determine the association of abundance and spatial clustering of tumor-infiltrating lymphocytes, cytotoxic T-cells, and regulatory T-cells, and overall survival. We found that EOC patients with high abundance and low spatial clustering of tumor-infiltrating lymphocytes and cytotoxic T-cells in their tumors had the best overall survival. In contrast, patients with low levels of regulatory T-cells but with a high level of spatial clustering (compare to those with a low level of spatial clustering) had better survival. These findings underscore the prognostic importance of evaluating not only immune cell abundance but also the spatial contexture of the immune cells in the TIME. In conclusion, the application of this spatial analysis framework to the study of the TIME could lead to the identification of immune content and spatial architecture that could aid in the determination of patients that are likely to respond to immunotherapies.
Applications of Digital Microscopy and Densely Connected Convolutional Neural Networks for Automated Quantitation of Babesia-Infected Erythrocytes
Authors: Durant Thomas JS , Dudgeon Sarah , McPadden Jacob , Simpson Anisia , Price Nathan , Schulz Wade , Torres Richard , Olson Eben M 
Published: April 2021

BackgroundClinical babesiosis is diagnosed, and parasite burden is determined, by microscopic inspection of a thick or thin Giemsa-stained peripheral blood smear. However, quantitative analysis by manual microscopy is subject to observer bias, slide distribution errors, statistical sampling error, recording errors, and is inherently burdensome from time management and workflow efficiency standpoints. As such, methods for the automated measurement of percent parasitemia in digital microscopic images of peripheral blood smears could improve clinical accuracy, relative to the predicate method.MethodsIndividual erythrocyte images (shape: 70×70×3) were manually labeled as “parasite” or “normal” and were used to train a model for binary image classification. The best model was then used to calculate percent parasitemia from a clinical validation dataset, and values were compared to a clinical reference value. Lastly, model interpretability was examined using an integrated gradient to identify pixels most likely to influence classification decisions.ResultsThe precision and recall of the model during development testing were 0.92 and 1.00, respectively. In clinical validation, the model returned increasing positive signal with increasing mean reference value. However, there were two highly erroneous false positive values returned by the model. Lastly, the model incorrectly assessed three cases well above the clinical threshold of 10%. The integrated gradient suggested potential sources of false positives including rouleaux formations, cell boundaries, and precipitate as deterministic factors in negative erythrocyte images.ConclusionsWhile the model demonstrated highly accurate single cell classification and correctly assessed most slides, several false positives were highly incorrect. This project highlights the need for integrated testing of ML-based models, even when models in the development phase perform well.
Estimating the early impact of vaccination against COVID-19 on deaths among elderly people in Brazil: analyses of routinely-collected data on vaccine coverage and mortality
Authors: Victora Cesar , Castro Marcia C , Gurzenda Susie , de Medeiros Arnaldo Correia , França Giovanny , Barros Aluisio J D 
Published: April 2021

AbstractBackgroundVaccination against COVID-19 in Brazil started in January 2021, with health workers and the elderly as the priority groups. We assessed whether there was an impact of vaccinations on the mortality of elderly individuals in a context of wide transmission of the SARS-CoV-2 gamma (P.1) variant.MethodsBy May 27, 2021, 147238,414 COVID-19 deaths had been reported to the Brazilian Mortality Information System. Denominators for mortality rates were calculated by correcting population estimates for all-cause deaths reported in 2020. Proportionate mortality at ages 70-79 and 80+ years relative to deaths at all ages were calculated for deaths due to COVID-19 and to other causes, as were COVID-19 mortality rate ratios relative to individuals aged 0-69 years. Vaccine coverage data were obtained from the Ministry of Health. All results were tabulated by epidemiological weeks 1-19, 2021.FindingsThe proportion of all COVID-19 deaths at ages 80+ years was over 25% in weeks 1-6 and declined rapidly to 12.4% in week 19, whereas proportionate COVID-19 mortality for individuals aged 70-79 years started to decline by week 15. Trends in proportionate mortality due to other causes remained stable. Mortality rates were over 13 times higher in the 80+ years age group compared to that of 0-69 year olds up to week 6, and declined to 5.0 times in week 19. Vaccination coverage (first dose) of 90% was reached by week 9 for individuals aged 80+ years and by week 13 for those aged 70-79 years. Coronavac accounted for 65.4% and AstraZeneca for 29.8% of all doses administered in weeks 1-4, compared to 36.5% and 53.3% in weeks 15-19, respectively.InterpretationRapid scaling up of vaccination coverage among elderly Brazilians was associated with important declines in relative mortality compared to younger individuals, in a setting where the gamma variant predominates. Had mortality rates among the elderly remained proportionate to what was observed up to week 6, an estimated additional 43,802 COVID-related deaths would have been expected up to week 19.
National hospital readiness for COVID-19 in Lesotho: Evidence for oxygen ecosystem strengthening
Authors: Sanders Jill E. , Chakare Tafadzwa , Mapota-Masoabi Lucy , Ranyali-Otubanjo Makhoase , Ramokhele Mareitumetse M. , Rozario Aleisha , McCollum Eric D. 
Published: April 2021

AbstractThe COVID-19 pandemic continues to challenge healthcare systems globally. To understand hospital capacity, including critical oxygen capacity, a pragmatic assessment of all public hospitals in Lesotho was made in July 2020 (baseline), with follow-up in December 2020. We developed a qualitative hospital services questionnaire modeled on the World Health Organization COVID-19 assessment tool and converted answers into quantitative ordinal variables. At baseline we found all 12 domains had areas demonstrating preparedness and weakness. Key baseline gaps within infection prevention and control were lack of a dedicated team, and insufficient personal protective equipment and space for donning and doffing. Substantial limitations were noted in hypoxemia diagnosis and treatment; information management and care coordination pathways were also suboptimal. Our baseline findings may reflect uneven early pandemic care quality. Targeted follow-up after five months revealed marked improvement in the availability of pulse oximetry, oxygen capacity, and heated high flow nasal cannula devices.
U.S. Regional Differences in Physical Distancing: Evaluating Racial and Socioeconomic Divides During the COVID-19 Pandemic
Authors: Zang Emma , West Jessica , Kim Nathan , Pao Christina 
Published: April 2021

AbstractHealth varies by U.S. region of residence. Despite regional heterogeneity in the outbreak of COVID-19, regional differences in physical distancing behaviors over time are relatively unknown. This study examines regional variation in physical distancing trends during the COVID-19 pandemic and investigates variation by race and socioeconomic status (SES) within regions.Data from the 2015-2019 five-year American Community Survey were matched with anonymized location pings data from over 20 million mobile devices (SafeGraph, Inc.) at the Census block group level. We visually present trends in the stay-at-home proportion by Census region, race, and SES throughout 2020 and conduct regression analyses to statistically examine these patterns.From March to December, the stay-at-home proportion was highest in the Northeast (0.25 in March to 0.35 in December) and lowest in the South (0.24 to 0.30). Across all regions, the stay-at-home proportion was higher in block groups with a higher percentage of Blacks, as Blacks disproportionately live in urban areas where stay-at-home rates were higher (0.009 [CI: 0.008, 0.009]). In the South, West, and Midwest, higher-SES block groups stayed home at the lowest rates pre-pandemic; however, this trend reversed throughout March before converging in the months following. In the Northeast, lower-SES block groups stayed home at comparable rates to higher-SES block groups during the height of the pandemic but diverged in the months following.Differences in physical distancing behaviors exist across U.S. regions, with a pronounced Southern and rural disadvantage. Results can be used to guide reopening and COVID-19 mitigation plans.
Exposure to landscape fire smoke extremely reduced birthweight in low- and middle-income countries
Authors: Li Jiajianghui , Guan Tianjia , Guo Qian , Geng Guannan , Wang Huiyu , Guo Fuyu , Li Jiwei , Xue Tao 
Published: April 2021

AbstractLandscape fire smoke (LFS) has been associated with reduced birthweight, but evidence from low- and middle-income countries (LMICs) is rare. Here, we present a sibling-matched case– control study of 227,948 newborns to identify an association between fire-sourced fine particulate matter (PM2.5) and birthweight in 54 LMICs from 2000 to 2014.We selected mothers from the geocoded Demographic and Health Survey with at least two children and valid birthweight records. Newborns affiliated with the same mother were defined as a family group. Gestational exposure to LFS was assessed in each newborn using the concentration of fire-sourced PM2.5. We determined the associations of the within-group variations in LFS exposure with birthweight differences between matched siblings using a fixed-effects regression model. Additionally, we analyzed the binary outcomes of low birthweight (LBW) or very low birthweight (VLBW).According to fully adjusted models, a 1 µg/m3 increase in the concentration of fire-sourced PM2.5 was significantly associated with a 2.17 g (95% confidence interval [CI]: 0.56–3.77) reduction in birthweight, a 2.80% (95% CI: 0.97–4.66) increase in LBW risk, and an 11.68% (95% CI: 3.59–20.40) increase in VLBW risk.Our findings indicate that gestational exposure to LFS harms maternal health.
Defining the KRAS-regulated kinome in KRAS-mutant pancreatic cancer
Authors: Diehl J. Nathaniel , Klomp Jennifer E. , Snare Kayla R. , Blake Devon R. , Hibshman Priya S. , Kaiser Zane D. , Gilbert Thomas S.K. , Baldelli Elisa , Pierobon Mariaelena , Papke Björn , Yang Runying , Hodge Richard G. , Rashid Naim U. , Petricoin Emanuel F. , Herring Laura E. , Graves Lee M. , Cox Adrienne D. , Der Channing J. 
Published: April 2021

AbstractOncogenic KRAS drives cancer growth by activating diverse signaling networks, not all of which have been fully delineated. We set out to establish a system-wide profile of the KRAS-regulated kinase signaling network (kinome) in KRAS-mutant pancreatic ductal adenocarcinoma (PDAC). We knocked down KRAS expression in a panel of six cell lines, and then applied Multiplexed Inhibitor Bead/Mass Spectrometry (MIB/MS) chemical proteomics to monitor changes in kinase activity and/or expression. We hypothesized that depletion of KRAS would result in downregulation of kinases required for KRAS-mediated transforming activities, and in upregulation of other kinases that could potentially compensate for the deleterious consequences of the loss of KRAS. We identified 15 upregulated and 13 downregulated kinases in common across the panel. In agreement with our hypothesis, all 15 of the upregulated kinases have established roles as cancer drivers (e.g., SRC, TGFBR1, ILK), and pharmacologic inhibition of the upregulated kinase, DDR1, suppressed PDAC growth. Interestingly, 11 of the 13 downregulated kinases have established driver roles in cell cycle progression, particularly in mitosis (e.g., WEE1, Aurora A, PLK1). Consistent with a crucial role for the downregulated kinases in promoting KRAS-driven proliferation, we found that pharmacologic inhibition of WEE1 also suppressed PDAC growth. The unexpected paradoxical activation of ERK upon WEE1 inhibition led us to inhibit both WEE1 and ERK concurrently, which caused further potent growth suppression and enhanced apoptotic death than WEE1 inhibition alone. We conclude that system-wide delineation of the KRAS-regulated kinome can identify potential therapeutic targets for KRAS-mutant pancreatic cancer.
Artificial Intelligence System Reduces False-Positive Findings in the Interpretation of Breast Ultrasound Exams
Authors: Shen Yiqiu , Shamout Farah E. , Oliver Jamie R. , Witowski Jan , Kannan Kawshik , Park Jungkyu , Wu Nan , Huddleston Connor , Wolfson Stacey , Millet Alexandra , Ehrenpreis Robin , Awal Divya , Tyma Cathy , Samreen Naziya , Gao Yiming , Chhor Chloe , Gandhi Stacey , Lee Cindy , Kumari-Subaiya Sheila , Leonard Cindy , Mohammed Reyhan , Moczulski Christopher , Altabet Jaime , Babb James , Lewin Alana , Reig Beatriu , Moy Linda , Heacock Laura , Geras Krzysztof J. 
Published: April 2021

AbstractUltrasound is an important imaging modality for the detection and characterization of breast cancer. Though consistently shown to detect mammographically occult cancers, especially in women with dense breasts, breast ultrasound has been noted to have high false-positive rates. In this work, we present an artificial intelligence (AI) system that achieves radiologist-level accuracy in identifying breast cancer in ultrasound images. To develop and validate this system, we curated a dataset consisting of 288,767 ultrasound exams from 143,203 patients examined at NYU Langone Health, between 2012 and 2019. On a test set consisting of 44,755 exams, the AI system achieved an area under the receiver operating characteristic curve (AUROC) of 0.976. In a reader study, the AI system achieved a higher AUROC than the average of ten board-certified breast radiologists (AUROC: 0.962 AI, 0.924±0.02 radiologists). With the help of the AI, radiologists decreased their false positive rates by 37.4% and reduced the number of requested biopsies by 27.8%, while maintaining the same level of sensitivity. To confirm its generalizability, we evaluated our system on an independent external test dataset where it achieved an AUROC of 0.911. This highlights the potential of AI in improving the accuracy, consistency, and efficiency of breast ultrasound diagnosis worldwide.
Patients with rheumatoid arthritis with moderate or high disease activity benefit from multidisciplinary rehabilitation: a nested case-control study
Authors: Cunha Bernardo M , Ferreira Bruno SA , Barros Camila SM , Silva Jesiniana R , Kauer Juliana B , Moreira Larissa A , Gushikem Andreia ,   GIRE - Grupo de Investigação em REabilitação REumatológica
Published: May 2021

AbstractBackgroundrheumatologists recognize the importance of rehabilitation in patients with rheumatoid arthritis (RA), but they are not confident if patients with significant disease activity would benefit from it.ObjectiveTo verify if rheumatoid arthritis patients with moderate to severe inflammatory activity (MHA) improve functional capacity (FC) after a comprehensive rehabilitation program.MethodsNested case-control study. RA patients who completed a rehabilitation program between June 2014 and December 2017 were included. The interventions were prescribed according to the rehabilitation team’s discretion. FC was assessed with Health Assessment Questionnaire Disability Index (HAQ) and compared between before and after interventions. The group which improved at least 50% in CDAI was compared to the group which achieved <50%.ResultsWe included 46 patients with complete HAQ and baseline CDAI data, with a mean age of 53.6 years and mean disease duration of 11.8 years. HAQ and CDAI improved on average 0.481 (± 0.500) and 14.2 (± 16.7), respectively. Patients who improved CDAI tended to have a greater mean HAQ difference (0.6 vs. 0.3; p = 0.058). Conversely, patients who did not improve disease activity had a HAQ reduction of 0.3 (± 0.4). Post-hoc analysis was performed on the group of 9 patients with baseline CDAI ≤10. A mean baseline CDAI of 5.2 and a mean HAQ difference of 0.319 (0.079; 0.56; p = 0.016) were found.ConclusionsAfter rehabilitation, RA patients with sustained MHA improved FC similarly to patients with baseline mild activity or remission. Thus, patients with RA and MHA may benefit from rehabilitation concurrently with drug treatment. This study suggests that the range of improvement in FC with rehabilitation appears to have an additive effect to the drug therapy.
“The added value of 18f-FDG PET/CT in the assessment of onset and steroid resistant polimyalgia rheumatica”
Authors: Alvarado Patricia Moya , Leon Alejandro Fernandez , Corica Maria Emilia , Marti Valle Camacho , López-Mora Diego Alfonso , Castellví Barranco Ivan , Corominas Hèctor 
Published: April 2021

AbstractPMR is a common inflammatory rheumatic disease. Although its clinical characteristics are fully recognized, no specific test for its diagnosis has been established to date. Several studies have described a wide variety of diseases that present with polymyalgic symptoms. A 18FDG-PET/CT scan could help to deal with these differential diagnoses. The goal of our study is to describe the findings of the 18FDG-PET/CT scan in a cohort of PMR patients and to detail how the 18FDG-PET/CT scan improves accuracy when diagnosing other underlying conditions. This cross-sectional study enrolled patients with a diagnosis of PMR who underwent to a 18FDG-PET/CT scan to rule out other diagnosis. The 18FDG-PET/CT scan was performed either following clinical criteria at the onset of clinical symptoms or when the patient became PMR steroid resistant. Patients’ demographic, clinical and analytical data at the moment of the 18FDG-PET/CT scan were recorded. The final diagnosis was confirmed according to clinical judgement. A total of 103 patients with PMR were included. In 49.51% of patients, the 18FDG-PET/CT scan was ordered to study resistance to steroid therapy. The final diagnoses of patients were PMR in 70.9% patients, large vessel vasculitis in 15.5%, neoplasms 4.8% and another diagnosis in the rest. The 18FDG-PET/CT scan is a very useful technique for the study of Polymyalgia Rheumatica, not only to help in the diagnostic process, but also due to its role in the identification of a variety of PMR-like patrons.
Antitumor activity of a lectibody targeting cancer-associated high-mannose glycans
Authors: Oh Young Jun , Dent Matthew W. , Freels Angela R. , Zhou Qingwen , Lebrilla Carlito B. , Merchant Michael L. , Matoba Nobuyuki 
Published: April 2021

ABSTRACTAberrant protein glycosylation is a hallmark of cancer, but few drugs targeting cancer glycobiomarkers are currently available. Here, we show that a “lectibody” consisting of the high-mannose glycan-binding lectin Avaren and human IgG1 Fc (AvFc) selectively recognizes a range of cell lines derived from lung, breast, colon and blood cancers at nanomolar concentrations. AvFc’s binding to the non-small cell lung cancer (NSCLC) cell lines A549 and H460 was characterized in detail. Co-immunoprecipitation proteomics analysis revealed that epidermal growth factor receptor (EGFR) and insulin-like growth factor 1 receptor (IGF1R) are among the lectibody’s common targets in these cells. AvFc blocked the activation of EGFR and IGF1R by their respective ligands in A549 cells and inhibited the migration of A549 and H460 cells upon stimulation with EGF and IGF1. Furthermore, AvFc induced potent Fc-mediated cytotoxic effects and significantly retarded A549 and H460 tumor growth in SCID mice. Immunohistochemistry analysis of primary lung tissues from NSCLC patients demonstrated that AvFc preferentially binds to tumors over adjacent non-tumor tissues. Our findings provide evidence that increased abundance of high-mannose glycans in the glycocalyx of cancer cells can be a druggable target, and AvFc may provide a new tool to probe and target this tumor-associated glycobiomarker.
POPULATION-BASED SERO-EPIDEMIOLOGICAL STUDY PROTOCOL FOR THE IMPACT OF SMOKING ON SARS-COV-2 INFECTION AND COVID-19 OUTCOMES – THE TROINA STUDY
Authors: Polosa R. , Tomaselli V. , Ferrara P. , Romeo A. C. , Rust S. , Saitta D. , Caraci F. , Romano C. , Thangaraju M. , Zuccarello P. , Rose J. , Ferrante M , Belsey J. , Cibella F. , Interlandi E. , Ferri R. 
Published: May 2021

AbstractAfter the global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), research has highlighted several aspects of the pandemic, focusing on clinical features and risk factors associated with infection and disease severity. However, emerging results on the role of smoking in SARS-CoV-2 infection susceptibility or COVID-19 outcomes are conflicting, and their robustness remains uncertain. In this context, this project aims at quantifying the proportion of SARS-CoV-S antibody seroprevalence, studying the changes in antibody levels over time, and analyzing the association between smoking status and infection using seroprevalence data.The added value of this research is that the current smoking status of the population to be studied will be biochemically verified, in order to avoid the bias associated with self-reported smoking status. As such, the results from this survey may provide actionable metric to study the role of smoking in SARS-CoV-2 spread, and therefore implement the most appropriate public health measures to control the pandemic.The research design involves a 6-month prospective cohort study with serial sampling of the same individuals. Each participant will be surveyed about their demographics and COVID-19-related information, and blood sampling will be collected upon recruitment and at specified follow-up time points (namely, after 8 and 24 weeks). Blood samples will be screened for the presence of SARS-CoV-2 specific antibodies and serum cotinine.Overall, we expect to find a higher prevalence of antibodies in individuals at high-risk for viral exposure (i.e., healthcare or other essential workers), according to previous literature, and to refine current estimates on the association between smoking status and SARS-CoV-2/COVID-19. Our results may serve as a reference for future clinical research and the methodology could be exploited in public health sectors and policies.