COVID-19 portal: Profiling researchers, bio-entities, and institutions

The outbreak of COVID-19 has a severe impact on our families, communities, and businesses. White House released the COVID19 literature dataset (called CORD-19 dataset) which has grown exponentially into a gigantic collection of over 500,000 articles. Researchers, practitioners, and administrators need a tool to help them digest this enormous amount of knowledge to address various scientific questions related to COVID-19. This paper showcases the COVID-19 portal to portray the research profiles of scientists, bio entities (e.g., gene, drug, disease), and institutions based on the integration of CORD-19 research literature, COVID-19 related clinical trials, PubMed knowledge graph, and the drug discovery knowledge graph. This portal provides the following profiles related to COVID-19: 1) the profile of a research scientist with his/her COVID-19 related publications and clinical trials which can be ranked by year or by the number of tweets; 2) the profile of a bio entity which could be a gene, a drug, or a disease with articles and clinical trials mentioned this bio entity; and 3) the profile of an institution with papers authored by researchers from this institution

Performance and Stability of Pearl Millet Varieties for Grain Yield and Micronutrients in Arid and Semi-Arid Regions of India

Pearl millet [Pennisetum glaucum (L.) R. Br.] is grown under both arid and semi-arid conditions in India, where other cereals are hard to grow. Pearl millet cultivars, hybrids, and OPVs (open pollinated varieties) are tested and released by the All India Coordinated Research Project on Pearl Millet (AICRP-PM) across three zones (A1, A, and B) that are classified based on rainfall pattern. Except in locations with extreme weather conditions, hybrids dominate pearl millet growing areas, which can be attributed to hybrid vigor and the active role of the private sector. The importance of OPVs cannot be ruled out, owing to wider adaptation, lower input cost, and timely seed availability to subsidiary farmers cultivating this crop. This study was conducted to scrutinize the presently used test locations for evaluation of pearl millet OPVs across India, identify the best OPVs across locations, and determine the variation in grain Fe and Zn contents across locations in these regions. Six varieties were evaluated across 20 locations in A1 and A (pooled as A) and B zones along with three common checks and additional three zonal adapted checks in the respective zones during the 2019 rainy season. Recorded data on yield and quality traits were analyzed using genotype main effects and genotype × environment interaction biplot method. The genotype × environment (G × E) interaction was found to be highly significant for all the grain yield and agronomic traits and for both micronutrients (iron and zinc). However, genotypic effect (G) was four (productive tillers) to 49 (grain Fe content) times that of G × E interaction effect for various traits across zones that show the flexibility of OPVs. Ananthapuramu is the ideal test site for selecting pearl millet cultivars effectively for adaptation across India, while Ananthapuramu, Perumallapalle, and Gurugram can also be used as initial testing locations. OPVs MP 599 and MP 600 are identified as ideal genotypes, because they showed higher grain and fodder yields and stability compared with other cultivars. Iron and zinc concentration showed highly significant positive correlation (across environment = 0.83; p < 0.01), indicating possibility of simultaneous effective selection for both traits. Three common checks were found to be significantly low yielders than the test entries or zonal checks in individual zones and across India, indicating the potential of genetic improvement through OPVs

Functional annotation of human long noncoding RNAs via molecular phenotyping

Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-todate lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.Peer reviewe

Exploring the effect of discharge summaries for the prediction of 30-day unplanned patient readmission to the ICU

Healthcare is transforming into a data-intensive industry with the expectation to double its own data every 73 days by 2020. Electronic Health Records hold a vast amount of information that has the potential of improving care delivery ranging from management tasks in hospitals to inferring diagnoses from X-ray images. The massive volume of data, such as demographic data, diagnoses, tests, prescribed medications, and procedures, can be used to predict health risk or diagnose diseases. But few pay attention to the medical notes which contain abundant and critical information written by healthcare service providers during a patient’s stay or visit to the hospital. Because of the unstructured feature in these notes, they are usually underutilized to build prediction models. This project incorporates medical notes (e.g., discharge notes) along with demographic data available in the MIMIC-III dataset, to visualize patterns and finally train a prediction model for readmission of patients in the ICU.Informatio

Head-to-Head Comparison between [⁶⁸Ga]Ga-DOTA.SA.FAPi and [¹⁸F]F-FDG PET/CT Imaging in Patients with Breast Cancer

This study aimed to compare the diagnostic performance of [68Ga]Ga-DOTA.SA.FAPi with that of [18F]F-FDG PET/CT in detecting primary and metastatic lesions of breast cancer. [18F]F-FDG and [68Ga]Ga-DOTA.SA.FAPi PET/CT scans of histologically proven breast cancer patients were compared according to patient-based and lesion-based analysis. Forty-seven patients with a mean age of 44.8 ± 9.9 years (range: 31–66 years) were evaluated. A total of 85% of patients had invasive ductal carcinoma, and 15% had invasive lobular carcinoma. The tracer uptake [SULpeak, SULavg, and the median tumor-to-background ratio (TBR)] was significantly higher in [68Ga]Ga-DOTA.SA.FAPi than with [18F]F-FDG PET/CT for lymph nodes, pleural metastases, and liver lesions (p p 18F]F-FDG. In patient-based analysis the sensitivity of [68Ga]Ga-DOTA.SA.FAPi PET/CT was higher, but not significant than that of [18F]F-FDG PET/CT in the detection of both primary tumors and metastatic lesions. According to lesion-based analysis, on diagnostic CT, 47 patients had 44 primary tumors, 248 lymph nodes, 15 pleural, 88 liver, and 42 brain metastases. [68Ga]Ga-DOTA.SA.FAPi scan identified more abnormal lesions than [18F]F-FDG in all the primary and metastatic sites with a maximum marked difference in the primary site [88.6% vs. 81.8%; p-0.001], lymph nodes [89.1% vs. 83.8%; p-0.0001], pleural metastases [93.3% vs. 73%; p-0.096] and brain metastasis [100% vs. 59.5%; p-0.0001]. [68Ga]Ga-DOTA.SA.FAPi PET/CT was superior to [18F]F-FDG PET/CT in the imaging of breast cancers