A domain-knowledge modeling of hospital-acquired infection risk in Healthcare personnel from retrospective observational data: A case study for COVID-19.

INTRODUCTION: Hospital-acquired infections of communicable viral diseases (CVDs) have been posing a tremendous challenge to healthcare workers globally. Healthcare personnel (HCP) is facing a consistent risk of viral infections, and subsequently higher rates of morbidity and mortality. MATERIALS AND METHODS: We proposed a domain-knowledge-driven infection risk model to quantify the individual HCP and the population-level risks. For individual-level risk estimation, a time-variant infection risk model is proposed to capture the transmission dynamics of CVDs. At the population-level, the infection risk is estimated using a Bayesian network model constructed from three feature sets, including individual-level factors, engineering control factors, and administrative control factors. For model validation, we investigated the case study of the Coronavirus disease, in which the individual-level and population-level infection risk models were applied. The data were collected from various sources such as COVID-19 transmission databases, health surveys/questionaries from medical centers, U.S. Department of Labor databases, and cross-sectional studies. RESULTS: Regarding the individual-level risk model, the variance-based sensitivity analysis indicated that the uncertainty in the estimated risk was attributed to two variables: the number of close contacts and the viral transmission probability. Next, the disease transmission probability was computed using a multivariate logistic regression applied for a cross-sectional HCP data in the UK, with the 10-fold cross-validation accuracy of 78.23%. Combined with the previous result, we further validated the individual infection risk model by considering six occupations in the U.S. Department of Labor O*Net database. The occupation-specific risk evaluation suggested that the registered nurses, medical assistants, and respiratory therapists were the highest-risk occupations. For the population-level risk model validation, the infection risk in Texas and California was estimated, in which the infection risk in Texas was lower than that in California. This can be explained by California's higher patient load for each HCP per day and lower personal protective equipment (PPE) sufficiency level. CONCLUSION: The accurate estimation of infection risk at both individual level and population levels using our domain-knowledge-driven infection risk model will significantly enhance the PPE allocation, safety plans for HCP, and hospital staffing strategies.

Examining hydraulic fracturing chemicals: A temporal and comparative analysis.

Hydraulic fracturing (HF) remains a current global energy policy issue, and understanding risks to drinking water resources from HF chemicals is an important aspect of this topic. The quantity and quality of disclosed HF chemical information are significant barriers for stakeholders attempting to perform systemic environmental and public health research. A repeatable approach for processing HF chemical disclosure data is provided using United States FracFocus data as a case study. We fill research gaps by examining HF chemical trends between 2014 and 2020 and comparing HF chemicals with a list of reference chemicals known or suspected to be in contact (unrelated to HF) with drinking water, food, or cosmetics. In total, 1,244 unique HF chemicals were identified. Compared with EPA's 2016 HF chemical disclosure research, 480 new chemicals are identified, and 318 previously reported chemicals were not observed. The annual unique chemical counts have dropped from 878 to 594 (32.3%) over the research period, while data quality and transparency have increased. Approximately 69.7% of the identified HF ingredients were found in a list of reference chemicals known or suspected to be in contact (unrelated to HF) with drinking water, food, or cosmetics. Chemical differences between production types (gas and oil) and states are also reviewed. Our research reveals that the sociotechnical system surrounding HF is dynamic and moving toward fewer and, in general, safer chemicals, for those that are disclosed. This study highlights opportunities for new and updated systemic research regarding HF chemical hazard dynamics and associated risk to drinking water resources.

Hydraulic Fracturing Chemical Disclosure Policy and Data Analysis: Metrics and Trends in Transparency.

This research presents two new policy-level performance indicators for measuring hydraulic fracturing chemical transparency to address the limitations of existing metrics and provide additional perspectives to stakeholders. Existing indicators do not capture the change in proportions of hydraulic fracturing wells with publicly available chemical information or percent of ingredient mass withheld on chemical disclosure forms. Based on the new indicators, state-level policy changes and the FracFocus register have increased hydraulic fracturing chemical transparency over the past decade and continue to drive measurable improvements. The percent of wells with publicly disclosed ingredients increased from ∼0 to 95% (2010-2019), and the average percent of hydraulic fracturing fluid mass withheld on chemical disclosure forms decreased ∼46.8% (2013-2019). The percent ingredient mass withholding was used to compare the two current regulatory chemical disclosure form approaches (system and traditional). In 2019, the average percent of hydraulic fracturing fluid mass withheld on system approach chemical disclosure forms (0.044%) was 66.3% less than the traditional forms (0.132%). This research improves our capabilities to understand, evaluate, and communicate the effect of chemical transparency policy decisions and corporate practices. Recent lessons learnt from the oil and gas industry should be used to study broader chemical transparency policies, information systems, and communication strategies.

Development of sub-tropically adapted diverse provitamin-A rich maize inbreds through marker-assisted pedigree selection, their characterization and utilization in hybrid breeding.

Malnutrition has emerged as one of the major health problems worldwide. Traditional yellow maize has low provitamin-A (proA) content and its genetic base in proA biofortification breeding program of subtropics is extremely narrow. To diversify the proA rich germplasm, 10 elite low proA inbreds were crossed with a proA rich donor (HP702-22) having mutant crtRB1 gene. The F2 populations derived from these crosses were genotyped using InDel marker specific to crtRB1. Severe marker segregation distortion was observed. Seventeen crtRB1 inbreds developed through marker-assisted pedigree breeding and seven inbreds generated using marker-assisted backcross breeding were characterized using 77 SSRs. Wide variation in gene diversity (0.08 to 0.79) and dissimilarity coefficient (0.28 to 0.84) was observed. The inbreds were grouped into three major clusters depicting the existing genetic diversity. The crtRB1-based inbreds possessed high ß-carotene (BC: 8.72µg/g), ß-cryptoxanthin (BCX: 4.58µg/g) and proA (11.01µg/g), while it was 2.35µg/g, 1.24µg/g and 2.97µg/g in checks, respectively. Based on their genetic relationships, 15 newly developed crtRB1-based inbreds were crossed with five testers (having crtRB1 gene) using line × tester mating design. 75 experimental hybrids with crtRB1 gene were evaluated over three locations. These experimental hybrids possessed higher BC (8.02µg/g), BCX (4.69µg/g), proA (10.37µg/g) compared to traditional hybrids used as check (BC: 2.36 µg/g, BCX: 1.53µg/g, proA: 3.13µg/g). Environment and genotypes × environment interaction had minor effects on proA content. Both additive and dominance gene action were significant for proA. The mean proportion of proA to total carotenoids (TC) was 44% among crtRB1-based hybrids, while 11% in traditional hybrids. BC was found to be positively correlated with BCX (r = 0.68) and proA (r = 0.98). However, no correlation was observed between proA and grain yield. Several hybrids with >10.0 t/ha grain yield with proA content >10.0 µg/g were identified. This is the first comprehensive study on development of diverse proA rich maize hybrids through marker-assisted pedigree breeding approach. The findings provides sustainable and cost-effective solution to alleviate vitamin-A deficiency.

Elicitor-Induced Biochemical and Molecular Manifestations to Improve Drought Tolerance in Rice (Oryza sativa L.) through Seed-Priming.

Rice (Oryza sativa L.) is one of the major grain cereals of the Indian subcontinent which face water-deficit stress for their cultivation. Seed-priming has been reported to be a useful approach to complement stress responses in plants. In the present study, seed-priming with hormonal or chemical elicitor [viz. methyl jasmonate (MJ), salicylic acid (SA), paclobutrazol (PB)] showed significant increase in total phenolic content, antioxidant activity and expression of Rice Drought-responsive (RD1 and RD2) genes (of AP2/ERF family) in contrasting rice genotypes (Nagina-22, drought-tolerant and Pusa Sugandh-5, drought-sensitive) under drought stress. However, decrease in lipid peroxidation and protein oxidation was observed not only under the stress but also under control condition in the plants raised from primed seeds. Expression analyses of RD1 and RD2 genes showed upregulated expression in the plants raised from primed seeds under drought stress. Moreover, the RD2 gene and the drought-sensitive genotype showed better response than that of the RD1 gene and the drought-tolerant genotype in combating the effects of drought stress. Among the elicitors, MJ was found to be the most effective for seed-priming, followed by PB and SA. Growth and development of the plants raised from primed seeds were found to be better under control and drought stress conditions compared to that of the plants raised from unprimed seeds under the stress. The present study suggests that seed-priming could be one of the useful approaches to be explored toward the development of simple, cost-effective and farmer-friendly technology to enhance rice yield in rainfed areas.