Modeling Occupational Fingernail Onycholysis Disorders in the Population of US Astronauts Who Have Engaged in Extravehicular Activity

Objectives Spacesuits are designed to be reliable personal spacecraft that preserve the life and well-being of the astronaut from the extremes of space. However, materials, operating pressures, and suit design requirements often result in a risk of musculoskeletal discomfort and injury to various areas of the body. In particular, this investigation looked at fingernails and their risk of developing onycholysis. Methods An onycholysis literature review was followed by a retrospective analysis of injury characteristics, astronaut suited training and spaceflight events, hand anthropometry, glove sizing, and astronaut demographics. Multiple logistic regression was used to assess the likelihood of onycholysis occurrence by testing potential risk variables against the dataset compiled from the retrospective data mining. Results The duration of event exposure, type of glove used, distance (delta) between the fingertip and the tip of the glove, sex, and age were found to be significantly related to occurrence of onycholysis (whether protective or injurious). Conclusion An initial risk formula (model) for onycholysis was developed as a result of this investigation. In addition to validation through a future study, further improvement to this onycholysis equation and spacesuit discomfort and injury in general can be aided by future investigations that lead to better definition of the threshold between safe and risky exposure for each type of risk factor. Application This work described a potential method that can be used for EVA spacesuit glove onycholysis injury risk analysis for either iterative glove design or between glove comparisons, such as during a product downselect process.

A Four−Gene-Based Risk Score With High Prognostic Value in Gastric Cancer

BackgroundGastric adenocarcinoma is an important contributor to cancer mortality and morbidity. This study aimed to explore the prognostic value of mutation patterns in gastric adenocarcinoma.Materials and MethodsWe extracted somatic mutation data for 437 gastric adenocarcinoma samples from The Cancer Genome Atlas (TCGA) Stomach Adenocarcinoma (STAD) cohort. Kaplan–Meier survival in the R package maftools was used to analyze associations between mutations and survival. Multivariate Cox proportional model was used to establish risk formula. A four-gene-based risk score was developed to predict the overall survival of patients with gastric adenocarcinoma. We used the Tianjin cohort dataset with survival information to further evaluate the clinical value of this mutation signature.ResultsForty-five survival-related mutated genes were identified and verified, most of which were co-occurring in their mutation pattern and co-occurring with MLH3 and polymerase ϵ (POLE) mutations. Gastric adenocarcinoma samples with the 45 mutated genes had a significantly higher mutation count. Four-gene [UTRN, MUC16, coiled-coil domain-containing protein 178 (CCDC178), and HYDIN] mutation status was used to build a prognostic risk score that could be translated into the clinical setting. The association between the four-gene-based signature and overall survival remained statistically significant after controlling for age, sex, TNM stage, and POLE mutation status in the multivariate model [hazard ratio (HR), 1.88; 95% CI, 1.33–2.7; p < 0.001]. The prognostic significance of the four-gene-based risk score identified in TCGA cohort was validated in the Tianjin cohort.ConclusionA four-mutated gene risk formula was developed that correlated with the overall survival of patients with gastric adenocarcinoma using a multivariable Cox regression model. In two independent genomic datasets from TCGA and Tianjin cohorts, low risk scores were associated with higher tumor mutation loads and improved outcome in patients with gastric adenocarcinoma. This finding may have implications for prognostic prediction and therapeutic guidance for gastric adenocarcinoma.

The Contribution of Eight Modifiable Risk Factors to Dementia Prevalence in Jamaica

The number and proportion of dementia cases in Jamaica attributable to eight modifiable lifestyle factors was calculated using factor analysis in Stata and Levin’s Attributable Risk formula (hypertension, diabetes mellitus, depression, low educational attainment, smoking, overweight, obesity and vision problems). Four sources of data were used: (1) risk factor prevalence data were obtained from the Jamaica Health and Lifestyle Survey, 2008, (2) relative risk data were sourced from published meta-analyses, (3) factor analysis in Stata version 15 was performed to estimate shared variance among risk factors utilising data from the Health and Social Status of Older Persons in Jamaica Study and, (4) estimated prevalence of dementia in Jamaica in 2012 was obtained from a 2018 publication by Shearer et al. Obesity was found to be responsible for the largest proportion of dementia cases (13.94%; 2508 cases) followed by hypertension (10.64%; 1917 cases), low educational attainment (7.21%; 1299 cases), overweight (6.42%; 1156 cases), smoking (3.90%; 702 cases), diabetes (3.38%; 608 cases), depression (1.00%; 181 cases) and impaired vision (0.002%; 34 cases%). Using this largely theoretical model, the eight factors examined account for approximately 46.0% of dementia cases. Dementia risk reduction programs that target even one of these factors has the potential to result in significant reduction in future dementia prevalence as they are all interrelated. In future work, as these data become available, the contribution of mid-life obesity, mid-life hypertension and physical inactivity will also be taken into consideration.

A novel way to estimate the epidemic risk index for assessing the government measures during the epidemic of respiratory transmitted person-to-person disease

The epidemic risk index is formulated in a novel way, extending the INFORM risk formula. The development is based on the well known gravity model. Modularity of the proposed epidemic risk index allows \textit{ad hoc} modifications according to the current knowledge of biological pathogen which is a cause of epidemic and available data about geographical areas of interest. Concerning the SARS-CoV-2 virus pandemic in 2020, the model is presented so that it can be usable, hopefully, in the current situation, although, in general, it should be applicable to any respiratory transmitted person-to-person disease.

A key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinoma

Background: Lymphovascular invasion (LOI), a key pathological feature of head and neck squamous cell carcinoma (HNSCC), is predictive of poor survival; however, the associated clinical characteristics and underlying molecular mechanisms remain largely unknown. Methods: We performed weighted gene co-expression network analysis to construct gene co-expression networks and investigate the relationship between key modules and the LOI clinical phenotype. Functional enrichment and KEGG pathway analyses were performed with differentially expressed genes. A protein–protein interaction network was constructed using Cytoscape, and module analysis was performed using MCODE. Prognostic value, expression analysis, and survival analysis were conducted using hub genes; GEPIA and the Human Protein Atlas database were used to determine the mRNA and protein expression levels of hub genes, respectively. Multivariable Cox regression analysis was used to establish a prognostic risk formula and the areas under the receiver operating characteristic curve (AUCs) were used to evaluate prediction efficiency. Finally, potential small molecular agents that could target LOI were identified with DrugBank. Results: Ten co-expression modules in two key modules (turquoise and pink) associated with LOI were identified. Functional enrichment and KEGG pathway analysis revealed that turquoise and pink modules played significant roles in HNSCC progression. Seven hub genes (CNFN, KIF18B, KIF23, PRC1, CCNA2, DEPDC1, and TTK) in the two modules were identified and validated by survival and expression analyses, and the following prognostic risk formula was established: [risk score = EXP DEPDC1 * 0.32636 + EXP CNFN * (−0.07544)]. The low-risk group showed better overall survival than the high-risk group ( P < 0.0001), and the AUCs for 1-, 3-, and 5-year overall survival were 0.582, 0.634, and 0.636, respectively. Eight small molecular agents, namely XL844, AT7519, AT9283, alvocidib, nelarabine, benzamidine, L-glutamine, and zinc, were identified as novel candidates for controlling LOI in HNSCC ( P < 0.05). Conclusions: The two-mRNA signature (CNFN and DEPDC1) could serve as an independent biomarker to predict LOI risk and provide new insights into the mechanisms underlying LOI in HNSCC. In addition, the small molecular agents appear promising for LOI treatment.

A key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinoma

Objective: Lymphovascular invasion (LOI), a key pathological feature of head and neck squamous cell carcinoma (HNSCC), predicts poor survival. However, the associated clinical characteristics remain uncertain, and the molecular mechanisms are largely unknown. Methods: Weighted gene co-expression network analysis was performed to construct gene co-expression networks and investigate the relationship between modules and LOI clinical trait. Functional enrichment and KEGG pathway enrichment analysis were performed for differentially expressed genes using DAVID database. The protein-protein interaction network was constructed using Cytoscape software, and module analysis was performed using MCODE. Prognosis role and expression analysis was further validated by survival analysis, GEPIA analysis and HPA database. Multivariable Cox regression analysis was used to establish a prognostic risk formula and the areas under the receiver operating characteristic curve (AUCs) were used to evaluate prediction efficiency. And the potential targeted LOI molecular agents were identified with DrugBank. Results: 10 co-expression modules in two key modules (turquoise and pink) associated with tumor LOI were identified. Functional enrichment and KEGG analysis identified turquoise and pink modules played significant roles in the progression of HNSCC. The seven hub genes (CNFN, KIF18B, KIF23, PRC1, CCNA2, DEPDC1 and TTK) in two modules were identified and validated by survival analysis and expression analysis. Multivariable Cox regression analysis was used to establish a prognostic risk formula (risk score = EXP DEPDC1 * 0.32636 + EXP CNFN * (-0.07544). The low-risk group had a better OS than the high-risk group ( P <0.001), and the areas under the receiver operating characteristic curve (AUCs) of 1-, 3- and 5-year OS were 0.582, 0.634 and 0.636, respectively. Eight small molecular agents, including XL844, AT7519, AT9283, Alvocidib, Nelarabine, Benzamidine, L-Glutamine, and Zinc, may be a candidate drug for treating LOI ( P < 0.05). Conclusions: Our research revealed the two-mRNA signature could serve as an independent biomarker to predict LOI risk, which provide some new insights into LOI of HNSCC. Additionally, the small molecular agents may be a candidate drug for treating LOI.

On the Reynaud-Bouret–Rivoirard–Tuleau-Malot problem

By using biorthogonal wavelets, Reynaud-Bouret, Rivoirard and Tuleau-Malot provide the adaptive and optimal [Formula: see text]-risk estimation for density functions (not necessarily having compact support) in a Besov space [Formula: see text] [P. Reynaud-Bouret, V. Rivoirard and C. Tuleau-Malot, Adaptive density estimation: A curse of support?, J. Stat. Plan. Inference 141(1) (2011) 115–139]. The authors pose an open problem: Can [Formula: see text]-risk ([Formula: see text]) estimation be given in their setting? In this paper, we try to solve that problem for [Formula: see text] by using wavelet estimators.

Food parenting practices and their association with child nutrition risk status: comparing mothers and fathers

In Canada, little is known about how food parenting practices are associated with young children’s dietary intakes and no studies have examined food parenting practices of Canadian fathers. This study aimed to examine associations between food parenting practices and preschool-age children’s nutrition risk. We conducted a cross-sectional analysis of thirty-one 2-parent families; 31 mothers, 31 fathers, and 40 preschool-age children. Parents completed an adapted version of the Comprehensive Feeding Practices Questionnaire. We calculated children’s nutrition risk using their NutriSTEP score. To account for sibling association, we used generalized estimating equations, adjusting for child age, sex, household income, and parental body mass index. Both mothers’ and fathers’ involvement of children in meal preparation were associated with lower child nutrition risk (mother [Formula: see text] = –3.45, p = 0.02; father [Formula: see text] = –1.74, p = 0.01), as were their healthy home environment scores (mother [Formula: see text] = –8.36, p < 0.001; father [Formula: see text] = –2.69, p = 0.04). Mothers’ encouragement of balance and variety was associated with lower nutrition risk ([Formula: see text] = –8.88, p = 0.01), whereas mothers’ use of food as a reward was associated with higher nutrition risk ([Formula: see text] = 4.67, p < 0.001). Fathers’ modelling of healthy behaviours was associated with lower nutrition risk ([Formula: see text] = –2.21, p = 0.01), whereas fathers’ restriction for health ([Formula: see text] = 2.21, p = 0.03) and pressure-to-eat scores ([Formula: see text] = 3.26, p = <0.001) were associated with higher nutrition risk. No associations were found between child nutrition status and parental emotion regulation, control, monitoring, or restriction for weight. In conclusion, both mothers’ and fathers’ food parenting practices are associated with their children’s nutrition status. Fathers should be included in food parenting practices interventions.

Risk of Transient Stability Using Rotor Trajectory Index as Severity Function

This paper presents a new approach to determine the risk of transient stability. It describes the implementation of rotor trajectory index (RTI) to assess the severity of power systems when it is subjected to a three-phase fault. The (RTI) is proposed as an index used to represent severity of transient instability. Risk of transient stability for three-phase fault is calculated using a well-known risk formula. Risk of transient stability provides a quantitative measure to evaluate the potential loss of synchronism of a generator that takes into account the probability and consequences. RTI index is calculated based on the machines rotor angles obtained at each step of a time domain simulation. RTI is proposed as an index to show the severity of the three-phase fault towards transient stability since it allows a fast and accurate measurement of the degree of stability of the system facing a fault. The proposed technique is implemented on the IEEE 39-bus system.