Inference for cumulative risk model under step-stress experiments and its application in nanocrystalline data

With the popularity of step-stress accelerated life testing, researchers are exploring more possibilities for models that relate the life distributions under different stress levels. Cumulative risk model assumes that the effects of stress changes have a lag period before they are fully observed, which guarantees the continuity of the hazard rate function. This paper studies the cumulative risk model for Lomax distribution with step-stress experiments. For maximum likelihood estimation, Newton-Rapson method is adopted to get point estimates. Meanwhile, the asymptotic normality of the maximum likelihood estimator is used to obtain asymptotic confidence intervals. For Bayesian estimation, point estimates and highest posterior density credible intervals under squared error loss function with informative prior and non-informative prior are derived using Metropolis-Hastings method and Metropolis-Hastings within Gibbs algorithm. To evaluate the effects of stress change time and the length of lag period, as well as the performance of different methods, numerical simulations are conducted. Then a real nanocrystalline data set is analyzed.

An Early Multi-Criteria Risk Assessment Model

Accurate time and budget is an essential estimate for planning software projects correctly. Quite often, the software projects fall into unrealistic estimates and the core reason generally owes to problems with the requirement analysis. For investigating such problems, risk has to identified and assessed at the requirement engineering phase only so that defects do not seep down to other software development phases. This article proposes a multi-criteria risk assessment model to compute risk at a requirement level by computing cumulative risk score based on a weighted score assigned to each criterion. The result of comparison with other approaches and experimentation shows that using this model it is possible to predict the risk at the early phase of software development life cycle with high accuracy.

Black and Latino Adolescents’ Self-Regulation: Placing College Preparedness in Context

Students from minoritized backgrounds, who disproportionately face higher poverty rates, are more likely to encounter risk factors, which tend to undermine individuals’ broader well-being by compromising self-regulatory processes. Yet, sociocultural theory highlights the presence of minoritized families’ cultural wealth. Consistent with a focus on assets, it is notable that college enrollment rates have increased among Black and Latino students in the U.S. Using a mixed methods approach, the current study integrated asset and risk frameworks, in order to advance knowledge on the context of minoritized teens’ college preparedness, defined here as making decisions and taking action steps toward college. Participants included low-income, predominantly Black and Latino families with adolescents ( n = 344). First, drawing from the voices of families, we examined responses to open-ended questions about aspirations, supports, and challenges. Salient themes included social-emotional and social-cultural factors. Indicators of cumulative contextual risk and cumulative individual risk were based on the qualitative data. Second, we tested whether the linkage from cumulative risk indices to teens’ college preparedness occurred via various dimensions of self-regulation (i.e., lower impulsivity, more cognitive control, and better organization skills), net of background characteristics. Adolescents’ organization skills were a significant mediator. Possible next steps for research are discussed.

Progression of myopia in teenagers and adults: a nationwide longitudinal study of a prevalent cohort

BackgroundThe prevalence of myopia is increasing worldwide. The purpose of this study was to evaluate the progression of myopia in teenagers and adults in France.MethodsThis nationwide prospective study followed 630 487 myopic adults and teenagers (mean age 43.4 years±18.2, 59.8% of women) between January 2013 and January 2019. Myopia and high myopia were defined as a spherical equivalent less than or equal to –0.50 and –6.00 diopters (D), respectively. Demographic data were collected at first visit and refractive characteristics were collected at each visit. Analysis of short-term progression (first 12 to 26 months postbaseline) was modelled using analysis of variance (ANOVA). Progression of myopia was stratified according to age, gender and spherical equivalent at first visit.ResultsHigher proportions of progressors were observed in the youngest age groups: 14–15 (18.2 %) and 16–17 years old (13.9 %). In multivariate analysis, after adjustment for over age, spherical equivalent and gender, the mean short-term progression decreased from –0.36 D in the 14–15 years age group to –0.13 D in the 28–29 years age group. Young age and higher myopia at baseline together were strongly associated with the risk of developing high myopia, the 5-year cumulative risk being 76% for youngest teenager with higher myopia status at baseline.ConclusionIn this large cohort of myopic teenagers and adults, myopia progression was reported in 18.2% and 13.9% of the 14–15 and 16–17 age groups, respectively. The risk to develop high myopia was higher for younger individuals with higher myopia at baseline examination.

GSTP1 and GSTM3 Variant Alleles Affect Susceptibility and Severity of COVID-19

Based on the premise that oxidative stress plays an important role in severe acute respiratory syndrome coronavirus (SARS-CoV-2) infection, we speculated that variations in the antioxidant activities of different members of the glutathione S-transferase family of enzymes might modulate individual susceptibility towards development of clinical manifestations in COVID-19. The distribution of polymorphisms in cytosolic glutathione S-transferases GSTA1, GSTM1, GSTM3, GSTP1 (rs1695 and rs1138272), and GSTT1 were assessed in 207 COVID-19 patients and 252 matched healthy individuals, emphasizing their individual and cumulative effect in disease development and severity. GST polymorphisms were determined by appropriate PCR methods. Among six GST polymorphisms analyzed in this study, GSTP1 rs1695 and GSTM3 were found to be associated with COVID-19. Indeed, the data obtained showed that individuals carrying variant GSTP1-Val allele exhibit lower odds of COVID-19 development (p = 0.002), contrary to carriers of variant GSTM3-CC genotype which have higher odds for COVID-19 (p = 0.024). Moreover, combined GSTP1 (rs1138272 and rs1695) and GSTM3 genotype exhibited cumulative risk regarding both COVID-19 occurrence and COVID-19 severity (p = 0.001 and p = 0.025, respectively). Further studies are needed to clarify the exact roles of specific glutathione S-transferases once the SARS-CoV-2 infection is initiated in the host cell.

Identification of the 7-lncRNA Signature as a Prognostic Biomarker for Acute Myeloid Leukemia

A lot of evidence has emphasized the function of long noncoding RNAs (lncRNAs) in tumors’ development and progression. Nevertheless, there is still a lack of lncRNA biomarkers that can predict the prognosis of acute myeloid leukemia (AML). Our goal was to develop a lncRNA marker with prognostic value for the survival of AML. AML patients’ RNA sequencing data as well as clinical characteristics were obtained from the public TARGET database. Then, differentially expressed lncRNAs were identified in female and male AML samples. By adopting univariate and multivariate Cox regression analyses, AML patients’ survival was predicted by a seven-lncRNA signature. It was found that 95 abnormal expressed lncRNAs existed in AML. Then, the analysis of multivariate Cox regression showed that, among them, 7 (LINC00461, RP11-309M23.1, AC016735.2, RP11-61I13.3, KIAA0087, RORB-AS1, and AC012354.6) had an obvious prognostic value, and according to their cumulative risk scores, these 7 lncRNA signatures could independently predict the AML patients’ overall survival. Overall, the prognosis of AML patients could be predicted by a reliable tool, that is, seven-lncRNA prognostic signature.