Surface Morphology and Electrical Resistivity in Polycrystalline Au/Cu/Si(100) System

This work describes the analysis of morphology and electrical resistivity (ρ) obtained in the Au/Cu/Si system. The Au/Cu bilayers were deposited by thermal evaporation technique with thicknesses from 50 to 250 nm on SiOx/Si(100) substrates. The Au : Cu concentration ratio of the samples was of 25 : 75 at%. The bilayers were annealed into a vacuum oven with argon atmosphere at 660 K for one hour. The crystalline structures of AuCu and CuSi alloys were confirmed by X-ray diffraction analysis. The scanning electron microscopy (SEM), the atomic force microscopy (AFM), and the energy dispersive spectroscopy (EDS) were used to study the morphology, final thickness, and the atomic concentration of the alloys formed, respectively. The four-point probe technique was used to measure the electrical resistivity (ρ) in the prepared alloys as a function of thickness. The ρ value was measured and it was numerically compared with the Fuchs–Sondheimer (FS) and the Mayadas–Shatzkes (MS) models of resistivity. Results show values of electrical resistivity between 0.9 and 1.9 μΩ-cm. These values are four times smaller than the values of the AuCu systems reported in literature

Effects of childhood multiple maltreatment experiences on depression of socioeconomic disadvantaged elderly in Brazil.

Childhood maltreatment is a risk factor for depression in nonelderly individuals. We investigated the effect of childhood abuse and neglect on the development of geriatric depression and its severity in socioeconomically disadvantaged individuals. A cross-sectional study investigated 449 individuals aged 60-103 years sorted by data using the enrollment list health coverage from the city of Porto Alegre, Brazil. The fifteen-item Geriatric Depression Scale was used to assess depression. The Childhood Trauma Questionnaire was used to identify emotional and physical neglect, in addition to emotional, physical, and sexual abuse. Geriatric depression was associated with emotional and physical abuse and neglect. Emotional abuse and neglect, as well as physical abuse, increased the odds of an individual developing severe depression. Correlations were observed for combined forms of maltreatment, with two to five maltreatment types producing mild to moderate symptoms. Similar trends were observed for severe symptoms in a limited number of cases. The cross-sectional design limit causal inference. Retrospective measurement of childhood maltreatment may increase recall and response bias. Late-life depression and its severity significantly correlated with the extent of childhood emotional and physical abuse and neglect. Thus, research should focus on supporting trauma survivors late in life, particularly when they come from low or middle income countries because these patients have higher rates of depression in elderly populations

Hidden new physics in meson decays

A model-independent analysis of a non-standard pseudoscalar contribution to leptonic meson decays ($\pi$,$K$,$D$,$D_s$ and $B$) is presented. As also seen from similar analyses in the literature, we find that two distinct regions in the parameter space arise, a region where the standard model contribution is predominant and a region where the new physics terms cancel precisely. So far, the latter has been regarded as a fine-tuning and for this reason it was neglected from the very beginning. This paper argues that this cancellation appears naturally in a class of models, most notably those that realize the Glashow-Weinberg-Paschos mechanism for avoiding flavor-changing neutral currents, in particular in the lepton sector. Thus, such a region that allows for larger Yukawa couplings ($10^{-4}\lesssim (G_\eta^{P}/G_F)U^{-1}m_l^{-1} \lesssim 10^{-3}$ MeV$^{-1}$) cannot be readily ruled out solely by the meson leptonic decays and is degenerated with the Standard Model prediction in these decays

Influence of childhood abuse and neglect subtypes on late-life suicide risk beyond depression.

The association of childhood maltreatment and suicide has been extensively examined within the population. Depression figures as a main cause for the elevated suicide rate in advanced ages and is often related to childhood maltreatment. The purpose of the present study was to examine the relationship between childhood maltreatment subtypes and suicide risk, testing geriatric depression as a moderator. This is a cross-sectional study looking at a sample of 449 individuals 60 year s old or older from the Multidimensional Study of the Elderly of Porto Alegre Family Health Strategy, Brazil (EMI-SUS/POA). Childhood maltreatment (Childhood Trauma Questionnaire), geriatric depressive symptoms (Geriatric Depression Scale), and suicide risk (Mini International Neuropsychiatric Interview) were assessed. The subtypes of childhood abuse and neglect were significantly associated with suicide risk. In the multivariate analysis, controlling for age, gender, income, marital status, ethnicity, smoking, and geriatric depression symptoms, all trauma subtypes remained associated with suicide risk with the exception of physical neglect (EA = 3.65; PA = 3.16; SA = 5.1; EN = 2.43; PN = 1.76). The present study showed that childhood maltreatment subtypes predicted suicide risk, and geriatric depression does not directly mediate this relation

Testcrosses are an efficient strategy for identifying cis-regulatory variation: Bayesian analysis of allele-specific expression (BayesASE)

Allelic imbalance (AI) occurs when alleles in a diploid individual are differentially expressed and indicates cis acting regulatory variation. What is the distribution of allelic effects in a natural population? Are all alleles the same? Are all alleles distinct? The approach described applies to any technology generating allele-specific sequence counts, for example for chromatin accessibility and can be applied generally including to comparisons between tissues or environments for the same genotype. Tests of allelic effect are generally performed by crossing individuals and comparing expression between alleles directly in the F1. However, a crossing scheme that compares alleles pairwise is a prohibitive cost for more than a handful of alleles as the number of crosses is at least (n2-n)/2 where n is the number of alleles. We show here that a testcross design followed by a hypothesis test of AI between testcrosses can be used to infer differences between nontester alleles, allowing n alleles to be compared with n crosses. Using a mouse data set where both testcrosses and direct comparisons have been performed, we show that the predicted differences between nontester alleles are validated at levels of over 90% when a parent-of-origin effect is present and of 60%-80% overall. Power considerations for a testcross, are similar to those in a reciprocal cross. In all applications, the testing for AI involves several complex bioinformatics steps. BayesASE is a complete bioinformatics pipeline that incorporates state-of-the-art error reduction techniques and a flexible Bayesian approach to estimating AI and formally comparing levels of AI between conditions. The modular structure of BayesASE has been packaged in Galaxy, made available in Nextflow and as a collection of scripts for the SLURM workload manager on github (https://github.com/McIntyre-Lab/BayesASE)

Baseline Characteristics of Sars-Cov-2 Vaccine Non-Responders in a Large Population-Based Sample

INTRODUCTION: Studies indicate that individuals with chronic conditions and specific baseline characteristics may not mount a robust humoral antibody response to SARS-CoV-2 vaccines. In this paper, we used data from the Texas Coronavirus Antibody REsponse Survey (Texas CARES), a longitudinal state-wide seroprevalence program that has enrolled more than 90,000 participants, to evaluate the role of chronic diseases as the potential risk factors of non-response to SARS-CoV-2 vaccines in a large epidemiologic cohort. METHODS: A participant needed to complete an online survey and a blood draw to test for SARS-CoV-2 circulating plasma antibodies at four-time points spaced at least three months apart. Chronic disease predictors of vaccine non-response are evaluated using logistic regression with non-response as the outcome and each chronic disease + age as the predictors. RESULTS: As of April 24, 2023, 18,240 participants met the inclusion criteria; 0.58% (N = 105) of these are non-responders. Adjusting for age, our results show that participants with self-reported immunocompromised status, kidney disease, cancer, and other non-specified comorbidity were 15.43, 5.11, 2.59, and 3.13 times more likely to fail to mount a complete response to a vaccine, respectively. Furthermore, having two or more chronic diseases doubled the prevalence of non-response. CONCLUSION: Consistent with smaller targeted studies, a large epidemiologic cohort bears the same conclusion and demonstrates immunocompromised, cancer, kidney disease, and the number of diseases are associated with vaccine non-response. This study suggests that those individuals, with chronic diseases with the potential to affect their immune system response, may need increased doses or repeated doses of COVID-19 vaccines to develop a protective antibody level

Methodology to Estimate Natural- and Vaccine-induced antibodies to Sars-Cov-2 in a Large Geographic Region

Accurate estimates of natural and/or vaccine-induced antibodies to SARS-CoV-2 are difficult to obtain. Although model-based estimates of seroprevalence have been proposed, they require inputting unknown parameters including viral reproduction number, longevity of immune response, and other dynamic factors. In contrast to a model-based approach, the current study presents a data-driven detailed statistical procedure for estimating total seroprevalence (defined as antibodies from natural infection or from full vaccination) in a region using prospectively collected serological data and state-level vaccination data. Specifically, we conducted a longitudinal statewide serological survey with 88,605 participants 5 years or older with 3 prospective blood draws beginning September 30, 2020. Along with state vaccination data, as of October 31, 2021, the estimated percentage of those 5 years or older with naturally occurring antibodies to SARS-CoV-2 in Texas is 35.0% (95% CI = (33.1%, 36.9%)). This is 3× higher than, state-confirmed COVID-19 cases (11.83%) for all ages. The percentage with naturally occurring or vaccine-induced antibodies (total seroprevalence) is 77.42%. This methodology is integral to pandemic preparedness as accurate estimates of seroprevalence can inform policy-making decisions relevant to SARS-CoV-2