No association between numerical ability and politically motivated reasoning in a large US probability sample.

The highly influential theory of "Motivated System 2 Reasoning" argues that analytical, deliberative ("System 2") reasoning is hijacked by identity when considering ideologically charged issues-leading people who are more likely to engage in such reasoning to be more polarized, rather than more accurate. Here, we fail to replicate the key empirical support for this theory across five contentious issues, using a large gold-standard nationally representative probability sample of Americans. While participants were more accurate in evaluating a contingency table when the outcome aligned with their politics (even when controlling for prior beliefs), we find that participants with higher numeracy were more accurate in evaluating the contingency table, regardless of whether or not the table's outcome aligned with their politics. These findings call for a reconsideration of the effect of identity on analytical reasoning.

Prevalence and nature of workplace bullying and harassment and associations with mental health conditions in England: a cross-sectional probability sample survey.

BACKGROUND: Evidence on workplace bullying and harassment (WBH) in the UK has not used probability-sample surveys with robust mental health assessments. This study aimed to profile the prevalence and nature of WBH in England, identify inequalities in WBH exposure, and quantify adjusted associations with mental health. METHODS: Data were from the 2014 Adult Psychiatric Morbidity Survey, a cross-sectional probability-sample survey of the household population in England, interviewed with verbal informed consent. Criteria for inclusion in the secondary analysis were being aged 16-70 years and in paid work in the past month (n=3838). Common mental disorders were assessed using the Clinical Interview Schedule-Revised and mental wellbeing using the Warwick-Edinburgh Mental Wellbeing Scale. Analyses were weighted. We examined associations between past-year WBH and current common mental disorders using multivariable regression modelling, adjusting for demographic and socioeconomic factors. Interaction terms tested for gender differences in associations. The study received ethics approval (ETH21220-299). FINDINGS: One in ten employees (10·6% (weighted), n=444/3838) reported past-year experience of WBH, with rates higher in women (12·2%, n=284/2189); those of mixed, multiple, and other ethnicity (21·0%, n=15/92); and people in debt (15·2%, n=50/281) or living in cold homes (14·6%, n=42/234). Most commonly identified perpetrators of WBH were line managers (53·6%, n=244/444) or colleagues (42·8%, n=194/444). Excessive criticism (49·3%, n=212/444), verbal abuse (42·6%, n=187/444), and humiliation (31·4%, n=142/444) were the most common types. WBH was associated with all adverse mental health indicators, including common mental disorders (adjusted odds ratio [aOR] 2·65, 95% CI 2·02-3·49), and 11 of 14 mental wellbeing indicators, including lower levels of confidence (aOR 0·57, 0·46-0·72) and of closeness to others (aOR 0·57, 0·46-0·72). Patterns of association between WBH and mental health were similar in men and women. INTERPRETATION: These findings reinforce a need for more cohesive UK legislation at the national level; guidance on recognition of bullying behaviours for employees, managers, and human resources at the organisational level, focusing on prevention and early intervention, and increased awareness of the impact of WBH on mental health among health-service practitioners. Study limitations include reliance on cross-sectional data collected before pandemic-related and other major changes in workplace practices. Longitudinal data are needed to improve evidence on causality and the longevity of mental health impacts. FUNDING: UK Prevention Research Partnership.

Efficient designs and analysis of two-phase studies with longitudinal binary data.

Researchers interested in understanding the relationship between a readily available longitudinal binary outcome and a novel biomarker exposure can be confronted with ascertainment costs that limit sample size. In such settings, two-phase studies can be cost-effective solutions that allow researchers to target informative individuals for exposure ascertainment and increase estimation precision for time-varying and/or time-fixed exposure coefficients. In this paper, we introduce a novel class of residual-dependent sampling (RDS) designs that select informative individuals using data available on the longitudinal outcome and inexpensive covariates. Together with the RDS designs, we propose a semiparametric analysis approach that efficiently uses all data to estimate the parameters. We describe a numerically stable and computationally efficient EM algorithm to maximize the semiparametric likelihood. We examine the finite sample operating characteristics of the proposed approaches through extensive simulation studies, and compare the efficiency of our designs and analysis approach with existing ones. We illustrate the usefulness of the proposed RDS designs and analysis method in practice by studying the association between a genetic marker and poor lung function among patients enrolled in the Lung Health Study (Connett et al, 1993).

Is the stability of folates in dried blood microsamples sufficient to perform home-sampling studies?

Dried blood microsampling is increasingly used for home-sampling and epidemiological studies because of its multiple advantages, including an often greatly improved analyte stability. However, a critical assessment of the stability under realistic conditions should always be performed as part of the validation, especially for unstable molecules like folates (vitamin B9). Here, the objective was to determine whether folate stability in dried blood microsamples is sufficient to allow the set-up of home-sampling studies for the monitoring of folate status in e.g., women of reproductive age. An extensive set of stability experiments was performed to evaluate the stability of the main folate vitamer 5-methyltetrahydrofolate (5MTHF), its oxidation product MeFOX and the minor non-methyl folate vitamers 10-formylfolic acid (10FoFA), 5,10-methenyltetrahydrofolate (5,10CH+THF) and tetrahydrofolate (THF) in dried blood microsamples using volumetric absorptive microsampling (VAMS) or regular dried blood spots (DBS). The evaluations included (EDTA-anticoagulated blood was collected from a single donor measured in four replicates per condition and time point): (i) the effect of temperature (-20 °C, 4 °C, ambient temperature and 37 °C), (ii) the effect of light (during drying and storage) and humidity, and (iii) the effect of storage under vacuum and pretreatment of the microsamples with stabilizing agents on folate stability. At -20 °C and 4 °C, all folate levels were within 85 to 115% of the baseline value up till two weeks of storage in both VAMS samples and DBS. However, at room temperature the stability of the analyzed folates was only consistently observed up till three days in VAMS samples, and for none of the folates at 37 °C. Humidity had a major impact on 5,10CH+THF stability, but this could be easily improved by using desiccant. Both vacuum treatment and pretreatment of microsamples with 0.1% DL-dithiothreitol and 5% butylated hydroxytoluene improved the stability at room temperature in VAMS samples, but these effects were limited at 37 °C and in DBS. Overall, the stability of the individual folate vitamers proved to be challenging and strongly temperature- and time-dependent. Nonetheless, if controlled transport (temperature and duration) can be assured, the set-up of home-sampling studies to evaluate the folate status using dried blood microsamples can still be beneficial.

Sampling weighting strategies in causal mediation analysis.

BACKGROUND: Causal mediation analysis plays a crucial role in examining causal effects and causal mechanisms. Yet, limited work has taken into consideration the use of sampling weights in causal mediation analysis. In this study, we compared different strategies of incorporating sampling weights into causal mediation analysis. METHODS: We conducted a simulation study to assess 4 different sampling weighting strategies-1) not using sampling weights, 2) incorporating sampling weights into mediation "cross-world" weights, 3) using sampling weights when estimating the outcome model, and 4) using sampling weights in both stages. We generated 8 simulated population scenarios comprising an exposure (A), an outcome (Y), a mediator (M), and six covariates (C), all of which were binary. The data were generated so that the true model of A given C and the true model of A given M and C were both logit models. We crossed these 8 population scenarios with 4 different sampling methods to obtain 32 total simulation conditions. For each simulation condition, we assessed the performance of 4 sampling weighting strategies when calculating sample-based estimates of the total, direct, and indirect effects. We also applied the four sampling weighting strategies to a case study using data from the National Survey on Drug Use and Health (NSDUH). RESULTS: Using sampling weights in both stages (mediation weight estimation and outcome models) had the lowest bias under most simulation conditions examined. Using sampling weights in only one stage led to greater bias for multiple simulation conditions. DISCUSSION: Using sampling weights in both stages is an effective approach to reduce bias in causal mediation analyses under a variety of conditions regarding the structure of the population data and sampling methods.

Evaluation of respondent-driven sampling in seven studies of people who use drugs from rural populations: findings from the Rural Opioid Initiative.

BACKGROUND: Accurate prevalence estimates of drug use and its harms are important to characterize burden and develop interventions to reduce negative health outcomes and disparities. Lack of a sampling frame for marginalized/stigmatized populations, including persons who use drugs (PWUD) in rural settings, makes this challenging. Respondent-driven sampling (RDS) is frequently used to recruit PWUD. However, the validity of RDS-generated population-level prevalence estimates relies on assumptions that should be evaluated. METHODS: RDS was used to recruit PWUD across seven Rural Opioid Initiative studies between 2018-2020. To evaluate RDS assumptions, we computed recruitment homophily and design effects, generated convergence and bottleneck plots, and tested for recruitment and degree differences. We compared sample proportions with three RDS-adjusted estimators (two variations of RDS-I and RDS-II) for five variables of interest (past 30-day use of heroin, fentanyl, and methamphetamine; past 6-month homelessness; and being positive for hepatitis C virus (HCV) antibody) using linear regression with robust confidence intervals. We compared regression estimates for the associations between HCV positive antibody status and (a) heroin use, (b) fentanyl use, and (c) age using RDS-1 and RDS-II probability weights and no weights using logistic and modified Poisson regression and random-effects meta-analyses. RESULTS: Among 2,842 PWUD, median age was 34 years and 43% were female. Most participants (54%) reported opioids as their drug of choice, however regional differences were present (e.g., methamphetamine range: 4-52%). Many recruitment chains were not long enough to achieve sample equilibrium. Recruitment homophily was present for some variables. Differences with respect to recruitment and degree varied across studies. Prevalence estimates varied only slightly with different RDS weighting approaches, most confidence intervals overlapped. Variations in measures of association varied little based on weighting approach. CONCLUSIONS: RDS was a useful recruitment tool for PWUD in rural settings. However, several violations of key RDS assumptions were observed which slightly impacts estimation of proportion although not associations.

Transition Path Sampling Study of Engineered Enzymes That Catalyze the Morita-Baylis-Hillman Reaction: Why Is Enzyme Design so Difficult?

It is hoped that artificial enzymes designed in laboratories can be efficient alternatives to chemical catalysts that have been used to synthesize organic molecules. However, the design of artificial enzymes is challenging and requires a detailed molecular-level analysis to understand the mechanism they promote in order to design efficient variants. In this study, we computationally investigate the mechanism of proficient Morita-Baylis-Hillman enzymes developed using a combination of computational design and directed evolution. The powerful transition path sampling method coupled with in-depth post-processing analysis has been successfully used to elucidate the different chemical pathways, transition states, protein dynamics, and free energy barriers of reactions catalyzed by such laboratory-optimized enzymes. This research provides an explanation for how different chemical modifications in an enzyme affect its catalytic activity in ways that are not predictable by static design algorithms.

Prevalence of mental disorders among middle-aged population of primary healthcare centers in Northeastern Iran.

BACKGROUND: Primary healthcare centers (PHCs) serve as the cornerstone of accessible medical services in society, playing a crucial role in screening, detecting, and treating various health issues. This study aimed to investigate the prevalence of psychiatric disorders in middle-aged individuals who refer to PHCs and the potential of PHCs in diagnosing mental disorders. METHODS: This cross-sectional study was implemented at PHCs under the supervision of Mashhad University of Medical Sciences (MUMS) in northeast Iran in 2018. The enrolled subjects were middle-aged adults who had electronic medical records in SINA, an integrated health management system, and the electronic medical records of MUMS. The prevalence of psychiatric disorders by type and their relationship with demographic information was evaluated by a Chi-square test using SPSS 22. RESULTS: This study involved 218,341 middle-aged participants. Prevalence of psychiatric disorders was 8.59%, and depression (53.72%) and anxiety (42.02%) were the most common psychiatric disorders in both males and females. The prevalence of mental disorders was significantly higher in females than in males (88.18% vs. 18.81%; P < 0.0001). Indeed, a significant higher prevalence of depression, anxiety, somatoform, childhood psychiatric disorder, and bipolar disorders was observed in females compared to males (P < 0.05). In addition, individuals between the age of 45-60 years, and those from rural areas showed more prevalence of mental disorders than others, but these differences were not significant. CONCLUSIONS: Considering the previous studies in Iran, the prevalence of mental disorders among patients presenting to PHCs was noticeably lower than expected rates. It seems probable that this huge difference is due to poor screening and detection of mental illness in PHCs of MUMS. It is recommended that health policymakers pursue specific measures to make PHCs more helpful for people with mental health problems in the community.

The Burden of Narcolepsy in Adults: A Population Sampling Study Using Personal Media.

OBJECTIVE: To obtain insight in the spectrum of narcolepsy symptoms and associated burden in a large cohort of patients. METHODS: We used the Narcolepsy Monitor, a mobile app, to easily rate the presence and burden of 20 narcolepsy symptoms. Baseline measures were obtained and analyzed from 746 users aged between 18 and 75 years with a reported diagnosis of narcolepsy. RESULTS: Median age was 33.0 years (IQR 25.0-43.0), median Ullanlinna Narcolepsy Scale 19 (IQR 14.0-26.0), 78% reported using narcolepsy pharmacotherapy. Excessive daytime sleepiness (97.2%) and lack of energy were most often present (95.0%) and most often caused a high burden (79.7% and 76.1% respectively). Cognitive symptoms (concentration 93.0%, memory 91.4%) and psychiatric symptoms (mood 76.8%, anxiety/panic 76.4%) were relatively often reported to be present and burdensome. Conversely, sleep paralysis and cataplexy were least often reported as highly bothersome. Females experienced a higher burden for anxiety/panic, memory, and lack of energy. CONCLUSIONS: This study supports the notion of an elaborate narcolepsy symptom spectrum. Each symptom's contribution to the experienced burden varied, but lesser-known symptoms did significantly add to this as well. This emphasizes the need to not only focus treatment on the classical core symptoms of narcolepsy.

Respondent-Driven Sampling for Estimation of the Cumulative Lifetime Incidence of Abortion in Soweto, Johannesburg, South Africa: A Methodological Assessment.

Respondent-driven sampling (RDS) is a potential strategy for addressing challenges in accurate estimation of abortion incidence, but it relies on often untested assumptions. We conducted an RDS study to estimate the cumulative lifetime incidence of abortion in Soweto, Johannesburg, South Africa (April-December 2018), to evaluate whether RDS assumptions were met, and to compare RDS estimates of incidence with estimates adjusted for employment and age based on census data. A total of 849 participants were recruited from 11 seed participants between April and December 2018. The assumption that individuals can identify target population members and the assumption of approximation of sampling with replacement was met. There were minor violations of the assumptions of seed independence from the final sample and reciprocity of ties. Assumptions of accurate degree reporting and random recruitment were not met. Failure to meet assumptions yielded a study sample with different employment characteristics than those of the target population; this could not be resolved by standard RDS methods. The RDS estimate of cumulative lifetime abortion incidence was 12.1% (95% confidence interval: 9.8, 14.3), and the employment-adjusted estimate was 16.9% (95% confidence interval: 12.8, 22.1). We caution researchers in using RDS for representative estimates of abortion incidence. Use of postsurvey weights to adjust for differences in characteristics between the sample and the target population may yield more representative results.

Innovative Strategies for Remotely Sampling Hard-to-Reach Populations: Assessing Phone Versus Internet Respondent-Driven Sampling Approaches Among Venezuelan Refugees and Migrants in Colombia.

It is challenging to quantitatively measure the health vulnerability and risk factors of refugees and migrants residing outside of formal settlement settings. For hard-to-reach populations without available sampling frames, researchers have increasingly turned to novel sampling and statistical methods, like respondent-driven sampling (RDS). "Standard" RDS is typically conducted face-to-face at fixed sites. However, during the coronavirus disease 2019 (COVID-19) pandemic, face-to-face survey methods and recruitment approaches posed high potential risk of virus transmission and infection, making remote RDS approaches optimal. In this paper, we explore the feasibility of implementing telephone and Internet RDS strategies to assess challenges faced by Venezuelan refugees and migrants in the city of Bogotá, Colombia's capital, and the department of Norte de Santander, the main Venezuelan-Colombian border crossing site. We describe RDS assumptions, survey design, formative research, and the implementation of both strategies and present diagnostics for determining whether assumptions are met. Phone-based recruitment strategies in both locations and the Internet strategy in Bogotá achieved their calculated sample size; however, the Internet strategy in Norte de Santander did not. Most RDS assumptions were sufficiently met at sites where sample sizes were reached. These surveys provide valuable lessons for implementing innovative remote strategies with which to study hard-to-reach populations such as refugees and migrants.

Psychosocial factors that distinguish between men and women who have suicidal thoughts and attempt suicide: findings from a national probability sample of adults.

BACKGROUND: Previous research has highlighted the importance of understanding which psychosocial factors distinguish between those with suicide thoughts compared to those who attempt suicide. This study aims to investigate these distinguishing factors further within an ideation-to-action framework and to explore sex differences in suicide risk. METHODS: Participants (n = 7546, aged 16+) were from the cross-sectional Adult Psychiatric Morbidity Survey (APMS; 2014) of England. Face-to-face and self-completion questionnaires assessed lifetime suicidal ideation, lifetime suicide attempts, demographic characteristics, life experiences, social support, health and mental illness. Multinomial logistic regression examined factors differentiating between those with suicidal ideation only and suicide attempt histories (with or without suicidal ideation) in men and women. RESULTS: Overall men were less likely to report suicidal thoughts and attempts, compared to females. More factors differentiated between suicidal thoughts and attempts in women compared to in men; these included hospital admission for mental illness, below degree level qualifications, being single and childhood adversity. In men, factors which significantly differentiated between suicidal thoughts and attempts included self-report of professional diagnosis of mental illness and childhood adversity. Higher levels of social support were associated with being in the suicidal thoughts group v. in the attempts group in men. CONCLUSION: This study identified some key differences between men and women in factors associated with suicide attempts compared to suicidal thoughts. The findings support the use of the ideation-to-action framework to investigate sex differences in suicidal behaviour. Future research should examine the extent to which these factors are associated with suicide risk over time.

Use of COVIDTests.gov At-Home Test Kits Among Adults in a National Household Probability Sample - United States, 2022.

At-home rapid antigen COVID-19 tests were first authorized by the Food and Drug Administration in late 2020 (1-3). In January 2022, the White House launched COVIDTests.gov, which made all U.S. households eligible to receive free-to-the-user at-home test kits distributed by the U.S. Postal Service (2). By May 2022, more than 70 million test kit packages had been shipped to households across the United States (2); however, how these kits were used, and which groups were using them, has not been reported. Data from a national probability survey of U.S. households (COVIDVu), collected during April-May 2022, were used to evaluate awareness about and use of these test kits (4). Most respondent households (93.8%) were aware of the program, and more than one half (59.9%) had ordered kits. Among persons who received testing for COVID-19 during the preceding 6 months, 38.3% used a COVIDTests.gov kit. Among kit users, 95.5% rated the experience as acceptable, and 23.6% reported being unlikely to have tested without the COVIDTests.gov program. Use of COVIDTests.gov kits was similar among racial and ethnic groups (42.1% non-Hispanic Black or African American [Black]; 41.5% Hispanic or Latino [Hispanic]; 34.8% non-Hispanic White [White]; and 53.7% non-Hispanic other races [other races]). Use of other home COVID-19 tests differed by race and ethnicity (11.8% Black, 44.4% Hispanic, 45.8% White, 43.8% other races). Compared with White persons, Black persons were 72% less likely to use other home test kits (adjusted relative risk [aRR] = 0.28; 95% CI = 0.16-0.50). Provision of tests through this well-publicized program likely improved use of COVID-19 home testing and health equity in the United States, particularly among Black persons. National programs to address availability and accessibility of critical health services in a pandemic response have substantial health value.

Models for cluster randomized designs using ranked set sampling.

Cluster randomized designs (CRD) provide a rigorous development for randomization principles for studies where treatments are allocated to cluster units rather than the individual subjects within clusters. It is known that CRDs are less efficient than completely randomized designs since the randomization of treatment allocation is applied to the cluster units. To mitigate this problem, we embed a ranked set sampling design from survey sampling studies into CRD for the selection of both cluster and subsampling units. We show that ranking groups in ranked set sampling act like a covariate, reduce the expected mean squared cluster error, and increase the precision of the sampling design. We provide an optimality result to determine the sample sizes at cluster and sub-sample level. We apply the proposed sampling design to a dental study on human tooth size, and to a longitudinal study from an education intervention program.

Implementation of web-based respondent driven sampling in epidemiological studies.

BACKGROUND: Respondent-driven sampling (RDS) is a peer chain-recruitment method for populations without a sampling frame or that are hard-to-reach. Although RDS is usually done face-to-face, the online version (WebRDS) has drawn a lot of attention as it has many potential benefits, despite this, to date there is no clear framework for its implementation. This article aims to provide guidance for researchers who want to recruit through a WebRDS. METHODS: Description of the development phase: guidance is provided addressing aspects related to the formative research, the design of the questionnaire, the implementation of the coupon system using a free software and the diffusion plan, using as an example a web-based cross-sectional study conducted in Spain between April and June 2022 describing the working conditions and health status of homecare workers for dependent people. RESULTS: The application of the survey: we discuss about the monitoring strategies throughout the recruitment process and potential problems along with proposed solutions. CONCLUSIONS: Under certain conditions, it is possible to obtain a sample with recruitment performance similar to that of other RDS without the need for monetary incentives and using a free access software, considerably reducing costs and allowing its use to be extended to other research groups.

Examining differential success in recruitment using respondent driven sampling (RDS) in a multi-site study of gay, bisexual and other men who have sex with men.

BACKGROUND: The Engage Study is a longitudinal biobehavioral cohort study of gay, bisexual and other men who have sex with men (GBM) in Toronto, Montreal, and Vancouver. Baseline data (2,449 participants) were collected from February 2017 - August 2019 using respondent-driven sampling (RDS). Recruitment in Montreal required fewer seeds, had a much shorter recruitment period, and recruited the largest sample. METHODS: To better understand why RDS recruitment was more successful in Montreal compared to other sites, we conducted an analysis to examine RDS recruitment characteristics for GBM in each of the three study sites, explore demographic characteristics and measures of homophily, that is, the tendency of individuals to recruit other study participants who are like themselves, and compared motivations for study participation. RESULTS: Montreal had the greatest proportion of participants over the age of 45 (29.1% in Montreal, 24.6% in Vancouver, and 21.0% in Toronto) and the highest homophily for this age group, but homophily was high across the three cities. Montreal also reported the lowest percentage of participants with an annual income greater or equal to $60,000 (7.9% in Montreal, 13.1% in Vancouver and 10.6% in Toronto), but homophily was similar across all three cities. The majority of participants indicated interest in sexual health and HIV as the main reason for participating (36.1% in Montreal, 34.7% in Vancouver, and 29.8% in Toronto). Financial interest as the main reason for participation was low (12.7% in Montreal, 10.6% in Vancouver, and 5.7% in Toronto). CONCLUSION: Taken together, although we found some differences in study demographic characteristics and homophily scores, we were unable to fully explain the different recruitment success based on the data available. Our study underlines the fact that success of RDS implementation may vary by unknown factors, and that researchers should be proactive and flexible to account for variability.

Epidemiology of mental health disorders in the citizens of Tehran: a report from Tehran Cohort Study.

BACKGROUND: Mental health disorders (MHD) impose a considerable burden on public health systems. With an increasing worldwide trend in urbanization, urban mental health stressors are affecting a larger population. In this study, we evaluated the epidemiology of mental health disorders in the citizens of Tehran using the Tehran Cohort Study (TeCS) data. METHODS: We utilized data from the TeCS recruitment phase. A total of 10,247 permanent residents of Tehran metropolitan (aged 15 years and older) were enrolled in the study from March 2016 to 2019 via systematic random sampling from all 22 districts of Tehran. The participant's demographic, socioeconomic, and medical characteristics were evaluated by conducting comprehensive interviews. The standardized Persian version of the General Health Questionnaire version 28 was utilized to assess the mental status of the patients according to four central mental health disorders. RESULTS: Almost 37.1% of Tehran residents suffered mental health problems (45.0% of women and 28.0% of men). The greatest incidence of MHDs was seen in the 25-34 and over 75 age groups. The most common mental health disorders were depression (43%) and anxiety (40%), followed by somatization (30%) and social dysfunction (8.1%). Mental health disorders were more frequent in the southeast regions of the city. CONCLUSIONS: Tehran residents have a significantly higher rate of mental health disorders compared to nationwide studies, with an estimated 2.7 million citizens requiring mental health care services. Awareness of mental health disorders and identifying vulnerable groups are crucial in developing mental health care programs by public health authorities.

Lipidemic Effects of Kissing are Mediated by Stress: Results from a National Probability Sample.

Previous studies have identified associations between affectionate communication and blood lipid levels but been limited by small, homogenous samples and failed replication attempts. Moreover, no study has tested the prediction derived from affection exchange theory that stress mediates the association between affectionate behavior and health. Using secondary analyses of data from the Midlife in the United States (MIDUS) Refresher study Biomarker Project, this paper remedies these limitations by testing the prediction that stress mediates the association between kissing and serum levels of triglycerides, high-density lipoproteins, and low-density lipoproteins using a large probability sample of U.S. American adults (N = 863). Results indicate significant indirect effects of kissing frequency on triglycerides and high-density lipoproteins for participants who reported kissing seven or more times in the previous month.

Hidden population size estimation and diagnostics using two respondent-driven samples with applications in Armenia.

Estimating the size of hidden populations is essential to understand the magnitude of social and healthcare needs, risk behaviors, and disease burden. However, due to the hidden nature of these populations, they are difficult to survey, and there are no gold standard size estimation methods. Many different methods and variations exist, and diagnostic tools are needed to help researchers assess method-specific assumptions as well as compare between methods. Further, because many necessary mathematical assumptions are unrealistic for real survey implementation, assessment of how robust methods are to deviations from the stated assumptions is essential. We describe diagnostics and assess the performance of a new population size estimation method, capture-recapture with successive sampling population size estimation (CR-SS-PSE), which we apply to data from 3 years of studies from three cities and three hidden populations in Armenia. CR-SS-PSE relies on data from two sequential respondent-driven sampling surveys and extends the successive sampling population size estimation (SS-PSE) framework by using the number of individuals in the overlap between the two surveys and a model for the successive sampling process to estimate population size. We demonstrate that CR-SS-PSE is more robust to violations of successive sampling assumptions than SS-PSE. Further, we compare the CR-SS-PSE estimates to population size estimations using other common methods, including unique object and service multipliers, wisdom of the crowd, and two-source capture-recapture to illustrate volatility across estimation methods.

TSC loss is a clonal event in eosinophilic solid and cystic renal cell carcinoma: a multiregional tumor sampling study.

Eosinophilic, solid and cystic (ESC) renal cell carcinoma (RCC) is characterized by a solid and cystic architecture with cells showing abundant eosinophilic cytoplasm with hobnail arrangement and a cytokeratin 7-negative/cytokeratin 20-positive immunophenotype. Recent studies have suggested that bi-allelic events affecting TSC genes might play an important role for such tumors. However, only indirect evidence of the clonal origin of TSC mutation has been gathered so far. Therefore, in this paper we aimed to perform multi-regional tumor sampling molecular analysis in four ESC RCC cases that had been completely embedded, three sporadic and one occurring in a patient with tuberous sclerosis complex (TSC). Histologically, the 4 cases showed cystic and solid architecture and cells with abundant eosinophilic cytoplasm with cytoplasmic stippling and round to oval nuclei. Immunohistochemistry showed at least focal expression of cytokeratin 20 in all tissue samples and negative cytokeratin 7, as well as diffuse positivity for S100A1 and at least focal expression of cathepsin K in three out of four cases. The sporadic cases showed the same somatic TSC1 mutations in all tissue samples analyzed, while the TSC-associated case showed the same TSC1 alteration in both normal tissue and all tumor samples analyzed, proving the germline nature of the alteration. In conclusion, our data demonstrate that clonal TSC loss is a key event in ESC RCC and support considering ESC RCC as an entity given its distinct morphologic, immunophenotypical and molecular characteristics.