Our findings do not provide support for a social media specific attentional bias. While there was a large range of individual differences in our measures of use, engagement, and 'addictive' severity, these were not predictive of, or associated with, individual differences in the magnitude of attentional capture by social media stimuli. More research is required before social media use can be definitively placed within an addiction framework. More research is required before social media use can be definitively placed within an addiction framework. The clinical utility and prognostic value of WHO 2017 lineage-based classification of pituitary tumours have not been assessed. This study aimed to (1) determine the clinical utility of transcription factor analysis for classification of pituitary tumours and (2) determine the prognostic value of improved lineage-based classification of pituitary tumours. This was a retrospective evaluation of patients who underwent surgical resection of pituitary tumours at St Vincent's Public and Private Hospitals, Sydney, Australia between 1990 and 2016. Included patients were at least 18 years of age and had complete histopathological data, forming the 'histological cohort'. Patients with at least 12 months of post-surgical follow-up were included in the subgroup 'clinical cohort'. The diagnostic efficacy of transcription factor immunohistochemistry in conjunction with hormone immunohistochemistry was compared with hormone immunohistochemistry alone. The prognostic value of identifying 'higher-risk' histological subtypes was assessed. There were 171 patient tumour samples analyzed in the histological cohort. https://www.selleckchem.com/products/bay-87-2243.html Of these, there were 95 patients forming the clinical cohort. Subtype diagnosis was changed in 20/171 (12%) of tumours. Within the clinical cohort, there were 21/95 (22%) patients identified with higher-risk histological subtype tumours. These were associated with tumour invasiveness (P = 0.050), early recurrence (12-24 months, P = 0.013), shorter median time to recurrence (49 (IQR 22.5-73.0) vs 15 (IQR 12.0-25.0) months, P = 0.005) and reduced recurrence-free survival (P = 0.031). Application of transcription factor analysis, in addition to hormone immunohistochemistry, allows for refined pituitary tumour classification and may facilitate an improved approach to prognostication. Application of transcription factor analysis, in addition to hormone immunohistochemistry, allows for refined pituitary tumour classification and may facilitate an improved approach to prognostication. We aimed to investigate the interaction of reduced skeletal muscle mass and abdominal obesity on coronary artery calcification (CAC). A total of 19 728 adults free of cardiovascular disease (CVD) who contemporaneously underwent cardiac tomography and bioelectrical impedance analysis were enrolled in a cross-sectional and longitudinal cohort. Skeletal muscle mass index (SMI) was calculated using the following formula SMI (%) = total appendicular muscle mass (kg)/body weight (kg) × 100 according to sex. CAC presence or incidence was defined as CAC score > 0, and CAC progression was defined as √CAC score (follow-up) - √CAC score (baseline)>2.5. Pre-sarcopenia was defined as SMI ≤ -1.0 s.d. of the sex-specific mean of a young reference group. Abdominal obesity was defined as waist circumference ≥ 90 cm for men and ≥85 cm for women. All individuals were further classified into four groups normal, abdominal obesity alone, pre-sarcopenia alone, and pre-sarcopenic obesity. Individuals with pre-sarcopenic obesity showed the highest adjusted odds ratio (AOR) for CAC presence (AOR 2.16, 95% CI 1.98-2.36, P < 0.001) as well as total CAC incidence and progression (adjusted hazard ratio 1.54, 95% CI 1.37-1.75, P < 0.001), compared with normal individuals. Pre-sarcopenic obesity significantly increased CAC incidence and progression compared to either pre-sarcopenia or abdominal obesity alone. Pre-sarcopenia and abdominal obesity together were significantly associated with a higher CAC presence and increased risk of CAC incidence and progression, independent of traditional CVD risk factors. Pre-sarcopenia and abdominal obesity together were significantly associated with a higher CAC presence and increased risk of CAC incidence and progression, independent of traditional CVD risk factors.There are different ways to quantify the relation between two or more continuous variables. Some researchers use correlation coefficients; others will apply regression methods such as linear regression. In this paper, we show that the choice between correlation and regression is not purely a statistical one but largely depends on the research aims. Importantly, one should always inspect the data before using either of the two methods. The COVID-19 pandemic and containment measures have severely affected families around the world. It is frequently assumed that digital technologies can supplement and perhaps even replace services for families. This is challenging in conditions of high device and data costs as well as poor internet provision and access, raising concerns about widening inequalities in availability of support and consequent effects on child and family outcomes. Very few studies have examined these issues, including in low- and middle-income countries. The study objectives were two-fold. The first objective was to gather data on the impact of the COVID-19 pandemic on families of young children using an online survey. The second objective was to assess the feasibility of using a data-free online platform to conduct regular surveys and, potentially, to provide support for parents and families of young children in South Africa. We used a data-free mobile messenger platform to conduct a short digital survey of the impact of thhnology allows for immediate feedback to respondents. These factors suggest that zero-rated, or no-cost, services could provide a feasible, sustainable, and equitable basis for ongoing interactions with families of young children. The COVID-19 pandemic has placed unprecedented stress on economies, food systems, and health care resources in Latin America and the Caribbean (LAC). Existing surveillance provides a proxy of the COVID-19 caseload and mortalities; however, these measures make it difficult to identify the dynamics of the pandemic and places where outbreaks are likely to occur. Moreover, existing surveillance techniques have failed to measure the dynamics of the pandemic. This study aimed to provide additional surveillance metrics for COVID-19 transmission to track changes in the speed, acceleration, jerk, and persistence in the transmission of the pandemic more accurately than existing metrics. Through a longitudinal trend analysis, we extracted COVID-19 data over 45 days from public health registries. We used an empirical difference equation to monitor the daily number of cases in the LAC as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R.