Search

Research Highlights The brain undergoes extensive development during late childhood and early adolescence. Cortical thinning is a prominent feature of this development, and some researchers have suggested that differences in cortical thickness may be related to internalizing symptoms, which typically increase during the same period. However, research has yielded inconclusive results. We utilized a new method that estimates the combined effect of individual differences in vertex‐wise cortical thickness on internalizing symptoms. This approach allows for many small effects to be distributed across the cortex and avoids the necessity of correcting for multiple tests. Using a sample of 8763 children aged 8.9 to 11.1 from the ABCD study, we decomposed the total variation in caregiver‐reported internalizing symptoms into differences in cortical thickness, additive genetics, and shared family environmental factors and unique environmental factors. Our results indicated that individual differences in cortical thickness accounted for less than 0.5% of the variation in internalizing symptoms. In contrast, the analysis revealed a substantial effect of additive genetics and family environmental factors on the different components of internalizing symptoms, ranging from 06% to 48% and from 0% to 34%, respectively. Overall, while this study found a minimal association between cortical thickness and internalizing symptoms, additive genetics, and familial environmental factors appear to be of importance for describing differences in internalizing symptoms in late childhood. We utilized a new method for modelling the total contribution of vertex‐wise individual differences in cortical thickness to internalizing symptoms in late childhood. The total contribution of individual differences in cortical thickness accounted for <0.5% of the variance in internalizing symptoms. Additive genetics and shared family environmental variation accounted for 17% and 34% of the variance in internalizing symptoms, respectively. Our results suggest that cortical thickness is not an important indicator for internalizing symptoms in childhood, whereas genetic and environmental differences have a substantial impact. [ABSTRACT FROM AUTHOR]

About 25% of melanoma harbor activating NRAS mutations, which are associated with aggressive disease therefore requiring a rapid antitumor intervention. However, no efficient targeted therapy options are currently available for patients with NRAS‐mutant melanoma. MEK inhibitors (MEKi) appear to display a moderate antitumor activity and also immunological effects in NRAS‐mutant melanoma, providing an ideal backbone for combination treatments. In our study, the MEKi binimetinib, cobimetinib and trametinib combined with the BRAF inhibitors (BRAFi) encorafenib, vemurafenib and dabrafenib were investigated for their ability to inhibit proliferation, induce apoptosis and alter the expression of immune modulatory molecules in sensitive NRAS‐mutant melanoma cells using two‐ and three‐dimensional cell culture models as well as RNA sequencing analyses. Furthermore, NRAS‐mutant melanoma cells resistant to the three BRAFi/MEKi combinations were established to characterize the mechanisms contributing to their resistance. All BRAFi induced a stress response in the sensitive NRAS‐mutant melanoma cells thereby significantly enhancing the antiproliferative and proapoptotic activity of the MEKi analyzed. Furthermore, BRAFi/MEKi combinations upregulated immune relevant molecules, such as ICOS‐L, components of antigen‐presenting machinery and the "don't eat me signal" molecule CD47 in the melanoma cells. The BRAFi/MEKi‐resistant, NRAS‐mutant melanoma cells counteracted the molecular and immunological effects of BRAFi/MEKi by upregulating downstream mitogen‐activated protein kinase pathway molecules, inhibiting apoptosis and promoting immune escape mechanisms. Together, our study reveals potent molecular and immunological effects of BRAFi/MEKi in sensitive NRAS‐mutant melanoma cells that may be exploited in new combinational treatment strategies for patients with NRAS‐mutant melanoma. [ABSTRACT FROM AUTHOR]

Background: Clinical forecasting models have potential to optimize treatment and improve outcomes in psychosis, but predicting long-term outcomes is challenging and long-term follow-up data are scarce. In this 10-year longitudinal study, we aimed to characterize the temporal evolution of cortical correlates of psychosis and their associations with symptoms., Design: Structural magnetic resonance imaging (MRI) from people with first-episode psychosis and controls (n = 79 and 218) were obtained at enrollment, after 12 months (n = 67 and 197), and 10 years (n = 23 and 77), within the Thematically Organized Psychosis (TOP) study. Normative models for cortical thickness estimated on public MRI datasets (n = 42 983) were applied to TOP data to obtain deviation scores for each region and timepoint. Positive and Negative Syndrome Scale (PANSS) scores were acquired at each timepoint along with registry data. Linear mixed effects models assessed effects of diagnosis, time, and their interactions on cortical deviations plus associations with symptoms., Results: LMEs revealed conditional main effects of diagnosis and time × diagnosis interactions in a distributed cortical network, where negative deviations in patients attenuate over time. In patients, symptoms also attenuate over time. LMEs revealed effects of anterior cingulate on PANSS total, and insular and orbitofrontal regions on PANSS negative scores., Conclusions: This long-term longitudinal study revealed a distributed pattern of cortical differences which attenuated over time together with a reduction in symptoms. These findings are not in line with a simple neurodegenerative account of schizophrenia, and deviations from normative models offer a promising avenue to develop biomarkers to track clinical trajectories over time., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.)

It is so far unclear how the COVID-19 winter waves started and what should be done to prevent possible future waves. In this study, we deciphered the dynamic course of a winter wave in 2021 in Saxony, a state in Eastern Germany neighbouring the Czech Republic and Poland. The study was carried out through the integration of multiple virus genomic epidemiology approaches to track transmission chains, identify emerging variants and investigate dynamic changes in transmission clusters. For identified local variants of interest, functional evaluations were performed. Multiple long-lasting community transmission clusters have been identified acting as driving force for the winter wave 2021. Analysis of the dynamic courses of two representative clusters indicated a similar transmission pattern. However, the transmission cluster caused by a locally occurring new Delta variant AY.36.1 showed a distinct transmission pattern, and functional analyses revealed a replication advantage of it. This study indicated that long-lasting community transmission clusters starting since early autumn caused by imported or locally occurring variants all contributed to the development of the 2021 winter wave. The information we achieved might help future pandemic prevention.