Distribution of sedimentary rock types through time in a back-arc basin: A case study from the Jurassic of the Greater Caucasus (Northern Neotethys)

Abstract The evolution of sedimentary basins can be explored by analyzing the changes in their lithologies and lithofacies (i.e. predominant lithologies). The Greater Caucasus Basin, which was located at the northern margin of the Neotethys Ocean, represents a complete Sinemurian-Tithonian succession. A quantitative analysis of compiled datasets suggests that principal lithologies and lithofacies are represented by siliciclastics, shale and carbonates. The relative abundance of siliciclastics and shale decreased throughout the Jurassic, whereas that of carbonates increased. Evaporites are known from the Upper Jurassic, while volcaniclastics and volcanics, as well as coals, are known only in the Lower to Middle Jurassic. Siliceous rocks are extremely rare. Lithology and lithofacies proportions change accordingly. The Sinemurian-Bathonian sedimentary complex is siliciclastic-and-shale-dominated, whereas the Callovian-Tithonian sedimentary complex is carbonate-dominated. A major change in the character of sedimentation occurred during the Aalenian-Callovian time interval. Regional transgressions and regressions were more important controls of changes in the sedimentary rock proportions than average basin depth. Landward shoreline shifts were especially favorable for carbonate accumulation, whereas siliciclastics and shale were deposited preferentially in regressive settings. An extended area of the marine basin, its lower average depth, and a sharp bathymetric gradient favored a higher diversity of sedimentation. An orogeny at the Triassic-Jurassic transition was responsible for a large proportion of siliciclastics and extensive conglomerate deposition. An arcarc collision in the Middle Jurassic also enhanced the siliciclastic deposition. Both phases of tectonic activity were linked with an increase in volcanics and volcaniclastics. Volcanism itself might have been an important control on sedimentation. A transition to carbonate-dominated sedimentation occurred in the Late Jurassic, reflecting a tectonically calm period

Physics of Solar Prominences: II - Magnetic Structure and Dynamics

Observations and models of solar prominences are reviewed. We focus on non-eruptive prominences, and describe recent progress in four areas of prominence research: (1) magnetic structure deduced from observations and models, (2) the dynamics of prominence plasmas (formation and flows), (3) Magneto-hydrodynamic (MHD) waves in prominences and (4) the formation and large-scale patterns of the filament channels in which prominences are located. Finally, several outstanding issues in prominence research are discussed, along with observations and models required to resolve them.Comment: 75 pages, 31 pictures, review pape

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Enhanced glycemic control with combination therapy for type 2 diabetes in primary care

Type 2 diabetes mellitus is an increasingly common medical problem for primary care clinicians to address. Treatment of diabetes has evolved from simple replacement of insulin (directly or through insulin secretagogs) through capture of mechanisms such as insulin sensitizers, alpha-glucosidase inhibitors, and incretins. Only very recently has recognition of the critical role of the gastrointestinal system as a major culprit in glucose dysregulation been established. Since glycated hemoglobin A1c reductions provide meaningful risk reduction as well as improved quality of life, it is worthwhile to explore evolving paths for more efficient use of the currently available pharmacotherapies. Because diabetes is a progressive disease, even transiently successful treatment will likely require augmentation as the disorder progresses. Pharmacotherapies with complementary mechanisms of action will be necessary to achieve glycemic goals. Hence, clinicians need to be well informed about the various noninsulin alternatives that have been shown to be successful in glycemic goal attainment. This article reviews the benefits of glucose control, the current status of diabetes control, pertinent pathophysiology, available pharmacological classes for combination, limitations of current therapies, and suggestions for appropriate combination therapies, including specific suggestions for thresholds at which different strategies might be most effectively utilized by primary care clinicians

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Editorial Statement About JCCAP’s 2023 Special Issue on Informant Discrepancies in Youth Mental Health Assessments: Observations, Guidelines, and Future Directions Grounded in 60 Years of Research

Issue 1 of the 2011 Volume of the Journal of Clinical Child and Adolescent Psychology (JCCAP) included a Special Section about the use of multi-informant approaches to measure child and adolescent (i.e., hereafter referred to collectively as “youth”) mental health (De Los Reyes, 2011). Researchers collect reports from multiple informants or sources (e.g., parent and peer, youth and teacher) to estimate a given youth’s mental health. The 2011 JCCAP Special Section focused on the most common outcome of these approaches, namely the significant discrepancies that arise when comparing estimates from any two informant’s reports (i.e., informant discrepancies). These discrepancies appear in assessments conducted across the lifespan (Achenbach, 2020). That said, JCCAP dedicated space to understanding informant discrepancies, because they have been a focus of scholarship in youth mental health for over 60 years (e.g., Achenbach et al., 1987; De Los Reyes & Kazdin, 2005; Glennon & Weisz, 1978; Kazdin et al., 1983; Kraemer et al., 2003; Lapouse & Monk, 1958; Quay et al., 1966; Richters, 1992; Rutter et al., 1970; van der Ende et al., 2012). Thus, we have a thorough understanding of the areas of research for which they reliably appear when clinically assessing youth. For instance, intervention researchers observe informant discrepancies in estimates of intervention effects within randomized controlled trials (e.g., Casey & Berman, 1985; Weisz et al., 2017). Service providers observe informant discrepancies when working with individual clients, most notably when making decisions about treatment planning (e.g., Hawley & Weisz, 2003; Hoffman & Chu, 2015). Scholars in developmental psychopathology observe these discrepancies when seeking to understand risk and protective factors linked to youth mental health concerns (e.g., Hawker & Boulton, 2000; Hou et al., 2020; Ivanova et al., 2022). Thus, the 2011 JCCAP Special Section posed a question: Might these informant discrepancies contain data relevant to understanding youth mental health? Suppose none of the work in youth mental health is immune from these discrepancies. In that case, the answer to this question strikes at the core of what we produce―from the interventions we develop and implement, to the developmental psychopathology research that informs intervention development