18 research outputs found

    Spitzer observations of the Massive star forming complex S254-S258: structure and evolution

    Full text link
    We present Spitzer-IRAC, NOAO 2.1meter-Flamingos, Keck-NIRC, and FCRAO-SEQUOIA observations of the massive star forming complex S254-S258, covering an area of 25x20 arc-minutes. Using a combination of the IRAC and NIR data, we identify and classify the young stellar objects (YSO) in the complex. We detect 510 sources with near or mid IR-excess, and we classify 87 Class I, and 165 Class II sources. The YSO are found in clusters surrounded by isolated YSO in a low-density distributed population. The ratio of clustered to total YSO is 0.8. We identify six new clusters in the complex. One of them, G192.63-00, is located around the ionizing star of the HII region S255. We hypothesize that the ionizing star of S255 was formed in this cluster. We also detect a southern component of the cluster in HII region S256. The cluster G192.54-0.15, located inside HII region S254 has a VLSR of 17 km/s with respect to the main cloud, and we conclude that it is located in the background of the complex. The structure of the molecular cloud is examined using 12CO and 13CO, as well as a near-IR extinction map. The main body of the molecular cloud has VLSR between 5 and 9 km/s. The arc-shaped structure of the molecular cloud, following the border of the HII regions, and the high column density in the border of the HII regions support the idea that the material has been swept up by the expansion of the HII regions.Comment: Accepted for publication in The Astrophysical Journa

    Psychological Distress Among Ethnically Diverse Participants From Eastern and Southern Africa

    Get PDF
    IMPORTANCE: Psychological distress is characterized by anxiety and depressive symptoms. Although prior research has investigated the occurrence and factors associated with psychological distress in low- and middle-income countries, including those in Africa, these studies' findings are not very generalizable and have focused on different kinds of population groups. OBJECTIVE: To investigate the prevalence and characteristics (sociodemographic, psychosocial, and clinical) associated with psychological distress among African participants. DESIGN, SETTING, AND PARTICIPANTS: This case-control study analyzed data of participants in the Neuropsychiatric Genetics in African Populations-Psychosis (NeuroGAP-Psychosis) study, which recruited from general outpatient clinics in Eastern (Uganda, Kenya, and Ethiopia) and Southern (South Africa) Africa. Individuals who participated in the control group of NeuroGAP-Psychosis from 2018 to 2023 were analyzed as part of this study. Data were analyzed from May 2023 to January 2024. MAIN OUTCOMES AND MEASURES: The prevalence of psychological distress was determined using the Kessler Psychological Distress Scale (K10), which measures distress on a scale of 10 to 50, with higher scores indicating more distress. Participants from the NeuroGAP-Psychosis study were categorized into cases as mild (score of 20-24), moderate (score of 25-29), and severe (score of 30-50), and participants with scores less than 20 were considered controls. Factors that were associated with psychological distress were examined using binomial logistic regression. RESULTS: From the data on 21 308 participants, the mean (SD) age was 36.5 (11.8) years, and 12 096 participants (56.8%) were male. The majority of the participants were married or cohabiting (10 279 participants [48.2%]), most had attained secondary education as their highest form of learning (9133 participants [42.9%]), and most lived with their families (17 231 participants [80.9%]). The prevalence of mild, moderate, and severe psychological distress was 4.2% (869 participants), 1.5% (308 participants), and 0.8% (170 participants), respectively. There were 19 961 participants (93.7%) who served as controls. Binomial logistic regression analyses indicated that the independent associations of psychological distress were experience of traumatic events, substance use (alcohol, tobacco, or cannabis), the physical comorbidity of arthritis, chronic neck or back pain, and frequent or severe headaches. CONCLUSIONS AND RELEVANCE: In this case-control study among ethnically diverse African participants, psychological distress was associated with traumatic stress, substance use, and physical symptoms. These findings were observed to be consistent with previous research that emphasizes the importance of traumatic events as a factor associated with risk for psychopathology and notes the frequent co-occurrence of conditions such as physical symptoms, depression, and anxiety

    Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

    Get PDF
    Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

    Calcium-independent smooth muscle contraction: a focus on zipper-interacting protein kinase (ZIPK)

    No full text
    Bibliography: p. 206-222.Many pages are in colour.Includes copy of Certification of Animal Protocol Approval form. Original with original copy of Partial Copyright Licence

    Ca 2+

    No full text

    Identifying chemogenetic interactions from CRISPR screens with drugZ

    No full text
    Abstract Background Chemogenetic profiling enables the identification of gene mutations that enhance or suppress the activity of chemical compounds. This knowledge provides insights into drug mechanism of action, genetic vulnerabilities, and resistance mechanisms, all of which may help stratify patient populations and improve drug efficacy. CRISPR-based screening enables sensitive detection of drug-gene interactions directly in human cells, but until recently has primarily been used to screen only for resistance mechanisms. Results We present drugZ, an algorithm for identifying both synergistic and suppressor chemogenetic interactions from CRISPR screens. DrugZ identifies synthetic lethal interactions between PARP inhibitors and both known and novel members of the DNA damage repair pathway, confirms KEAP1 loss as a resistance factor for ERK inhibitors in oncogenic KRAS backgrounds, and defines the genetic context for temozolomide activity. Conclusions DrugZ is an open-source Python software for the analysis of genome-scale drug modifier screens. The software accurately identifies genetic perturbations that enhance or suppress drug activity. Interestingly, analysis of new and previously published data reveals tumor suppressor genes are drug-agnostic resistance genes in drug modifier screens. The software is available at github.com/hart-lab/drugz
    corecore