Abundance and Seasonal Occurrence of Psorophora columbiae in a Northeast Arkansas Ricefield Community

Increased population levels of the dark ricefield mosquito, Psorophora columbiae (Dyar and Knab), have been shown to be associated with rice cultivation in Arkansas and several other states. Four standard New Jersey light traps were operated daily between May 30 and October 2 of 1981 and 1982 to determine the relative abundance and seasonal occurrence of this species in NE Arkansas. The effect of trap distance from nearby rice on the number of adult P. columbiae collected was assessed by comparing weekly totals from 2 traps located within 0.9 km of rice fields with totals from 2 traps situated beyond 1.2 km. A total of 68,155 mosquitoes representing five genera was trapped during this study. Of this number, 45,760 (67.1% of all mosquitos captured) were P. columbiae. Female adults comprised 98.8% of the trapped ricefield mosquitoes. The peak period of abundance for this species was found to occur between mid-July and late August and was closely associated with area rice-culture practices. The capture of more than 95.0% of all P. columbiae adults within 0.9 km of rice fields confirmed the reported short flight range of this species

Rates and Pathways of N2 Production in a Persistently Anoxic Fjord: Saanich Inlet, British Columbia

Marine oxygen minimum zones (OMZs) support 30–50% of global fixed-nitrogen (N) loss but comprise only 7% of total ocean volume. This N-loss is driven by canonical denitrification and anaerobic ammonium oxidation (anammox), and the distribution and activity of these two processes vary greatly in space and time. Factors that regulate N-loss processes are complex, including organic matter availability, oxygen concentrations, and NO2− and NH4+ concentrations. While both denitrification and anammox produce N2, the overall geochemical outcome of these processes are different, as incomplete denitrification, for example, produces N2O, which is a potent greenhouse gas. Information on rates of anammox and denitrification and more detailed ecophysiological knowledge of the microorganisms catalyzing these processes are needed to develop more robust models of N-loss in OMZs. To this end, we conducted monthly incubations with 15N-labeled N during under anoxic conditions and during a deep water renewal cycle in Saanich Inlet, British Columbia, a persistently anoxic fjord. Both denitrification and anammox operated throughout the low oxygen water column with depth integrated rates of anammox and denitrification ranging from 0.15 ± 0.03 to 3.4 ± 0.3 and 0.02 ± 0.006 to 14 ± 2 mmol N2 m−2 d−1, respectively. Most N2 production in Saanich Inlet was driven by denitrification, with high rates developing in response to enhanced substrate supply from deep water renewal. Dynamics in rates of denitrification were linked to shifts in microbial community composition. Notably, periods of intense denitrification were accompanied by blooms in an Arcobacter population against a background community dominated by SUP05 and Marinimicrobia. Rates of N2 production through denitrification and anammox, and their dynamics, were then explored through flux-balance modeling with higher rates of denitrification linked to the physiology of substrate uptake. Overall, both denitrification and anammox operated throughout the year, contributing to an annual N-loss of 2 × 10−3 Tg N2 yr−1, 37% of which we attribute to anammox and 63% to complete denitrification. Extrapolating these rates from Saanich Inlet to all similar coastal inlets in BC (2478 km2), we estimate that these inlets contribute 0.1% to global pelagic N-loss

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder:a mega-analysis by the ENIGMA-PGC PTSD workgroup

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p -FDR &lt; 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.</p

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder:a mega-analysis by the ENIGMA-PGC PTSD workgroup

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p -FDR &lt; 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.</p

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable

Correction to: Cluster identification, selection, and description in Cluster randomized crossover trials: the PREP-IT trials

An amendment to this paper has been published and can be accessed via the original article

American College of Rheumatology Provisional Criteria for Clinically Relevant Improvement in Children and Adolescents With Childhood-Onset Systemic Lupus Erythematosus

10.1002/acr.23834ARTHRITIS CARE & RESEARCH715579-59

Initial Benchmarking Of The Quality Of Medical Care In Childhood-onset Systemic Lupus Erythematosus.

To assess the quality of medical care in childhood-onset systemic lupus erythematosus (SLE) at tertiary pediatric rheumatology centers as measured by observance of SLE quality indicators (SLE-QIs). International consensus has been achieved for childhood-onset SLE-QIs capturing medical care provision in 9 domains: diagnostic testing, education of cardiovascular (CV) risk and lifestyles, lupus nephritis (LN), medication management, bone health, ophthalmologic surveillance, transition, pregnancy, and vaccination. Using medical record information, the level of performance of these childhood-onset SLE-QIs was assessed in childhood-onset SLE populations treated at 4 tertiary pediatric rheumatology centers in the US, 2 in Brazil, and 1 center in India. A total of 483 childhood-onset SLE patients were assessed. Care for the 310 US patients differed markedly for childhood-onset SLE-QIs addressing LN, bone health, vaccinations, education on CV risk, and transition planning. Performance of safety blood testing for medications was high at all centers. Despite often similar performance on the childhood-onset SLE-QI, access to kidney biopsies was lower in Brazil than in the US. Irrespective of the country of practice, larger centers tended to meet the childhood-onset SLE-QIs more often than smaller centers. The childhood-onset SLE-QIs, evidence-based minimum standards of medical care, are not consistently met in the US or some other countries outside the US. This has the potential to contribute to suboptimal childhood-onset SLE outcomes.68179-18