Structural and functional abnormities of amygdala and prefrontal cortex in major depressive disorder with suicide attempts

Finding neural features of suicide attempts (SA) in major depressive disorder (MDD) may be helpful in preventing suicidal behavior. The ventral and medial prefrontal cortex (PFC), as well as the amygdala form a circuit implicated in emotion regulation and the pathogenesis of MDD. The aim of this study was to identify whether patients with MDD who had a history of SA show structural and functional connectivity abnormalities in the amygdala and PFC relative to MDD patients without a history of SA. We measured gray matter volume in the amygdala and PFC and amygdala-PFC functional connectivity using structural and functional magnetic resonance imaging (MRI) in 158 participants [38 MDD patients with a history of SA, 60 MDD patients without a history of SA, and 60 healthy control (HC)]. MDD patients with a history of SA had decreased gray matter volume in the right and left amygdala (F = 30.270, P = 0.000), ventral/medial/dorsal PFC (F = 15.349, P = 0.000), and diminished functional connectivity between the bilateral amygdala and ventral and medial PFC regions (F = 22.467, P = 0.000), compared with individuals who had MDD without a history of SA, and the HC group. These findings provide evidence that the amygdala and PFC may be closely related to the pathogenesis of suicidal behavior in MDD and implicate the amygdala-ventral/medial PFC circuit as a potential target for suicide intervention

Structural and functional abnormities of amygdala and prefrontal cortex in major depressive disorder with suicide attempts

Finding neural features of suicide attempts (SA) in major depressive disorder (MDD) may be helpful in preventing suicidal behavior. The ventral and medial prefrontal cortex (PFC), as well as the amygdala form a circuit implicated in emotion regulation and the pathogenesis of MDD. The aim of this study was to identify whether patients with MDD who had a history of SA show structural and functional connectivity abnormalities in the amygdala and PFC relative to MDD patients without a history of SA. We measured gray matter volume in the amygdala and PFC and amygdala-PFC functional connectivity using structural and functional magnetic resonance imaging (MRI) in 158 participants [38 MDD patients with a history of SA, 60 MDD patients without a history of SA, and 60 healthy control (HC)]. MDD patients with a history of SA had decreased gray matter volume in the right and left amygdala (F = 30.270, P = 0.000), ventral/medial/dorsal PFC (F = 15.349, P = 0.000), and diminished functional connectivity between the bilateral amygdala and ventral and medial PFC regions (F = 22.467, P = 0.000), compared with individuals who had MDD without a history of SA, and the HC group. These findings provide evidence that the amygdala and PFC may be closely related to the pathogenesis of suicidal behavior in MDD and implicate the amygdala-ventral/medial PFC circuit as a potential target for suicide intervention

Road Assessment Model and Pilot Application in China

Risk assessment of roads is an effective approach for road agencies to determine safety improvement investments. It can increases the cost-effective returns in crash and injury reductions. To get a powerful Chinese risk assessment model, Research Institute of Highway (RIOH) is developing China Road Assessment Programme (ChinaRAP) model to show the traffic crashes in China in partnership with International Road Assessment Programme (iRAP). The ChinaRAP model is based upon RIOH’s achievements and iRAP models. This paper documents part of ChinaRAP’s research work, mainly including the RIOH model and its pilot application in a province in China

Influence of external heat sources on volumetric thermal errors of precision machine tools

Volumetric accuracy is susceptible to thermal gradient caused by internal heat source (IHS) and external heat source (EHS). A temperature-structure multi-step calculation method is presented to investigate the influences of EHSs on volumetric thermal errors of precision machine tools. The temperature and structure of the machine tool are simulated first, and then, the volumetric thermal errors are calculated using multi-body theory method. Simulations are completed to study the effects of different EHSs on a machine tool, and series of validating experiments are carried out to verify the modeling method. The test results in specific position and working condition revealed that EHSs contribute 53, 21, and 68% of thermal deviations in X, Y, and Z directions individually. It is illustrated that the EHS is an important factor affecting the volumetric accuracy of precision machine tools. The methods provided in this paper are valuable for machine tool designers to evaluate the EHS effects on volumetric thermal errors during designing process; furthermore, some insulating measures are suggested to improve the accuracy and accuracy stability of precision machine tools by reducing the EHS influences

Application of the Empirical Bayes Method with the Finite Mixture Model for Identifying Accident-Prone Spots

Hotspot identification (HSID) is an important component of the highway safety management process. A number of methods have been proposed to identify hotspots. Among these methods, previous studies have indicated that the empirical Bayes (EB) method can outperform other methods for identifying hotspots, since the EB method combines the historical crash records of the site and expected number of crashes obtained from a safety performance function (SPF) for similar sites. However, the SPFs are usually developed based on a large number of sites, which may contain heterogeneity in traffic characteristic. As a result, the hotspot identification accuracy of EB methods can possibly be affected by SPFs, when heterogeneity is present in crash data. Thus, it is necessary to consider the heterogeneity and homogeneity of roadway segments when using EB methods. To address this problem, this paper proposed three different classification-based EB methods to identify hotspots. Rural highway crash data collected in Texas were analyzed and classified into different groups using the proposed methods. Based on the modeling results for Texas crash dataset, it is found that one proposed classification-based EB method performs better than the standard EB method as well as other HSID methods

The grading detection model for fingered citron slices (citrus medica ‘fingered’) based on YOLOv8-FCS

IntroductionFingered citron slices possess significant nutritional value and economic advantages as herbal products that are experiencing increasing demand. The grading of fingered citron slices plays a crucial role in the marketing strategy to maximize profits. However, due to the limited adoption of standardization practices and the decentralized structure of producers and distributors, the grading process of fingered citron slices requires substantial manpower and lead to a reduction in profitability. In order to provide authoritative, rapid and accurate grading standards for the market of fingered citron slices, this paper proposes a grading detection model for fingered citron slices based on improved YOLOv8n.MethodsFirstly, we obtained the raw materials of fingered citron slices from a dealer of Sichuan fingered citron origin in Shimian County, Ya'an City, Sichuan Province, China. Subsequently, high-resolution fingered citron slices images were taken using an experimental bench, and the dataset for grading detection of fingered citron slices was formed after manual screening and labelling. Based on this dataset, we chose YOLOv8n as the base model, and then replaced the YOLOv8n backbone structure with the Fasternet main module to improve the computational efficiency in the feature extraction process. Then we redesigned the PAN-FPN structure used in the original model with BiFPN structure to make full use of the high-resolution features to extend the sensory field of the model while balancing the computation amount and model volume, and finally we get the improved target detection algorithm YOLOv8-FCS.ResultsThe findings from the experiments indicated that this approach surpassed the conventional RT-DETR, Faster R-CNN, SSD300 and YOLOv8n models in most evaluation indicators. The experimental results show that the grading accuracy of the YOLOv8-FCS model reaches 98.1%, and the model size is only 6.4 M, and the FPS is 130.3.DiscussionThe results suggest that our model offers both rapid and precise grading for fingered citron slices, holding significant practical value for promoting the advancement of automated grading systems tailored to fingered citron slices

Surface water numerical modelling for the Clarence-Moreton bioregion. Product 2.6.1 from the Clarence-Moreton Bioregional Assessment

No abstract available

Downregulation of MicroRNA-9 in iPSC-Derived Neurons of FTD/ALS Patients with TDP-43 Mutations

Transactive response DNA-binding protein 43 (TDP-43) is a major pathological protein in frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). There are many disease-associated mutations in TDP-43, and several cellular and animal models with ectopic overexpression of mutant TDP-43 have been established. Here we sought to study altered molecular events in FTD and ALS by using induced pluripotent stem cell (iPSC) derived patient neurons. We generated multiple iPSC lines from an FTD/ALS patient with the TARDBP A90V mutation and from an unaffected family member who lacked the mutation. After extensive characterization, two to three iPSC lines from each subject were selected, differentiated into postmitotic neurons, and screened for relevant cell-autonomous phenotypes. Patient-derived neurons were more sensitive than control neurons to 100 nM straurosporine but not to other inducers of cellular stress. Three disease-relevant cellular phenotypes were revealed under staurosporine-induced stress. First, TDP-43 was localized in the cytoplasm of a higher percentage of patient neurons than control neurons. Second, the total TDP-43 level was lower in patient neurons with the A90V mutation. Third, the levels of microRNA-9 (miR-9) and its precursor pri-miR-9-2 decreased in patient neurons but not in control neurons. The latter is likely because of reduced TDP-43, as shRNA-mediated TDP-43 knockdown in rodent primary neurons also decreased the pri-miR-9-2 level. The reduction in miR-9 expression was confirmed in human neurons derived from iPSC lines containing the more pathogenic TARDBP M337V mutation, suggesting miR-9 downregulation might be a common pathogenic event in FTD/ALS. These results show that iPSC models of FTD/ALS are useful for revealing stress-dependent cellular defects of human patient neurons containing rare TDP-43 mutations in their native genetic contexts

Surface water numerical modelling for the Clarence-Moreton bioregion. Product 2.6.1 from the Clarence-Moreton Bioregional Assessment

No abstract available