Associations Among Suicidal Ideation, White Matter Integrity and Cognitive Deficit in First-Episode Schizophrenia

Objective: The study was aimed to investigate the possible associations among suicidal ideation, brain white matter (WM) integrity and cognitive deficit in first-episode schizophrenia (FES) using diffusion tensor imaging.Methods: The sample contained 18 FES patients with suicidal ideation (SI+), 45 FES patients without suicidal ideation (SI–) and 44 healthy controls. The Calgary Depression Scale for Schizophrenia was used to measure the suicidal ideation and depression symptoms. The whole brain WM integrity and three domains of cognitive function: working memory, verbal comprehension as well as processing speed were compared between the three groups.Results: Compared with SI–, SI+ showed preserved WM integrity as indicated by significantly higher factional anisotropy (FA) or lower mean diffusivity (MD) in multiple WM tracts, and higher FA coupled with lower MD in bilateral posterior corona radiata. Compared with SI−, SI+ were more depressed and had less cognitive deficit in working memory and verbal comprehension. The fiber tracts in bilateral posterior corona radiata connect to the precuneus as shown by probabilistic tractography, and their WM integrity disruptions were found to be positively associated with the cognitive deficits in the FES patients.Discussion: Preserved WM integrity may be a risk factor for suicidal ideation in FES patients. One possible explanation is that it contributes to preserved cognitive function, especially in working memory and verbal comprehension, which may be associated with greater insight and could lead to increased depression and suicidal ideation. The posterior corona radiata and the precuneus may be linked to the related biological processes

Spatio-temporal evolution of population mobility differentiation patterns in a pandemic context: based on a network perspective

AbstractThe COVID-19 has caused adverse effects in various aspects, and its impact on population mobility cannot be ignored. In this study, we obtain mobility data for the Beijing–Tianjin–Hebei region during the Chunyun period of 2019–2021 and divide it into four stages. By developing directional weighted networks, the mobility patterns for pre- and post-epidemic are examined. Firstly, the migration scale declines significantly post-epidemic. The fourth stage migration scale exceeds 65% of 2019 in 2021 indicating the situation improves. Secondly, the structural characteristics are compared. The average degree values, clustering coefficients, and path lengths in the fourth stage of 2021 are higher than the values in 2020, showing the recovery of migration, but also efficiency degradation. Thirdly, community detection results show that three communities can be highlighted in the network, which followed Regional Development Pattern. Finally, the findings of Modified Alter-based Centrality and Alter-based Power models show that Beijing (27.78, 17.74) and Tianjin (14.92, 4.38) are typical cities, Tangshan (3.74, 0.03) and Langfang (3.40, 2.00) are gateway cities and others are general cities. A reasonable population distribution has not been formed. The study provides fresh perspectives for applying spatio-temporal data in health emergencies, and the results provide theoretical support for policy formulation of socio-economic recovery

Uncertainty Analysis of Inverse Problem of Resistivity Model in Internal Defects Detection of Buildings

Fissure detection in ancient buildings is of vital importance in the evaluation of resistance or remediation in urban areas. Electrical resistivity imaging is an efficient tool to detect fissures or moisture erosion in buildings by highlighting the resistivity contrasts in the inversion models. The traditional results of ERT images give deterministic interpretations of the internal artifact. However, the existence of equivalent models may correspond to different physical realities in engineering cases, to which the traditional ERT model cannot respond. In this paper, through the application of a field test on an ancient wall, it is shown that the segmentation of the equivalent model family is applicable to solve the internal defects detection problem in a probabilistic approach. It is achieved by performing a probabilistic approach to apply the uncertainty analysis. The procedure begins with the reduction in dimensions of the model by spectral decomposition, and the uncertainty space is rebuilt via Particle Swarm Optimization (PSO). By computing the uncertainty space, probabilistic maps are created to demonstrate the electrical anomaly in a simpler structure. The proposed method provides a more accurate approach for the internal defects detection of buildings by considering the possibilities hidden in the equivalent model family of ERT results

Adjustable thermal expansion in La(Fe, Si)13-based conductive composites by high-pressure synthesis

Providing a suitable contact interface, where a high conductivity material with a desirable coefficient of thermal expansion (CTE) adjoins the target micro-electric devices, is very crucial to optimize the properties and service life of the relevant instruments. Regrettably, a high conductivity, low thermal expansion and relatively inexpensive material is very rare. Composites, fortunately, can offer a method to design materials with adjustable properties by mixing two or more diverse constituents. In this paper, high conductivity composites with adjustable thermal expansion were successfully prepared by a high-pressure synthesis. The composites are based on combining La(Fe,Si)13-based compounds, the materials showing a giant, isotropic negative thermal expansion (NTE) properties, within Cu matrix. The La(Fe,Si)13-based compounds were used to adjust the CTE of the composites, while the Cu phase is in charge of tuning the thermal conductivity properties. Thus, by changing the relative amount of the two components, the composites with high conductivities and adjustable CTE were achieved. Furthermore, the thermal expansion and magnetic properties of the composites were investigated by a physical property measurement system. The present results highlight the potential applications of the Cu-based high conductivity composites with room-temperature NTE properties in the thermal contacts to various semiconductor and microelectronic devices. Keywords: La(Fe, Si)13-based compounds, Metal-matrix composites, Negative thermal expansio

The dynamic effect of opposing opinions on individual opinion change

Exposure to heterogeneous information, such as counter-attitudinal information or balanced information, is considered to be the first step in breaking out of the echo chamber, but the actual usefulness of this practice is controversial: some studies have found that counter-attitudinal information enhances polarization of opinion, while others have found that counter-attitudinal information diminishes pre-existing opinion. In response to these inconsistent results, current research focuses on whether and how counter-attitudinal messages change people's pre-existing views

Data for 'Body size as a metric for the affordable world'

The original data for the results reported in the manuscript 'Body size as a metric for the affordable world'. For detailed description, please see README and the methods section.</p

Development and Internal Validation of an Interpretable Machine Learning Model to Predict Readmissions in a United States Healthcare System

(1) One in four hospital readmissions is potentially preventable. Machine learning (ML) models have been developed to predict hospital readmissions and risk-stratify patients, but thus far they have been limited in clinical applicability, timeliness, and generalizability. (2) Methods: Using deidentified clinical data from the University of California, San Francisco (UCSF) between January 2016 and November 2021, we developed and compared four supervised ML models (logistic regression, random forest, gradient boosting, and XGBoost) to predict 30-day readmissions for adults admitted to a UCSF hospital. (3) Results: Of 147,358 inpatient encounters, 20,747 (13.9%) patients were readmitted within 30 days of discharge. The final model selected was XGBoost, which had an area under the receiver operating characteristic curve of 0.783 and an area under the precision-recall curve of 0.434. The most important features by Shapley Additive Explanations were days since last admission, discharge department, and inpatient length of stay. (4) Conclusions: We developed and internally validated a supervised ML model to predict 30-day readmissions in a US-based healthcare system. This model has several advantages including state-of-the-art performance metrics, the use of clinical data, the use of features available within 24 h of discharge, and generalizability to multiple disease states

Screening of ent-copalyl diphosphate synthase and metabolic engineering to achieve de novo biosynthesis of ent-copalol in Saccharomyces cerevisiae

The diterpene ent-copalol is an important precursor to the synthesis of andrographolide and is found only in green chiretta (Andrographis paniculata). De novo biosynthesis of ent-copalol has not been reported, because the catalytic activity of ent-copalyl diphosphate synthase (CPS) is very low in microorganisms. In order to achieve the biosynthesis of ent-copalol, Saccharomyces cerevisiae was selected as the chassis strain, because its endogenous mevalonate pathway and dephosphorylases could provide natural promotion for the synthesis of ent-copalol. The strain capable of synthesizing diterpene geranylgeranyl pyrophosphate was constructed by strengthening the mevalonate pathway genes and weakening the competing pathway. Five full-length ApCPSs were screened by transcriptome sequencing of A. paniculata and ApCPS2 had the best activity and produced ent-CPP exclusively. The peak area of ent-copalol was increased after the ApCPS2 saturation mutation and its configuration was determined by NMR and ESI-MS detection. By appropriately optimizing acetyl-CoA supply and fusion-expressing key enzymes, 35.6 mg/L ent-copalol was generated. In this study, de novo biosynthesis and identification of ent-copalol were achieved and the highest titer ever reported. It provides a platform strain for the further pathway analysis of andrographolide and derivatives and provides a reference for the synthesis of other pharmaceutical intermediates