Effect of rs1344706 in the ZNF804A gene on the brain network.

ZNF804A rs1344706 (A/C) was the first SNP that reached genome-wide significance for schizophrenia. Recent studies have linked rs1344706 to functional connectivity among specific brain regions. However, no study thus far has examined the role of this SNP in the entire functional connectome. In this study, we used degree centrality to test the role of rs1344706 in the whole-brain voxel-wise functional connectome during the resting state. 52 schizophrenia patients and 128 healthy controls were included in the final analysis. In our whole-brain analysis, we found a significant interaction effect of genotype × diagnosis at the precuneus (PCU) (cluster size = 52 voxels, peak voxel MNI coordinates: x = 9, y = - 69, z = 63, F = 32.57, FWE corrected P < 0.001). When we subdivided the degree centrality network according to anatomical distance, the whole-brain analysis also found a significant interaction effect of genotype × diagnosis at the PCU with the same peak in the short-range degree centrality network (cluster size = 72 voxels, F = 37.29, FWE corrected P < 0.001). No significant result was found in the long-range degree centrality network. Our results elucidated the contribution of rs1344706 to functional connectivity within the brain network, and may have important implications for our understanding of this risk gene's role in functional dysconnectivity in schizophrenia

Evidence for the contribution of COMT gene Val158/108Met polymorphism (rs4680) to working memory training-related prefrontal plasticity.

BackgroundGenetic factors have been suggested to affect the efficacy of working memory training. However, few studies have attempted to identify the relevant genes.MethodsIn this study, we first performed a randomized controlled trial (RCT) to identify brain regions that were specifically affected by working memory training. Sixty undergraduate students were randomly assigned to either the adaptive training group (N = 30) or the active control group (N = 30). Both groups were trained for 20 sessions during 4 weeks and received fMRI scans before and after the training. Afterward, we combined the data from the 30 participants in the RCT study who received adaptive training with data from 71 additional participants who also received the same adaptive training but were not part of the RCT study (total N = 101) to test the contribution of the COMT Val158/108Met polymorphism to the interindividual difference in the training effect within the identified brain regions.ResultsIn the RCT study, we found that the adaptive training significantly decreased brain activation in the left prefrontal cortex (TFCE-FWE corrected p = .030). In the genetic study, we found that compared with the Val allele homozygotes, the Met allele carriers' brain activation decreased more after the training at the left prefrontal cortex (TFCE-FWE corrected p = .025).ConclusionsThis study provided evidence for the neural effect of a visual-spatial span training and suggested that genetic factors such as the COMT Val158/108Met polymorphism may have to be considered in future studies of such training

The impact of novel coronavirus SARS-CoV-2 among healthcare workers in hospitals: An aerial overview

The ongoing outbreak of COVID-19, caused by the novel coronavirus SARS-CoV-2, places healthcare workers at an increased risk of infection as they are in close contact with patients. In this article, we report an overview of cases of infected healthcare workers in China and Italy during the early periods of the COVID-19 epidemic. China’s coronavirus response highlights the importance of implementing effective public health strategies. The authorities worldwide therefore, need to be extremely cautious when they implement stringent protective measures that safeguard healthcare workers in hospitals and counteract the threats created by the pandemic. Key Words: COVID-19 disease, Medical staff, Protective measures, Severe acute respiratory syndrome, coronavirus 2, Person-to-person transmissio

Geographical and epidemiological characteristics of sporadic coronavirus disease 2019 outbreaks from June to December 2020 in China: an overview of environment-to-human transmission events

China quickly brought the severe acute respiratory syndrome coronavirus 2 under control during the early stage of 2020; thus, this generated sufficient confidence among the public, which enabled them to respond to several sporadic coronavirus disease 2019 outbreaks. This article presents geographical and epidemiological characteristics of several sporadic coronavirus disease 2019 outbreaks from June to December 2020 in China. The data show that the coronavirus disease may be transmitted by imported cold-chain food and international exchange, and this viewpoint deserves our great attention

Revisit Input Perturbation Problems for LLMs: A Unified Robustness Evaluation Framework for Noisy Slot Filling Task

With the increasing capabilities of large language models (LLMs), these high-performance models have achieved state-of-the-art results on a wide range of natural language processing (NLP) tasks. However, the models' performance on commonly-used benchmark datasets often fails to accurately reflect their reliability and robustness when applied to real-world noisy data. To address these challenges, we propose a unified robustness evaluation framework based on the slot-filling task to systematically evaluate the dialogue understanding capability of LLMs in diverse input perturbation scenarios. Specifically, we construct a input perturbation evaluation dataset, Noise-LLM, which contains five types of single perturbation and four types of mixed perturbation data. Furthermore, we utilize a multi-level data augmentation method (character, word, and sentence levels) to construct a candidate data pool, and carefully design two ways of automatic task demonstration construction strategies (instance-level and entity-level) with various prompt templates. Our aim is to assess how well various robustness methods of LLMs perform in real-world noisy scenarios. The experiments have demonstrated that the current open-source LLMs generally achieve limited perturbation robustness performance. Based on these experimental observations, we make some forward-looking suggestions to fuel the research in this direction.Comment: Accepted at NLPCC 2023 (Oral Presentation

Polymorphism in schizophrenia risk gene MIR137 is associated with the posterior cingulate Cortex's activation and functional and structural connectivity in healthy controls

MIR137 gene has been repeatedly reported as a schizophrenia risk gene in genome-wide association studies (GWAS). A polymorphism (rs1625579) at the MIR137 gene has been associated with both neural activation and behavioral performance during a working memory task. This study examined MIR137's associations with task-related (N-back working memory) fMRI, resting state fMRI, and diffusion tensor images (DTI) data in 177 healthy adults. We found less deactivation of the PCC in risk allele homozygotes (TT) as compared to the GT heterozygotes (cluster size = 630 voxels, cluster level PFWE < 0.001) during the N-back task, which replicated previous findings. Using the identified cluster within the PCC as the seed, we further found decreased functional connectivity between the PCC and the anterior cingulate cortex and its adjacent medial prefrontal cortex (ACC/MPFC) in risk allele homozygotes during both resting state (cluster size = 427 voxels, cluster level PFWE = 0.001) and the N-back task (cluster size = 73 voxels, cluster level PFWE = 0.05). Finally, an analysis of our DTI data showed decreased white matter integrity of the posterior cingulum in risk allele homozygotes (cluster size = 214 voxels, cluster level PFWE = 0.03). Taken together, rs1625579 seems to play an important role in both functional and structural connectivity between the PCC and the ACC/MPFC, which may serve as the brain mechanisms for the link between rs1625579 and schizophrenia

Prediction of Relative Permeability of Unsaturated Porous Media Based on Fractal Theory and Monte Carlo Simulation

Mass transport through porous media is an important subject to engineers and scientists in various:areas including oil engineering, fuel cells, soil science, textile engineering, etc. The relative permeability and capillary pressure are the key parameters that affect liquid transport through porous. Media. In this :paper, the Monte Carlo technique applied to product the relative permeability of unsaturated porous media, Considering the effect of capillary pressure and tortuosity of capillaries. The relative permeability expressed as a function of porosity, area fractal dimension of pores, fractal dimension of tortuous capillaries, degree of saturation, and capillary pressure. It is found that the Phase fractal dimensions (D-f,D-w and D-f,D-g) strongly depend on Porosity. Besides, it is shown that the capillary pressure increases With the decrease of saturation, and at low saturation the capillary pressure increases sharply with the decrease of saturation. There is no empirical constant in the proposed model, and each parameter in the model has a clear physical meaning. The predicted relative permeability obtained by the present Monte Carlo simulation is shown to have a good agreement with the experimental results reported in the literature. The proposed model improved the understanding of the physical mechanisms of liquid transport through porous media

Experimental and Theoretical Analysis of Sound Absorption Properties of Finely Perforated Wooden Panels

Perforated wooden panels are typically utilized as a resonant sound absorbing material in indoor noise control. In this paper, the absorption properties of wooden panels perforated with tiny holes of 1–3 mm diameter were studied both experimentally and theoretically. The Maa-MPP (micro perforated panels) model and the Maa-Flex model were applied to predict the absorption regularities of finely perforated wooden panels. A relative impedance comparison and full-factorial experiments were carried out to verify the feasibility of the theoretical models. The results showed that the Maa-Flex model obtained good agreement with measured results. Control experiments and measurements of dynamic mechanical properties were carried out to investigate the influence of the wood characteristics. In this study, absorption properties were enhanced by sound-induced vibration. The relationship between the dynamic mechanical properties and the panel mass-spring vibration absorption was revealed. While the absorption effects of wood porous structure were not found, they were demonstrated theoretically by using acoustic wave propagation in a simplified circular pipe with a suddenly changed cross-section model. This work provides experimental and theoretical guidance for perforation parameter design

Improving the Sound Absorption Capacity of Wood by Microwave Treatment

Microwave treatment (MW) was used to improve the sound absorption capacity of Pinus sylvestris var. mongolica wood. The effects of the processing parameters such as MW intensity, processing time, and board thickness on the sound absorption of treated wood were investigated. Microstructure changes of the wood after microwave treatment were observed using scanning electron microscopy (SEM) and mercury intrusion porosimetry (MIP). It was found that the microwave treatment significantly enhanced the sound absorption capacity of the wood in the middle frequencies. The optimum microwave treatment parameters for Pinus sylvestris var. mongolica wood to achieve an improved permeability are: MW intensity of 18 Kw, board thickness of 30 mm, and processing time of 80 s. The maximum sound absorption coefficient of treated wood was 0.51. Micro-voids were formed in treated wood due to the destruction of the pit membranes, the wood ray cells, as well as the damage in the intercellular layer of the longitudinal tracheids. The number of micro-voids ranging from 7427.6 nm to 400 um increased, resulting in the increase in the air permeability and in sound absorption by the treated wood

Evidence for the contribution of HCN1 gene polymorphism (rs1501357) to working memory at both behavioral and neural levels in schizophrenia patients and healthy controls.

Gene HCN1 polymorphism (rs1501357) has been proposed to be one of the candidate risk genes for schizophrenia in the second report of the Psychiatric Genomics Consortium-Schizophrenia Workgroup. Although animal studies repeatedly showed a role of this gene in working memory, its contribution to working memory in human samples, especially in schizophrenia patients, is still unknown. To explore the association between rs1501357 and working memory at both behavioral (Study 1) and neural (Study 2) levels, the current study involved two independent samples. Study 1 included 876 schizophrenia patients and 842 healthy controls, all of whom were assessed on a 2-back task, a dot pattern expectancy task (DPX), and a digit span task. Study 2 included 56 schizophrenia patients and 155 healthy controls, all of whom performed a 2-back task during functional magnetic resonance imaging (fMRI) scanning. In both studies, we consistently found significant genotype-by-diagnosis interaction effects. For Study 1, the interaction effects were significant for the three tasks. Patients carrying the risk allele performed worse than noncarriers, while healthy controls showed the opposite pattern. For Study 2, the interaction effects were observed at the parietal cortex and the medial frontal cortex. Patients carrying the risk allele showed increased activation at right parietal cortex and increased deactivation at the medial frontal cortex, while healthy controls showed the opposite pattern. These results suggest that the contributions of rs1501357 to working memory capability vary in different populations (i.e., schizophrenia patients vs. healthy controls), which expands our understanding of the functional impact of the HCN1 gene. Future studies should examine its associations with other cognitive functions