Down-regulation of NRIP1 alleviates pyroptosis in human lens epithelial cells exposed to hydrogen peroxide by inhibiting NF-κB activation

Purpose: To investigate the role of nuclear receptor-interacting protein 1 (NRIP1) in oxidative stressinduced apoptosis and pyroptosis in cataract disease.Methods: Human lens epithelial cells (HLE-B3 cells) were exposed to hydrogen peroxide (H2O2). NRIP1 expression in hydrogen peroxide (H2O2)-treated HLE-B3 cells was determined by western blotting and quantitative reverse transcription polymerase chain reaction (qRT-PCR). CCK8 and EdU staining were used to assess cell viability. Flow cytometry and western blotting were used to assess pyroptosis.Results: NRIP1 was significantly up-regulated in HLE-B3 cells post-H2O2 incubation (p < 0.01). Hydrogen peroxide incubation reduced cell viability and proliferation of HLE-B3 cells, while NRIP1 knockdown enhanced cell viability and proliferation. NRIP1 silencing attenuated the H2O2-induced increase in NLRP3, N-terminal domain of gasdermin D, caspase-1, interleukin (IL)-1β, and IL-18 in HLEB3 cells, but suppressed the pyroptosis of H2O2-treated HLE-B3 cells. Hydrogen peroxide incubation down-regulated protein expression of cytoplasmic NF-κB and up-regulated nuclear NF-κB, while the expression of cytoplasmic NF-κB was increased and nuclear NF-κB was decreased in HLE-B3 cells by HLE-B3 interference.Conclusion: NRIP1 down-regulation represses apoptosis and pyroptosis of H2O2-treated human lens epithelial cells by inhibiting NF-κB activation, thus, providing a potential strategy to treat cataract disease

Association study of monoamine oxidase A/B genes and schizophrenia in Han Chinese

<p>Abstract</p> <p>Background</p> <p>Monoamine oxidases (MAOs) catalyze the metabolism of dopaminergic neurotransmitters. Polymorphisms of isoforms MAOA and MAOB have been implicated in the etiology of mental disorders such as schizophrenia. Association studies detected these polymorphisms in several populations, however the data have not been conclusive to date. Here, we investigated the association of <it>MAOA </it>and <it>MAOB </it>polymorphisms with schizophrenia in a Han Chinese population.</p> <p>Methods</p> <p>Two functional single nucleotide polymorphisms (SNPs), rs6323 of <it>MAOA </it>and rs1799836 of <it>MAOB</it>, were selected for association analysis in 537 unrelated schizophrenia patients and 536 healthy controls. Single-locus and Haplotype associations were calculated.</p> <p>Results</p> <p>No differences were found in the allelic distribution of rs6323. The G allele of rs1799836 was identified as a risk factor in the development of schizophrenia (<it>P </it>= 0.00001). The risk haplotype rs6323T-rs1799836G was associated with schizophrenia in female patients (<it>P </it>= 0.0002), but the frequency difference was not significant among male groups.</p> <p>Conclusions</p> <p>Our results suggest that <it>MAOB </it>is a susceptibility gene for schizophrenia. In contrast, no significant associations were observed for the <it>MAOA </it>functional polymorphism with schizophrenia in Han Chinese. These data support further investigation of the role of MAO genes in schizophrenia.</p

The prevalence of autism spectrum disorders in China: A comprehensive meta-analysis

There are conflicting prevalence estimates of autism spectrum disorders (ASDs) in mainland China (China thereafter). This study is a comprehensive meta-analysis of the pooled prevalence of ASDs in the general population in China. Study investigators independently conducted a systematic literature search of the following databases: PubMed, EMBASE, PsycINFO, China National Knowledge Infrastructure, Chinese biomedical literature service system, and Wan Fang. Studies reporting prevalence of ASDs and autism in Chinese population were identified and analysed using the Comprehensive Meta-Analysis program with the random effects model. Forty-four studies were included in the meta-analysis comprising 2,337,321 subjects of whom 46.66 % were females. The mean age of subjects ranged from 1.6 to 8 years. Based on diagnostic criteria the pooled prevalence of ASDs was 39.23 per 10,000 (95% CI: 28.44-50.03 per 10,000, I2=89.2%); specifically, the prevalence of autism was 10.18 per 10,000 (95% CI: 8.46-11.89 per 10,000, I2=92.5%). Subgroup analyses revealed significant difference in the prevalence of ASDs between genders (72.77 per 10,000 in males vs. 16.45 per 10,000 in females). In conclusion, the prevalence of ASDs and autism in China was found generally lower than those reported in other countries. Further studies are needed to clarify the variation in prevalence

A Simple Temporal Information Matching Mechanism for Entity Alignment Between Temporal Knowledge Graphs

Entity alignment (EA) aims to find entities in different knowledge graphs (KGs) that refer to the same object in the real world. Recent studies incorporate temporal information to augment the representations of KGs. The existing methods for EA between temporal KGs (TKGs) utilize a time-aware attention mechanism to incorporate relational and temporal information into entity embeddings. The approaches outperform the previous methods by using temporal information. However, we believe that it is not necessary to learn the embeddings of temporal information in KGs since most TKGs have uniform temporal representations. Therefore, we propose a simple graph neural network (GNN) model combined with a temporal information matching mechanism, which achieves better performance with less time and fewer parameters. Furthermore, since alignment seeds are difficult to label in real-world applications, we also propose a method to generate unsupervised alignment seeds via the temporal information of TKG. Extensive experiments on public datasets indicate that our supervised method significantly outperforms the previous methods and the unsupervised one has competitive performance.Comment: Accepted by COLING 202

BRAU-Net++: U-Shaped Hybrid CNN-Transformer Network for Medical Image Segmentation

Accurate medical image segmentation is essential for clinical quantification, disease diagnosis, treatment planning and many other applications. Both convolution-based and transformer-based u-shaped architectures have made significant success in various medical image segmentation tasks. The former can efficiently learn local information of images while requiring much more image-specific inductive biases inherent to convolution operation. The latter can effectively capture long-range dependency at different feature scales using self-attention, whereas it typically encounters the challenges of quadratic compute and memory requirements with sequence length increasing. To address this problem, through integrating the merits of these two paradigms in a well-designed u-shaped architecture, we propose a hybrid yet effective CNN-Transformer network, named BRAU-Net++, for an accurate medical image segmentation task. Specifically, BRAU-Net++ uses bi-level routing attention as the core building block to design our u-shaped encoder-decoder structure, in which both encoder and decoder are hierarchically constructed, so as to learn global semantic information while reducing computational complexity. Furthermore, this network restructures skip connection by incorporating channel-spatial attention which adopts convolution operations, aiming to minimize local spatial information loss and amplify global dimension-interaction of multi-scale features. Extensive experiments on three public benchmark datasets demonstrate that our proposed approach surpasses other state-of-the-art methods including its baseline: BRAU-Net under almost all evaluation metrics. We achieve the average Dice-Similarity Coefficient (DSC) of 82.47, 90.10, and 92.94 on Synapse multi-organ segmentation, ISIC-2018 Challenge, and CVC-ClinicDB, as well as the mIoU of 84.01 and 88.17 on ISIC-2018 Challenge and CVC-ClinicDB, respectively.Comment: 12 pages, 6 figures, 9 tables code: https://github.com/Caipengzhou/BRAU-Netplusplu

Eucomic acid methanol monosolvate

In the crystal structure of the title compound [systematic name: 2-hy­droxy-2-(4-hy­droxy­benz­yl)butane­dioic acid methanol monosolvate], C11H12O6·CH3OH, the dihedral angles between the planes of the carboxyl groups and the benzene ring are 51.23 (9) and 87.97 (9)°. Inter­molecular O—H⋯O hydrogen-bonding inter­actions involving the hy­droxy and carb­oxy­lic acid groups and the methanol solvent mol­ecule give a three-dimensional structure

Quantum dense coding in multiparticle entangled states via local measurements

In this paper, we study quantum dense coding between two arbitrarily fixed particles in a (N+2)-particle maximally-entangled states through introducing an auxiliary qubit and carrying out local measurements. It is shown that the transmitted classical information amount through such an entangled quantum channel usually is less than two classical bits. However, the information amount may reach two classical bits of information, and the classical information capacity is independent of the number of the entangled particles in the initial entangled state under certain conditions. The results offer deeper insights to quantum dense coding via quantum channels of multi-particle entangled states.Comment: 3 pages, no figur

Multiplexed detection of eight respiratory viruses based on nanozyme colorimetric microfluidic immunoassay

Pandemics caused by respiratory viruses, such as the SARS-CoV-1/2, influenza virus, and respiratory syncytial virus, have resulted in serious consequences to humans and a large number of deaths. The detection of such respiratory viruses in the early stages of infection can help control diseases by preventing the spread of viruses. However, the diversity of respiratory virus species and subtypes, their rapid antigenic mutations, and the limited viral release during the early stages of infection pose challenges to their detection. This work reports a multiplexed microfluidic immunoassay chip for simultaneous detection of eight respiratory viruses with noticeable infection population, namely, influenza A virus, influenza B virus, respiratory syncytial virus, SARS-CoV-2, human bocavirus, human metapneumovirus, adenovirus, and human parainfluenza viruses. The nanomaterial of the nanozyme (Au@Pt nanoparticles) was optimized to improve labeling efficiency and enhance the detection sensitivity significantly. Nanozyme-binding antibodies were used to detect viral proteins with a limit of detection of 0.1 pg/mL with the naked eye and a microplate reader within 40 min. Furthermore, specific antibodies were screened against the conserved proteins of each virus in the immunoassay, and the clinical sample detection showed high specificity without cross reactivity among the eight pathogens. In addition, the microfluidic chip immunoassay showed high accuracy, as compared with the RT-PCR assay for clinical sample detection, with 97.2%/94.3% positive/negative coincidence rates. This proposed approach thus provides a convenient, rapid, and sensitive method for simultaneous detection of eight respiratory viruses, which is meaningful for the early diagnosis of viral infections. Significantly, it can be widely used to detect pathogens and biomarkers by replacing only the antigen-specific antibodies

{Bis[4-(2-pyrid­yl)pyrimidin-2-yl] sulfide}dibromidocobalt(II)

The title compound, [CoBr2(C18H12N6S)], is a mononuclear complex in which a twofold rotation axis passes through the Co and S atoms. The CoII center is six-coordinated by four N atoms from one bis­[4-(2-pyrid­yl)pyrimidin-2-yl] sulfide (L) ligand and two bromide anions, forming an octa­hedral coordination geometry, where the four donor N atoms are located in the equatorial plane and the Br atoms occupy the axial positions. The sum of the bond angles around the Co atom in the equatorial plane is 360.5°, with the four N atoms and the central Co atom almost coplanar. In the crystal structure, the mononuclear units are linked by π–π stacking inter­actions (the inter­planar distances are 3.469 and 3.533 Å, and the corresponding centroid–centroid distances are 3.791 and 3.896 Å) into a three-dimensional supra­molecular network