Origin of reconnecting current sheets in shocked turbulent plasma.

Magnetic reconnection, the rearrangement of magnetic field topologies, is a fundamental plasma process throughout the universe, which converts magnetic energy to plasma kinetic energy and results in particle energization. A current sheet is a prerequisite for the occurrence of magnetic reconnection. It has been well documented that reconnecting current sheets are prevalent in turbulent plasmas. However, how these current sheets are formed remains unclear. Among natural plasmas, the region downstream of the Earth's bow shock, the magnetosheath, is one of the most turbulent. Here, we show that the reconnecting current sheets in the turbulent magnetosheath originate from the waves in the region upstream of the shock. Once excited, the upstream waves are transmitted across the shock, compressed, and then transformed into current sheets in the downstream region. Magnetic reconnection subsequently occurs in these downstream current sheets. This process can be generalized to various shocked plasmas in astrophysical and laboratorial environments where turbulent magnetic reconnection should be common.

3MT-Net: A Multi-modal Multi-task Model for Breast Cancer and Pathological Subtype Classification Based on a Multicenter Study.

Breast cancer significantly impacts women's health, with ultrasound being crucial for lesion assessment. To enhance diagnostic accuracy, computer-aided detection (CAD) systems have attracted considerable interest. This study introduces a prospective deep learning architecture called "Multi-modal Multi-task Network" (3MT-Net). 3MT-Net utilizes a combination of clinical data, B-mode, and color Doppler ultrasound. We have designed the AM-CapsNet network, specifically tailored to extract crucial tumor features from ultrasound. To combine clinical data in 3MT-Net, we have employed a cascaded cross-attention to fuse information from three distinct sources. To ensure the preservation of pertinent information during the fusion of high-dimensional and low-dimensional data, we adopt the idea of ensemble learning and design an optimization algorithm to assign weights to different modalities. Eventually, 3MT-Net performs binary classification of benign and malignant lesions as well as pathological subtype classification. In addition, we retrospectively collected data from nine medical centers. To ensure the broad applicability of the 3MT-Net, we created two separate testsets and conducted extensive experiments. Furthermore, a comparative analysis was conducted between 3MT-Net and the industrial-grade CAD product S-detect. The AUC of 3MT-Net surpasses S-Detect by 1.4% to 3.8%.

Stimuli-Responsive Ion Transport Regulation in Nanochannels by Adhesion-Induced Functionalization of Macroscopic Outer Surface.

Responsive regulation of ion transport through nanochannels is crucial in the design of smart nanofluidic devices for sequencing, sensing, and water-energy nexus. Functionalization of the inner wall of the nanochannel enhances interaction with ions and fluid but restricts versatile chemical approaches and accurate characterizations of fluidic interfaces. Herein, we reveal a responsive regulating mechanism of ion transport through nanochannels by polydopamine (PDA)-induced functionalization on the macroscopic outer surface of nanochannels. Responsive molecules were codeposited with PDA on the outer surface of nanochannels and formed a valve of nanometer thickness to manually manipulate ion transport by changing its gap spacing, surface charge, and wettability under external stimulus. The response ratio can be up to 100-fold by maximizing the proportion of responsive molecules on the outer surface. Laminating the codepositions of different responsive molecules with PDA on the channel's outer surface produces multiple responses. A nearly universal adhesion of PDA with responsive molecules on the open outer surface induces nanochannels responsive to different external stimuli with variable response ratios and arbitrary combinations. The results challenge the primary role of functionalization on the nanoconfined interface of nanofluidics and open opportunities for developing new-style nanofluidic devices through the functionalization of macroscopic interface.

Xiaoqing: A Q&A model for glaucoma based on LLMs.

Glaucoma is one of the leading cause of blindness worldwide. Individuals affected by glaucoma, including patients and their family members, frequently encounter a deficit in dependable support beyond the confines of clinical environments. Seeking advice via the internet can be a difficult task due to the vast amount of disorganized and unstructured material available on these sites, nevertheless. This research explores how Large Language Models (LLMs) can be leveraged to better serve medical research and benefit glaucoma patients. We introduce Xiaoqing, a Natural Language Processing (NLP) model specifically tailored for the glaucoma field, detailing its development and deployment. To evaluate its effectiveness, we conducted two forms of experiments: comparative and experiential. In the comparative analysis, we presented 22 glaucoma-related questions in simplified Chinese to three medical NLP models (Xiaoqing LLMs, HuaTuo, Ivy GPT) and two general models (ChatGPT-3.5 and ChatGPT-4), covering a range of topics from basic glaucoma knowledge to treatment, surgery, research, management standards, and patient lifestyle. Responses were assessed for informativeness and readability. The experiential experiment involved glaucoma patients and non-patients interacting with Xiaoqing, collecting and analyzing their questions and feedback on the same criteria. The findings demonstrated that Xiaoqing notably outperformed the other models in terms of informativeness and readability, suggesting that Xiaoqing is a significant advancement in the management and treatment of glaucoma in China. We also provide a Web-based version of Xiaoqing, allowing readers to directly experience its functionality. The Web-based Xiaoqing is available at https://qa.glaucoma-assistant.com//qa.

Identification of clinical characteristics biomarkers for rheumatoid arthritis through targeted DNA methylation sequencing.

OBJECTIVES: Rheumatoid arthritis (RA) is a complex disease with a challenging diagnosis, especially in seronegative patients. The aim of this study is to investigate whether the methylation sites associated with the overall immune response in RA can assist in clinical diagnosis, using targeted methylation sequencing technology on peripheral venous blood samples. METHODS: The study enrolled 241 RA patients, 30 osteoarthritis patients (OA), and 30 healthy volunteers control (HC). Fifty significant cytosine guanine (CG) sites between undifferentiated arthritis and RA were selected and analyzed using targeted DNA methylation sequencing. Logistic regression models were used to establish diagnostic models for different clinical features of RA, and six machine learning methods (logit model, random forest, support vector machine, adaboost, naive bayes, and learning vector quantization) were used to construct clinical diagnostic models for different subtypes of RA. Least absolute shrinkage and selection operator regression and detrended correspondence analysis were utilized to screen for important CGs. Spearman correlation was used to calculate the correlation coefficient. RESULTS: The study identified 16 important CG sites, including tumor necrosis factort receptor associated factor 5 (TRAF5) (chr1:211500151), mothers against decapentaplegic homolog 3 (SMAD3) (chr15:67357339), tumor endothelial marker 1 (CD248) (chr11:66083766), lysosomal trafficking regulator (LYST) (chr1:235998714), PR domain zinc finger protein 16 (PRDM16) (chr1:3307069), A-kinase anchoring protein 10 (AKAP10) (chr17:19850460), G protein subunit gamma 7 (GNG7) (chr19:2546620), yes1 associated transcriptional regulator (YAP1) (chr11:101980632), PRDM16 (chr1:3163969), histone deacetylase complex subunit sin3a (SIN3A) (chr15:75747445), prenylated rab acceptor protein 2 (ARL6IP5) (chr3:69134502), mitogen-activated protein kinase kinase kinase 4 (MAP3K4) (chr6:161412392), wnt family member 7A (WNT7A) (chr3:13895991), inhibin subunit beta B (INHBB) (chr2:121107018), deoxyribonucleic acid replication helicase/nuclease 2 (DNA2) (chr10:70231628) and chromosome 14 open reading frame 180 (C14orf180) (chr14:105055171). Seven CG sites showed abnormal changes between the three groups (P < 0.05), and 16 CG sites were significantly correlated with common clinical indicators (P < 0.05). Diagnostic models constructed using different CG sites had an area under the receiver operating characteristic curve (AUC) range of 0.64-0.78 for high-level clinical indicators of high clinical value, with specificity ranging from 0.42 to 0.77 and sensitivity ranging from 0.57 to 0.88. The AUC range for low-level clinical indicators of high clinical value was 0.63-0.72, with specificity ranging from 0.48 to 0.74 and sensitivity ranging from 0.72 to 0.88. Diagnostic models constructed using different CG sites showed good overall diagnostic accuracy for the four subtypes of RA, with an accuracy range of 0.61-0.96, a balanced accuracy range of 0.46-0.94, and an AUC range of 0.46-0.94. CONCLUSIONS: This study identified potential clinical diagnostic biomarkers for RA and provided novel insights into the diagnosis and subtyping of RA. The use of targeted deoxyribonucleic acid (DNA) methylation sequencing and machine learning methods for establishing diagnostic models for different clinical features and subtypes of RA is innovative and can improve the accuracy and efficiency of RA diagnosis.

Plasma exosomal miR-30a-5p inhibits osteogenic differentiation of bone marrow mesenchymal stem cells from a chronic unpredictable mild stress-induced depression rat model.

With rising society stress, depression-induced osteoporosis is increasing. However, the mechanism involved is unclear. In this study, we explored the effect of plasma exosomal miRNAs on bone marrow mesenchymal stem cell (BMSC) osteogenic differentiation in a chronic unpredictable mild stress (CUMS)-induced depression rat model. After 12 weeks of CUMS-induced depression, the pathological changes in the bone tissue and markers of osteogenic differentiation were tested by micro-computed tomography, hematoxylin-eosin staining, and quantitative real-time reverse transcription PCR (qRT-PCR). Plasma exosomes from rats were isolated and co-incubated with BMSCs for 14 d to detect the effect on osteogenic markers. Next-generation sequencing identified the miRNAs in the plasma exosomes, and the differential miRNAs were analyzed and verified by qRT-PCR. BMSCs were infected with lentivirus to upregulate miRNA-30a-5p and incubated in a medium that induced osteogenic differentiation for 14 d. The effect of miR-30a-5p on osteogenic differentiation was determined by qPCR and alizarin red staining. CUMS-induced depression rat model was established successfully, and exhibited reduced bone mass and damaged bone microstructure compared to that of the controls. The observed pathological changes suggested the occurrence of osteoporosis in the CUMS group, and the mRNA expression of osteogenic markers was also significantly reduced. Incubation of BMSCs with plasma exosomes from the CUMS group for 14 d resulted in a significant decrease in the expression of osteogenic markers. Twenty-five differentially expressed miRNAs in plasma exosomes were identified and upregulation of miR-30a-5p was observed to significantly inhibit the expression of osteogenic markers in BMSCs. Our findings contributed to a comprehensive understanding of the mechanism of osteoporosis caused by depression, and demonstrated the potential of miR-30a-5p as a novel biomarker or therapeutic target for the treatment of osteoporosis.

QTL-seq analysis identified the genomic regions of plant height and days to heading in high-latitude rice.

Introduction: Rice (Oryza sativa L.) is one of the most extensive crops in the world. China's Heilongjiang Province is the northernmost rice-growing region in the world. However, rice cultivars suitable for growth in low-latitude regions may not mature normally due to their distinct climate and short frost-free period. It is necessary to precisely determine the frost-free period for each region to make the best use of the rice growth stage so as to ensure the maturity and yield of different rice cultivars in Heilongjiang Province. The time span of the heading stage is a key parameter for evaluating the adaptability of a rice cultivar to a specific rice-growing region. Given the above facts, it is of high importance to study the associated genes and sites controlling days to heading (DH) and plant height (PH) of rice in Heilongjiang Province. Bulked segregant analysis (BSA) combined with high-throughput sequencing can effectively exclude interferences from background genomic differences, making it suitable for analyzing the associated sites of complex agronomic traits in early generations. Methods: In this study, an F3 segregating population was obtained by crossing two main cultivars that are grown under different temperatures and day-light conditions in Heilongjiang. Two pools of extreme phenotypes were built for the DH and PH of the population. For SNP and InDel variants obtained from whole-genome resequencing in the pools, an association analysis was performed using the Euclidean distance (ED) algorithm and the SNP/InDel index algorithm. Results: The intersection of SNP and InDel regions associated with the phenotypes was considered to obtain the final associated sites. After excluding interferences from the cloned genes on chromosomes 2 and 7, a total length of 6.34 Mb on chromosomes 1, 3, and 10 and 3.16 Mb on chromosomes 1 and 10 were left associated with PH and DH, respectively. Then, we performed a gene annotation analysis for candidate genes in the remaining regions using multiple genome annotation databases. Our research provides basic data for subsequent gene mapping and cloning. Discussion: By mining more genetic loci associated with the days to heading and plant height of rice, we may provide abundant genetic resources for refined molecular breeding in Heilongjiang Province.

Comprehensive profiling of cell subsets of gastric cancer and liver metastasis based on single cell RNA-sequencing analysis.

Background: Liver metastasis (Li) is one of the most common distant metastatic sites for gastric cancer. A deeper understanding of its mechanism of action from a bioinformatics perspective may provide new insights. Therefore, the aim of this study was to use single cell RNA sequencing (scRNA-seq) to evaluate cell subtypes and understand the molecular mechanism of gastric cancer Li. Methods: The scRNA-seq data GSE163558 of gastric cancer and Li were downloaded from Gene Expression Omnibus (GEO). Single cell data were analyzed by various R packages such as Seurat, CellChat, gene set variation analysis (GSVA), monocle, gene set enrichment analysis (GSEA), and survival analysis and the results were plotted by ggplot2, R4.1.1. Protein expression was confirmed by immunohistochemistry in an additional patient cohort. Results: The genes APOD, CXCL5, and JUN are involved in epithelial cell metastasis. The infiltration of cytotoxic CD8 T cells was more frequent in gastric primary tumors (PTs) than in Lis. IL7R high natural killer (NK) cells that had high TXNIP and RIPOR2 expression were located at the site of Li and corresponded to a favorable prognosis. NK cells with high TNFAIP3 expression were located at the PT site and corresponded to a poor prognosis. Furthermore, the gene expression of myeloid cells was different depending on their localization in the PT site or Li. MHC-I signaling pathway was found to be activated in the PT compared to MHC-II at the site of Li, as revealed by cell-cell interaction, and HLA-E-CD94/NKG2A of NK cells was only activated in the PT and not in the Li. Conclusions: The present study revealed the difference between Li and gastric PT by scRNA-seq, demonstrating the impact of partial gene expression on patient prognosis. Our study provides new insights into gastric cancer and Li.

Positive regulation of the PhcB neighbouring regulator PrhX on expression of the type III secretion system and pathogenesis in Ralstonia solanacearum.

Ralstonia solanacearum PhcB and PhcA control a quorum-sensing (QS) system that globally regulates expression of about one third of all genes, including pathogenesis genes. The PhcB-PhcA QS system positively regulates the production of exopolysaccharide (EPS) and negatively regulates hrp gene expression, which is crucial for the type III secretion system (T3SS). Both EPS and the T3SS are essential for pathogenicity. The gene rsc2734 is located upstream of a phcBSR operon and annotated as a response regulator of a two-component system. Here, we demonstrated that RSc2734, hereafter named PrhX, positively regulated hrp gene expression via a PrhA-PrhIR-PrhJ-HrpG signalling cascade. Moreover, PrhX was crucial for R. solanacearum to invade host roots and grow in planta naturally. prhX expression was independent of the PhcB-PhcA QS system. PrhX did not affect the expression of phcB and phcA and the QS-dependent phenotypes, such as EPS production and biofilm formation. Our results provide novel insights into the complex regulatory network of the T3SS and pathogenesis in R. solanacearum.

Identification of immunological characterization and Anoikis-related molecular clusters in rheumatoid arthritis.

Objective: To investigate the potential association between Anoikis-related genes, which are responsible for preventing abnormal cellular proliferation, and rheumatoid arthritis (RA). Methods: Datasets GSE89408, GSE198520, and GSE97165 were obtained from the GEO with 282 RA patients and 28 healthy controls. We performed differential analysis of all genes and HLA genes. We performed a protein-protein interaction network analysis and identified hub genes based on STRING and cytoscape. Consistent clustering was performed with subgrouping of the disease. SsGSEA were used to calculate immune cell infiltration. Spearman's correlation analysis was employed to identify correlations. Enrichment scores of the GO and KEGG were calculated with the ssGSEA algorithm. The WGCNA and the DGIdb database were used to mine hub genes' interactions with drugs. Results: There were 26 differentially expressed Anoikis-related genes (FDR = 0.05, log2FC = 1) and HLA genes exhibited differential expression (P < 0.05) between the disease and control groups. Protein-protein interaction was observed among differentially expressed genes, and the correlation between PIM2 and RAC2 was found to be the highest; There were significant differences in the degree of immune cell infiltration between most of the immune cell types in the disease group and normal controls (P < 0.05). Anoikis-related genes were highly correlated with HLA genes. Based on the expression of Anoikis-related genes, RA patients were divided into two disease subtypes (cluster1 and cluster2). There were 59 differentially expressed Anoikis-related genes found, which exhibited significant differences in functional enrichment, immune cell infiltration degree, and HLA gene expression (P < 0.05). Cluster2 had significantly higher levels in all aspects than cluster1 did. The co-expression network analysis showed that cluster1 had 51 hub differentially expressed genes and cluster2 had 72 hub differentially expressed genes. Among them, three hub genes of cluster1 were interconnected with 187 drugs, and five hub genes of cluster2 were interconnected with 57 drugs. Conclusion: Our study identified a link between Anoikis-related genes and RA, and two distinct subtypes of RA were determined based on Anoikis-related gene expression. Notably, cluster2 may represent a more severe state of RA.

Site-specific protein conjugates incorporating Para-Azido-L-Phenylalanine for cellular and in vivo imaging.

This work features the use of amber suppression-mediated unnatural amino acid (UAA) incorporation into proteins for various imaging purposes. The site-specific incorporation of the UAA, p-azido-L-phenylalanine (pAzF), provides an azide handle that can be used to complete the strain promoted azide-alkyne click cycloaddition (SPAAC) reaction to introduce an imaging modality such as a fluorophore or a positron emission tomography (PET) tracer on the protein of interest (POI). Such methodology can be pursued directly in mammalian cell lines or on proteins expressed in vitro, thereby conferring a homogeneous pool of protein conjugates. A general procedure for UAA incorporation to use with a site-specific protein labeling method is provided allowing for in vitro and in vivo imaging applications based on the representative proteins PTEN and PD-L1. This approach would help elucidate the cellular or in vivo biological activities of the POI.

Specific detection of Phytophthora parasitica by recombinase polymerase amplification (RPA) assays based on a unique multi-copy genomic sequence.

Phytophthora parasitica is a highly destructive oomycete plant pathogen that is capable of infecting a wide range of hosts including many agricultural cash crops, fruit trees, and ornamental garden plants. One of the most important diseases caused by P. parasitica worldwide is black shank of tobacco. Rapid, sensitive, and specific pathogen detection is crucial for early rapid diagnosis which can facilitate effective disease management. In this study, we used a genomics approach to identify repeated sequences in the genome of P. parasitica by genome sequence alignment, and identified a 203 bp P. parasitica-specific sequence, PpM34, that is present in 31-60 copies in the genome. The P. parasitica genome-specificity of PpM34 was supported by PCR amplification of 24 genetically diverse strains of P. parasitica, 32 strains representing twelve other Phytophthora species, one Pythium specie, six fungal species and three bacterial species, all of which are plant pathogens. Our PCR and real-time PCR assays showed that the PpM34 sequence was highly sensitive in specifically detecting P. parasitica. Finally, we developed a PpM34-based high-efficiency Recombinase Polymerase Amplification (RPA) assay, which allowed us to specifically detect as little as 1 pg of P. parasitica total DNA from both pure cultures and infected Nicotiana benthamiana at 39°C using a fluorometric thermal cycler. The sensitivity, specificity, convenience and rapidity of this assay represents a major improvement for early diagnosis of P. parasitica infection.

Focus-RCNet: a lightweight recyclable waste classification algorithm based on focus and knowledge distillation.

Waste pollution is a significant environmental problem worldwide. With the continuous improvement in the living standards of the population and increasing richness of the consumption structure, the amount of domestic waste generated has increased dramatically, and there is an urgent need for further treatment. The rapid development of artificial intelligence has provided an effective solution for automated waste classification. However, the high computational power and complexity of algorithms make convolutional neural networks unsuitable for real-time embedded applications. In this paper, we propose a lightweight network architecture called Focus-RCNet, designed with reference to the sandglass structure of MobileNetV2, which uses deeply separable convolution to extract features from images. The Focus module is introduced to the field of recyclable waste image classification to reduce the dimensionality of features while retaining relevant information. To make the model focus more on waste image features while keeping the number of parameters small, we introduce the SimAM attention mechanism. In addition, knowledge distillation was used to further compress the number of parameters in the model. By training and testing on the TrashNet dataset, the Focus-RCNet model not only achieved an accuracy of 92[Formula: see text] but also showed high deployment mobility.

Circulating DNA methylation level of CXCR5 correlates with inflammation in patients with rheumatoid arthritis.

OBJECTIVES: To assess the differences in circulating DNA methylation levels of CXCR5 between rheumatoid arthritis (RA) and osteoarthritis (OA) and healthy controls (HC), and the correlation of methylation changes with clinical characteristics of RA patients. METHODS: Peripheral blood samples were collected from 239 RA patients, 30 patients with OA, and 29 HC. Target region methylation sequencing to the promoter region of CXCR5 was achieved using MethylTarget. The methylation level of cg04537602 and methylation haplotype were compared among the three groups, and the correlation between methylation levels and clinical characteristics of RA patients was performed by Spearman's rank correlation analysis. RESULTS: The methylation level of cg04537602 was significantly higher in the peripheral blood of RA patients compared with OA patients (p = 1.3 × 10-3 ) and in the HC group (p = 5.5 × 10- 4 ). The sensitivity was enhanced when CXCR5 methylation level combined with rheumatoid factor and anti-cyclic citrullinated peptide with area under curve (AUC) of 0.982 (95% confidence interval 0.970-0.995). The methylation level of cg04537602 in RA was positively correlated with C-reactive protein (CRP) (r = .16, p = .01), and in RA patients aged 60 years and above, cg04537602 methylation levels were positively correlated with CRP (r = .31, p = 4.7 × 10- 4 ), tender joint count (r = .21, p = .02), visual analog scales score (r = .21, p = .02), Disease Activity Score in 28 joints (DAS28) using the CRP level DAS28-CRP (r = .27, p = 2.1 × 10- 3 ), and DAS28-ESR (r = .22, p = .01). We also observed significant differences of DNA methylation haplotypes in RA patients compared with OA patients and HC, which was consistent with single-loci-based CpG methylation measurement. CONCLUSION: The methylation level of CXCR5 was significantly higher in RA patients than in OA and HC, and correlated with the level of inflammation in RA patients, our study establishes a link between CXCR5 DNA methylation and clinical features that may help in the diagnosis and disease management of RA patients.

Meeting Proceedings from ICBS 2022 - Uncovering Solutions for Diseases.

ICBS 2022 was a refreshing multi-day event where it was justified that the advancement of chemical biology did not halt due to the pandemic, but in contrast, amazing findings were discovered within the restrictions of the SARS-CoV-2 pandemic. All aspects of this annual gathering reinforced that interconnecting the branches of chemical biology through collaboration, the sharing of ideas and knowledge, and networking are enabling the discovery and diversification of applications that will arm scientists of this world in "uncovering solutions for diseases."

ALKBH5-YTHDF2 m6A modification axis inhibits rheumatoid arthritis progression by suppressing NLRP3.

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease. Recently, NLRP3 has been demonstrated to be closely related to RA. The objective of our research was to analyze the specific mechanism of NLRP3 in RA. The m6A levels of NLRP3 was detected with methylated RNA immunoprecipitation (MeRIP) kit. The mRNA and protein levels of related genes were tested with RT-qPCR and Western blot. The inflammatory factors levels were detected with ELISA kits. The cell proliferative ability was measured with CCK-8 and EdU staining assays. NLRP3 levels was prominently in synovial tissues and fibroblast-like synoviocytes (FLS) from RA patients. NLRP3 silencing suppressed FLS proliferation and inflammatory factor levels. Additionally, ALKBH5 was found to bind with NLRP3, and ALKBH5 silencing suppressed FLS proliferation and inflammatory factor levels while NLRP3 overexpressing neutralized the role of ALKBH5 in FLS. Furthermore, m6A modified induced by ALKBH5 suppressed NLRP3 mRNA level through YTHDC2 in RA, and NLRP3 is a hinge factor in RA progression.

LightR-YOLOv5: A compact rotating detector for SARS-CoV-2 antigen-detection rapid diagnostic test results.

Nucleic acid testing is currently the golden reference for coronaviruses (SARS-CoV-2) detection, while the SARS-CoV-2 antigen-detection rapid diagnostic tests (RDT) is an important adjunct. RDT can be widely used in the community or regional screening management as self-test tools and may need to be verified by healthcare authorities. However, manual verification of RDT results is a time-consuming task, and existing object detection algorithms usually suffer from high model complexity and computational effort, making them difficult to deploy. We propose LightR-YOLOv5, a compact rotating SARS-CoV-2 antigen-detection RDT results detector. Firstly, we employ an extremely light-weight L-ShuffleNetV2 network as a feature extraction network with a slight reduction in recognition accuracy. Secondly, we combine semantic and texture features in different layers by judiciously combining and employing GSConv, depth-wise convolution, and other modules, and further employ the NAM attention to locate the RDT result detection region. Furthermore, we propose a new data augmentation approach, Single-Copy-Paste, for increasing data samples for the specific task of RDT result detection while achieving a small improvement in model accuracy. Compared with some mainstream rotating object detection networks, the model size of our LightR-YOLOv5 is only 2.03MB, and it is 12.6%, 6.4%, and 7.3% higher in mAP@.5:.95 metrics compared to RetianNet, FCOS, and R3Det, respectively.

Fluorine-thiol displacement probes for acetaminophen's hepatotoxicity.

Chemicals possessing reactive electrophiles can denature innate proteins leading to undesired toxicity, and the overdose-induced liver injury by drugs containing electrophiles has been one of the major causes of non-approval and withdraw by the US Food and Drug Administration (FDA). Elucidating the associated proteins could guide the future development of therapeutics to circumvent these drugs' toxicities, but was largely limited by the current probing tools due to the steric hindrance of chemical tags including the common "click chemistry" labels. Taking the widely used non-steroidal anti-inflammatory drug acetaminophen (APAP) as an example, we hereby designed and synthesized an APAP analogue using fluorine as a steric-free label. Cell toxicity studies indicated our analogue has similar activity to the parent drug. This analogue was applied to the mouse hepatocellular proteome together with the corresponding desthiobiotin-SH probe for subsequent fluorine-thiol displacement reactions (FTDRs). This set of probes has enabled the labeling and pull-down of hepatocellular target proteins of the APAP metabolite as validated by Western blotting. Our preliminary validation results supported the interaction of APAP with the thioredoxin protein, which is an important redox protein for normal liver function. These results demonstrated that our probes confer minimal steric perturbation and mimic the compounds of interest, allowing for global profiling of interacting proteins. The fluorine-thiol displacement probing system could emerge as a powerful tool to enable the investigation of drug-protein interactions in complex biological environments.

Upgrading the genome of an elite japonica rice variety Kongyu 131 for lodging resistance improvement.

Developing a new rice variety requires tremendous efforts and years of input. To improve the defect traits of the excellent varieties becomes more cost and time efficient than breeding a completely new variety. Kongyu 131 is a high-performing japonica variety with early maturity, high yield, wide adaptability and cold resistance, but the poor-lodging resistance hinders the industrial production of Kongyu 131 in the Northeastern China. In this study, we attempted to improve the lodging resistance of Kongyu 131 from perspectives of both gene and trait. On the one hand, by QTL analysis and fine mapping we discovered the candidate gene loci. The following CRISPR/Cas9 and transgenic complementation study confirmed that Sd1 dominated the lodging resistance and favourable allele was mined for precise introduction and improvement. On the other hand, the Sd1 allelic variant was identified in Kongyu 131 by sequence alignment, then introduced another excellent allelic variation by backcrossing. Then, the two new resulting Kongyu 131 went through the field evaluation under different environments, planting densities and nitrogen fertilizer conditions. The results showed that the plant height of upgraded Kongyu 131 was 17%-26% lower than Kongyu 131 without penalty in yield. This study demonstrated a precise and targeted way to update the rice genome and upgrade the elite rice varieties by improving only a few gene defects from the perspective of breeding.

Circulating methylation level of HTR2A is associated with inflammation and disease activity in rheumatoid arthritis.

Objectives: HTR2A is previously identified as a susceptibility gene for rheumatoid arthritis (RA). In this study, we performed the association analysis between DNA methylation of HTR2A with RA within peripheral blood samples. Methods: We enrolled peripheral blood samples from 235 patients with RA, 30 osteoarthritis (OA) patients, and 30 healthy controls. The DNA methylation levels of about 218 bp from chr13: 46898190 to chr13: 46897973 (GRCh38/hg38) around HTR2A cg15692052 from patients were analyzed by targeted methylation sequencing. Results: We measured methylation status for 7 CpGs in the promoter region of HTR2A and obseved overall methylation status are signficantly increased in RA compared with normal inviduals (FDR= 9.05 x 10-5). The average cg15692052 methylation levels (methylation score) showed a positive correlation with CRP (r=0.15, P=0.023). Compared with the OA group or HC group, the proportion of haplotypes CCCCCCC (FDR=0.02 and 2.81 x 10-6) is signficantly increased while TTTTTCC (FDR =0.01) and TTTTTTT(FDR =6.92 x 10-3) are significantly decreased in RA. We find methylation haplotypes combining with RF and CCP could signficantly enhance the performance of the diagnosing RA and its comorbidities (hypertension, interstitial lung disease, and osteoporosis), especially in interstitial lung disease. Conclusions: In our study, we found signficant hypermethylation of promoter region of HTR2A which indicates the potential clinical diagnostic role in rheumatoid arthritis.