Gut microbiota plays a significant role in gout.

With the development of social economy, the incidence of gout is increasing, which is closely related to people's increasingly rich diet. Eating a diet high in purine, fat, sugar and low-fibre for a long time further aggravates gout by affecting uric acid metabolism. The renal metabolism mechanism of uric acid has been thoroughly studied. To find a new treatment method for gout, increasing studies have recently been conducted on the mechanism of intestinal excretion, metabolism and absorption of uric acid. The most important research is the relationship between intestinal microbiota and the risk of gout. Gut microbiota represent bacteria that reside in a host's gastrointestinal tract. The composition of the gut microbiota is associated with protection against pathogen colonization and disease occurrence. This review focuses on how gut microbiota affects gout through uric acid and discusses the types of bacteria that may be involved in the occurrence and progression of gout. We also describe potential therapy for gout by restoring gut microbiota homeostasis and reducing uric acid levels. We hold the perspective that changing intestinal microbiota may become a vital method for effectively preventing or treating gout.

Recent Advances on the Molecular Mechanism and Clinical Trials of Venous Thromboembolism.

Venous thromboembolism is a condition that includes deep vein thrombosis and pulmonary embolism. It is the third most common cardiovascular disease behind acute coronary heart disease and stroke. Over the past few years, growing research suggests that venous thrombosis is also related to the immune system and inflammatory factors have been confirmed to be involved in venous thrombosis. The role of inflammation and inflammation-related biomarkers in cerebrovascular thrombotic disease is the subject of ongoing debate. P-selectin leads to platelet-monocyte aggregation and stimulates vascular inflammation and thrombosis. The dysregulation of miRNAs has also been reported in venous thrombosis, suggesting the involvement of miRNAs in the progression of venous thrombosis. Plasminogen activator inhibitor-1 (PAI-1) is a crucial component of the plasminogen-plasmin system, and elevated levels of PAI-1 in conjunction with advanced age are significant risk factors for thrombosis. In addition, it has been showed that one of the ways that neutrophils promote venous thrombosis is the formation of neutrophil extracellular traps (NETs). In recent years, the role of extracellular vesicles (EVs) in the occurrence and development of VTE has been continuously revealed. With the advancement of research technology, the complex regulatory role of EVs on the coagulation process has been gradually discovered. However, our understanding of the causes and consequences of these changes in venous thrombosis is still limited. Therefore, we review our current understanding the molecular mechanisms of venous thrombosis and the related clinical trials, which is crucial for the future treatment of venous thrombosis.

High Genetic Diversity of HIV-1 and Active Transmission Clusters among Male-to-Male Sexual Contacts (MMSCs) in Zhuhai, China.

Monitoring genetic diversity and recent HIV infections (RHIs) is critical for understanding HIV epidemiology. Here, we report HIV-1 genetic diversity and RHIs in blood samples from 190 HIV-positive MMSCs in Zhuhai, China. MMSCs with newly reported HIV were enrolled from January 2020 to June 2022. A nested PCR was performed to amplify the HIV polymerase gene fragments at HXB2 positions 2604-3606. We constructed genetic transmission network at both 0.5% and 1.5% distance thresholds using the Tamura-Nei93 model. RHIs were identified using a recent infection testing algorithm (RITA) combining limiting antigen avidity enzyme immunoassay (LAg-EIA) assay with clinical data. The results revealed that 19.5% (37/190) were RHIs and 48.4% (92/190) were CRF07_BC. Two clusters were identified at a 0.5% distance threshold. Among them, one was infected with CRF07_BC for the long term, and the other was infected with CRF55_01B recently. We identified a total of 15 clusters at a 1.5% distance threshold. Among them, nine were infected with CRF07_BC subtype, and RHIs were found in 38.8% (19/49) distributed in eight genetic clusters. We identified a large active transmission cluster (n = 10) infected with a genetic variant, CRF79_0107. The multivariable logistic regression model showed that clusters were more likely to be RHIs (adjusted OR: 3.64, 95% CI: 1.51~9.01). The RHI algorithm can help to identify recent or ongoing transmission clusters where the prevention tools are mostly needed. Prompt public health measures are needed to contain the further spread of active transmission clusters.

Imaginal disc growth factor is involved in melanin synthesis and energy metabolism in Bombyx mori.

The imaginal disc growth factor (IDGF), belonging to the glycoside hydrolase 18 family, plays an important role in various physiological processes in insects. However, the detail physiological function of IDGF is still unclear. In this study, transcriptome analysis was performed on the fatbody isolated from staged control and BmIDGF mutant silkworm larvae. Transcriptional profiling revealed that the absence of BmIDGF significantly affected differentially expressed genes involved in tyrosine and purine metabolism, as well as multiple energy metabolism pathways, including glycolysis, galactose, starch, and sucrose metabolism. The interruption of BmIDGF caused similar and specific gene expression changes to male and female fatbody. Furthermore, a genome-scale metabolic network integrating metabolomic and transcriptomic datasets revealed 11 pathways significantly altered at the transcriptional and metabolic levels, including amino acid, carbohydrate, uric acid metabolism pathways, insect hormone biosynthesis, and ABC transporters. In conclusion, this multiomics analysis suggests that IDGF is involved in gene-metabolism interactions, revealing its unique role in melanin synthesis and energy metabolism. This study provides new insights into the physiological function of IDGF in insects.

Comparison between HIV self-testing and facility-based HIV testing approach on HIV early detection among men who have sex with men: A cross-sectional study.

Background: To assess whether HIV self-testing (HIVST) has a better performance in identifying HIV-infected cases than the facility-based HIV testing (HIVFBT) approach. Methods: A cross-sectional study was conducted among men who have sex with men (MSM) by using an online questionnaire (including information on sociodemographic, sexual biography, and HIV testing history) and blood samples (for limiting antigen avidity enzyme immunoassay, gene subtype testing, and taking confirmed HIV test). MSM who were firstly identified as HIV positive through HIVST and HIVFBT were compared. Chi-square or Fisher's exact test was used to explore any association between both groups and their subgroups. Results: In total, 124 MSM HIV cases were identified from 2017 to 2021 in Zhuhai, China, including 60 identified through HIVST and 64 through HIVFBT. Participants in the HIVST group were younger (≤30 years, 76.7% vs. 46.9%), were better educated (>high school, 61.7% vs. 39.1%), and had higher viral load (≥1,000 copies/ml, 71.7% vs. 50.0%) than MSM cases identified through HIVFBT. The proportion of early HIV infection in the HIVST group was higher than in the HIVFBT group, identified using four recent infection testing algorithms (RITAs) (RITA 1, 46.7% vs. 25.0%; RITA 2, 43.3% vs. 20.3%; RITA 3, 30.0% vs. 14.1%; RITA 4, 26.7% vs. 10.9%; all p < 0.05). Conclusions: The study showed that HIVST has better HIV early detection among MSM and that recent HIV infection cases mainly occur in younger and better-educated MSM. Compared with HIVFBT, HIVST is more accessible to the most at-risk population on time and tends to identify the case early. Further implementation studies are needed to fill the knowledge gap on this medical service model among MSM and other target populations.

Alcohol Consumption and Risk of Liver Fibrosis in People Living With HIV: A Systematic Review and Meta-Analysis.

Objectives: It is unclear if a high level of alcohol consumption is a risk factor for liver fibrosis for people living with HIV (PLWH). This study systematically summarizes the risk relationship between different alcohol consumption and the incidence of liver fibrosis among PLWH. Methods: We identified potential studies by searching the PubMed, Embase, Web of Science Library, and CNKI databases up to September 26th, 2021. Observation studies in PLWH that evaluated the relationship between alcohol consumption and the risk of liver fibrosis and estimated the effect of alcohol with pooled odds ratios (pooled ORs) and 95% confidence intervals (CIs) were included. Results: There were total 15 studies included in data analysis. Three studies were set up as cohort studies and the other twelve were cross-sectional studies. Our study was based on 22,676 individuals and 2,729 liver fibrosis cases from 15 studies. Alcohol abuse is a significant risk factor of liver fibrosis (pooled OR = 2.25, 95% CI: 1.59-3.17, p < 0.05) among PLWH. Daily alcohol consumption > 50 g can elevate the risk of liver fibrosis (pooled OR = 3.10, 95% CI: 2.02-4.73, p < 0.05) among PLWH. However, high-risk alcohol consumption determined by AUDIT-C (AUDIT-C ≥ 4) had little or no effect on subsequent liver fibrosis risk. Further, alcohol consumption > 50 g is also a risk factor to liver fibrosis in PLWH co-infected with HCV (pooled OR = 2.48, 95% CI: 1.62-3.80, p < 0.05) and in HIV mono-infected (pooled OR = 1.85, 95% CI: 1.00-3.43, p < 0.05). Conclusion: Alcohol consumption is associated with an increased risk of liver fibrosis in PLWH. HCV co-infection with alcohol abuse could possibly induce a higher risk of liver fibrosis than HIV mono-infected patients. Systematic Review Registration: PROSPERO, identifier (CRD42021272604).

FCL-Net: Towards accurate edge detection via Fine-scale Corrective Learning.

Integrating multi-scale predictions has become a mainstream paradigm in edge detection. However, most existing methods mainly focus on effective feature extraction and multi-scale feature fusion while ignoring the low learning capacity in fine-level branches, limiting the overall fusion performance. In light of this, we propose a novel Fine-scale Corrective Learning Net (FCL-Net) that exploits semantic information from deep layers to facilitate fine-scale feature learning. FCL-Net mainly consists of a Top-down Attentional Guiding (TAG) and a Pixel-level Weighting (PW) module. TAG module adopts semantic attentional cues from coarse-scale prediction into guiding the fine-scale branches by learning a top-down LSTM. PW module treats the contribution of each spatial location independently and promote fine-level branches to detect detailed edges with high confidence. Experiments on three benchmark datasets, i.e., BSDS500, Multicue, and BIPED, show that our approach significantly outperforms the baseline and achieves a competitive ODS F-measure of 0.826 on the BSDS500 benchmark. The source code and models are publicly available at https://github.com/DREAMXFAR/FCL-Net.

Mechanisms and Clinical Trials of Hepatocellular Carcinoma Immunotherapy.

Hepatocellular carcinoma (HCC), one of the most common and lethal tumors worldwide, is usually not diagnosed until the disease is advanced, which results in ineffective intervention and unfavorable prognosis. Small molecule targeted drugs of HCC, such as sorafenib, provided only about 2.8 months of survival benefit, partially due to cancer stem cell resistance. There is an urgent need for the development of new treatment strategies for HCC. Tumor immunotherapies, including immune check point inhibitors, chimeric antigen receptor T cells (CAR-T) and bispecific antibodies (BsAb), have shown significant potential. It is known that the expression level of glypican-3 (GPC3) was significantly increased in HCC compared with normal liver tissues. A bispecific antibody (GPC3-S-Fabs) was reported to recruit NK cells to target GPC3 positive cancer cells. Besides, bispecific T-cell Engagers (BiTE), including GPC3/CD3, an aptamer TLS11a/CD3 and EpCAM/CD3, were recently reported to efficiently eliminate HCC cells. It is known that immune checkpoint proteins programmed death-1 (PD-1) binding by programmed cell death-ligand 1 (PD-L1) activates immune checkpoints of T cells. Anti-PD-1 antibody was reported to suppress HCC progression. Furthermore, GPC3-based HCC immunotherapy has been shown to be a curative approach to prolong the survival time of patients with HCC in clinically trials. Besides, the vascular endothelial growth factor (VEGF) inhibitor may inhibit the migration, invasion and angiogenesis of HCC. Here we review the cutting-edge progresses on mechanisms and clinical trials of HCC immunotherapy, which may have significant implication in our understanding of HCC and its immunotherapy.

The Latest Battles Between EGFR Monoclonal Antibodies and Resistant Tumor Cells.

Epidermal growth factor receptor (EGFR) is a tyrosine kinase receptor involved in homeostatic regulation of normal cells and carcinogenesis of epithelial malignancies. With rapid development of the precision medicine era, a series of new therapies targeting EGFR are underway. Four EGFR monoclonal antibody drugs (cetuximab, panitumumab, nimotuzumab, and necitumumab) are already on the market, and a dozen other EGFR monoclonal antibodies are in clinical trials. Here, we comprehensively review the newly identified biological properties and anti-tumor mechanisms of EGFR monoclonal antibodies. We summarize recently completed and ongoing clinical trials of the classic and new EGFR monoclonal antibodies. More importantly, according to our new standard, we re-classify the complex evolving tumor cell resistance mechanisms, including those involving exosomes, non-coding RNA and the tumor microenvironment, against EGFR monoclonal antibodies. Finally, we analyzed the limitations of EGFR monoclonal antibody therapy, and discussed the current strategies overcoming EGFR related drug resistance. This review will help us better understand the latest battles between EGFR monoclonal antibodies and resistant tumor cells, and the future directions to develop anti-tumor EGFR monoclonal antibodies with durable effects.

Webly-Supervised Fine-Grained Visual Categorization via Deep Domain Adaptation.

Learning visual representations from web data has recently attracted attention for object recognition. Previous studies have mainly focused on overcoming label noise and data bias and have shown promising results by learning directly from web data. However, we argue that it might be better to transfer knowledge from existing human labeling resources to improve performance at nearly no additional cost. In this paper, we propose a new semi-supervised method for learning via web data. Our method has the unique design of exploiting strong supervision, i.e., in addition to standard image-level labels, our method also utilizes detailed annotations including object bounding boxes and part landmarks. By transferring as much knowledge as possible from existing strongly supervised datasets to weakly supervised web images, our method can benefit from sophisticated object recognition algorithms and overcome several typical problems found in webly-supervised learning. We consider the problem of fine-grained visual categorization, in which existing training resources are scarce, as our main research objective. Comprehensive experimentation and extensive analysis demonstrate encouraging performance of the proposed approach, which, at the same time, delivers a new pipeline for fine-grained visual categorization that is likely to be highly effective for real-world applications.

Friend or Foe: Fine-Grained Categorization With Weak Supervision.

Multi-instance learning (MIL) is widely acknowledged as a fundamental method to solve weakly supervised problems. While MIL is usually effective in standard weakly supervised object recognition tasks, in this paper, we investigate the applicability of MIL on an extreme case of weakly supervised learning on the task of fine-grained visual categorization, in which intra-class variance could be larger than inter-class due to the subtle differences between subordinate categories. For this challenging task, we propose a new method that generalizes the standard multi-instance learning framework, for which a novel multi-task co-localization algorithm is proposed to take advantage of the relationship among fine-grained categories and meanwhile performs as an effective initialization strategy for the non-convex multi-instance objective. The localization results also enable object-level domain-specific fine-tuning of deep neural networks, which significantly boosts the performance. Experimental results on three fine-grained datasets reveal the effectiveness of the proposed method, especially the importance of exploiting inter-class relationships between object categories in weakly supervised fine-grained recognition.

[Value of amino-terminal pro-brain natriuretic peptide as a predictive marker of symptomatic patent ductus arteriosus in preterm infants].

OBJECTIVE: To study the value of amino-terminal pro-brain natriuretic peptide (NT-proBNP) in predicting symptomatic patent ductus arteriosus (sPDA) in preterm infants. METHODS: Preterm infants born at a gestational age (GA) of ≤ 32 weeks and diagnosed with patent ductus arteriosus (PDA) by echocardiography within 48 hours after birth between June 2014 and April 2015 were selected as subjects. Their clinical manifestations were observed, and serum NT-proBNP levels were measured and echocardiography was performed at 3 and 5 days after birth. The infants were divided into sPDA group and asymptomatic PDA (asPDA) group based on their clinical manifestations and the results of echocardiography. The correlations between serum NT-proBNP level and echocardiographic indices were analyzed. Serum NT-proBNP levels were compared between the two groups. The receiver operator characteristic (ROC) curve was applied to determine the sensitivity and specificity of serum NT-proBNP in the prediction of sPDA. RESULTS: A total of 69 preterm infants were enrolled in this study, with 13 infants in the sPDA group and 56 infants in the asPDA group. Serum NT-proBNP level was positively correlated with the diameter of the arterial duct (r=0.856; P<0.05)and the ratio of left atrial diameter to aortic root diameter (LA/AO) (r=0.713; P<0.05). At 3 and 5 days after birth, the serum NT-proBNP levels in the sPDA group were significantly higher than those in the asPDA group (P<0.05). The area under the ROC curve (AUC) for the prediction of sPDA by NT-proBNP levels at 3 days after birth was 0.949 (95% CI: 0.892-1.000; P<0.001), with a cut-off value of 27 035 pg/mL (sensitivity: 92.3%; specificity: 94.6%); the AUC for the prediction of sPDA by NT-proBNP levels at 5 days after birth was 0.924 (95% CI: 0.848-1.000; P<0.001), with a cut-off value of 6 411 pg/mL (sensitivity: 92.3%; specificity: 92.9%). CONCLUSIONS: NT-proBNP may be a quantitative index for shunt volume. The measurement of serum NT-proBNP levels on 3 and 5 days after birth may be useful to predict sPDA in preterm infants.