Exploring the mechanism of action of Shuangyang houbitong granules in the treatment of acute pharyngitis based on network pharmacology and molecular docking.

BACKGROUND: Acute pharyngitis (AP) refers to the acute inflammation of the pharynx, characterized by swelling and pain in the throat. Shuangyang houbitong granules (SHG), a traditional Chinese medicine compound, have been found to be effective in providing relief from symptoms associated with AP. METHODS: The chemical components of SHG were screened using Traditional Chinese Medicine Systems Pharmacology database, HERB database, and China National Knowledge Infrastructure. The targets of the granules were predicted using SwissTargetPrediction database. A network was constructed based on the targets of AP obtained from Genecards database, and protein-protein interaction analysis was performed on the intersection targets using STRING database. Key targets were screened for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and the binding activity of components and targets was predicted using AutoDockTools-1.5.7. RESULTS: A total of 65 components of SHG that met the screening criteria were retrieved, resulting in 867 corresponding targets. Additionally, 1086 AP target genes were retrieved, and 272 gene targets were obtained from the intersection as potential targets for SHG in the treatment of AP. Molecular docking results showed that the core components genkwanin, acacetin, apigenin, quercetin can stably bind to the core targets glyceraldehyde 3-phosphate dehydrogenase, interleukin 6, tumor necrosis factor, serine/threonine protein kinase, tumor protein 53, and epidermal growth factor receptor. CONCLUSION: The research results preliminarily predict and verify the mechanism of action of SHG in the treatment of AP, providing insights for further in-depth research.

Deep evolutionary fusion neural network: a new prediction standard for infectious disease incidence rates.

BACKGROUND: Previously, many methods have been used to predict the incidence trends of infectious diseases. There are numerous methods for predicting the incidence trends of infectious diseases, and they have exhibited varying degrees of success. However, there are a lack of prediction benchmarks that integrate linear and nonlinear methods and effectively use internet data. The aim of this paper is to develop a prediction model of the incidence rate of infectious diseases that integrates multiple methods and multisource data, realizing ground-breaking research. RESULTS: The infectious disease dataset is from an official release and includes four national and three regional datasets. The Baidu index platform provides internet data. We choose a single model (seasonal autoregressive integrated moving average (SARIMA), nonlinear autoregressive neural network (NAR), and long short-term memory (LSTM)) and a deep evolutionary fusion neural network (DEFNN). The DEFNN is built using the idea of neural evolution and fusion, and the DEFNN + is built using multisource data. We compare the model accuracy on reference group data and validate the model generalizability on external data. (1) The loss of SA-LSTM in the reference group dataset is 0.4919, which is significantly better than that of other single models. (2) The loss values of SA-LSTM on the national and regional external datasets are 0.9666, 1.2437, 0.2472, 0.7239, 1.4026, and 0.6868. (3) When multisource indices are added to the national dataset, the loss of the DEFNN + increases to 0.4212, 0.8218, 1.0331, and 0.8575. CONCLUSIONS: We propose an SA-LSTM optimization model with good accuracy and generalizability based on the concept of multiple methods and multiple data fusion. DEFNN enriches and supplements infectious disease prediction methodologies, can serve as a new benchmark for future infectious disease predictions and provides a reference for the prediction of the incidence rates of various infectious diseases.

The efficacy and safety of diterpene ginkgolides meglumine injection for cerebral infarction: A meta-analysis of randomized controlled trials.

OBJECTIVE: To systemically evaluate the efficacy and safety of diterpene ginkgolides meglumine injection (DGMI) on cerebral infarction (CI). METHODS: Comprehensively collect randomized controlled trials of DGMI in the treatment of CI in 7 databases including Embase, PubMed, the Cochrane Library, the China National Knowledge Infrastructure Database, the WanFang Database, the China Science and Technology Journal Database, and the China Biology Medicinedisc as of January 2023. The studies were screened according to the inclusion and exclusion criteria and evaluated according to the criteria recommended by the Cochrane Handbook, then RevMan 5.3, Stata 12.0 software were used for Meta-analysis. RESULTS: A total of 22 randomized controlled trials with 2194 patients were included. Meta analysis showed that: the total effective rate of treatment (relative risk = 1.29, 95% confidence interval (1.21, 1.38), P < .001), National Institute of Health stroke scale score, Barthel index and Modified Rankin Scale were better in DGMI group than in Conventional Western Medicine Treatment group. The included studies reported 42 adverse events, 25 of which belonged to DGMI groups. CONCLUSION: Available evidence suggested that DGMI can significantly improve the clinical efficiency in the treatment of CI. DGMI is an ideal treatment for CI, which has high clinical application value.

Systematic review and meta-analysis on the efficacy and safety of Injectable Lentinan combined with chemotherapy in the treatment of gastric cancer.

BACKGROUND: This study employed a meta-analysis to evaluate the efficacy and safety of adjunctive treatment with injectable Lentinan (LNT) in combination with chemotherapy for gastric cancer (GC). METHODS: Computer-based searches of 6 databases were performed to identify randomized controlled trials (RCTs) relevant to the treatment of GC with LNT through mid-March 2023. Two independent researchers performed risk of bias assessment and trial sequential analysis(TSA), extracted the data and used Revman 5.3 software for data analysis. The certainty of evidence was graded based on the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. RESULTS: A total of 31 RCTs with 2729 patients were included in the analysis. The results revealed that adjunctive therapy with LNT was associated with improved treatment efficacy (RR = 1.48, 95%CI: 1.36 ∼ 1.61, p < 0.00001), improvement in clusters of differentiation (CD3+, CD4+, and CD4+/CD8+), natural killer (NK) cells, and quality of life assessment (RR = 1.32, 95%CI: 1.20 ∼ 1.45, p < 0.00001) compared to using chemotherapy alone. In addition, there was a reduction in CD8+ levels, incidence of white blood cell decline, gastrointestinal reactions, and platelet decline. TSA results indicated that there was sufficient evidence to draw firm conclusions about these outcomes, and the GRADE scores showed 'high' or 'moderate' quality of evidence for these outcomes. CONCLUSION: The efficacy of treatment of GC with LNT in combination with chemotherapy was found to be better than chemotherapy alone. And no serious adverse effects were observed. However, further RCTs are needed to further validate the results of this study.

Corrigendum: Revealing the mechanism of Huazhi Rougan granule in the treatment of nonalcoholic fatty liver through intestinal flora based on 16S rRNA, metagenomic sequencing and network pharmacology.

[This corrects the article DOI: 10.3389/fphar.2022.875700.].

[Carbon Sequestration Characteristics Under Natural Vegetation Restoration in Ziwuling Area of the Loess Plateau].

The aim of this study was to analyze the carbon sink effect under natural vegetation restoration and the influence of changes in vegetation community characteristics on ecosystem carbon density in ecologically fragile areas of the Loess Plateau. In this study, the changes in carbon sequestration of a vegetation-soil system under eight successional stages[slope cropland, abandoned cropland for 10 years, abandoned cropland for 20 years, Sophora davidii (Franch.) Skeels., Betula platyphylla Suk., Pinus tabulaeformis Carr., Quercus wutaishanic Mary+P. tabulaeformis Carr mixed forests, and Q. wutaishanic Mary] in Ziwuling area over 150 restoration periods were investigated using the common method of spatial and temporal substitution. This study also discussed the relationship between changes in vegetation community characteristics and vegetation-soil system carbon density. The results showed that the community coverage of the investigated vegetation fluctuated from 85% in the slope cropland stage to 100% in the arbor stage. The number of species, Margalef index, Shannon-Wiener index, Pielou index, and Simpson index initially increased rapidly, then declined slowly until becoming stable, and reached a peak in the middle of the succession (B. platyphylla Suk.). The biomass and carbon density of vegetation components (above-ground biomass, below-ground roots, and litter) increased exponentially during the succession, i.e., increased slowly before B. platyphylla Suk. but increased significantly in B. platyphylla Suk. and P. tabulaeformis Carr.(P<0.05). The biomass and carbon density reached the maximum values of 27858.08 g·m-2 and 13232.51 g·m-2, respectively, in Q. wutaishanic Mary+P. tabulaeformis Carr mixed forests and tended to be stable in the late succession stage. Soil organic carbon density showed a power function relationship with vegetation restoration, with the greatest increase in the stages of abandoned cropland for 10 years and B. platyphylla, but no significant changes in the subsequent stages (P>0.05). In the early succession stage, the carbon density of the farmland ecosystem was the lowest (4395.70 g·m-2), whereas the other seven stages increased by 55.54%, 40.37%, 69.96%, 202.48%, 326.35%, 357.43%, and 351.07%, respectively, compared with the farmland ecosystem. Community coverage, Margalef index, Shannon-Wiener index, above-ground biomass, root biomass, and litter biomass were significantly positively correlated with vegetation-soil system carbon density (P<0.05). The carbon sink effect of long-term natural restoration in Ziwuling Region was significant, and the carbon density of the vegetation-soil system under interspecific competition tended to be stable in the late succession stage. Dynamic changes in the vegetation community structure and plant diversity during the succession process increased vegetation carbon density and soil carbon density. This study helps to clarify the carbon sink effect of natural vegetation restoration in ecologically fragile areas of the Loess Plateau and provides a theoretical basis for promoting natural forest conservation and achieving carbon neutrality.

Isoliquiritigenin inhibits virus replication and virus-mediated inflammation via NRF2 signaling.

BACKGROUND: The transcription factor NRF2 is a master redox switch that regulates the cellular antioxidant response. However, recent advances have revealed new roles for NRF2, including the regulation of antiviral responses to various viruses, suggesting that pharmacological NRF2-activating agents may be a promising therapeutic drug for viral diseases. Isoliquiritigenin (ISL), a chalcone isolated from liquorice (Glycyrrhizae Radix) root, is reported to be a natural NRF2 agonist and has has antiviral activities against HCV (hepatitis C virus) and IAV (influenza A virus). However, the spectrum of antiviral activity and associated mechanism of ISL against other viruses are not well defined. PURPOSE: This study investigated the antiviral activity and underlying mechanism of ISL against vesicular stomatitis virus (VSV), influenza A virus (H1N1), encephalomyocarditis virus (EMCV), herpes simplex virus type 1 (HSV-1). METHODS: We evaluated the antiviral activity of ISL against VSV, H1N1, EMCV, and HSV-1 using flow cytometry and qRT-PCR analysis. RNA sequencing and bioinformatic analysis were performed to investigate the potential antiviral mechanism of ISL. NRF2 knockout cells were used to investigate whether NRF2 is required for the antiviral activity of ISL. The anti-apoptosis and anti-inflammatory activities of ISL were further measured by counting cell death ratio and assessing proinflammatory cytokines expression in virus-infected cells, respectively. In addition, we evaluated the antiviral effect of ISL in vivo by measuring the survival rate, body weights, histological analysis, viral load, and cytokine expression in VSV-infected mouse model. RESULTS: Our data demonstrated that ISL effectively suppressed VSV, H1N1, HSV-1, and EMCV replication in vitro. The antiviral activity of ISL could be partially impaired in NRF2-deficient cells. Virus-induced cell death and proinflammatory cytokines were repressed by ISL. Finally, we showed that ISL treatment protected mice against VSV infection by reducing viral titers and suppressing the expression of inflammatory cytokines in vivo. CONCLUSION: These findings suggest that ISL has antiviral and anti-inflammatory effects in virus infections, which are associated with its ability to activate NRF2 signaling, thus indicating that ISL has the potential to serve as an NRF2 agonist in the treatment of viral diseases.

ZNFX1 antisense RNA1 promotes antiviral innate immune responses via modulating ZNFX1 function.

Increasing evidence suggests that natural antisense transcriptional lncRNAs regulate their adjacent coding genes to mediate diverse aspects of biology. Bioinformatics analysis of the previously identified antiviral gene ZNFX1 revealed neighboring lncRNA ZFAS1 transcribed on the opposite strand from ZNFX1. Whether ZFAS1 exerts antiviral function via regulating the dsRNA sensor ZNFX1 is unknown. Here we found that ZFAS1 was upregulated by RNA and DNA viruses and type I IFNs (IFN-I) dependent on Jak-STAT signaling, similar to the transcription regulation of ZNFX1. Knockdown of endogenous ZFAS1 partially facilitated viral infection, while ZFAS1 overexpression showed opposite effects. In addition, mice were more resistant to VSV infection with the delivery of human ZFAS1. We further observed that ZFAS1 knockdown significantly inhibited IFNB1 expression and IFR3 dimerization, whereas ZFAS1 overexpression positively regulated antiviral innate immune pathways. Mechanistically, ZFAS1 positively regulated ZNFX1 expression and antiviral function by enhancing the protein stability of ZNFX1, thereby establishing a positive feedback loop to enhance antiviral immune activation status. In short, ZFAS1 is a positive regulator of antiviral innate immune response via regulating its neighbor gene ZNFX1, adding new mechanistic insight into lncRNA-mediated regulation of signaling in innate immunity.

Identification of key pharmacological components and targets for Aidi injection in the treatment of pancreatic cancer by UPLC-MS, network pharmacology, and in vivo experiments.

BACKGROUND: Pancreatic cancer is one of the most lethal cancers worldwide. Aidi injection (ADI) is a representative antitumor medication based on Chinese herbal injection, but its antitumor mechanisms are still poorly understood. MATERIALS AND METHODS: In this work, the subcutaneous xenograft model of human pancreatic cancer cell line Panc-1 was established in nude mice to investigate the anticancer effect of ADI in vivo. We then determined the components of ADI using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS) and explored the possible molecular mechanisms against pancreatic cancer using network pharmacology. RESULTS: In vivo experiments, the volume, weight, and degree of histological abnormalities of implanted tumors were significantly lower in the medium and high concentration ADI injection groups than in the control group. Network pharmacology analysis identified four active components of ADI and seven key targets, TNF, VEGFA, HSP90AA1, MAPK14, CASP3, P53 and JUN. Molecular docking also revealed high affinity between the active components and the target proteins, including Astragaloside IV to P53 and VEGFA, Ginsenoside Rb1 to CASP3 and Formononetin to JUN. CONCLUSION: ADI could reduce the growth rate of tumor tissue and alleviate the structural abnormalities in tumor tissue. ADI is predicted to act on VEGFA, P53, CASP3, and JUN in ADI-mediated treatment of pancreatic cancer.

Scoparone suppresses mitophagy-mediated NLRP3 inflammasome activation in inflammatory diseases.

Recent evidence shows that targeting NLRP3 inflammasome activation is an important means to treat inflammasome-driven diseases. Scoparone, a natural compound isolated from the Chinese herb Artemisia capillaris Thunb, has anti-inflammatory activity. In this study we investigated the effect of scoparone on NLRP3 inflammasome activation in inflammatory diseases. In LPS-primed, ATP or nigericin-stimulated mouse macrophage J774A.1 cells and bone marrow-derived macrophages (BMDMs), pretreatment with scoparone (50 µM) markedly restrained canonical and noncanonical NLRP3 inflammasome activation, evidenced by suppressed caspase-1 cleavage, GSDMD-mediated pyroptosis, mature IL-1ß secretion and the formation of ASC specks. We then conducted a transcriptome analysis in scoparone-pretreated BMDMs, and found that the differentially expressed genes were significantly enriched in mitochondrial reactive oxygen species (ROS) metabolic process, mitochondrial translation and assembly process, as well as in inflammatory response. We demonstrated in J774A.1 cells and BMDMs that scoparone promoted mitophagy, a well-characterized mechanism to control mitochondrial quality and reduce ROS production and subsequent NLRP3 inflammasome activation. Mitophagy blockade by 3-methyladenine (3-MA, 5 mM) reversed the protective effects of scoparone on mitochondrial damage and inflammation in the murine macrophages. Moreover, administration of scoparone (50 mg/kg) exerted significant preventive effects via inhibition of NLRP3 activation in mouse models of bacterial enteritis and septic shock. Collectively, scoparone displays potent anti-inflammatory effects via blocking NLRP3 inflammasome activation through enhancing mitophagy, highlighting a potential action mechanism in treating inflammasome-related diseases for further clinical investigation.

[Carbon Sequestration Characteristics of Different Restored Vegetation Types in Loess Hilly Region].

Since 1999, the "Grain for Green" Program has been extensively implemented in the Loess Plateau region. This measure has largely been of concern not only for its contribution to soil erosion reduction but also for its effects on carbon sequestration. The aim of this study was to assess the carbon sequestration characteristics of different restored vegetation types in areas with severe soil erosion on the Loess Plateau and to compare the effects of restoration age and slope direction on the vegetation carbon sequestration. To evaluate the carbon density and composition characteristics of different ecosystem types, six typical vegetation types (including farmland, grassland, Hippophae rhamnoides Linn., Caragana korshinskii Kom., Robinia pseudoacacia L., and Populus davidiana Dode.) were selected in the Loess Hilly Region, i.e., Wuqi County and Zhidan County in Northern Shaanxi province, which is a typical area for the implementation of artificial vegetation restoration. The results showed that:① vegetation restoration in the semi-arid loess region had a profound impact on carbon sequestration. The carbon density of different vegetations, as well as different vegetation components including above-ground vegetation, below-ground roots, and litter, shared the same pattern as tree>scrub>grassland>farmland. The 0-40 cm soil layer of the farmland showed the lowest soil organic carbon density (1355.5 g·m-2), compared to which those of grassland, H. rhamnoides Linn., C. korshinskii Kom., R. pseudoacacia L., and P. davidiana Dode. were higher by 91.4%, 125.2%, 144.0%, 124.5%, and 232.6%, respectively. ② It was common in grassland, H. rhamnoides Linn., C. korshinskii Kom., and P. davidiana Dode. for the carbon density of different vegetation components as well as soil organic carbon density of different soil layers (0-5, 5-20, and 20-40 cm) to generally show an increasing trend with increased restoration age. ③ Slope direction had a significant impact on the vegetation carbon density only for H. rhamnoides Linn., C. korshinskii Kom., R. pseudoacacia L., and P. davidiana Dode., while showing the contrary for farmland and grassland. Soil organic carbon densities for sunny slopes were significantly lower than those for shaded slopes by 22.9%, 34.3%, 75.8%, 49.1%, 22.4%, and 69.4%, respectively, for farmland, grassland, H. rhamnoides Linn., C. korshinskii Kom., R. pseudoacacia L., and P. davidiana Dode. ④ Ecosystem carbon density varied significantly for different ecosystem types, among which farmland showed the lowest (2022.1 g·m-2), and grassland, H. rhamnoides Linn., C. korshinskii Kom., R. pseudoacacia L., and P. davidiana Dode. showed values higher by 48.7%, 152.8%, 125.1%, 166.3%, and 530.7%, respectively. The carbon density of each ecosystem component showed a pattern as follows:soil layer>above-ground vegetation layer>root layer>litter layer. Soil organic carbon constituted the main part of the ecosystem carbon density and accounted for 67.0%, 86.3%, 59.7%, 72.7%, and 56.5%, respectively, for farmland, grassland, H. rhamnoides Linn., C. korshinskii Kom., and R. pseudoacacia L. These results can provide an essential basis for scientific management of ecosystem carbon pools and promote ecological environment management on the Loess Plateau.

E-DU: Deep neural network for multimodal medical image segmentation based on semantic gap compensation.

BACKGROUND: U-Net includes encoder, decoder and skip connection structures. It has become the benchmark network in medical image segmentation. However, the direct fusion of low-level and high-level convolution features with semantic gaps by traditional skip connections may lead to problems such as fuzzy generated feature maps and target region segmentation errors. OBJECTIVE: We use spatial enhancement filtering technology to compensate for the semantic gap and propose an enhanced dense U-Net (E-DU), aiming to apply it to multimodal medical image segmentation to improve the segmentation performance and efficiency. METHODS: Before combining encoder and decoder features, we replace the traditional skip connection with a multiscale denoise enhancement (MDE) module. The encoder features need to be deeply convolved by the spatial enhancement filter and then combined with the decoder features. We propose a simple and efficient deep full convolution network structure E-DU, which can not only fuse semantically various features but also denoise and enhance the feature map. RESULTS: We performed experiments on medical image segmentation datasets with seven image modalities and combined MDE with various baseline networks to perform ablation studies. E-DU achieved the best segmentation results on evaluation indicators such as DSC on the U-Net family, with DSC values of 97.78, 97.64, 95.31, 94.42, 94.93, 98.85, and 98.38 (%), respectively. The addition of the MDE module to the attention mechanism network improves segmentation performance and efficiency, reflecting its generalization performance. In comparison to advanced methods, our method is also competitive. CONCLUSION: Our proposed MDE module has a good segmentation effect and operating efficiency, and it can be easily extended to multiple modal medical segmentation datasets. Our idea and method can achieve clinical multimodal medical image segmentation and make full use of image information to provide clinical decision support. It has great application value and promotion prospects.

Investigation on the efficiency of Brucea javanica oil emulsion injection with chemotherapy for treating malignant pleural effusion: A meta-analysis of randomized controlled trials.

Introduction: Systematic evaluation of the clinical efficacy and safety of Brucea javanica oil emulsion injection (BJOEI) in combination with chemotherapy in the treatment of malignant pleural effusion (MPE). Methods: The study searched CNKI, Wanfang database, VIP database, SinoMed, PubMed, Embase, the Cochrane Library, and the Web of Science database and retrieved randomized controlled trials (RCTs) on the treatment of MPE with BJOEI in combination with chemotherapy from seven electronic databases from inception to 31 March 2022. Meta-analysis and sensitivity analysis were performed using Revman 5.4 and Stata 13.0 software. Results: Ultimately, 30 RCTs with 2035 patients were included, including 1002 cases in the control group and 1033 cases in the treatment group. The results of the meta-analysis showed that the overall efficacy rate of BJOEI combined with chemotherapy was higher in the treatment of MPE compared with chemotherapy alone (RR = 1.45, 95%CI: 1.36-1.54, p < 0.00001). And it could improve the Karnofsky (KPS) score (RR = 1.54, 95%CI: 1.41-1.68, p < 0.00001), reduce adverse reactions such as fever (RR = 0.82, 95%CI:0.60-1.12), chest pain (RR = 0.90, 95%CI: 0.67-1.21), gastrointestinal reactions (RR = 0.70, 95%CI: 0.57-0.87, p < 0.005), and leukopenia (RR = 0.51, 95%CI: 0.43-0.61, p < 0.00001). Conclusion: BJOEI combined with chemotherapy has better clinical efficacy than chemotherapy alone in the treatment of MPE. It can further improve KPS score, improve patients' quality of life, and reduce the occurrence of adverse reactions. However, the conclusions of this study need to be confirmed by further randomized, double-blind, controlled trials with large sample size, reasonable design, and strict implementation.

Integrated bioinformatics analysis reveals potential mechanisms associated with intestinal flora intervention in nonalcoholic fatty liver disease.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is a common chronic liver disease that imposes a huge economic burden on global public health. And the gut-liver axis theory supports the therapeutic role of intestinal flora in the development and progression of NAFLD. To this end, we designed bioinformatics study on the relationship between intestinal flora disorder and NAFLD, to explore the possible molecular mechanism of intestinal flora interfering with NAFLD. METHODS: Differentially expressed genes for NAFLD were obtained from the GEO database. And the disease genes for NAFLD and intestinal flora disorder were obtained from the disease databases. The protein-protein interaction network was established by string 11.0 database and visualized by Cytoscape 3.7.2 software. Cytoscape plug-in MCODE and cytoHubba were used to screen the potential genes of intestinal flora disorder and NAFLD, to obtain potential targets for intestinal flora to interfere in the occurrence and process of NAFLD. Enrichment analysis of potential targets was carried out using R 4.0.2 software. RESULTS: The results showed that 7 targets might be the key genes for intestinal flora to interfere with NAFLD. CCL2, IL6, IL1B, and FOS are mainly related to the occurrence and development mechanism of NAFLD, while PTGS2, SPINK1, and C5AR1 are mainly related to the intervention of intestinal flora in the occurrence and development of NAFLD. The gene function is mainly reflected in basic biological processes, including the regulation of metabolic process, epithelial development, and immune influence. The pathway is mainly related to signal transduction, immune regulation, and physiological metabolism. The TNF signaling pathway, AGE-RAGE signaling pathway in diabetic activity, and NF-Kappa B signaling pathways are important pathways for intestinal flora to interfere with NAFLD. According to the analysis results, there is a certain correlation between intestinal flora disorder and NAFLD. CONCLUSION: It is speculated that the mechanism by which intestinal flora may interfere with the occurrence and development of NAFLD is mainly related to inflammatory response and insulin resistance. Nevertheless, further research is needed to explore the specific molecular mechanisms.

Construction of a Medical Micro-Object Cascade Network for Automated Segmentation of Cerebral Microbleeds in Susceptibility Weighted Imaging.

Aim: The detection and segmentation of cerebral microbleeds (CMBs) images are the focus of clinical diagnosis and treatment. However, segmentation is difficult in clinical practice, and missed diagnosis may occur. Few related studies on the automated segmentation of CMB images have been performed, and we provide the most effective CMB segmentation to date using an automated segmentation system. Materials and Methods: From a research perspective, we focused on the automated segmentation of CMB targets in susceptibility weighted imaging (SWI) for the first time and then constructed a deep learning network focused on the segmentation of micro-objects. We collected and marked clinical datasets and proposed a new medical micro-object cascade network (MMOC-Net). In the first stage, U-Net was utilized to select the region of interest (ROI). In the second stage, we utilized a full-resolution network (FRN) to complete fine segmentation. We also incorporated residual atrous spatial pyramid pooling (R-ASPP) and a new joint loss function. Results: The most suitable segmentation result was achieved with a ROI size of 32 × 32. To verify the validity of each part of the method, ablation studies were performed, which showed that the best segmentation results were obtained when FRN, R-ASPP and the combined loss function were used simultaneously. Under these conditions, the obtained Dice similarity coefficient (DSC) value was 87.93% and the F2-score (F2) value was 90.69%. We also innovatively developed a visual clinical diagnosis system that can provide effective support for clinical diagnosis and treatment decisions. Conclusions: We created the MMOC-Net method to perform the automated segmentation task of CMBs in an SWI and obtained better segmentation performance; hence, this pioneering method has research significance.

Revealing the Mechanism of Huazhi Rougan Granule in the Treatment of Nonalcoholic Fatty Liver Through Intestinal Flora Based on 16S rRNA, Metagenomic Sequencing and Network Pharmacology.

Background: The incidence of Nonalcoholic Fatty Liver (NAFL) is increasing year by year, growing evidence suggests that the intestinal flora plays a causative role in NAFL. Huazhi Rougan Granule (HRG) is commonly used in the clinical treatment of NAFL. It is reported that it can reduce lipids and protect the liver, but no research has confirmed whether the drug's effect is related to the intestinal flora. Therefore, we investigated whether the effect of HRG is related to the regulation of intestinal flora to further explore the mechanism of HRG in the treatment of NAFL through intestinal flora. Methods: In this study, C57BL/6J mice were fed a high-fat diet for 8 weeks, and the high-fat diet plus HRG or polyene phosphatidylcholine capsules were each administered by gavage for 4 weeks. High-throughput sequencing, network pharmacology, and molecular docking were used to explore the mechanism of HRG in the treatment of NAFL through intestinal flora. Results: HRG treatment can reduce body weight gain, lipid accumulation in liver and lipogenesis and reduce serum biochemical indexes in high-fat-fed mice. Analysis of intestinal flora showed that HRG changed the composition of intestinal flora, which was characterized by a decrease in the Firmicutes/Bacteroidetes ratio. Moreover, the species distribution was significantly correlated with AKP, HDL-C, and TG. Metagenetic analysis showed that HRG altered the functional composition and functional diversity of microorganisms, which was mainly characterized by an increase in the abundance of metabolic pathways. The network pharmacology results show that the mechanism of HRG in the treatment of NAFL through intestinal flora is mainly reflected in the biological process of gene function and related to infectious diseases, immune systems, and signal transduction pathways, such as cytokine-cytokine receptor interaction, Chagas disease, IL-17 signaling pathway and other signaling pathways. Conclusion: These results strongly suggest that HRG may alleviate NAFL by preventing IFD.

Spatial Heterogeneity of Household Food Consumption and Nutritional Characteristics of Grassland Transects in Inner Mongolia, China.

Household food consumption is the associative link between ecosystems and anthropogenic activities. In grassland areas, inappropriate food consumption patterns will cause irreversible damage to vulnerable local ecosystems. For this study, we selected three typical transitional grassland areas of Inner Mongolia, China (i.e., meadow steppe, typical steppe, and desert steppe), to analyze spatial heterogeneity in household food consumption and nutritional characteristics. Results showed that: (a) Food consumption structures exhibited zonal gradients from east to west alongside a reduction in grassland conditions. Additionally, the average food consumption quantity also decreased. Available food supplies altered household preferences for vegetables and fruits, meat, dairy products, and other food consumption category types. (b) The nutritional structure implied that grains provided the main source of energy, proteins, and fat for local rural households, while meat, dairy products, beans (including bean byproducts), and oils caused a fluctuation in the nutritional structure of residents. (c) Local food supplies affect short-term local food consumption patterns, while socioeconomic development affects long-term food consumption patterns. This study is intended to provide a reference for the development of sustainable strategies for regional resource management.

COVID-19 epidemic and public health interventions in Shanghai, China: Statistical analysis of transmission, correlation and conversion.

Background: The Shanghai COVID-19 epidemic is an important example of a local outbreak and of the implementation of normalized prevention and disease control strategies. The precise impact of public health interventions on epidemic prevention and control is unknown. Methods: We collected information on COVID-19 patients reported in Shanghai, China, from January 30 to May 31, 2022. These newly added cases were classified as local confirmed cases, local asymptomatic infections, imported confirmed cases and imported asymptomatic infections. We used polynomial fitting correlation analysis and illustrated the time lag plot in the correlation analysis of local and imported cases. Analyzing the conversion of asymptomatic infections to confirmed cases, we proposed a new measure of the conversion rate (C r ). In the evolution of epidemic transmission and the analysis of intervention effects, we calculated the effective reproduction number (R t ). Additionally, we used simulated predictions of public health interventions in transmission, correlation, and conversion analyses. Results: (1) The overall level of R t in the first three stages was higher than the epidemic threshold. After the implementation of public health intervention measures in the third stage, R t decreased rapidly, and the overall R t level in the last three stages was lower than the epidemic threshold. The longer the public health interventions were delayed, the more cases that were expected and the later the epidemic was expected to end. (2) In the correlation analysis, the outbreak in Shanghai was characterized by double peaks. (3) In the conversion analysis, when the incubation period was short (3 or 7 days), the conversion rate fluctuated smoothly and did not reflect the effect of the intervention. When the incubation period was extended (10 and 14 days), the conversion rate fluctuated in each period, being higher in the first five stages and lower in the sixth stage. Conclusion: Effective public health interventions helped slow the spread of COVID-19 in Shanghai, shorten the outbreak duration, and protect the healthcare system from stress. Our research can serve as a positive guideline for addressing infectious disease prevention and control in China and other countries and regions.

A novel strategy to reveal clinical advantages and molecular mechanism of aidi injection in the treatment of pancreatic cancer based on network meta-analysis and network pharmacology.

ETHNOPHARMACOLOGICAL RELEVANCE: Pancreatic cancer is a common malignancy worldwide due to its poor prognosis and high mortality rate. It is clinically proven that the combination of chemotherapeutic drugs and Traditional Chinese Medicine injections (TCMIs) significantly improves the therapeutic effect. AIM OF THE STUDY: To evaluate the efficacy and clinical benefits of TCMIs in combination with chemotherapy in the treatment of pancreatic cancer and to explore the mechanism of clinical advantage of Aidi injection. METHODS: Randomized controlled trials (RCTs) were searched in databases by NMA before December 29, 2020. WinBUGS 1.4, Stata 14.0, and R 4.0.4 software were used for calculations. All results were expressed as odds ratios and 95% credible intervals. Through the network pharmacology method, the chemical components and their targets, as well as the disease targets were further analyzed. And then, biological experiments were integrated to verify the results of network pharmacology analysis. (PROSPERO ID: CRD42021283559). RESULTS: A total of 33 RCTs with 8 TCMIs and 2011 patients were included. The results of NMA showed that Aidi injection can significantly improve the clinical efficacy (OR = 0.34, 95%CI: 0.16-0.74), and the clinical advantage was that it can significantly alleviate the leukopenia and thrombocytopenia caused by chemotherapy (OR = 5.65, 95%CI: 1.18-28.13). A total of 23 chemical compounds and 280 potential targets for Aidi injection were obtained from the online databases. Among them, there were 22 compounds, 50 targets and 211 signaling pathways closely related to leukopenia. Five genes were predicted to be core targets of ADI in alleviating leukopenia, and 2 of them (TP53 and VEGFA) were confirmed by biological experiments as regulatory targets of ADI in the treatment of PC. CONCLUSIONS: In conclusion, TCMIs in combination with chemotherapy, can improve clinical efficacy and safety in the treatment of pancreatic cancer. However, the overall evidence base is low, and large samples with multi-center RCTs are still needed to support further research findings. Aidi injection can alleviate leukopenia mainly by intervening in oxidative stress, regulating cell proliferation and apoptosis, and regulating the inflammatory response. The combined application of NMA, network pharmacology, and biological experiments provides a reference for clinical evaluation and mechanism of action exploration of other drugs.

Research progress in laboratory detection of SARS-CoV-2.

BACKGROUND: Nucleic acid testing is a reliable method for diagnosing viral infection in clinical samples. However, when the number of cases is huge and there are individual differences in the virus itself, the probability of false-negative results increases. With the advancement in research on the new coronavirus, new detection technologies that use serum-specific antibodies as detection targets have been developed. These detection technologies have high efficiency and shorter turnaround time, which ultimately shortens the time required for diagnosis. This article summarizes the methods that have been reported to date for the detection of the new coronavirus and discusses their principles and technical characteristics. AIMS: Compare the advantages and disadvantages of various SARS-CoV-2 detection methods and analyze their principles. METHODS: Searched reports on SARS-CoV-2 detection methods published so far, extracted the data and analyzed them. Use the primer blast function of NCBI to analyze the primers used in qRT-PCR detection. RESULTS: The detection sensitivity was the highest when nucleocapsid protein gene was used as the target, reaching 96.6%. The detection efficiency of the remaining targets ranged from 66.7% to 96.0%. Various new detection methods, like Serum specific antibody detection, can speed up the test time. However, due to the complexity of the method and higher testing requirements, it seems that it cannot be used as a complete replacement for qRT-PRC testing. CONCLUSIONS: With the advancement of technology and the improvement of methods, the detection methods of SARSCoV-2 have become more mature. These advances provided great help to the detection of SARS-CoV-2.