Discussion on the mechanism of Danggui Sini decoction in treating diabetic foot based on network pharmacology and molecular docking and verification of the curative effect by meta-analysis

ObjectiveThe main active components and mechanism of Danggui Sini decoction (DSD) in treating diabetic foot (DF) were studied and verified by network pharmacology and molecular docking. Evidence-based medicine was used to prove its efficacy.MethodsThe TCMSP systematic pharmacology platform screened out DSD’s practical components and targets—screening disease targets in GeneCards database, using Cytoscape 3.7.2 to draw DSD–active ingredient–target network diagram, and drawing the protein interaction network diagram through STRING database. The Metascape platform was used to analyze the GO function enrichment and KEGG signal pathway. The molecular docking experiment was carried out by using Auto Dock vina 4.2. The related literature on DSD in treating DF in China Zhiwang, Wanfang, Weipu, and China Biomedical Literature Database was searched. The literature was screened, data was extracted, and quality was evaluated according to the inclusion and exclusion criteria. Then, a meta-analysis was performed using RevMan 5.3 software.ResultsA total of 256 targets of all effective components of DSD were obtained. Among 1,272 disease targets, there are 113 common targets. The GO analysis received 6,179 entries, and the KEGG pathway enrichment analysis found 251 related pathways. The molecular docking results of the main targets of diabetic foot and the active substances of DSD all showed a high docking activity. The meta-analysis included six literature, all of which were randomized controlled experiments. The quality grade of the literature was C, and the results showed that the total effective rate of clinical efficacy in the experimental group was significantly higher than that in the control group.ConclusionsDSD may treat DF by participating in biological processes such as cell proliferation regulation, inflammatory reaction, oxidative stress reaction, and promotion of angiogenesis. DSD treats DF through AKT1, TP53, IL6, TNF, VEGFA, and other targets. DSD plays a role in treating DF mainly through the AGE-RAGE signaling pathway and PI3K-AKT signaling pathway. The molecular docking results of AKT1, TP53, IL-6, TNF, and VEGFA with the active substances of DSD show that they all have a high docking activity; among them, VEGFA has a higher docking activity. Compared with conventional treatment, DSD has a high effective rate, short wound healing time, large wound healing area, and high ABI index

Analysis of the rainfall threshold for post-fire debris flow initiation: A case study of the debris flow at Ren’eyong gully in Xiangcheng County, Sichuan Province

In the early summer of 2014, a wildfire ravaged the Ren’eyong valley in the central Mt. Hengduan region of southwestern China. Following the blaze, debris flows were triggered three times in branch No. 3 due to short-term, low intensity rainfall. A year later, in August 2015, a brief period of high-intensity rainfall generated debris flows not only in branch No.3, but also in branch No. 1 and No. 2, as well as several smaller basins in the vicinity. To investigate the rainfall response characteristics of post-wildfire debris flow, the distance correction method was used to process the rainfall data. By analyzing the rainfall patterns of four debris flow events, the reseachers were able to identify the effects of watershed characteristics on the initiation of debris flow and its influence on different rainfall thresholds in each branch. The study found that: 1） Post fire debris flows can occur at a low rainfall threshold, which tends to increase over time. 2） The Ren’eyong valley experience high-frequency post fire debris flows, which can be attributed not only to the amplification of slope runoff and erosion caused by rainfall after the destruction of natural vegetation due to the wildfire, but also to the geological and geomorphic conditions of the area. 3） The rainfall threshold in each branch is primarily dependent on the drainage area, as the magnitude of discharge controls the entrainment

Prediction of wheat SPAD using integrated multispectral and support vector machines

Rapidly obtaining the chlorophyll content of crop leaves is of great significance for timely diagnosis of crop health and effective field management. Multispectral imagery obtained from unmanned aerial vehicles (UAV) is being used to remotely sense the SPAD (Soil and Plant Analyzer Development) values of wheat crops. However, existing research has not yet fully considered the impact of different growth stages and crop populations on the accuracy of SPAD estimation. In this study, 300 materials from winter wheat natural populations in Xinjiang, collected between 2020 to 2022, were analyzed. UAV multispectral images were obtained in the experimental area, and vegetation indices were extracted to analyze the correlation between the selected vegetation indices and SPAD values. The input variables for the model were screened, and a support vector machine (SVM) model was constructed to estimate SPAD values during the heading, flowering, and filling stages under different water stresses. The aim was to provide a method for the rapid acquisition of winter wheat SPAD values. The results showed that the SPAD values under normal irrigation were higher than those under water restriction. Multiple vegetation indices were significantly correlated with SPAD values. In the prediction model construction of SPAD, the different models had high estimation accuracy under both normal irrigation and water limitation treatments, with correlation coefficients of predicted and measured values under normal irrigation in different environments the value of r from 0.59 to 0.81 and RMSE from 2.15 to 11.64, compared to RE from 0.10% to 1.00%; and under drought stress in different environments, correlation coefficients of predicted and measured values of r was 0.69–0.79, RMSE was 2.30–12.94, and RE was 0.10%–1.30%. This study demonstrated that the optimal combination of feature selection methods and machine learning algorithms can lead to a more accurate estimation of winter wheat SPAD values. In summary, the SVM model based on UAV multispectral images can rapidly and accurately estimate winter wheat SPAD value

Physisorption-based charge transfer in two-dimensional SnS2 for selective and reversible NO2 gas sensing

Nitrogen dioxide (NO2) is a gas species that plays an important role in certain industrial, farming, and healthcare sectors. However, there are still significant challenges for NO2 sensing at low detection limits, especially in the presence of other interfering gases. The NO2 selectivity of current gas-sensing technologies is significantly traded-off with their sensitivity and reversibility as well as fabrication and operating costs. In this work, we present an important progress for selective and reversible NO2 sensing by demonstrating an economical sensing platform based on the charge transfer between physisorbed NO2 gas molecules and two-dimensional (2D) tin disulfide (SnS2) flakes at low operating temperatures. The device shows high sensitivity and superior selectivity to NO2 at operating temperatures of less than 160 °C, which are well below those of chemisorptive and ion conductive NO2 sensors with much poorer selectivity. At the same time, excellent reversibility of the sensor is demonstrated, which has rarely been observed in other 2D material counterparts. Such impressive features originate from the planar morphology of 2D SnS2 as well as unique physical affinity and favorable electronic band positions of this material that facilitate the NO2 physisorption and charge transfer at parts per billion levels. The 2D SnS2-based sensor provides a real solution for low-cost and selective NO2 gas sensing

The effect of psychological stress on iron absorption in rats

© 2009 Chen et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Bacterial Effector Binding to Ribosomal Protein S3 Subverts NF-κB Function

Enteric bacterial pathogens cause food borne disease, which constitutes an enormous economic and health burden. Enterohemorrhagic Escherichia coli (EHEC) causes a severe bloody diarrhea following transmission to humans through various means, including contaminated beef and vegetable products, water, or through contact with animals. EHEC also causes a potentially fatal kidney disease (hemolytic uremic syndrome) for which there is no effective treatment or prophylaxis. EHEC and other enteric pathogens (e.g., enteropathogenic E. coli (EPEC), Salmonella, Shigella, Yersinia) utilize a type III secretion system (T3SS) to inject virulence proteins (effectors) into host cells. While it is known that T3SS effectors subvert host cell function to promote diarrheal disease and bacterial transmission, in many cases, the mechanisms by which these effectors bind to host proteins and disrupt the normal function of intestinal epithelial cells have not been completely characterized. In this study, we present evidence that the E. coli O157:H7 nleH1 and nleH2 genes encode T3SS effectors that bind to the human ribosomal protein S3 (RPS3), a subunit of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) transcriptional complexes. NleH1 and NleH2 co-localized with RPS3 in the cytoplasm, but not in cell nuclei. The N-terminal region of both NleH1 and NleH2 was required for binding to the N-terminus of RPS3. NleH1 and NleH2 are autophosphorylated Ser/Thr protein kinases, but their binding to RPS3 is independent of kinase activity. NleH1, but not NleH2, reduced the nuclear abundance of RPS3 without altering the p50 or p65 NF-κB subunits or affecting the phosphorylation state or abundance of the inhibitory NF-κB chaperone IκBα NleH1 repressed the transcription of a RPS3/NF-κB-dependent reporter plasmid, but did not inhibit the transcription of RPS3-independent reporters. In contrast, NleH2 stimulated RPS3-dependent transcription, as well as an AP-1-dependent reporter. We identified a region of NleH1 (N40-K45) that is at least partially responsible for the inhibitory activity of NleH1 toward RPS3. Deleting nleH1 from E. coli O157:H7 produced a hypervirulent phenotype in a gnotobiotic piglet model of Shiga toxin-producing E. coli infection. We suggest that NleH may disrupt host innate immune responses by binding to a cofactor of host transcriptional complexes

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions

Mutual regulation of microRNAs and DNA methylation in human cancers

microRNAs (miRNAs) and DNA methylation are the 2 epigenetic modifications that have emerged in recent years as the most critical players in the regulation of gene expression. Compelling evidence has indicated the roles of miRNAs and DNA methylation in modulating cellular transformation and tumorigenesis. miRNAs act as negative regulators of gene expression and are involved in the regulation of both physiologic conditions and during diseases, such as cancer, inflammatory diseases, and psychiatric disorders, among others. Meanwhile, aberrant DNA methylation manifests in both global genome changes and in localized gene promoter changes, which influences the transcription of cancer genes. In this review, we described the mutual regulation of miRNAs and DNA methylation in human cancers. miRNAs regulate DNA methylation by targeting DNA methyltransferases or methylation-related proteins. On the other hand, both hyper- and hypo-methylation of miRNAs occur frequently in human cancers and represent a new level of complexity in gene regulation. Therefore, understanding the mechanisms underlying the mutual regulation of miRNAs and DNA methylation may provide helpful insights in the development of efficient therapeutic approaches