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Abstract Background Shaoyao Decoction (SYD) is a widely recognized herbal formula utilized in traditional Chinese medicine for the treatment of diarrhea. Although it has demonstrated significant effectiveness in clinical practice for treating ulcerative colitis, the precise mechanisms by which it operates remain largely elusive. Methods The active ingredients of SYD were obtained by ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS), which were used to explore the potential pharmacological mechanism based on TCMSP (Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform) and PANTHER (Protein Analysis Through Evolutionary Relationships) classification system. In a mouse model of dextran sulfate sodium (DSS)-induced colitis, mRNA sequencing, 16S rDNA sequencing and targeted metabolomics techniques were used to elucidate the mechanisms of SYD, and immunohistochemistry, immunofluorescence, enzyme linked immunosorbent assay, real time quantitative polymerase chain reaction and western blot were used to test the key targets. In addition, QGP-1 and H9 cells were performed to validate the discoveries from the animal experiments. Results In the mouse model of DSS-induced colitis, SYD effectively alleviated symptoms such as bloody stool, tissue damage, inflammation, intestinal flora dysbiosis and abnormal gene expression. Analyses of both differential expressed genes in colonic tissue and predicted 16S rDNA genes, as well as the analyses of targeted genes from TCMSP based on the active ingredients in UPLC-MS/MS of SYD, uncovered the enrichment of pathways involved in the biosynthesis and degredation of 5-hydroxytryptamine (5-HT). Interestingly, SYD suppressed the relative abundance of key genes in 5-HT synthesis, Tph1(Tryptophan hydroxylase 1) and Ddc (Dopa decarboxylase), in faeces from DSS-induced mice, leading to a reduction in the concentration of fecal 5-HT. Moreover, SYD augmented the production of butyric acid. Subsequently, increasing butyric acid influenced the metabolism of 5-HT in the organism through G protein-coupled receptor 43 by impeding its synthesis, facilitating its transport and degredation. These findings were additionally corroborated in a model utilizing enterochromaffin cell (QGP-1 cells). Furthermore, reduced levels of 5-HT hindered the activation of T lymphocytes (H9 cells) via the PKC (Protein kinase C) and NF-κB (Nuclear factor kappa-B) signaling pathways, by means of HTR1A (5-HT receptor 1A) and HTR3 (5-HT receptor 3). Additionally, diminished secretion of 5-HT resulted in reduced secretion of associated cytokines, thereby alleviating inflammation in the colon. Conclusion Through modulation of T lymphocyte activation mediated by 5-HT metabolism in the local colon via the intestinal flora and its metabolite, SYD effectively mitigated colonic inflammation in DSS-induced mice.

ObjectiveThis study aims to investigate the pathogenesis of hyperglycemia and its associated vasculopathy using multiomics analyses in diabetes and impaired glucose tolerance, and validate the mechanism using the cell experiments.MethodsIn this study, we conducted a comprehensive analysis of the metagenomic sequencing data of diabetes to explore the key genera related to its occurrence. Subsequently, participants diagnosed with impaired glucose tolerance (IGT), and healthy subjects, were recruited for fecal and blood sample collection. The dysbiosis of the gut microbiota (GM) and its associated metabolites were analyzed using 16S rDNA sequencing and liquid chromatograph mass spectrometry, respectively. The regulation of gene and protein expression was evaluated through mRNA sequencing and data-independent acquisition technology, respectively. The specific mechanism by which GM dysbiosis affects hyperglycemia and its related vasculopathy was investigated using real-time qPCR, Western blotting, and enzyme-linked immunosorbent assay techniques in HepG2 cells and neutrophils.ResultsBased on the published data, the key alterable genera in the GM associated with diabetes were identified as Blautia, Lactobacillus, Bacteroides, Prevotella, Faecalibacterium, Bifidobacterium, Ruminococcus, Clostridium, and Lachnoclostridium. The related metabolic pathways were identified as cholate degradation and L-histidine biosynthesis. Noteworthy, Blautia and Faecalibacterium displayed similar alterations in patients with IGT compared to those observed in patients with diabetes, and the GM metabolites, tauroursodeoxycholic acid (TUDCA) and carnosine (CARN, a downstream metabolite of histidine and alanine) were both found to be decreased, which in turn regulated the expression of proteins in plasma and mRNAs in neutrophils. Subsequent experiments focused on insulin-like growth factor-binding protein 3 and interleukin-6 due to their impact on blood glucose regulation and associated vascular inflammation. Both proteins were found to be suppressed by TUDCA and CARN in HepG2 cells and neutrophils.ConclusionDysbiosis of the GM occurred throughout the entire progression from IGT to diabetes, characterized by an increase in Blautia and a decrease in Faecalibacterium, leading to reduced levels of TUDCA and CARN, which alleviated their inhibition on the expression of insulin-like growth factor-binding protein 3 and interleukin-6, contributing to the development of hyperglycemia and associated vasculopathy.

Objective: To investigate the molecular mechanism and identify potential drugs for subthreshold depression (SD), and elucidate the detalied mechanism of Danzhi Xiaoyao powder (DZXY) in SD. Methods: Using RNA-sequencing, we identified differentially expressed genes (DEGs) in leukocytes of SD compared to healthy controls, deciphered their functions and pathways, and identified the hub genes of SD. We also assessed changes in leukocyte transcription factor activity in patients with SD using the TELiS platform. The Connectivity Map database was retrieved to screen candidate drugs for SD. Based on network pharmacology, we elucidated the “multi-component, multi-target, and multi-pathway” mechanism of DZXY in the treatment of SD. Results: We identified 1080 DEGs (padj

Objective: To explore the structural and functional characteristics of microbiota in oropharynx of sub-healthy children with gastrointestinal heat retention syndrome (GHRS) differentiated by traditional Chinese medicine, and screen the biometric operational taxonomic units (OTUs) to assist the clinical diagnosis. Methods: We recruited children according to the “GHRS diagnostic scale”, collected their oropharyngeal swabs, and sequenced the 16S rDNA V4 region. We described the bacterial structure with alpha-indexes, beta-distances, and relative abundances; moreover, we screened the differential genera/OTUs with Wilcoxon rank-sum test, MetagenomeSeq analysis, and linear discriminant analysis effect size (LEfSe) analysis, in which biometric OTUs were selected to construct the receiver operating characteristic curve to verify the diagnostic value. The bacterial function was predicted with Kyoto Encyclopedia of Genes and Genomes pathways according to 16S rDNA gene by using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States. Results: The study population was composed of 10 children with GHRS and 10 healthy control children. GHRS children were more likely to overeat (gluttony, P = .033). Alpha-indexes, such as Sobs, abundance-based coverage estimator, Bootstrap, and Qstat, were significantly higher in the GHRS group, while beta-distances did not exhibit any significant intergroup differences. There were 9 differently distributed non-predominant genera between the groups in Wilcoxon rank-sum test, as well as 13 non-predominant genera in MetagenomeSeq analysis and 3 non-predominant OTUs in LEfSe analysis. OTU44 and OTU196 were used to construct the receiver operating characteristic curve, and the area under curve was 0.92. Predicted functions showed that pathways related to oxidative phosphorylation and carbon metabolism were enriched in healthy control samples, while the pathway related to renin secretion was remarkably enriched in GHRS samples. Conclusion: Unique oropharyngeal microbial structure and function were identified in GHRS children. OTU44 and OTU196 were specific OTUs, which could be used as biomarkers of GHRS to assist clinical diagnosis.

Objective: This study aimed to explore the structural and functional characteristics of the fecal-associated microbiome (FAM) between the phlegm-dampness constitution (PDC) and balanced constitution (BC), and to screen the related specific operational taxonomic unit (OTU) biomarkers. Methods: This was a cross-sectional study. After strictly identifying the constitution of subjects, their clinical index was recorded and counted. Fecal samples were collected for 16S rDNA sequencing. Alpha diversity, beta diversity, and the relative abundance of dominant bacterial taxa were used to describe the FAM structure, and the Wilcoxon rank-sum test, MetagenomeSeq, and linear discriminant analysis effect size (LEfSe) were used to screen specific bacterial taxa. Specific OTUs were screened to construct receiver operating characteristic (ROC) curves. Results: Thirty-two subjects were enrolled, including 22 subjects with BC and 10 subjects with PDC. There were significant differences in cold preference, levels of aspartate transaminase, β2-microglobulin, and creatine kinase MB, and alpha diversity indices (Shannon and Shannoneven) between the two groups. In principal coordinate analysis by abund-jaccard distance measure and partial least squares discriminant analysis, bacterial communities clustered separately between the two groups. Furthermore, based on MetagenomeSeq, LEfSe, and the Wilcoxon rank-sum test, a total of 43, 18, and 130 OTUs were differentially distributed between BC group and PDC group, respectively, and OTU200, OTU133, and OTU353 were screened when P≤ .01. The area under the ROC curve constructed from the 3 selected OTUs was 0.93. Conclusion: The FAM structure and related functional characteristics of the PDC group differed from those of the BC group. In particular, OTU200, OTU133, and OTU353 can be used as unique markers of PDC to assist clinical diagnosis.

Objective: To investigate whether the specific traditional Chinese medicine (TCM) constitution of individuals can be defined by certain biological indexes instead of answering the questionnaire, and to explore the possibility of discriminating nine TCM constitutions from each other simultaneously using biological indexes. Methods: Blood and urine samples from 152 individuals with nine TCM constitutions were collected, and the related biological indexes were analyzed combining ANOVA, multiple comparison, discriminant analysis, and support vector machine. Results: We found that 4 out of 24 blood routine indexes, 7 out of 10 urine routine indexes, and 12 out of 32 biochemical indexes showed differences among the constitutions. High-sensitivity C-reactive protein, apolipoprotein A1, and alkaline phosphatase were potential candidates for screening out individuals with unbalanced constitutions. Combining uric acid, high-density lipoprotein, apolipoprotein A1, creatine kinase, total protein, aspartate aminotransferase, total bile acid, dehydrogenase, sodium, and calcium levels had the potential to directly distinguish the nine TCM constitutions from each other. Among these indexes, the highest ratio of discriminant analysis between two constitutions was 95.5%, while the lowest was 66.1%. Conclusion: Our results suggest that some biochemical and urine indexes are related to various TCM constitutions, and thus they have the potential to be used for TCM constitution classification.

Botanicals have attracted much attention in the field of anti-inflammatory due to their good pharmacological activity and efficacy. Andrographis paniculata is a natural plant ingredient that is widely used around the world. Andrographolide is the main active ingredient derived from Andrographis paniculata, which has a good effect on the treatment of inflammatory diseases. This article reviews the application, anti-inflammatory mechanism and molecular targets of andrographolide in different inflammatory diseases, including respiratory, digestive, immune, nervous, cardiovascular, skeletal, and tumor system diseases. And describe its toxicity and explain its safety. Studies have shown that andrographolide can be used to treat inflammatory lesions of various systemic diseases. In particular, it acts on many inflammation-related signalling pathways. The future direction of andrographolide research is also introduced, as is the recent research that indicates its potential clinical application as an anti-inflammatory agent.

Abstract Background SAPHO syndrome is a group of symptoms consisting of synovitis, acne, pustulosis, hyperostosis and osteosis. There is no specific laboratory index assist in the diagnosis of SAPHO because of its highly heterogeneous clinical manifestations. Pathogenic microorganisms had been identified in biopsies of some SAPHO cases and particular gene mutations were also linked to the occurrence of SAPHO. It is largely unknown whether intestinal microbiome plays a role in pathogenesis of SAPHO. To explore the intestinal microbiome structure of SAPHO syndrome, fecal samples from 17 SAPHO patients and 14 healthy controls (HC) were collected for 16S rDNA sequencing. Results Our results showed that there was no significant difference in alpha indexes and beta diversity between SAPHO and HC samples, while there were 14 operational taxonomic units (OTUs) in the Wilcoxon rank-sum test and 42 OTUs in the MetagenomeSeq analysis showed significant difference in distribution between the SAPHO and HC groups, 3 of which in Firmicutes were also observed in the random forest analysis and used to construct a receiver operating characteristic curve to evaluate the diagnostic value, the area under the curve was 0.86. Conclusion Fecal-associated microbiome in the SAPHO samples was characterized by the alteration in abundance of some nondominant species, and the 3 selected OTUs in Firmicutes could serve as candidate biomarkers for SAPHO syndrome diagnosis.

Objective: To clarify the structural and functional characteristics of the gut microbiota in individuals with qi stagnation constitution (QSC) and identify the potential biomarkers related to QSC. Methods: This cross-sectional study involved individuals with QSC and balanced constitution (BC) confirmed by TCM clinicians. The clinical features were recorded, and fecal samples were collected for 16S rDNA sequencing. The structure of the fecal-associated microbiome (FAM) was described by the alpha-diversity indexes, beta-distances, and relative abundances of dominant taxa. The differences in FAM distribution were analyzed by the Wilcoxon rank-sum test, MetagenomeSeq, and LEfSe analysis. The 16S rDNA gene sequences were assigned to the KEGG dataset to predict the functional information of bacterial metabolic pathways by using PICRUSt. Differences in functional pathways between groups were assessed with the Wilcoxon rank-sum test. The ROC curve based on specific operational taxonomic units (OTUs) was constructed, and the AUC was calculated. Results: Twenty-two individuals with BC and 8 with QSC were recruited. Significant differences between the two groups were found in body mass index, health status, and low-density lipoprotein, etc. There was no significant difference in the alpha-diversity index. PCoA showed no evident clustering of bacterial communities according to constitutions. Bacteroidaceae, Lachnospiraceae, Ruminococcaceae, and Prevotellaceae were the four common bacteria with high abundances. Notably, MetagenomeSeq, LEfSe analysis, and the Wilcoxon rank-sum test identified significantly different distributions of 66, 42, and 36 OTUs, respectively. Predictive function analysis showed that 13 metabolic pathways were significantly differentially distributed, including those related to fatty acid synthesis. Five specific OTUs were selected as potential biomarkers of a QSC, and the AUC was 0.94. Conclusion: Individuals with QSC have unique FAM structure and related functional characteristics. Five specific OTUs were identified to serve as potentially effective biomarkers related to QSC.

ObjectiveThis study aimed to investigate the diagnostic value and underlying mechanisms of sialic acid-binding Ig-like lectin 9 (SIGLEC9) in gliomas.Patients and MethodsThe Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases were used to analyze the association of SIGLEC9 expression levels with tumor stages and survival probability. Immunohistochemical staining of SIGLEC9 and survival analysis were performed in 177 glioma patients. Furthermore, related mechanisms were discovered about SIGLEC9 in glioma tumorigenesis, and we reveal how SIGLEC9 functions in macrophages through single-cell analysis.ResultsTCGA and CGGA databases indicated that patients with high SIGLEC9 expression manifested a significantly shorter survival probability than those with low SIGLEC9 expression. SIGLEC9 was upregulated significantly in malignant pathological types, such as grade III, grade IV, mesenchymal subtype, and isocitrate dehydrogenase wild-type gliomas. The immunohistochemical staining of tissue sections from 177 glioma patients showed that high-SIGLEC9-expression patients manifested a significantly shorter survival probability than low-SIGLEC9-expression patients with age ≧60 years, grade IV, glioblastoma multiforme, alpha thalassemia/intellectual disability syndrome X-linked loss, and without radiotherapy or chemotherapy. Furthermore, the SIGLEC9 expression level was positively correlated with myeloid-derived suppressor cell infiltration and neutrophil activation. The SIGLEC9 expression was also positively correlated with major immune checkpoints, such as LAIR1, HAVCR2, CD86, and LGALS9. Through single-cell analysis, we found that the SIGLEC9 gene is related to the ability of macrophages to process antigens and the proliferation of macrophages.ConclusionThese findings suggested that SIGLEC9 is a diagnostic marker of poor outcomes in glioma and might serve as a potential immunotherapy target for glioma patients in the future.

Objective: To search for specific metabolites in the lungs of pneumonia rats fed with a high-calorie diet, as well as explore the changes in the lung metabolites of young rats treated with Yinlai Decoction (YD) and its effects on inflammation-related metabolic pathways. Methods: Lipopolysaccharides (LPS) and a special high-calorie diet were used to induce Sprague Dawley (SD) rats to simulate the intestinal state of infant pneumonia. Liquid chromatography-mass spectrometry technology (LC-MS/MS) was used to detect metabolites in each group. Supervised orthogonal partial least squares discriminant analysis (OPLS-DA) model values were used for the detection results to find the differential metabolites. The metabolic pathways that are involved with the differential metabolites were clarified through enrichment analysis and topological analysis. Finally, the T cell receptor signaling pathway (TCR) signal conversion was analyzed by the network pharmacology method. Results: In the high-calorie diet combined with pneumonia group (M3), a total of 55 metabolites were determined to be different from the normal group (N). A total of 36 metabolites were determined to be different from those in the lung metabolites of the YD treatment group (T1). YD had a regulatory effect on glutathione metabolism, arginine and proline metabolism, ascorbic acid and aldehyde metabolism and phenylalanine metabolism. And the small molecule metabolites could act on the FYN and lymphocyte-specific protein tyrosine kinase (LCK) target proteins in the TCR signaling pathway, thereby affecting the immune function of the lungs. Conclusion: A high-calorie diet can cause abnormal sphingolipid metabolism in the lungs of young rats, thereby creating chronic lung inflammation in young rats. YD has a beneficial effect when used to treat young rats with LPS-induced pneumonia fed on high-calorie diets. Its mechanisms of action may affect the body’s immune pathways by regulating the oxidative stress pathway affected by glutathione metabolism.

Objective: To explore the structural and functional characteristics of the fecal-associated microbiome (FAM) in a traditional Chinese medicine (TCM) qi-deficiency constitution (QDC) by comparing with balanced constitution (BC) and screen the related biomarkers. Methods: In this cross-sectional study, the TCM constitutions of subjects were determined based on published the Classification and Determination of constitution in TCM and further confirmed by a TCM clinician. Clinical characteristics were recorded, and fecal samples were collected for 16S rDNA sequencing using the Illumina Miseq platform. The FAM structure was described using alpha-diversity indexes, beta-diversity indexes, and the relative abundances of the dominant taxa. Differences in the FAM distribution and function were analyzed with a Wilcoxon rank-sum test, MetagenomeSeq, and LEfSe analysis, after which a receiver operating characteristic curve based on the specific operational taxonomic units (OTUs) was constructed to calculate the area under the curve. Results: Our study population was composed of 22 BCs and 9 QDCs. There were no significant differences between the two groups in the distribution of clinical characteristics or alpha-diversity indexes, except for the sweets preference and blood glucose level. In principal coordinate analysis and partial least squares discriminant analysis, the bacterial communities in the BC group samples and QDC group samples clustered separately. Notably, there were 214 OTUs significantly distributed between groups in the MetagenomeSeq analysis, 200 OTUs identified by the Wilcoxon rank-sum test, and 6 OTUs found by the LEfSe analysis. Predicted function analysis revealed that six metabolic pathways were distinctly distributed between the two groups. The area under the curve for the receiver operating characteristic curve based on the four specific OTUs was 0.88. Conclusion: Unique FAM structural and related functional characteristics are displayed in individuals with a QDC, and four specific OTUs could be used as QDC biomarkers to assist in clinical diagnosis.

Objective: To examine the effects of accumulated heat in GI tract (AHGIT) on lung tissue protein expression in pneumonic mice. Methods: Nebulized lipopolysaccharides (LPS) were administered to induce a pneumonic mouse model (M1), and a high-calorie/protein diet combined with nebulized LPS was used to induce AHGIT pneumonia (M2). Isobaric tag for relative and absolute quantitation (iTRAQ) proteomics was applied to study lung protein expression, followed by bioinformatics analysis. Results: M1 mice developed alveolar damage with prominent septum thickening, vascular dilation, hyperaemia and infiltration of large amounts of inflammatory cells. M2 mice developed more severe pathological responses. A total of 2626 proteins were reliably identified in the lung tissue. Compared with normal mice, the M1 mice had 344 differentially expressed proteins in their lungs, which are involved in the following biological processes: response to organic substance, response to cytokine, response to external stimulus, defense response and immune system process. They are also involved in the following Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways: ECM-receptor interaction, leukocyte transendothelial migration, Fc gamma R-mediated phagocytosis, complement and coagulation cascades, and antigen processing and presentation. Compared with the M1 group, the M2 mice had 164 differentially expressed proteins in their lungs, including 14 upregulated and 150 downregulated proteins. These proteins are involved in the following biological processes: small molecule metabolism, ribose phosphate metabolic process, cell adhesion and biological adhesion. The relevant KEGG pathways included oxidative phosphorylation, Citrate cycle (TCA cycle), complement and coagulation cascades, and vascular smooth muscle contraction. Conclusions: AHGIT aggravated the lung inflammatory damage in the mice with LPS-induced pneumonia. It may affect the mouse substance/energy metabolism, and therefore the immune function, to aggravate the LPS-induced inflammatory damage.

Abstract The global spread of Severe Acute Respiratory Syndrome Coronavirus 2. (SARS-CoV-2) and its variant strains, including Alpha, Beta, Gamma, Delta, and now Omicron, pose a significant challenge. With the constant evolution of the virus, Omicron and its subtypes BA.1, BA.2, BA.3, BA.4, and BA.5 have developed the capacity to evade neutralization induced by previous vaccination or infection. This evasion highlights the urgency in discovering new monoclonal antibodies (mAbs) with neutralizing activity, especially broadly neutralizing antibodies (bnAbs), to combat the virus.In the current study, we introduced a fully human neutralizing mAb, CR9, that targets Omicron variants. We demonstrated the mAb’s effectiveness in inhibiting Omicron replication both in vitro and in vivo. Structural analysis using cryo-electron microscopy (cryo-EM) revealed that CR9 binds to an epitope formed by RBD residues, providing a molecular understanding of its neutralization mechanism. Given its potency and specificity, CR9 holds promise as a potential adjunct therapy for treating Omicron infections. Our findings highlight the importance of continuous mAb discovery and characterization in addressing the evolving threat of COVID-19.

Abstract Surface damage detection in concrete structures is critical for maintaining structural integrity, yet current object detection algorithms often struggle in low-light environments. To address this challenge, this study proposed a methodology that integrates image enhancement and object detection networks to improve damage identification in such conditions. Specifically, we employ the self-calibrated illumination (SCI) model to reconstruct low-light images, which are then processed by an improved YOLOv5-based network, YOLOv5-GAM-ASFF, incorporating a global attention mechanism (GAM) and adaptive spatial feature fusion (ASFF). The performance of YOLOv5-GAM-ASFF is evaluated on a dataset of concrete structure damage images, demonstrating its superiority over YOLOv5s, YOLOv6s, and YOLOv7-tiny. The results show that YOLOv5-GAM-ASFF achieves a mAP@0.5 of 79.1%, surpassing the other models by 1.3%, 3.3%, and 5.8%, respectively. This approach provides a reliable solution for surface damage detection in low-light environments, advancing the field of structural health monitoring by improving detection accuracy under challenging conditions.

Abstract Microglial activation-mediated neuroinflammation is a major contributor to neuronal damage after cerebral ischemia. The Fractalkine (FKN)/CX3C chemokine receptor 1 (CX3CR1) axis plays a critical role in regulating microglial activation and neuroinflammation. The aim of this study is to ascertain the role and mechanism of FKN/CX3CR1 axis in hypoxic postconditioning (HPC)-induced anti-inflammatory and neuroprotective effects on transient global cerebral ischemia (tGCI). We found that HPC suppressed microglial activation and alleviated neuroinflammation in hippocampal CA1 after tGCI. Meanwhile, HPC upregulated the expression of FKN and CX3CR1 in neurons, but it downregulated the expression of CX3CR1 in glial cells after tGCI. In addition, the overexpression of FKN induced by the administration of FKN-carried lentivirus reduced microglial activation and inhibited neuroinflammation in CA1 after tGCI. Furthermore, silencing CX3CR1 with CX3CRi-carried lentivirus in CA1 after tGCI suppressed microglial activation and neuroinflammation and exerted neuroprotective effects. Finally, the overexpression of FKN caused a marked increase of neuronal CX3CR1 receptors, upregulated the phosphorylation of Akt, and reduced neuronal loss of rats in CA1 after tGCI. These findings demonstrated that HPC protected against neuronal damage in CA1 of tGCI rats through inhibiting microglial activation and activating Akt signaling pathway via FKN/CX3CR1 axis.

In aquaculture, the presence of dead fish on the water surface can serve as a bioindicator of health issues or environmental stressors. To enhance the precision of detecting dead fish floating on the water’s surface, this paper proposes a detection approach that integrates data-driven insights with advanced modeling techniques. Firstly, to reduce the influence of aquatic disturbances and branches during the identification process, prior information, such as branches and ripples, is annotated in the dataset to guide the model to better learn the scale and shape characteristics of dead fish, reduce the interference of branch ripples on detection, and thus improve the accuracy of target identification. Secondly, leveraging the foundational YOLOv8 architecture, a DD-IYOLOv8 (Data-Driven Improved YOLOv8) dead fish detection model is designed. Considering the significant changes in the scale of dead fish at different distances, DySnakeConv (Dynamic Snake Convolution) is introduced into the neck network detection head to adaptively adjust the receptive field, thereby improving the network’s capability to capture features. Additionally, a layer for detecting minor objects has been added, and the detection head of YOLOv8 has been modified to 4, allowing the network to better focus on small targets and occluded dead fish, which improves detection performance. Furthermore, the model incorporates a HAM (Hybrid Attention Mechanism) in the later stages of the backbone network to refine global feature extraction, sharpening the model’s focus on dead fish targets and further enhancing detection accuracy. The experimental results showed that the accuracy of DD-IYOLOv8 in detecting dead fish reached 92.8%, the recall rate reached 89.4%, the AP reached 91.7%, and the F1 value reached 91.0%. This study can achieve precise identification of dead fish, which will help promote the research of automatic pond patrol machine ships.

The use of mobile robots in substations improves maintenance efficiency and ensures the personal safety of staff working at substations, which is a trend in the development of technologies. Strong electric and solid magnetic fields around high-voltage equipment in substations may lead to the breakdown and failure of inspection devices. Therefore, safe operation range measurement and coordinated planning are key factors in ensuring the safe operation of substations. This paper first summarizes the current developments that are occurring in the field of fixed and mobile safe operating range sensing methods for substations, such as ultra-wideband technology, the two-way time flight method, and deep learning image processing algorithms. Secondly, this paper introduces path-planning algorithms based on safety range sensing and analyzes the adaptability of global search methods based on a priori information, local planning algorithms, and sensor information in substation scenarios. Finally, in view of the limitations of the existing range awareness and path-planning methods, we investigate the problems that occur in the dynamic changes in equipment safety zones and the frequent switching of operation scenarios in substations. Furthermore, we explore a new type of barrier and its automatic arrangement system to improve the performance of distance control and path planning in substation scenarios.

Background: Chronic kidney disease (CKD) is now globally recognized as a critical public health concern. Vascular calcification (VC) represents a significant risk factor for cardiovascular events in individuals with CKD. It is the accessible and precise diagnostic biomarkers for monitoring the progression of CKD and the concurrent VC are urgently needed.Methods: The adenine diet-induced CKD rat model was utilized to investigate chronic kidney injury, calcification in the kidney and thoracic aorta, and dysregulation of biochemical indices. Enzyme-linked immune sandwich assays were employed to analyze changes in calcification-related proteins. 16S rRNA sequencing was performed to delineate the microbiota characteristics in the gut and blood of CKD-afflicted rats. Additionally, transcriptome sequencing of kidney tissue was conducted to explore the relationship between CKD-associated microbiota features and alterations in kidney function.Results: The adenine diet-induced CKD inhibited body weight gain, and led to kidney injury, and pronounced calcification in kidney and thoracic aorta. The microbiota both in the gut and blood of these affected rats exhibited significantly lower alpha diversity and distinctive beta diversity than those in their healthy counterparts. CKD resulted in dysregulation of several biochemical indices (including elevated levels of creatinine, low-density lipoprotein-cholesterol, sodium, phosphorous, total cholesterol, and urea and decreased levels of albumin, calcium, lactate dehydrogenase, and total bilirubin). Moreover, it upregulated calcification-related factors (bone sialoprotein [BSP], Klotho, fibroblast growth factor [FGF]-23, and sclerostin [SOST]) and lipopolysaccharide (LPS). Notably, the increased Acinetobacter in the blood was positively associated with calcifications in the kidney and thoracic aorta, in addition to the positive correlation with gut microbiota. The enrichment of Acinetobacter was concurrent with increases in calcification factors (BSP, FGF-23, and SOST), LPS, and phosphorous. Furthermore, transcriptome sequencing revealed that the enrichment of Acinetobacter was positively correlated with the majority of upregulated genes and negatively correlated with downregulated genes involved in the mineral absorption pathway.Conclusion: Our findings, for the first time, underscore that dysbiosis of symbiotic microbiota, both in the gut and blood, is involved in the progression of CKD. Particularly, the enrichment of Acinetobacter in blood emerges as a potential risk factor for CKD and its accompanying VC.

Metabolic syndrome (MetS) has a high prevalence and is prone to many complications. However, current MetS diagnostic methods require blood tests that are not conducive to self-testing, so a user-friendly and accurate method for predicting MetS is needed to facilitate early detection and treatment. In this study, a MetS prediction model based on a simple, small number of Traditional Chinese Medicine (TCM) clinical indicators and biological indicators combined with machine learning algorithms is investigated. Electronic medical record data from 2040 patients who visited outpatient clinics at Guangdong Chinese medicine hospitals from 2020 to 2021 were used to investigate the fusion of Bayesian optimization (BO) and eXtreme gradient boosting (XGBoost) in order to create a BO-XGBoost model for screening nineteen key features in three categories: individual bio-information, TCM indicators, and TCM habits that influence MetS prediction. Subsequently, the predictive diagnostic model for MetS was developed. The experimental results revealed that the model proposed in this paper achieved values of 93.35 %, 90.67 %, 80.40 %, and 0.920 for the F1, sensitivity, FRS, and AUC metrics, respectively. These values outperformed those of the seven other tested machine learning models. Finally, this study developed an intelligent prediction application for MetS based on the proposed model, which can be utilized by ordinary users to perform self-diagnosis through a web-based questionnaire, thereby accomplishing the objective of early detection and intervention for MetS.

Tongue diagnosis holds significant importance in Traditional Chinese Medicine (TCM), with cracked tongues serving as a key diagnostic feature. However, the considerable variability in the morphology, depth, and distribution of tongue cracks poses a challenge for accurate extraction. In this paper, a novel deep learning approach is proposed to enhance the decoder of the U-Net model for cracked tongue extraction by incorporating the Hybrid Parallel Attention Mechanism (HPAM). The inclusion of HPAM enables the model to better concentrate on the small-scale feature information of tongue cracks, thereby improving the accuracy of crack segmentation. Experimental results demonstrate the effectiveness of the proposed method across all three tongue crack datasets. The method achieves a MIoU of 69.31% on the open environment dataset, 76.05% MIoU on the non-open environment dataset, and an overall MIoU of 76.92% on the combined dataset. These results signify a significant improvement over existing methods. This study not only offers an effective approach for automating the extraction of cracked tongues but also contributes to the automation and accuracy of tongue diagnosis, thereby benefiting the field of TCM.

Abstract Purpose We aimed to evaluate the performance of Chinese visceral adiposity index (CVAI), visceral adiposity index (VAI), lipid accumulation product (LAP), triglyceride glucose (TyG) as indices in screening abnormal glucose tolerance (AGT) in Chinese women with polycystic ovary syndrome (PCOS), using the oral glucose tolerance test (OGTT) as a reference test. In addition, we essentially compared the abilities of these indices with body mass index (BMI), waist circumference (WC), fasting plasma glucose (FPG). Materials and methods All 1113 PCOS patients evaluated in this study underwent OGTTs. The 2-h post-oral glucose load (2 h-PG) level was used to categorize subjects into two groups: those having AGT or normal glucose tolerance (NGT) levels. Results A statistically significant positive correlation between levels of 2 h-PG and FPG, BMI, WC, LAP, VAI, CVAI, TyG, (P

ING1 is a chromatin targeting subunit of the Sin3a histone deacetylase (HDAC) complex that alters chromatin structure to subsequently regulate gene expression. We find that ING1 knockdown increases expression of Twist1, Zeb 1&2, Snai1, Bmi1 and TSHZ1 drivers of EMT, promoting EMT and cell motility. ING1 expression had the opposite effect, promoting epithelial cell morphology and inhibiting basal and TGF-β-induced motility in 3D organoid cultures. ING1 binds the Twist1 promoter and Twist1 was largely responsible for the ability of ING1 to reduce cell migration. Consistent with ING1 inhibiting Twist1 expression in vivo, an inverse relationship between ING1 and Twist1 levels was seen in breast cancer samples from The Cancer Genome Atlas (TCGA). The HDAC inhibitor vorinostat is approved for treatment of multiple myeloma and cutaneous T cell lymphoma and is in clinical trials for solid tumours as adjuvant therapy. One molecular target of vorinostat is INhibitor of Growth 2 (ING2), that together with ING1 serve as targeting subunits of the Sin3a HDAC complex. Treatment with sublethal (LD25-LD50) levels of vorinostat promoted breast cancer cell migration several-fold, which increased further upon ING1 knockout. These observations indicate that correct targeting of the Sin3a HDAC complex, and HDAC activity in general decreases luminal and basal breast cancer cell motility, suggesting that use of HDAC inhibitors as adjuvant therapies in breast cancers that are prone to metastasize may not be optimal and requires further investigation.

A longer pulse, lower adiabat drive in a low gas-fill hohlraum is an inertial confinement fusion design with potential higher gain, but has challenges such as the less tamped wall plasma. Thus, it is necessary to alter the laser spot regions to control low-mode drive asymmetry when using such laser pulses. The hollow wall is designed [Vandenboomgaerde et al 2018 Phys. Plasmas 25 012713] and has been demonstrated with experiments to be effective in holding back the gold bubble expansion [Depierreux et al 2020 Phys. Rev. Lett . 125 255 002]. This paper presents experimental and simulation results demonstrating that hollow wall hohlraums effectively reduce laser spot motion. Experiment results indicate that the laser spot position in hollow wall hohlraum moves less than that in classical solid hohlraum, similar data are obtained by 2D simulation. This reduction in motion is beneficial for improving P4 drive asymmetry.

This study proposes Combining Attention and Brightness Adjustment Network (CABA-Net), a deep learning network for underwater image restoration, to address the issues of underwater image color-cast, low brightness, and low contrast. The proposed approach achieves a multi-branch ambient light estimation by extracting the features of different levels of underwater images to achieve accurate estimates of the ambient light. Additionally, an encoder-decoder transmission map estimation module is designed to combine spatial attention structures that can extract the different layers of underwater images’ spatial features to achieve accurate transmission map estimates. Then, the transmission map and precisely predicted ambient light were included in the underwater image formation model to achieve a preliminary restoration of underwater images. HSV brightness adjustment was conducted by combining the channel and spatial attention to the initial underwater image to complete the final underwater image restoration. Experimental results on the Underwater Image Enhancement Benchmark (UIEB) and Real-world Underwater Image Enhancement (RUIE) datasets show excellent performance of the proposed method in subjective comparisons and objective assessments. Furthermore, several ablation studies are conducted to understand the effect of each network component and prove the effectiveness of the suggested approach.

In practical usage, QR codes often become difficult to recognize due to damage. Traditional restoration methods exhibit a limited effectiveness for severely damaged or densely encoded QR codes, are time-consuming, and have limitations in addressing extensive information loss. To tackle these challenges, we propose a two-stage restoration model named the EHFP-GAN, comprising an edge restoration module and a QR code reconstruction module. The edge restoration module guides subsequent restoration by repairing the edge images, resulting in finer edge details. The hierarchical feature pyramid within the QR code reconstruction module enhances the model’s global image perception. Using our custom dataset, we compare the EHFP-GAN against several mainstream image processing models. The results demonstrate the exceptional restoration performance of the EHFP-GAN model. Specifically, across various levels of contamination, the EHFP-GAN achieves significant improvements in the recognition rate and image quality metrics, surpassing the comparative models. For instance, under mild contamination, the EHFP-GAN achieves a recognition rate of 95.35%, while under a random contamination, it reaches 31.94%, both outperforming the comparative models. In conclusion, the EHFP-GAN model demonstrates remarkable efficacy in the restoration of damaged QR codes.

Deep-sea pressure vessels are specialized pressure vessels designed for automatic deployment from underwater to the surface. These vessels find extensive applications in underwater life-saving and transportation. Their interiors are furnished with a pair of sealing rings, one of which is lip-shaped, and the other is a convex shape, to ensure a dependable seal. With increasing water depth, the sealing rings experience augmented pressure, resulting in a gradual pressing of the rings into the sealing groove. Using ANSYS workbench finite element software, a two-dimensional axisymmetric lip seal finite element model using forces for overall constraint was established, the complete process of progressive pressing into the sealing groove was simulated, and the deformation, contact stress, maximum shear stress, and von Mises stress distribution was also simulated. We also conducted a comparative analysis of lip seals under low and high-water pressure sealing conditions. The findings of the study indicate that when subjected to a combined effect of the installation pre-tightening force and the working water pressure, the lip seal experiences complete compression into the sealing groove at a specific water depth. When subjected to the simultaneous influence of water pressure on the sealing ring material and friction force on the contact surface, two extremes of contact stress manifest in the primary sealing zone of the lip seal. These extremes have the capacity to elevate the contact stress and the effective sealing width, ultimately leading to an improvement in the sealing performance. Concurrently, as the water pressure gradually increases, the inner concave circle of the sealing ring experiences stretching, leading to a reduction in stress concentration, equivalent stress, and shear stress to a considerable extent. This mechanism ensures that the lip-shaped sealing ring retains sufficient strength. This study offers a viable solution for conducting sealing studies on deep-sea separable pressure vessels.

In this paper, we study how and when competing firms cooperate horizontally to manage supply disruption risks. Specifically, we consider a system consisting of two competing retailers that sell the same product in a market where the price depends on the total quantity of products on hand. Each retailer has its own supply disruption probability. In terms of complete information, we show that they should cooperate to manage supply disruption risk and design a cooperation mechanism using cooperative bargaining. Furthermore we study the cooperation problem in the case of private information. We model the problem as a dynamic bargaining model in which the informed retailer’s supply disruptions are either high or low. In the dynamic negotiation process, the informed retailer can signal information through their offers. With the uninformed retailer’s acceptance criteria, we characterize the perfect Bayesian equilibrium of the bargaining game. We show that the uninformed retailer may reach an agreement with either the high type or the low type first, or with both simultaneously. We find that retailer’s surplus with private information may be higher than that with complete information.

Understanding the grassland ecosystem is crucial for improving grassland ecosystem functions and services such as climate regulation, water and soil conservation, carbon sequestration, and biodiversity and gene pool maintenance. However, a systematic and comprehensive review of the relevant literature is still unclear and lacking. The VOSviewer software and cluster analysis were used to visually analyze and perform dimension reduction classification on the 27,778 studies related to grassland ecosystem research based on the Web of Science database. The number of publications targeting grassland ecosystem increased rapidly from 2006 to 2021. Ecology, agronomy, and environmental science were the most popular research categories, and the top journal sources were Remote Sensing, Journal of Ecology, and Ecology and Evolution. The leading publishing countries were the United States, China, and Germany. The top three institutions were the Chinese Academy of Sciences, the University of Chinese Academy of Sciences, and Colorado State University. Cooperation between different countries and institutions had increased. Keyword co-occurrence network analysis showed that Biodiversity, Vegetation and Conservation were the most popular study areas, grassland management, climate change, land use pattern, and ecosystem impact were the hot research topics. All studies could be divided into three categories by cluster analysis: grassland ecological characteristics including basic physicochemical properties, vegetation community characteristics, aboveground and belowground biomass, and soil structural quality of grassland; driving mechanisms that demonstrated effects of human activities and climate change on grassland ecosystem function; and grassland ecosystem services that focused the influences of different grassland management strategies on ecological services, animal welfare and human well-being. The three topic categories of reviewed studies were interrelated and consistent with each other, and the performances were progressive. This paper reviewed the trend evolution through keyword hotspots and analyzed the future research directions to provide an important reference for scientists to better respond to the balance of herbage and sustainable utilization of grassland and maintenance of ecological security.

Determining the homogeneity of material mixing in real time during product processing is critical for quality control. According to the Kubelka–Munk (K-M) function of diffuse reflectance absorption spectrum, absorbance (A) is approximately linear with the content of the components when the sample scattering coefficient (S) is in a certain range. The S is determined by the particle size of powder samples. Therefore, this study determined particle size ranges that satisfy linear additivity in near-infrared diffuse reflectance spectroscopy (NIRDRS). Thus, the proposed NIRDRS analysis technique can be used to determine the homogeneity of material mixes or analyze the percentages of the components in the mixture. In this study, vitamin B3 and vitamin C were used for preparing mixed samples with varying percentages. The experimental results revealed that linear additivity is satisfied when the powder particle size is in the range of less than 280, 280–450, and 450–900 μm. When the confidence level is 0.01, the actual mixed spectra are not significantly different from the “simulated mixed spectra” constructed by linear addition, with their relative deviations less than 1.08%. The absolute errors of the actual and analytic percentages were within 2.98% for each component in the mixtures. The above conclusions also hold for sorghum, which has a complex material composition. Statistical models cannot analyze the percentages of components in the mixture. In contrast, linear addition and direct calibration approach avoids the use of a large number of samples for statistical modeling and analyze the percentages of mixed samples. Meanwhile, it can be used to discriminate and analyze the material mixing uniformity by building a mechanistic model.

A predetermined quanta-to-energy ratio is often used in many ecosystem models to transform photosynthetically radiant flux density into photosynthetic photon flux density when light penetrates seawater. The calculation formula of the ratio is reduced in this study as the product of a constant and the defined principal wavelength. The principal wavelength is discussed in this paper and may be expressed as an exponential function using theoretical reasoning. The deviation of the principal wavelength is defined as the difference between two natural logarithms of the observed principal wavelength in real seawater and the simulated principal wavelengths of pure seawater under the same surface solar radiation. The deviation has a quasi-linear relationship with the non-water diffuse attenuation coefficient at 490 nm, which is related to the chlorophyll-a concentration. A semi-empirical formula between the deviation and chlorophyll-a concentration is established with a determination coefficient of more than 84%. In pure seawater, an empirical formula for the principal wavelength profile is also constructed. The parameterization formula for the quanta-to-energy ratio is provided as a function of the chlorophyll-a concentration and the surface principal wavelength. When applied to in situ observations, the statistical relative inaccuracy is found to be less than 10%. The parameterization formula can be applied to the ecosystem models to realize the transformation between photos and energy in the PAR waveband.

Background: Recurrent respiratory tract infections (RRTIs) have a negative impact on both children's health and family wellbeing. Deficiency of ZhengQi used to be an instinct factor driving RRTI in Traditional Chinese Medicine (TCM). Our clinical observations suggest that children with gastrointestinal heat retention syndrome (GHRS) may have a greater risk of catching respiratory tract infections (RTIs). GHRS is a new predisposing factor for RRTI and it is dietary related. This study is aimed to explore association between GHRS and RRTI. Methods: A prospective cohort study has been conducted in Beijing, China; children aged 1-18 were enrolled. TCM symptoms, demographic and physiological characteristics were recorded by using semi-structured questionnaire. GHRS was considered as a predisposing factor. Children were followed up for next 12 months. We contacted with their parents using a face-to-face questionnaire survey, via email or phone every 3 months. Episodes of RTIs were recorded in detail. Results: Three hundred thirty four children were enrolled and 307 (91.92 %) followed up for 12 months. The incidence of RTI was 4.32 episodes per child-year (95 % CI 4.03-4.61). 69 (43.13 %) children in the group with GHRS suffered from RRTI; there were 48 (32.65 %) children in group without GHRS. The risk ratio (RR) value of RRTI occurrence was 1.32 (95 % CI 0.91-1.91, P = 0.139), and the attributable risk percent (AR%) was 24.28 %. Dry stool and irritability were positively correlated with RTI episodes, age and BMI were negatively correlated with RTI episodes in a linear regression model. Dry stool (OR = 1.510) was positively correlated with RRTI occurrence, age (OR = 0.889) and BMI (OR = 0.858) were negatively correlated with RRTI occurrence in our logistic regression model. Conclusions: GHRS is associated with RRTI in this cohort. Dry stool was positively associated with RRTI, and BMI was negatively associated with RRTI. Studies with larger sample size and longer follow up are needed to further evaluate this association. Relieving GHRS should be considered when TCM practitioners treat RRTI children, and this may protect children from suffering RTIs. Trial registration: Chinese Clinical Trial Registry Number: ChiCTR-CCH-13003756 [ABSTRACT FROM AUTHOR]

The x-ray emissivity of gadolinium (Gd) and gold (Au) has been studied using the FLYCHK code. The results show that the Gd M-band is lower than 2 keV and that Gd has a higher x-ray emissivity at low temperature. Thus, we proposed a Gd + Au + Gd sandwich design to improve the x-ray conversion efficiency (CE). Under a laser intensity of 1 × 1015 W/cm2, a 11%–17% enhancement of the CE and an optimized x-ray spectrum were achieved in one-dimensional simulation. The enhancement of the CE is mainly due to an enhancement of the soft x-ray flux (0 keV–2 keV). In addition, the high energy x-ray flux (2 keV–5 keV) is lower than that of Au. Particularly at an early stage, the laser ablates the Gd layer, and the temperature of the Au layer is insufficient for producing an M-band emission. Thus, the high energy x-ray flux is rather low. A sandwich design not only takes advantage of the higher x-ray emissivity of Gd under specific conditions in an efficient manner but also simplifies the target fabrication, which is important. In addition, Gd can also be used to optimize the future design of depleted uranium Hohlraum.