ObjectiveTo investigate the mechanism by which Gegen Qinliantang（GQT） improves skeletal muscle insulin resistance. MethodsThe db/m mice were used as the normal group， while db/db mice were assigned to a model group， low-dose （3.12 g·kg^-1）， medium-dose （6.24 g·kg^-1）， and high-dose （12.48 g·kg^-1） GQT groups， and a Western medicine group （semaglutide， 0.045 mg·kg^-1），n=6 in each group. All groups received corresponding interventions. Intraperitoneal glucose tolerance test （IPGTT）， intraperitoneal insulin tolerance test （IPITT）， and hematoxylin-eosin （HE） staining were used to evaluate insulin resistance and therapeutic efficacy. Serum lipid levels were measured using an automatic biochemical analyzer， and apoptosis in skeletal muscle was assessed via TUNEL assay. Transcriptome sequencing combined with gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses was performed to identify differentially expressed genes （DEGs）. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to validate gene expression. Molecular docking was applied to evaluate the binding patterns between active components of GQT and key regulatory genes to elucidate pharmacological mechanisms. ResultsCompared with the model group， the medium-dose and high-dose GQT groups showed significantly reduced fasting blood glucose （FBG） levels （P<0.01）. Triglycerides （TG）， total cholesterol （TC）， and low-density lipoprotein cholesterol （LDL-C） were markedly decreased （P<0.01）， while high-density lipoprotein cholesterol （HDL-C） was significantly increased （P<0.01）. IPGTT， IPITT， and HE staining demonstrated that GQT enhanced insulin sensitivity and restored skeletal muscle morphology. GQT also alleviated apoptosis in skeletal muscle tissue. Transcriptome analysis revealed that GQT primarily affected biological processes such as oxidative phosphorylation， metabolic pathways， cellular processes， and protein binding. Real-time PCR results showed that CBR2， CDK6， F830016B08Rik， IL-1β， Rab27b， and COLEC12 were key regulatory genes. Molecular docking demonstrated that CBR2， IL-1β， Rab27b， and COLEC12 formed stable binding with the main active components of GQT. The therapeutic effects of high- and medium-dose GQT were comparable to those of the semaglutide group. ConclusionGQT improves skeletal muscle insulin resistance， potentially by regulating apoptosis as part of its underlying biological mechanism.

ObjectiveTo explore the clinical application value of CIE 1976 L*a*b*（Lab） color space in the differential diagnosis of early esophageal cancer and non-cancerous lesions. MethodsWe selected the endoscopic images of patients with esophageal lesions confirmed by pathology who underwent white light imaging endoscopy （WLI） and narrow band imaging endoscopy （NBI）. Five regions of interest （ROI） were selected respectively from the mucosa of the lesion area and the mucosa of the surrounding normal area for labeling. The Lab color space parameters were extracted and counted， and the color difference values（ΔE*）were calculated. ResultsA total of 213 eligible patients were included for analysis in the study. In WLI and NBI modes， there were differences in mucosal color between the early esophageal cancer group and the non-cancer group （P<0.05）. Compared with WLI mode， NBI mode could significantly increase the color difference between early esophageal cancer and non-cancerous lesions （P<0.05）. The lightness component value （L* value） of the early esophageal cancer lesion area was lower than that of the non-cancerous lesion area， and this color difference was more significant in the NBI mode （P<0.05）. In WLI mode， there was no significant difference in yellow-blue component value （b* value） between the mucosa of early esophageal cancer and non-cancerous lesions. However， in the NBI mode， the b* value of the mucosa in the non-cancerous lesion area was higher than that in the early esophageal cancer lesion area （P<0.05）. On the red-green axis， the mucosa of the early esophageal cancer and non-cancerous lesions was red in WLI mode and green in NBI mode. There was no significant difference in red-green component value （a* value） between the two groups. ConclusionThere are color differences between early esophageal cancer and non-cancerous lesions under WLI and NBI. The color of early esophageal cancer is darker under WLI， and the color of non-cancerous lesions is yellower under non-magnified NBI mode. Lab color space is helpful to identify early esophageal cancer and non-cancerous lesions.

Diabetic cardiomyopathy （DCM）， a cardiovascular complication caused by diabetes mellitus， is a major cause of heart failure and even sudden cardiac death in diabetic patients. Traditional Chinese medicine （TCM） posits that the core pathogenesis of DCM lies in internal deficiency and superficial excess， characterized by deficiency of both Qi and Yin combined with phlegm and blood stasis. Modern medical treatments for DCM primarily focus on blood glucose control and symptom alleviation yet lack targeted therapeutic strategies. In contrast， TCM offers a wealth of practical experience and a complete theoretical system， demonstrating definite clinical efficacy and high medication safety in DCM management. As a classic formula for tonifying Qi and nourishing Yin， Shengmaisan comprises Ginseng Radix et Rhizoma， Ophiopogonis Radix， and Schisandrae Chinensis Fructus. It contains multiple bioactive components， including ginsenosides， ophiopogonin， schisandrins， and homoisoflavonoids， which exhibit cardioprotective properties. The therapeutic mechanisms of Shengmaisan-like formulae for DCM involve enhancing myocardial contractility， attenuating myocardial fibrosis， modulating mitochondrial quality control， regulating glucose metabolism， mitigating oxidative stress， and suppressing inflammatory responses. Clinically， Shengmaisan-like formulae not only manage hyperglycemic status but also ameliorate cardiac structural and functional impairments and enhance exercise tolerance in DCM patients， playing a vital role in the prevention， treatment， and rehabilitation of DCM. This paper analyzes the feasibility of Shengmaisan-like formulae in DCM management and synthesizes current research achievements regarding their chemical components， mechanisms of action， and clinical applications， aiming to provide a scientific foundation for the use of such formulae in the treatment of DCM.

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical burden and standardize the healthcare. In this study, the CDSS was built under a hierarchical-label interpretable classification framework, trained by a state-of-the-art transformer-based model, and validated in a multi-center style. METHODS: We conducted stratified sampling on a previously established dataset containing 302,965 electronic colonoscopy reports with pathology, identified 2041 patients' records representative of overall features, and randomly divided into the training and testing sets (7:3). A total of five main labels and 22 sublabels were applied to annotate each record on a network platform, and the data were trained respectively by three pre-training models on Chinese corpus website, including bidirectional encoder representations from transformers (BERT)-base-Chinese (BC), the BERT-wwm-ext-Chinese (BWEC), and ernie-3.0-base-zh (E3BZ). The performance of trained models was subsequently compared with a randomly initialized model, and the preferred model was selected. Model fine-tuning was applied to further enhance the capacity. The system was validated in five other hospitals with 3177 consecutive colonoscopy cases. RESULTS: The E3BZ pre-trained model exhibited the best performance, with a 90.18% accuracy and a 69.14% Macro-F1 score overall. The model achieved 100% accuracy in identifying cancer cases and 99.16% for normal cases. In external validation, the model exhibited favorable consistency and good performance among five hospitals. CONCLUSIONS The novel CDSS possesses high-level semantic recognition of colonoscopy reports, provides appropriate recommendations, and holds the potential to be a powerful tool for physicians and patients. The hierarchical multi-label strategy and pre-training method should be amendable to manage more medical text in the future.
Humans ; Colonoscopy/methods* ; Deep Learning ; Decision Support Systems, Clinical ; Female ; Male

In the clinical stage, suspected hemolytic plasma may cause hemolysis illness, manifesting as symptoms such as heart failure, severe anemia, etc. Applying a deep learning method to plasma images significantly improves recognition accuracy, so that this paper proposes a plasma quality detection model based on improved "You Only Look Once" 5th version (YOLOv5). Then the model presented in this paper and the evaluation system ‌were introduced‌ into the plasma datasets, and ‌the average accuracy of the final classification reached 98.7%‌. The results of this paper's experiment were obtained through the combination of several key algorithm modules including‌ omni-dimensional dynamic convolution, pooling with separable kernel attention, residual bi-fusion feature pyramid network, ‌and‌ re-parameterization convolution. The method of this paper‌ obtains the feature information of spatial mapping efficiently, and enhances the average recognition accuracy of plasma quality detection. This paper presents a high-efficiency detection method for plasma images, aiming to provide a practical approach to prevent hemolysis illnesses caused by external factors.
Algorithms ; Humans ; Hemolysis ; Plasma ; Deep Learning ; Image Processing, Computer-Assisted/methods*

Five new flavan-4-ol glycosides jixueqiosides A-E (1-5) and two new flavan glycosides jixueqiosides F and G (6 and 7), along with twelve known flavan-4-ol glycosides (8-19), were isolated from the roots of Pronephrium penangianum. Comprehensive spectral analyses, X-ray single-crystal diffraction, and theoretical electronic circular dichroism (ECD) calculations established structures and absolute configurations. A single crystal structure of flavan-4-ol glycoside (14) was reported for the first time, while the characteristic ECD and NMR data for all isolated flavan-4-ol glycosides (1-5 , 8-19) were analyzed, establishing a set of empirical rules. Activity screening of these isolates showed that 8 and 9 could inhibit the proliferation of MDA-MB-231 and MCF-7 cells with IC₅₀ values of 7.93 ? 2.85 ?mol?L^-1 and 5.87 ? 1.58 ?mol?L^-1 (MDA-MB-231), and 2.21 ? 1.38 ?mol?L^-1 and 3.52 ? 1.55 ?mol?L^-1 (MCF-7), respectively. Western blotting and flow cytometry analyses demonstrated that 8 and 9 dose-dependently induced apoptosis in MDA-MB-231 cells by up-regulating BAX, activating caspase-3 and down-regulating BCL-2. Additionally, compound 8 affected autophagy-related proteins, increasing the ratio of LC3-II/LC3-I and Beclin-1 levels to inhibit MDA-MB-231 cell proliferation. Moreover, anti-inflammatory studies indicated that 2, 3, 7, 13, 14, and 18 moderately inhibited tumor necrosis factor-a (TNF-a), interleukin-6 (IL-6), and nitric oxide (NO) release.
Humans ; Plant Roots/chemistry* ; Glycosides/isolation & purification* ; Anti-Inflammatory Agents/isolation & purification* ; Flavonoids/isolation & purification* ; Cell Proliferation/drug effects* ; Antineoplastic Agents, Phytogenic/isolation & purification* ; Molecular Structure ; Apoptosis/drug effects* ; Cell Line, Tumor ; Tumor Necrosis Factor-alpha/immunology* ; Drugs, Chinese Herbal/pharmacology* ; Interleukin-6/immunology* ; Animals ; Mice

Accurately obtaining the crop quantity and density is not only crucial for the demand-based input of water and fertilizer in the field but also vital for ensuring the yield and quality of crops. Aerial photography by unmanned aerial vehicles (UAVs) can quickly acquire the distribution image information of crops over a large area. However, the accurate recognition of a single type of dense targets is a huge challenge for most recognition algorithms. Taking banana seedlings as an example in this study, we captured the images of banana plantations by UAVs from high altitudes to explore an efficient recognition method for dense targets. We proposed a strategy of "cut-recognition-stitch" and constructed a counting method based on the improved Faster R-CNN algorithm. First, the images containing highly dense targets were cropped into a large number of image tiles according to different sizes (simulating different flight altitudes), and the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm was adopted to improve the image quality. A banana seedling dataset containing 36 000 image tiles was constructed. Then, the Faster R-CNN network with optimized parameters was used to train the banana seedling recognition model. Finally, the recognition results were reversely stitched together, and a boundary deduplication algorithm was designed to correct the final counting results to reduce the repeated recognition caused by image cropping. The results show that the recognition accuracy of the Faster R-CNN with optimized parameters for banana image datasets of different sizes can reach up to 0.99 at most. The deduplication algorithm can reduce the average counting error for the original aerial images from 1.60% to 0.60%, and the average counting accuracy of banana seedlings reaches 99.4%. The proposed method effectively addresses the challenge of recognizing dense small objects in high-resolution aerial images, providing an efficient and reliable technical solution for intelligent crop density monitoring in precision agriculture.
Musa/growth & development* ; Crops, Agricultural/growth & development* ; Algorithms ; Neural Networks, Computer ; Unmanned Aerial Devices ; Seedlings/growth & development* ; Image Processing, Computer-Assisted/methods* ; Photography ; Agriculture/methods*

OBJECTIVES: To investigate the structural changes of rat thoracic aorta and changes in expression levels of Bmal1 and cyclins in thoracic aorta endothelial cells following heat stress. METHODS: Twenty male SD rats were randomized equally into control group and heat stress group. After exposure to 32 ℃ for 2 weeks in the latter group, the rats were examined for histopathological changes and Bmal1 expression in the thoracic aorta using HE staining and immunohistochemistry. In the cell experiments, cultured rat thoracic aortic endothelial cells (RTAECs) were incubated at 40 ℃ for 12 h with or without prior transfection with a Bmal1-specific small interfering RNA (si-Bmal1) or a negative sequence. In both rat thoracic aorta and RTAECs, the expressions of Bmal1, the cell cycle proteins CDK1, CDK4, CDK6, and cyclin B1, and apoptosis-related proteins Bax and Bcl-2 were detected using Western blotting. TUNEL staining was used to detect cell apoptosis in rat thoracic aorta, and the changes in cell cycle distribution and apoptosis in RTAECs were analyzed with flow cytometry. RESULTS: Compared with the control rats, the rats exposed to heat stress showed significantly increased blood pressures and lowered heart rate with elastic fiber disruption and increased expressions of Bmal1, cyclin B1 and CDK1 in the thoracic aorta (P<0.05). In cultured RTAECs, heat stress caused significant increase of Bmal1, cyclin B1 and CDK1 protein expression levels, which were obviously lowered in cells with prior si-Bmal1 transfection. Bmal1 knockdown also inhibited heat stress-induced increase of apoptosis in RTAECs as evidenced by decreased expression of Bax and increased expression of Bcl-2. CONCLUSIONS Heat stress upregulates Bmal1 expression and causes alterations in expressions of cyclins to trigger apoptosis of rat thoracic aorta endothelial cells, which can be partly alleviated by suppressing Bmal1 expression.
Animals ; ARNTL Transcription Factors/genetics* ; Male ; Aorta, Thoracic/metabolism* ; Rats ; Rats, Sprague-Dawley ; Endothelial Cells/metabolism* ; Apoptosis ; Cells, Cultured ; Heat-Shock Response ; Cyclin B1/metabolism* ; CDC2 Protein Kinase/metabolism* ; Cyclins/metabolism* ; RNA, Small Interfering ; bcl-2-Associated X Protein/metabolism*

Corticotomy is a clinical procedure to accelerate orthodontic tooth movement characterized by the regional acceleratory phenomenon (RAP). Despite its therapeutic effects, the surgical risk and unclear mechanism hamper the clinical application. Numerous evidences support macrophages as the key immune cells during bone remodeling. Our study discovered that the monocyte-derived macrophages primarily exhibited a pro-inflammatory phenotype that dominated bone remodeling in corticotomy by CX3CR1^CreERT2; R26^GFP lineage tracing system. Fluorescence staining, flow cytometry analysis, and western blot determined the significantly enhanced expression of binding immunoglobulin protein (BiP) and emphasized the activation of sensor activating transcription factor 6 (ATF6) in macrophages. Then, we verified that macrophage specific ATF6 deletion (ATF6^f/f; CX3CR1^CreERT2 mice) decreased the proportion of pro-inflammatory macrophages and therefore blocked the acceleration effect of corticotomy. In contrast, macrophage ATF6 overexpression exaggerated the acceleration of orthodontic tooth movement. In vitro experiments also proved that higher proportion of pro-inflammatory macrophages was positively correlated with higher expression of ATF6. At the mechanism level, RNA-seq and CUT&Tag analysis demonstrated that ATF6 modulated the macrophage-orchestrated inflammation through interacting with Tnfα promotor and augmenting its transcription. Additionally, molecular docking simulation and dual-luciferase reporter system indicated the possible binding sites outside of the traditional endoplasmic reticulum-stress response element (ERSE). Taken together, ATF6 may aggravate orthodontic bone remodeling by promoting Tnfα transcription in macrophages, suggesting that ATF6 may represent a promising therapeutic target for non-invasive accelerated orthodontics.
Animals ; Mice ; Macrophages/metabolism* ; Tumor Necrosis Factor-alpha/genetics* ; Tooth Movement Techniques/methods* ; Activating Transcription Factor 6/metabolism* ; Bone Remodeling ; Flow Cytometry ; Blotting, Western

This study aims to investigate the isolate and identify of infectious bronchitis virus(IBV)in chickens,and study its genetic variation and pathogenicity.In 2023,two strains named CK/CH/HN/SQ202301 and CK/CH/HN/SQ202302 were obtained from suspected infectious bronchitis(IB)infected materials collected in a region of Henan Province,China.Further analysis showed that the two isolates belong to the G Ⅰ-13 and GⅥ genotypes,respectively.The cleavage sites of S protein were all RRSRR.The prediction of glycosylation sites showed that the two isolates had 18 and 12 N-glycosylation sites respectively,but no O-glycosylation site.Recombinant analysis shows that C2023-1 was a recombinant strain.Pathogenicity was assessed by infecting 1-day-old SPF chicks with the two isolates,and the results showed that C2023-1 strain infection could cause clini-cal symptoms such as depression and head shaking,as well as death in chicks,with a mortality rate of 37.5％.There were no clinical symptoms or deaths after infection with C2023-2 strain.Viral load test results showed that both isolates continued to detoxify until the 10th day,and had strong rep-lication capacity in the kidney,trachea and bursa of Fabricius.The results indicate significant differences in the genetic characteristics and pathogenicity of the two isolates due to their different genotypes.This study not only provides new epidemiological data on IB,which contributes to a bet-ter understanding of IBV's epidemiological features and control challenges,but also adds valuable bioinformatics resources for IBV by analyzing its variation mechanisms and biological information.