BACKGROUND:Lijin manipulation can promote skeletal muscle repair and treat skeletal muscle injury.However,the formation of fibrosis and scar tissue hyperplasia are closely related to the quality of skeletal muscle repair.To study the regulatory effect of Lijin manipulation on the formation of fibrosis and scar tissue hyperplasia is helpful to explain the related mechanism of Lijin manipulation to improve the repair quality of skeletal muscle injury. OBJECTIVE:To explore the mechanism of Lijin manipulation to improve the repair quality of skeletal muscle injury in rabbits,thereby providing a scientific basis for clinical treatment. METHODS:Forty-five healthy adult Japanese large-ear white rabbits were randomly divided into blank group,model group and Lijin group,with 15 rats in each group.Gastrocnemius strike modeling was performed in both model group and Lijin group.The Lijin group began to intervene with tendon manipulation on the 3rd day after modeling,once a day,and 15 minutes at a time.Five animals in each group were killed on the 7th,14th and 21st days after modeling.The morphology and inflammatory cell count of gastrocnemius were observed by hematoxylin-eosin staining,the collagen fiber amount was observed by Masson staining,the expression of interleukin-6 and interleukin-10 in gastrocnemius was detected by ELISA.The protein and mRNA expressions of paired cassette gene 7,myogenic differentiation factor,myoblastogenin,alpha-actin,transforming growth factor beta 1,and type Ⅰ collagen were detected by western blot and RT-PCR,respectively,and the expression of type Ⅰ collagen protein was detected by immunohistochemistry. RESULTS AND CONCLUSION:Hematoxylin-eosin staining and Masson staining showed that compared with the model group,inflammatory cell infiltration and collagen fiber content decreased in the Lijin group(P<0.01),and the muscle fibers gradually healed.ELISA results showed that compared with the model group,the expression of interleukin-6 in the Lijin group continued to decrease(P<0.05),and the expression of interleukin-10 increased on the 7th day after modeling(P<0.05)and then showed a decreasing trend(P<0.05).Western blot and RT-PCR results showed that compared with the model group,the protein and mRNA expressions of paired cassette gene 7,myogenic differentiation factor,myoblastogenin in the Lijin group were significantly increased on the 14th day after modeling(P<0.05),but decreased on the 21st day(P<0.05);the protein and mRNA expressions of alpha-actin,transforming growth factor beta 1,and type Ⅰ collagen in the Lijin group were significantly decreased compared with those in the model group(P<0.05).Immunohistochemical results showed that the expression of type Ⅰ collagen in the Lijin group was significantly lower than that in the model group(P<0.05).To conclude,Lijin manipulation could improve the repair quality of skeletal muscle injury by inhibiting inflammation,promoting the proliferation and differentiation of muscle satellite cells,and reducing fibrosis.

AIM: To evaluate the clinical efficacy of intense pulsed light(IPL)therapy in patients with primary Sjogren's syndrome-related dry eye(SS-DE).METHODS:In this prospective randomized trial, 82 cases(82 eyes)diagnosed with moderate-to-severe SS-DE at our hospital from January 2023 to December 2023 were selected. If both eyes meet the criteria, one eye will be randomly selected for inclusion, and if one eye meets the inclusion criteria, the eye will be selected for enrollment. They were randomly assigned to either an experiment group receiving dextran hydroxypropyl methylcellulose eye drops and 0.05% cyclosporine A eye drops plus IPL therapy, or a control group receiving dextran hydroxypropyl methylcellulose eye drops and 0.05% cyclosporine A eye drops. Ocular surface disease index(OSDI)score, tear meniscus height(TMH), noninvasive tear breakup time(NITBUT), meibomian gland loss score, Schirmer I test(SⅠt), corneal fluorescein staining(CFS)score, conjunctival lissamine green staining(CLGS)score, lipid layer thickness(LLT), blink frequency, corneal Langerhans cell density(CLCD)and complications of both groups were assessed at baseline and at 4, 8, and 12 wk after treatment.RESULTS:There were 6 cases lost to follow-up in the experiment group, with a missing rate of 14.6%, and 1 case was lost to follow-up in the control group, with a missing rate of 2.4%, and valid data were eventually obtained from 35 cases(35 eyes)in the experiment group and 40 cases(40 eyes)in the control group. Baseline parameters did not differ significantly between the two groups of patients(all P>0.05). At 4, 8 and 12 wk after treatment, both groups showed significant reductions in OSDI scores, CFS scores, CLGS score, blink frequency, and CLCD, while the reductions were significantly greater in the experiment group compared to the control group(all P<0.05). The experiment group also demonstrated significant increases in TMH, SⅠt, and NITBUT at 4, 8 and 12 wk after treatment, which were significantly greater than those observed in the control group(all P<0.05). No significant intergroup differences were observed in LLT, meibomian gland loss score in the experiment group at any time point(all P>0.05). Furthermore, no severe ocular or cutaneous complications were associated with IPL treatment.CONCLUSION:IPL significantly improves ocular signs and symptoms, enhances aqueous tear secretion, and reduces ocular surface inflammation in patients with SS-DE, with no significant adverse reactions observed.

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

Lysosomes represent a promising target for cancer therapy and reducing drug resistance. However, the short treatment time and low efficiency of lysosomal targeting have limited the application in lysosome-targeting anticancer drugs. In this study, we proposed an adhesive-bandage approach and synthesized a new lysosomal targeting drug, namely long-term lysosome-targeting anticancer drug (LLAD). It contains a SLC38A9-targeting covalently bound moiety and an alkaline component both to prolong the inhibition of SLC38A9 in lysosomes and alkalinize lysosomes. Upon short term and low-dose treatment of HeLa cells, at passage 0, with LLAD, it rapidly alkalinized lysosomes and also can be detected in lysosomes even at passage 15. LLAD induced apoptosis in HeLa cells through long-term lysosomal damage, and showed better long-term anticancer effect than cisplatin in vivo. Overall, our study paves the way for developing long-term lysosomal targeting drugs to treat cancer and overcome the drug resistance of cancer cells, and also provides a candidate drug, LLAD, for treating cancer.

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*

Objective:To investigate the correlation between the expression of GLI1 and im-mune invasion and clinical prognosis in gastric cancer.To study the effect of GLI1 expression on drug resistance in gastric cancer.Methods:The expression difference of GLI1 in gastric cancer and normal tissues was analyzed by using TCGA database,and the effect of clinical features and GLI1 gene ex-pression level on prognosis of patients with gastric cancer was analyzed.The correlation between GLI1 gene expression and tumor immune cell infiltration in gastric cancer tissues was analyzed to explore its influence on drug resistance of chemotherapy drugs and targeted drugs.Clinical samples were collect-ed to analyze the difference of GLI1 expression in gastric cancer and paracancer tissues.Results:The expression of GLI1 in gastric cancer tissues was 1.7 times that in normal tissues,and the overall sur-vival and disease-free survival of patients with high expression are shorter than those with low ex-pression(P＜0.05).The interstitial score,immune score and abundance of immunoinfiltrating cells were higher in the high expression of GLI1 in gastric cancer tissues.High expression of GLI1 reduces drug sensitivity and is positively correlated with the expression of immune checkpoint markers PDCD1(P＜0.05).GLI1 expression was significantly increased in patients with subdifferentiated gastric cancer.Conclusions:GLI1 expression is associated with the prognosis and immune infiltration of patients with gastric cancer,and it may lead to poor prognosis of patients by regulating chemotherapy resis-tance,which may be a potential therapeutic target and molecular marker for gastric cancer.

Objective:To investigate the associated factors of depressive symptoms among patients with neo-plasms.Methods:Nationwide(excluding Hong Kong,Macao,and Taiwan),30 505 residents were selected by a combination of stratified sampling and quota sampling according to the proportion of the seventh national population census.Patient Health Questionnaire-9(PHQ-9),General Anxiety Disorder-7(GAD-7),self-made questionnaire,and simplified perceived social support scale used to evaluate depressive symptoms,anxiety symptoms,behaviors,and perceived social support among patients with neoplasms.Results:Totally 359(1.2％)patients with self-repor-ted clinically diagnosed neoplasms were included,of which 151(42.1％)patients with malignant neoplasms and 208(57.9％)patients with benign neoplasms.The detection rate of depressive symptoms in patients with neo-plasms was 76.6％.Less than three days of walking for more than 10 minutes per day in the past week(OR=6.63),4-6 days of walking for more than 10 minutes per day in the past week(OR=5.00),the low(OR=4.80)or medium(OR=3.06)overall sleep quality,the lower perceived friend support(OR=4.66),and anxiety symp-toms(OR=1.74)among patients with neoplasms were risk factors for depressive symptoms.Conclusion:Patients with neoplasms generally might be at a high risk of depressive symptoms,especially for those patients with less ex-ercise,poor sleep quality,and low perceived social support.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective As primary Sj?gren's syndrome(pSS)primarily affects the salivary glands,saliva can serve as an indicator of the glands'pathophysiology and the disease's status.This study aims to illustrate the salivary proteomic profiles of pSS patients and identify potential candidate biomarkers for diagnosis. Methods The discovery set contained 49 samples(24 from pSS and 25 from age-and gender-matched healthy controls[HCs])and the validation set included 25 samples(12 from pSS and 13 from HCs).Totally 36 pSS patients and 38 HCs were centrally randomized into the discovery set or to the validation set at a 2:1 ratio.Unstimulated whole saliva samples from pSS patients and HCs were analyzed using a data-independent acquisition(DIA)strategy on a 2D LC-HRMS/MS platform to reveal differential proteins.The crucial proteins were verified using DIA analysis and annotated using gene ontology(GO)and International Pharmaceutical Abstracts(IPA)analysis.A prediction model for SS was established using random forests. Results A total of 1,963 proteins were discovered,and 136 proteins exhibited differential representation in pSS patients.The bioinformatic research indicated that these proteins were primarily linked to immunological functions,metabolism,and inflammation.A panel of 19 protein biomarkers was identified by ranking order based on P-value and random forest algorichm,and was validated as the predictive biomarkers exhibiting good performance with area under the curve(AUC)of 0.817 for discovery set and 0.882 for validation set. Conclusions The candidate protein panel discovered may aid in pSS diagnosis.Salivary proteomic analysis is a promising non-invasive method for prognostic evaluation and early and precise treatments for pSS patients.DIA offers the best time efficiency and data dependability and may be a suitable option for future research on the salivary proteome.