Ulcerative colitis （UC）， a chronic relapsing inflammatory bowel disease， involves multifaceted pathological mechanisms such as intestinal barrier dysfunction， immune dysregulation， and oxidative stress. Current therapeutic strategies remain limited in efficacy and safety. In recent years， the adenosine monophosphate-activated protein kinase （AMPK） signaling pathway has emerged as a pivotal therapeutic target for UC due to its central role in energy metabolism， inflammatory regulation， and intestinal homeostasis. This article systematically reviewed the mechanisms by which traditional Chinese medicine （TCM） prevented and treated UC through the regulation of the AMPK signaling pathway， with a focus on elucidating AMPK's multidimensional regulatory network in inflammatory signaling crosstalk， alleviating oxidative stress， restoring intestinal immune balance， repairing the intestinal barrier， and modulating gut microbiota. Leveraging its unique advantages of multi-target engagement and low toxicity， TCM demonstrates promising potential in UC treatment and has become a focal area of research. By systematically summarizing and synthesizing the existing literature on TCM-mediated AMPK pathway modulation in UC， this review aims to provide a theoretical foundation for advancing mechanistic research and clinical interventions in UC.

Objective: To analyze the association between drinking behaviors and anxiety symptoms, with the mediating role of insomnia symptoms among college freshmen, so as to provide a reference basis for reducing the occurrence of anxiety symptoms in college freshmen. Methods: From October to December 2021, 31 856 freshmen were selected by the purposive sampling method in 22 colleges across 11 provinces (Fujian, Jiangsu, Guangdong, Henan, Anhui, Hubei, Shanxi, Jiangxi, Shaanxi, Yunnan, Chongqing) in China. The Semi quantitative Food Frequency Questionnaire was used to investigate college freshmen drinking behaviors. The Depression Anxiety Stress Scale 21 and the Insomnia Severity Index were used to assess anxiety symptoms and insomnia symptoms in college freshmen. The generalized linear model was employed to analyze the association between drinking behaviors and anxiety symptoms in college freshmen, and the structural equation modeling was used to assess the mediating effect of insomnia symptoms on the association. Results: The detection rate of anxiety symptoms among college freshmen was 28.2%, the detection rates of the mild, moderate, severe and extremely severe were 6.6%, 15.9%, 3.2% and 2.6%, respectively. While 23.6% of college freshmen reported drinking in the past month, the rates were 39.8% among boys and 15.9% among girls. After adjusting for demographic variables (ethnicity, education, major, etc.) and confounding variables (self evaluation of learning burden, number of close friends, screen time, etc.), the results of generalized linear model analysis showed that beer consumption was associated with anxiety symptoms in college freshmen( β =0.09, 95% CI =0.04-0.14), girls( β =0.14, 95% CI =0.07-0.21) and those aged 19-20 years ( β =0.12, 95% CI =0.05-0.19)(all P <0.05). Red wine consumption was associated with anxiety symptoms in male students ( β =0.13, 95% CI =0.02-0.24, P <0.05). Alcohol and beer consumption were associated with insomnia in college freshmen[ β (95% CI ) =0.22(0.08-0.36),0.31(0.23-0.39),both P <0.01]. Insomnia symptoms partially mediated the association between drinking behaviors and anxiety symptoms among college freshmen with a mediating effect value of 0.05, accounting for 50.49% of the total effect. Conclusions Insomnia symptoms partially mediates the association between drinking behaviors and anxiety symptoms in college freshmen. Measures should be taken to simultaneously intervene in the drinking behaviors and insomnia symptoms of college freshmen to prevent the occurrence of their anxiety symptoms.

Objective To investigate the effects of laparoscopic sleeve gastrectomy(LSG)on the cardiac structure and function in obese patients with heart failure(HF)and compare the efficacy of LSG across obese patients with different HF types.Methods This study included 33 obese patients with HF who underwent LSG.The clinical indicators were compared between before operation and 12 months after operation.Repeated measures analysis of variance was employed to evaluate the changes in echocardiographic parameters before operation and 3,6,and 12 months after operation.Patients were allocated into a HF with preserved ejection fraction group(n=17),a HF with mildly reduced ejection fraction group(n=5)and a HF with reduced ejection fraction(HFrEF)group(n=11)based on left ventricular ejection fraction(LVEF)before operation for subgroup analyses of the effects of LSG on the cardiac structure and function of obese patients with HF.The paired samples t-test was conducted to assess the degree of cardiac structural and functional alterations after LSG.Results The 33 patients included 69.7% males,with an average age of(35.3±9.9)years,and a body mass index(BMI)of(51.2±9.8)kg/m².The median follow-up was 9.0(5.0,13.3)months.Compared with the preoperative values,the postoperative BMI(P=0.002),body surface area(BSA)(P=0.009),waist circumference(P=0.010),hip circumference(P=0.031),body fat content(P=0.007),and percentage of patients with cardiac function grades Ⅲ-IV(P<0.001)decreased.At the 12-month follow-up left atrial diameter(P=0.006),right atrial long-axis inner diameter(RAD1)(P<0.001),right atrial short-axis inner diameter(RAD2)(P<0.001),right ventricular inner diameter(P=0.002),interventricular septal thickness at end-diastolic(P=0.002),and left ventricular end-diastolic volumes(P=0.004)and left ventricular end-systolic volumes(P=0.003) all significantly reduced compared with preoperative values.Additionally,left ventricular fractional shortening and LVEF improved(both P<0.001).Subgroup analyses revealed that cardiac structural parameters significantly decreased in the HF with preserved ejection fraction,HF with mildly reduced ejection fraction,and HFrEF subgroups compared with preoperative values.Notably,the HFrEF group demonstrated the best performance in terms of left atrial diameter(P=0.003),left ventricular inner diameter at end-diastole(P=0.008),RAD1(P<0.001),RAD2(P=0.004),right ventricular inner diameter(P=0.019),left ventricular end-diastolic volume(P=0.004)and left ventricular end-systolic volume(P=0.001),cardiac output(P=0.006),tricuspid regurgitation velocity(P=0.002),and pulmonary artery systolic pressure(P=0.001) compared to preoperatively.Postoperative left ventricular fractional shortening(P<0.001,P=0.003,P<0.001)and LVEF(P<0.001,P=0.011,P=0.001)became higher in all the three subgroups than the preoperative values.Conclusions LSG decreased the body weight,BMI,and BSA,improved the cardiac function grade,reversed the enlargement of the left atrium and left ventricle,reduced the right atrium and right ventricle,and enhanced the left ventricular systolic function.It was effective across obese patients with different HF types.Particularly,LSG demonstrates the best performance in improving the structures of both atria and ventricles in obese patients with HFrEF.
Humans ; Male ; Female ; Gastrectomy/methods* ; Heart Failure/complications* ; Adult ; Obesity/physiopathology* ; Laparoscopy ; Middle Aged ; Heart/physiopathology* ; Stroke Volume

Greater trochanteric pain syndrome(GTPS)is a disease caused by structural lesions of the muscles,fascia,ligaments,and bursae near the greater trochanter of the femur.GTPS causes lateral hip joint pain,severely affecting patients' quality of life.Ultrasound has many advantages,such as real-time diagnosis,portable operation,non-radiation,and high resolution,demonstrating a high application value in the diagnosis and interventional therapy of GTPS.This article reviews the current status of ultrasound in the diagnosis and interventional therapy of GTPS and prospects its application.
Humans ; Ultrasonography ; Femur/diagnostic imaging* ; Hip Joint/diagnostic imaging* ; Arthralgia/therapy*

ObjectiveTomatoes are one of the highest-yielding and most widely cultivated economic crops globally, playing a crucial role in agricultural production and providing significant economic benefits to farmers and related industries. However, early blight in tomatoes is known for its rapid infection, widespread transmission, and severe destructiveness, which significantly impacts both the yield and quality of tomatoes, leading to substantial economic losses for farmers. Therefore, accurately identifying early symptoms of tomato early blight is essential for the scientific prevention and control of this disease. Additionally, visualizing affected areas can provide precise guidance for farmers, effectively reducing economic losses. This study combines hyperspectral imaging technology with machine learning algorithms to develop a model for the early identification of symptoms of tomato early blight, facilitating early detection of the disease and visual localization of affected areas. MethodsTo address noise interference present in hyperspectral images, robust principal component analysis (RPCA) is employed for effective denoising, enhancing the accuracy of subsequent analyses. To avoid insufficient information representation caused by the subjective selection of regions of interest, the Otsu’s thresholding method is utilized to extract tomato leaves effectively from the background, with the average spectrum of the entire leaf taken as the primary object of study. Furthermore, a comprehensive spectral preprocessing workflow is established by integrating multivariate scatter correction (MSC) and standardization methods, ensuring the reliability and effectiveness of the data. Based on the processed spectral data, a discriminant model utilizing a linear kernel function support vector machine (SVM) is constructed, focusing on characteristic wavelengths to improve the model's discriminative capability. ResultsCompared to full-spectrum modeling, this approach results in an 8.33% increase in accuracy on the test set. After optimizing the parameters of the SVM model, when C=1.64, the accuracies of the training set and test set reach 91.67% and 94.44%, respectively, demonstrating a 1.19% increase in training set accuracy compared to the unoptimized model, while maintaining the same accuracy on the test set, effectively alleviating issues of underfitting. ConclusionThis study successfully establishes an early discriminant model for tomato early blight using hyperspectral imaging and achieves visualization of early symptoms. Experimental results indicate that the SVM discriminant model based on characteristic wavelengths and a linear kernel function can effectively identify early symptoms of tomato early blight. Visualization of these symptoms in terms of disease probability allows for a more intuitive detection of early diseases and timely implementation of corresponding control measures. This visual analysis not only enhances the efficiency of disease identification but also provides farmers with more straightforward and practical information, aiding them in formulating more reasonable prevention strategies. These research findings provide valuable references for the early identification and visualization of plant diseases, holding significant practical implications for monitoring, identifying, and scientifically preventing crop diseases. Future research could further explore how to apply this model to disease detection in other crops and how to integrate IoT technology to create intelligent disease monitoring systems, enhancing the scientific and efficient management of crops.

ObjectiveEarly blight is a common destructive disease in the growth process of Solanaceae crops, which can lead to crop failure and serious losses. Traditional crop disease detection methods are difficult to detect disease characteristics in a timely manner during the incubation period of disease, and thus take scientific and effective prevention and control measures. This study obtained hyperspectral images of early blight of peppers at different infection stages through continuous monitoring with a hyperspectral imager. The earliest identifiable time during the incubation period of early blight in peppers (the earliest identifiable time during the incubation period in this experiment was 24 h after inoculation) was determined using the spectral angle cosine-correlation coefficient and Chebyshev distance. MethodsTaking the symptoms of the latent period of early blight in peppers as the research object, 13 characteristic wavelengths were selected using a genetic algorithm. An identification model of crop disease latent period symptoms based on spectral features was established through optimized combinations of characteristic wavelengths combined with a logistic regression model. Simultaneously, a recognition model of the latent period of early blight in peppers based on image texture features was established using local binary patterns. ResultsThe experiment was tested with 120 samples. The accuracy of the identification model of crop disease latent period symptoms based on spectral features reached over 93% in both the training set and the test set. The accuracy of the identification model of crop disease latent period symptoms based on texture features reached 98.96% and 100% in the training set and test set, respectively. ConclusionBoth spectral features and texture features can be used to detect and identify crop disease latent period symptoms. Texture features more significantly revealed the characteristics of the latent period of the disease compared to spectral features, effectively improving the detection performance of the model. The research results in this article can provide theoretical references for monitoring and identifying other crop disease latent period symptoms.

Objective: Huntington’s disease (HD) is characterized by motor, cognitive, and neuropsychiatric symptoms. Oculomotor impairments and gait variability have been independently considered as potential markers in HD. However, an integrated analysis of eye movement and gait is lacking. We performed multiple examinations of eye movement and gait variability in HTT mutation carriers, analyzed the consistency between these parameters and clinical severity, and then examined the associations between oculomotor impairments and gait deficits. Methods: We included 7 patients with pre-HD, 30 patients with HD and 30 age-matched controls. We collected demographic data and assessed the Unified Huntington’s Disease Rating Scale (UHDRS) score. Examinations, including saccades, smooth pursuit tests, and optokinetic (OPK) tests, were performed to evaluate eye movement function. The parameters of gait include stride length, walking velocity, step deviation, step length, and gait phase. Results: HD patients have significant impairments in the latency and velocity of saccades, the gain of smooth pursuit, and the gain and slow phase velocities of OPK tests. Only the speed of saccades significantly differed between pre-HD patients and controls. There are significant impairments in stride length, walking velocity, step length, and gait phase in HD patients. The parameters of eye movement and gait variability in HD patients were consistent with the UHDRS scores. There were significant correlations between eye movement and gait parameters. Conclusion Our results show that eye movement and gait are impaired in HD patients and that the speed of saccades is impaired early in pre-HD. Eye movement and gait abnormalities in HD patients are significantly correlated with clinical disease severity.

Objective: Huntington’s disease (HD) is characterized by motor, cognitive, and neuropsychiatric symptoms. Oculomotor impairments and gait variability have been independently considered as potential markers in HD. However, an integrated analysis of eye movement and gait is lacking. We performed multiple examinations of eye movement and gait variability in HTT mutation carriers, analyzed the consistency between these parameters and clinical severity, and then examined the associations between oculomotor impairments and gait deficits. Methods: We included 7 patients with pre-HD, 30 patients with HD and 30 age-matched controls. We collected demographic data and assessed the Unified Huntington’s Disease Rating Scale (UHDRS) score. Examinations, including saccades, smooth pursuit tests, and optokinetic (OPK) tests, were performed to evaluate eye movement function. The parameters of gait include stride length, walking velocity, step deviation, step length, and gait phase. Results: HD patients have significant impairments in the latency and velocity of saccades, the gain of smooth pursuit, and the gain and slow phase velocities of OPK tests. Only the speed of saccades significantly differed between pre-HD patients and controls. There are significant impairments in stride length, walking velocity, step length, and gait phase in HD patients. The parameters of eye movement and gait variability in HD patients were consistent with the UHDRS scores. There were significant correlations between eye movement and gait parameters. Conclusion Our results show that eye movement and gait are impaired in HD patients and that the speed of saccades is impaired early in pre-HD. Eye movement and gait abnormalities in HD patients are significantly correlated with clinical disease severity.

Objective This study examines serum lipid metabolism characteristics in colorectal cancer patients and its diagnostic potential.Methods Serum samples from 57 colorectal cancer patients and 54 healthy controls underwent lipidomic analysis using ultra-high performance liquid chromatography-time-of-flight mass spec-trometry,combined with principal component analysis(PCA)and orthogonal partial least squares discriminant analysis(OPLS-DA).Differential lipids were identified based on criteria of P<0.05,VIP>1,and fold change<0.67 or>1.5.These lipids were further evaluated using receiver operating characteristic(ROC)analysis to identify biomarkers with strong diagnostic value.Results Five classes and 66 differential lipids were identified,with phos-phatidylcholine(PC)and triglyceride(TG)comprising 59.09%.KEGG pathway enrichment indicated involvement in glycerophospholipid and glycerol ester metabolism pathways.ROC analysis identified Sphinganine,MG(19∶0),LysoPC(18∶2),PA(42∶6),PC(36∶5),PC(36∶4),PC(38∶6),and PC(40∶8)as having areas under the curve greater than 0.85.Conclusion The lipid metabolic profile of colorectal cancer(CRC)patients can be systematically analyzed through the efficient enrichment of lipid metabolites in serum using the UPLC-Q/TOF-MS technique,in conjunction with a modified Bligh-Dyer method.The identification of eight specific lipids including Sphinganine,MG(19∶0),LysoPC(18∶2),PA(42∶6),PC(36∶5),PC(36∶4),PC(38∶6),and PC(40∶8)offer novel insights and parameters for differentiating between healthy individuals and those diagnosed with colorec-tal cancer.

Objective:To observe the efficacy of probiotics in the adjuvant treatment of bronchial asthma and to explore the relationship between their action and intestinal flora.Methods:A total of 76 newly diagnosed patients with mild-to-moderate bronchial asthma treated at Baotou Central Hospital between November 2023 and January 2025 were randomly divided into two groups:the conventional treatment group(n=38)and the combined probiotic treatment group(n=38).Post-treatment comparisons were made between the two groups regarding symptom resolution time,Asthma Control Test(ACT)scores,lung function,fractional exhaled nitric oxide(FeNO)levels,serum inflammatory cytokines,complement levels,and other indicators.Faecal samples were collected for 16S rDNA sequencing of gut microbiota.Results:Baseline characteristics showed no significant differences between the two groups(P＞0.05).Compared to the conventional treatment group,the combined probiotic group exhibited significantly shorter resolution times for asthma symptoms and lung rales(P＜0.001),significantly higher ACT scores,FEV1,and PEF(P＜0.001),and significantly lower FeNO levels(P＜0.001).Additionally,serum interleukin-6(IL-6),tumor necrosis factor-α(TNF-α),and complement C3 levels were significantly reduced(P＜0.001),while serum interleukin-6(IL-10)levels were significantly increased(P＜0.001).16S rDNA sequencing revealed no significant changes in gut microbiota richness or diversity in the conventional treatment group before and after treatment(P＞0.05),whereas intestinal flora richness and diversity were significantly increased in the combined probiotic treatment group compared to the pre-treatment group(P＜0.05).Correlation analysis between gut microbiota and inflammatory markers demonstrated that Faecalibacterium and Bifidobacterium abundance were negatively correlated with TNF-α levels(P＜0.05),while Escherichia-Shigella,and Streptococcus abundance were positively correlated with TNF-α levels(P＜0.05).Streptococcus and Klebsiella abundance were positively correlated with IL-6 levels(P＜0.05).Escherichia-Shigella and Streptococcus abundance were negatively correlated with IL-10 levels and positively correlated with complement C3 levels(P＜0.05).Conclusion:Probiotics may assist in improving bronchial asthma symptoms by influencing the gut flora to reduce the inflammatory response.