Lung cancer is the malignant tumor with the highest incidence and mortality rates globally. Current treatment methods for lung cancer primarily include surgery， chemotherapy， targeted therapy， and immunotherapy. However， the main limitations of these treatments are their side effects， the drug resistance， and the economic burden they impose. As a critical cancer pathway， the Janus kinase （JAK）/signal transducer and activator of transcription （STAT） signaling pathway regulates tumor occurrence and development through multiple mechanisms by influencing various downstream targets. Consequently， the JAK/STAT signaling pathway offers a promising avenue for lung cancer treatment research. Numerous studies have demonstrated that the JAK/STAT signaling pathway plays a key role in the proliferation and growth of lung cancer cells， angiogenesis， epithelial-mesenchymal transition （EMT）， metabolic alterations， remodeling of the immune microenvironment， and the development of treatment resistance. Traditional Chinese medicine （TCM） has garnered increasing attention due to its minimal side effects， low economic burden， and its potential to enhance efficacy and reduce toxicity when used in conjunction with Western medicine. In addition to traditional Chinese medicine compounds， a growing number of Chinese medicine monomers have come into the spotlight because of their more targeted effects. Numerous studies investigating the regulation of the JAK/STAT signaling pathway by TCM in the treatment of lung cancer have demonstrated that TCM can inhibit the proliferation and invasion of lung cancer cells， tumor angiogenesis， and EMT， improve the inflammatory and immunosuppressive microenvironments， and enhance treatment sensitivity by intervening in the JAK/STAT signaling pathway， thereby impeding the progression of lung cancer. In recent years， the research on the regulation of this pathway by TCM in the treatment of lung cancer has been updated rapidly. However， the summary of these studies has not been updated in time. This review summarizes and reflects on the recent research findings regarding the regulation of the JAK/STAT signaling pathway by TCM to intervene in lung cancer from three aspects， introducing the JAK/STAT pathway， elaborating the mechanism of this pathway in lung cancer， and exploring the intervention of TCM in the treatment of lung cancer through this pathway， to provide more reference for the treatment of lung cancer in the future.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Coronary restenosis is an important cause of poor long-term prognosis in patients with coronary heart disease. Here, we show that lysine methyltransferase SMYD2 expression in the nucleus is significantly elevated in serum- and PDGF-BB-induced vascular smooth muscle cells (VSMCs), and in tissues of carotid artery injury-induced neointimal hyperplasia. Smyd2 overexpression in VSMCs (Smyd2-vTg) facilitates, but treatment with its specific inhibitor LLY-507 or SMYD2 knockdown significantly inhibits VSMC phenotypic switching and carotid artery injury-induced neointima formation in mice. Transcriptome sequencing revealed that SMYD2 knockdown represses the expression of serum response factor (SRF) target genes and that SRF overexpression largely reverses the inhibitory effect of SMYD2 knockdown on VSMC proliferation. HDAC3 directly interacts with and deacetylates SRF, which enhances SRF transcriptional activity in VSMCs. Moreover, SMYD2 promotes HDAC3 expression via tri-methylation of H3K36 at its promoter. RGFP966, a specific inhibitor of HDAC3, not only counteracts the pro-proliferation effect of SMYD2 overexpression on VSMCs, but also inhibits carotid artery injury-induced neointima formation in mice. HDAC3 partially abolishes the inhibitory effect of SMYD2 knockdown on VSMC proliferation in a deacetylase activity-dependent manner. Our results reveal that the SMYD2-HDAC3-SRF axis constitutes a novel and critical epigenetic mechanism that regulates VSMC phenotypic switching and neointimal hyperplasia.

Aural vertigo frequently encountered in the otolaryngology department of traditional Chinese medicine （TCM） mainly involves peripheral vestibular diseases of Western medicine， such as Meniere's disease， benign paroxysmal positional vertigo， vestibular neuritis， and vestibular migraine， being a hot research topic in both TCM and Western medicine. Western medical therapies alone have unsatisfactory effects on recurrent aural vertigo， aural vertigo affecting the quality of life， aural vertigo not relieved after surgery， aural vertigo with complex causes， and children's aural vertigo. The literature records and clinical practice have proven that TCM demonstrates unique advantages in the treatment of aural vertigo. The China Association of Chinese medicine sponsored the "17th youth salon on the diseases responding specifically to TCM： Aural vertigo" and invited vertigo experts of TCM and Western medicine to discuss the difficulties and advantages of TCM diagnosis and treatment of aural vertigo. The experts deeply discussed the achievements and contributions of TCM and Western medicine in the diagnosis and treatment of aural vertigo， the control and mitigation of the symptoms， and the solutions to disease recurrence. The discussion clarified the positioning and advantages of TCM treatment and provided guidance for clinical and basic research on aural vertigo.

Six compounds were isolated from the roots of Ephedra sinica Stapf using various chromatographic techniques such as silica gel column chromatography, thin layer chromatography and semi-preparative HPLC. Their chemical structures were identified by analysis of physicochemical properties and spectral data, and determined as (Z)-docosanylferulate (1), (E)-docosanylferulate (2), bis (2-ethylheptyl) phythalate (3), 2,2′-oxybis (1,4-di-tert-butylbenzene) (4), diisobutyl phthalate (5), bis (2-ethylhexyl) phthalate (6). Among them, compound 1 is a new compound, compounds 2-4 were first isolated from Ephedra. A corticosterone-induced PC-12 cell injury model was used for compound activity screening. The results showed that compounds 1 and 5 significantly improved corticosterone-induced PC-12 cell injury and significantly increased 5-HT₇ receptor protein expression in the cells, indicating potential antidepressant activity.

Amantadine(AMD)residue can accumulate in organisms through the food chain and cause serious harm to human body.AMD can specifically bind to AMD specific aptamer and cause its conformation to change from a random single strand to a stem-loop structure.To avoid the influence of excess nucleotides on binding of aptamer to AMD,the truncation of the AMD original aptamer J was optimized by retaining an appropriate stem-loop structure,and a new type of truncation aptamers was developed in this work.By comparing the truncated aptamer with the original aptamer,it was found that the truncated aptamer J-7 had better affinity and specificity with AMD.The detection limit of AMD was 0.11 ng/mL by using J-7 as specific recognition element and molybdenum disulfide nanosheet(MoS2Ns)as signal amplification element.The developed method base on truncated aptamer J-7 was used for detection of AMD in milk,yogurt and SD rat serum samples for the first time with recoveries of 86.6%-108.2%.This study provided a reference for truncating other long sequence aptamers and provided a more sensitive detection method for monitoring AMD residues in food.

Objective To make an epidemiological investigation on traditional Chinese medicine(TCM)dampness syndrome manifestations in the population at risk of cerebrovascular diseases in Guangdong area.Methods A cross-sectional study was conducted to analyze the clinical data related to the risk of cerebrovascular diseases in 330 Guangdong permanent residents.The diagnosis of dampness syndrome,quantitative scoring of dampness syndrome and rating of the risk of stroke were performed for the investigation of the distribution pattern of dampness syndrome and its influencing factors.Results(1)A total of 306(92.73%)study subjects were diagnosed as dampness syndrome.The percentage of dampness syndrome in the risk group was 93.82%(258/275),which was slightly higher than that of the healthy group(48/55,87.27%),but the difference was not statistically significant(χ2 = 2.91,P = 0.112).The quantitative score of dampness syndrome in the risk group was higher than that of the healthy group,and the difference was statistically significance(Z =-2.24,P = 0.025).(2)Among the study subjects at risk of cerebrovascular disease,evaluation time(χ2 = 26.11,P = 0.001),stroke risk grading(χ2= 8.85,P = 0.031),and history of stroke or transient ischemic attack(TIA)(χ2 = 9.28,P = 0.015)were the factors influencing the grading of dampness syndrome in the population at risk of cerebrovascular disease.Conclusion Dampness syndrome is the common TCM syndrome in the population of Guangdong area.The manifestations of dampness syndrome are more obvious in the population with risk factors of cerebrovascular disease,especially in the population at high risk of stroke,and in the population with a history of stroke or TIA.The assessment and intervention of dampness syndrome should be taken into account for future project of stroke prevention in Guangdong.

BACKGROUND:Medial open wedge high tibial osteotomy is an effective procedure for preserving the knee joint in patients with medial compartmental osteoarthritis.Previous studies have demonstrated that the forgotten joint score provides a lower ceiling effect and consistency of medial open wedge high tibial osteotomy outcomes compared to traditional assessment tools. OBJECTIVE:To identify predictive factors associated with the occurrence of a forgotten joint after medial open wedge high tibial osteotomy. METHODS:117 patients with medial open wedge high tibial osteotomy who were treated at First Affiliated Hospital of Guangzhou University of Chinese Medicine were selected,including 35 males and 82 females,with an average age of 61 years.They were followed up for at least 2 years.Patients were divided into a forgotten joint group(n=28)and a non-forgotten joint group(n=89)by evaluating whether they achieved forgotten joint after surgery.Univariate and multivariate logistic regression analyses were performed with preoperative patient characteristics and surgery-related factors as potential predictors. RESULTS AND CONCLUSION:(1)There were significant differences in the proximal medial tibial angle between the two groups before surgery(P<0.05).There were significant differences in the forgotten joint score,Knee Injury and Osteoarthritis Outcome Score,knee society knee score,function score,and patients joint perception between the two groups after surgery(P<0.05).There was a significant difference between the hip-knee-ankle angle and the medial proximal tibial angle after operation(P<0.05).(2)Univariate Logistic regression analysis showed that the medial proximal tibial angle had a significant influence on the forgotten joint before operation[OR=0.755,95%CI(0.635-0.897),P<0.001].There were significant effects on the forgotten joint of hip-knee-ankle angle and medial proximal tibial angle[OR=1.546,95%CI(1.242-1.924),P<0.001;OR=0.815,95%CI(0.713-0.931),P=0.003].(3)Multivariate logistic regression analysis showed that preoperative K-L grade 1 was a favorable factor for obtaining forgotten joints.Preoperative medial proximal tibial angle and postoperative hip-knee-ankle angle were independent predictors of forgetting joints,and they had a curvilinear relationship with the probability of achieving forgetting joints.When preoperative medial proximal tibial angle increased by 1°,the probability of achieving a forgotten joint decreased by 27.7%[OR=0.723,95%CI(0.593-0.882),P<0.001].Conversely,when postoperative hip-knee-ankle angle increased by 1°,the probability of achieving a forgotten joint increased by 46.4%[OR=1.464,95%CI(1.153-1.860),P=0.002].(4)The results showed that patients with preoperative knee osteoarthritis K-L grade 1,small medial proximal tibial angle(<85.5°),and large postoperative hip-knee-ankle angle(>176.0°)were predictors of forgotten joint.

Objective To investigate the relationship between insomnia,gastrointestinal symptoms,and glycosylated hemoglobin(HbA1c)levels in individuals diagnosed with type 2 diabetes mellitus(T2DM),as well as the related influencing factors.Methods A total of 910 T2DM patients treated in our multicenter from January 2022 to December 2022 were enrolled in this study.General information(gender,age,smoking and drinking history,exercise,course of disease,treatment and complications),HbA1c,Athens Insomnia Scale(AIS)scores and Gastrointestinal Symptoms Rating Scale(GSRS)scores of patients were collected.The differences of sleep and gastrointestinal symptoms between groups were analyzed,and the correlation between the differences and HbA1c was analyzed.Furthermore,the risk factors for non-standard HbA1c were analyzed.Results The AIS score and GSRS score in the HbA1c control group were less than those in the non-standard group(P＜0.01).Insomnia was reported by 37.0％of T2DM patients,and the HbA1c level in the insomnia group was significantly higher than that in the non-insomnia group(10.00％±2.38％vs.8.26％±1.73％,P＜0.01).Gastrointestinal symptoms were present in 57.5％of T2DM patients,and the HbA1c levels in the group with gastrointestinal symptoms were significantly higher than those in the group without gastrointestinal symptoms(9.26％±2.23％vs.8.43％±1.98％,P＜0.01).Furthermore,26.3％of T2DM patients experienced both insomnia and gastrointestinal symptoms.Remarkably,the HbA1c levels in the group with both insomnia and gastrointestinal symptoms were significantly higher than those in the group without either condition(10.18％±2.44％vs.8.45％±1.86％,P＜0.01).Correlation analysis demonstrated a significant association between sleep quality,gastrointestinal function,and HbA1c levels(P＜0.01).The logistic regression analysis result revealed that age,GSRS score,AIS score,and the presence of insomnia combined with gastrointestinal symptoms were independent risk factors for predicting HbA1c≥6.5％(P＜0.01).Having both insomnia and gastrointestinal symptoms concurrently was the strongest risk factor for substandard HbA1c control,and the risk of blood sugar control may increase about 5 times when both appear together.Conclusion Insomnia and gastrointestinal symptoms are common comorbidities in T2DM patients,showing a cross-interfering relationship,and they appear together with poor blood sugar control,interact causally,and amplify each other.

Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.