OBJECTIVE: To elucidate the rules of temporal and spatial variations in distal skin potential at Hegu (LI4) under different stimulation modes by extracting nonlinear characteristic parameters from array multichannel data and adopting multivariate statistical analysis. METHODS: Seven healthy subjects were selected and the surface potential at the left Quchi (LI11) was collected using 14×9 array multichannel electrodes. Using Hegu (LI4) on the left as the stimulation point, four stimulation modes were applied, i.e. being quiescent, point pressing, moxibustion, and manual needling manipulation. Electrical signals were collected for 30 s in each mode, with a 5-min interval between operations, and a sampling frequency of 16 384 Hz. The data was denoised using ensemble empirical mode decomposition (EEMD), and sample entropy (SaEn) features were extracted. Statistical analysis was conducted on these data using factor analysis and multivariate analysis of variance. RESULTS: The SaEn values of most electrode channels were higher under point pressing, moxibustion and manual needling manipulation compared with those under quiescent condition. Under manual needling manipulation, the SaEn value of the electrode channel reached the peak in the first time interval (1-5 s) and it was declining thereafter. Factor analysis showed that the specificity of activation channels was concentrated at the left Quchi (LI11) (loading capacity ≥0.90). Analysis of variance indicated that the significant differences were presented in average sample entropy (SaEn()) values of activation channels among different stimulation modes at Hegu (LI4) (P<0.001), but there was no statistically significant interaction effect between groups and time intervals (P>0.05). CONCLUSION Through nonlinear characteristic parameter extraction and multivariate statistical analysis, we have uncovered the complex temporal and spatial dynamical rules of distal skin potential at Hegu (LI4) under various stimulation modes and successfully identified the specific activation characteristics at Quchi (LI11).
Humans ; Moxibustion ; Acupuncture Points ; Male ; Adult ; Female ; Young Adult ; Acupuncture Therapy/instrumentation*

OBJECTIVE: To explore the pain-location interaction between pressure-sensitive points on the body surface and traditional acupoints in patients with chronic non-specific low back pain (CNLBP) under different disease courses, using Euclidean distance and multivariate statistical analysis. METHODS: A pressure-sensitive point detection was performed on 30 CNLBP patients with varying disease courses. A constant pressure was applied using an FDK20 algometer within a designated lumbar area, a total of 50 points were tested, and the tested points were numbered; the visual analogue scale (VAS) pain score was recorded simultaneously. MatlabR2022a9.12. software was used to extract the positions of pressure-sensitive points, and preprocessing and normalization of point location and VAS scores data were conducted. Under constraint conditions (VAS≥8.0 ∩ Euclidean distance to acupoint≤0.5), the proportion of pressure-sensitive points within the Euclidean distance threshold to each acupoint (PVD_acupoint) was calculated, followed by multivariate statistical analysis. RESULTS: ①Constrained analysis of PVD_acupoint showed that PVD_{Qihaishu (BL24)} and PVD_{Dachangshu (BL25)} were positively correlated with disease course (r=0.55, P<0.01). ②Factor analysis and silhouette analysis revealed that PVD_{Shenshu (BL23)} and PVD_{Dachangshu (BL25)} exhibited trends consistent with disease course progression (P>0.05), with different degree (P<0.01). CONCLUSION The PVD_acupoint value based on Euclidean distance can characterize the pressure sensitivity features of traditional acupoints associated with disease. Multivariate statistical analysis of PVD_acupoint confirms that selecting the acupoint combination of Shenshu (BL23) and Dachangshu (BL25) for CNLBP is associated with the distribution of surrounding pressure-sensitive points and the pathological characteristics of the condition.
Humans ; Acupuncture Points ; Low Back Pain/physiopathology* ; Male ; Female ; Middle Aged ; Adult ; Aged ; Acupuncture Therapy ; Young Adult ; Pressure

Lung cancer is one of the malignant tumours with the highest morbidity and mortality rates worldwide today, posing a major threat to human health. Accurate diagnosis and standardised treatment play a crucial role in improving the survival rate of lung cancer patients. In recent years, the rapid rise of artificial intelligence (AI) has brought about significant changes in the medical field, providing a new diagnostic and treatment model for lung cancer, and making a series of breakthroughs in lung cancer diagnostic imaging, pathological diagnosis, surgical oncology, radiotherapy, and drug development and treatment. This article introduces the current status of AI application in the field of lung cancer diagnosis and treatment, and extensively discusses the current challenges and future prospects, hoping to provide references and suggestions for future clinical practice.

Objective To assess stromal fibrosis in epidermal growth factor receptor(EGFR)mutant lung adenocarcinoma and its association with resistance to targeted therapy and patient prognosis.Methods Medical records of 207 patients diagnosed with EGFR-mutant advanced lung adenocarcinoma who received treatment at a hospital between January 2021 and December 2022 were reviewed.A total of 86 patients were ultimately included based on their prognosis and survival duration.These patients were categorized into a resistance group(32 cases)and a non-resistance group(54 cases),depending on whether they developed resistance to targeted therapy within one year.Additionally,patients were classified into mild,moderate,and severe fibrosis groups according to the extent of fibrosis observed.Clinical and pathological characteristics,as well as fibrosis levels,were compared between the two groups.Factors influencing the development of resistance to targeted therapy in patients with EGFR-mutant lung adenocarcinoma were analyzed,and the survival outcomes of patients with varying degrees of fibrosis were evaluated during follow-up.Results In the resistance group,the prevalence of EGFR exon 20 insertion mutations,elevated CA125 levels,and the presence of moderate-to-severe fibrosis were significantly higher compared to the non-resistance group(P<0.05).Multivariate logistic regression analysis revealed that EGFR exon 20 inser-tion mutation(OR=3.691,95%CI:1.043～13.057),elevated CA125 levels(OR=4.104,95%CI:1.160～14.517),and moderate-to-severe fibrosis(OR=3.959,95%CI:1.410～11.115)were independent risk factors associated with resistance to targeted therapy among patients with EGFR-mutant lung adenocarcinoma(P<0.05).The Cox proportional hazards model demonstrated a C-index of 0.72(95%CI:0.65～0.79),with area under the curve(AUC)values for 1-year and 2-year survival predictions of 0.781 and 0.734,respectively.EGFR exon 20 insertion mutation(HR=3.691),moderate-to-severe fibrosis(HR=3.959),and elevated CA125 levels(HR=4.104)were identified as independent prognostic factors for overall survival in these patients following targeted therapy.The median progression-free survival(PFS)for patients with mild,moderate,and severe fibrosis was 10.5 months,7.2 months,and 3.9 months,respectively,while the median overall survival(OS)was 21.4 months,16.1 months,and 11.5 months,respectively.Statistically significant differences in both PFS and OS were observed across the three fibrosis severity groups.(P<0.05).Conclusion The extent of stromal fibrosis in EGFR-mutant lung adenocarcinoma influences resistance to targeted therapy,and the progression of fibrosis is correlated with an unfavorable prognosis.

Objective:To investigate the clinical characteristics, treatment and prognosis of juvenile dermatomyositis (JDM) complicated by sever gastrointestinal hemorrhage in children.Methods:A retrospective analysis was conducted on 4 JDM patients with sever gastrointestinal hemorrhage admitted to our hospital, from January 2017 to January 2025. Data including demographics, clinical manifestations, laboratory and imaging findings, treatment courses, and outcomes were reviewed.Results:The cohort comprised 4 patients (2 males, 2 females), with onset ages of 6.1, 6.2, 10.0 and 8.0 years. All presented with rash and fatigue and were diagnosed with severe refractory JDM (strongly positive anti-NXP2 antibodies). Sever gastrointestinal hemorrhage occurred 18, 12, 51, and 2 months after JDM diagnosis. Two cases had confirmed gastrointestinal infections due to contaminated food. Abdominal pain was the initial gastrointestinal symptom and black stool was observed in all cases, hemoglobin levels dropped below 60 g/L (case 1-4 decreased to 38, 59, 60 and 43 g/L respectively). All patients exhibited intestinal wall thickening. Active bleeding sites included the duodenum (3 cases: 2 cases near the duodenal papilla, 1 cases with diffuse duodenal oozing). Emergency endoscopic hemostasis was performed in 3 cases. One patient with diffuse duodenal bleeding required additional glucocortieoid pulse therapy after failed interventional embolization. Three patients stabilized following aggressive treatment of JDM, while 1 case died due to duodenal perforation.Conclusions:Anti-NXP2 antibody-positive JDM patients are prone to gastrointestinal involvement, particularly in chronic cases. Duodenal bleeding is common, with vascular erosion and deep mucosal ulcers posing life-threatening risks. For children with positive anti-NXP2 antibodies who present with abdominal pain and thickened intestinal walls, early endoscopic examination should be conducted as soon as possible to detect digestive tract lesions and provide timely treatment. Patients with severe digestive tract bleeding usually require active treatment for the underlying disease combined with endoscopic hemostasis therapy. Under timely treatment, the prognosis is relatively favorable.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective To establish the content determination method of Zhihuoding granules(ZHDG)by the anti-inflammatory active ingredients and fingerprint.Methods The inflammatory model of BEAS-2B cells was established by LPS(10 μg·mL-1)stimulation for 24 h,and the level of TNF-α in the supernatant was detected by enzyme-linked immunosorbent assay(ELISA).Using the reverse high-performance liquid chromatography(RP-HPLC)of 7 batch ZHDG fingerprint;HPLC was used to determine the content of geniposide and baicalin in granules.Results Compared with LPS Group,ZHDG,prim-O-glucosylcimifugin,5-O-methylvisammioside,baicalin,geniposide,and total polysaccharide extract all significantly decreased TNF-αlevels in BEAS-2B cells induced by LPS(P＜0.05).Fingerprint spectra of 7 batches of ZHDG were established,with a similarity of 1.000 to the reference.A total of 15 peaks were calibrated,and 7 chromatographic peaks were identified.Gardenin and baicalin were selected as the index components of ZHDG for evaluation.The established method was rapid and accurate.Conclusion The method for the determination of baicalin and geniposide in ZHDG are exclusive,accurate,and effective,providing reference for the quality control and clinical application of ZHDG.

Objective:To gain a understanding of the occurrence of cognitive impairment among residents in drinking water-borne endemic fluorosis (drinking water-borne fluorosis) areas, and to study its influencing factors.Methods:In March 2023, a cluster sampling method was used to select local residents aged 18 and above from the drinking water-borne fluorosis areas in Jishan County, Shanxi Province as survey subjects. General demographic data were collected through face-to-face surveys, and a random urine sample was collected once to determine urinary fluoride level. Cognitive function was assessed using the mini-mental state examination (MMSE), and the survey subjects were divided into a cognitive impairment group ( < 27 points) and a control group (27 - 30 points) based on the MMSE scores. A multiple logistic regression model and a decision tree model based on chi-squared automatic interaction detector were constructed to analyze the factors affecting cognitive impairment, and the model fitting effect was evaluated using receiver operating characteristic (ROC) curve.Results:A total of 3 301 subjects were included in the survey, including 2 081 females and 1 220 males. There were 1 515 subjects < 60 years old and 1 786 subjects ≥60 years old, with urinary fluoride level [ M ( Q1, Q3)] of 2.92 (1.78, 4.54) mg/L. There were 1 939 cases in the cognitive impairment group and 1 362 cases in the control group, with a detection rate of 58.74% (1 939/3 301) for cognitive impairment; and the differences in gender, age, education level, marital status, annual household income, alcohol consumption, smoking distribution, and urinary fluoride level between the two groups were statistically significant ( P < 0.05). The results of multiple logistic regression analysis showed that female, ≥60 years, and urinary fluoride > 4.54 mg/L were risk factors for cognitive impairment [ OR (95% CI): 1.25 (1.01, 1.54), 2.66 (2.26, 3.14), 1.32 (1.06, 1.65), P < 0.05]. Education level of primary school or above, annual household income≥12 000 yuan, and mild alcohol consumption were protective factors for cognitive impairment [ OR (95% CI): 0.15 (0.09, 0.25), 0.58 (0.48, 0.68), 0.67 (0.51, 0.87), P < 0.05]. The analysis results of the decision tree model showed that age had the greatest impact on the occurrence of cognitive impairment, followed by annual household income, education level, and urinary fluoride. The areas under the ROC curves of the multiple logistic regression and decision tree model were 0.72 and 0.70 ( P < 0.001), respectively, indicating good model fitting performance. Conclusion:The detection rate of cognitive impairment in residents of drinking water-borne fluorosis areas is relatively high, and age, annual household income, education level, and urinary fluoride are all influencing factors for occurrence of cognitive impairment.

Primary liver cancer(PLC)is a prevalent malignancy with high incidence and mortality rates globally.Hepatocellular carcinoma(HCC),primarily resulting from hepatitis B virus infections in Asia,constitutes most PLC cases.Despite advancements in targeted therapies and localized treatments,the 5-year survival rate remains low,indicating limited efficacy of current approaches.The advent of immunotherapy,particularly immune checkpoint inhibitors(ICIs),has brought new hope for patients with PLC.However,the liver's unique immune microenvironment presents significant challenges to the effectiveness of immunotherapy in HCC.This article reviews recent research developments in liver cancer immunotherapy,focusing on ICIs,combination therapies,emerging treatments,and prospective future directions.

Lung cancer is one of the malignant tumours with the highest morbidity and mortality rates worldwide today, posing a major threat to human health. Accurate diagnosis and standardised treatment play a crucial role in improving the survival rate of lung cancer patients. In recent years, the rapid rise of artificial intelligence (AI) has brought about significant changes in the medical field, providing a new diagnostic and treatment model for lung cancer, and making a series of breakthroughs in lung cancer diagnostic imaging, pathological diagnosis, surgical oncology, radiotherapy, and drug development and treatment. This article introduces the current status of AI application in the field of lung cancer diagnosis and treatment, and extensively discusses the current challenges and future prospects, hoping to provide references and suggestions for future clinical practice.