Objective: To analyze the space time characteristics of poor vision among primary and secondary school students in Chengdu, in order to provide the reference for formulating myopia prevention and control policies for students. Methods: The data relating to poor vision among primary and secondary school students in Chengdu from 2021 to 2023 were sourced from the Sichuan Students Physical Health Big Data Center. The districts and counties of Chengdu were divided into three circles, including the main urban area, suburban districts and counties, and suburban districts and counties. The Chi square test was used for inter group comparison, and the Cochran-Armitage test was used to analyze the trend of changes. Global and local Moran s I were used to analyze spatial clustering. Results: The detection rates of poor vision among primary and secondary school students in Chengdu from 2021 to 2023 were 62.47%, 61.61% and 60.78%, respectively, showing a decreasing trend ( Z=-32.01, P <0.01). For each year, the higher detection rate of poor vision among students was detected in the higher level of education, and differences were statistically significant ( χ 2=161 549.47, 173 471.87, 233 459.09, P <0.01). The rate of poor vision among primary and secondary school students gradually decreased from the central districts and counties of Chengdu to the surrounding districts and counties for each year, and the differences were statistically significant ( χ 2=299.20, 776.22, 633.16, P <0.01). The spatial autocorrelation analysis showed that the first circle of Chengdu City was mainly characterized by high-high agglomeration ( P <0.01), with the rate of poor vision among primary school students in Wuhou District in 2023 exhibiting a low-high anomaly. The third circle was mainly characterized by low-low aggregation ( P <0.01), while the spatial clusterings of the second circle was not significant ( P >0.05). Conclusions The myopia prevention and control work in Chengdu has achieved preliminary results. It should continue to consolidate existing achievements and implement targeted myopia prevention and control measures based on regional characteristics.

Objective To reveal the scientific output and trends in pulmonary nodules/early-stage lung cancer prediction models. Methods Publications on predictive models of pulmonary nodules/early lung cancer between January 1, 2002 and June 3, 2023 were retrieved and extracted from CNKI, Wanfang, VIP and Web of Science database. CiteSpace 6.1.R3 and VOSviewer 1.6.18 were used to analyze the hotspots and theme trends. Results A marked increase in the number of publications related to pulmonary nodules/early-stage lung cancer prediction models was observed. A total of 12581 authors from 2711 institutions in 64 countries/regions published 2139 documents in 566 academic journals in English. A total of 282 articles from 1256 authors were published in 176 journals in Chinese. The Chinese and English journals which published the most pulmonary nodules/early-stage lung cancer prediction model-related papers were Journal of Clinical Radiology and Frontiers in Oncology, respectively. Chest was the most frequently cited journal. China and the United States were the leading countries in the field of pulmonary nodules/early-stage lung cancer prediction models. The institutions represented by Fudan University had significant academic influence in the field. Analysis of keywords revealed that multi-omics, nomogram, machine learning and artificial intelligence were the current focus of research. Conclusion Over the last two decades, research on risk-prediction models for pulmonary nodules/early-stage lung cancer has attracted increasing attention. Prognosis, machine learning, artificial intelligence, nomogram, and multi-omics technologies are both current hotspots and future trends in this field. In the future, in-depth explorations using different omics should increase the sensitivity and accuracy of pulmonary nodules/early-stage lung cancer prediction models. More high-quality future studies should be conducted to validate the efficacy and safety of pulmonary nodules/early-stage lung cancer prediction models further and reduce the global burden of lung cancer.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective To explore the recognition capabilities of electronic nose combined with machine learning in identifying the breath odor map of benign and malignant pulmonary nodules and Traditional Chinese Medicine (TCM) syndrome elements. Methods The study design was a single-center observational study. General data and four diagnostic information were collected from 108 patients with pulmonary nodules admitted to the Department of Cardiothoracic Surgery of Hospital of Chengdu University of TCM from April 2023 to March 2024. The patients' TCM disease location and nature distribution characteristics were analyzed using the syndrome differentiation method. The Cyranose 320 electronic nose was used to collect the odor profiles of oral exhalation, and five machine learning algorithms including random forest (RF), K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and eXtreme gradient boosting (XGBoost) were employed to identify the exhaled breath profiles of benign and malignant pulmonary nodules and different TCM syndromes. Results (1) The common disease locations in pulmonary nodules were ranked in descending order as liver, lung, and kidney; the common disease natures were ranked in descending order as Yin deficiency, phlegm, dampness, Qi stagnation, and blood deficiency. (2) The electronic nose combined with the RF algorithm had the best efficacy in identifying the exhaled breath profiles of benign and malignant pulmonary nodules, with an AUC of 0.91, accuracy of 86.36%, specificity of 75.00%, and sensitivity of 92.85%. (3) The electronic nose combined with RF, LR, or XGBoost algorithms could effectively identify the different TCM disease locations and natures of pulmonary nodules, with classification accuracy, specificity, and sensitivity generally exceeding 80.00%.Conclusion Electronic nose combined with machine learning not only has the potential capabilities to differentiate the benign and malignant pulmonary nodules, but also provides new technologies and methods for the objective diagnosis of TCM syndromes in pulmonary nodules.

Curcumin is a natural yellow pigment， a natural phenolic antioxidant extracted from the rhizomes of Curcuma longa and Curcumae Rhizoma of the ginger family， with anti-inflammatory， anti-tumor and antioxidant properties. In recent years， it has been found that curcumin also has good antidepressant properties， and it is considered a safe and effective antidepressant potential drug. The mechanism of curcumin’s antidepressant efficacy mainly includes regulating neurotransmitters， modulating the hypothalamic-pituitary-adrenal axis， regulating brain-derived neurotrophic factor， inhibiting neuroinflammation， inhibiting oxidative stress， and regulating gut microbiota， etc.， and there is an overlapping and synergistic therapeutic effect of the above mechanisms. At present， the antidepressant mechanism of curcumin is still not fully understood， and will be combined with multi-omics technology， new formulation technology， and clinical trials to obtain further breakthroughs in the future.

Objective To understand the sleep status in patients with Parkinson's disease (PD), and to explore its relationship with dyskinesia and negative emotions. Methods A total of 308 patients with PD who met the inclusion and exclusion criteria in the hospital from September 2022 to May 2024 were selected as the research subjects. The scores of sleep status [Pittsburgh Sleep Quality Index (PSQI)], dyskinesia [Simplified Fugl-Meyer Motor Assessment (FMA)] and negative emotions [Beck Anxiety Inventory (BAI), Beck Depression Inventory-II (BDI-II)] were analyzed, and the PSQI score was compared among patients with different demographic characteristics. Pearson correlation analysis was performed to analyze the correlation of sleep with dyskinesia and negative emotions in patients with PD. Results The total score of PSQI scale was (6.16±0.97) points in 308 PD patients, of which 208 cases (67.53%) were complicated with sleep disorders. The proportions of female, 61-75 years old, technical secondary school or below, disease course of 4 years and above, Hoehn-Yahr stage IV and unmarried status in the sleep disorder group were higher than those in the non-sleep disorder group (P<0.05). Compared with the non-sleep disorder group, the FMA score in the sleep disorder group was lower (P<0.05) while the BAI score and BDI-II score were higher (P<0.05). Pearson correlation analysis revealed that PSQI was negatively correlated with FMA (r=-0.489, P<0.05), and was positively correlated with BAI and BDI-II (r=0.476, 0.502, P<0.05). Conclusion The incidence rate of sleep disorders in PD patients is high. PSQI is negatively correlated with FMA, and is positively correlated with BAI and BDI-II.

ObjectiveTo explore the effects of the Tai Chi training on bone density， bone turnover markers， and heart rate variability for people with high-risk osteoporosis， and to provide evidence for the prevention of osteoporosis at early stage. MethodsSixty-six cases of people with high risk of osteoporosis were included， and they were divided into 33 cases each in the intervention group and the control group using the random number table method. The control group received osteoporosis health education three times a week， and the intervention group received Tai Chi training under the guidance of a trainer three times a week for 40 mins each time on the basis of the control group， and both groups were intervened for 12 weeks. Dual-energy X-ray absorptiometry was used to measure the bone density of L₁~L₄ vertebrae， bilateral femoral necks and bilateral total hips in the two groups before and after the intervention； enzyme-linked immunosorbent assay was used to determine bone turnover markers before and after the intervention， including pro-collagen type Ⅰ pro-amino-terminal prepropyl peptide （P1NP） and β-collagen type Ⅰ cross-linking carboxy-terminal peptide （β-CTX）. Seven cases with good compliance in the intervention group were selected. After wearing the heart rate sensor， they successively performed Tai Chi training and walking activities recommended by the guideline for 20 mins each， and the heart rate variability （HRV） during exercise was collected， including time-domain indexes such as standard deviation of normal sinus intervals （SDNN）， root-mean-square of the difference between adjacent RR intervals （RMSSD）， frequency-domain metrics such as low-frequency power （LF）， high-frequency power （HF）， and low-frequency/high-frequency power ratio （LF/HF）， as well as nonlinear metrics such as approximate entropy （ApEn）， sample entropy （SampEn）. ResultsFinally， 63 cases were included in the outcome analysis， including 30 cases in the intervention group and 33 cases in the control group. After the intervention， the differences of L₁~L₄ vertebrae， bone density of bilateral femoral neck and bilateral total hip in the intervention group were not statistically significant when compared with those before intervention （P＞0.05）， while the bone density of all parts of the control group decreased significantly compared with that before intervention （P＜0.05）， and the difference in the bone density of the L₁~L₄ vertebrae， bilateral femoral neck， and the right total hip before and after the intervention of the intervention group was smaller than that of the control group （P＜0.05）. The differences in P1NP and β-CTX between groups before and after intervention was not statistically significant （P＞0.05）. Compared with walking exercise， LF decreased， HF increased and LF/HF decreased during Tai Chi exercise （P＜0.05）； the time domain indexes and non-linear indexes between groups had no statistically significant difference （P＞0.05）. ConclusionTai Chi exercise can maintain lumbar， hip， and femoral bone density and improve sympathetic/parasympathetic balance in people at high risk for osteoporosis， but cannot significantly improve bone turnover markers.

Objective To analyze the differences in distribution of traditional Chinese medicine (TCM) syndrome elements and salivary microbiota between the individuals with pulmonary nodules and those without, and to explore the potential correlation between the distribution of TCM syndrome elements and salivary microbiota in patients with pulmonary nodules. Methods We retrospectively recruited 173 patients with pulmonary nodules (PN) and 40 healthy controls (HC). The four diagnostic information was collected from all participants, and syndrome differentiation method was used to analyze the distribution of TCM syndrome elements in both groups. Saliva samples were obtained from the subjects for 16S rRNA high-throughput sequencing to obtain differential microbiota and to explore the correlation between TCM syndrome elements and salivary microbiota in the evolution of the pulmonary nodule disease. Results The study found that in the PN group, the primary TCM syndrome elements related to disease location were the lung and liver, and the primary TCM syndrome elements related to disease nature were yin deficiency and phlegm. In the HC group, the primary TCM syndrome elements related to disease location were the lung and spleen, and the primary TCM syndrome elements related to disease nature were dampness and qi deficiency. There were differences between the two groups in the distribution of TCM syndrome elements related to disease location (lung, liver, kidney, exterior, heart) and disease nature (yin deficiency, phlegm, qi stagnation, qi deficiency, dampness, blood deficiency, heat, blood stasis) (P<0.05). The species abundance of the salivary microbiota was higher in the PN group than that in the HC group (P<0.05), and there was significant difference in community composition between the two groups (P<0.05). Correlation analysis using multiple methods, including Mantel test network heatmap analysis and Spearman correlation analysis and so on, the results showed that in the PN group, Prevotella and Porphyromonas were positively correlated with disease location in the lung, and Porphyromonas and Granulicatella were positively correlated with disease nature in yin deficiency (P<0.05). Conclusion The study concludes that there are notable differences in the distribution of TCM syndrome elements and the species abundance and composition of salivary microbiota between the patients with pulmonary nodules and the healthy individuals. The distinct external syndrome manifestations in patients with pulmonary nodules, compared to healthy individuals, may be a cascade event triggered by changes in the salivary microbiota. The dual correlation of Porphyromonas with both disease location and nature suggests that changes in its abundance may serve as an objective indicator for the improvement of symptoms in patients with yin deficiency-type pulmonary nodules.

OBJECTIVE: To explore the rules of acupoint selection and compatibility of acupuncture and moxibustion in treatment of chronic cough using data mining. METHODS: The ancient and modern medical record cloud platform, and the databases, i.e. CNKI, Wanfang, VIP, EMbase, Web of Science and PubMed, were searched to screen the ancient and modern literature on acupuncture and moxibustion treatment of chronic cough. The prescription database was established for acupuncture and moxibustion treatment of chronic cough, and the analysis conducted on the frequency and use percentage in the aspects of intervention measures, acupoint selection, acupoint distribution, meridian tropism, special points and acupoint combination, as well as the association rules and clustering rules of acupoint selection. The subgroup analysis was performed in accordance with the etiology of chronic cough and intervention measures. RESULTS: A total of 106 articles were included and 158 prescriptions were extracted. The intervention measures were acupuncture, moxibustion, herbal medication and the combination of several measures. The high-frequency acupoints included Feishu (BL13), Zusanli (ST36), Dazhui (GV14), Pishu (BL20), Danzhong (CV17), Shenshu (BL23), Lieque (LU7), Dingchuan (EX-B1), Tiantu (CV22), and Fenglong (ST40). These acupoints are mainly distributed on the back, lumbar region, chest and abdomen. The involved meridians were bladder meridian of foot-taiyang, conception vessel, and lung meridian of hand-taiyin. The special points covered back-shu points, crossing points and five-shu point. Regarding the compatibility of acupoints, the combination of upper and lower points, and the combination of front and back points were predominant in treatment. The analysis of association rules found that the support of Feishu (BL13)→Zusanli (ST36) was the highest; the cluster analysis obtained 8 clusters of acupoints. The acupoint compatibility and overall rules were similar when cough variant asthma (CVA) or the mixed reasons were involved, and the local treatment approach was adopted if the etiology of disease was related to upper airway cough syndrome (UACS) and gastroesophageal reflux cough (GERC). The acupoint selection was similar among different intervention measures. When two kinds of measures were combined in treatment, Feishu (BL13), Pishu (BL20) and Zusanli (ST36) were the most common. CONCLUSION In treatment with acupuncture and moxibustion for chronic cough, the acupoints are selected on the affected local area, depending on syndrome differentiation, and focusing on back-shu points. The main acupoints are Feishu (BL13), Zusanli (ST36), Dazhui (GV14), Pishu (BL20), Danzhong (CV17) and Shenshu (BL23). The combined therapy is dominant with acupuncture, moxibustion and herbal medicine involved.
Acupuncture Points ; Moxibustion/history* ; Humans ; Cough/history* ; Acupuncture Therapy/history* ; Chronic Disease/therapy* ; Data Mining ; History, Ancient ; Meridians ; Chronic Cough

BACKGROUND: Temozolomide (TMZ) resistance is a significant challenge in treating glioblastoma (GBM). Collagen remodeling has been shown to be a critical factor for therapy resistance in other cancers. This study aimed to investigate the mechanism of TMZ chemoresistance by GBM cells reprogramming collagens. METHODS: Key extracellular matrix components, including collagens, were examined in paired primary and recurrent GBM samples as well as in TMZ-treated spontaneous and grafted GBM murine models. Human GBM cell lines (U251, TS667) and mouse primary GBM cells were used for in vitro studies. RNA-sequencing analysis, chromatin immunoprecipitation, immunoprecipitation-mass spectrometry, and co-immunoprecipitation assays were conducted to explore the mechanisms involved in collagen accumulation. A series of in vitro and in vivo experiments were designed to assess the role of the collagen regulators prolyl 4-hydroxylase subunit alpha 1 (P4HA1) and yes-associated protein (YAP) in sensitizing GBM cells to TMZ. RESULTS: This study revealed that TMZ exposure significantly elevated collagen type I (COL I) expression in both GBM patients and murine models. Collagen accumulation sustained GBM cell survival under TMZ-induced stress, contributing to enhanced TMZ resistance. Mechanistically, P4HA1 directly binded to and hydroxylated YAP, preventing ubiquitination-mediated YAP degradation. Stabilized YAP robustly drove collagen type I alpha 1 ( COL1A1) transcription, leading to increased collagen deposition. Disruption of the P4HA1-YAP axis effectively reduced COL I deposition, sensitized GBM cells to TMZ, and significantly improved mouse survival. CONCLUSION P4HA1 maintained YAP-mediated COL1A1 transcription, leading to collagen accumulation and promoting chemoresistance in GBM.
Temozolomide ; Humans ; Glioblastoma/drug therapy* ; Animals ; Mice ; Cell Line, Tumor ; Drug Resistance, Neoplasm/genetics* ; YAP-Signaling Proteins ; Hydroxylation ; Dacarbazine/pharmacology* ; Adaptor Proteins, Signal Transducing/metabolism* ; Transcription Factors/metabolism* ; Collagen/biosynthesis* ; Collagen Type I/metabolism* ; Prolyl Hydroxylases/metabolism* ; Antineoplastic Agents, Alkylating/therapeutic use*