Digital and intelligent technologies serve as the core engine driving the inheritance of the essence and the innovation while upholding the fundamentals of traditional Chinese medicine（TCM）. Currently， the digital and intelligent transformation of TCM has undergone four developmental stages， exhibiting inherent characteristics such as long-term inevitability， objective standardization， and ecological evolution. By introducing quantitative metrics， digital and intelligent technologies have achieved breakthroughs in TCM knowledge inheritance and innovation， clinical diagnosis and treatment， and herbal medicine supply. The practical applicability of methodological innovations has been empirically validated， though significant disparities exist in technological adaptability and application depth across different fields. Overall， the digital and intelligent transformation of TCM remains in its nascent stage， grappling with multiple structural challenges：weak data foundations， inadequate technological adaptability， incomplete institutional frameworks， shortages of multidisciplinary talent， lagging policies and regulations， and urban-rural digital divide. In order to foster sustainable development and modernization of TCM， this paper establishes a six-dimensional collaborative governance framework of encompassing data， technology， organization， institutions， environment and ethics， which is rooted in data governance and digital governance theories. Future efforts should center on standardization， integration， and ecosystem development to build a data and technology foundation. Focus should be placed on deepening innovation and application of key TCM-specific technologies， while simultaneously strengthening interdisciplinary talent cultivation， improving institutional mechanisms and policy frameworks， and increasing support for rural areas. By adopting a people-centered and technology-empowered approach， we can overcome developmental constraints and unleash the powerful driving force of digital and intelligent technologies for the inheritance of TCM.

Purpose: The aim of this study is to determine the impact of solute carrier family 3 member 2 (SLC3A2) on the malignant phenotype of gliomas and its role in regulating ferroptosis sensitivity. Materials and Methods: The malignant phenotype of glioma was assessed by cell proliferation assay, colony formation assay, EdU assay, wound healing, and Transwell experiments. We further validated the impact of reduced SLC3A2 expression on the sensitivity to ferroptosis in glioma cells through Cell Counting Kit-8 assays, flow cytometry, western blotting, and transmission electron microscopy. Western blot was used to explore how SLC3A2 affects glioma sensitivity to ferroptosis through the AKT/NF-E2-related factor 2 (NRF2)/glutathione peroxidase 4 (GPX4) axis. By establishing a subcutaneous xenograft tumor model in BALB/c-nude mice, we investigated the growth of tumors following the knockout of SLC3A2 in glioma cells. Results: Downregulation of SLC3A2 suppressed the malignant phenotype of glioma by blocking the cell cycle and epithelial-mesenchymal transition processes. On the other hand, loss of SLC3A2 not only downregulated SLC7A11 but also prevented the activation of the AKT/NRF2/GPX4 axis. These lead to increased accumulation of reactive oxygen species and lipid peroxides, ultimately enhancing the susceptibility of glioma to ferroptosis. Conclusion Our findings suggest that SLC3A2 is an oncogene in gliomas, promoting their occurrence and development. It plays a critical role in ferroptosis resistance through the AKT/NRF2/GPX4 axis.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

Objective To establish a method for rapid detection of tramadol in urine by liquid-liquid extraction（LLE）-surface-enhanced Raman spectroscopy （SERS）. Methods Tramadol was extracted from urine with chloroform∶isopropyl alcohol （9∶1） extractant and detected in urine samples by enhanced Raman spectroscopy （wavelength 785 nm）. Results The quantitative curve of tramadol was Y=204.35 X−465.62, r=0.9952, and the linear range was 1-100 μg/ml. The detection limit of tramadol by this method （S/N=3） was 0.53 μg/ml. The sensitivity of SERS was higher than that of conventional methods, and it had reasonable reproducibility. Conclusion This method is simple, efficient and economical, and can be used for qualitative and quantitative analysis of tramadol personalized medicine.

Objective To investigate the seroprevalence of antibody against Toxoplasma gondii among patients with hematological malignancies, and compare it with that among health individuals, so as to provide insights into unraveling the pathogenesis of hematological malignancies. Methods A total of 225 patients with hematological malignancies in Department of Hematology, Xuzhou Central Hospital and 300 healthy individuals in the same hospital were enrolled from 2017 to 2024. Blood samples were collected from all subjects, and the serum IgG and IgM antibodies against T. gondii were detected using chemiluminescent immunoassay. Demographic and clinical features were collected from patients with hematological malignancies, including gender, age, contact with cats, consumption of raw or undercooked meat, type of malignancy, clinical symptoms, blood transfusion and treatment, and the seroprevalence of anti-T. gondii antibody was compared among patients with different characteristics. Results The age (t = 0.72, P > 0.05) and gender (χ² = 0.93, P > 0.05) were compared between patients with hematological malignancies and healthy individuals. The seroprevalence of T. gondii infection was 20.89% among patients with hematological malignancies and 4.33% among healthy individuals (χ² = 34.81, P < 0.01), and the seroprevalence of anti-T. gondii IgG antibody was 20.89% among patients with hematological malignancies and 4.33% among healthy individuals (χ² = 34.81, P < 0.01), while there was no significant difference in the seroprevalence of anti-T. gondii IgM antibody between patients with hematological malignancies and healthy individuals (1.33% vs. 0; corrected χ² = 2.02, P > 0.05). The seroprevalence of T. gondii infection was 23.08% among patients with leukemia, 16.67% among patients with lymphoma, 19.23% among patients with multiple myeloma, 24.00% among patients with myeloproliferative neoplasm, and 26.09% among patients with myelodysplastic syndrome (χ² = 1.44, P > 0.05), and was all higher than among healthy individuals (corrected χ² = 23.92, 10.74, 13.76, 12.84 and 14.54; all P values < 0.01). In addition, there were no significant differences in the detection of anti-T. gondii antibody among patients with hematological malignancies in terms of gender, age, contact with cats, consumption of raw or undercooked meat, chemotherapy or blood transfusion (χ² = 0.76, 1.97, 0, 2.81, 2.38 and 0.66; all P values > 0.05). Conclusions There is a high risk of T. gondii infection among patients with hematological malignancies, and intensified surveillance of T. gondii infection is recommended among patients with hematological malignancies.

ObjectiveTo compare colonoscopy compliance rates under different screening strategies, to explore ways to enhance colonoscopy compliance among residents with colorectal carcinoma. MethodsResidents aged between 50‒80 years were recruited through extensive community outreach and voluntary participation. A total of 210 630 residents who participated in the colorectal carcinoma screening program in Jiading District, Shanghai, between 2013 and 2019 were selected as the research subjects. All subjects underwent a colorectal carcinoma risk assessment questionnaire survey and two fecal occult blood tests (FOBT). Positive results in the initial screening were defined as a positive questionnaire survey or a positive result in at least one FOBT. Participants with positive initial screening results were advised to undergo colonoscopy screening in a hospital. Colonoscopy results were collected from hospital reports and physician follow-ups. Compliance with colonoscopy was analyzed under different screening strategies to identify possible factors influencing residents’ willingness to undergo the procedure. ResultsA total of 21 403 individuals (10.16%) were identified as positive with the questionnaire survey, 31 595 individuals (15.00%) tested positive with at least one FOBT. Combined questionnaire and FOBT positivity was observed in 3 501 individuals (1.66%). Among the 48 453 individuals with positive initial screening results, 17 230 (35.56%) underwent colonoscopy, and a total of 315 cases of colorectal cancer were detected. The sensitivity, specificity value of FOBT initial screening were 83.81% and 84.66%, respectively. According to the combined risk assessment and FOBT initial screening preliminary screening, the lowest colonoscopy compliance rate (25.63%) was observed among individuals with only a positive questionnaire, and the highest compliance rate (52.55%) was among those with both positive questionnaire survey and two positive FOBT results. Multivariate analysis revealed that FOBT positivity had the greatest impact on colonoscopy compliance. Those with one positive FOBT test result were 2.64 times more likely to undergo colonoscopy screening than those with negative FOBT results, while individuals with two positive FOBT results were 3.18 times more likely to do so. After adjusting for FOBT results, individuals with positive questionnaire survey results were 1.43 times more likely to undergo colonoscopy screening than those with negative results (95%CI: 1.34‒1.52). Compared to questionnaire-based risk assessment, FOBT results were more influential in determining compliance with colonoscopy. ConclusionThe choice of initial screening method significantly impacts residents’ compliance with colonoscopy. While implementing colorectal carcinoma screening programs, it is necessary to strictly adhere to screening protocols, including risk assessment and FOBT. Additionally, efforts should be made to raise public awareness, encouraging residents to actively participate in risk assessments and FOBT, thereby improving their compliance with colonoscopy.

The establishment of modern biliary surgery system, alongside pivotal scientific paradigm shifts, has heralded a new era featured by precision, personalization, life-cycle care, and multidisciplinary management in the treatment of both benign and malignant biliary diseases. However, two formidable challenges persist in haunting the treatment of biliary diseases: (1) The refinement of surgical techniques has reached a plateau in reducing the disability associated with benign biliary conditions and in improving survival outcomes in biliary tract cancers; (2) Traditional evidence-based clinical studies have shown limited power in addressing complex dilemmas, such as determining whether to excise or preserve pathological gallbladders or selecting the optimal biliary drainage strategy. Consequently, the authors propose the conceptual framework of “biliary ecosystem”. In this model, diverse and abundant cholangiocytes represent forest, while blood vessels, nerves, and lymphatic vessels serve as nurturing soil, biliary stem cells function as seeds, bile flows like river network, and hepatocytes mark the river′s origins. Both benign and malignant biliary diseases exhibit significant spatiotemporal dynamics. The bile ducts form the “macro” environment, bile constitutes the “sub-macro” environment, and diverse cellular niches create the microenvironment. Specific pathological biliary conditions are shaped by intricate regulatory mechanisms that operate across these three tiers. Within the biliary ecosystem, cellular subpopulations exist remarkable diversity with states of homeostasis, oscillation, perturbation, or imbalance, underpinned by complex signaling networks. This holistic approach allows us to reframe and critically examine the pressing scientific issues confronting biliary tract diseases. Based on this framework, the authors distill key scientific questions and offer preliminary recommendations for embracing the paradigm shift. The authors anticipate that this conceptual model will promote interdisciplinary integration and accelerate clinical and translational researches.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

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.

The establishment of modern biliary surgery system, alongside pivotal scientific paradigm shifts, has heralded a new era featured by precision, personalization, life-cycle care, and multidisciplinary management in the treatment of both benign and malignant biliary diseases. However, two formidable challenges persist in haunting the treatment of biliary diseases: (1) The refinement of surgical techniques has reached a plateau in reducing the disability associated with benign biliary conditions and in improving survival outcomes in biliary tract cancers; (2) Traditional evidence-based clinical studies have shown limited power in addressing complex dilemmas, such as determining whether to excise or preserve pathological gallbladders or selecting the optimal biliary drainage strategy. Consequently, the authors propose the conceptual framework of “biliary ecosystem”. In this model, diverse and abundant cholangiocytes represent forest, while blood vessels, nerves, and lymphatic vessels serve as nurturing soil, biliary stem cells function as seeds, bile flows like river network, and hepatocytes mark the river′s origins. Both benign and malignant biliary diseases exhibit significant spatiotemporal dynamics. The bile ducts form the “macro” environment, bile constitutes the “sub-macro” environment, and diverse cellular niches create the microenvironment. Specific pathological biliary conditions are shaped by intricate regulatory mechanisms that operate across these three tiers. Within the biliary ecosystem, cellular subpopulations exist remarkable diversity with states of homeostasis, oscillation, perturbation, or imbalance, underpinned by complex signaling networks. This holistic approach allows us to reframe and critically examine the pressing scientific issues confronting biliary tract diseases. Based on this framework, the authors distill key scientific questions and offer preliminary recommendations for embracing the paradigm shift. The authors anticipate that this conceptual model will promote interdisciplinary integration and accelerate clinical and translational researches.