OBJECTIVE: To propose a machine learning-based method for predicting the trajectories during manual acupuncture manipulation (MAM), aiming to improve the precision and consistency of acupuncture practitioner' operation and provide the real-time suggestions on MAM error correction. METHODS: Computer vision technology was used to analyze the hand micromotion when holding needle during acupuncture, and provide a three-dimensional coordinate description method of the index finger joints of the holding hand. Focusing on the 4 typical motions of MAM, a machine learning-based MAM trajectory predictive model was designed. By integrating the changes of phalangeal joint angle and hand skeletal information of acupuncture practitioner, the motion trajectory of the index finger joint was predicted accurately. Besides, the roles of machine learning-based MAM trajectory predictive model in the skill transmission of acupuncture manipulation were verified by stratified randomized controlled trial. RESULTS: The performance of MAM trajectory predictive model, based on the long short-term memory network (LSTM), obtained the highest stability and precision, up to 98%. The learning effect was improved when the model applied to the skill transmission of acupuncture manipulation. CONCLUSION The machine learning-based MAM predictive model provides acupuncture practitioner with precise action prediction and feedback. It is valuable and significant for the inheritance and error correction of manual operation of acupuncture.
Humans ; Acupuncture Therapy/instrumentation* ; Machine Learning ; Adult ; Male ; Female

OBJECTIVE: To investigate the effect of manual acupuncture manipulations (MAMs) on subcutaneous muscle tissue, by developing quantitative models of "lifting and thrusting" and "twisting and rotating", based on machine learning techniques. METHODS: A depth camera was used to capture the acupuncture operator's hand movements during "lifting and thrusting" and "twisting and rotating" of needle. Simultaneously, the ultrasound imaging was employed to record the muscle tissue responses of the participants. Amplitude and angular features were extracted from the movement data of operators, and muscle fascicle slope features were derived from the data of ultrasound images. The dynamic time warping barycenter averaging algorithm was adopted to align the dual-source data. Various machine learning techniques were applied to build quantitative models, and the performance of each model was compared. The most optimal model was further analyzed for its interpretability. RESULTS: Among the quantitative models built for the two types of MAMs, the random forest model demonstrated the best performance. For the quantitative model of the "lifting and thrusting" technique, the coefficient of determination (R²) was 0.825. For the "twisting and rotating" technique, R² reached 0.872. CONCLUSION Machine learning can be used to effectively develop the models and quantify the effects of MAMs on subcutaneous muscle tissue. It provides a new perspective to understand the mechanism of acupuncture therapy and lays a foundation for optimizing acupuncture technology and designing personalized treatment regimen in the future.
Humans ; Acupuncture Therapy/methods* ; Machine Learning ; Male ; Adult ; Female ; Subcutaneous Tissue/diagnostic imaging* ; Young Adult

Large language models (LLMs) such as ChatGPT, Claude, Llama, and Qwen are emerging as transformative technologies for the diagnosis and treatment of various diseases. With their exceptional long-context reasoning capabilities, LLMs are proficient in clinically relevant tasks, particularly in medical text analysis and interactive dialogue. They can enhance diagnostic accuracy by processing vast amounts of patient data and medical literature and have demonstrated their utility in diagnosing common diseases and facilitating the identification of rare diseases by recognizing subtle patterns in symptoms and test results. Building on their image-recognition abilities, multimodal LLMs (MLLMs) show promising potential for diagnosis based on radiography, chest computed tomography (CT), electrocardiography (ECG), and common pathological images. These models can also assist in treatment planning by suggesting evidence-based interventions and improving clinical decision support systems through integrated analysis of patient records. Despite these promising developments, significant challenges persist regarding the use of LLMs in medicine, including concerns regarding algorithmic bias, the potential for hallucinations, and the need for rigorous clinical validation. Ethical considerations also underscore the importance of maintaining the function of supervision in clinical practice. This paper highlights the rapid advancements in research on the diagnostic and therapeutic applications of LLMs across different medical disciplines and emphasizes the importance of policymaking, ethical supervision, and multidisciplinary collaboration in promoting more effective and safer clinical applications of LLMs. Future directions include the integration of proprietary clinical knowledge, the investigation of open-source and customized models, and the evaluation of real-time effects in clinical diagnosis and treatment practices.
Humans ; Large Language Models ; Tomography, X-Ray Computed

Based on the pharmacokinetics theory, this study investigated the pharmacokinetic characteristics of albiflorin, paeoniflorin, wogonoside, and wogonin in normal and febrile rats and summarized absorption and elimination rules of Dayuanyin in them to provide reference for further development and clinical application of Dayuanyin. Blood samples were taken from the fundus venous plexus of normal and model rats after intragastric administration of Dayuanyin at different time points. The concentration of each substance in blood was determined by ultra performance liquid chromatography-triple quadrupole mass spectrometry(UPLC-MS/MS) technique at different time points. DAS 2.0, a piece of pharmacokinetics software, was used to calculate the pharmacokinetic parameters of each component. The results show that the 4 components had good linear relationship in their respective ranges, and the results of methodological investigation met the requirements. The pharmacokinetic parameters of C_(max), T_(max), t_(1/2), AUC_(0-t), AUC_(0-∞), and MRT_(0-t) were calculated by the DAS 2.0 non-compartmental model. Compared with those in the normal group, C_(max) and AUC_(0-t) of the 4 components in the model group were significantly increased. There were significant differences in the pharmacokinetic characteristics between the normal and model groups, suggesting that the absorption and elimination of Dayuanyin may be affected by the changes of internal environment of the body in different physiological states.
Animals ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Rats, Sprague-Dawley ; Fever/metabolism* ; Tandem Mass Spectrometry ; Chromatography, High Pressure Liquid ; Glucosides/pharmacokinetics* ; Monoterpenes

To elucidate the mechanism by which steaming affects the quality of Curcuma kwangsiensis root tubers, methods such as LSCM, RVA, dual-wavelength spectrophotometry, LF-NMR, and LC-MS were employed to qualitatively and quantitatively detect changes in starch gelatinization characteristics, water distribution, and material composition of C. kwangsiensis root tubers under different steaming durations. Based on multivariate statistical analysis, the correlation between differences in gelatinization parameters, water distribution, and terpenoid material composition was investigated. The results indicate that steaming affects both starch gelatinization and water distribution in C. kwangsiensis. During the steaming process, transformations occur between amylose and amylopectin, as well as between semi-bound water and free water. After 60 min of steaming, starch gelatinization and water distribution reached an equilibrium state. The content of amylopectin, the amylose-to-amylopectin ratio, and parameters such as gelatinization temperature, viscosity, breakdown value, and setback value were significantly correlated(P≤0.05). Additionally, the amylose-to-amylopectin ratio was significantly correlated with total free water and total water content(P≤0.05). Steaming induced differences in the material composition of C. kwangsiensis root tubers. Clustering of primary metabolites in the OPLS-DA model was distinct, while secondary metabolites were classified into 9 clusters using the K-means clustering algorithm. Differential terpenoid metabolites such as(-)-α-curcumene were significantly correlated with zerumbone, retinal, and all-trans-retinoic acid(P<0.05). Curcumenol was significantly correlated with isoalantolactone and ursolic acid(P<0.05), while all-trans-retinoic acid was significantly correlated with both zerumbone and retinal(P<0.05). Alpha-tocotrienol exhibited a significant correlation with retinal and all-trans-retinoic acid(P<0.05). Amylose was extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and α-tocotrienol(P<0.05). Amylopectin was significantly correlated with zerumbone(P<0.05) and extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and 9-cis-retinoic acid(P<0.01). The results provide scientific evidence for elucidating the mechanism of quality formation of steamed C. kwangsiensis root tubers as a medicinal material.
Curcuma/chemistry* ; Starch/chemistry* ; Multivariate Analysis ; Water/chemistry* ; Terpenes/analysis* ; Plant Roots/chemistry* ; Plant Tubers/chemistry* ; Drugs, Chinese Herbal/chemistry*

The polymerase 1 and transcript release factor (PTRF)-cytoplasmic phospholipase A2 (cPLA2) phospholipid remodeling pathway facilitates tumor proliferation in glioma. Nevertheless, blockade of this pathway leads to the excessive activation of oncogenic receptors on the plasma membrane and subsequent drug resistance. Here, CD26/dipeptidyl peptidase 4 (DPP4) was identified through screening of CRISPR/Cas9 libraries. Suppressing PTRF-cPLA2 signaling resulted in the activation of the epidermal growth factor receptor (EGFR) pathway through phosphatidylcholine and lysophosphatidylcholine remodeling, which ultimately increased DPP4 transcription. In turn, DPP4 interacted with EGFR and prevented its ubiquitination. Linagliptin, a DPP4 inhibitor, facilitated the degradation of EGFR by blocking its interaction with DPP4. When combined with the cPLA2 inhibitor AACOCF3, it exhibited synergistic effects and led to a decrease in energy metabolism in glioblastoma cells. Subsequent in vivo investigations provided further evidence of a synergistic impact of linagliptin by augmenting the sensitivity of AACOCF3 and strengthening the efficacy of temozolomide. DPP4 serves as a novel target and establishes a constructive feedback loop with EGFR. Linagliptin is a potent inhibitor that promotes EGFR degradation by blocking the DPP4-EGFR interaction. This study presents innovative approaches for treating glioma by combining linagliptin with AACOCF3 and temozolomide.

Probiotics play a crucial role in colon cancer treatment by metabolizing prebiotics to generate short-chain fatty acids (SCFAs). Colon cancer patients are frequently propositioned to supplement with probiotics to enhance the conversion and utilization of prebiotics. Nevertheless, the delivery and colonization of probiotics is hindered by the harsh conditions of gastrointestinal tract (GIT). Here, we devised a straightforward yet potent modified prebiotic-based "shield" (Gelatin-Inulin, GI), employing dietary inulin and natural polymer gelatin crosslinked via hydrogen bonding for enveloping Lactobacillus reuteri (Lr) to formulate synbiotic hydrogel capsules (Lr@Gl). The GI "shield" serves as a dynamic barrier, augmenting the resistance of Lr to gastric acid and facilitating its bioactivity and adherence in the GIT, synergizing with Lr to elicit an anti-tumor effect. Simultaneously, Lr@GI demonstrates anti-tumor effects by depleting glutathione to release reactive oxygen species, accompanied by the activation of NLRP3 (NOD-like receptor family pyrin domain containing 3), and the induction M1 macrophage polarization. Furthermore, Lr@GI can not only promote the recovery of intestinal barrier but also regulate intestinal flora, promoting the production of SCFAs and further exerting anti-tumor effect. Crucially, Lr@GI also potentiates the anti-tumor effect of 5-Fluorouracil. The construction and synergistic anti-tumor mechanism of synbiotic hydrogel capsules system provide valuable insights for gut microbial tumor therapy.

Purpose: Since 1995, the Korean Gastric Cancer Association (KGCA) has been periodically conducting nationwide surveys on patients with surgically treated gastric cancer. This study details the results of the survey conducted in 2023. Materials and Methods: The survey was conducted from March to December 2024 using a standardized case report form. Data were collected on 86 items, including patient demographics, tumor characteristics, surgical procedures, and surgical outcomes. The results of the 2023 survey were compared with those of previous surveys. Results: Data from 12,751 cases were collected from 66 institutions. The mean patient age was 64.6 years, and the proportion of patients aged ≥71 years increased from 9.1% in 1995 to 31.7% in 2023. The proportion of upper-third tumors slightly decreased to 16.8% compared to 20.9% in 2019. Early gastric cancer accounted for 63.1% of cases in 2023.Regarding operative procedures, a totally laparoscopic approach was most frequently applied (63.2%) in 2023, while robotic gastrectomy steadily increased to 9.5% from 2.1% in 2014.The most common anastomotic method was the Billroth II procedure (48.8%) after distal gastrectomy and double-tract reconstruction (51.9%) after proximal gastrectomy in 2023.However, the proportion of esophago-gastrostomy with anti-reflux procedures increased to 30.9%. The rates of post-operative mortality and overall complications were 1.0% and 15.3%, respectively. Conclusions The results of the 2023 nationwide survey demonstrate the current status of gastric cancer treatment in Korea. This information will provide a basis for future gastric cancer research.

Background and Objectives: In chronic heart failure (HF), natriuretic peptide (NP) levels are higher in atrial fibrillation (AF) compared to sinus rhythm (SR). However, due to the loss of atrial contraction, AF patients are prone to hemodynamic decompensation at earlier stages.Since NP levels reflect disease severity, acutely decompensated AF patients may exhibit lower NP levels compared to SR patients, who retain greater hemodynamic reserve. Methods: We analyzed 5,048 patients with acute HF from the Korea Acute Heart Failure registry with available NP data. NP levels and echocardiographic parameters were compared between AF and SR patients. The association of NP levels with in-hospital and one-year mortality was also assessed according to cardiac rhythm. Results: Brain natriuretic peptide (BNP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) were measured in 2,027 and 3,021 patients, respectively. NP levels were lower in AF than in SR (median BNP, 740 vs. 1,044 pg/mL; median NT-proBNP, 4,420 vs. 5,198 pg/mL), particularly in HF with reduced or mildly reduced ejection fraction. A similar trend was observed regardless of HF onset or etiology. AF patients had smaller left ventricular (LV) end-diastolic diameter and larger left atrial size compared to SR patients. Higher NP tertiles were associated with increased in-hospital and one-year mortality in both groups. Conclusions In acute HF, NP levels are lower in AF than in SR. AF patients also exhibited smaller LV chamber sizes. Nevertheless, NP levels remain strong predictors of outcomes in both AF and SR patients.