OBJECTIVE To explore the transformation of the dispensing and drug pickup process in traditional Chinese medicine pharmacy （TCM Pharmacy） in our hospital based on data-intelligence-driven， aiming to improve pharmacists’ work efficiency and patients’ drug pickup experience. METHODS Value stream mapping and journey mapping were used to systematically identify non-value-added links in pharmacists’ dispensing process and key pain points in patients’ drug pickup under the traditional process. An intelligent dispensing and drug pickup system for the TCM Pharmacy was developed based on the C# and Android television platforms， and a machine-learning model was adopted to predict patients’ drug pickup waiting time. A comprehensive evaluation was performed from three perspectives： system performance， prediction accuracy， and satisfaction of pharmacists and patients. RESULTS The system successfully streamlined non-value-added links such as “waiting for writing on the board” and “searching for drugs”， and realized multimodal dynamic prompts of dispensing status through auditory （number calling） and visual （television terminal） channels. The constructed model for predicting drug pickup waiting time exhibited good fitting degree and generalization ability （mean absolute error＝4.28 min， R 2 ＝0.882）. The comprehensive satisfaction scores of pharmacists and patients in the traditional mode were significantly increased from （70.99±1.74） and （73.58±1.98） to （90.02±1.30） and （88.61±2.08） in the new system， respectively （ P ＜0.01）. CONCLUSIONS The transformation of the intelligent drug dispensing and pickup system for TCM pharmacy based on data-intelligence-driven effectively improves the efficiency of pharmacists’ dispensing work， realizes process transparency and waiting time predictability， and significantly enhances patients’ drug pickup experience.

Esophageal cancer is a prevalent malignant tumor of the digestive tract in China, and radical surgery remains the cornerstone of its comprehensive treatment. However, multifactorial challenges such as postoperative gastrointestinal tract reconstruction, traumatic stress, and tumor-related metabolic disturbances render esophageal cancer patients highly susceptible to malnutrition. Perioperative nutritional support therapy plays a crucial role in enhancing surgical safety, improving clinical outcomes, and elevating patients' quality of life by regulating metabolic homeostasis, preserving organ function, and optimizing the immune microenvironment. This article reviews the mechanisms underlying malnutrition in esophageal cancer, methods for nutritional status assessment, and precision intervention pathways based on multi-omics evaluations. The aim is to strengthen clinicians' awareness of standardized perioperative nutritional management for esophageal cancer patients and promote its clinical implementation, thereby facilitating postoperative recovery and improving long-term quality of life.

The daoqi tongjing （导气同精） acupuncture method， is an important acupuncture method focusing on regulating qi mechanism in traditional Chinese medicine （TCM） derived from Inner Canon of Yellow Emperor （《黄帝内经》）， and is characterized by a relatively comprehensive theoretical framework and operational principles. Its core theory is "slow insertion and slow withdrawal is called daoqi （guiding qi）， supplementation and draining without visible manipulation is called tongjing （harmonizing essence）". This paper conducts a systematic analysis from four dimensions including theoretical origin， connotation analysis， clinical application， and operation standard， revealing the therapeutic essence of this acupuncture method for the pathogenesis of "qi disorder"， clarifying its unique advantages in treating chaos syndromes， pain syndromes， diseases in special parts， and complex and difficult diseases. By combing literature and summarizing clinical experience， the operation process and technical essentials are standardized. The research aims to provide theoretical support for the modern clinical application of the daoqi tongjing acupuncture method and promote its standardized inheritance and innovative development in contemporary acupuncture practice.

Objective To externally validate a prediction model based on clinical and CT imaging features for the preoperative identification of high-grade patterns (HGP), such as micropapillary and solid subtypes, in early-stage lung adenocarcinoma, in order to guide clinical treatment decisions. Methods This study conducted an external validation of a previously developed prediction model using a cohort of patients with clinical stage ⅠA lung adenocarcinoma from the Fourth Hospital of Hebei Medical University. The model, which incorporated factors including tumor size, density, and lobulation, was assessed for its discrimination, calibration performance, and clinical impact. Results A total of 650 patients (293 males, 357 females; age range: 30-82 years) were included. The validation showed that the model demonstrated good performance in discriminating HGP (area under the curve>0.7). After recalibration, the model's calibration performance was improved. Decision curve analysis (DCA) indicated that at a threshold probability>0.6, the number of HGP patients predicted by the model closely approximated the actual number of cases. Conclusion This study confirms the effectiveness of a clinical and imaging feature-based prediction model for identifying HGP in stage ⅠA lung adenocarcinoma in a clinical setting. Successful application of this model may be significant for determining surgical strategies and improving patients' prognosis. Despite certain limitations, these findings provide new directions for future research.

Objective:To evaluate the utility of pulse oximetry-derived parameters—specifically, the pulse oximetry plethysmographic waveform area under the curve (POP AUC) and the peripheral perfusion index (PPI)—in assessing disease severity and predicting prognosis in patients with sepsis. Methods:In this prospective descriptive study, 68 patients with sepsis were categorized based on illness severity into septic shock and non-shock groups, and by 28-day outcome into survival and non-survival groups. POP AUC, PPI, and lactate (Lac) levels were recorded at 0, 24, 48, 72, and 96 hours after admission. APACHEⅡ and SOFA scores were calculated within the first 24 hours. The prognostic value of these parameters was evaluated. Results:Significant differences were observed between the septic shock and non-shock groups in POP AUC, PPI, Lac (all P < 0.05 except at 96 h), APACHEⅡ, and SOFA scores (all P < 0.05). These differences were most pronounced at admission: POP AUC0 (2475.1 ± 899.0) vs. (4260.3 ± 1028.5), PPI 0 (0.78 ± 0.74) vs. (3.13 ± 2.18), Lac 0 (4.95 ± 4.32) vs. (2.07 ± 1.55), APACHE Ⅱ (16.78 ± 5.59) vs. 11.82 ± 4.89), and SOFA (8.89 ± 3.25) vs. (5.06 ± 2.60). Optimal prognostic cut-off values were 2741.43 for POP AUC, 0.97 for PPI, 2.05 for Lac, 12.5 for APACHEⅡ, and 5.5 for SOFA. ROC curve analysis showed that at 24 hours, POP AUC and PPI had significantly larger AUC values than Lac ( P < 0.05), while no significant differences were found among other parameters. Significant differences between non-survivors and survivors were also found in POP AUC, PPI (at 0, 24, and 48 h), APACHE II, and SOFA (all P < 0.05). No significant differences were observed in PPI (72 h and 96 h) or Lac between the two outcome groups. Conclusions:POP AUC and PPI, as derived from pulse oximetry, are non-inferior to Lac, SOFA, and APACHEⅡ scores in evaluating disease severity and predicting 28-day mortality in sepsis patients. These parameters show promise as practical and non-invasive tools for clinical assessment in sepsis.

Objective:To construct a personalized service platform based on Internet of Things technique of medical equipment for rehabilitation information,so as to analyze the application effect of that in the management for rehabilitation information of patients.Methods:Based on the Internet of Things technique of medical equipment,a personalized service platform was constructed to conduct intelligent management for rehabilitation information of patients through sensor technique,wireless communication technique and big data analysis technique.A total of 112 patients who received treatment in the department of rehabilitation medicine of Dushan Hospital,Nanyang City Hospital of Traditional Chinese Medicine from February to December 2023 were selected,and they were divided into control group which adopted conventional platform to manage rehabilitation information,and observation group which adopted personalized service platform based on IoTs technique of medical equipment for rehabilitation information to manage rehabilitation information,with 56 cases in each group.A self-made questionnaire was used to investigate the satisfaction of patients of two groups for the service platform of rehabilitation information,and the acceptance scores of maintainers for platform,relevant operators,doctors and nurses for different service platform.The service efficiency and success of rehabilitation treatment of different service platforms were compared.Results:53 patients satisfied for the service platform of rehabilitation information(94.64%)in the observation group,which was higher than that in the control group,and the difference was statistically significant(x2=13.187,P＜0.05).The scores of convenience,flexibility and continuity of patients of observation group were respectively(94.74±3.36),(94.57±4.12)and(93.65±4.02)for the platform,which were higher than those of control group,and the differences were statistically significant(t=14.279,13.604,13.553,P＜0.05).The acceptance scores of maintainers for platform,relevant operators,doctors and nurses were respectively(91.69±2.11),(94.52±3.65),(93.87±4.58)and(94.74±3.36)for the personalized service platform for rehabilitation information of the observation group,which were higher than those in the control group,and the differences were statistically significant(t=15.280,13.236,12.373,14.279,P＜0.05).The waiting time,appointment time and treatment cycle of patients in observation group were respectively(4.65±2.01)min,(3.21±1.03)d and(13.02±1.02)months,which were shorter than those of control group,and the differences were statistically significant(t=9.768,11.401,12.300,P＜0.05).Conclusion:The personalized service platform based on the IoTs technique of medical equipment for rehabilitation information can take doctors to timely adjust rehabilitation programs by combining the dynamic changes of patients'information,and formulate targeted rehabilitation guidance,and provide effective rehabilitation treatment for patients,and reduce waiting time of patient,and shorten the rehabilitation cycle.

Objective:To explore the movement patterns and factors influencing lung tumors tracked using the M6 cyberknife stereotactic radiotherapy(SRT)system and to provide a reference for the implementation of precise stereotactic radiotherapy for lung tumors.Method:A retrospective analysis was conducted on 29 patients with lung tumors who were treated using x-sight lung tracking technology and the M6 cyberknife SRT system at Tianjin Medical University Cancer Institute&Hospital,from January 2022 to August 2024.The tumor location and volume,irradiation dose,isodose line,and number of divisions were recorded.Lung tumor location and SPSS 26.0 software were used to analyze the movement amplitude of tumors in the left and right(LFT/RGT,LR)directions,the anterior-posterior(ANT/POS,AP)direction,and the superior-inferior(SUP/INF,SI)direction.The results are expressed as the mean±standard deviation((x)±s)mm,and a t-test was used for inter-group comparisons.Multiple linear regression was used to analyze the effects of factors such as age,gender,tumor location(upper and lower lungs),and tumor volume on the amplitudes of the lung tumor movements.Result:The average motion amplitudes in the LR direc-tions,AP direction,and SI direction of the tumor target areas were(3.5±1.8)mm,(5.3±1.7)mm,and(7.3±5.4)mm for the upper lung,based on 19 cases,and(3.1±1.6)mm,(4.5±2.2)mm,and(12.2±4.4)mm for the lower lung,based on 10 cases,respectively.There was a statistic-ally significant difference(P=0.015 3)in the amplitude of movements between the lower and upper lung tumors in the SI direction.The lung tumor movement amplitude in the SI direction was influenced by tumor location(P=0.035),and the movement amplitudes in the LR direc-tions and the AP direction were not related to factors such as gender,age,tumor location,and tumor volume.Conclusions:The lung tumor movement amplitudes for the different locations varied depending on the respiratory movement shown by the patient.In the SI direction,the movement amplitude of the lower lung tumors was greater than that of upper lung tumors,and this was due to tumor location effects.The movement amplitudes of the lower and upper lung tumors were similar in the LR directions and AP directions.Furthermore,movement amplitude was not affected by gender,age,tumor location,and tumor volume.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

The chemical constituents were systematically separated from the roots of Berberis polyantha by various chromatographic methods, including silica gel column chromatography, HP20 column chromatography, polyamide column chromatography, reversed-phase C_(18) column chromatography, and preparative high-performance liquid chromatography. The structures of the compounds were identified by physicochemical properties and spectroscopic techniques(1D NMR, 2D NMR, UV, MS, and CD). Four phenylpropanoids were isolated from the methanol extract of the roots of B. polyantha, and they were identified as(2R)-1-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone-O-β-D-glucopyranoside(1), methyl 4-hydroxy-3,5-dimethoxybenzoate(2),(+)-syringaresinol(3), and syringaresinol-4-O-β-D-glucopyranoside(4). Compound 1 was a new compound, and other compounds were isolated from this plant for the first time. The anti-inflammatory activity of these compounds was evaluated based on the release of nitric oxide(NO) in the culture of lipopolysaccharide(LPS)-induced RAW264.7 macrophages. At a concentration of 10 μmol·L~(-1), all the four compounds inhibited the LPS-induced release of NO in RAW264.7 cells, demonstrating potential anti-inflammatory properties.
Plant Roots/chemistry* ; Animals ; Mice ; Berberis/chemistry* ; RAW 264.7 Cells ; Macrophages/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; Nitric Oxide/metabolism* ; Molecular Structure ; Anti-Inflammatory Agents/isolation & purification*