Parkinson's disease （PD） is a common neurodegenerative disorder characterized by motor impairments， with its pathological mechanisms involving multiple processes such as the degeneration of dopaminergic neurons and the abnormal aggregation of α-synuclein. Current Western medical treatments face challenges including diminished long-term efficacy and motor complications. In recent years， Traditional Chinese Medicine （TCM） has demonstrated advantages in the prevention and treatment of PD through its systematic regulatory capabilities， featuring multi-component， multi-target， and multi-pathway approaches.This article systematically reviews the roles of seven key signaling pathways-NF-κB， AMPK/mTOR， PI3K/Akt， MAPKs， Nrf2/ARE， Wnt/β-catenin， and BDNF/TrkB-in the pathological process of PD and the regulatory mechanisms of TCM. Research indicates that active ingredients of Chinese herbs and compound formulations can synergistically modulate these pathways， exerting comprehensive effects in inhibiting neuroinflammation， alleviating oxidative stress， promoting autophagy to clear abnormal proteins， and enhancing neurotrophic support. These signaling pathways form a complex regulatory network through crosstalk among key nodal molecules， constituting an intricate regulatory system in PD pathology. The multi-target intervention characteristics of TCM align well with this network-based regulatory requirement， achieving integrated anti-inflammatory， antioxidant， autophagy-regulating， and neurorestorative effects through synergistic multi-pathway modulation. This article systematically outlines the mechanisms of TCM in the coordinated regulation of multiple pathways， providing a theoretical basis for elucidating the pathological process of PD and the intervention mechanisms of TCM， while also offering new perspectives and directions for modern research on TCM in the prevention and treatment of PD.

ObjectiveThis paper aims to investigate the differential mechanisms underlying the staged therapeutic effects of Qijia Rougan formula on liver fibrosis using proteomic technology. MethodsThe staged rat model of liver fibrosis was established by subcutaneous injection of carbon tetrachloride （CCl₄） and olive oil. One hundred and four SD rats were randomized into thirteen groups：a normal group，a two-week model group，a four-week model group，a six-week model group，an eight-week model group，a two-week Qijia Rougan formula group，a four-week Qijia Rougan formula group，a six-week Qijia Rougan formula group，an eight-week Qijia Rougan formula group，a two-week compound Biejia Ruangan tablet group，a four-week Compound Biejia Ruangan Tablet group，a six-week Compound Biejia Ruangan Tablet group，and an eight-week compound Biejia Ruangan tablet group. After two weeks of drug intervention，liver tissue and abdominal aortic blood samples were collected from the rats for testing. Hematoxylin-eosin （HE） staining，Masson staining，and Picro Sirius red staining were used to observe pathological damage and collagen fiber deposition in liver tissues. Immunohistochemistry （IHC） was employed to detect the contents of fibrosis markers in liver tissues. The contents of liver function indicators in the serum were measured using a fully automated biochemical analyzer，and the levels of liver fibrosis indicators in the serum were assessed by enzyme-linked immunosorbent assay （ELISA）. Liver tissues from the normal group，each model group，and each Qijia Rougan formula group were subjected to label-free quantitative proteomic analysis to identify differential proteins among the groups，with key proteins validated by Western blot. Finally，bioinformatics analysis was performed on the differential proteins. Results（1） The staged rat model of liver fibrosis constructed with CCl₄ and olive oil showed pathological results at the 2^nd，4^th，6^th，and 8^th weeks of modeling that were consistent with the Metavir standards for the F1，F2，F3，and F4 stages. Compared with those in the normal control group，the protein expressions of α-smooth muscle actin （α-SMA） and Collagen Ⅰ were significantly increased in each stage （P<0.05）. The levels of liver function indicators in the serum，including alanine aminotransferase （ALT），aspartate aminotransferase （AST），alkaline phosphatase （ALP），direct bilirubin （DBIL），and total bilirubin （TBil） in each model group，were significantly elevated in each stage （P<0.01）. The levels of liver fibrosis indicators in the serum，including procollagen Ⅲ peptide （PⅢP），type Ⅳ collagen（Ⅳ-C），hyaluronic acid （HA），and laminin （LN） in each model group，were significantly increased in each stage （P<0.05，P<0.01）. This study successfully established a staged rat model of liver fibrosis. （2） Compared with the model groups at each stage，the administration groups showed a reduction in hepatocyte ballooning degeneration，a more orderly arrangement of hepatocytes，and a decrease of inflammatory cell infiltration. The blue-stained collagen fibers became significantly thinner and finer，with reduced and narrowed fibrous septa. The areas of collagen fibers and Picro Sirius red staining were reduced （P<0.05）. The positive areas of α-SMA and Collagen Ⅰ expression were significantly decreased （P<0.05）. The levels of ALT，AST，ALP，DBIL，and TBil in the rats of the model groups at each stage were significantly reduced （P<0.05，P<0.01）. The levels of PⅢP，Ⅳ-C，HA，and LN in the rats of the model groups at each stage were significantly decreased （P<0.05）. Among these，the improvements in all indicators were most significant in the F3 stage （P<0.01）.（3） The proteomic results show that a total of 165 differential proteins exhibit a callback trend when comparing the model groups at four stages with the normal group，and when comparing the Qijia Rougan formula group with the model group. Western blot analysis reveals that the levels of NAD（P）H：quinone oxidoreductase 1 （NQO1），mitogen-activated protein kinase 1 （MAPK1），arginase 1 （Arg1），and glutathione S-transferase α1 （GSTA1） were consistent with the proteomic results. Bioinformatics results reveal that 165 differentially expressed proteins are enriched in multiple signaling pathways. Notably，signaling pathways such as drug metabolism-cytochrome P450，arginine biosynthesis，and the peroxisome proliferator-activated receptor （PPAR） signaling pathway were found to be closely associated with liver fibrosis，suggesting that the Qijia Rougan formula may exert its staged regulatory effects on liver fibrosis by regulating these pathways. ConclusionThe Qijia Rougan formula may achieve staged regulation of liver fibrosis by regulating drug metabolism-cytochrome P450，arginine biosynthesis，and the PPAR signaling pathway.

Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

Objective: To assess the nutritional supply status of school meals for primary and secondary school students in Henan Province, so as to provide a basis for scientific guidance of school meals. Methods: During 2021-2023, 115 lunch and dinner samples were collected from 25 primary and secondary schools in Zhoukou, Anyang and Luoyang of Henan Province by a direct selection method, and 13 nutrients were determined for each sample. The nutrient supply was evaluated based on Nutrition Guidelines of School Meals and Reference Intake of Dietary Nutrients for Chinese Residents (2023 Edition). Mann-Whitney U test was used to compare the differences of nutritional supply between urban and rural schools. Results: The median values for energy (709.77 kcal,1 kcal=4.18 kJ), fat energy supply ratio (0.27) and carbohydrate energy supply ratio (0.55) in the 66 lunches and dinners from primary school were within the recommended range. The supply of protein (28.39 g) and sodium (1 464.59 mg) was excessive. The median values of zinc (2.62 mg) and dietary fiber (5.19 g) were lower than the reference values. No statistically significant differences were observed in the supply of 13 nutrients between urban and rural primary schools( U = 427.00 -633.00, P > 0.05 ). Among 49 samples from secondary schools, the median value of energy supply (930.02 kcal), carbohydrate energy ratio ( 0.54 ) and fat energy supply ratio(0.25) were within the recommended range; and the median values of protein (38.82 g) and sodium (2 556.80 mg) were higher than the standard; and the median values of calcium (250.32 mg) and vitamin B1 (0.16 mg) were lower than the standard. Additionally, the differences in the level of vitamin B2 ( U =372.00) and zinc ( U =375.00) between the urban and rural secondary schools were statistically significant ( P <0.05). Conclusion Nutrient supply of primary and secondary school meals in three cities of Henan Province is inadequate and imbalanced, and the recipe need to be further optimized and improved.

OBJECTIVE: To observe the effects of antagonistic needling therapy on lower limb spasticity and the muscle morphology of the tibialis anterior and gastrocnemius in patients with stroke. METHODS: A total of 100 patients with post-stroke lower limb spasticity were randomly divided into an antagonistic needling group (50 cases, 1 case dropped out) and a routine acupuncture group (50 cases, 1 case dropped out). Both groups received basic treatment and rehabilitation training. The routine acupuncture group was treated with scalp acupuncture at anterior oblique line of vertex-temporal and vertex lateral line 1, combined with body acupuncture at Jianyu (LI15), Hegu (LI4), Zusanli (ST36), Taichong (LR3), etc. on the affected side, with Quchi (LI11) and Hegu (LI4), Zusanli (ST36) and Fenglong (ST40), Yanglingquan (GB34) and Taichong (LR3) connected to an electroacupuncture device, using disperse wave at 2 Hz of frequency. The antagonistic needling group used the same scalp and upper limb acupoints as the routine acupuncture group, with additional antagonistic needling on the lower limb at Yanglingquan (GB34), Qiuxu (GB40), Jiexi (ST41), and Xuanzhong (GB39) on the affected side, with Quchi (LI11) and Hegu (LI4), Yanglingquan (GB34) and Qiuxu (GB40), Jiexi (ST41), and Xuanzhong (GB39) connected to an electroacupuncture device, using disperse wave at 2 Hz of frequency. Both groups received treatment once daily for 6 consecutive days per course, with a total of 4 courses. The modified Ashworth scale (MAS), Holden functional ambulation classification (FAC), lower limb Fugl-Meyer assessment (FMA), composite spasticity scale (CSS), and musculoskeletal ultrasound parameters (thickness and fiber length of the tibialis anterior and gastrocnemius, and pennation angle of the gastrocnemius on both sides) were evaluated before and after treatment. Clinical efficacy was compared between the two groups. RESULTS: Compared before treatment, the MAS grades and CSS scores were decreased in both groups after treatment (P<0.01), with greater reductions in the antagonistic needling group (P<0.05, P<0.01). FAC grades and FMA scores were increased in both groups after treatment (P<0.01, P<0.05), with greater improvements in the antagonistic needling group (P<0.05). The muscle thickness, fiber length of the tibialis anterior, the muscle thickness, fiber length and pennation angle of the gastrocnemius on the affected side were improved in both groups after treatment (P<0.01), with greater improvements in the antagonistic needling group (P<0.01, P<0.05). On the unaffected side, these parameters were also increased after treatment in both groups (P<0.01, P<0.05), but the antagonistic needling group showed smaller increases than the routine acupuncture group (P<0.01, P<0.05). The total effective rate in the antagonistic needling group was 91.8% (45/49), higher than 81.6% (40/49) in the routine acupuncture group (P<0.05). CONCLUSION Antagonistic needling could effectively reduce spasticity, improve motor function, and enhance muscle structure in patients with post-stroke lower limb spasticity.
Humans ; Male ; Female ; Acupuncture Therapy ; Middle Aged ; Muscle Spasticity/pathology* ; Aged ; Stroke/physiopathology* ; Lower Extremity/physiopathology* ; Acupuncture Points ; Adult ; Muscle, Skeletal/pathology* ; Treatment Outcome

Neuraxial opioids, widely used in obstetric and perioperative pain management, often lead to unwanted itch, reducing patient satisfaction. While the μ-opioid receptor has been implicated in opioid-induced itch, the genetic basis for variable itch incidence remains unknown. This study examined 3616 patients receiving epidural opioids, revealing an itch occurrence of 26.55%, with variations among opioid types and gender. Analysis of the OPRM1 gene identified six single-nucleotide polymorphisms, notably rs1799971 (A118G), that correlated with opioid-induced itch. Mouse models with an equivalent A112G mutation showed reduced neuraxial opioid-induced itch and light touch-evoked itch, mirroring human findings. The 118G allele demonstrated an anti-itch effect without impacting analgesia, addiction, or tolerance, offering insights for risk stratification and potential anti-itch pretreatment strategies.
Receptors, Opioid, mu/genetics* ; Pruritus/chemically induced* ; Humans ; Analgesics, Opioid/administration & dosage* ; Female ; Male ; Animals ; Polymorphism, Single Nucleotide/genetics* ; Adult ; Mice ; Middle Aged

Objective:To construct and evaluate a radiomics model for predicting perineural invasion in patients with intrahepatic cholangiocarcinoma (ICC).Methods:Clinical data of 144 patients with ICC undergoing surgery in the People’s Hospital of Zhengzhou University ( n=113) and the Affiliated Cancer Hospital of Zhengzhou University ( n=31) from January 2018 to June 2023 were retrospectively analyzed, including 80 males and 64 females, aged (58.8±10.1) years. The patients were randomly divided into a training set ( n=100) and a test set ( n=44) at a ratio of 7: 3. The former set was used to build the model for predicting perineural invasion, and the latter was used to evaluate the model. Enhanced CT images and clinical data of the patients were collected, and features related to perineural invasion were screened. A light gradient boosting machine was used to construct an imaging genomics model. The model was evaluated using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results:Univariate and multivariate logistic regression analysis showed that none of the clinical features were associated with neural invasion in ICC patients (all P>0.05). Six, 25, 32, and 37 radiomics features were obtained by screening the intratumoral, 2 mm peritumoral, 5 mm peritumoral, and 8 mm peritumoral regions, respectively. The area under the ROC curve for predicting perineural invasion in ICC patients was 0.849 (95% CI: 0.774-0.923) in the training set and 0.745 (95% CI: 0.597-0.894) in the test set for the intratumoral model, 0.966 (95% CI: 0.938-0.995) and 0.750 (95% CI: 0.604-0.896) for the 5mm peritumoral model, 0.936 (95% CI: 0.892-0.980) and 0.792 (95% CI: 0.644-0.939) for the 2mm peritumoral model, and 0.961 (95% CI: 0.929-0.992) and 0.689 (95% CI: 0.526-0.853) for the 8mm peritumoral model. The area under the ROC curve, accuracy, sensitivity, and specificity of the combined intratumoral and 5mm peritumoral model for predicting perineural invasion were 0.927 (95% CI: 0.878-0.976), 88.0%, 84.5%, and 89.8% in the training set, and 0.849 (95% CI: 0.737-0.960), 77.3%, 85.2%, and 72.0% in the test set, respectively. The calibration curve showed a deviation between the calibration curve of the combined intratumoral and 5mm peritumoral model and the ideal line, but it could achieve basic consistency. DCA showed that when the threshold was between 0.18 and 0.70, the combined intratumoral and 5mm peritumoral model could bring clinical net benefit to patients when predicting neural invasion. Conclusion:The intratumoral and 5mm peritumoral imaging genomics model based on enhanced CT features can effectively predict neural invasion and offer clinical benefits in patients with ICC.

OBJECTIVE: To explore the feasibility of incorporating simple bedside indicators into death predictive model for elderly critically ill patients based on interpretability machine learning algorithms, providing a new scheme for clinical disease assessment. METHODS: Elderly critically ill patients aged ≥ 65 years who were hospitalized in the intensive care unit (ICU) of Tacheng People's Hospital of Ili Kazak Autonomous Prefecture from June 2017 to May 2020 were retrospectively selected. Basic parameters including demographic characteristics, basic vital signs and fluid intake and output within 24 hours after admission, as well acute physiology and chronic health evaluation II (APACHE II), Glasgow coma score (GCS) and sequential organ failure assessment (SOFA) were also collected. According to outcomes in hospital, patients were divided into survival group and death group. Four datasets were constructed respectively, namely baseline dataset (B), including age, body temperature, heart rate, pulse oxygen saturation, respiratory rate, mean arterial pressure, urine output volume, infusion volume, and crystal solution volume; B+APACHE II dataset (BA), B+GCS dataset (BG), and B+SOFA dataset (BS). Then three machine learning algorithms, Logistic regression (LR), extreme gradient boosting (XGboost) and gradient boosting decision tree (GBDT) were used to develop the corresponding mortality predictive models within four datasets. The feature importance histogram of each prediction model was drawn by SHapley additive explanation (SHAP) method. The area under curve (AUC), accuracy and F1 score of each model were compared to determine the optimal prediction model and then illuminate the nomogram. RESULTS: A total of 392 patients were collected, including 341 in the survival group and 51 in the death group. There were statistically significant differences in heart rate, pulse oxygen saturation, mean arterial pressure, infusion volume, crystal solution volume, and etiological distribution between the two groups. The top three causes of death were shock, cerebral hemorrhage, and chronic obstructive pulmonary disease. Among the 12 prognostic models trained by three machine learning algorithms, overall performance of prognostic models based on B dataset was behind, whereas the LR model trained by BA dataset achieved the best performance than others with AUC of 0.767 [95% confidence interval (95%CI) was 0.692-0.836], accuracy of 0.875 (95%CI was 0.837-0.903) and F1 score of 0.190. The top 3 variables in this model were crystal solution volume with first 24 hours, heart rate and mean arterial pressure. The nomogram of the model showed that the total score between 150 and 230 were advisable. CONCLUSION The interpretable machine learning model including simple bedside parameters combined with APACHE II score could effectively identify the risk of death in elderly patients with critically illness.
Humans ; Critical Illness ; Machine Learning ; Aged ; Algorithms ; Intensive Care Units ; Retrospective Studies ; APACHE ; Prognosis ; Organ Dysfunction Scores ; Hospital Mortality ; Male ; Female

Organoids are three-dimensional (3D) cellular structures formed through the differentiation and self-organization of pluripotent stem cells or tissue-derived cells, showing considerable potential in the research on disease mechanism, personalized medicine, and developmental biology. However, the development of organoids is limited by the complex composition, batch-to-batch variations, and immunogenicity of basement-membrane matrix in the current culture system, which hinders the clinical translation and in vivo applications of organoids. Hydrogels are highly hydrated 3D polymer network materials, with modifiable mechanical and biochemical properties by engineering, representing an ideal alternative to basement-membrane matrix. This article reviews the research progress in engineered hydrogels with defined composition currently used in organoid culture. We introduce the structural characteristics and engineering design considerations of hydrogels, emphasize the latest research progress and specific application cases, and discuss the future development of these engineered hydrogels, provide valuable insights for the further advancement and optimization of engineered hydrogels for organoid.
Hydrogels/chemistry* ; Organoids/cytology* ; Tissue Engineering/methods* ; Humans ; Animals ; Pluripotent Stem Cells/cytology* ; Cell Culture Techniques, Three Dimensional/methods* ; Tissue Scaffolds

The construction of a medical safety system based on the medical core quality and safty systems is the foundation of the hospital. Multi-campus operation coordinated development is key to the high-quality development of public hospitals and the balanced distribution of high-quality medical resources. Building a medical safety system that comfoms to the specialized layout and operation of branch districts is very important the construction of multi-campus hospitals. In January 2023, Xidan Campus of Peking Union Medical College Hospital established a medical safety system that was compatible with its development, based on the construction of the medical core quality and safty system. The system covered four dimensions: early identification, early assessment, early intervention, and fast response. It included high-risk surgical evaluation and filing, early warning of nursing rooms, periodic medical safety rounds, and rapid response teams and cross hospital transportation of critical care rapid response teams. As of June 2024, the hospital had recorded 570 high-risk surgeries with no unplanned secondary surgeries or unplanned readmissions; Reported nursing warnings 68 times, initiated 93 emergency treatments and cross hospital transfers. All emergency patients received early warning assessments and completed graded and classified transfers and management, effectively ensuring patient safety. This practice could provide references for other multi-campus hospitals to promote the construction and development of medical safety systems.