ObjectiveTo construct an automatic measurement model for palmar tilt and radial inclination suitable for traditional Chinese medicine （TCM） clinical scenarios， and to validate its accuracy and efficiency in TCM manipulative reduction settings. MethodsData on anteroposterior （AP） and lateral X-rays of distal radius fractures were collected from patients admitted to 18 TCM/ integrated TCM and western medicine hospitals in Jiangsu province between September 1st， 2023， and September 1st， 2024， via the Jiangsu Diagnosis and Treatment Big Data Platform for TCM Dominant Diseases. A medical image segmentation framework based on multi-scale feature fusion and edge-awareness was employed， combined with anatomical knowledge specific to TCM orthopedics， to optimize the feature extraction strategy of an artificial intelligence （AI） model. This framework enabled automatic segmentation of fracture regions and measurement of distal radius palmar tilt and radial inclination. The accuracy of the AI model in measuring radial inclination and volar tilt was validated， and the measurement time and average time gain rate of the AI model were compared to those of manual measurement. ResultsA total of 15,444 AP and lateral X-ray images of distal radius fractures were collected， and were divided into a training set （11,144 images， 5066 AP and 6078 lateral）， a validation set （3700 images， 1840 AP and 1860 lateral）， and an independent test set （600 images， 300 AP and 300 lateral） after preprocessing. In the measurement of 300 AP X-rays in the independent test set for radial inclination， when the degree error between AI measurement and manual measurement was ＜3° and ＜5°， AI measurement accuracy was 83% and 93%， respectively. In 300 lateral X-rays in the test set for palmar tilt， when AI measurements had an error of ＜3° and ＜5° compared to manual measurements， corresponding accuracy rate was 78% and 90%， respectively. For 50 X-ray images， AI measurement time was （1.37±0.05） min for radial inclination while manual measurement time was （22.57±2.52） min （P＜0.001）； in terms of palmar tilt， the AI measurement time was （1.33±0.14） min， shorter than （23.70±2.80） min for manual measurement time （P＜0.001）. Average time gain rates for manual and AI measurements were 93.93% and 94.39% respectively. ConclusionAn automatic measurement model for palmar tilt and radial inclination in distal radius fractures has been established， enabling more accurate and efficient assessment as well as providing a tool to support the quantitative evaluation of the efficacy of TCM manipulative reduction and large-sample clinical research.

Chronic post-surgical pain (CPSP) is a common long-term complication following lung surgery. Its high incidence significantly impacts patients’ quality of life and functional recovery, and imposes a substantial socioeconomic burden. This consensus aims to systematically establish a standardized integrated Chinese and Western medicine diagnostic and treatment framework for chronic post-lung surgery pain (CPLSP). Based on the latest domestic and international evidence-based medical research and multidisciplinary clinical experience, the working group comprehensively elaborates on core issues regarding CPLSP, including its definition, epidemiology, pathogenesis, clinical assessment, Western medical treatment, traditional Chinese medicine (TCM) treatment, and integrated strategies. The consensus emphasizes a patient-centered approach, adhering to the principles of multimodality, individualization, and stepwise management, highlighting the synergistic advantages of integrating Chinese and Western medicine throughout the entire perioperative management cycle encompassing "perioperative anti-inflammation, acute analgesia, and chronic rehabilitation." Through systematic literature retrieval and evidence integration, a total of 9 core recommendations were established to provide scientifically sound and clinically practical guidance.

OBJECTIVE To investigate the effects and mechanism of the Yishen paidu formula on renal fibrosis in rats with chronic renal failure （CRF） through the reactive oxygen species （ROS）/thioredoxin-interacting protein （TXNIP）/NOD-like receptor thermal protein domain associated protein 3 （NLRP3） pathway. METHODS Rats were randomly divided into control group， model group， Yishen paidu formula low-dose （Yishen paidu formula-L） group， Yishen paidu formula high-dose （Yishen paidu formula- H） group， Yishen paidu formula-H+pcDNA-NC group， and Yishen paidu formula-H+ pcDNA-TXNIP group， with 10 rats in each group. Except for control group， all other rats were fed a diet containing 0.5% adenine to establish a CRF model； the rats were then administered corresponding drugs or normal saline intragastrically or via tail vein， once daily， for 8 consecutive weeks. After the last administration， the levels of serum creatinine （Scr）， blood urea nitrogen （BUN）， ROS， superoxide dismutase （SOD）， malondialdehyde （MDA）， tumor necrosis factor-α （TNF-α）， interleukin （IL）-6， and IL-1β were measured in each group. Pathological changes in renal tissue were observed， and the protein expression levels of Collagen Ⅲ， α-smooth muscle actin （α-SMA）， transforming growth factor-β1 （TGF-β1）， TXNIP and NLRP3 in renal tissue were detected. RESULTS Compared with model group， the renal histopathological damage and fibrosis of rats in Yishen paidu formula-L group and Yishen paidu formula-H group were significantly alleviated. The levels of Scr， BUN， ROS， MDA， TNF- α， IL-6 and IL-1β， and the protein expressions of Collagen Ⅲ， α-SMA， TGF-β1， TXNIP and NLRP3 were significantly decreased， while SOD levels were significantly increased （P＜0.05）. Moreover， the changes were more pronounced in the Yishen paidu formula-H group （P＜0.05）. Compared with Yishen paidu formula-H+pcDNA-NC group， above indexes of rats in Yishen paidu formula-H+pcDNA-TXNIP group were reversed significantly （P＜0.05）. CONCLUSIONS Yishen paidu formula can inhibit renal fibrosis in CRF rats by suppressing the ROS/TXNIP/NLRP3 pathway.

Plant-derived extracellular vesicles (PDEVs) are nanoscale extracellular vesicles secreted by plant cells, characterized by a lipid bilayer structure. These vesicles carry a variety of bioactive molecules, including proteins, nucleic acids, and lipids, and play essential roles in intercellular communication and physiological regulation in plants. Compared to animal-derived extracellular vesicles, PDEVs offer several advantages, such as a broad range of sources, high biocompatibility, low immunogenicity, and low production costs. Furthermore, PDEVs have demonstrated remarkable potential as natural nanocarriers for drug delivery, due to their ability to efficiently traverse biological barriers, such as the blood-brain barrier, making them promising candidates for drug delivery systems. This review systematically elaborates on the complex composition of PDEVs, which consists of lipids, proteins, and nucleic acids, the typical structural characteristics of their lipid bilayers ranging from 30 to 150 nm, and their versatile loading capabilities as drug carriers, efficiently encapsulating various types of therapeutic agents such as hydrophilic small molecules, hydrophobic drugs, nucleic acids, and proteins. We systematically summarize the recent advancements in strategies for enhancing the loading efficiency of PDEVs, which include methods such as co-incubation, ultrasound-assisted loading, electroporation, freeze-thaw cycles, and microfluidic technology. These techniques are evaluated based on their underlying principles, suitable drug types, and their respective advantages. In addition to loading strategies, we focus on the engineered approaches to achieve targeted delivery using PDEVs, such as genetic engineering modifications, chemical ligand conjugation, membrane fusion technology, and polyethylene glycol (PEG) modification. We discuss the mechanisms of these strategies in enhancing targeting efficiency, prolonging in vivo circulation time, and improving therapeutic efficacy. Further, this review highlights the application of PDEVs in various disease models, including tumor, skin inflammation, metabolic disorders, and neurodegenerative diseases, showcasing their therapeutic potential as multifunctional delivery platforms. The ability of PDEVs to encapsulate diverse therapeutic agents and target specific tissues or cells opens up new avenues for the treatment of complex diseases, offering advantages over conventional drug delivery systems. However, despite the promising applications of PDEVs, several challenges remain in their development and clinical translation. These challenges include variability in source materials, standardization of preparation processes, quality control, scalability of production, and the need for clinical validation. To overcome these obstacles, the integration of advanced technologies such as artificial intelligence-assisted design and multi-omics analysis is proposed as a way to facilitate the precise development of PDEVs. These emerging technologies hold the potential to further enhance the precision and effectiveness of plant-based drug delivery systems, ultimately advancing the field of precision medicine. In conclusion, the use of PDEVs as a platform for drug delivery represents a promising area of research with the potential to revolutionize therapeutic strategies. Their ability to encapsulate and deliver a wide variety of bioactive molecules, along with their inherent advantages in biocompatibility and versatility, makes them a valuable tool in the development of more efficient and targeted therapeutic interventions. Continued research and innovation in this field will pave the way for the clinical implementation of PDEVs in the treatment of various diseases, offering new hope for more effective and sustainable therapeutic options.

Pancreatic ductal adenocarcinoma （PDAC） is highly malignant and often has an extremely poor prognosis， and early postoperative liver metastasis is one of the key influencing factors for prognosis. With reference to the clinical and experimental studies in recent years， this article reviews the clinical risk factors for early liver metastasis after PDAC and systematically elaborates on major molecular events underlying early postoperative liver metastasis from various aspects of construction of the pre-metastatic niche in the liver driven by tumor-derived exosomes， the pro-metastatic microenvironment maintained by metastasis-associated macrophages and neutrophil extracellular traps， the invasive phenotype and liver-tropic migration of tumor cells， intrahepatic immunometabolic adaptation， and fibrotic remodeling， in order to provide a theoretical basis for perioperative risk stratification and the development of intervention strategies.

Objective: To investigate the incidence and influencing factors of new onset suicidal behaviors among junior and senior high school students, so as to provide evidence for early warning and intervention. Methods: Using a cluster sampling method, baseline data were collected from September to November 2023 among 2 379 adolescents selected from 2 junior high schools, 2 general senior high schools and 2 vocational senior high schools in Wuhan, Hubei Province, with follow up carried out from September to November 2024. Data were collected using the School Adaptation Scale, the Essential Resilience Scale, the Personal Social Support Scale, the Adverse Childhood Experiences Questionnaire, the Adolescent Life Events Scale, the Pittsburgh Sleep Quality Index, the Center for Epidemiologic Studies Depression Scale, and the Columbia-Suicide Severity Rating Scale. Multivariate Logistic regression analysis was used to identify factors influencing new onset suicidal behavior among junior and senior high school students. Results: Among junior and senior high school students without suicide risk at baseline, 53.55% remained stable risk free during follow up, while 13.28% developed new suicidal behavior during follow up, of which suicidal ideation, suicide plan and suicide attempts accounted for 11.69%, 8.83% and 6.52%, respectively. Multivariate Logistic regression revealed that increased depressive symptoms at follow up elevated the risk of overall new onset suicidal behaviors ( OR =4.14), ideation ( OR = 4.59), plans ( OR =4.24), and attempts ( OR =4.09); poor sleep quality also increased the risk of overall new onset suicidal behaviors ( OR =2.23), plans ( OR =2.03), and attempts ( OR =2.65) (all P <0.05). Non boarding junior and senior high school students had lower risks of overall new onset suicidal behaviors and ideation ( OR=0.70 and 0.49, respectively); secondary school students with academic performance ranking in the top 20%-30% of their class had a lower risk of new onset ideation ( OR =0.27); and those whose place of origin was outside the city had a lower risk of new onset plans ( OR =0.49) (all P <0.05). Conclusions New onset suicidal behaviors among junior and senior high school students exhibit dynamic and stage specific differences. Depressive symptoms serve as a common core risk factor across all stages, whereas sleep quality, academic performance, boarding status, and place of origin exert differential influences at distinct stages.

Metal-organic frameworks(MOFs)are porous materials composed of metal ions or metal clusters and organic ligands by coordination,which have the advantages of large specific surface area,good thermal stability and adjustable pore size,and have a promising application in gas chromatographic separation.In recent years,MOFs materials have been used as stationary phases for gas chromatography mainly including ZIF,MIL,UiO-66,HKUST-1,IRMOFs,etc.Based on the molecular sieve effect,van der Waals forces,hydrogen bonding and π-π interactions,the pore size,pore microenvironment,unsaturated metal site and special functional group of the MOFs stationary phase materials can be specifically designed and regulated.MOFs materials as stationary phases have unique separation performance for n-alkanes and their isomers,aromatic compounds and their isomers,alcohols/ketones/aldehydes and their isomers,and chiral compounds.The combination of organic polymers and novel nanomaterials with MOFs materials can improve the separation performance and stability of MOFs.Therefore,MOFs materials are expected to be the promising stationary phase that can be applied to gas separation in complex environments.In this article,the research advances of various stationary phases based on MOFs for gas chromatography in recent years were reviewed.The separation performance and separation mechanism of MOFs stationary phases for mixed gas samples were discussed,and the development trends in the future were prospected.

In this study,an ON/OFF type micro-valve with a sandwich(glass-silicon-glass)structure was designed and fabricated based on the micro-electro-mechanical system(MEMS)technique.The deformable membrane of this micro-valve was prepared on the silicon on insulator(SOI)substrate and sealed using Si-Si bonding and anodic bonding methods.The micro-valve had high-temperature stability and was suitable for integration with other gas chromatography components.The deformable membrane with a thickness of 10 μm was processed on the top silicon of the SOI substrate.The flow control of the micro-valve could be achieved by changing the driving pressure applied to the deformable membrane to deform it.Compared with polymer membranes,the deformable membrane prepared on the top layer silicon of SOI had better temperature stability and could be released using the deep reactive ion etching technique after silicon-silicon bonding,avoiding deformation during the preparation process.In addition,due to the small gap between the membrane and the inlet/outlet holes,the dead volume of the microvalve was very small.The test results indicated that the micro-valve achieved flow control and ON/OFF functions with good repeatability.

A novel analytical method was developed in this study by combining online solid phase extraction with ultra performance liquid chromatography-tandem mass spectrometry(Online SPE-UPLC-MS/MS)for simultaneous determination of 50 kinds of steroid hormones in surface water.Specifically,after high-speed centrifugation of 4 mL water samples,the supernatant was directly injected into an Oasis HLB online SPE column for enrichment and purification.Subsequently,the target compounds were transferred to the analytical column via valve switching for separation and analysis.The chromatographic separation was performed on a Thermo Acclaim RSLC C18 column(100 mm×2.1 mm,2.2 μm),using a mobile phase composed of 5 mmol/L ammonium fluoride aqueous solution and acetonitrile.Mass spectrometric detection was conducted in positive ion mode,utilizing multiple reaction monitoring(MRM)with quantification achieved by the internal standard method.The method validation demonstrated that the limits of detection(LOD)for the 50 kinds of steroid hormones ranged from 0.02 to 0.50 ng/L,while the limits of quantification(LOQ)were between 0.08 and 1.67 ng/L.The average recoveries in surface water samples at spiked concentrations of 5,20 and 200 ng/L were between 74.1％and 119％,with relative standard deviations(RSDs)of 0.2％to 9.9％.This method was applied to analyze 11 surface water samples collected from sites surrounding a pharmaceutical and chemical industrial park.A total of 44 kinds of steroid hormones were detected,with concentrations ranging from 0.11 to 88.6 ng/L,revealing the presence of hormone contamination in the environmental waters surrounding industrial areas.Compared with the traditional offline SPE methods,the proposed online SPE technique significantly reduced sample volume requirements and pretreatment time,while minimizing the loss of target compounds during the pretreatment process.Moreover,compared to reported online SPE techniques,this method achieved high-throughput analysis of multiple classes of steroid hormones,with lower detection limits and higher recoveries.Overall,this method provided rapid sample preparation,high sensitivity,and excellent stability,making it suitable for the direct analysis of trace steroid hormones in surface water.

A monolithic integrated gas chromatography chip,consisting of a micro gas chromatography column(μGCC)and a micro helium discharge ionization detector(μHDID)was proposed.The chip was fabricated using micro electromechanical system(MEMS)technique,and its sensitivity was improved from two aspects.On one hand,open tubular column was selected as the separation device,and the auxiliary helium channel width of μHDID was modulated based on the microchannel width of the μGCC to match the flow rates of μHDID and μGCC.On the other hand,the electrode structure inside the μHDID collection zone was optimized,a bias electrode group around the collection electrode was constructed,and the ion collection efficiency was improved.After coating HKUST-1 as the stationary phase,the monolithic integrated gas chromatography chip could achieve baseline separation and detection of light hydrocarbon gas mixture(methane,ethane,propane,andn-butane),with a detection limit for propane as low as 25 pg.The chip could carried out test under temperature-programmed conditions,with a resolution of 9.24 for ethane and propane.