Objective To explore a method for rapid and differential diagnosis of rejection after kidney transplantation through urine hyperspectral imaging technology. Methods Hyperspectral data information from urine samples of 118 recipients after kidney transplantation was collected, and a deep learning model was constructed to diagnose and classify the types of rejection. Results A deep learning diagnostic model based on the 34-layer residual network (ResNet-34) was constructed, and 118 patients were included and divided into the training set and the test set. Based on the pathological results of the transplanted kidney puncture, the urine samples of the patients were classified into five groups: the non-rejection group, the T-cell-mediated rejection group, the antibody-mediated rejection group, the mixed rejection group and the nephropathy recurrence group. The results showed that the diagnostic sensitivities of the model for the above five groups were 0.960, 0.980, 0.930, 0.940 and 0.943 respectively, and the diagnostic specificities were 0.983, 0.993, 0.997, 0.989 and 0.989 respectively. The overall diagnostic accuracy rate reached 95.7%. Conclusions The study provides a non-invasive, rapid and accurate auxiliary diagnostic method for the differential diagnosis of rejection after kidney transplantation.

ObjectiveTo observe the analgesic efficacy and safety of Qihuang acupuncture theory combined with opioid analgesics in patients with moderate to severe cancer pain due to lung cancer. MethodsPatients with moderate to severe cancer pain from lung cancer were randomly divided into Qihuang acupuncture group and control group， with 33 cases in each group. The control group was treated with long-acting opioid analgesics at maintenance doses and supplementary analgesic medications as needed. In case of breakthrough pain， short-acting opioids were used for rescue. The Qihuang acupuncture group received Qihuang acupuncture treatment in addition to the treatment used in the control group， administered once every other day， with 3 sessions constituting one treatment course. The treatment duration for both groups was 5 days. The primary outcome was the change in pain intensity， measured using the numerical rating scale （NRS） before and after treatment， and the NRS change rate was calculated. Secondary endpoints included the daily NRS change rate， the Eastern Cooperative Oncology Group （ECOG） Performance Status （PS） score， the European Organization for Research and Treatment of Cancer Quality of Life Core Questionnaire （EORTC QLQ-C30） score， and the 24-hour equivalent hydrocodone sustained-release tablet dose. Laboratory tests， including routine blood， urine， stool， liver function， and kidney function， were performed before and after treatment. Adverse events were recorded throughout the trial. ResultsAll patients completed the trial， and both groups showed a decrease in average NRS scores and PS scores after treatment， with the Qihuang acupuncture group showing lower average NRS scores and PS scores than the control group （P＜0.05 or P＜0.01）. After treatment， the NRS change rate in the Qihuang acupuncture group was （0.42±0.17）， significantly higher than that in the control group （0.14±0.27， P＜0.01）. The daily NRS change rate during treatment was also higher in the Qihuang acupuncture group compared to the control group （P＜0.01）. The Qihuang acupuncture group showed an increase in overall health status and functional scores in the EORTC QLQ-C30， and a decrease in symptom scores for fatigue， nausea and vomiting， pain， dyspnea， insomnia， appetite loss， constipation， and financial difficulties. In contrast， overall health status and constipation scores in the control group increased， while scores of fatigue， nausea and vomiting， pain， and appetite loss decreased （P＜0.05 or P＜0.01）. After treatment， the 24-hour equivalent hydrocodone sustained-release tablet dose did not show significant difference in the Qihuang acupuncture group （P＞0.05）， while the control group showed a significant increase in the 24-hour dose （P＜0.01）. No significant abnormalities were observed in laboratory tests before and after treatment in either group. During the study， the incidence of nausea and vomiting as well as constipation in the Qihuang acupuncture group was both 3.03% （1/33）， while the incidence in the control group was 27.27% （9/33） and 36.36% （12/33）， respectively， with the Qihuang acupuncture group showing significantly lower incidence （P＜0.01）. No serious adverse reactions were observed in either group. ConclusionQihuang acupuncture therapy combined with opioid analgesics is more effective than using opioids alone in relieving pain in patients with moderate to severe cancer pain due to lung cancer. It can improve the patients' physical condition and quality of life， reduce the dose of opioid analgesics， and has good safety.

Polypoidal choroidal vasculopathy(PCV)is one of the important subtypes of neovascular age-related macular degeneration(nARMD), which causes severe vision loss. It is necessary to distinguish PCV from other nARMD subtypes to guide the clinical treatment plans and predict disease outcomes. In recent years, artificial intelligence(AI)has been widely used in the diagnosis and research of ophthalmic diseases. By utilizing machine learning or deep learning combined with examination images in disease classification, lesion segmentation, and quantitative assessment, etc. This article reviews the recent applications of AI in the differential diagnosis of PCV through various examination images, the segmentation and quantification of biomarkers, as well as the prediction of genotype, response to anti-vascular endothelial growth factor(VEGF)therapy, and the short-term risk of vitreous hemorrhage. It summarizes the difficulties and challenges in clinical practice of AI and looks forward to the advantages and development trends of AI in PCV applications in the future. The article aims to provide more information for further research and application, thereby improving the diagnostic rate of PCV, optimizing treatment plans, and improving patients' visual prognosis.

Polypoidal choroidal vasculopathy(PCV)is one of the important subtypes of neovascular age-related macular degeneration(nARMD), which causes severe vision loss. It is necessary to distinguish PCV from other nARMD subtypes to guide the clinical treatment plans and predict disease outcomes. In recent years, artificial intelligence(AI)has been widely used in the diagnosis and research of ophthalmic diseases. By utilizing machine learning or deep learning combined with examination images in disease classification, lesion segmentation, and quantitative assessment, etc. This article reviews the recent applications of AI in the differential diagnosis of PCV through various examination images, the segmentation and quantification of biomarkers, as well as the prediction of genotype, response to anti-vascular endothelial growth factor(VEGF)therapy, and the short-term risk of vitreous hemorrhage. It summarizes the difficulties and challenges in clinical practice of AI and looks forward to the advantages and development trends of AI in PCV applications in the future. The article aims to provide more information for further research and application, thereby improving the diagnostic rate of PCV, optimizing treatment plans, and improving patients' visual prognosis.

ObjectiveTo explore the pharmacological mechanism involved in the treatment of allergic cough （AC） by Xiaoer Huatan Zhike granules （XEHT） based on proteomics and network pharmacology. MethodsAfter sensitization by intraperitoneal injection of 1 mL suspension containing 2 mg ovalbumin （OVA） and 100 mg aluminum hydroxide， a guinea pig model of allergic cough was constructed by nebulization with 1% OVA. The modeled guinea pigs were randomized into the model， low-， medium- and high-dose （1， 5， 20 g·kg^-1， respectively） XEHT， and sodium montelukast （1 mg·kg^-1） groups （n=6）， and another 6 guinea pigs were selected as the blank group. The guinea pigs in drug administration groups were administrated with the corresponding drugs by gavage， and those in the blank and model groups received the same volume of normal saline by gavage， 1 time·d^-1. After 10 consecutive days of drug administration， the guinea pigs were stimulated by 1% OVA nebulization， and the coughs were observed. The pathological changes in the lung tissue were observed by hematoxylin-eosin staining. The enzyme-linked immunosorbent assay was performed to measure the levels of C-reactive protein （CRP）， interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α）， superoxide dismutase （SOD）， and malondialdehyde （MDA） in the bronchoalveolar lavage fluid （BALF） and immunoglobulin G （IgG） and immunoglobulin A （IgA） in the serum. Immunohistochemistry （IHC） was employed to observe the expression of IL-6 and TNF-α in the lung tissue. Transmission electron microscopy was employed observe the alveolar type Ⅱ epithelial cell ultrastructure. Real-time PCR was employed to determine the mRNA levels of IL-6， interleukin-1β （IL-1β）， and TNF-α in the lung tissue. Label-free proteomics was used to detect the differential proteins among groups. Network pharmacology was used to predict the targets of XEHT in treating AC. The Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis was performed to search for the same pathways from the results of proteomics and network pharmacology. ResultsCompared with the blank group， the model group showed increased coughs （P<0.01）， elevated levels of CRP， TNF-α， IL-6， and MDA and lowered level of SOD in the BALF （P<0.05， P<0.01）， elevated levels of IgA and IgG in the serum （P<0.05， P<0.01）， congestion of the lung tissue and infiltration of inflammatory cells， increased expression of IL-6 and TNF-α （P<0.01）， large areas of low electron density edema in type Ⅱ epithelial cells， obvious swelling and vacuolization of the organelles， karyopyknosis or sparse and dissolved chromatin， and up-regulated mRNA levels of IL-6， IL-1β， and TNF-α （P<0.01）. Compared with the model group， the drug administration groups showed reduced coughs （P<0.01）， lowered levels of CRP， TNF-α， IL-6， and MDA and elevated level of SOD in the BALF （P<0.05， P<0.01）， alleviated lung tissue congestion， inflammatory cell infiltration， and type Ⅱ epithelial cell injury， and decreased expression of IL-6 and TNF-α （P<0.01）. In addition， the medium-dose XEHT group and the montelukast sodium group showcased lowered serum levels of IgA and IgG （P<0.05， P<0.01）. The medium- and high-dose XEHT groups and the montelukast sodium showed down-regulated mRNA levels of IL-6， IL-1β， and TNF-α and the low-dose XEHT group showed down-regulated mRNA levels of IL-6 and TNF-α （P<0.05， P<0.01）. Phospholipase D， mammalian target of rapamycin （mTOR）， and epidermal growth factor receptor family of receptor tyrosine kinase （ErbB） signaling pathways were the common pathways predicted by both proteomics and network pharmacology. ConclusionProteomics combined with network pharmacology reveal that XEHT can ameliorate AC by regulating the phospholipase D， mTOR， and ErbB signaling pathways.

The European Society of Cardiology (ESC) released the "2024 ESC guidelines for the management of elevated blood pressure and hypertension" on August 30, 2024. This guideline updates the 2018 "Guidelines for the management of arterial hypertension." One notable update is the introduction of the concept of "elevated blood pressure" (120-139/70-89 mm Hg). Additionally, a new systolic blood pressure target range of 120-129 mm Hg has been proposed for most patients receiving antihypertensive treatment. The guideline also includes numerous additions or revisions in areas such as non-pharmacological interventions and device-based treatments for hypertension. This article interprets the guideline's recommendations on definition and classification of elevated blood pressure and hypertension, and cardiovascular disease risk assessment, diagnosing hypertension and investigating underlying causes, preventing and treating elevated blood pressure and hypertension. We provide a comparison interpretation with the 2018 "Guidelines for the management of arterial hypertension" and the "2017 ACC/AHA guideline on the prevention, detection, evaluation, and management of high blood pressure in adults."

Objective To determine the prognostic biomarkers and new therapeutic targets of the lung adenocarcinoma (LUAD), based on which to establish a prediction model for the survival of LUAD patients. Methods An integrative analysis was conducted on gene expression and clinicopathologic data of LUAD, which were obtained from the UCSC database. Subsequently, various methods, including screening of differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA), were employed to analyze the data. Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to establish an assessment model. Based on this model, we constructed a nomogram to predict the probable survival of LUAD patients at different time points (1-year, 2-year, 3-year, 5-year, and 10-year). Finally, we evaluated the predictive ability of our model using Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves. The validation group further verified the prognostic value of the model. Results The different-grade pathological subtypes' DEGs were mainly enriched in biological processes such as metabolism of xenobiotics by cytochrome P450, natural killer cell-mediated cytotoxicity, antigen processing and presentation, and regulation of enzyme activity, which were closely related to tumor development. Through Cox regression and LASSO regression, we constructed a reliable prediction model consisting of a five-gene panel (MELTF, MAGEA1, FGF19, DKK4, C14ORF105). The model demonstrated excellent specificity and sensitivity in ROC curves, with an area under the curve (AUC) of 0.675. The time-dependent ROC analysis revealed AUC values of 0.893, 0.713, and 0.632 for 1-year, 3-year, and 5-year survival, respectively. The advantage of the model was also verified in the validation group. Additionally, we developed a nomogram that accurately predicted survival, as demonstrated by calibration curves and C-index. Conclusion We have developed a prognostic prediction model for LUAD consisting of five genes. This novel approach offers clinical practitioners a personalized tool for making informed decisions regarding the prognosis of their patients.

ObjectiveTo clearly identify the difference between rescue injuries and agonal injuries and to avoid duplicate identifications and misidentifications. MethodsBased on the forensic pathological data of 5 923 cases of death cause identification from 2013 to 2022 in Sun Yat-sen University Forensic Identification Center and Guangzhou Tianhe District Branch of Guangzhou Public Security Bureau， this study retrospectively studied the characteristics of rescue injuries and agonal injuries seen in cause of death identification and their influence on cause of death identification. ResultsAmong all the 5 923 cases， 640 cases were found to have rescue injuries or agonal injuries， and 624 cases received treatment， of which 609 cases were found to have rescue injuries （97.60%）， 44 cases were found to have agonal injuries， and 13 cases were found to have both types of injuries. Among the 640 cases， 441 were male and 199 were female. The age of death was discontinuously distributed from 0 to 95 years old. The leading cause of death was disease， followed by mechanical injury and asphyxia. The main manifestations of rescue injuries were rib and sternum fractures， soft tissue injuries in the prechest area or face， and pericardial rupture. The most common injuries in agonal stage were falling after unconsciousness， inhalation of foreign body in respiratory tract or multiple violent injuries. Among the 640 cases， 19 cases were repeatedly identified， including 15 cases of rescue injuries， 6 cases of agonal injuries， and 2 cases of both types of injuries. Compared with the cases where neither type of injuries was detected， the repeated identification rate of treatment injuries and agonal injuries was significantly increased （χ²=4.04， P=0.044； χ²=43.49， P<0.001）. Among the 640 cases， 11 cases （1.72%） were misidentified as the initial injuries in the first identification， and 13 cases had combined rescue injuries or agonal injuries that were involved in death. ConclusionsBy elucidating the epidemiological characteristics of the two types of injuries， this study proved that the two types of injuries were associated with higher rates of repeated identification and misidentification， which provided a reference for reducing repeated identification and misidentification and improving the accuracy of cause of death identification.

N6-methyladenosine(m6A)is recognized as the most prevalent mRNA modification in mammals, intricately involved in a multitude of processes pertaining to mRNA metabolism, encompassing RNA transcription, translation, and degradation. It plays a pivotal role in various physiological functions. Under the coordinated actions of methyltransferases, demethylases, and m6A-binding proteins, m6A modifications undergo reversible changes to fulfill their diverse molecular functions.Methyltransferase-like 3(METTL3), as the core catalytic subunit of methyltransferases and the most extensively studied methyltransferase, holds a central position in m6A modification. In recent years, it has been found that METTL3-mediated m6A modification is involved in the occurrence and development of various ocular diseases, such as ocular surface diseases, glaucoma, cataract, retinal diseases, and ocular tumors, by affecting the expression of inflammatory factors and thus regulating the inflammatory response, and by regulating various pathways that affect the proliferation of cells and oxidative stress. In this paper, we comprehensively review the mechanisms under the role of METTL3 in ocular diseases, offering novel insights and perspectives for the prevention and management of these conditions.

OBJECTIVE To explore optimization pathways for the drug traceability code management model in outpatient pharmacy workflows， providing practical evidence for enhancing the efficiency of pharmaceutical service. METHODS Taking the outpatient pharmacy of the First Affiliated Hospital of Sun Yat-sen University as the research subject， a comprehensive drug traceability system was established through three key interventions： upgrading the information system architecture [including integration of the hospital information system （HIS） with the traceability platform]， workflow optimization （reorganizing the inventory-dispensing-verification tripartite process）， and designing a dual-mode traceability data collection mechanism （primary data capture at dispensing stations and supplementary capture at verification stations）. Operational efficiency differences before and after implementation were analyzed using the medical insurance data and service timeliness metrics in September 2024. RESULTS After the implementation of drug traceability code management， in terms of data collection: Mode Ⅰ （verification-stage capture） uploaded 26 144 records， while Mode Ⅲ （inventory-as-sales capture） uploaded 443 061 records， totaling 469 205 entries； in terms of time efficiency： average drug dispensing time increased from 28.74 s to 43.37 s （enhanced by 51%）. Through dynamic staffing adjustments， patient wait time only extended from 8.04 min to 8.67 min （enhanced by 8%）. CONCLUSIONS Drug traceability code management can be effectively implemented via a “system reconstruction-process reengineering-human-machine collaboration” trinity strategy， leveraging informatization （e.g.， dual-mode data capture） to offset manual operation delays， which validates the feasibility of balancing national traceability demands with service efficiency in outpatient pharmacies.