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.

The promulgation of the Technical Specifications for Clinical Use of Blood (2025 Edition) signifies that China's clinical blood transfusion management has transitioned from mere technical operations to a new stage centered on patient blood management (PBM). Through an in-depth comparison of the new and old specifications, this paper analyzes the core transformations regarding conceptual reconstruction, legal alignment, technological upgrades, and closed-loop management. The new specifications establish PBM principles, reinforce legal safeguards for informed consent and emergency treatment, and construct a comprehensive, refined quality control system by specifying compatibility testing standards and introducing a post-transfusion evaluation system. Medical institutions should seize this opportunity to update management protocols and information systems, deepen multidisciplinary collaboration, and drive the profound transformation of clinical blood use from focusing solely on safety assurance to placing equal emphasis on science and value.

Prostate cancer is one of the most common malignant tumors of male genitourinary system. Prostate cancer has the following characteristics： insidious onset， early asymptomatic or not obvious symptoms， complex etiology and pathogenesis， long incubation period and so on. Therefore， the realization of its early diagnosis and treatment is of great significance to the prognosis of patients. Prostate-specific membrane antigen （PSMA） is a type 2 transmembrane glycoprotein that is highly expressed on the membrane of almost all primary and metastatic prostate cancer cells， and is an ideal target for prostate cancer imaging and treatment. In recent years， with the approval of urea-containing small molecule PET （positron emission computed tomography） radiopharmaceutical based on PSMA （⁶⁸Ga-PSMA-11， ¹⁸F-PSMA-1007）， PET-CT （positron emission computed tomography/computed tomography） has shown new potential for early diagnosis and accurate staging of prostate cancer patients. This review mainly summarizes the research progress of urea-containing PSMA PET imaging agents and finds that they have defects such as uptake in non-target tissues like the kidneys， lacrimal glands， and salivary glands. Thus， further optimizing their structure to reduce the uptake in non-target tissues， providing provide convenience for the labeling of therapeutic radiopharmaceuticals， thereby achieving the goal of integrated diagnosis and treatment， is an important development direction in this field.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

RNA methylation is a key process in the epigenetic regulation of post-transcriptional gene expression.5-Methylcytosine(m⁵C)is a type of RNA methylation,commonly existing in eukaryotic mRNA and non-coding RNAs.It mainly regulates transfer RNA stability,ribosomal RNA assembly,and mRNA translation,stability,and translation.RNA methylation is dynamically reversible and regulated by methyltransferase,demethylase,and methylation recognition protein.It has been confirmed that aberrant m⁵C RNA methylation is involved in the pathogenesis of non-neoplastic kidney diseases.This article summarizes the current progress of m⁵C RNA methylation associated with non-neoplastic acute and chronic kidney diseases,aiming to provide potential targets for the diagnosis and treatment of such diseases.
Humans ; Methylation ; 5-Methylcytosine/metabolism* ; Kidney Diseases/metabolism* ; Epigenesis, Genetic ; RNA Methylation

Objective To analyze the influencing factors of death in the elderly with coronavirus disease 2019(COVID-19).Methods The case data of death caused by COVID-19 in West China Fourth Hospital from January 1 to July 8,2023 were collected,and surviving cases from the West China Elderly Health Cohort infected with COVID-19 during the same period were selected as the control.LASSO-Logistic regression was adopted to analyze the data after propensity score matching and the validity of the model was verified by drawing the receiver operating characteristic curve.Results A total of 3 239 COVID-19 survivors and 142 deaths with COVID-19 were included.The results of LASSO-Logistic regression showed that smoking(OR=3.33,95%CI=1.46-7.59,P=0.004),stroke(OR=3.55,95%CI=1.15-10.30,P=0.022),malignant tumors(OR=19.93, 95%CI=8.52-49.23, P<0.001),coronary heart disease(OR=7.68, 95%CI=3.52-17.07, P<0.001),fever(OR=0.51, 95%CI=0.26-0.96, P=0.042),difficulty breathing or asthma symptoms(OR=21.48, 95%CI=9.44-51.95, P<0.001),and vomiting(OR=8.19,95%CI=2.87-23.58, P<0.001)increased the risk of death with COVID-19.The prediction model constructed based on the influencing factors achieved an area under the curve of 0.889 in the test set.Conclusions Smoking,stroke,malignant tumors,coronary heart disease,fever,breathing difficulty or asthma symptoms,and vomiting were identified as key factors influencing the death risk in COVID-19.
Humans ; COVID-19/mortality* ; Aged ; Propensity Score ; China/epidemiology* ; Risk Factors ; Logistic Models ; Smoking ; SARS-CoV-2 ; Male ; Female ; Stroke ; Neoplasms

Pregnancy complicated with acute myeloid leukemia is uncommon,requiring the collaborative management by specialists from departments of hematology,obstetrics,anesthesiology,and neonatology for both the parturient and the neonate.This article reports an anesthesic management process of a parturient woman with acute myeloid leukemia and reviews relevant literature published in recent years to systematically summarize the approach for anesthesia-related perinatal management of such patients.
Humans ; Female ; Pregnancy ; Leukemia, Myeloid, Acute/complications* ; Pregnancy Complications, Neoplastic ; Adult ; Anesthesia, Obstetrical/methods*

Objective: This study aims to investigate the anatomical relationship among the nerve roots, intervertebral space, pedicles, and intradural rootlets of the cervical spine for improving operative outcomes and exploring neuroventral decompression approach in posterior endoscopic cervical discectomy (PECD). Methods: Cervical computed tomography myelography imaging data from January 2021 to May 2023 were collected, and the RadiAnt DICOM Viewer Software was employed to conduct multiplane reconstruction. The following parameters were recorded: width of nerve root (WN), nerve root-superior pedicle distance (NSPD), nerve root-inferior pedicle distance (NIPD), and the relationship between the intervertebral space and the nerve root (shoulder, anterior, and axillary). Additionally, the descending angles between the spinal cord and the ventral (VRA) and dorsal (DRA) rootlets were measured. Results: The WN showed a gradual increase from C4 to C7, with measurements notably larger in men compared to women. The NSPD decreased gradually from the C2–3 to the C5–6 levels. However, the NIPD showed an opposite level-related change, notably larger than the NSPD at the C4–5, C5–6, and C7–T1 levels. Furthermore, significant differences in NIPD were observed between different age groups and genders. The incidence of the anterior type exhibited a gradual decrease from the C2–3 to the C5–6 levels. Conversely, the axillary type exhibited an opposite level-related change. Additionally, the VRA and DRA decreased as the level descended, with measurements significantly larger in females. Conclusion A prediction of the positional relationship between the intervertebral space and the nerve root is essential for the direct neuroventral decompression in PECD to avoid damaging the neural structures. The axillary route of the nerve root offers a safer and more effective pathway for performing direct neuroventral decompression compared to the shoulder approach.