Objective: To establish an accurate and rapid typing method for Rh typing of samples from patients who have received recent blood transfusions by utilizing the difference in osmotic fragility between fresh and old red blood cells. Methods: A lysing solution suitable for destroying old RBCs was prepared. Sixty-one samples collected in our hospital in 2024 with Rh typing of double groups were treated with the lysing solution to remove the old allogeneic red blood cells while preserving the patient's own fresh red blood cells, followed by repeat Rh typing tests. Results: For 61 samples with Rh typing in double groups, 41 were accurately detected identified through the red blood cell lysis method, yielding an identification rate of 67.21%. No significant difference was observed compared to the detection rate of the commonly used capillary centrifugation modified method (χ =0.103, P>0.05). Conclusion: The red blood cell lysis method provides a novel and rapid experimental approach for clinical use in processing Rh-typed samples that are of double groups, thereby offering a basis for Rh compatibility blood transfusion.

ObjectiveBased on the established characteristic profiles， quantitative analysis of multiple components， and chemometric analysis of Taraxacum mongolicum， the quality of different T. mongolicum germplasms was evaluated at the chemical level， thereby providing a reference for the screening of high-quality germplasms and the rational utilization of wild resources. MethodsAn ultra-performance liquid chromatography （UPLC） was employed to establish characteristic profiles. Principal component analysis （PCA） and partial least squares-discriminant analysis （PLS-DA） were then adopted to screen and comprehensively rank marker compounds. ResultsThe UPLC fingerprint of T. mongolicum germplasm identified 13 chromatographic peaks corresponding to gallic acid， coumaric acid， neochlorogenic acid， monocaffeoyltartaric acid， chlorogenic acid， cryptochlorogenic acid， caffeic acid， p-coumaric acid， cichoric acid， luteoloside， isochlorogenic acid B， isochlorogenic acid A， and isochlorogenic acid C. Combined with chemometric analysis such as PCA and PLS-DA， eight core markers （cichoric acid， luteoloside， cryptochlorogenic acid， isochlorogenic acid B， chlorogenic acid， caffeic acid， isochlorogenic acid C， and isochlorogenic acid A） were screened for distinguishing wild and cultivated germplasms. Additionally， eight core markers （cichoric acid， caffeic acid， luteoloside， chlorogenic acid， cryptochlorogenic acid， isochlorogenic acid A， monocaffeoyltartaric acid， and neochlorogenic acid） were selected for the evaluation and screening of different T. mongolicum germplasms. ConclusionThis study establishes a UPLC analysis method capable of simultaneously determining 13 characteristic components in T. mongolicum， such as cichoric acid and chlorogenic acid， as well as their precursor compound contents in the biosynthetic pathway. Based on the above methods， three T. mongolicum germplasms （PGY-004， PGY-009， and PGY-010） with promising medicinal potential are selected for subsequent research on variety breeding. The present study provides a reference for quality control of Taraxacum mongolicum， germplasm screening， and the rational development and utilization of wild resources.

ObjectiveTo investigate the role and mechanism of ribosomal DNA （rDNA） transcription and ribosome biogenesis in muscle atrophy induced by acute kidney injury （AKI）. MethodsEight male C57BL/6 mice were randomly divided into a control group （Ctrl） and a model group （AKI）. An AKI model was established via intraperitoneal injection of cisplatin. Muscle atrophy was phenotypically assessed by measuring muscle mass， myofiber cross-sectional area （HE staining）， and mRNA expression levels of atrophy-related genes （Murf-1， Atrogin-1， Igf-1） using qRT-PCR. In vivo protein synthesis rates were determined via the SUnSET assay （puromycin incorporation）. Ribosome biogenesis was evaluated by assessing rRNA content and 47S pre-rRNA expression levels. Myotubes differentiated from mouse skeletal muscle cell lines （C2C12 myotubes） were treated with serum from AKI mice， and the effects on rDNA transcription， ribosome biogenesis， and protein metabolism were analyzed using chromatin immunoprecipitation followed by quantitative polymerase chain reaction （ChIP-qPCR） and Western blot. ResultsAKI successfully induced muscle atrophy， as evidenced by a significant reduction in skeletal muscle mass. The most pronounced decrease occurred in the extensor digitorum longus muscle （21.0%， P 0.01）， along with a trend toward reduced myofiber cross-sectional area. At the molecular level， AKI inhibited muscle protein synthesis （83.14% reduction in puromycin incorporation， P 0.000 1） and impaired ribosome biogenesis， manifested by suppressed rDNA transcription elongation （52.62% decrease in 47S pre-rRNA ITS-1 levels， P 0.01） and reduced total rRNA content （65.29%， P 0.000 1）. In contrast， serum from AKI mice promoted rDNA transcription initiation and protein synthesis in C2C12 myotubes in vitro. ConclusionAKI induces muscle atrophy by suppressing rDNA transcription and ribosome biogenesis in skeletal muscle， leading to impaired protein synthesis. Dysregulated ribosome biogenesis may play a critical role in AKI-induced muscle atrophy.

Objective: To develop a RHCE genotyping assay based on kompetitive allele-specific PCR (KASP) and assess its clinical accuracy for RhCE blood group determination. Methods: KASP primers were designed to interrogate three RHCE loci: the 109 bp insertion/deletion in intron 2, c. 307T>C, and c. 676C>G. A total of 1 194 RhD-positive inpatients from Chengdu were typed by both KASP genotyping and manual tube serology. Discordant samples (n=10) were retested by both methods and further resolved by Sanger sequencing. An additional 377 cases were tested for the c. 48C>G locus to evaluate the predictive accuracy of individual loci and combined locus testing for RhC antigen. Results: Genotyping concordance with serology was 100.0% for both the c. 676C>G locus (RhE/Rhe) and the c. 307T>C locus (Rhc). For RhC prediction using the 109 bp insertion, overall accuracy was 99.7% (1 191/1 194); the 3 discordant cases were confirmed by Sanger sequencing to be false negatives attributable to 109 bp deletion in intron 2. Testing the c. 48C>G allele for RhC prediction yielded 7 false positives, with an accuracy of 98.1% (370/377). RhC antigen status was determined by combining the 109 bp insertion and the c. 48C allele. After excluding 10 samples with inconsistent results between the two loci, the accuracy reached 100% in the remaining 367 samples. When both loci were applied in combination, accuracy reached 100% in the 367 cases with concordant results. Among the 1 194 patients, CCee (45.8%) and CcEe (31.7%) were the most common RhCE phenotypes. The e antigen had the highest positivity rate (92.2%), and the Ce haplotype was the most frequent (66.9%). Conclusion: The KASP-based RHCE genotyping method achieves high accuracy for clinical RhCE typing. Combining the 109 bp insertion/deletion with the c. 48C allele significantly improves RhC antigen prediction compared with either locus alone. This method was applied to RhCE genotyping of 1 194 RhD-positive inpatients in Chengdu, providing local RhCE phenotype and haplotype distribution data to support RhCE-matched transfusion practice.

Objective To analyze the factors influencing occupational health literacy (OHL), work-related musculoskeletal disorders (WMSDs), and occupational stress in medical staff, and to investigate the potential associations between OHL and WMSDs as well as occupational stress. Methods A total of 880 medical staff members from 18 medical institutions were selected as the study subjects using a probability proportional method. Data on OHL, WMSDs, and occupational stress were investigated using the National Key Populations Occupational Health Literacy Surveillance Individual Questionnaire (including the Musculoskeletal Disorders Questionnaire and the Core Occupational Stress Scale), and the influencing factors and potential relationships were analyzed. Results The OHL level was 63.1%, the prevalence of WMSDs was 88.1%, and the detection rate of occupational stress was 24.0% in the study subjects. Multivariable logistic regression analysis showed that female medical staff had lower OHL levels than males (P<0.05). Medical staff with higher education levels and those working in higher-level medical institutions had higher OHL levels (all P<0.05). Medical staff working >40-<49 hours per week and those working ≥49 hours per week had higher OHL levels than those working ≤40 hours per week (all P<0.01). Medical staff with higher education levels or longer working hours had a higher risk of WMSDs (all P<0.05). Medical staff with lower monthly personal income, longer weekly working hours, and lower OHL levels had a higher risk of occupational stress (all P<0.05), and those working night shifts had a higher risk of occupational stress than those who did not (P<0.01). Conclusion The study participants had a relatively high level of OHL, a high prevalence of WMSDs, and a low detection rate of occupational stress. It is recommended that medical institutions effectively implement occupational health promotion and support measures to improve the OHL level of medical staff, to reduce the risk of WMSDs and occupational stress.

OBJECTIVE To develop and validate interpretable machine learning models for predicting the risk of medication-related osteonecrosis of the jaw （MRONJ） and surgical outcomes， thereby providing quantitative support for MRONJ risk assessment and treatment decision-making.METHODS Two study cohorts were established. Cohort A adopted a nested case-control study design to develop a predictive model for the risk of MRONJ onset. Cohort B comprised patients with MRONJ from Cohort A who underwent surgical treatment and met the follow-up eligibility criteria， and employed a prospective follow-up cohort study design to develop a predictive model for the efficacy of MRONJ surgery. After missing-data processing， variable standardization， and encoding， predictive features were selected using the least absolute shrinkage and selection operator （LASSO） regression， and collinearity was assessed using the variance inflation factor （VIF）. Random Forest （RF）， eXtreme Gradient Boosting （XGB）， Multi-layer Perceptron （MLP）， Support Vector Machine （SVM）， and Gaussian Naive Bayes （NB） models were subsequently developed using the selected features. Hyperparameter optimization and internal performance evaluation were performed using two-level nested cross-validation repeated 20 times. In Cohort B， the synthetic minority over-sampling technique （SMOTE） was applied within the inner training folds to address class imbalance. Model performance was comprehensively evaluated using the receiver operating characteristic （ROC） curve， the precision-recall （PR） curve， calibration curve， and decision curve analysis （DCA）. Shapley additive explanations （SHAP） were used to quantify the relative contributions of individual clinical features to model predictions.RESULTS Seven clinical features， including alkaline phosphatase and tooth extraction， were retained for Cohort A； whereas eight clinical features， including age and duration of medication use， were retained for Cohort B. In Cohort A， the area under the ROC curve， the area under the PR curve， Brier score， sensitivity， and specificity of the RF model were 0.94， 0.92， 0.09， 0.92， and 0.85， respectively； the corresponding values in Cohort B were 0.93， 0.93， 0.12， 0.83， and 0.93， respectively. The results of calibration curves and DCA indicated that the RF models achieved favorable calibration and clinical net benefit， with VIF values for all variables below 5. SHAP visualization results showed that alkaline phosphatase， tooth extraction， and cumulative drug dose made substantial contributions to MRONJ risk prediction in Cohort A， whereas age， duration of medication use， and MRONJ stage contributed substantially to surgical outcome prediction in Cohort B.CONCLUSIONS The RF-based models for predicting MRONJ risk and surgical outcomes demonstrated good discrimination， accuracy of probabilistic predictions， and potential clinical utility during internal validation. These models may provide decision support for comprehensive MRONJ risk management and individualized clinical decision-making. However， external validation in independent， multicenter， and geographically diverse cohorts is still required.

Objective To develop and validate a machine learning model based on preoperative clinical characteristics, laboratory indices, and radiological features for the non-invasive prediction of spread through air spaces (STAS) in patients with early-stage lung adenocarcinoma. Methods Preoperative data from patients with early-stage lung adenocarcinoma who underwent surgical resection at Northern Jiangsu People's Hospital between January 2020 and August 2025 were retrospectively collected. The data included clinical characteristics, laboratory indices, and radiological features. Patients were divided into a STAS-positive and a STAS-negative group based on postoperative pathological findings. The dataset was randomly split into a training set and a testing set at a 7 : 3 ratio. Feature variables were selected using the maximum relevance and minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator (LASSO) regression. Five machine learning models were constructed: logistic regression (LR), random forest (RF), support vector machine (SVM), light gradient boosting machine (LightGBM), and extreme gradient boosting (XGBoost). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). The shapley additive explanations (SHAP) method was employed to interpret the optimal prediction model. Results A total of 377 patients were included, comprising 177 (46.9%) males and 200 (53.1%) females, with a mean age of (63.31±9.73) years. There were 261 patients in the training set and 116 patients in the testing set. In the training set, statistically significant differences were observed between the STAS-positive group (n=130) and STAS-negative group (n=131) across multiple features, including age, sex, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), clinical T stage, and maximum solid component diameter (P<0.05). A final set of 10 feature variables was selected by combining mRMR and LASSO regression, and five machine learning models (LR, RF, SVM, LightGBM, XGBoost) were developed. The XGBoost model demonstrated optimal performance in both the training and testing sets, achieving AUCs of 0.947 [95%CI (0.920, 0.975)] and 0.943 [95%CI (0.894, 0.993)], respectively. DCA indicated that the XGBoost model provided a high net clinical benefit across a wide range of threshold probabilities. SHAP analysis revealed that the vessel convergence sign, clinical T stage, age, consolidation-to-tumor ratio (CTR), and MLR were the features with the highest contributions to STAS prediction. Conclusion The XGBoost model effectively predicts preoperative STAS status in early-stage lung adenocarcinoma, exhibiting excellent discriminative performance and good clinical interpretability. Key predictors such as the vessel convergence sign, clinical T stage, age and CTR provide a crucial reference for preoperative risk assessment and the individualized selection of surgical strategies, ultimately benefiting patients.

Osteoporosis is a common senile bone metabolism disease， clinically characterized by decreased bone mass， destruction of bone microstructure， increased bone fragility， and easy fracture. It tends to occur in the elderly and postmenopausal women， seriously threatening the quality of life and physical and mental health of the elderly. At present， the treatment of osteoporosis is mainly based on oral western medicines， such as calcium， Vitamin D， and bisphosphonates. Still， there are drawbacks such as a long medication cycle and many adverse reactions. In recent years， due to the advantages of multi-component， multi-pathway， and multi-target， some traditional Chinese medicines and effective ingredients can regulate the osteogenic and osteoclastic differentiation process in both directions and are widely used in the prevention and treatment of osteoporosis. Hippophae rhamnoides is a commonly used herbal medicine， and its fruits are rich in flavonoids， polyphenols， fatty acids， vitamins， and trace elements， which have been proven to have a good anti-osteoporosis effect. Isorhamnetin is the main effective ingredient of Hippophae rhamnoides fruits， which has many pharmacological effects such as anti-inflammation， anti-oxidative stress， anti-aging， and anti-tumor. Studies have shown that isorhamnetin can participate in the regulation of bone metabolism and has a good anti-osteoporosis effect. However， the pharmacological effects and related mechanisms of isorhamnetin against osteoporosis have not been systematically summarized. Therefore， this paper reviewed the pharmacological effects and related mechanisms of isorhamnetin against osteoporosis by referring to relevant literature to provide more basis for the development and application of isorhamnetin.

OBJECTIVES: The integrated endoplasmic reticulum stress inhibitor (ISRIB) is a selective inhibitor of the protein kinase R-like endoplasmic reticulum kinase (PERK) signaling pathway within endoplasmic reticulum stress (ERS) and can improve spatial and working memory in aged mice. Although ERS and oxidative stress are tightly interconnected, it remains unclear whether ISRIB alleviates cognitive impairment by restoring the balance between ERS and oxidative stress. This study aims to investigate the effects and mechanisms of ISRIB on lipopolysaccharide (LPS)-induced cognitive impairment in mice. METHODS: Eight-week-old male ICR mice were randomly divided into 3 groups: Normal saline (NS) group, LPS group, and ISRIB+LPS group. NS and LPS groups received daily intraperitoneal injections of normal saline for 7 days; on day 7, LPS group mice received intraperitoneal LPS (0.83 mg/kg) to establish a cognitive impairment model. ISRIB+LPS group received ISRIB (0.25 mg/kg) intraperitoneally for 7 days, with LPS injected 30 minutes after ISRIB on day 7. Cognitive ability was evaluated by the novel place recognition test (NPRT). Real-time fluorogenic quantitative PCR (RT-qPCR) was used to detect changes in nitric oxide synthase (NOS), superoxide dismutase-1 (SOD-1), and catalase (CAT) gene expression in the hippocampus and prefrontal cortex. Oxidative stress markers malondialdehyde (MDA), glutathione (GSH), and oxidized glutathione (GSSG), were measured in hippocampal and prefrontal cortex tissues. RESULTS: Compared with the NS group, mice in LPS group showed a significant reduction in novel place recognition ratio, upregulation of hippocampal NOS-1 and NOS-2 mRNA, downregulation of SOD-1 and CAT mRNA, increased MDA and GSSG, decreased GSH, and reduced GSH/GSSG ratio (all P<0.05). Compared with the LPS group, mice in ISRIB+LPS group exhibited significantly improved novel place recognition, downregulated NOS-1 and NOS-2 mRNA, upregulated SOD-1 and CAT mRNA, decreased MDA and GSSG, increased GSH, and an elevated GSH/GSSG ratio in the hippocampus (all P<0.05). No significant changes were observed in the prefrontal cortex. CONCLUSIONS ISRIB improves LPS-induced cognitive impairment in mice by restoring the oxidative/antioxidant balance in the hippocampus.
Animals ; Lipopolysaccharides ; Male ; Mice, Inbred ICR ; Cognitive Dysfunction/drug therapy* ; Mice ; Oxidative Stress/drug effects* ; Endoplasmic Reticulum Stress/drug effects* ; Hippocampus/drug effects* ; Nitric Oxide Synthase Type II/genetics* ; Guanidines/pharmacology* ; eIF-2 Kinase/antagonists & inhibitors* ; Signal Transduction/drug effects* ; Superoxide Dismutase/metabolism*

In order to study the effects of prostaglandin D2(PGD2)on cow bone marrow-derived macrophages induced by E.coli,cultured cow bone marrow-derived macrophages were taken as the research object.The effects of endogenous and exogenous PGD2 on the secretion and phagocytosis of E.coli induced proinflammatory cytokines(IL-1β,IL-6 and TNF-α)in macrophages were ana-lyzed.The results showed that the synthesis of PGD2 in macrophages induced by E.coli is depend-ent on the natural pattern recognition receptors TLR2,TLR4 and NLRP3.Inhibition of endogenous PGD2can down-regulate the secretion of pro-inflammatory cytokines(IL-1β,IL-6 and TNF-α)in E.coli induced macrophages(P＜0.001),and inhibition of endogenous PGD2 can enhance the kill-ing function of macrophages to a certain extent(P＜0.01).In addition,exogenous PGD2 could up-regulate the secretion of pro-inflammatory cytokines(IL-1β,IL-6 and TNF-α)in macrophages af-ter E.coli stimulation(P＜0.01),and exogenous PGD2 could weaken the killing function of mac-rophages within a certain concentration range(P＜0.01).Results indicated that PGD2 had certain effects on the secretion of cytokines and phagocytosis and killing function of macrophages induced by E.coli.