Objective To develop and validate a model to predict the risk of radiation-induced lung injury (RILI) and assess its clinical feasibility. Methods Clinical data from 125 patients with non-small cell lung cancer (NSCLC) were included in the study. The patients were divided into training group (88 cases) and validation group (38 cases). Key predictive factors were identified using univariate and multivariate logistic regression analyses combined with least absolute shrinkage and selection operator (LASSO) regression. A predictive model was constructed and evaluated using a nomogram, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis. Results The key variables identified by the model were tumor volume (P = 0.017), Eastern Cooperative Oncology Group performance status score (P = 0.035), 95% of the minimum dose to the target volume (P = 0.028), percentage of bilateral lung volume receiving 20 Gy of radiation (P < 0.001), and neutrophil-to-lymphocyte ratio (P = 0.021). The ROC curve showed that the areas under the curve (AUC) for the model in the training and validation groups were 0.987 and 0.992, respectively, indicating good predictive ability. The calibration curve and decision curve further confirmed the accuracy and clinical practicability of the model. Conclusion The predictive model proposed in this study can accurately assess the risk of developing RILI in patients with NSCLC who have undergone radiotherapy, demonstrating its potential value in clinical practice.

Primary liver cancer is one of the most common causes of cancer-related deaths in China,with hepatocellular carcinoma(HCC)accounting for 75%-85%.Approximately 70%of HCC patients are in the advanced stage at the time of diagnosis and miss the opportunity for radical surgery,leading to a poor prognosis.Yttrium-90 microsphere selective internal radiation therapy(90Y-SIRT),an emerging therapeutic modality,delivers radioactive microspheres via the hepatic artery to target tumors and uses beta radiation for localized tumor ablation.Compared to conventional transarterial chemoembolization and pharmacotherapy,90Y-SIRT shows the advan-tages of significant clinical benefits,good safety profiles,and broad applicability across diverse patient populations.This article re-views the advances in the application of 90Y-SIRT in HCC treatment.

Primary liver cancer is a malignant tumor with high incidence and mortality rates worldwide,and the early diagnosis of pri-mary liver cancer and the optimization of precise treatment strategies have become critical issues in the healthcare field.Due to the in-sufficient capabilities for molecular characterization,it is increasingly difficult for traditional imaging techniques to meet clinical needs in the era of precision medicine.Multimodal molecular imaging technology integrates the advantages of imaging modalities such as ul-trasound imaging,magnetic resonance imaging,and optical imaging,thereby achieving synergistic enhancement between molecular bio-logical information of liver cancer and precise anatomical localization and demonstrating a significant value in the diagnosis and treat-ment of liver cancer.This article reviews the advances in the application of multimodal molecular imaging in the early diagnosis,pre-cise treatment,and therapeutic efficacy monitoring of liver cancer.

Objective By using ultrasonography to calculate the ratio of optic nerve sheath diameter(ONSD)at 3 mm behind eyeball to the eyeball transverse diameter(ETD),based on which to evaluate the effect of dexmedetomidine on intracranial pressure(ICP)in patients with intracranial aneurysm after receiving interventional embolization under general anesthesia.Methods A total of 40 patients with intracranial aneurysm,who were scheduled to receive interventional embolization under general anesthesia at the Affiliated Lihuili Hospital of Ningbo University of China from May 2023 to November 2023,were selected for this study.By using random number table method,the patients were divided into control group(group C)and dexmedetomidine group(group D)with 20 patients in each group.Standardized anesthesia strategy was adopted in both groups.For patients of group D,a loading dose of dexmedetomidine was pumped at a velocity of 1 μg/(kg·h)for 10 min before the surgery,the pumping was continued at 0.5 μg/(kg·h)velocity during the operation,and the pumping stopped half an hour before the end of the operation.For patients of group C,the same anesthesia strategy was used,while no any special treatment was given.At the different time points,including before awakening(T0),immediately after extubation(T1),and 5 min(T2),10 min(T3),15 min(T4)after extubation,ONSD at 3 mm behind eyeball and ETD were measured by transorbital ultrasonography,and ONSD/ETD ratio was calculated to evaluate ICP.The mean arterial pressure(MAP),heart rate(HR),blood oxygen saturation(SPO2),severity of cough,and extubation time were recorded at the time to remove the catheter.Results Compared with the data obtained at T0,the ONSD/ETD ratios obtained at T1 and T2 were increased in both groups(P＜0.05),while the ONSD/ETD ratios obtained at other time points were not significantly different from the ONSD/ETD ratio obtained at T0(P＞0.05).Compared with Group C,in Group D the ONSD/ETD ratios obtained at T1 and T2 were smaller,the differences were statistically significant(P＜0.05).The incidence of moderate to severe cough in Group D was lower than that in Group C(P＜0.05).Compared with Group C,in Group D the HR and MAP determined at the time of removing catheter were lower(P＜0.05).The extubation time in Group D was longer than that in group C,the difference was statistically significant(P＜0.05).Conclusion ONSD/ETD ratio calculated by ultrasono-graphy can objectively reflect the changes of ICP during the extubation period.Dexmedetomidine can reduce the elevation degree of ICP through effectively inhibiting cough reflex and circulatory fluctuation during tracheal extubation.However,dexmedetomidine may increase the incidence of adverse events such as bradycardia,delayed extubation,etc.

Objective To investigate the value of cranial CT cisternal grading combined with D-dimer(D-D)and Glasgow Coma Scale(GCS)score in predicting the short-term postoperative prog-nosis of patients with severe traumatic brain injury.Methods A total of 165 patients with severe trau-matic brain injury who were treated in the hospital from January 2019 to May 2024 were selected as study subjects,all underwent craniotomy surgery.Postoperative follow-up was conducted for 3 months to analyze the differences in clinical data and preoperative indicators such as cranial CT cisternal grad-ing,D-D levels,and GCS scores between patients with poor and good prognosis.The value of cranial CT cisternal grading,D-D levels,and GCS scores in predicting short-term postoperative poor prognosis in patients with severe traumatic brain injury was also analyzed.Results Compared with patients with good prognosis,patients with poor prognosis had higher proportion of age,cranial CT cisternal grading of Ⅰ to Ⅱ,D-D levels,and GCS scores＜6(P＜0.05).There were no statistically significant differences in C-reactive protein,prothrombin time,activated partial thromboplastin time,international normalized ratio,total cholesterol,triglycerides,high-density lipoprotein cholesterol,and low-density lipoprotein cholesterol levels between patients with poor and good prognosis(P＞0.05).Cranial CT cisternal grading,D-D levels,and GCS scores were influencing factors for short-term postoperative poor prognosis in patients with severe traumatic brain injury(P＜0.05).The area under the curve for poor prognosis by three indicators in combination was 0.941(95％CI,0.906 to 0.975),which was higher than the area under the curve for the individual predictions of cranial CT cisternal grad-ing,D-D levels,and GCS scores(P＜0.05).Conclusion The influencing factors for short-term postoperative prognosis in patients with severe traumatic brain injury include cranial CT cisternal grading,D-D levels,and GCS scores.The model based on these three indicators has certain appli-cation value in predicting patient prognosis.

Understanding the metabolism of endogenous and exogenous substances in the human body is essential for elucidating disease mechanisms and evaluating the safety and efficacy of drug candidates during the drug development process.Recent advancements in artificial intelligence(AI),particularly in machine learning(ML)and deep learning(DL)techniques,have introduced innovative approaches to metabolism research,enabling more accurate predictions and insights.This paper emphasizes computational and AI-driven methodologies,highlighting how ML enhances predictive modeling for human metabolism at the molecular level and facilitates integration into genome-scale metabolic models(GEMs)at the omics level.Challenges still remain,including data heterogeneity and model interpretability.This work aims to provide valuable insights and references for researchers in drug discovery and development,ultimately contributing to the advancement of precision medicine.

Objective:To establish a rapid detection method based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry(MALDI-TOF MS)for drug resistance of Carbapenem-resistant Enterobacteriaceae(CRE),so as to provide basis for enhancing clinically diagnostic effect.Methods:A total of 120 suspected CRE strains that were isolated from the clinical laboratory of Jiading District Central Hospital Affiliated to Shanghai University of Medicine&Health Sciences during October 2023 and September 2024 were collected,and the experimental detection of 44 strains was finally completed.The 44 suspected CRE bacterial strains were all from hospitalized patients.A rapid detection protocol based on the MALDI-TOF MS platform was initially established and improved,and experimental detection was carried out using the fully automatic rapid microbial mass spectrometry detection system(VITEK MS).The results of identification review and antimicrobial susceptibility test(AST)for VitEK-2 Compact strain was used as the reference standard.The screening results and detection efficacy of two kinds of detection methods were compared.Results:In the 44 suspected CRE strains,31 CRE strains were screened out by MALDI-TOF MS detection,and 31 CRE stains were screened out by VITEK-2 Compact recheck detection.In them,one strain of Enterobacter cloacae was confirmed as negativity by the MALDI-TOF MS test,but it was confirmed as CRE by the VITEK-2 Compact test.One strain of Klebsiella pneumoniae was confirmed as positivity by the MALDI-TOF MS test,but it was confirmed as mediator for carbapenem drugs by the VITEK-2 Compact test.The tested results of VITEK-2 Compact was used as standard,the results of four-grid table(2×2 contingency table)statistical method indicated that the sensitivity,specificity,accuracy rate and Youden index(R)of MALDI-TOF MS were respectively 96.7%,92.3%,100%and 89.1%.Conclusion:The rapid detection method based on the MALDI-TOF MS platform for CRE drug resistance has simple operation process and high accuracy rate,which can provide a basis for the application of targeted antibacterial drugs at early stage.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Neurodegenerative disorders (NDDs) are prevalent chronic conditions characterized by progressive synaptic loss and pathological protein alterations. Increasing evidence suggested that mitochondrial quality control (MQC) serves as the key cellular process responsible for clearing misfolded proteins and impaired mitochondria. Herein, we provided a comprehensive analysis of the mechanisms through which MQC mediates the onset and progression of NDDs, emphasizing mitochondrial dynamic stability, the clearance of damaged mitochondria, and the generation of new mitochondria. In addition, traditional Chinese medicines (TCMs) and their active monomers targeting MQC in NDD treatment have been demonstrated. Consequently, we compiled the TCMs that show great potential in the treatment of NDDs by targeting MQC, aiming to offer novel insights and a scientific foundation for the use of MQC stabilizers in NDD prevention and treatment.

Understanding the metabolism of endogenous and exogenous substances in the human body is essential for elucidating disease mechanisms and evaluating the safety and efficacy of drug candidates during the drug development process. Recent advancements in artificial intelligence (AI), particularly in machine learning (ML) and deep learning (DL) techniques, have introduced innovative approaches to metabolism research, enabling more accurate predictions and insights. This paper emphasizes computational and AI-driven methodologies, highlighting how ML enhances predictive modeling for human metabolism at the molecular level and facilitates integration into genome-scale metabolic models (GEMs) at the omics level. Challenges still remain, including data heterogeneity and model interpretability. This work aims to provide valuable insights and references for researchers in drug discovery and development, ultimately contributing to the advancement of precision medicine.