Objective To explore the application value of dual-phase dual-energy CT (DECT) perfusion imaging in preoperative lung function assessment of lung cancer patients. Methods Data were collected from patients with stageⅠA non-small cell lung cancer who underwent surgical treatment in the Department of Thoracic Surgery, the First Affiliated Hospital of Nanjing Medical University, from November 2022 to June 2024. All patients underwent DECT perfusion imaging and pulmonary function testing (PFT) before surgery. PFT observation indicators included ventilation function indicators such as forced expiratory volume in one second (FEV1), forced vital capacity (FVC), 1-second rate (FEV1/FVC), maximal voluntary ventilation (MVV), and diffusion function indicators such as diffusing capacity for carbon monoxide (DLCO) and DLCO per liter of alveolar volume (DLCO/VA). The software eXamine was used to obtain quantitative parameters of DECT perfusion imaging, including volume parameters and perfusion parameters of both lungs and each lung lobe. The correlation between the volume parameters and perfusion parameters of both lungs and the ventilation and diffusion function indicators of the patients, as well as the differences in quantitative parameters of each lung lobe, was analyzed. Results The end-inspiration lung volume and biphasic volume difference were strongly positively correlated with FEV1 and FVC (r=0.636, r=0.682, r=0.614, r=0.624, P<0.001) and moderately positively correlated with MVV and DLCO (r=0.499, r=0.514, r=0.549, r=0.447, P<0.001); the end-expiration lung volume was weakly negatively correlated with DLCO/VA (r=−0.295, P=0.026); the volume ratio was positively correlated with FEV1, FVC, MVV, and MVV% (r=0.424, r=0.399, r=0.415, r=0.310, P<0.05); the end-inspiration iodine content was weakly positively correlated with DLCO/VA% (rs=0.292, P=0.030); the end-expiration iodine content was weakly positively correlated with FEV1, FVC, MVV, DLCO%, and DLCO/VA (r=0.307, r=0.299, r=0.295, r=0.366, r=0.320, P<0.05) and moderately positively correlated with DLCO (r=0.439, P<0.001); the end-inspiration iodine concentration was negatively correlated with FEV1, FVC, MVV, and MVV% (rs=−0.407, rs=−0.426, rs=−0.352, rs=−0.277, P＜0.05); the end-expiratory phase iodine concentration was moderately positively correlated with DLCO/VA (r=0.403, P=0.002); both the iodine concentration difference and the iodine concentration ratio were moderately positively correlated with FEV1, FEV1%, FVC, MVV, MVV% (P<0.05). The lung volume and iodine concentration ratio values were both highest in the left upper lung lobe and lowest in the right middle lung lobe; the differences in lung volume, lung volume ratio, intrapulmonary iodine content, and intrapulmonary iodine concentration were all highest in the lower lobes of both lungs and lowest in the middle lobe of the right lung. Conclusion Dual-phase DECT perfusion imaging can accurately assess overall lung function and quantify regional lung function.

ObjectiveZheng’s San Qi San (ZSQS) power, a classic traditional Chinese medicine (TCM) formula, is used for treating soft tissue injuries involving muscles, tendons, and ligaments. However, its underlying therapeutic mechanisms remain unclear. This study aimed to screen and identify pharmaceutically active ingredients and their candidate biomolecule targets, and further elucidate the molecular mechanism of ZSQS in the treatment of skeletal muscle injury. MethodsNetwork pharmacology was employed to construct “ZSQS-component-target”, “protein-protein interaction (PPI)” and “active ingredient-core protein-pathway” networks to predict the key active ingredients and potential core targets of ZSQS for skeletal muscle injury. The predicted results were then validated via microarray data from the GEO database. Molecular docking was then performed to assess the binding ability between the screened active ingredients of ZSQS and the candidate core targets. Moreover, liquid chromatography-mass spectrometry (LC-MS) was used for qualitative and quantitative analysis to verify the active components of the drug and ZSQS serum. Finally, an animal model of eccentric exercise-induced skeletal muscle injury and a myotube cell model of oxidative stress-induced injury were established to validate the effects of ZSQS and its interventional effects on the biological functions of critical targets, thereby demonstrating the potential therapeutic mechanism of ZSQS. ResultsAmong the 111 active components identified in ZSQS and their corresponding 204 targets related to the skeletal muscle injury repair process, 14 core targets (including AKT1) and 4 core active components (quercetin, luteolin, kaempferol, and β‑sitosterol) were screened out, while the corresponding metabolites of quercetin, luteolin and kaempferol were detected in the ZSQS serum. Among these targets, 5 candidate genes (IL-6, CASP3, HIF1A, STAT3, and JUN) overlapped with the differential expression screening results with GEO data, and IL-6 was confirmed to be enriched in the PI3K/AKT pathway. Combined with the prediction results of the AKT expression levels, these findings suggest that the phosphorylation level of AKT1 plays a core role in the therapeutic mechanism of ZSQS. Molecular docking analysis further revealed that the PH domain of AKT1 had high binding energy with all 4 core active components, as verified by LC-MS. Finally, animal model studies have shown the promoting effect of ZSQS administration on skeletal muscle injury repair and its possible antioxidant damage mechanism. Cell model studies further demonstrated that ZSQS-containing serum, core active ingredient combination therapy, and quercetin monomer could increase the phosphorylation level of AKT, promote the nuclear translocation of Nrf2, upregulate the expression of downstream antioxidant enzymes (SOD, GPx, and GR), and inhibit the expression of inflammatory factors (IL-6 and TNF-α), thereby alleviating oxidative stress and the inflammatory response. ConclusionZSQS alleviates skeletal muscle injury mainly by activating the AKT/Nrf2 signaling pathway, enhancing cellular antioxidant and anti-inflammatory capabilities. The results of this study provide a scientific basis for the clinical application and modernized development of ZSQS.

Objective To develop a rapid detection method for tiletamine that is easy to operate and low-cost under the premise of ensuring sensitivity and accuracy,to assist in carrying out rapid screening and drug control work on-site.Methods This study integrates dual-ligand copper nanozymes with mo-lecular imprinting technology.Initially,copper nanozymes were synthesized using readily available raw materials at 120℃.Subsequently,specific cavities were imprinted on their surface at room temperature using a sol-gel method to construct a novel fluorescent sensing probe.This probe was characterized and methodologically validated,and then applied to the detection of actual samples.Results The developed probe exhibited stable fluorescence properties,strong anti-interference capability,and excellent specificity and sensitivity,with a detection limit of 5 ng/mL and a quantitative concentration range from 15 to 500 ng/mL.It enabled the rapid detection of tiletamine in real samples such as blood and e-cigarette oil.Conclusion This fluorescent probe can be used for rapid detection and on-site preliminary screening of tiletamine in various types of samples.It significantly improves the detection efficiency and reduces analysis costs,showing high research value and broad application prospects.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

OBJECTIVE: To analyze the correlation between baseline ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and circulating tumor DNA (ctDNA) parameters in diffuse large B-cell lymphoma (DLBCL) and compare the value of the two methods in the prognosis assessment of DLBCL. METHODS: A total of 50 DLBCL patients confirmed by pathology, including 26 males and 24 females, with a median age of 55.5(43.5, 64.0) years from August 2018 to April 2021 were retrospectively analyzed. PET/CT parameters, including maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), ctDNA parameters, including mutation number, mutation gene number, mean variant allele frequency (meanVAF), and clinical data of patients were collected. The relationship between PET/CT, ctDNA parameters and patient clinical features was analyzed, as well as the correlation between PET/CT and ctDNA parameters. The diagnostic efficacy of PET/CT and ctDNA parameters was compared. Patients were followed up for 36-69 months. Progression-free survival (PFS) was calculated, and survival analysis was performed. RESULTS: PET/CT parameters all had good correlation with ctDNA parameters, among which MTV was moderately correlated with mutation number, mutation gene number, and meanVAF (r_s=0.72, 0.64, 0.71), TLG was strongly correlated with mutation number (r_s=0.83) and moderately correlated with mutation gene number and mean VAF (r_s=0.72, 0.79), while SUVmax was weakly correlated with mutation number, mutation gene number and meanVAF (r_s=0.47, 0.46, 0.47). PET/CT parameters and ctDNA parameters showed no statistically significant differences in predicting the prognosis of DLBCL and area under the curve (AUC) of receiver operating characteristic (ROC) (P >0.05). However, the specificity of MTV and TLG in predicting prognosis of 1-, 2- and 3-year PFS was better than that of meanVAF (all P < 0.05), while the sensitivity of meanVAF in predicting prognosis of 1-, 2- and 3-year PFS was better than that of MTV (all P < 0.05). The optimal cut-off values of SUVmax, MTV, TLG, mutation number, mutation gene number and meanVAF in predicting tumor progression were obtained using ROC curve analysis. Patients were divided into high and low expression groups according to the cut-off values and survival analysis was performed. The results of survival analysis showed that there were statistically significant differences in PFS between the high and low expression groups (all P < 0.05). CONCLUSION Baseline ¹⁸F-FDG PET/CT and ctDNA parameters can both predict the prognosis of DLBCL, and are equally valuable in the evaluation of DLBCL prognosis.
Humans ; Lymphoma, Large B-Cell, Diffuse/diagnosis* ; Positron Emission Tomography Computed Tomography ; Fluorodeoxyglucose F18 ; Middle Aged ; Prognosis ; Female ; Male ; Circulating Tumor DNA ; Retrospective Studies ; Adult ; Mutation

OBJECTIVES: To characterize fine particulate matter (PM _2.5)-bound polycyclic aromatic hydrocarbons (PAHs) emitted from different cooking fumes and their exposure routes and assess their health-associated impact to provide a reference for health risk prevention from PAH exposure across different age and sex groups. METHODS: Sixteen PM _2.5-bound PAHs emitted from 11 cooking styles were analyzed using GC-MS/MS. The health hazards of these PAHs in the Handan City population (stratified by age and sex) were predicted using the incremental lifetime cancer risk ( ILCR) model. The respiratory deposition doses ( RDDs) of the PAHs in children and adults were calculated using the PM _2.5 deposition rates in the upper airway, tracheobronchial, and alveolar regions. RESULTS: The total concentrations of PM _2.5-bound PAHs ranged from 61.10 to 403.80 ng/m ³. Regardless of cooking styles, the ILCR _total values for adults (1.23 × 10 ^-6 to 3.70 × 10 ^-6) and older adults (1.28 × 10 ^-6 to 3.88 × 10 ^-6) exceeded the acceptable limit of 1.00 × 10 ^-6. With increasing age, the ILCR _total value first declined and then increased, varying substantially among the population groups. Cancer risk exhibited particularly high sensitivity to short exposure to barbecue-derived PAHs under equivalent body weights. Furthermore, barbecue, Sichuan and Hunan cuisine, Chinese cuisine, and Chinese fast food were associated with higher RDDs for both adults and children. CONCLUSION ILCR _total values exceeded the acceptable limit for both females and males of adults, with all cooking styles showing a potentially high cancer risk. Our findings serve as an important reference for refining regulatory strategies related to catering emissions and mitigating health risks associated with cooking styles.
Humans ; Polycyclic Aromatic Hydrocarbons/analysis* ; Cooking/methods* ; Male ; Female ; Particulate Matter/analysis* ; Adult ; Child ; Middle Aged ; Air Pollutants/analysis* ; Adolescent ; Air Pollution, Indoor/analysis* ; Young Adult ; Child, Preschool ; Aged ; China ; Inhalation Exposure ; Age Factors ; Sex Factors ; Cities ; Infant

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Objective:To explore the effect of preoperative visits based on lean management theory in the preoperative psychological state of patients undergoing cardiopulmonary bypass surgery.Methods:According to the coin toss method,72 patients undergoing cardiopulmonary bypass surgery admitted to the Cardiothoracic Surgery Department of Chenzhou First People's Hospital from May 2024 to August 2024 were randomly divided into control group and observation group,with 36 cases in each group.The control group was given routine preoperative visits,and the observation group was given preoperative visits based on lean management theory on the basis of the control group.The psychological state,information demand level,vital signs and satisfaction of the patients were compared between the two groups 1 day before operation and when entering the room.Results:After intervention,the scores of State Anxiety Scale(S-AI)and Amsterdam Preoperative Anxiety and Information Scale(APAIS)were decreased in both groups,and the observation group were significantly lower than control group(P＜0.05).The vital signs(heart rate,systolic blood pressure and diastolic blood pressure)in observation group were lower than control group(P＜0.05).After intervention,the satisfaction of patients in observation group was significantly increased(P＜0.05).Conclusion:The implementation of preoperative visit based on lean management theory can help improve the preoperative psychological state of patients undergoing cardiopulmonary bypass surgery,eliminate anxiety,provide patients with more targeted surgical information support for patients,stabilize patients 'vital signs,and improve patients' satisfaction.