ObjectivePhotoacoustic pump-probe imaging can effectively eliminate the interference of blood background signal in traditional photoacoustic imaging, and realize the imaging of weak phosphorescence molecules and their triplet lifetimes in deep tissues. However, background differential noise in photoacoustic pump-probe imaging often leads to large fitting results of phosphorescent molecule concentration and triplet lifetime. Therefore, this paper proposes a novel triplet lifetime fitting method for photoacoustic pump-probe imaging. By extracting the phase of the triplet differential signal and the background noise, the fitting bias caused by the background noise can be effectively corrected. MethodsThe advantages and feasibility of the proposed algorithm are verified by numerical simulation, phantom and in vivo experiments, respectively. ResultsIn the numerical simulation, under the condition of noise intensity being 10% of the signal amplitude, the new method can optimize the fitting deviation from 48.5% to about 5%, and has a higher exclusion coefficient (0.88>0.79), which greatly improves the fitting accuracy. The high specificity imaging ability of photoacoustic pump imaging for phosphorescent molecules has been demonstrated by phantom experiments. In vivo experiments have verified the feasibility of the new fitting method proposed in this paper for fitting phosphoometric lifetime to monitor oxygen partial pressure content during photodynamic therapy of tumors in nude mice. ConclusionThis work will play an important role in promoting the application of photoacoustic pump-probe imaging in biomedicine.

Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.

Objective Based on the interventional operating room,the nursing quality evaluation index system was con-structed under the background of medical union and empirical analysis was conducted,so as to provide support and basis for accu-rate and efficient evaluation of nursing quality in interventional operating room.Methods From July to September 2024,based on evidence-based methods,the relevant literature was retrieved and evaluated,and the structure-process-outcome theory was taken as the basic framework,and the relevant nursing quality indicators were preliminarily drawn up in interventional operating rooms.In October 2024,a total of 28 experts were selected to conduct expert letter consultation(2 rounds)with Delphi method,from which the indicators were revised and finally clarified,and empirical analysis was carried out.Results There were two rounds of expert consultation in this paper.The questionnaire recovery rate of the first round was 85.71％(24/28).The Cs,Ca and Cr of the first round were 0.895,0.942 and 0.919,respectively.The recovery rate of the second round questionnaire,Cs,Ca and Cr of the experts were 100.00％(24/24),0.891,0.941 and 0.916,respectively,and Kendall's W value was within 0.088-0.301(P＜0.05).The final nursing quality sensitive index system consists of 1 structure,5 process and 2 outcome inde-xes,respectively.Fifty patients undergoing interventional surgery were included before and after intervention.Empirical analysis showed that the incidence of adverse events after intervention(4.00％)was lower than that before intervention(16.00％)(P＜0.05).Conclusion The sensitive index of nursing quality based on the background of medical union is practical and scientific,and can provide practical guidance for the evaluation,continuous improvement and optimization of nursing quality in interventional operating room,and reduce the incidence of adverse events.

This study was aimed at establishing a sensitive and specific sandwich ELISA detection method for Brucella.We screened monoclonal capture antibodies and detection antibodies for Brucella detection,and optimized and determined the opti-mal antibody coating time and concentration,as well as the optimal blocking solution,blocking time,and yin-yang critical val-ue.The specificity of this method was verified by examination of other bacteria prone to cross-reacting with Brucella.The sen-sitivity of the method was verified by detection of a gradient dilution of inactivated Brucella.Moreover,the sandwich ELISA detection results were compared with test tube agglutination and qPCR results.The selected capture antibody was 4A12,and the selected detection antibody was 6C12.Experimental analysis indicated that the optimal coating concentration for the 4A12 capture antibody was 5 μg/mL,and the optimal dilution ratio for the 6C12 detection antibody was 1∶2000.The optimal coating conditions were overnight at 4℃,and blocking with 5％skim milk powder for 2 hours.The established double antibody sand-wich ELISA method reacted with only Brucella but not other bacteria,thus demonstrating the method's good specificity.Inac-tivated Brucella solution was still detectable after dilution to 1 × 105 CFU/mL,thus demonstrating the method's good sensitiv-ity.The intra-and inter batch coefficients of variation were both below 10％,thus indicating the method's good repeatability.Thus,this study successfully established a dual antibody sandwich ELISA method for Brucella detection,which has good spe-cificity and sensitivity,and might provide an effective approach for the precise diagnosis and effective prevention and control of brucellosis.

AIM To explore the differential metabolites of different aged Citrus reticulate'Chachi'and their processed cakes.METHODS Non-targeted metabolomics technology of GC-TOF-MS was used to analyze the chemical constituents.The data was processed by principal component analysis and orthogonal partial least squares discriminant analysis,and the differential metabolites were identified.RESULTS A total of 74 differential metabolites were identified,including 16 glycosides,14 organic acids and their derivatives,11 amino acids and their derivatives,and 4 flavonoids.Comparative analysis revealed 40 and 30 differential metabolites between fresh C.reticulate'℃hachi'and 3-year or 5-year aged samples,respectively.Furthermore,27 and 34 differential metabolites were identified between the 3-year or 5-year aged samples and their corresponding processed cakes,respectively.Differential metabolites among fresh,aged C.reticulate'Chachi',and processed cakes were predominantly enriched in 6 metabolic pathways,including the biosynthesis of secondary metabolites.Specifically,differential metabolites between 3-year aged C.reticulate'Chachi'and its processed cake were significantly enriched in 4 pathways,such as ABC transporters.Differential metabolites between 5-year aged C.reticulate'Chachi'and its processed cake were mainly enriched in 5 pathways,including carbon metabolism.CONCLUSION Non-targeted metabolomics technology can elucidate the chemical compositional differences among fresh/aged and processed cakes of C.reticulate'Chachi',laying a foundation for the research into C.reticulate'Chachi'aging processing techniques and the development of processed products.

Olfactory disorders are a common symptom in patients with chronic rhinosinusitis, and their diagnosis and treatment have garnered extensive attention from both patients and doctors. Currently, there are various evaluation and treatment methods for olfactory dysfunction; however, choosing a simpler and more accurate assessment, as well as an effective treatment, remains a clinical challenge. In this article, we review the assessment and treatment methods commonly used in clinical practice in recent years to provide better support for the diagnosis and treatment of olfactory disorders.
Humans ; Olfaction Disorders/etiology* ; Sinusitis/complications* ; Chronic Disease ; Rhinitis/complications* ; Rhinosinusitis

Cancer stem cells (CSCs) are proposed to account for the progression, metastasis, and recurrence of diverse malignancies. However, the disorganized vasculars in tumors hinder the accumulation and penetration of nanomedicines, posing a challenge in eliminating CSCs located distantly from blood vessels. Herein, a pair of twin-like small-sized nanoparticles, sunitinib (St)-loaded ROS responsive micelles (RM@St) and salinomycin (SAL)-loaded GSH responsive micelles (GM@SAL), are developed to normalize disordered tumor vessels and eradicate CSCs. RM@St releases sunitinib in response to the abundant ROS in the tumor extracellular microenvironment for tumor vessel normalization, which improved intratumor accumulation and homogeneous distribution of small-sized GM@SAL. Sequentially, GM@SAL effectively accesses CSCs and achieves reduction-responsive drug release at high GSH concentrations within CSCs. More importantly, RM@St significantly extends the window of vessel normalization and enhances vessel integrity compared to free sunitinib, thus further amplifying the anti-tumor effect of GM@SAL. The combination therapy of RM@St plus GM@SAL produces considerable depression of tumor growth, drastically reducing CSCs fractions to 5.6% and resulting in 78.4% inhibition of lung metastasis. This study offers novel insights into rational nanomedicines designed for superior therapeutic effects by vascular normalization and anti-CSCs therapy.

OBJECTIVE: To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis (TB) in the Guangdong Province between 2010 and 2019. METHOD: Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering. Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive (ST-CAR) model. RESULTS: Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000 in 2019. Spatial hotspots were found in northeastern Guangdong, particularly in Heyuan, Shanwei, and Shantou, while Shenzhen, Dongguan, and Foshan had the lowest rates in the Pearl River Delta. The ST-CAR model showed that the TB risk was lower with higher per capita Gross Domestic Product (GDP) [Relative Risk ( RR), 0.91; 95% Confidence Interval ( CI): 0.86-0.98], more the ratio of licensed physicians and physician ( RR, 0.94; 95% CI: 0.90-0.98), and higher per capita public expenditure ( RR, 0.94; 95% CI: 0.90-0.97), with a marginal effect of population density ( RR, 0.86; 95% CI: 0.86-1.00). CONCLUSION The incidence of TB in Guangdong varies spatially and temporally. Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection. Strategies focusing on equitable health resource distribution and economic development are the key to TB control.
Humans ; China/epidemiology* ; Incidence ; Bayes Theorem ; Spatio-Temporal Analysis ; Tuberculosis/epidemiology* ; Socioeconomic Factors