ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

It has gradually become a consensus in the industry that the traditional Chinese medicine gypsum should be decocted first, but the understanding of decocting method is not completely unified in the works of doctors since ancient times, and there are occasional disputes about whether it is necessary to decocting first. In this study, the phase determination, physical and chemical characterization, qualitative and quantitative analysis of inorganic and organic components of the decoctions of herbal pairs and the whole prescription Maxingshigan decoction with gypsum as the center, and the pre-decoctions and co-decoctions of them were carried out to explore the scientific connotation of the pre-decoctions of gypsum. Results show that decoction phases were different between the co-decoctions and pre-decoctions of licorice-gypsum (Gancao-Shigao, GC-SG), ephedra-gypsum (Mahuang-Shigao, MH-SG) and almond-gypsum (Xingren-Shigao, XR-SG). The results of the micromorphology, particle size and zeta potential of herbal pairs and prescription (Quanfang, QF) showed that the supramolecular particles in pre-decoctions were smaller, more uniform and more stable than the co-decoctions. The results of organic components analysis showed that different cooking methods did not change the organic composition and content. ICP-OES results showed that the content of inorganic components in pre-decoctions was higher than in co-decoctions for the same boiling time of gypsum. The IR results showed that the pre-decoctions had stronger chemical functional group effect than the co-decoctions. To sum up, compared with the co-decoction, the pre-decoction of gypsum has different phase state and chemical composition interaction, and the difference of inorganic composition is an important material basis affecting the change of phase state compared with the co-decoction. It indicates that the material basis of traditional Chinese medicine decoction is indeed different whether gypsum is decocted first or not, which can provide a basis for the clinical application of decocted gypsum.

Anti-tumor traditional Chinese medicine has a long history of clinic application, in which the star molecules have always been the hotspot of modern drug research, but they are limited by the solubility, stability, targeting, bioactivity or toxicity of the monomer components of traditional Chinese medicine anti-tumor star molecules and other pharmacokinetic problems, which hinders the traditional Chinese medicine anti-tumor star molecules for further clinical translation and application. Currently, the nanosystems prepared by supramolecular technologies such as molecular self-assembly and nanomaterial encapsulation have broader application prospects in improving the anti-tumor effect of active components of traditional Chinese medicine, which has attracted extensive attention from scholars at home and abroad. In this paper, we systematically review the research progress in preparation of supramolecular nano-systems from anti-tumor star molecule of traditional Chinese medicine, and summarize the two major categories and ten small classes of carrier-free and carrier-based supramolecular nanosystems and their research cases, and the future development direction is put forward. The purpose of this paper is to provide reference for the research and clinical transformation of using supramolecular technology to improve the clinical application of anti-tumor star molecule of traditional Chinese medicine.

Nanozyme is novel nanoparticle with enzyme-like activity, which can be classified into peroxidase-like nanozyme, catalase-like nanozyme, superoxide dismutase-like nanozyme, oxidase-like nanozyme and hydrolase-like nanozyme according to the type of reaction they catalyze. Since researchers first discovered Fe₃O₄ nanoparticles with peroxidase-like activity in 2007, a variety of nanoparticles have been successively found to have catalytic activity and applied in bioassays, inflammation control, antioxidant damage and tumor therapy, playing a key role in disease diagnosis and treatment. We summarize the use of nanozymes with different classes of enzymatic activity in the diagnosis and treatment of diseases and describe the main factors influencing nanozyme activity. A Mn-based peroxidase-like nanozyme that induces the reduction of glutathione in tumors to produce glutathione disulfide and Mn²⁺, which induces the production of reative oxygen species (ROS) in tumor cells by breaking down H₂O₂ in physiological media through Fenton-like action, thereby inhibiting tumor cell growth. To address the limitation of tumor tissue hypoxia during photodynamic tumor therapy, the effect of photodynamic therapy is significantly enhanced by using hydrogen peroxide nanozymes to catalyze the production of oxygen from H₂O₂. In pathological states, where excess superoxide radicals are produced in the body, superoxide dismutase-like nanozymes are able to selectively regulate intracellular ROS levels, thereby protecting normal cells and slowing down the degradation of cellular function. Based on this principle, an engineered nanosponge has been designed to rapidly scavenge free radicals and deliver oxygen in time to save nerve cells before thrombolysis. Starvation therapy, in which glucose oxidase catalyzes the hydrolysis of glucose to gluconic acid and hydrogen peroxide in cancer cells with the involvement of oxygen, attenuates glycolysis and the production of intermediate metabolites such as nucleotides, lipids and amino acids, was used to synthesize an oxidase-like nanozyme that achieved effective inhibition of tumor growth. Furthermore, by fine-tuning the Lewis acidity of the metal cluster to improve the intrinsic activity of the hydrolase nanozyme and providing a shortened ligand length to increase the density of its active site, a hydrolase-like nanozyme was successfully synthesized that is capable of cleaving phosphate bonds, amide bonds, glycosidic bonds and even biofilms with high efficiency in hydrolyzing the substrate. All these effects depend on the size, morphology, composition, surface modification and environmental media of the nanozyme, which are important aspects to consider in order to improve the catalytic efficiency of the nanozyme and have important implications for the development of nanozyme. Although some progress has been made in the research of nanozymes in disease treatment and diagnosis, there are still some problems, for example, the catalytic rate of nanozymes is still difficult to reach the level of natural enzymes in vivo, and the toxic effects of some heavy metal nanozymes material itself. Therefore, the construction of nanozyme systems with multiple functions, good biocompatibility and high targeting efficiency, and their large-scale application in diagnosis and treatment is still an urgent problem to be solved. (1) To improve the selectivity and specificity of nanozymes. By using antibody coupling, the nanoparticles are able to specifically bind to antigens that are overexpressed in certain cancer cells. It also significantly improves cellular internalization through antigen-mediated endocytosis and enhances the enrichment of nanozymes in target tissues, thereby improving targeting during tumor therapy. Some exogenous stimuli such as laser and ultrasound are used as triggers to control the activation of nanozymes and achieve specific activation of nanozyme. (2) To explore more practical and safer nanozymes and their catalytic mechanisms: biocompatible, clinically proven material molecules can be used for the synthesis of nanoparticles. (3) To solve the problem of its standardization and promote the large-scale clinical application of nanozymes in biomonitoring. Thus, it can go out of the laboratory and face the market to serve human health in more fields, which is one of the future trends of nanozyme development.

Currently,human health due to corona virus disease 2019(COVID-19)pandemic has been seriously threatened.The coronavirus severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)spike(S)protein plays a crucial role in virus transmission and several S-based therapeutic approaches have been approved for the treatment of COVID-19.However,the efficacy is compromised by the SARS-CoV-2 evolvement and mutation.Here we report the SARS-CoV-2 S protein receptor-binding domain(RBD)inhibitor licorice-saponin A3(A3)could widely inhibit RBD of SARS-CoV-2 variants,including Beta,Delta,and Omicron BA.1,XBB and BQ1.1.Furthermore,A3 could potently inhibit SARS-CoV-2 Omicron virus in Vero E6 cells,with EC50 of 1.016 pM.The mechanism was related to binding with Y453 of RBD deter-mined by hydrogen-deuterium exchange mass spectrometry(HDX-MS)analysis combined with quan-tum mechanics/molecular mechanics(QM/MM)simulations.Interestingly,phosphoproteomics analysis and multi fluorescent immunohistochemistry(mIHC)respectively indicated that A3 also inhibits host inflammation by directly modulating the JNK and p38 mitogen-activated protein kinase(MAPK)path-ways and rebalancing the corresponding immune dysregulation.This work supports A3 as a promising broad-spectrum small molecule drug candidate for COVID-19.

Objective:To investigate the predictive value of high-resolution magnetic resonance vessel wall imaging (HRMR-VWI) features for the etiology of acute ischemic stroke (AIS) caused by intracranial large vessel occlusion (LVO).Methods:Patients diagnosed with AIS caused by LVO at the Affiliated Hospital of Yangzhou University from August 1, 2019 to August 1, 2022 were retrospectively collected. All patients underwent HRMR-VWI evaluation and endovascular treatment between 4.5 and 24 hours after onset. Complete recanalization of occluded vessels after direct aspiration first-pass was defined as embolic LVO, and those with residual stenosis >50% after the direct aspiration first-pass were classified as intracranial atherosclerotic stenosis related LVO (ICAS-LVO).Results:A total of 28 patients were included. Their age was 65.32±2.23 years, 20 (71.4%) were males. There were 22 patients (78.6%) in the embo-LVO group and 6 (21.4%) in the ICAS-LVO group. Multivariate logistic regression analysis showed that the remodeling index was an independent predictor of ICAS-LVO (odds ratio 1.081, 95% confidence interval 1.001-1.167; P=0.046). The receiver operating characteristic curve analysis showed that the area under the curve of the remodeling index for predicting ICAS-LVO was 0.882 (95% confidence interval 0.724-1.00; P=0.003). The optimal cutoff value was 1.1, and the predictive sensitivity and specificity were 66.7% and 100.0%, respectively. Conclusions:The HRMR-VWI remodeling index is an independent predictor of ICAS-LVO, with a remodeling index ≥1.1 indicating ICAS-LVO. HRMR-VWI can help identify the etiology of patients with AIS caused by LVO, thereby guiding endovascular treatment.

Objective To compare the efficacy and safety between thermal ablation combined with synchronous transcatheter arterial chemoembolization(TACE)and TACE in patients with liver metastasis of neuroendocrine tumors of different pathologic grades.Methods A retrospective analysis was performed on patients with liver metastases of neuroendocrine tumors admitted to Department of Interventional Radiology,Zhongshan Hospital,Fudan University from Nov 1,2006 to Jul 31,2022.The patients were divided into synchronous ablation group and TACE group according to treatment mode and subgroups according to pathological grade.The lesions were evaluated by postoperative imaging examination.The patients were followed up until Jul 31,2023,and surgery-related complications were recorded.The endpoint of prognosis were progression-free survival(PFS)and overall survival(OS).Results A total of 86 patients with neuroendocrine tumor were collected,including 34 patients in simultaneous ablation group and 52 patients in TACE group.According to WHO classification,21 patients at G1 stage,45 patients at G2 stage and 20 patients at G3 stage were included.No serious postoperative complications occurred in all patients.The median OS was 47.0(95%CI:31.2-62.8)months in the TACE group and 56.0(95%CI:8.3-73.4)months in the synchronous ablation group,with no statistical difference between the two groups(P=0.50).The median PFS was 18.0(95%CI:6.0-30.0)months in the TACE group and 29.0(95%CI:10.0-48.0)months in the synchronous ablation group,with no statistical difference between the two groups(P=0.22).Of the 45 patients at G2 stage,27 received TACE with a median OS of 47.0 months,and 18 received synchronous ablation with a median OS of 59.0 months,and there was no statistical difference between the two groups(P=0.45).The median PFS was 12.0 months in the TACE group and 32.0 months in the synchronous ablation group,and the difference between the two groups was statistically significant(P=0.03).Conclusion Comparing with TACE,simultaneous ablation can delay disease progression in patients with liver metastasis of neuroendocrine tumors to a certain extent and has good safety,especially for patients with liver metastases of neuroendocrine tumors with intermediate or low grade.

Objective To investigate the value of predicting the pathological results of labial gland biopsy in Sj?gren's syndrome(SS)based on the labial gland MRI radiomics machine learning models.Methods The labial gland MRI data of 178 suspected SS patients were analyzed retrospectively,and the labial gland biopsy pathology results were positive in 97 cases and negative in 81 cases.The samples were divided into training set(143 cases)and test set(35 cases)using a randomized stratified sampling according to the ratio of 4:1.The region of interest(ROI)was manually outlined at the maximal level of the lower labial gland in T2WI water phase and radiomics features(104)were extracted.Feature screening was performed using the least absolute shrinkage and selection operator(LASSO),and the selected features set was used to construct Extra Trees,LightGBM,and Gradient Boosting classifier models.The predictive efficacy of the models was evaluated using the receiver operating characteristic(ROC)curve,and the DeLong test was used to compare the differences in the area under the curve(AUC)between the models.Decision curve analysis(DCA)was used to evaluate the clinical application value of the models in guiding biopsy.Results After LASSO screening,five optimal radiomics features were obtained.The AUC of Extra Trees,LightGBM,and Gradient Boosting models on the training and test sets were as follows 1.000,0.807,0.960 and 0.655,0.779,0.639,respectively.The DeLong test showed no statistically significant difference in AUC among the three models in the test set.DCA showed that the LightGBM model of guided biopsy had a higher clinical net benefit over a wider range of risk thresholds than other models.Conclusion Based on the radiomics features of the labial gland T2WI water phase,the LightGBM model has a high accuracy in predicting the pathological results of labial gland biopsy in SS,and guiding biopsy can obtain high clinical benefits,which has potential clinical application value.

Objective To investigate the value of non-contrast CT(NCCT)-based radiomics for identifying acute unilateral middle cerebral artery occlusion(MCAO)with negative hyperdense artery sign(HAS).Methods All 80 patients with acute unilateral MCAO confirmed by angiography(MR angiography[MRA]or CT angiography[CTA]or DSA)and presenting with negative NCCT presentation for HAS were enrolled from January 2015 to June 2023 in the Emergency Department of Stroke Center of Affiliated Hospital of Yangzhou university.On the NCCT images,the occluded segment of the middle cerebral artery on the affected side of each case and the corresponding segment of the vessel on the normal side were used as the regions of interest,and a total of 108 radiomic features were extracted.The least absolute shrinkage and selection operator(LASSO)was used to screen the key features,construct and calculate the radiomics score,and four imaging histology models,support vector machine(SVM),light gradient boosting machine(LightGBM),GradientBoosting and adaptive boosting(AdaBoost),were built respectively to predict MCAO.Predictive performance was evaluated by the area under the receiver operating characteristic curves,and comparisons between the modeled receiver operating characteristic curves were made using the Delong test.Finally,the value of the application of radiological modeling was assessed by clinical decision curve analysis(DCA).Results The NCCT images based on 160 vessels were finally screened for 6 key features,including skewness,energy,gray level size zone matrix(GLSZM)-gray uneven,GLSZM-low gray area emphasis,GLSZM-size area non-uniform standardization,GLSZM-area entropy.The area under the curve(AUC)of the SVM-test was 0.688(95％CI 0.497-0.878)with an accuracy of 0.688;the AUC of the LightGBM-test was 0.787(95％CI 0.620-0.955)with an accuracy of 0.781;the AUC of the GradientBoosting-test was 0.654(95％CI 0.457-0.852)with an accuracy of 0.688;the AUC of the AdaBoost-test was 0.707(95％CI 0.515-0.899)with an accuracy of 0.750.The Delong test showed a statistically significant difference between LightGBM-test and GradientBoosting-test(P=0.040),and no statistically significant difference in performance between the remaining models(all P＞0.05).DCA showed that the LightGBM-test performed better.Conclusion NCCT-based radiomics has good diagnostic efficacy for identifying acute unilateral MCAO with negative HAS,and this conclusion needs to be further verified by multi-center and large sample studies.

Objective:To investigate the changes of dynamic functional brain network connectivity in patients with Parkinson disease(PD) using Hidden Markov model(HMM), and to analyze the correlation between dynamic functional parameters and clinical parameters.Methods:Forty-eight PD patients(PD group) and thirty-three healthy controls(HC group) were included from 2019 to 2023. The cognitive function was assessed using the Montreal cognitive assessment (MoCA), and motor status was assessed using the unified Parkinson's disease rating scale Ⅲ(UPDRS-Ⅲ) in PD group.HMM technique was used to analyze the dynamic functional brain network connectivity, and the dynamic higher-order index fractional occupancy(FO), switching rate(SR), and mean dwell time(MDT) were obtained. Two independent samples t-test was used to calculate the differences between groups of functional connectivity matrices in different states, and Mann-Whitney U test was used to calculate the differences between groups of dynamic higher-order indicators in different states. Spearman correlation analysis was used to calculate the correlation between dynamic higher-order parameters and clinical parameters in the PD group. Results:The HMM was used to construct 6 spatial states for all subjects.MDT was significantly higher in PD group(24.93(19.73)) in state 1 sparse junctions than that in HC group(17.63(14.80)) ( Z=-2.030, P=0.042), but significantly lower MDT was showed in PD group(6.00(3.00)) in state 5 tight junctions than that in HC group(9.75(7.70)) ( Z=-2.210, P=0.027).FO in state 3 was negatively correlated with MoCA score in PD group( r=-0.331, P=0.022).FO in state 5 was positively correlated with UPDRS-Ⅲ score in PD patients( r=0.412, P=0.004), and MDT in state 5 was positively correlated with UPDRS-Ⅲ score( r=0.448, P=0.001). Conclusion:HMM can capture the transient changes of dynamic brain network, which can provide some value for the study of dynamic brain network in patients with Parkinson disease.