Chemiluminescence,as a self-luminous phenomenon that does not require light,heat,acoustic,electric and magnetic excitation,has been widely used in the fields of analytical chemistry,cold light source and bio-imaging because of its advantages including high sensitivity,wide linear range,simple equipment and fast detection speed compared with other analytical techniques.Carbon dots(CDs)are a class of nanomaterials with excellent photoluminescence properties and high biocompatibility.CDs are stable,easy to prepare and abundant in types,and researchers have introduced many types of CDs into different chemiluminescence systems.In this paper,the applications of CDs in common chemiluminescence systems and the possible mechanisms of action were discussed,and the research progresses on the application of CDs in different chemiluminescence detection fields in recent years were summarized.Finally,the development trend of CDs in chemiluminescence was analyzed.

Twelve pre-processing protocols for formalin-fixed paraffin-embedded(FFPE)tissue samples were developed by orthogonal experimental design,incorporating different dewaxing buffers(Triton X-100 and xylene),lysis buffers(TFE and RapiGest),and enzyme digestion methods(iST,SP3,and FASP)to explore the optimal experimental conditions.These protocols were assessed based on protein and peptide identification depth,identification stability,and quantitative levels of protein abundance.The results indicated that Triton X-100 and xylene minimally impacted proteomics identification,whereas the TFE lysis buffer and iST digestion method significantly enhanced the proteomics analysis of FFPE samples.Considering the potential toxicity of xylene,the TTI protocol based on Triton X-100,TFE,and iST was determined to be the optimal choice.This protocol exhibited the best repeatability and stability,and a higher number of proteins associated with significant biological functions were identified.In conclusion,the established TTI protocol offered an efficient and comprehensive approach for proteomic analysis of FFPE samples,significantly enhancing the repeatability and stability of protein identification.

Poly(lactic-co-glycolide)(PLGA)is a key excipient in long-acting sustained-release preparations,and its degradation properties directly affect the drug release behavior.In this study,PLGA microspheres were prepared by microfluidic techniques,and the morphology changes of the microspheres were observed by scanning electron microscopy(SEM).In alkaline environment,due to the accelerated hydrolysis of ester bonds,the surface of the microspheres was rapidly dissolved and eroded,and the degradation rate was significantly higher than that in acidic environment.High temperature accelerated the degradation of PLGA microspheres.Under neutral and alkaline conditions,the microspheres showed aggregation and adhesion.Under acidic conditions,the microspheres gradually decomposed into irregular fragments.The high ionic strength further promoted the surface corrosion of the microspheres,especially under extreme pH conditions.Simultaneously,PLGA microspheres encapsulating coumarin were prepared to simulate the microsphere formulation.The release rate of coumarin after degradation of the microspheres under different conditions was observed by measuring the absorbance with ultraviolet-visible spectrophotometry.The results were consistent with those of the blank microspheres.This study revealed that the degradation of PLGA microspheres was significantly pH-dependent,temperature sensitive and ion strength responsive.These findings not only helped to understand and optimize the long-term stability and controlled release performance of drug-carrying microspheres,but also provided a theoretical basis for further improvement of PLGA-based drug carrier design.

Introducing fingerprint level 3 features(especially sweat pores)in fingerprint recognition can significantly improve the value of fingerprints.However,conventional fingerprint visualization methods suffer from issues such as poor stability and reproducibility,insufficient resolution,and feature masking in detecting level 3 features.Electrospun membrane has unique advantages in latent fingerprint(LFP)detection due to its excellent adsorption performance and high specific surface area,and thus its application potential in LFP visualization urgently need to be explored.A novel pore visualization method based on core-shell structured PAN-Flu/PVP composite nanofibrous membrane was proposed in this work.Specifically,the PAN-Flu/PVP composite nanofibrous membrane was prepared via coaxial electrospinning technology,with polyacrylonitrile(PAN)loaded with fluorescein(Flu)as the core and polyvinylpyrrolidone(PVP)as the shell.The experimental results showed that the prepared PAN Flu/PVP composite nanofibrous membrane had a porous structure and excellent adsorption performance.Based on the water solubility of the outer shell PVP and the water induced fluorescence enhancement effect of the core Flu,high-resolution visualization of sweat pores could be achieved within 2 s.The optimization experiment showed that the best quality of sweat latent fingerprints was obtained when the Flu content was 4 mg/mL,the spinning time was 1 h,and the sweating time was 2 min.Through repeated fingerprinting and live fingerprint comparison experiment,the strong stability and high reproducibility of the as-produced membrane in displaying fingerprint sweat pores were finally verified.In summary,the development method could quickly,stably and accurately extract the spatial distribution and activity level of fingerprint sweat pores,which was of great significance for improving the utilization and value of fingerprints.

Due to the poor ionization efficiency and the weak mass spectrometry(MS)intensity of weakly polar substances,direct analysis using the traditional electrospray ionization mass spectrometry(ESI-MS)is a big challenge.In this study,a novel rapid on-site detection method of four prohibited sex hormones in cosmetics was proposed using online derivatization strategy coupled with a miniature mass spectrometer.The target substances in the samples were extracted by a custom-made polyaniline/multi-walled carbon nanotube solid-phase microextraction(SPME)probe.The stirring speed was 200 r/min,the extraction temperature was 40℃,and the extraction time was 2 min.A pulled dual-channel θ borosilicate glass capillary emitter was used as the nano-ESI ion source.The SPME probe was inserted into the channel containing methanol in theθborosilicate glass capillary.When the spray voltage was applied,the four sex hormones were desorbed and formed spray microdroplets,which then collided with the hydroxylamine microdroplets generated from the other channel.The microdroplets of reaction product entered into the miniature mass spectrometer for direct analysis.The limits of detection(LOD)and limits of quantification(LOQ)for the four sex hormones were 10-20 ng/mL and 20-50 ng/mL,respectively.The recoveries were from 84.6%to 107.8%with the relative standard deviations(RSD)from 4.1%to 11.6%.Compared to detection without derivatization,the MS signals of the four target substances were increased by 3 to 15 times.This method was simple,rapid,highly efficient and sensitive,and suitable for on-site rapid analysis of weakly polar sex hormones in cosmetics.

Objective:To investigate the differences in clinical characteristics and antibiotic resistance of neonatal sepsis（NS）caused by different Gram-staining pathogens.Methods:A retrospective study was conducted on confirmed NS cases admitted to the Neonatal Ward of the Pediatric Department at The First Affiliated Hospital of Dali University，from June 1，2014，to May 31，2024.Patients were divided into Gram-positive and Gram-negative groups based on blood or cerebrospinal fluid（CSF）culture results.Clinical characteristics，pathogen distribution，and antibiotic resistance were compared between the two groups.Results:A total of 98 cases were included，with 81 in the Gram-positive group and 17 in the Gram-negative group.Multivariate logistic regression analysis revealed that NS cases with a high neutrophil percentage（ OR=0.933，95% CI：0.899-0.969）or hemorrhagic symptoms/signs（ OR=0.059，95% CI：0.008-0.458）were less likely to have Gram-positive pathogens detected in blood or CSF cultures（ P<0.05）.Common Gram-positive pathogens included Staphylococcus epidermidis with 35 strains（33.65%）and Staphylococcus hominis with 22 strains（21.15%）.The predominant Gram-negative pathogen was Escherichia coli with 14 strains（13.46%）.Gram-positive pathogens exhibited high resistance to oxacillin（91.30%），erythromycin（90.91%），and penicillin G（90.00%），but low resistance to tigecycline（0），linezolid（0），and vancomycin（0）.Gram-negative pathogens showed high resistance to ampicillin（92.31%），cefazolin（90.00%），and ampicillin/sulbactam（75.00%），but low resistance to amikacin（6.25%），latamoxef（0），and ertapenem（0）.The incidence of concurrent purulent meningitis was lower in the Gram-positive group than in the Gram-negative group（9.88% vs.47.06%， χ2=11.628， P<0.05），and there was significant difference. Conclusion:NS cases with high neutrophil percentages or hemorrhagic symptoms/signs are less likely to be caused by Gram-positive pathogens.Staphylococcus epidermidis and Staphylococcus hominis are common Gram-positive pathogens，while Escherichia coli is the predominant Gram-negative pathogen in NS.Both Gram-positive and Gram-negative pathogens exhibit resistance to specific antibiotics.NS caused by Gram-positive pathogens is less likely to be complicated by purulent meningitis compared to those caused by Gram-negative pathogens.

Objectives:To evaluate the predictive value of Tabular Prior-data Fitted Network(TabPFN) for short-term outcome in patients with spontaneous intracerebral hemorrhage (sICH), and compared with the Extreme Gradient Boosting (XGboost) model and traditional logistic regression (LR) model. Methods:Patients with sICH admitted to the Department of Neurology, Hefei Second People's Hospital from January 2018 to March 2024 were included retrospectively. The demographic and baseline data were collected. At 3 months after onset, the modified Rankin Scale score was used to determine the outcome, 0-2 was defined as good outcome and >2 was defined as poor outcome. All enrolled patients were randomly divided into a training set and a testing set at a ratio of 7:3. Feature selection was performed using recursive feature elimination (RFE) method, and then the selected feature variables were included into TabPFN, XGboost, and LR models for training and testing. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the models. Shapley additive explanations (SHAP) method was used for model interpretation.Results:A total of 547 patients with sICH were enrolled, including 367 males (67.1%), with a median age of 65 (interquartile range, 54-76) years. Two hundred twenty-six patients (41.3%) had poor outcome. Age, baseline blood pressure (systolic blood pressure, diastolic blood pressure), baseline laboratory tests (white blood cell count, red blood cell count, platelet count, neutrophil count, hemoglobin, fasting blood glucose, creatinine, uric acid, urea nitrogen, alanine aminotransferase, aspartate aminotransferase), hematoma rupture into the ventricle, island sign, baseline hematoma volume, and baseline National Institutes of Health Stroke Scale (NIHSS) score were selected as characteristic variables using RFE method. ROC curve analysis showed that the ROC AUC for TabPFN, Xgboost, and LR models predicting poor short-term outcome in the testing set were 0.918 (95% confidence interval [ CI] 0.870-0.966], 0.883 (95% CI 0.826-0.940), and 0.905 (95% CI 0.854-0.957), respectively. SHAP analysis showed that the top four important variables in the TabPFN model were baseline NIHSS score, baseline hematoma volume, baseline aspartate aminotransferase, and age. Conclusions:The TabPFN model is superior to the LR model and the XGBoost model in predicting poor outcome in patients with sICH. In the TabPFN model, baseline NIHSS score, baseline hematoma volume, aspartate aminotransferase, and age are the most important predictors of poor outcome in patients with sICH.Objectives To evaluate the predictive value of Tabular Prior-data Fitted Network(TabPFN) for short-term outcome in patients with spontaneous intracerebral hemorrhage (sICH), and compared with the Extreme Gradient Boosting (XGboost) model and traditional logistic regression (LR) model. Methods Patients with sICH admitted to the Department of Neurology, Hefei Second People's Hospital from January 2018 to March 2024 were included retrospectively. The demographic and baseline data were collected. At 3 months after onset, the modified Rankin Scale score was used to determine the outcome, 0-2 was defined as good outcome and >2 was defined as poor outcome. All enrolled patients were randomly divided into a training set and a testing set at a ratio of 7:3. Feature selection was performed using recursive feature elimination (RFE) method, and then the selected feature variables were included into TabPFN, XGboost, and LR models for training and testing. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the models. Shapley additive explanations (SHAP) method was used for model interpretation. Results A total of 547 patients with sICH were enrolled, including 367 males (67.1%), with a median age of 65 (interquartile range, 54-76) years. Two hundred twenty-six patients (41.3%) had poor outcome. Age, baseline blood pressure (systolic blood pressure, diastolic blood pressure), baseline laboratory tests (white blood cell count, red blood cell count, platelet count, neutrophil count, hemoglobin, fasting blood glucose, creatinine, uric acid, urea nitrogen, alanine aminotransferase, aspartate aminotransferase), hematoma rupture into the ventricle, island sign, baseline hematoma volume, and baseline National Institutes of Health Stroke Scale (NIHSS) score were selected as characteristic variables using RFE method. ROC curve analysis showed that the ROC AUC for TabPFN, Xgboost, and LR models predicting poor short-term outcome in the testing set were 0.918 (95% confidence interval [ CI] 0.870-0.966], 0.883 (95% CI 0.826-0.940), and 0.905 (95% CI 0.854-0.957), respectively. SHAP analysis showed that the top four important variables in the TabPFN model were baseline NIHSS score, baseline hematoma volume, baseline aspartate aminotransferase, and age. Conclusions The TabPFN model is superior to the LR model and the XGBoost model in predicting poor outcome in patients with sICH. In the TabPFN model, baseline NIHSS score, baseline hematoma volume, aspartate aminotransferase, and age are the most important predictors of poor outcome in patients with sICH.

Objective To analyze the correlation between tongue image features and the risk levels of disease in patients with idiopathic membranous nephropathy(IMN).Methods Based on IMN clinical research electronic data acquisition system,a cross-sectional study method was used to analyze the clinical diagnosis and treatment data of 135 IMN patients from Guangdong Provincial Hospital of Chinese Medicine.The patients were grouped according to the risk levels of disease,and then the correlation between the risk levels of disease and tongue image features was analyzed.During the description of tongue image features,TB is for tongue body,TC is for tongue coating,L is for luminance,a is for red-green axis,G is for the value of green,B is for the value of blue,and AUT is for the value of autocorrelation.Results The comparison of tongue image feature indicators of patients with different risk levels of IMN showed that:(1)the higher the level of disease risk of IMN patients,the greater the values of TB-L,TB-G and TB-B(P<0.05 or P<0.01).The values of tongue image indicator TB-a and TC-a of the patients with different risk levels of IMN were shown in decreasing sequence:low-risk group>high-risk group>middle-risk group>extremely-high-risk group(P<0.05).(2)Linear regression analysis showed that TB-L,TB-G,and TB-B were significantly increased in the high-risk group compared with those in the middle-and low-risk groups(P<0.05 or P<0.01),whereas there were no significant differences between the middle-risk group and low-risk group(P>0.05).(3)The results of correlation analysis showed that there was a positive correlation among most of the tongue image feature indicators(including TB-L,TB-G,TB-B,TB-AUT,TC-L,TC-G,and TC-B,etc.)and the risk level of disease,while TB-a was negatively correlated with the risk level of disease,and the differences were all statistically significant(P<0.05 or P<0.01).(4)All patients were treated with Chinese medicine and/or Chinese patent medicine,and 46.7%of patients were given hormones and immunosuppressants,and there was no statistically significant difference in the the use of hormones and immunosuppressants among various groups(P=0.637).Conclusion There is a correlation between the tongue image features of IMN patients and the risk level of disease,and the results will provide an objective reference for the assessment of illness state and traditional Chinese medicine(TCM)syndrome differentiation of IMN patients.With reference to the changes in the tongue image features,the illness state can be precisely identified,which is more accurate than the inspection of four diagnostic methods of TCM.

Rare tumors pose significant challenges to clinical research, diagnosis, and therapy due to their low incidence, high molecular heterogeneity, and the lack of preclinical models.Conventional patient-derived cell lines and patient-derived tumor xenografts have significant limitations in recapitulating the characteristics of rare tumors. As an emerging in vitro biological model, organoids preserve the molecular characteristics of original tumors and possess high biological relevance, efficient amplification capabilities, and potential for personalized medicine applications. They have currently been applied in the research of various rare tumors. This review summarizes current research on organoid models of rare tumors derived from different tissue origins, and outlines current challenges and future development directions.

Objective: To enhance the solubility expression of carbonyl reductase ChKRED20 and investigate its enzymatic properties. Methods : The ChKRED20 gene was synthesized and transformed into Escherichia coli BL21(DE3) for heterologous expression. The solubility of the protein was evaluated by adding or removing His⁃tag ,changing its position , and adjusting the induction conditions. Further optimization was performed by varying the in⁃duction time , temperature and IPTG concentration. Subsequently , the enzymatic properties of the recombinant en⁃zyme were examined. Results: The ChKRED20 was cloned within the Escherichia coli system to achieve soluble protein expression . This was achieved by removing the His_tag and optimizing expression conditions . Compared to enzymes with the N_terminal and C _terminal His_tags , the enzyme activity of ChKRED20 without His_tag increased by 0. 77 and 1 . 28 times , respectively. The optimal temperature and pH for enzyme activity were 55 ℃ and 8. 0 , respectively. Furthermore , the enzyme demonstrated good adaptability in higher temperature and alkaline environ_ ments . Conclusion The removal of the His_tag and the optimization of expression conditions can significantly im_ prove the soluble expression of ChKRED20 in Escherichia coli .