Objective:This study aimed to construct a prediction model for diagnosis of proliferative lupus nephritis based on a machine learning algorithm. Additionally, a user-friendly platform was developed to propose a non-invasive method to assist the pathologic classification of lupus nephritis.Methods:A retrospective analysis was conducted on clinical and pathological data of lupus nephritis patients confirmed by renal biopsy at Zhengzhou University People′s Hospital from January 2017 to August 2023. The study population was randomly divided into training and testing sets in a 7∶3 ratio. Utilizing six machine learning algorithms, classification models were developed. The predictive performance of each model was assessed using metrics such as accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). The optimal model, once identified, was deployed as a web-based calculator for convenient model application. SPSS 25.0 and R 4.2.2 were used to analyze the data.Results:The study included a total of 212 patients, with 138 cases with proliferative lupus nephritis and 74 cases with non-proliferative lupus nephritis. The AUC values for the six models, namely logistic regression, decision tree, random forest, support vector machine, extreme gradient boosting, and light gradient boosting machine, were 0.79, 0.62, 0.79, 0.88, 0.81, and 0.77, respectively; the accuracy rates were 82.54%, 65.08%, 74.60%, 85.71%, 69.84%, 71.43%, respectively. Among them, the support vector machine model demonstrated the optimal performance. This model had deployed as a web-based calculator. Based on feature importance scores, the top 10 influencing factors were identified, including anti URNP antibody, immunoglobulin G, serum globulin, estimated glomerular filtration rate, anti Smith antibody, BMI index, anti dsDNA antibody, uric acid, anti-Rib.p antibody, and gender.Conclusion:A prediction model based on machine learning algorithms was successfully established, and a web calculator was developed to offer a simple and non-invasive method for diagnosing proliferative lupus nephritis. This can assist clinicians in evaluating the risk-benefit ratio of kidney biopsy in patients with lupus nephritis.

Objective:To construct a nanoparticle vaccine displaying the prefusion F (preF) protein of respiratory syncytial virus (RSV) using the I53-50 protein nanoparticle platform, and to systematically evaluate its immunogenicity and protective efficacy.Methods:The RSV preF trimer antigen was genetically fused to I53-50A and assembled in vitro with I53-50B to form preF-I53-50 nanoparticles, theoretically displaying 20 preF antigens per particle. The structure and purity were characterized by size-exclusion chromatography, SDS-PAGE, and negative-stain electron microscopy. BALB/c mice were intramuscularly immunized with varying doses (1 μg or 5 μg) of preF antigen or an equimolar amount of preF-I53-50 nanoparticles. Humoral immunity, B-cell responses, and protective efficacy were assessed following intranasal viral challenge.Results:The preF-I53-50 nanoparticles self-assembled into spherical structures (50-60 nm in diameter) with uniformly arrayed antigens. The nanoparticle vaccine enhanced RSV-specific IgG1 and IgG2a antibody responses, promoting a Th1-biased immune profile. At equimolar preF doses, the neutralizing antibody titers induced by 1 μg and 5 μg nanoparticle formulations were 2.8-fold and 2.3-fold higher, respectively, than those elicited by preF alone ( P<0.05). Notably, even the low-dose nanoparticle group outperformed the high-dose preF group (1.6-fold increase). Viral challenge experiments demonstrated that preF-I53-50 effectively suppressed pulmonary viral replication, mitigated pathological damage, and induced stronger germinal center and memory B-cell responses, suggesting enhanced B-cell affinity maturation and long-term immune memory. Conclusion:The preF-I53-50 vaccine improves the immunogenicity and protective efficacy of RSV preF through multivalent antigen display.

Objective:To construct a nanoparticle vaccine displaying the prefusion F (preF) protein of respiratory syncytial virus (RSV) using the I53-50 protein nanoparticle platform, and to systematically evaluate its immunogenicity and protective efficacy.Methods:The RSV preF trimer antigen was genetically fused to I53-50A and assembled in vitro with I53-50B to form preF-I53-50 nanoparticles, theoretically displaying 20 preF antigens per particle. The structure and purity were characterized by size-exclusion chromatography, SDS-PAGE, and negative-stain electron microscopy. BALB/c mice were intramuscularly immunized with varying doses (1 μg or 5 μg) of preF antigen or an equimolar amount of preF-I53-50 nanoparticles. Humoral immunity, B-cell responses, and protective efficacy were assessed following intranasal viral challenge.Results:The preF-I53-50 nanoparticles self-assembled into spherical structures (50-60 nm in diameter) with uniformly arrayed antigens. The nanoparticle vaccine enhanced RSV-specific IgG1 and IgG2a antibody responses, promoting a Th1-biased immune profile. At equimolar preF doses, the neutralizing antibody titers induced by 1 μg and 5 μg nanoparticle formulations were 2.8-fold and 2.3-fold higher, respectively, than those elicited by preF alone ( P<0.05). Notably, even the low-dose nanoparticle group outperformed the high-dose preF group (1.6-fold increase). Viral challenge experiments demonstrated that preF-I53-50 effectively suppressed pulmonary viral replication, mitigated pathological damage, and induced stronger germinal center and memory B-cell responses, suggesting enhanced B-cell affinity maturation and long-term immune memory. Conclusion:The preF-I53-50 vaccine improves the immunogenicity and protective efficacy of RSV preF through multivalent antigen display.

To elucidate the mechanism by which steaming affects the quality of Curcuma kwangsiensis root tubers, methods such as LSCM, RVA, dual-wavelength spectrophotometry, LF-NMR, and LC-MS were employed to qualitatively and quantitatively detect changes in starch gelatinization characteristics, water distribution, and material composition of C. kwangsiensis root tubers under different steaming durations. Based on multivariate statistical analysis, the correlation between differences in gelatinization parameters, water distribution, and terpenoid material composition was investigated. The results indicate that steaming affects both starch gelatinization and water distribution in C. kwangsiensis. During the steaming process, transformations occur between amylose and amylopectin, as well as between semi-bound water and free water. After 60 min of steaming, starch gelatinization and water distribution reached an equilibrium state. The content of amylopectin, the amylose-to-amylopectin ratio, and parameters such as gelatinization temperature, viscosity, breakdown value, and setback value were significantly correlated(P≤0.05). Additionally, the amylose-to-amylopectin ratio was significantly correlated with total free water and total water content(P≤0.05). Steaming induced differences in the material composition of C. kwangsiensis root tubers. Clustering of primary metabolites in the OPLS-DA model was distinct, while secondary metabolites were classified into 9 clusters using the K-means clustering algorithm. Differential terpenoid metabolites such as(-)-α-curcumene were significantly correlated with zerumbone, retinal, and all-trans-retinoic acid(P<0.05). Curcumenol was significantly correlated with isoalantolactone and ursolic acid(P<0.05), while all-trans-retinoic acid was significantly correlated with both zerumbone and retinal(P<0.05). Alpha-tocotrienol exhibited a significant correlation with retinal and all-trans-retinoic acid(P<0.05). Amylose was extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and α-tocotrienol(P<0.05). Amylopectin was significantly correlated with zerumbone(P<0.05) and extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and 9-cis-retinoic acid(P<0.01). The results provide scientific evidence for elucidating the mechanism of quality formation of steamed C. kwangsiensis root tubers as a medicinal material.
Curcuma/chemistry* ; Starch/chemistry* ; Multivariate Analysis ; Water/chemistry* ; Terpenes/analysis* ; Plant Roots/chemistry* ; Plant Tubers/chemistry* ; Drugs, Chinese Herbal/chemistry*

Objective:This study aimed to construct a prediction model for diagnosis of proliferative lupus nephritis based on a machine learning algorithm. Additionally, a user-friendly platform was developed to propose a non-invasive method to assist the pathologic classification of lupus nephritis.Methods:A retrospective analysis was conducted on clinical and pathological data of lupus nephritis patients confirmed by renal biopsy at Zhengzhou University People′s Hospital from January 2017 to August 2023. The study population was randomly divided into training and testing sets in a 7∶3 ratio. Utilizing six machine learning algorithms, classification models were developed. The predictive performance of each model was assessed using metrics such as accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). The optimal model, once identified, was deployed as a web-based calculator for convenient model application. SPSS 25.0 and R 4.2.2 were used to analyze the data.Results:The study included a total of 212 patients, with 138 cases with proliferative lupus nephritis and 74 cases with non-proliferative lupus nephritis. The AUC values for the six models, namely logistic regression, decision tree, random forest, support vector machine, extreme gradient boosting, and light gradient boosting machine, were 0.79, 0.62, 0.79, 0.88, 0.81, and 0.77, respectively; the accuracy rates were 82.54%, 65.08%, 74.60%, 85.71%, 69.84%, 71.43%, respectively. Among them, the support vector machine model demonstrated the optimal performance. This model had deployed as a web-based calculator. Based on feature importance scores, the top 10 influencing factors were identified, including anti URNP antibody, immunoglobulin G, serum globulin, estimated glomerular filtration rate, anti Smith antibody, BMI index, anti dsDNA antibody, uric acid, anti-Rib.p antibody, and gender.Conclusion:A prediction model based on machine learning algorithms was successfully established, and a web calculator was developed to offer a simple and non-invasive method for diagnosing proliferative lupus nephritis. This can assist clinicians in evaluating the risk-benefit ratio of kidney biopsy in patients with lupus nephritis.

Objective:To establish a Plaque-reduction Neutralization Test (PRNT) for the detection of neutralizing antibody titers of Human Respiratory Syncytial Virus (HRSV) and optimize the conditions for preliminary application.Methods:The CHO expression system was used to produce palivizumab monoclonal antibody (palivizumab) and the influencing factors such as cell type, cell culture duration, fixation and permeabilization protocols, and blocking agents. The reproducibility of the method was verified and its correlation was verified with conventional PRNT. Finally, the optimized PRNT assay was further used to determine neutralizing antibody titers against HRSV subtypes A and B in BALB/c mouse serum (immunized by intramuscular injection of HRSV fusion proteins).Results:Palivizumab was expressed at approximately 50 mg/L. The optimal working conditions for PRNT were as follows: culturing HEp-2 cells for 2 days, fixing with 4% (V/V) paraformaldehyde at room temperature for 15 min followed by 0.2% (V/V) Triton X-100 permeabilization for 15 minutes as the optimal fixation-permeabilization and removing the blocking step. The overall coefficient of variation (CV) for the reproducibility validation of this method was <15%, showing a good linear relationship with the conventional PRNT. The Spearman correlation coefficient r s was 0.983. This method was used to detect neutralizing antibody titers in mouse sera against HRSV subtype A strain long and subtype B strain 9320, and the fusion proteins combined with AlOH and CpG adjuvant induced the highest neutralizing antibody titers in mice. Conclusion:The HRSV neutralizing antibody assay established in this study is rapid, reproducible, high-throughput, and can be used to detect neutralizing antibodies to HRSV subtypes A and B.

Fluorescent sensing technology plays a crucial role in rapid detection of substances and research on visual analysis. In this work,a new type of fluorescent molecule,named SA-AP-PPh3,was successfully synthesized through a two-step process,with a structure composed of triphenylphosphine and salicylaldehyde-aniline Schiff base. This molecule showed the nature of excited-state intramolecular proton transfer (ESIPT) and a large Stokes shift. SA-AP-PPh3 had the ability to selectively detect Cu2+,with a detection range from 0.5 to 15μmol/L and a detection limit as low as 261 nmol/L,which could be used to determine the concentration of Cu2+in actual water samples. In addition,the molecule contained a mitochondrial targeting functional group and had good biocompatibility,which could achieve the visualization of cellular mitochondria and effective detection of Cu2+in cells.

Objective:To explore the impact on analgesic efficacy and safety of esketamine as an adductor canal block adjuvant in knee arthroplasty.Methods:The study was a prospective, single center, randomized controlled trial. The subjects were patients who received knee arthroplasty in Zhangjiakou First hospital from October 2021 to October 2023. The patients were randomly divided into trial group and control group using a random number table method. The patients in the both groups received general anesthesia and postoperative patient-controlled intravenous analgesia (PCIA). The patients in the trial group were injected with 0.375% ropivacaine combined with esmketamine, while those in the control group were only injected with 0.375% ropivacaine. The postoperative vital signs, quadriceps femoris muscle strength, resting and dynamic visual analogue scale (VAS) pain score, use of PCIA, and incidence of postoperative adverse reactions in patients between the 2 groups were compared.Results:A total of 120 patients were included in this study, with 60 cases in each group. There were no significant differences in heart rate, mean arterial pressure, respiratory rate, and body temperature in patients between the trial group and the control group at 24 and 48 hours after operation (all P>0.05). There were no significant differences in quadriceps femoris muscle strength at 12, 24 and 48 hours after operation (all P>0.05). At rest, the VAS pain score at 12 hours after operation in the trial group was lower than that in the control group [(2.89±0.49) points vs. (3.36±0.23) points], the difference was statistically significant ( P<0.05). In the active state, the VAS scores at 12 and 24 hours after operation in the trial group were lower than those in the control group [(3.78±0.41) points vs. (4.11±0.45) points, (3.79±0.56) points vs. (4.19±0.69) points], the differences were statistically significant (all P<0.05). The number of times of PCIA compression 24 hours after operation in the experimental group was less than that in the control group [(5.35±1.03) times vs. (7.89±1.34) times], and the difference was statistically significant ( P<0.05), the sensory block time in the experimental group was longer than that in the control group [(488.26±57.75) min vs. (92.26±65.15) min], and the difference was statistically significant ( P<0.05). There were no significant differences in total incidence of adverse reactions including nausea, vomiting, urinary retention, dizziness, drowsiness, delirium and hallucination in patients between the 2 groups within 1 week after operation (all P>0.05). Conclusion:Esketamine as an adjuvant of ropivacaine for adductor block can alleviate the pain level of patients undergoing knee arthroplasty, and it has good safety.

Objective To investigate the correlation between serum levels of prostaglandin-endoperoxide synthase 2(PTGS2),chitinase-3-like protein 1(CHI3L1)and cognitive impairment caused by cerebrovascular disease.Methods From October 2020 to October 2022,96 inpatients with cerebrovascular diseases admitted to the Third People's Hospital of Chengdu were regarded as the study subjects.The basic clinical data of the patients were recorded,the serum levels of PTGS2 and CHI3L1 were detected by enzyme-linked immunosorbent assay,and these patients were grouped into normal group(n=60)and impaired group(n=36)based on the presence or absence of cognitive impairment.The correlation between serum PTGS2 and CHI3L1 levels and fasting blood glucose(FBG)and homocysteine(Hcy)was analyzed by Pearson method.Logistic regression model was used to determine whether serum PTGS2 and CHI3L1 were independent risk factors for predicting cognitive impairment.Receiver operating characteristic(ROC)curve was drawn,and the predictive value of CHI3L1 and serum PTGS2 expression level in cognitive impairment in patients with cerebrovascular disease was analyzed according to the area under the curve(AUC).Results Compared with the normal group,the levels of serum PTGS2(29.30±9.46 pg/ml vs 17.86±5.40 pg/ml)and CHI3L1(13.04±4.06 pg/ml vs 7.51±2.66 pg/ml)in the disorder group were increased,and the differences were statistically significant(t=7.553,8.065,all P＜0.05).Multivariate Logistic regression analysis showed that FBG(OR=3.612,95%CI:2.324～5.614),Hcy(OR=2.584,95%CI:1.351～4.944),PTGS2(OR=1.964,95%CI:1.194～3.231)and CHI3L1(OR= 1.556,95%CI:1.023～2.367)were independent risk factors of cognitive impairment(all P＜0.05).PTGS2 was positively correlated with FBG and Hcy(r=0.368,0.551,all P＜0.05),and CHI3L1 was positively correlated with FBG and Hcy(r=0.510,0.376,all P＜0.05).The ROC curve showed that the area under curve(AUC)of PTGS2 and CHI3L1 in predicting cognitive impairment was 0.819 and 0.829,respectively.The AUC of the combined prediction of cognitive impairment was 0.902,which was obviously higher than that of the independent prediction of the two(Z =2.089,2.293;P=0.037,0.021),with sensitivity and specificity of 77.78%and 98.33%,respectively.Conclusion PTGS2 and CHI3L1 were highly expressed in the serum of patients with cognitive impairment of cerebrovascular disease,indicating that both were related to cognitive impairment of patients with cerebrovascular disease.

Objective:To establish a Plaque-reduction Neutralization Test (PRNT) for the detection of neutralizing antibody titers of Human Respiratory Syncytial Virus (HRSV) and optimize the conditions for preliminary application.Methods:The CHO expression system was used to produce palivizumab monoclonal antibody (palivizumab) and the influencing factors such as cell type, cell culture duration, fixation and permeabilization protocols, and blocking agents. The reproducibility of the method was verified and its correlation was verified with conventional PRNT. Finally, the optimized PRNT assay was further used to determine neutralizing antibody titers against HRSV subtypes A and B in BALB/c mouse serum (immunized by intramuscular injection of HRSV fusion proteins).Results:Palivizumab was expressed at approximately 50 mg/L. The optimal working conditions for PRNT were as follows: culturing HEp-2 cells for 2 days, fixing with 4% (V/V) paraformaldehyde at room temperature for 15 min followed by 0.2% (V/V) Triton X-100 permeabilization for 15 minutes as the optimal fixation-permeabilization and removing the blocking step. The overall coefficient of variation (CV) for the reproducibility validation of this method was <15%, showing a good linear relationship with the conventional PRNT. The Spearman correlation coefficient r s was 0.983. This method was used to detect neutralizing antibody titers in mouse sera against HRSV subtype A strain long and subtype B strain 9320, and the fusion proteins combined with AlOH and CpG adjuvant induced the highest neutralizing antibody titers in mice. Conclusion:The HRSV neutralizing antibody assay established in this study is rapid, reproducible, high-throughput, and can be used to detect neutralizing antibodies to HRSV subtypes A and B.