BACKGROUND:Peripheral nerve axon rupture seriously affects patients' physical function and mental health.Microsurgery,nerve autograft,nerve allograft,fibrin glue and catheter technology are the main treatments for peripheral nerve injury,each of which has its own advantages and disadvantages,but the overall treatment effect is not satisfactory.Despite the clinical success of Schwann cells in promoting axonal regeneration,there are still many challenges in the treatment with Schwann cells,such as slow expansion of Schwann cells,immune rejection,and low survival rate of transplanted cells.OBJECTIVE:To summarize the role and mechanism of Schwann cells in promoting the regeneration of peripheral nerve axons,and the difficulties and challenges of Schwann cells in the process of nerve regeneration treatment.METHODS:PubMed,Medline,WanFang,VIP,and CNKI were searched by computer using the search terms of"Schwann cells,synaptic Schwann cell,macrophage,peripheral nerve axon rupture,Wallerian degeneration,Peripheral nerve axon regeneration,Central nervous system repair"in English and Chinese.Literature related to Schwann cell proliferation and differentiation,promotion of peripheral nerve regeneration,and clinical applications was retrieved from database inception to October 2024,and a total of 95 articles were finally included for review.RESULTS AND CONCLUSION:Schwann cells interact with macrophages,T cells and other cells,to initiate the regeneration process through signaling pathways,including Krox20/C-Jun,NRG-1/ErbB,Notch,MAPK,and PI3K/Akt/mTOR,synthesize and release nerve growth factors,and thus promote regeneration of the peripheral nervous system.Schwann cells have been experimentally demonstrated to have great potential in peripheral nerve repair and are expected to become the key target of therapeutic intervention.However,there are still problems such as difficulties in cell harvest and culture,as well as the occurrence of other diseases during the treatment process.

BACKGROUND:Peripheral nerve axon rupture seriously affects patients' physical function and mental health.Microsurgery,nerve autograft,nerve allograft,fibrin glue and catheter technology are the main treatments for peripheral nerve injury,each of which has its own advantages and disadvantages,but the overall treatment effect is not satisfactory.Despite the clinical success of Schwann cells in promoting axonal regeneration,there are still many challenges in the treatment with Schwann cells,such as slow expansion of Schwann cells,immune rejection,and low survival rate of transplanted cells.OBJECTIVE:To summarize the role and mechanism of Schwann cells in promoting the regeneration of peripheral nerve axons,and the difficulties and challenges of Schwann cells in the process of nerve regeneration treatment.METHODS:PubMed,Medline,WanFang,VIP,and CNKI were searched by computer using the search terms of"Schwann cells,synaptic Schwann cell,macrophage,peripheral nerve axon rupture,Wallerian degeneration,Peripheral nerve axon regeneration,Central nervous system repair"in English and Chinese.Literature related to Schwann cell proliferation and differentiation,promotion of peripheral nerve regeneration,and clinical applications was retrieved from database inception to October 2024,and a total of 95 articles were finally included for review.RESULTS AND CONCLUSION:Schwann cells interact with macrophages,T cells and other cells,to initiate the regeneration process through signaling pathways,including Krox20/C-Jun,NRG-1/ErbB,Notch,MAPK,and PI3K/Akt/mTOR,synthesize and release nerve growth factors,and thus promote regeneration of the peripheral nervous system.Schwann cells have been experimentally demonstrated to have great potential in peripheral nerve repair and are expected to become the key target of therapeutic intervention.However,there are still problems such as difficulties in cell harvest and culture,as well as the occurrence of other diseases during the treatment process.

Objective:To explore differences in the efficacy and safety of ruxolitinib in patients with myelofibrosis by age and to identify prognostic factors by analyzing clinical features and characteristics of chromosomes and gene mutations.Methods:This study retrospectively analyzed 188 patients with myelofibrosis who received ruxolitinib in the Department of Hematology, Qilu Hospital, Shandong University from January 1, 2017, to July 1, 2024. According to age at diagnosis, the patients were divided into the middle-aged group (≤55 years), young elderly group (56-65 years), and elderly group (>65 years). Clinical features, the characteristics of chromosomes and gene mutations, and the efficacy and safety of ruxolitinib treatment were compared across the three age groups. Independent factors influencing overall survival were identified through Cox proportional risk regression analysis.Results:Before treatment, the elderly group had more underlying comorbidities, a heavier symptom burden, higher leukocyte count, higher proportion and frequency of JAK2 mutations, and lower proportion of CALR mutations. The incidence of nondriver gene mutations was significantly higher in the young elderly group. After ruxolitinib treatment, the degree of reduction in spleen size did not differ significantly among the three groups. The length of the palpable spleen below the left costal margin reduced by more than 50% from baseline in 50.9% (27/53) of the patients in the middle-aged group, 43.5% (27/62) in the young elderly group, and 45.5% (20/44) in the elderly group ( P=0.720). No significant difference was observed among the three groups in the degree of reduction in Myeloproliferative Neoplasm Symptom Assessment Form (10-item version) score ( P=0.153), with a reduction in total symptom score by more than 50% achieved by 54.0% (27/50), 60.3% (41/68), and 66.7% (34/51) of the patients from the three groups, respectively ( P=0.429). The most common hematological adverse events were anemia and thrombocytopenia, while the most common nonhematological adverse events were electrolyte disturbance, elevated transaminase activity, and pulmonary infection. Multivariate analysis indicated that in ruxolitinib-treated patients with myelofibrosis, poor overall survival was independently predicted by increased age, reduced hemoglobin, percentage of bone marrow blasts ≥ 1%, absence of JAK2 mutations, chromosomal abnormalities, ≥2 high-molecular-risk mutations, and TP53 mutations. Conclusions:Patients with myelofibrosis stratified by age exhibited heterogeneous clinical features and gene mutation profiles but similar efficacy of ruxolitinib treatment and occurrence of adverse events.

Objective:To investigate the prognostic factors for esophageal cancer after radical resection and the application value of machine learning prediction model.Methods:The retrospective cohort study was conducted. The clinicopatholigical data of 406 esophageal cancer patients who were admitted to Qilu Hospital of Shandong University from January 2018 to March 2022 were collected. There were 357 males and 49 females, aged (64±8)years. All patients underwent radical resection of esophageal cancer. The 406 patients were randomly divided into a training set of 285 cases and a validation set of 121 cases at a 7∶3 ratio based on a random number table. The training set was used to construct prediction model, and the validation set was used to validate prediction model. Patients were divided into high-risk group and low-risk group based on risk scores. Observation indicators: (1) follow-up of patients and analysis of influencing factors for prognosis; (2) construction and validation of machine learning prediction models. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the rank sum test. The Kaplan-Meier method was used to calculate survival rate and plot survival curve, and the Log-rank test was used for survival analysis. The Cox proportional hazard regression model was used for univariate and multivariate analyses. Independent influencing factors were included, and data processing, machine learning model construction, and visualization were performed using R packages including random survival forest (RSF), gradient boosting machine (GBM), least absolute shrinkage and selection operator Cox regression (LASSO-Cox), Cox proportional hazards model boosting (CoxBoost), survival support vector machine (survivalsvm), extreme gradient boosting (XGBoost), supervised principal component analysis (SuperPC), and Cox partial least squares regression (plsRcox). Receiver operating characteristic (ROC) curves were drawn, and sensitivity, specificity, and area under the curve (AUC) were calculated. The Delong test was used to assess the differences in AUC among different models in the training set, and the time-dependent ROC was used to compare the predictive performance of different models. Calibration curves were used to evaluate model accuracy, and decision curve analysis (DCA) was used to evaluate overall net benefit. Results:(1) Follow-up of patients and analysis of influencing factors for prognosis. All 406 patients were followed up postoperatively for 28(range, 6-36)months, with 1- and 3-year overall survival rate of 86.5% and 40.9%, respectively. The 285 patients in the training set were followed up postoperatively for 30(range, 6-36)months, with 1- and 3-year overall survival rate of 85.1% and 35.5%, respectively. The 121 patients in the validation set were followed up postoperatively for 25(range, 6-36)months, with 1- and 3-year overall survival rate of 87.0% and 43.2%, respectively. There was no significant difference in postoperative overall survival rate between the training set and the validation set ( χ2=3.20, P>0.05). Results of multivariate analysis showed that left thoracic surgical approach, preopera-tive neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia were independent risk factors affecting postoperative survival of 285 patients in the training set ( hazard ratio=1.466, 1.037, 1.482, 1.549, 5.268, 7.727, 22.202, 2.539, 2.686, 1.425, 95% confidence interval as 1.026-2.096, 1.003-1.073, 1.008-2.179, 1.105-2.170, 1.201-23.099, 1.833-32.576, 4.734-104.128, 1.577-4.087, 1.631-4.422, 1.018-1.994, P<0.05). (2) Construction and validation of machine learning prediction models. Independent risk factors affecting postoperative survival were included to construct RSF, GBM, LASSO-Cox, CoxBoost, survivalsvm, XGBoost, SuperPC, and plsRcox machine learning prediction models. Results of Delong test showed that there were significant differences in the AUC of RSF and GBM from the other six models ( P<0.05). Results of time-dependent ROC curve showed that all 8 machine learning predic-tion models had good discriminative ability in the training cohort, among which the RSF machine learning prediction model had the best predictive performance. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postoperative 1-, 2-, and 3-year overall survival in the training cohort, with high consistency with actual results. Results of decision curve analysis showed that within a threshold range of 0-0.80, the RSF machine learning prediction model provided a better overall net benefit. Further analysis showed that in the validation set, the AUC of RSF machine learning prediction model for postoperative 1-, 2-, and 3-year survival prediction were 0.786 (95% confidence interval as 0.609-0.962), 0.774 (95% confidence interval as 0.676-0.873), and 0.750 (95% confidence interval as 0.652-0.848), respectively. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postopera-tive 1-, 2-, and 3-year overall survival in the validation set, with high consistency with actual results. In the training set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score <11.7 as the low-risk group. The median survival times of the two groups were 18.0 months and >36.0 months, respectively, showing a significant difference between them ( χ2=73.30, P<0.05). In the validation set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score<11.7 as the low-risk group. The median survival times of the two groups were 17.0 months and>36.0 months for the high-risk and low-risk groups, respectively, showing a significant difference between them ( χ2=35.20, P<0.05). Conclusions:Left thoracic surgical approach, preoperative neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia are independent risk factors affecting survival of esophageal cancer patients after radical resection. The RSF machine learning prediction model constructed based on these factors can effectively distinguish the survival prognosis of high-risk and low-risk patients.

Objective To observe the value of endovascular stenting(EVS)for treating transverse sinus stenosis(TSS)-related unilateral pulsatile tinnitus(PT).Methods Totally 42 patients with TSS-related unilateral PT who underwent EVS were retrospectively enrolled.The technical and clinical success rates of EVS for treating TSS-related unilateral PT were evaluated,and the complications and recurrence after treatment were observed.Results Among 42 cases,stent implantation was successfully performed in 40 cases,with the technical success rate of EVS was 95.24%(40/42).After treatment,the tinnitus symptoms in the above 40 cases improved significantly,the tinnitus handicap inventory(THI)score immediately decreased to mild PT,the trans-stenotic pressure gradient(TPG)decreased from 8.00(6.00,11.75)mmHg before treatment to 1.00(1.00,1.00)mmHg,and the clinical success rate of EVS was 100%(40/40).During the follow-up period,no serious complication was found.PT recurred 3 months after treatment in 1 case but spontaneously released 3 months later without any management.Conclusion EVS was safe and effective for treating TSS-related unilateral PT.

Objective:To explore differences in the efficacy and safety of ruxolitinib in patients with myelofibrosis by age and to identify prognostic factors by analyzing clinical features and characteristics of chromosomes and gene mutations.Methods:This study retrospectively analyzed 188 patients with myelofibrosis who received ruxolitinib in the Department of Hematology, Qilu Hospital, Shandong University from January 1, 2017, to July 1, 2024. According to age at diagnosis, the patients were divided into the middle-aged group (≤55 years), young elderly group (56-65 years), and elderly group (>65 years). Clinical features, the characteristics of chromosomes and gene mutations, and the efficacy and safety of ruxolitinib treatment were compared across the three age groups. Independent factors influencing overall survival were identified through Cox proportional risk regression analysis.Results:Before treatment, the elderly group had more underlying comorbidities, a heavier symptom burden, higher leukocyte count, higher proportion and frequency of JAK2 mutations, and lower proportion of CALR mutations. The incidence of nondriver gene mutations was significantly higher in the young elderly group. After ruxolitinib treatment, the degree of reduction in spleen size did not differ significantly among the three groups. The length of the palpable spleen below the left costal margin reduced by more than 50% from baseline in 50.9% (27/53) of the patients in the middle-aged group, 43.5% (27/62) in the young elderly group, and 45.5% (20/44) in the elderly group ( P=0.720). No significant difference was observed among the three groups in the degree of reduction in Myeloproliferative Neoplasm Symptom Assessment Form (10-item version) score ( P=0.153), with a reduction in total symptom score by more than 50% achieved by 54.0% (27/50), 60.3% (41/68), and 66.7% (34/51) of the patients from the three groups, respectively ( P=0.429). The most common hematological adverse events were anemia and thrombocytopenia, while the most common nonhematological adverse events were electrolyte disturbance, elevated transaminase activity, and pulmonary infection. Multivariate analysis indicated that in ruxolitinib-treated patients with myelofibrosis, poor overall survival was independently predicted by increased age, reduced hemoglobin, percentage of bone marrow blasts ≥ 1%, absence of JAK2 mutations, chromosomal abnormalities, ≥2 high-molecular-risk mutations, and TP53 mutations. Conclusions:Patients with myelofibrosis stratified by age exhibited heterogeneous clinical features and gene mutation profiles but similar efficacy of ruxolitinib treatment and occurrence of adverse events.

Objective To observe the value of endovascular stenting(EVS)for treating transverse sinus stenosis(TSS)-related unilateral pulsatile tinnitus(PT).Methods Totally 42 patients with TSS-related unilateral PT who underwent EVS were retrospectively enrolled.The technical and clinical success rates of EVS for treating TSS-related unilateral PT were evaluated,and the complications and recurrence after treatment were observed.Results Among 42 cases,stent implantation was successfully performed in 40 cases,with the technical success rate of EVS was 95.24%(40/42).After treatment,the tinnitus symptoms in the above 40 cases improved significantly,the tinnitus handicap inventory(THI)score immediately decreased to mild PT,the trans-stenotic pressure gradient(TPG)decreased from 8.00(6.00,11.75)mmHg before treatment to 1.00(1.00,1.00)mmHg,and the clinical success rate of EVS was 100%(40/40).During the follow-up period,no serious complication was found.PT recurred 3 months after treatment in 1 case but spontaneously released 3 months later without any management.Conclusion EVS was safe and effective for treating TSS-related unilateral PT.

Objective:To explore the correlation between intestinal flora disturbance and the diagnosis,treatment of rheumatoid arthritis(RA),and to provide bioinformatics basis for further research on precise targeted intervention of RA.Methods:Genes related to intestinal flora disorders and RA genes were downloaded from disease database.Correlation between the two diseases was analyzed via bioinformatics approach.PPI network was conducted by STRING,Cytoscape and their plug-ins,and key genes were screened.Key genes were mapped into Coremine Medicinal to identify medicinal chemicals and medicinal herbs.Results:A total of 525 genes shared by intestinal flora disorders and RA were obtained through integrated screening of the disease database,and key genes with the highest degree of protein interaction were finally selected,namely IL-6,IL-1β,TNF-α,IL-10,STAT3,STAT1 and RELA.These related tar-geted genes were mainly involved in biological processes such as negative feedback regulation and antigen stimulation,and mediate molecular functions such as lipopolysaccharide receptor binding and NF-κB receptor binding,which are mainly concentrated in the plasma membrane region.KEGG analysis showed that these related genes were mainly involved in classical signaling pathways such as IL-17 pathway and Toll-like receptor pathway.Through drug prediction,it was found that Astragalus,Scutellaria,Schisandra and Cop-tis in traditional Chinese medicine might be potential drug sources for RA treatment.Conclusion:Bioinformatics method can predict key genes and signaling pathways of intestinal flora intervention in pathogenesis and progression of RA,and predict the Chinese herbs that may target the regulation of flora for treatment of risk factors,which providing a theoretical basis for further exploration of targeted treatment of RA.

Objective:To explore the correlation between intestinal flora disturbance and the diagnosis,treatment of rheumatoid arthritis(RA),and to provide bioinformatics basis for further research on precise targeted intervention of RA.Methods:Genes related to intestinal flora disorders and RA genes were downloaded from disease database.Correlation between the two diseases was analyzed via bioinformatics approach.PPI network was conducted by STRING,Cytoscape and their plug-ins,and key genes were screened.Key genes were mapped into Coremine Medicinal to identify medicinal chemicals and medicinal herbs.Results:A total of 525 genes shared by intestinal flora disorders and RA were obtained through integrated screening of the disease database,and key genes with the highest degree of protein interaction were finally selected,namely IL-6,IL-1β,TNF-α,IL-10,STAT3,STAT1 and RELA.These related tar-geted genes were mainly involved in biological processes such as negative feedback regulation and antigen stimulation,and mediate molecular functions such as lipopolysaccharide receptor binding and NF-κB receptor binding,which are mainly concentrated in the plasma membrane region.KEGG analysis showed that these related genes were mainly involved in classical signaling pathways such as IL-17 pathway and Toll-like receptor pathway.Through drug prediction,it was found that Astragalus,Scutellaria,Schisandra and Cop-tis in traditional Chinese medicine might be potential drug sources for RA treatment.Conclusion:Bioinformatics method can predict key genes and signaling pathways of intestinal flora intervention in pathogenesis and progression of RA,and predict the Chinese herbs that may target the regulation of flora for treatment of risk factors,which providing a theoretical basis for further exploration of targeted treatment of RA.

OBJECTIVE To evaluate the effects of phthalic acid esters(PAEs)on the expression of heme oxygenase-1(HO-1)in HepG2 cells,and to construct an HO-1-based three-dimensional quantita-tive structure-activity relationship(3D-QSAR)model.METHODS ① HepG2 cells were treated with seven types of PAEs:di-(2-ethylhexyl)phthalate(DEHP),di-n-octyl phthalate(DnOP),dimethyl phthalate(DMP),diethyl phthalate(DEP),dihexyl phthalate(DHXP),dimethylglycol phthalate(DMEP),and dibutyl phthalate(DBP),at final concentrations of 0(DMSO,solvent control),0.062 5,0.125,0.25,0.5 and 1 mmol·L-1(n=6)for 48 h at 37℃.The expression level of HO-1 was measured by Western blotting.② A 3D-QSAR model was constructed using comparative molecular similarity indices analysis(CoMSIA)based on the measured HO-1 levels.The applicability domain(AD)of the model was evaluated using the leverage method.Model fitting quality and predictive ability were evaluated via the KNIME Enalos+node to verify model stability.Additionally,molecular docking was performed to validate the binding interactions between PAEs and HO-1.RESULTS ① Compared with the solvent control group,48 h of exposure to 0.062 5 mmol·L-1 PAEs(DMP,DMEP,DEHP,DnOP and DEP)significantly increased HO-1 protein expressions,while 1 mmol·L-1 PAEs(DMP,DBP,DnOP,DEP and DHXP)significantly suppressed HO-1 expressions.② The 3D-QSAR model showed a non-cross-validated coefficient(R2)of 0.996 and a cross-validated coefficient(Q2)of 0.548.All the seven PAEs in the 3D-QSAR model were within the applicability domain(AD)and passed external validation.Molecular docking results indi-cated that DBP,DnOP,DEHP and DHXP exhibited stronger binding affinities to HO-1.CONCLUSION Forty-eight hours of exposure of HepG2 cells to 1 mmol·L-1 PAEs can significantly suppress HO-1 expres-sions.The 3D-QSAR model established in this study provides a potential tool for predicting the HO-1-related toxic effects of novel PAEs.