Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective To explore the effect of Xinwei Granules on cell proliferation in rats with precancerous lesions of gastric cancer based on CyclinD1-CDK4/6-P16 pathway.Methods 180 Wistar rats were randomly divided into 6 groups,30 rats in each group:blank control group(blank),model group,Weifuchun control group,Xinwei Granule(low,medium and high dose)group.The PLGC rat model was made by MNNG method.Xinwei granule low,medium and high dose group were 0.72 g·kg-1,1.44 g·kg-1,2.88 g·kg-1;weifuchun group was given 0.52 g·kg-1,once a day by intragastric administration,and the blank group and the model group were given the same amount of normal saline by intragastric administration.The experimental period was 16 weeks.After the end of the experiment,the general condition of the rats was observed,and the mRNA and protein expressions of CyclinD1,CDK4/6 and P16 in gastric mucosa were detected by RT-PCR and Western blotting.Results The activity and diet of rats in each group of Xinwei Granules and Weifuchun group were improved to varying degrees compared with the model group.Compared with the blank control group,the mRNA and protein expression levels of CyclinD1,CDK4 and CDK6 in the model group were significantly increased.The mRNA and protein expression levels of P1 6 were significantly decreased(P＜0.05).The expression levels of CyclinD1,CDK4,CDK6 mRNA and protein in Xinwei granule(low,medium and high dose)group and Weifuchun group were lower than those in model group.The mRNA and protein expression levels of P16 were significantly increased(P＜0.05),and the effect of Xinwei granule medium dose group was the most significant.Conclusion Xinwei granules participate in the regulation of cell cycle through the CyclinD1-CDK4/6-P16 pathway,thereby inhibiting the proliferation of PLGC cells.

This work was aimed at predicting and verifying B-cell epitopes of SARS-CoV-2 E protein through bioinformatics methods,and clarifying the dominant B cell epitopes with mouse polyclonal antibody serum prepared through SARS-CoV-2 re-combinant E protein immunization and human positive serum vaccinated with inactivated SARS-CoV-2 vaccine.The structural and B-cell linear epitopes of SARS-CoV-2 E protein were predicted with SOPMA,Expasy,SWISS-MODEL,IEDB database,and Bepid-2.0 software.Candidate epitopes were expressed as GST-tagged recombinant protein fragments in an E.coli sys-tem,and their immunoreactivity with mouse and human poly-clonal positive serum against SARS-CoV-2 E protein was de-tected by western blotting and indirect ELISA,respectively.The epitope prediction results showed that E protein contained linear B cell epitopes Ser6-Val14 and Tyr57-Pro71,and the conformational epitopes of Glu8-Val12,Leu39-Tyr59,and Ser60-Leu65.The GST tagged recombinant E protein fragments of E1 and E3,containing Ser6-Val14 and Tyr57-Pro71 epitopes,respectively,as well as E2 without an epitope sequence as a control,were expressed in an E.coli expression system and successfully purified with an Ni-NTA column.Western blotting and indirect ELISA analysis indicated that all mouse and human SARS-CoV-2 positive sera positively reacted with only E1 and E3 proteins,but negatively reacted with E2 protein,thus indicating that the corresponding epitope prediction with Ser6-Val14 and Tyr57-Pro71 was correct.This study successfully predicted and preliminarily identified two linear B cell epitopes of SARS-CoV-2 E protein,thus providing a reference for the preparation of new coronavirus vaccines and the analysis of immune response characteristics.

AIM To study the secondary metabolites from the endophytic fungi Candida sp.of Berberis atrocarpa Schneid.METHODS The ethyl acetate fraction and petroleum ether fraction from the secondary metabolites of Candida sp.fermentation extract were separated and purified by silica gel,Sephadex LH-20 and preparative liquid chromatography,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Eighteen compounds were isolated and identified as 1-phenyl-1,2-ethanediol(1),4-hydroxyphenethyl alcohol(2),4-hydroxybenzoic acid(3),4-hydroxyphenylacetic acid(4),3-hydroxyphenylacetic acid(5),3-methylsulfinyl propionic acid(6),phenylacetic acid(7),(S)-N-nitroso-1-amino-p-hydroxy phenylethanol(8),2-phenylacetamide(9),p-hydroxybenzaldehyde(10),ethyl 2-(4-hydroxyphenyl)acetate(11),dibutyl phthalate(12),5,5'-dimethoxybiphenyl-2,2'-diol(13),3-indolealdehyde(14),N-acetyl-L-phenylalanine(15),9-hydroxy-10E,12Z-octadecadienoic acid(16),9-hydroxy-10E,12E-octadecadienoic acid(17),(6E)-5-methylene-6-tetradecenoic acid(18).CONCLUSION Compounds 1,3-8 and 10-18 are isolated from Candida sp for the first time.

Objective: To analyze the clinical characteristics and prognosis of primary and secondary pancreatic diffuse large B-cell lymphoma (DLBCL) . Methods: Clinical data of patients with pancreatic DLBCL admitted at Shanghai Rui Jin Hospital affiliated with Shanghai Jiao Tong University School of Medicine from April 2003 to June 2020 were analyzed. Gene mutation profiles were evaluated by targeted sequencing (55 lymphoma-related genes). Univariate and multivariate Cox regression models were used to evaluate the prognostic factors of overall survival (OS) and progression-free survival (PFS) . Results: Overall, 80 patients were included; 12 patients had primary pancreatic DLBCL (PPDLBCL), and 68 patients had secondary pancreatic DLBCL (SPDLBCL). Compared with those with PPDLBCL, patients with SPDLBCL had a higher number of affected extranodal sites (P<0.001) and had higher IPI scores (P=0.013). There was no significant difference in the OS (P=0.120) and PFS (P=0.067) between the two groups. Multivariate analysis indicated that IPI intermediate-high/high risk (P=0.025) and double expressor (DE) (P=0.017) were independent adverse prognostic factors of OS in patients with pancreatic DLBCL. IPI intermediate-high/high risk (P=0.021) was an independent adverse prognostic factor of PFS in patients with pancreatic DLBCL. Targeted sequencing of 29 patients showed that the mutation frequency of PIM1, SGK1, BTG2, FAS, MYC, and MYD88 in patients with pancreatic DLBCL were all >20%. PIM1 (P=0.006 for OS, P=0.032 for PFS) and MYD88 (P=0.001 for OS, P=0.017 for PFS) mutations were associated with poor OS and PFS in patients with SPDLBCL. Conclusion: There was no significant difference in the OS and PFS between patients with PPDLBCL and those with SPDLBCL. IPI intermediate-high/high risk and DE were adverse prognostic factors of pancreatic DLBCL. PIM1, SGK1, BTG2, FAS, MYC, and MYD88 were common mutations in pancreatic DLBCL. PIM1 and MYD88 mutations indicated worse prognosis.
Humans ; Myeloid Differentiation Factor 88 ; Disease-Free Survival ; Retrospective Studies ; China/epidemiology* ; Prognosis ; Lymphoma, Large B-Cell, Diffuse/drug therapy* ; Antineoplastic Combined Chemotherapy Protocols ; Pancreas/pathology* ; Immediate-Early Proteins/therapeutic use* ; Tumor Suppressor Proteins

Persistent neurogenesis exists in the subventricular zone (SVZ) of the ventricles and the subgranular zone (SGZ) of the dentate gyrus of the hippocampus in the adult mammalian brain. Adult endogenous neurogenesis not only plays an important role in the normal brain function, but also has important significance in the repair and treatment of brain injury or brain diseases. This article reviews the process of adult endogenous neurogenesis and its application in the repair of traumatic brain injury (TBI) or ischemic stroke, and discusses the strategies of activating adult endogenous neurogenesis to repair brain injury and its practical significance in promoting functional recovery after brain injury.
Adult ; Animals ; Humans ; Brain/physiopathology* ; Hippocampus/physiopathology* ; Mammals/physiology* ; Neurogenesis/physiology* ; Brain Hemorrhage, Traumatic/therapy* ; Ischemic Stroke/therapy* ; Recovery of Function ; Spinal Cord/physiopathology*