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.

This study was conducted retrospectively on a cohort of 68 patients with steroid 5 α-reductase 2 (SRD5A2) deficiency and 46,XY disorders of sex development (DSD). Whole-exon sequencing revealed 28 variants of SRD5A2 , and further analysis identified seven novel mutants. The preponderance of variants was observed in exon 1 and exon 4, specifically within the nicotinamide adenine dinucleotide phosphate (NADPH)-binding region. Among the entire cohort, 53 patients underwent initial surgery at Sichuan Provincial People's Hospital (Chengdu, China). The external genitalia scores (EGS) of these participants varied from 2.0 to 11.0, with a mean of 6.8 (standard deviation [s.d.]: 2.5). Thirty patients consented to hormone testing. Their average testosterone-to-dihydrotestosterone (T/DHT) ratio was 49.3 (s.d.: 23.4). Genetic testing identified four patients with EGS scores between 6 and 9 as having this syndrome; and their T/DHT ratios were below the diagnostic threshold. Furthermore, assessments conducted using the crystal structure of human SRD5A2 have provided insights into the potential pathogenic mechanisms of these novel variants. These mechanisms include interference with NADPH binding (c.356G>C, c.365A>G, c.492C>G, and c.662T>G) and destabilization of the protein structure (c.727C>T). The c.446-1G>T and c.380delG variants were verified to result in large alterations in the transcripts. Seven novel variations were identified, and the variant database for the SRD5A2 gene was expanded. These findings contribute to the progress of diagnostic and therapeutic approaches for individuals with SRD5A2 deficiency.
Humans ; 3-Oxo-5-alpha-Steroid 4-Dehydrogenase/genetics* ; Disorder of Sex Development, 46,XY/blood* ; Male ; Membrane Proteins/genetics* ; Child, Preschool ; Child ; Retrospective Studies ; Adolescent ; Female ; Mutation ; Testosterone/blood* ; Infant ; Dihydrotestosterone/blood*

The Animal Molecular Biology course is a crucial and foundational course for both Animal Medicine and Animal Science majors.Apart from teaching fundamental principles of molecular biology,the course provides updated applications of these principles in the field of animal science research.Im-portantly,it plays a fundamental role in cultivating students'research capabilities.With the rise of over-whelming information and their optimal utilization,the demand for integrating digital education with tradi-tional teaching methods is increasing.Based on the five years of teaching practice,this paper summarizes four highlights of the course:the construction of teaching resource,the restructuring of teaching syllabus,the adjustment of classroom teaching hours,and the improvement of assessment methodology.It focuses on Electronic-Learning"E(E-Learning)",offline classroom intensive teaching"C(Classroom)",and post-class extension to construct a blended teaching model that integrates Electronic-Learning and Class-room teaching,namely the"E+C"blended teaching model.Offline classroom teaching emphasizes the combination of theory and knowledge systems,while online Electronic-Learning mainly focuses on popular science and interesting aspects to stimulate students' interests and enthusiasm in learning.Over five years of practice,the"E+C"blended model has been proven to exert a good teaching effect.Students have reported significant gains from the course,with tightly connected and strongly complementary class-room teaching and E-Learning,which greatly aids in mastering professional knowledge.It also cultivates intrinsic motivation for learning and enhances the sense of accomplishment in acquiring knowledge,sig-nificantly improving teaching effectiveness.

Aim To evaluate the role of the glucose transporter protein 1(GLUT1)-dependent glycolytic in the attenuation of oxygen-glucose deprivation-reoxygen-ation(OGD/R)injury in HK-2 cells by dexmedetomi-dine(Dex).Methods C57/BL6 mice were random-ly divided into three groups(n=6),namely,sham operation group(Sham group),renal ischemia reper-fusion group(I/R group)and Dex group(I/R+Dex group).Serum creatinine(Cr)and urea nitrogen(BUN)were measured,while the levels of key glyco-lytic enzymes HK2,PFKFB3 and GLUT1 were meas-ured.HK-2 cells were cultured and randomised into seven groups(n=6),which was treated with OGD/R,overexpression or interference with GLUT1,Dex and glycolysis inhibitor 2-DG.CCK-8 and LDH activi-ty were used to detect cellular damage.Glycolysis lev-els were detected by lactate and ECAR.The inflamma-tory level was reflected by qRT-PCR for IL-6 and TNF-α.qRT-PCR and Western blot were performed to de-tect the levels of GLUT1,HK2,and PFKFB3.Results Dex significantly ameliorated kidney injury and HK-2 cell injury(P＜0.05).Dex inhibited the OGD/R-induced rise in lactate and extracellular acidification rate(ECAR),as evidenced by suppression of the ex-pression of GLUT1,HK2 and PFKFB3(P＜0.05).In vitro experiments showed that GLUT1 knockdown sig-nificantly improved OGD/R-induced cellular damage.Lactate,ECAR,glycolysis-related mRNAs and pro-teins were inhibited by GLUT1 knockdown(P＜0.05).Significantly,there were no significant differ-ences in above indexes after Dex treatment based on GLUT1 knockdown.Overexpression of GLUT1 abroga-ted the protective effects of Dex,while reversing the inhibitory effects of Dex on the expression of GLUT1,HK2,and PFKFB3(P＜0.05).Conclusions Dexmedetomidine attenuates OGD/R induced injury in HK-2 cells by inhibiting GLUT1-dependent glycolysis.

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 mechanism of action of jolkinolide B in the treatment of gastric cancer by network pharmacology combined with molecular docking technique.Methods The SwissTargetPrediction database was used to obtain the targets of the active compounds.Search Genecards,OMIM,Drugbank,TTD,and PharmGKB databases to obtain targets for gastric cancer.The intersection between the targets of jolkinolide B and those of gastric cancer was identified pinpoint potential targets for jolkinolide B in treating gastric cancer.The String database was utilized construct a protein-protein interaction(PPI)network.Bioconductor bioinformatics packages with R software was employed conduct Gene Ontology(GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis on the shared targets.This process revealed significant regulatory pathways crucial for jolkinolide B's efficacy in treating gastric cancer.Cytoscape 3.7.1 software was utilized create the core network of"Potential Targets of Triptolide B in Gastric Cancer Treatment",and SYBYL-X2.1.1 software was employed conduct molecular docking validation of the selected main active ingredients and critical targets.Results Jolkinolide B may target multiple proteins,including MAPK1,glycogen synthase kinae-3β(GSK-3β),and JUN,impacting the proliferation,invasion,and metastasis of gastric cancer,ultimately inhibiting its growth.Conclusion We predicted the possible molecular mechanism of jolkinolide B in the treatment of gastric cancer to provide guide information for the subsequent experimental research and clinical application.