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.

This study aims to investigate the molecular mechanism by which naringin alleviates cerebral ischemia/reperfusion(CI/R) injury through DRP1/LRRK2/MCU signaling axis. A total of 60 SD rats were randomly divided into the sham group, the model group, the sodium Danshensu group, and low-, medium-, and high-dose(50, 100, and 200 mg·kg~(-1)) naringin groups, with 10 rats in each group. Except for the sham group, a transient middle cerebral artery occlusion/reperfusion(tMCAO/R) model was established in SD rats using the suture method. Longa 5-point scale was used to assess neurological deficits. 2,3,5-Triphenyl tetrazolium chloride(TTC) staining was used to detect the volume percentage of cerebral infarction in rats. Hematoxylin-eosin(HE) staining and Nissl staining were employed to assess neuronal structural alterations and the number of Nissl bodies in cortex, respectively. Western blot was used to determine the protein expression levels of B-cell lymphoma-2 gene(Bcl-2), Bcl-2-associated X protein(Bax), cleaved cysteine-aspartate protease-3(cleaved caspase-3), mitochondrial calcium uniporter(MCU), microtubule-associated protein 1 light chain 3(LC3), and P62. Mitochondrial structure and autophagy in cortical neurons were observed by transmission electron microscopy. Immunofluorescence assay was used to quantify the fluorescence intensities of MCU and mitochondrial calcium ion, as well as the co-localization of dynamin-related protein 1(DRP1) with leucine-rich repeat kinase 2(LRRK2) and translocase of outer mitochondrial membrane 20(TOMM20) with LC3 in cortical mitochondria. The results showed that compared with the model group, naringin significantly decreased the volume percentage of cerebral infarction and neurological deficit score in tMCAO/R rats, alleviated the structural damage and Nissl body loss of cortical neurons in tMCAO/R rats, inhibited autophagosomes in cortical neurons, and increased the average diameter of cortical mitochondria. The Western blot results showed that compared to the sham group, the model group exhibited increased levels of cleaved caspase-3, Bax, MCU, and the LC3Ⅱ/LC3Ⅰ ratio in the cortex and reduced protein levels of Bcl-2 and P62. However, naringin down-regulated the protein expression of cleaved caspase-3, Bax, MCU and the ratio of LC3Ⅱ/LC3Ⅰ ratio and up-regulated the expression of Bcl-2 and P62 proteins in cortical area. In addition, immunofluorescence analysis showed that compared with the model group, naringin and positive drug treatments significantly decreased the fluorescence intensities of MCU and mitochondrial calcium ion. Meanwhile, the co-localization of DRP1 with LRRK2 and TOMM20 with LC3 in cortical mitochondria was also decreased significantly after the intervention. These findings suggest that naringin can alleviate cortical neuronal damage in tMCAO/R rats by inhibiting DRP1/LRRK2/MCU-mediated mitochondrial fragmentation and the resultant excessive mitophagy.
Animals ; Rats, Sprague-Dawley ; Reperfusion Injury/genetics* ; Flavanones/administration & dosage* ; Rats ; Dynamins/genetics* ; Male ; Brain Ischemia/genetics* ; Protein Serine-Threonine Kinases/genetics* ; Signal Transduction/drug effects* ; Humans ; Drugs, Chinese Herbal/administration & dosage*

This study primarily aimed to investigate the prevalence of human papillomavirus (HPV) and other common pathogens of sexually transmitted infections (STIs) in spermatozoa of infertile men and their effects on semen parameters. These pathogens included Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae, Pseudomonas aeruginosa , and Staphylococcus aureus . A total of 1951 men of infertile couples were recruited between 23 March 2023, and 17 May 2023, at the Department of Reproductive Medicine of The First People's Hospital of Yunnan Province (Kunming, China). Multiplex polymerase chain reaction and capillary electrophoresis were used for HPV genotyping. Polymerase chain reaction and electrophoresis were also used to detect the presence of other STIs. The overall prevalence of HPV infection was 12.4%. The top five prevalent HPV subtypes were types 56, 52, 43, 16, and 53 among those tested positive for HPV. Other common infections with high prevalence rates were Ureaplasma urealyticum (28.3%), Ureaplasma parvum (20.4%), and Enterococcus faecalis (9.5%). The prevalence rates of HPV coinfection with Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae , and Staphylococcus aureus were 24.8%, 25.4%, 10.6%, 6.4%, 2.4%, 7.9%, 5.9%, 0.9%, and 1.3%, respectively. The semen volume and total sperm count were greatly decreased by HPV infection alone. Coinfection with HPV and Ureaplasma urealyticum significantly reduced sperm motility and viability. Our study shows that coinfection with STIs is highly prevalent in the semen of infertile men and that coinfection with pathogens can seriously affect semen parameters, emphasizing the necessity of semen screening for STIs.
Humans ; Male ; Infertility, Male/epidemiology* ; Coinfection/microbiology* ; Papillomavirus Infections/virology* ; Adult ; Sexually Transmitted Diseases/complications* ; China/epidemiology* ; Staphylococcus aureus/isolation & purification* ; Chlamydia trachomatis/isolation & purification* ; Prevalence ; Mycoplasma genitalium/isolation & purification* ; Ureaplasma urealyticum/isolation & purification* ; Neisseria gonorrhoeae/isolation & purification* ; Enterococcus faecalis/isolation & purification* ; Streptococcus agalactiae/isolation & purification* ; Herpesvirus 2, Human/genetics* ; Pseudomonas aeruginosa/isolation & purification* ; Semen/virology* ; Sperm Motility ; Spermatozoa/microbiology* ; Human Papillomavirus Viruses

Primary ciliary dyskinesia (PCD) is a genetically heterogeneous disorder characterized by impaired motility of cilia and flagella. Mutations in cilia- and flagella-associated protein 300 ( CFAP300 ) are associated with human PCD and male infertility; however, the underlying pathogenic mechanisms remain poorly understood. In a consanguineous Chinese family, we identified a homozygous CFAP300 loss-of-function variant (c.304delC) in a proband presenting with classical PCD symptoms and severe sperm abnormalities, including dynein arm deficiency and acrosomal malformation, as confirmed by transmission electron microscopy (TEM). Histological analysis revealed multiple morphological abnormalities of the sperm flagella in CFAP300 -mutant individual, whereas immunofluorescence demonstrated markedly reduced CFAP300 expression in the spermatozoa of the proband. Furthermore, tandem mass tag (TMT)-based quantitative proteomics showed that the CFAP300 mutation reduced key spermatogenesis proteins (e.g., sperm flagellar 2 [SPEF2], solute carrier family 25 member 31 [SLC25A31], and A-kinase anchoring protein 3 [AKAP3]) and mitochondrial ATP synthesis factors (e.g., SLC25A31, cation channel sperm-associated 3 [CATSPER3]). It also triggered abnormal increases in autophagy-related proteins and signaling mediator phosphorylation. These molecular alterations are likely to contribute to progressive deterioration of sperm ultrastructure and function. Notably, successful pregnancy was achieved via intracytoplasmic sperm injection (ICSI) using the proband's sperm. Overall, this study expands the known CFAP300 mutational spectrum and offers novel mechanistic insights into its role in spermatogenesis.
Humans ; Male ; Infertility, Male/pathology* ; Acrosome/pathology* ; Sperm Tail/pathology* ; Pedigree ; Spermatozoa ; Adult ; Loss of Function Mutation ; Ciliary Motility Disorders/genetics* ; Spermatogenesis/genetics* ; Female

Objective:To investigate the effect of genetic polymorphism of MTHFR C677T (rs1801133) on methotrexate (MTX) related toxicity in pediatric mature B-cell lymphoma patients. Methods:Fifty-eight intermediate and high risk patients under 18 years of age with mature B-cell lymphoma who received 5 g/m2 MTX (24 h intravenous infusion) in Sun Yat-sen University Cancer Center from August 2014 to December 2021 were included,and their toxicity of high-dose MTX (HD-MTX) were monitored and analyzed. Results:Among the 58 pediatric patients,the number of CC,CT,and TT genotypes for MTHFR C677T was 33,19 and 6,respectively. A total of 101 courses of HD-MTX therapy were counted,of which plasma MTX level>0.2 μmol/L at 48 h post-MTX infusion were observed in 35 courses,≤0.2 μmol/L in 66 courses. Inter-group comparison showed that plasma MTX level>0.2 μmol/L at 48 h post-MTX infusion increased the risk of developing oral mucositis (P<0.05). Compared with wild-type (CC genotype),patients in the mutant group (CT+TT genotype) were more likely to develop myelosuppression,manifested as anemia,leucopenia,neutropenia and thrombocytopenia. However,plasma MTX level at 48 h was not associated with MTHFR C677T gene polymorphism. Conclusion:The risk of developing oral mucositis in children with mature B-cell lymphoma is associated with plasma MTX concentration. Polymorphism of MTHFR C677T gene is not related to plasma MTX concentration in children with mature B-cell lymphoma,but is related to grade Ⅲ to Ⅳ hematological toxicity.

In recent years, artificial intelligence (AI) technology has advanced rapidly and has been widely applied in various fields such as medicine and pharmacy, accelerating the drug development process. Focusing on the application of AI in the discovery and optimization of lead compounds, this review provides a detailed introduction to AI-assisted virtual screening and molecular generation methods for discovering lead compounds, while particularly highlighting the cases of AI-drived drugs into clinical trials. Additionally, we briefly outline the application of AI basic algorithm models in quantitative structure-activity relationship (QSAR) and drug repurposing, offering insights for AI-based drug discovery.