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.

Abstract： ObjectiveThe study aims to explore the effects and regulatory roles of glucose transporter 1 （GLUT1） on the proliferation， migration， adhesion， and angiogenesis of human umbilical vein endothelial cells （HUVECs） under ischemia-hypoxic conditions. MethodsIn vitro experiments were conducted to subject HUVECs to an ischemia-hypoxic-mimicking environment （1% O₂， 5% CO₂， 94% N₂）. The biological characteristics of HUVECs under normoxic and ischemia-hypoxic conditions were compared by assessing cell viability， proliferation capacity， and examining the expression changes of GLUT1， HIF-1α， and VEGFA proteins under ischemia-hypoxia using Western blot technology. Further， GLUT1 was overexpressed using plasmid transfection and the proliferation， migration， adhesion， and angiogenic capabilities of HUVECs were evaluated through scratch assays， cell adhesion assays， and tube formation assays. Mitochondrial morphological changes were observed by transmission electron microscopy，and oxygen consumption rate （OCR） was detected by Seahorse metabolic analyzer to evaluate mitochondrial function. ResultsCompared with normoxic conditions， the ischemia-hypoxic environment significantly inhibited the proliferation， cell viability， migration， and adhesion capabilities of HUVECs and impaired their angiogenic potential. The expression levels of GLUT1， HIF-1α and VEGFA proteins were also markedly reduced. However， when GLUT1 expression was upregulated， the migration， adhesion， and angiogenic capabilities of HUVECs were significantly improved， and the protein expression levels of HIF-1α， VEGFA and VEGFR were increased. Transmission electron microscopy revealed that ischemic-hypoxia leads to mitochondrial swelling and matrix damage， while GLUT1 overexpression significantly alleviates mitochondrial morphology abnormalities. OCR results suggest that GLUT1 overexpression may enhance oxidative phosphorylation of endothelial cells in ischemic-hypoxic environments to improve energy metabolism. These results suggest that GLUT1 may influence the function and angiogenic potential of HUVECs by regulating glucose metabolism and energy supply. ConclusionsThis study reveals the significant regulatory role of GLUT1 in the function of HUVECs under ischemia-hypoxic conditions， potentially through modulating cellular energy metabolism and signal transduction pathways， thereby affecting cell proliferation， migration， adhesion， and angiogenesis. These findings provide a new perspective on the role of GLUT1 in cardiovascular diseases and may offer potential targets for the development of new therapeutic strategies.

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

The aim of this investigation was to determine the optimal storage medium for testicular hypothermic transportation and identify the ideal concentration for the application of the protective agent 5-aminolevulinic acid (5-ALA). Furthermore, this study aimed to explore the underlying mechanism of the protective effects of 5-ALA. First, we collected and stored mouse testicular fragments in different media, including Hank's balanced salt solution (HBSS; n = 5), Dulbecco's Modified Eagle Medium/Nutrient Mixture F-12 (DMEM/F12; n = 5), and alpha-minimum essential medium (αMEM; n = 5). Storage of testicular tissue in HBSS preserved the integrity of testicular morphology better than that in the DMEM/F12 group ( P < 0.05) and the αMEM group ( P < 0.01). Testicular fragments were subsequently placed in HBSS with various concentrations of 5-ALA (0 [control], 1 mmol l -1 , 2 mmol l -1 , and 5 mmol l -1 ) to determine the most effective concentration of 5-ALA. The 2 mmol l -1 5-ALA group ( n = 3) presented the highest positive rate of spermatogonial stem cells compared with those in the control, 1 mmol l -1 , and 5 mmol l -1 5-ALA groups. Finally, the tissue fragments were preserved in HBSS with control ( n = 3) and 2 mmol l -1 5-ALA ( n = 3) under low-temperature conditions. A comparative analysis was performed against fresh testes ( n = 3) to elucidate the underlying mechanism of 5-ALA. Gene set enrichment analysis (GSEA) for WikiPathways revealed that the p38 mitogen-activated protein kinase (MAPK) signaling pathway was downregulated in the 2 mmol l -1 5-ALA group compared with that in the control group (normalized enrichment score [NES] = -1.57, false discovery rate [FDR] = 0.229, and P = 0.019). In conclusion, these data suggest that using 2 mmol l -1 5-ALA in HBSS effectively protected the viability of spermatogonial stem cells upon hypothermic transportation.
Male ; Animals ; Testis/cytology* ; Aminolevulinic Acid/pharmacology* ; Mice ; Organ Preservation/methods* ; Organ Preservation Solutions/pharmacology* ; Cryopreservation/methods*