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.

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. The introduction of the foundation model has revolutionized the application of AI in medical treatment and facilitated its integration into clinical practice. This review emphasizes the clinical application of AI in PCa by discussing recent advancements from both pathological and imaging perspectives. Furthermore, it explores the current challenges faced by AI in clinical applications while also considering future developments, aiming to provide a valuable point of reference for the integration of AI and clinical applications.
Humans ; Prostatic Neoplasms/diagnosis* ; Male ; Artificial Intelligence ; Deep Learning ; Prognosis

BACKGROUND: Stroke is the leading cause of death and long-term disability worldwide, including China. This study aimed to provide timely updates on stroke burden and stroke-related risk factors to help improve population-based prevention and control strategies. METHODS: Based on the Global Burden of Disease study 2021, incidence rate, prevalence rate, mortality rate, and disability-adjusted life-year (DALY) rate were used to estimate stroke burden trend from 1990 to 2021. RESULTS: In 2021, China had 4.1 million incident stroke cases, 26.3 million prevalent stroke cases, 2.6 million stroke related deaths, and 53.2 million stroke related DALYs, compared to 11.9 million incident stroke cases, 93.8 million prevalent stroke cases, 7.3 million stroke related deaths, and 160.5 million stroke-related DALYs worldwide. In 2021, the top six risk factors contributing to stroke burden were high blood pressure, air pollution, tobacco consumption, dietary risk factors, high low-density lipoprotein cholesterol, and high fasting plasma glucose, both in China and worldwide. From 1990 to 2021, China had significant increases of incidence rate, prevalence rate, mortality rate, and DALY rate for stroke, with estimates of 100.6 (95% uncertainty intervals [UI]: 87.2, 114.1)%, 102.9 (95% UI: 95.5, 110.9)%, 40.0 (95% UI: 14.9, 72.3)% and 15.7 (95% UI: -4.6, 41.2)%, respectively, while global incidence rate, prevalence rate, mortality rate and DALY rate for total stroke showed relatively moderate increases or even decreases, with estimates of 15.0 (95% UI: 12.1,18.0)%, 25.8 (95% UI: 23.7, 28.0)%, -2.6 (95% UI: -10.6, 5.5)%, and -10.7 (95% UI: -17.7, -3.6)%, respectively. CONCLUSION Stroke remains a huge disease burden worldwide and in China, and compared to the worldwide China has a significantly higher burden of stroke.
Humans ; Stroke/etiology* ; China/epidemiology* ; Risk Factors ; Global Burden of Disease ; Disability-Adjusted Life Years ; Prevalence ; Incidence ; Female ; Quality-Adjusted Life Years ; Male

OBJECTIVE: To investigate the characteristics of gut microbiota changes in patients with acute myeloid leukemia (AML) undergoing induction chemotherapy and to explore the relationship between infectious complications and gut microbiota. METHODS: Fecal samples were collected from 37 newly diagnosed AML patients at four time points: before induction chemotherapy, during chemotherapy, during the neutropenic phase, and during the recovery phase. Metagenomic sequencing was used to analyze the dynamic changes in gut microbiota. Correlation analyses were conducted to assess the relationship between changes in gut microbiota and the occurrence of infectious complications. RESULTS: During chemotherapy, the gut microbiota α-diversity (Shannon index) of AML patients exhibited significant fluctuations. Specifically, the diversity decreased significantly during induction chemotherapy, further declined during the neutropenic phase (P < 0.05, compared to baseline), and gradually recovered during the recovery phase, though not fully returning to baseline levels.The abundances of beneficial bacteria, such as Firmicutes and Bacteroidetes, gradually decreased during chemotherapy, whereas the abundances of opportunistic pathogens, including Enterococcus, Klebsiella, and Escherichia coli, progressively increased.Analysis of the dynamic changes in gut microbiota of seven patients with bloodstream infections revealed that the bloodstream infection pathogens could be detected in the gut microbiota of the corresponding patients, with their abundance gradually increasing during the course of infection. This finding suggests that bloodstream infections may be associated with opportunistic pathogens originating from the gut microbiota.Compared to non-infected patients, the baseline samples of infected patients showed a significantly lower relative abundance of Bacteroidetes (P < 0.05). Regression analysis indicated that Bacteroidetes abundance is an independent predictive factor for infectious complications (P < 0.05, OR =13.143). CONCLUSION During induction chemotherapy in AML patients, gut microbiota α-diversity fluctuates significantly, and the abundance of opportunistic pathogens increase, which may be associated with bloodstream infections. Patients with lower baseline Bacteroidetes abundance are more prone to infections, and its abundance can serve as an independent predictor of infectious complications.
Humans ; Gastrointestinal Microbiome ; Leukemia, Myeloid, Acute/microbiology* ; Induction Chemotherapy ; Feces/microbiology* ; Male ; Female ; Middle Aged

OBJECTIVE: To investigate the efficacy and safety of stanozolol combined with avatrombopag in the treatment of chemotherapy-induced thrombocytopenia (CIT) in patients with relapsed/refractory tumors. METHODS: Twenty-five patients with relapsed/refractory CIT admitted to the Hematology Department of Xiyuan Hospital, China Academy of Chinese Medical Sciences between March 2023 to December 2023 were enrolled. These patients received a combined therapy of stanozolol and avatrombopag. The clinical efficacy, onset time, changes in platelet levels and blood cell counts before and after treatment, and adverse reactions of patients were evaluated. RESULTS: The combination therapy demonstrated remarkable efficacy with a total effective rate of 100%. Among the 25 patients, 19 achieved complete remission and 6 achieved partial remission. The median onset time was 42.5（range: 35-48）days. The average platelet count of the 25 patients increased from (25.73±17.75)×10⁹/L before treatment to (146.4±49.59)×10⁹/L after 3 months of treatment, with a statistically significant difference ( P < 0.05). 18 patients who previously required platelet transfusion were all weaned off platelet transfusion after 3 months of treatment, with a median time to be free from platelet transfusion was 26 (range: 18-51) days. During the treatment, both neutrophils and hemoglobin exhibited various degrees of elevation. Two patients experienced a slight increase in alanine aminotransferase(ALT) levels, which normalized after treatment with oral hepatoprotective drug. One patient had a PLT increase exceeding 350×10⁹/L, and the treatment with avatrombopag was suspended, and aspirin and other drugs were given to prevent thrombosis. No thrombose events or CIT-related bleeding events were observed in all patients. CONCLUSION The combination therapy of stanozolol and avatrombopag is significantly effective for treating relapsed/refractory CIT patients, with a high response rate and good safety, making it a suitable clinical treatment option.
Humans ; Thrombocytopenia/chemically induced* ; Stanozolol/therapeutic use* ; Male ; Female ; Neoplasms/drug therapy* ; Middle Aged ; Thiophenes/therapeutic use* ; Adult ; Platelet Count ; Treatment Outcome ; Antineoplastic Agents/adverse effects* ; Recurrence ; Thiazoles

OBJECTIVE: To identify the CDYL-interacting proteins in murine testis and investigate the mechanism of CDYL involved in spermatogenesis. METHODS: CDYL-interacting partners in testis were identified using co-immunoprecipitation coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Expression pattern of CDYL-interacting protein MYH9 was analyzed through immunohistochemistry (IHC), confocal immunofluorescence (IF) and Western blot (WB) in mouse testicular cells. The effect of the Cdyl conditional knockout (CdylcKO) in spermatogenic cell on Myh9 expression was quantified via RT-qPCR, WB and IF imaging in both spermatids and spermatozoa from cauda epididymides. RESULTS: Direct interaction between MYH9 and CDYL was confirmed in murine testis. During spermiogenesis, MYH9 exhibited co-localization with CDYL at the manchette structure, and binding to F-ACTIN, the component of manchette. In cauda epididymal spermatozoa, MYH9 signal concentrated on acrosomal region and continuously distributed along the tail length. Conditional deletion of Cdyl in spermatogenic cell resulted in the transcriptional downregulation of Myh9. In spermatids, CdylcKO led to reduced but retained MYH9 localization to the disorganized manchette structure. In spermatozoa from CdylcKO mice, abnormalities of MYH9 localization were observed, including attenuation of acrosomal signal and/or partial vanishment/enhancement of tail signal. CONCLUSION In murine spermatids, MYH9 protein is localized to the manchette structure, with its expression and subcellular distribution is affected by CDYL protein. CDYL-MYH9 interaction is essential for the spermiogenesis.
Animals ; Male ; Mice ; Testis/metabolism* ; Myosin Heavy Chains/metabolism* ; Spermatogenesis ; Mice, Knockout