The clinical significance of PD-1 expression in patients with bladder cancer without lymph node metastasis: a comparative study with drained lymph nodes and tumor tissues.

OBJECTIVE: In light of the increasing importance of immunotherapy in bladder cancer treatment, this study is aim to investigate the expression and clinical significance of programmed cell surface death-1 (PD-1) in bladder cancer patients without lymph node metastasis, and to compare and analyze the difference of PD-1 in draining lymph nodes and tumor tissues. METHODS: The expression of PD-1 on T cells and the proportion of positive PD-1 + T cells of IFN-γ and CD105a were detected by flow cytometry, and the correlation between PD-1 expression and clinical parameters was analyzed. RESULTS: The percentage of PD-1 positive cells in drainage lymph nodes was higher than that in tumor tissues (P < 0.001). PD-1 positive cells accounted for the highest proportion in CD3 + T cells. The proportion of IFN-γ-positive PD-1 + T cells in draining lymph nodes was significantly higher than that in tumor tissues (P < 0.001), while there was no significant difference in CD105a positive PD-1 + T cells between tumor tissues and draining lymph nodes. Pathological grade, tumor size and stage were positively correlated with PD-1 expression level in the lymph nodes. CONCLUSION: The high expression of PD-1 in patients with bladder cancer without lymph node metastasis, especially in draining lymph nodes, suggests that PD-1 may play a key role in the regulation of tumor immune microenvironment. The correlation between PD-1 and clinical parameters indicates its potential prognostic value. These findings provide important clinical implications for PD-1 targeted therapy, but further prospective studies are needed to determine the application value of PD-1 in therapeutic strategies.

Enhancing medical image segmentation with a multi-transformer U-Net.

Various segmentation networks based on Swin Transformer have shown promise in medical segmentation tasks. Nonetheless, challenges such as lower accuracy and slower training convergence have persisted. To tackle these issues, we introduce a novel approach that combines the Swin Transformer and Deformable Transformer to enhance overall model performance. We leverage the Swin Transformer's window attention mechanism to capture local feature information and employ the Deformable Transformer to adjust sampling positions dynamically, accelerating model convergence and aligning it more closely with object shapes and sizes. By amalgamating both Transformer modules and incorporating additional skip connections to minimize information loss, our proposed model excels at rapidly and accurately segmenting CT or X-ray lung images. Experimental results demonstrate the remarkable, showcasing the significant prowess of our model. It surpasses the performance of the standalone Swin Transformer's Swin Unet and converges more rapidly under identical conditions, yielding accuracy improvements of 0.7% (resulting in 88.18%) and 2.7% (resulting in 98.01%) on the COVID-19 CT scan lesion segmentation dataset and Chest X-ray Masks and Labels dataset, respectively. This advancement has the potential to aid medical practitioners in early diagnosis and treatment decision-making.

Multifunctional Polyoxometalates-Based Ionohydrogels toward Flexible Electronics.

Multifunctional flexible electronics present tremendous opportunities in the rapidly evolving digital age. One potential avenue to realize this goal is the integration of polyoxometalates (POMs) and ionic liquid-based gels (ILGs), but the challenge of macrophase separation due to poor compatibility, especially caused by repulsion between like-charged units, poses a significant hurdle. Herein, the possibilities of producing diverse and homogenous POMs-containing ionohydrogels by nanoconfining POMs and ionic liquids (ILs) within an elastomer-like polyzwitterionic hydrogel using a simple one-step random copolymerization method, are expanded vastly. The incorporation of polyzwitterions provides a nanoconfined microenvironment and effectively modulates excessive electrostatic interactions in POMs/ILs/H2O blending system, facilitating a phase transition from macrophase separation to a submillimeter scale worm-like microphase-separation system. Moreover, combining POMs-reinforced ionohydrogels with a developed integrated self-powered sensing system utilizing strain sensors and Zn-ion hybrid supercapacitors has enabled efficient energy storage and detection of external strain changes with high precision. This work not only provides guidelines for manipulating morphology within phase-separation gelation systems, but also paves the way for developing versatile POMs-based ionohydrogels for state-of-the-art smart flexible electronics.

Therapeutic strategies and predictive models for Xp11.2 translocation/TFE3 gene fusion renal cell carcinoma in adults based on data of two Chinese medical centers.

OBJECTIVE: This study aims to establish an effective predictive model for predicting Xp11.2 translocation/TFE3 gene fusion renal cell carcinoma (TFE3-RCC) and develop optimal therapeutic strategies. METHODS: Data from 4961 patients diagnosed with renal cell carcinoma at two medical centers in China were retrospectively analyzed. A cohort of 1571 patients from Zhejiang Provincial People's Hospital (Ra cohort) was selected to construct the model. Another cohort of 1124 patients from the Second Affiliated Hospital of Zhejiang Chinese Medical University was used for external validation (the Ha cohort). All patients with TFE3-RCC in both cohorts were included in the Ta cohort for the prognostic analysis. Univariate and multivariate binary logistic regression analyses were performed to identify independent predictors of the predictive nomogram. The apparent performance of the model was validated. Decision curve analysis was also performed to assess the clinical utility of the developed model. Factors associated with progression and prognosis in the Ta cohort were analyzed using the log-rank method, and Cox regression analysis and Kaplan-Meier survival curves were used to describe the effects of factors on prognosis and progression. RESULTS: Univariate and multivariate logistic regression analyses demonstrated that age, sex, BMI, smoking, eosinophils, and LDL were independent predictors of TFE3-RCC. Therefore, a predictive nomogram for TFE3-RCC, which had good discriminatory power (AUC = 0.796), was constructed. External validation (AUC = 0.806) also revealed good predictive ability. The calibration curves displayed good consistency between the predicted and observed incidences of TFE3-RCC. Invasion of regional lymph nodes, tyrosine kinase inhibitors, and surgical methods were independent factors associated with progression. Tyrosine kinase inhibitors are independent prognostic factors. CONCLUSION: This study not only proposed a high-precision clinical prediction model composed of various variables for the early diagnosis of Xp11.2 translocation/TFE3 gene fusion renal cell carcinoma but also optimized therapeutic strategies through prognostic analysis.

A Meta-Analysis of Circulating Microvesicles in Patients with Myocardial Infarction / Uma Meta-Análise de Microvesículas Circulantes em Pacientes com Infarto do Miocárdio

Abstract Background: Cell-derived microvesicles (MVs) are vesicles released from activated or apoptotic cells. However, the levels of MVs in myocardial infarction have been found inconsistent in researches. Objective: To assess the association between MVs and myocardial infarction by conducting a meta-analysis. Methods: A systematic literature search on PubMed, Embase, Cochran, Google Scholar electronic database was conducted. Comparison of the MVs levels between myocardial infarction patients and healthy persons were included in our study. Standard Mean Difference (SMD) and 95% confidence interval (CI) in groups were calculated and meta-analyzed. Results: 11 studies with a total of 436 participants were included. Compared with the health persons, AMVs [SMD = 3.65, 95% CI (1.03, 6.27)], PMVs [SMD = 2.88, 95% CI (1.82, 3.93),] and EMVs [SMD = 2.73, 95% CI (1.13, 4.34)], levels were higher in patients with myocardial infarction. However, LMVs levels [SMD = 0.73, 95% CI (-0.57, 2.03)] were not changed significantly in patients with myocardial infarction. Conclusions: AMVs, PMVs and EMVs might be potential biomarkers for myocardial infarction.

Resumo Fundamentos: As microvesículas derivadas de células (MVs) são vesículas liberadas de células ativadas ou apoptóticas. No entanto, os níveis de MVs no infarto do miocárdio foram encontrados inconsistentes nas pesquisas. Objetivo: Avaliar a associação entre MV e infarto do miocárdio por meio de uma meta-análise. Métodos: Foi realizada uma pesquisa sistemática na literatura em PubMed, Embase, Cochran e no banco de dados eletrônico do Google Scholar. Uma comparação dos níveis de MV entre pacientes com infarto do miocárdio e pessoas saudáveis foi incluída no nosso estudo. A Diferença Média Padrão (DMP) e o intervalo de confiança (IC) de 95% nos grupos foram calculadas e meta-analisadas. Resultados: Foram incluídos 11 estudos com um total de 436 participantes. Em comparação com as pessoas saudáveis, as MVA [DMP = 3,65, IC 95% (1,03, 6,27)], MVPs [DMP = 2,88, IC 95% (1,82, 3,93)] e MVEs [DMP = 2,73, IC 95% (1,13, 4.34)], foram maiores em pacientes com infarto do miocárdio. No entanto, os níveis de MVL [DMP = 0,73, IC 95% (-0,57, 2,03)] não foram alterados significativamente em pacientes com infarto do miocárdio. Conclusões: MVAs, MVPs e MVEs podem ser biomarcadores potenciais para o infarto do miocárdio.