Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Glycoprotein non-metastatic melanoma protein B (GPNMB) is a transmembrane glycoprotein that plays an important role in various physiological and pathological processes. In recent years, its role in lung diseases has gradually attracted attention. Studies have found that GPNMB is abnormally expressed in lung diseases and is involved in regulating pathological processes such as inflammatory responses, fibrosis, and tumorigenesis. This article systematically reviews the research progress of GPNMB in common lung diseases such as chronic obstructive pulmonary disease (COPD), pulmonary fibrosis, and lung cancer, and explores its potential as a therapeutic target, providing new insights for the diagnosis and treatment of lung diseases in the future.

Lupus nephritis (LN), one of the most severe complications of systemic lupus erythematosus (SLE), has a complex pathogenesis involving various endogenous factors including autoimmune complex deposition, inflammatory cell infiltration, and cellular damage. Recent research has increasingly highlighted the prominent role of inflammasomes, particularly the nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome, in LN pathogenesis. Substantial evidence has confirmed its significant role in both the onset and progression of LN. Given that the NLRP3 inflammasome is a critical factor in triggering and exacerbating LN, its mechanism of action warrants in-depth exploration. Furthermore, research on intervention strategies targeting the NLRP3 inflammasome to ameliorate LN is of great significance. This article reviews the latest advances in the role of the NLRP3 inflammasome in LN pathogenesis and related intervention studies, which may offer new insights for the clinical diagnosis and treatment of LN.
Humans ; Lupus Nephritis/etiology* ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Inflammasomes/immunology* ; Animals

Objective: To investigate the expression of transient receptor polycystic protein 2(TRPP2) in oral squamous epithelial cell and its effect on the invasion and migration of oral squamous cell carcinoma(OSCC), and to explore the potential signaling pathway of TRPP2 affecting OSCC metastasis. Methods: The OSCC model with TRPP2 knockdown was constructed by CRISPR-Cas9 lentivirus plasmid transfection technique. The effect of TRPP2 protein knockdown was verified by Western blot. The effect of TRPP2 on OSCC proliferation was detected by CCK-8 assay and clone formation assay. RT-qPCR was used to detect the target genes associated with TRPP2 metastasis to OSCC. Western blot and RT-qPCR were used to detect the expression of EpCAM and its transcription factors associated with unfolded protein response(UPR). The effects of TRPP2 on the invasion and migration of OSCC were examined by invasion test and scratch test. Results: Compared with HOK in oral epithelial cells, the expression of TRPP2 in OSCC was significantly higher. When TRPP2 was knocked down, OSCC proliferation and clonalformation were significantly enhanced. Compared with the control group, a total of 494 differential genes were significantly expressed in TRPP2 knockdown transcription profile, among which 234 genes were up-regulated and 260 genes were down-regulated. The expression of EpCAM gene, which is related to cell adhesion, was up-regulated. In addition, UPR related genes PERK, ATF6, GRP78 were up-regulated, while ATF6 and EpCAM were down-regulated in OSCC compared to HOK cells. The expression of ATF6 and EpCAM in oral squamous cell carcinoma cells was up-regulated by TRPP2 knockdown, and the cell migration and invasion ability decreased. The ATF6 inhibitor ceapin-A7(5 μmol/L) restored the OSCC migration and invasion ability of TRPP2 knockdown. Conclusion TRPP2 is highly expressed in OSCC. When TRPP2 is knocked down, OSCC proliferation ability is enhanced, migration and invasion ability are inhibited. TRPP2 mediates the expression of EpCAM through activation of UPR, thus affecting the invasion and migration of oral squamous cell carcinoma.

The vast majority of thyroid cancers show a good prognosis. However, the treatment of locally advanced thyroid cancer presents a huge problem. The wide application of targeted and immunotherapy in neoadjuvant therapy for locally advanced thyroid cancer has become a new therapeutic direction. This article summarizes the research on neoadjuvant chemotherapy, radiotherapy, and targeted therapy and immunotherapy related to various pathological types of thyroid cancer, with a focus on the recent advancements and thoughts on the application of targeted and immunotherapeutic drugs in neoadjuvant therapy. The results provide additional options for the clinical treatment of locally advanced thyroid cancer.

Lung cancer is one of the most lethal malignancies in the world, with non-small cell lung cancer (NSCLC) accounting for approximately 80%-85% of all pathological types. Approximately 30%-55% of NSCLC patients develop brain metastases. It has been reported that 5%-6% of patients with brain metastases harbor anaplastic lymphoma kinase (ALK) fusion. ALK-positive NSCLC patients have shown significant therapeutic benefits after treatment with ALK inhibitors. Over the past decade, ALK inhibitors have rapidly evolved and now exist in three generations: first-generation drugs such as Crizotinib; second-generation drugs including Alectinib, Brigatinib, Ceritinib, and Ensartinib; and third-generation drugs like Lorlatinib. These drugs have exhibited varying efficacy in treating brain metastases in ALK-positive NSCLC patients. However, the numerous options available for ALK inhibition present a challenge for clinical decision-making. Therefore, this review aims to provide clinical guidance by summarizing the efficacy and safety of ALK inhibitors in treating NSCLC brain metastases.
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Humans ; Carcinoma, Non-Small-Cell Lung/drug therapy* ; Lung Neoplasms/drug therapy* ; Brain Neoplasms/drug therapy* ; Protein Kinase Inhibitors/adverse effects* ; Crizotinib