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.

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.

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.

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

The majority patients of differentiated thyroid carcinoma (DTC) with indolent progression have general good prognosis after standard primary treatments including surgery, thyroid stimulating hormone (TSH) suppression and radioactive iodine (RAI) therapy. However, there are still some patients suffered from recurrence or distant metastasis after initial treatment. They may lose the ability of uptaking iodine during their natural course of disease or treatment and could not benefit from subsequent RAI treatment, which will result in radioiodine-refractory differentiated thyroid cancer (RAIR-DTC). Options are very limited for RAIR-DTC patients, which is associated with a poor prognosis. Recently, with the research advances on the molecular mechanism of RAIR-DTC, redifferentiation combined with RAI therapy have been increasingly used to treat RAIR-DTC, and some outcomes are quite encouraging. This paper reviews the progress of signaling pathway inhibitors, histone deacetylase inhibitors, DNA methyltransferase inhibitors, retinoids and peroxisome proliferator-activated receptor agonists in redifferentiating therapy of RAIR-DTC.

The cold chain safety of vaccines is a global issue. The electronic vaccine vial monitor (eVVM) label can monitor the temperature of vaccines in real time and provide "early warning" prompts. In order to comprehensively evaluate the monitoring efficiency of eVVM, this study selected 75 eVVM labels and distributed them with a total of 600 vaccine vial monitor (VVM) labels of four different types in different experimental environment (2-8℃, -20℃ and 40℃), and used a temperature recorder as "gold standard". The results showed that the accuracy of the eVVM labels and VVM labels in high temperature environment was as same as that of the temperature recorder (
Drug Storage ; Electronics ; Refrigeration ; Temperature ; Vaccines