Taste is a sensation produced by the reaction of substances in the mouth with taste receptor cells， and a normal taste function is essential for our daily life and health. As receivers of taste molecules， taste receptors include sour， bitter， sweet， salty， and umami receptors， which are mainly distributed in the oral cavity， gastrointestinal tract， respiratory tract epithelium and other organs and play a physiological role. Traditional Chinese medicine （TCM） has five flavors （sour， bitter， sweet， pungent， and salty）， which are closely related to the efficacy. Except the pungent flavor and umami taste receptors， the other five taste receptors correspond to the five flavors in the TCM theory， while the correlations between them have not been studied， such as those between bitter receptors and bitter TCM and between sweet receptors and sweet TCM. This article reviews the research reports on taste receptors in recent years. By analyzing the relationships of taste receptors with five flavors of TCM， signaling mechanisms， and diseases based on "receptor-TCM" correlations， this article puts forward the possibility of combining the TCM theory of five flavors with modern biomedical research， providing a reference for the research on "flavors" in TCM and the correlations between TCM and taste receptors.

Taste is a sensation produced by the reaction of substances in the mouth with taste receptor cells， and a normal taste function is essential for our daily life and health. As receivers of taste molecules， taste receptors include sour， bitter， sweet， salty， and umami receptors， which are mainly distributed in the oral cavity， gastrointestinal tract， respiratory tract epithelium and other organs and play a physiological role. Traditional Chinese medicine （TCM） has five flavors （sour， bitter， sweet， pungent， and salty）， which are closely related to the efficacy. Except the pungent flavor and umami taste receptors， the other five taste receptors correspond to the five flavors in the TCM theory， while the correlations between them have not been studied， such as those between bitter receptors and bitter TCM and between sweet receptors and sweet TCM. This article reviews the research reports on taste receptors in recent years. By analyzing the relationships of taste receptors with five flavors of TCM， signaling mechanisms， and diseases based on "receptor-TCM" correlations， this article puts forward the possibility of combining the TCM theory of five flavors with modern biomedical research， providing a reference for the research on "flavors" in TCM and the correlations between TCM and taste receptors.

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.

Objective:This study aims to investigate the influence of microvessel density（MVD） and microlymphatic vessel density（MLVD） on the prognosis of patients with hypopharyngeal squamous cell carcinoma（HPSCC） and to develop a nomogram prediction model for prognosis based on pathological characteristics. Methods:A retrospective analysis was conducted on clinicopathological and follow-up data from HPSCC patients who underwent surgical treatment at our institution between June 2010 and June 2020. Immunohistochemical staining was performed on tumor tissues and adjacent normal margin tissues to evaluate MVD and MLVD. The associations among MVD, MLVD, and clinicopathological features were analyzed. Univariate and multivariate Cox regression analyses were conducted to identify independent risk factors affecting overall survival（OS）. Based on these findings, a nomogram model was constructed and its predictive accuracy was assessed using C-index, receiver operating characteristic（ROC） curve, and calibration curve. Results:Both MVD and MLVD were significantly higher in HPSCC tumor tissues compared to normal tissues. Patients in the high MVD and high MLVD groups exhibited significantly lower OS rates than those in the low MVD and low MLVD groups. Multivariate Cox regression analysis revealed that N stage, recurrence, nerve invasion, lymph node capsule invasion, MVD, and MLVD were independent prognostic factors of OS. Based on these factors, a nomogram prognosis model was successfully constructed. The nomograms demonstrated superior performance in terms of C-index, area under the ROC curve, and calibration, outperforming the AJCC TNM staging system. Conclusion:Elevated MVD and MLVD levels are associated with poorer prognosis in HPSCC patients. The nomogram model based on pathological features provides valuable insights for clinical assessment and decision-making.
Humans ; Hypopharyngeal Neoplasms/blood supply* ; Prognosis ; Retrospective Studies ; Microvascular Density ; Nomograms ; Lymphatic Vessels/pathology* ; Male ; Female ; Middle Aged ; Carcinoma, Squamous Cell/blood supply* ; Microvessels/pathology* ; Lymphatic Metastasis ; Survival Rate

OBJECTIVE To explore the effects of dihydroartemisinin(DHA)on the functions of cancer-associated fibroblasts(CAFs)in the tumor microenvironment in hypopharyngeal squamous cell carcinoma(HPSCC).METHODS The influence of conditioned media from CAFs and normal fibroblasts(NFs)on tube formation was assessed using a tube formation assay.Secreted protein levels of IL-6,VEGFA,and VEGFC were measured by immunofluorescence and ELISA.Western blotting was used to evaluate the expression of α-SMA,p-STAT3,STAT3,VEGF-A,and VEGF-C within the STAT3 signaling pathway.After treatment with DHA,the optimal concentration for DHA's effect was determined using CCK8 assays and morphological observations of cells.The impact of DHA on angiogenesis was analyzed through tube formation assays,changes in IL-6 expression were detected using ELISA and immunofluorescence,and alterations in α-SMA,p-STAT3,and STAT3 expression were examined by Western blot.RESULTS Both CAFs and NFs exhibited pro-angiogenic and pro-lymphangiogenic effects,with CAFs showing a more pronounced impact.Activated CAFs overexpressed and secreted high levels of IL-6,VEGF-A,and VEGF-C.The concentration of IL-6 in the conditioned medium supernatants of CAF1 and CAF2 was significantly higher than that of NF1 and NF2(P1<0.001,P2<0.05).Similarly,the concentration of VEGF-A was significantly increased(P1<0.05,P2<0.01),and the concentration of VEGF-C was also significantly increased(P1<0.05,P2<0.01).Treatment with DHA inhibited the activated state of CAFs,reducing the expression and secretion of IL-6 and p-STAT3,thereby suppressing tube formation.CONCLUSION Our findings indicate that CAFs promote angiogenesis and lymphangiogenesis in HPSCC via activation of the STAT3 pathway.DHA effectively inhibits this process,suggesting a potential new therapeutic strategy for the treatment of HPSCC.

OBJECTIVE: To analyze four patients with a 16q22 fragile site with miscarriage or infertility by using cytogenetic methods. METHODS: Four patients presented at Northwest Women's and Children's Hospital between January 2022 and December 2024 were selected as the study subjects. Peripheral blood samples were collected from the patients and subjected to G-banded chromosomal karyotyping, among whom two were also subjected to copy number variation (CNV) sequencing. This study has been approved by the Ethics Committee of the Hospital (Ethics No. 2020-022). RESULTS: The chromosomal karyotypes of the patients were mos 46,XX,fra(16)(q22)[26]/47,XX,del(16)(q22),+chrb(16)(q22)[4]/46,XX,del(16)(q22)[3]/46,XX[91], mos 46,XY,fra(16)(q22)[21]/46,XY,del(16)(q22)[3]/46,XY[76], mos 46,XX,fra(16)(q22)[21]/ 46,XX,del(16)(q22)[4]/46,XX[75] and mos 46,XX,fra(16)(q22)[16]/46,XX,del(16)(q22)[7]/47,XX,del(16)(q22),+chrb(16)(q22)[6]/47,XX,fra(16)(q22),+chrb(16)(q22)[3]/46,XX[68], respectively. CNV sequencing of patients 2 and 4 revealed no deletion or duplication on chromosome 16. CONCLUSION Identification of the 16q22 fragile site has facilitated genetic counseling for these patients.
Humans ; Chromosome Fragile Sites/genetics* ; Chromosomes, Human, Pair 16/genetics* ; DNA Copy Number Variations/genetics* ; Karyotyping