Effects of carnosic acid on mitochondrial biogenesis and insulin sensitivity in 3T3-L1 adipocytes are through induction of PGC-1α and ubiquitination of PARIS by parkin

The PGC-1α plays a vital role in regulating mitochondrial biogenesis and insulin sensitivity. This study investigated the role of PGC-1α in preventing the effects of carnosic acid (CA) against TNF-α-suppressed mitochondrial biogenesis and insulin signaling. Exposure of 3T3-L1 adipocytes to TNF-α decreased the proteins of PGC-1α and nuclear respiratory factor 1 (NRF1). However, pretreatment with CA improved this change. Additionally, CA led to increases in parkin protein and decreases in PARIS protein. Using immunoprecipitation assay, the protein interaction between PARIS and ubiquitin was increased and that between PARIS and parkin was decreased after CA treatment. Parkin siRNA blocked the effects of CA on PARIS, PGC-1α, and NRF1 proteins. PGC-1α siRNA abolished the capacity of CA to reverse the TNF-α-inhibited insulin signaling and membrane GLUT4 protein translocation. Therefore, CA attenuates the TNF-α induced impairment of mitochondrial biogenesis and glucose uptake through activation of PGC-1α via ubiquitination of PARIS by parkin

CLEFMA Induces the Apoptosis of Oral Squamous Carcinoma Cells through the Regulation of the P38/HO-1 Signalling Pathway

The purpose of this research was to evaluate the impact and the underlying molecular mechanism of CLEFMA-induced cell death in human OSCC. The anti-tumour properties of CLEFMA in oral cancer were explored using colony formation, flow cytometry, human apoptosis array, Western blot, and immunohistochemistry assays. The in vivo anti-tumour effect of CLEFMA administered by oral gavage was evaluated using SCC-9-derived xenograft-bearing nude mouse models. CLEFMA significantly suppressed colony formation and elicited cellular apoptosis in oral cancer cells. CLEFMA treatment remarkably increased phosphorylated p38 and HO-1 along with cleavage of poly ADP-ribose polymerase and activation of caspase-8, -9, and -3 in HSC-3 and SCC-9 cells. Administration of HO-1 small interfering RNA significantly protected the cells from CLEFMA-induced caspase-3, -8, and -9 activation. Attenuation of p38 activity by the pharmacologic inhibitor SB203580 dramatically reduced CLEFMA-induced caspase-3, -8, and -9 activation and HO-1 expression in OSCC. The subcutaneous murine xenograft models showed that CLEFMA in vivo suppressed tumour growth in implanted SCC-9 cells. All of these findings indicated that CLEFMA induced apoptosis through the p38-dependent rise in HO-1 signal transduction cascades in OSCC

Cancers Screening in an Asymptomatic Population by Using Multiple Tumour Markers.

Analytic measurement of serum tumour markers is one of commonly used methods for cancer risk management in certain areas of the world (e.g. Taiwan). Recently, cancer screening based on multiple serum tumour markers has been frequently discussed. However, the risk-benefit outcomes appear to be unfavourable for patients because of the low sensitivity and specificity. In this study, cancer screening models based on multiple serum tumour markers were designed using machine learning methods, namely support vector machine (SVM), k-nearest neighbour (KNN), and logistic regression, to improve the screening performance for multiple cancers in a large asymptomatic population.AFP, CEA, CA19-9, CYFRA21-1, and SCC were determined for 20 696 eligible individuals. PSA was measured in men and CA15-3 and CA125 in women. A variable selection process was applied to select robust variables from these serum tumour markers to design cancer detection models. The sensitivity, specificity, positive predictive value (PPV), negative predictive value, area under the curve, and Youden index of the models based on single tumour markers, combined test, and machine learning methods were compared. Moreover, relative risk reduction, absolute risk reduction (ARR), and absolute risk increase (ARI) were evaluated.To design cancer detection models using machine learning methods, CYFRA21-1 and SCC were selected for women, and all tumour markers were selected for men. SVM and KNN models significantly outperformed the single tumour markers and the combined test for men. All 3 studied machine learning methods outperformed single tumour markers and the combined test for women. For either men or women, the ARRs were between 0.003-0.008; the ARIs were between 0.119-0.306.Machine learning methods outperformed the combined test in analysing multiple tumour markers for cancer detection. However, cancer screening based solely on the application of multiple tumour markers remains unfavourable because of the inadequate PPV, ARR, and ARI, even when machine learning methods were incorporated into the analysis

AUC Values of Various Classifiers and Tumour Markers for Cancer Screening (Male).

<p>AUC Values of Various Classifiers and Tumour Markers for Cancer Screening (Male).</p

Performance of the Various Methods for Cancer Screening (Female).

<p>Performance of the Various Methods for Cancer Screening (Female).</p

Moringa oleifera Lam.

原著和名: ワサビノキ科名: ワサビノキ科 = Moringaceae採集地: 静岡県 賀茂郡 南伊豆町 下賀茂 (伊豆 賀茂郡 南伊豆町 下賀茂)採集日: 1965/4/10採集者: 萩庭丈壽整理番号: JH045405国立科学博物館整理番号: TNS-VS-99540

Arctiin Inhibits Cervical Cancer Cell Migration and Invasion through Suppression of S100A4 Expression via PI3K/Akt Pathway

Arctiin, a lignan glycoside, is isolated from Arctium lappa L. The anticancer effects of arctiin have been demonstrated in several studies. However, no research has been conducted on the anti-migration effect of arctiin in cervical cancer cells. The present study examined the effects of arctiin on cervical cancer cells and investigated the possible molecular mechanism. We demonstrated that arctiin exhibited low cytotoxicity and significantly inhibited cell migration and invasion in human cervical cancer cells. The S100A4 protein expression and mRNA levels were significantly reduced in HeLa and SiHa cells with arctiin treatment. Furthermore, silencing S100A4 by using small interfering RNA reduced cell migration, while overexpression of S100A4 mitigated the migration inhibition imposed by arctiin in cervical cancer cells. Western blotting revealed that arctiin significantly reduced phosphoinositide 3-kinase (PI3K) and phosphorylation of Akt in cervical cancer cells. Moreover, selective Akt induction by an Akt activator, SC-79, reverted cervical cancer cell migration and S100A4 protein expression, which were reduced in response to arctiin. Taken together, these results suggest that arctiin inhibits cervical cancer cell migration and invasion through suppression of S100A4 and the PI3K/Akt pathway

Performance of the Various Methods for Cancer Screening (Male).

<p>Performance of the Various Methods for Cancer Screening (Male).</p

Dihydromyricetin Inhibited Migration and Invasion by Reducing S100A4 Expression through ERK1/2/β-Catenin Pathway in Human Cervical Cancer Cell Lines

Cervical cancer has a poor prognosis and is the fourth most common cancer among women. Dihydromyricetin (DHM), a flavonoid compound, exhibits several pharmacological activities, including anticancer effects; however, the effects of DHM on cervical cancer have received insufficient research attention. This study examined the antitumor activity and underlying mechanisms of DHM on human cervical cancer. Our results indicated that DHM inhibits migration and invasion in HeLa and SiHa cell lines. Mechanistically, RNA sequencing analysis revealed that DHM suppressed S100A4 mRNA expression in HeLa cells. Moreover, DHM inhibited the protein expressions of β-catenin and GSK3β through the regulated extracellular-signal-regulated kinase (ERK)1/2 signaling pathway. By using the ERK1/2 activator, T-BHQ, reverted β-catenin and S100A4 protein expression and cell migration, which were reduced in response to DHM. In conclusion, our study indicated that DHM inhibited cell migration by reducing the S100A4 expression through the ERK1/2/β-catenin pathway in human cervical cancer cell lines

AUC Values of the Various Classifiers and Tumour Markers for Cancer Screening (Female).

<p>AUC Values of the Various Classifiers and Tumour Markers for Cancer Screening (Female).</p