Stearoyl-CoA desaturase 1 inhibition induces ER stress-mediated apoptosis in ovarian cancer cells.

Ovarian cancer is a leading cause of death among gynecologic tumors, often detected at advanced stages. Metabolic reprogramming and increased lipid biosynthesis are key factors driving cancer cell growth. Stearoyl-CoA desaturase 1 (SCD1) is a crucial enzyme involved in de novo lipid synthesis, producing mono-unsaturated fatty acids (MUFAs). Here, we aimed to investigate the expression and significance of SCD1 in epithelial ovarian cancer (EOC). Comparative analysis of normal ovarian surface epithelial (NOSE) tissues and cell lines revealed elevated SCD1 expression in EOC tissues and cells. Inhibition of SCD1 significantly reduced the proliferation of EOC cells and patient-derived organoids and induced apoptotic cell death. Interestingly, SCD1 inhibition did not affect the viability of non-cancer cells, indicating selective cytotoxicity against EOC cells. SCD1 inhibition on EOC cells induced endoplasmic reticulum (ER) stress by activating the unfolded protein response (UPR) sensors and resulted in apoptosis. The addition of exogenous oleic acid, a product of SCD1, rescued EOC cells from ER stress-mediated apoptosis induced by SCD1 inhibition, underscoring the importance of lipid desaturation for cancer cell survival. Taken together, our findings suggest that the inhibition of SCD1 is a promising biomarker as well as a novel therapeutic target for ovarian cancer by regulating ER stress and inducing cancer cell apoptosis.

Zirconium-Based Metal-Organic Framework Capable of Binding Proinflammatory Mediators in Hydrogel Form Promotes Wound Healing Process through a Multiscale Adsorption Mechanism.

The regulation of proinflammatory mediators has been explored to promote natural healing without abnormal inflammation or autoimmune response induced by their overproduction. However, most efforts to control these mediators have relied on pharmacological substances that are directly engaged in biological cycles. It is believed that functional porous materials removing target mediators provide a new way to promote the healing process using their adsorption mechanisms. In this study, the Zr-based metal-organic frameworks (MOF)-808 (Zr6 O4 (OH)4 (BTC)2 (HCOO)6 ) crystals are found to be effective at removing proinflammatory mediators, such as nitric oxide (NO), cytokines, and reactive oxygen species (ROS) in vitro and in vivo, because of their porous structure and surface affinity. The MOF-808 crystals are applied to an in vivo skin wound model as a hydrogel dispersion. Hydrogel containing 0.2 wt% MOF-808 crystals shows significant improvement in terms of wound healing efficacy and quality over the corresponding control. It is also proven that the mode of action is to remove the proinflammatory mediators in vivo. Moreover, the application of MOF-808-containing hydrogels promotes cell activation, proliferation and inhibits chronic inflammation, leading to increased wound healing quality. These findings suggest that Zr-based MOFs may be a promising drug-free solution for skin problems related to proinflammatory mediators.

Mettl14 mutation restrains liver regeneration by attenuating mitogens derived from non-parenchymal liver cells.

Liver regeneration is a well-known systemic homeostatic phenomenon. The N6-methyladenosine (m6A) modification pathway has been associated with liver regeneration and hepatocellular carcinoma. m6A methyltransferases, such as methyltransferase 3 (METTL3) and methyltransferase 14 (METTL14), are involved in the hepatocyte-specific-regenerative pathway. To illustrate the role of METTL14, secreted from non-parenchymal liver cells, in the initiation phase of liver regeneration, we performed 70% partial hepatectomy (PH) in Mettl14 heterozygous (HET) and wild-type (WT) mice. Next, we analyzed the ratio of liver weight to body weight and the expression of mitogenic stimulators derived from non-parenchymal liver cells. Furthermore, we evaluated the expression of cell cycle-related genes and the hepatocyte proliferation rate via MKI67-immunostaining. During regeneration after PH, the weight ratio was lower in Mettl14 HET mice compared to WT mice. The expressions of hepatocyte growth factor (HGF) and tumor necrosis factor (TNF)-α, mitogens derived from non-parenchymal liver cells that stimulate the cell cycle, as well as the expressions of cyclin B1 and D1, which regulate the cell cycle, and the number of MKI67-positive cells, which indicate proliferative hepatocyte in the late G1-M phase, were significantly reduced in Mettl14 HET mice 72 h after PH. Our findings demonstrate that global Mettl14 mutation may interrupt the homeostasis of liver regeneration after an acute injury like PH by restraining certain mitogens, such as HGF and TNF-α, derived from sinusoidal endothelial cells, stellate cells, and Kupffer cells. These results provide new insights into the role of METTL14 in the clinical treatment strategies of liver disease. [BMB Reports 2022; 55(12): 633-638].

ROS-Induced SIRT2 Upregulation Contributes to Cisplatin Sensitivity in Ovarian Cancer.

Cisplatin resistance remains a significant obstacle for improving the clinical outcome of ovarian cancer patients. Recent studies have demonstrated that cisplatin is an important inducer of intracellullar reactive oxygen species (ROS), triggering cancer cell death. Sirtuin 2 (SIRT2), a member of class III NAD+ dependent histone deacetylases (HDACs), has been reported to be involved in regulating cancer hallmarks including drug response. In this study, we aimed to identify the role of SIRT2 in oxidative stress and cisplatin response in cancer. Two ovarian cancer cell lines featuring different sensitivities to cisplatin were used in this study. We found different expression patterns of SIRT2 in cisplatin-sensitive (A2780/S) and cisplatin-resistant (A2780/CP) cancer cells with cisplatin treatment, where SIRT2 expression was augmented only in A2780/S cells. Furthermore, cisplatin-induced ROS generation was responsible for the upregulation of SIRT2 in A2780/S cells, whereas overexpression of SIRT2 significantly enhanced the sensitivity of cisplatin-resistant counterpart cells to cisplatin. Our study proposes that targeting SIRT2 may provide new strategies to potentiate platinum-based chemotherapy in ovarian cancer patients.

Compact fiber optic dual-detection confocal displacement sensor.

We propose a dual-detection confocal displacement sensor (DDCDS) with a compact fiber-based optical probe. This all-fiber-optic sensor probe is simple and robust, since it only requires simple alignment of a gradient refractive index lens and a double-clad fiber (DCF). The DDCDS is composed of two point detectors, one coupled to a single mode fiber and the other coupled to a multimode fiber, which are used to measure the light intensity from a core and an inner clad of a DCF, respectively. The ratio of the axial response curves, measured by the two detectors, can be used to obtain a linear relationship between the axial position of the object plane and the ratio of the intensity signals. We demonstrate the performance of the proposed method by measuring micromovement and fast vibration.

Stress detection and classification of laying hens by sound analysis.

Stress adversely affects the wellbeing of commercial chickens, and comes with an economic cost to the industry that cannot be ignored. In this paper, we first develop an inexpensive and non-invasive, automatic online-monitoring prototype that uses sound data to notify producers of a stressful situation in a commercial poultry facility. The proposed system is structured hierarchically with three binary-classifier support vector machines. First, it selects an optimal acoustic feature subset from the sound emitted by the laying hens. The detection and classification module detects the stress from changes in the sound and classifies it into subsidiary sound types, such as physical stress from changes in temperature, and mental stress from fear. Finally, an experimental evaluation was performed using real sound data from an audio-surveillance system. The accuracy in detecting stress approached 96.2%, and the classification model was validated, confirming that the average classification accuracy was 96.7%, and that its recall and precision measures were satisfactory.