Recently, the interplay between autophagy and apoptosis has become an important factor in chemotherapy for cancer treatment. Inhibition of autophagy may be an effective strategy to improve the treatment of chemo-resistant cancer by consistent exposure to chemotherapeutic drugs. However, no reports have clearly elucidated the underlying mechanisms. Therefore, in this study, we assessed whether salinomycin, a promising anticancer drug, induces apoptosis and elucidated potential antitumor mechanisms in chemo-resistant prostate cancer cells. Cell viability assay, Western blot, annexin V/propidium iodide assay, acridine orange (AO) staining, caspase-3 activity assay, reactive oxygen species (ROS) production, and mitochondrial membrane potential were assayed. Our data showed that salinomycin alters the sensitivity of prostate cancer cells to autophagy. Pretreatment with 3-methyladenine (3-MA), an autophagy inhibitor, enhanced the salinomycin-induced apoptosis. Notably, salinomycin decreased phosphorylated of AKT and phosphorylated mammalian target of rapamycin (mTOR) in prostate cancer cells. Pretreatment with LY294002, an autophagy and PI3K inhibitor, enhanced the salinomycin-induced apoptosis by decreasing the AKT and mTOR activities and suppressing autophagy. However, pretreatment with PD98059 and SB203580, an extracellular signal-regulated kinases (ERK), and p38 inhibitors, suppressed the salinomycin-induced autophagy by reversing the upregulation of ERK and p38. In addition, pretreatment with N-acetyl-l-cysteine (NAC), an antioxidant, inhibited salinomycin-induced autophagy by suppressing ROS production. Our results suggested that salinomycin induces apoptosis, which was related to ROS-mediated autophagy through regulation of the PI3K/AKT/mTOR and ERK/p38 MAPK signaling pathways.

4 Gb/s/pin 32 bit 512 Mb GDDR4 (Graphics Double Data Rate 4) SDRAM was implemented by using an 80 nm CMOS process. It employs a data bus inversion (DBI) coding to overcome the bottleneck of a parallel single-ended signaling, a power consumption of I/O, power supply noise, and crosstalk. Both DBI AC and DC modes are combined to a single circuit by eliminating the feedback path of a conventional DBI AC circuit while achieving high-speed operation. The proposed DBI circuit uses an analog majority voter insensitive to mismatch for small area and delay. R_onmiddot tuning further improves the voltage and time margin by adding a user-supplied offset to auto-calibrated R_onmiddot. In addition, a dual duty cycle corrector (DCC) is used to reduce duty error and jitter by averaging two outputs of two DCCs. Measured results show that DBI DC coding reduces the peak-to-peak jitter from 65.5 ps to 44.5 ps and the voltage fluctuation from 183 mV to 115 mV at the data rate of 4 Gb/s with the 2 V.

Network pharmacology has gained significant traction as a tool for identifying the mechanisms and therapeutic effects of herbal medicines. However, despite the usefulness of these approaches, their diversity underscores the critical need for a systematic evaluation to ensure consistency and reliability. We aimed to evaluate the network pharmacological analyses, focusing on identifying the mechanisms and therapeutic effects of herbal medicines. We employed a comprehensive approach involving systematic data retrieval, network construction, and analysis. Herbal compounds and their targets were meticulously extracted from five distinct network pharmacology databases to ensure extensive coverage and high data reliability. Advanced network-based methods were used to identify key herbal targets and predict therapeutic effects, thereby enriching the depth and breadth of the analysis. Experimental validation was performed on prostate cancer models to substantiate the computational predictions. The results of the recapitulating task for known herbal ingredient targets revealed distinct patterns in performance and coverage based on network construction and aggregation methods. We performed the same analysis to identify herbal targets and found that network centrality, path counts, and downweighted path counts had their own pros and cons. By comparing network-based methods, we found that considering the impact on the multiscale interactome yielded the highest accuracy in discriminating known therapeutic effects. Using optimal conditions, we successfully identified new indications for herbal medicines and validated these findings through follow-up in vitro and in vivo experiments. This study presents the first comprehensive and critical evaluation of the current network pharmacology analyses in the field of herbal medicine and provides valuable guidance for continued advances in the elucidation of the mechanisms and therapeutic effects.

We investigated the effects of a Leonurus japonicus ethanol extract (LJE) on nonalcoholic fatty liver disease (NAFLD). An in vitro model of hepatic steatosis was treated with 1 mM free fatty acid (FFA) in HepG2 cells. An in vivo NAFLD model was established using C57BL/6 mice fed a high-fat diet (HFD) and administered LJE (100 or 200 mg/kg) orally for 14 weeks. LJE treatment suppressed lipid accumulation and intracellular triglyceride levels significantly in a concentration-dependent manner in HepG2 cells. Moreover, LJE significantly reduced the expression of sterol regulatory element binding protein 1-c, and its downstream genes, which are associated with lipogenesis, in HepG2 cells. In HFD-fed mice, LJE treatment decreased body weight significantly and decreased serum alanine transaminase levels to normal values, concurrent with a decrease in hepatic lipid accumulation. Furthermore, LJE supplementation ameliorated insulin sensitivity by decreasing serum glucose and insulin levels. LJE improved hepatic steatosis by increasing the expression of phosphorylated AMP-activated protein kinase and peroxisome proliferator-activated receptor-α in HFD-fed mice and FFA-treated HepG2 cells. The results suggested that LJE might be a potential therapeutic agent to treat NAFLD.