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The molecular weight (MW) of an enzyme is a critical parameter in enzyme-constrained models (ecModels). It is determined by two factors: the presence of subunits and the abundance of each subunit. Although the number of subunits (NS) can potentially be obtained from UniProt, this information is not readily available for most proteins. In this study, we addressed this gap by extracting and curating subunit information from the UniProt database to establish a robust benchmark dataset. Subsequently, we propose a novel model named DeepSub, which leverages the protein language model and Bi-directional Gated Recurrent Unit (GRU), to predict NS in homo-oligomers solely based on protein sequences. DeepSub demonstrates remarkable accuracy, achieving an accuracy rate as high as 0.967, surpassing the performance of QUEEN. To validate the effectiveness of DeepSub, we performed predictions for protein homo-oligomers that have been reported in the literature but are not documented in the UniProt database. Examples include homoserine dehydrogenase from Corynebacterium glutamicum, Matrilin-4 from Mus musculus and Homo sapiens, and the Multimerins protein family from M. musculus and H. sapiens. The predicted results align closely with the reported findings in the literature, underscoring the reliability and utility of DeepSub. [ABSTRACT FROM AUTHOR]

AIM: The paper is to explore a rapid and simple method for the culture of mouse primary thyroid cells. METHODS: Mouse thyroid cells were isolated by enzyme digestion and cultured with improved medium, and their morphology, characteristics and secretory function were observed within 14 d. RESULTS: In the cultures, the active primary cells were obtained from the thyroid tissue after digestion for 25 min; adherent growth was observed on the 2nd day. And secondary follicles appeared from the 5th to 7th day. Over 95% cells were detected with thyroglobulin. The secretion of total triiodothyronine and total thyroxine maintains over 60% in 7 d. The expression levels of specific genes can still maintain more than 50% in 10 d. CONCLUSION: Mouse thyroid primary cells can be rapidly cultured by this method, and the cells can be used for studying thyroid endocrine secretion within 7 d and studying thyroid genes within 10 d. [ABSTRACT FROM AUTHOR]

Background: Sanguinarine chloride (S.C) is a benzophenanthrine alkaloid derived from the root of sanguinaria canadensis and other poppy-fumaria species. Studies have reported that S.C exhibits antioxidant, anti-inflammatory, proapoptotic, and growth inhibitory effects, which contribute to its anti-cancer properties. Recent studies suggested that the antitumor effect of S.C through inducing ferroptosis in some cancers. Nevertheless, the precise mechanism underlying the regulation of ferroptosis by S.C remains poorly understood. Methods: A small molecule library was constructed based on FDA and CFDA approved small molecular drugs. CCK-8 assay was applied to evaluate the effects of the small molecule compound on tumor cell viability. Prostate cancer cells were treated with S.C and then the cell viability and migration ability were assessed using CCK8, colony formation and wound healing assay. Reactive oxygen species (ROS) and iron accumulation were quantified through flow cytometry analysis. The levels of malondialdehyde (MDA) and total glutathione (GSH) were measured using commercially available kits. RNA-seq analysis was performed to identify differentially expressed genes (DEGs) among the treatment groups. Western blotting and qPCR were utilized to investigate the expression of relevant proteins and genes. In vivo experiments employed a xenograft mice model to evaluate the anti-cancer efficacy of S.C. Results: Our study demonstrated that S.C effectively inhibited the viability of various prostate cancer cells. Notably, S.C exhibited the ability to enhance the cytotoxicity of docetaxel in DU145 cells. We found that S.C-induced cell death partially relied on the induction of ferroptosis, which was mediated through up-regulation of HMOX1 protein. Additionally, our investigation revealed that S.C treatment decreased the stability of BACH1 protein, which contributed to HMOX1expression. We further identified that S.C-induced ROS caused BACH1 instability by suppressing USP47expression. Moreover, In DU145 xenograft model, we found S.C significantly inhibited prostate cancer growth, highlighting its potential as a therapeutic strategy. Collectively, these findings provide evidence that S.C could induce regulated cell death (RCD) in prostate cancer cells and effectively inhibit tumor growth via triggering ferroptosis. This study provides evidence that S.C effectively suppresses tumor progression and induces ferroptosis in prostate cancer cells by targeting ROS/USP47/BACH1/HMOX1 axis. Conclusion: This study provides evidence that S.C effectively suppresses tumor progression and induces ferroptosis in prostate cancer cells by targeting the ROS/USP47/BACH1/HMOX1 axis. These findings offer novel insights into the underlying mechanism by which S.C inhibits the progression of prostate cancer. Furthermore, leveraging the potential of S.C in targeting ferroptosis may present a new therapeutic opportunity for prostate cancer. This study found that S.C induces ferroptosis by targeting the ROS/USP47/BACH1/HMOX1 axis in prostate cancer cells. [ABSTRACT FROM AUTHOR]

Computers are widely used for business and entertainment purposes throughout our modern lives. Computer kits provide a variety of services such as text processing, programming, shopping, and gaming. Computers have greatly enhanced the quality of our lives; however, we discover an often-overlooked fact that engaging in computer-related activities may be eavesdropped upon by an attacker by sniffing the emitted acoustic signals from keyboard and mouse. The activity of eavesdropping via acoustic side channel has lower requirements in terms of hardware instrumentation and is easier to implement in real-world applications than other side channel attacks that have been presented in previous work. In this paper, we design and implement a system, namely, Behavicker, to validate the feasibility of this kind of attack. Unlike conventional activity recognition, Behavicker infers high-level computer-usage activities with a semantics-preserving multiscale learning scheme, based on the recognition of basic keyboard and mouse events including left click, right click, middle click, scrolling up, and scrolling down. Real-world experiments show that Behavicker can recognize six interaction events with an accuracy of 88.3% and infer computer-usage activities with an accuracy of 82.7% in an indoor environment. [ABSTRACT FROM AUTHOR]