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Protein degradation is a fundamental process in all living cells and is essential to remove both damaged proteins and intact proteins that are no longer needed by the cell. We are interested in creating synthetic genetic circuits that function in a cell-free expression system. This will require not only an efficient protein expression platform but also a robust protein degradation system in cell extract. Therefore, we purified and tested the activity of E. coli ClpXP protease in cell-free transcription-translation (TX-TL) systems that used E. coli S30 cell extract. Surprisingly, our studies showed that purified ClpXP added to the TX-TL system has very low proteolytic activity. The low activity of ClpXP was correlated with the rapid consumption of adenosine triphosphate (ATP) in cell extract. We improved the activity of ClpXP in cell extract by adding exogenous ATP and an energy regeneration system. We then established conditions for both protein synthesis, and protein degradation by ClpXP to occur simultaneously in the TX-TL systems. The optimized conditions for ClpXP activity will be useful for creating tunable synthetic genetic circuits and in vitro synthetic biology.

Abstract Emerging studies suggest the application of self-regulation learning (SRL) to improve generalization abilities in poststroke patients. SRL has been proposed to have an added effect on computer-aided cognitive training (CACT). This study aimed to examine the efficacy of an intervention combining computer-aided SRL (CA-SRL) training and CACT for generalization abilities and cognitive function in patients with poststroke cognitive impairment (PSCI). A total of 75 patients recruited from a rehabilitation centre were randomly assigned to a CA-SRL group, demonstration learning (DL) group and traditional learning (TL) group. Finally, 72 patients were included in the analysis. Over 3 weeks, the patients in these three groups underwent CA-SRL or DL training combined with cognitive training. After the intervention, all outcomes significantly improved (P

Abstract Modern money transfer services are convenient, attracting fraudulent actors to run scams in which victims are deceived into transferring funds to fraudulent accounts. Machine learning models are broadly applied due to the poor fraud detection performance of traditional rule-based approaches. Learning directly from raw transaction data is impractical due to its high-dimensional nature; most studies construct features instead by extracting patterns from raw transaction data. Past literature categorizes these features into recency, frequency, monetary, and anomaly detection features. We use various machine learning algorithms to examine the performance of features in these four categories with real transaction data; we compare them with the performance of our feature generation guideline based on the statistical perspectives and characteristics of (non)-fraudulent accounts. The results show that except for the monetary category, other feature categories used in the literature perform poorly regardless of which machine learning algorithm is used; anomaly detection features perform the worst. We find that even statistical features generated based on financial knowledge yield limited performance on a real transaction dataset. Our atypical detection characteristic of normal accounts improves the ability to distinguish them from fraudulent accounts and hence improves the overall detection results, outperforming other existent methods.

To quantify the societal impact of disability in patients with non-small cell lung cancer (NSCLC), this study estimated the disability-free life expectancy (DFLE), loss-of-DFLE and explored their associations with quality-adjusted life expectancy (QALE) and loss-of-QALE. We interlinked national databases and applied a rolling-over algorithm to estimate the lifetime survival function for patients with NSCLC. Using the EuroQOL-5 Dimension (EQ-5D) and Barthel index (BI), we repeatedly measured the quality-of-life and disability functions of NSCLC patients who visited our hospital from 2011 to 2020. Age-, sex-matched referents were simulated from lifetables of the same calendar year of diagnosis. We categorized BI scores ≤ 70 as in need of long-term care and constructed linear mixed models to estimate the utility values and disability scores. We collected 960 cases and 3088 measurements. The proportions of measurements without disability at age 50-64 and in stage I-IIIa, 50-64 and stage IIIb-IV, 65-89 and stage I-IIIa and 65-89 and stage IIIb-IV were 97.3%, 89.3%, 94.8%,78.3%, corresponding to DFLEs of 15.3, 2.4, 6.8, 1.2 years and losses-of-DFLE of 8.1, 20.7, 4.0, 8.6 years, respectively, indicating that advanced stage had a stronger effect than old age. Survivors in advanced stages showed increased demands for assistance in almost all subitems. The DFLEs seemed to be approximate to the QALEs and the latter were shorter than the former due to discomfort and depression. From a societal perspective, future health technology assessment should consider the impact of lifetime duration of functional disability. Early diagnosis of NSCLC may decrease the burden of long-term care., (© 2023. Springer Nature Limited.)

DNA methylation alteration, such as global hypomethylation and localized hypermethylation, within the promoters of tumor suppressor genes, is an important risk factor in cervical cancer. The potential use of DNA methylation detection, in cervical cancer screening or triage of mildly abnormal cytology, has recently been demonstrated. In particular, PAX1 DNA methylation testing was approved as an adjunct to cytology, in Taiwan, and is now undergoing registration trials in China. However, the function of PAX1 in cancer biology remains largely unknown. Here, we show that PAX1 inhibits malignant phenotypes upon oncogenic stress. Specifically, PAX1 expression inhibited the phosphorylation of multiple kinases, after challenges with oncogenic growth factors such as EGF and IL-6. Analogously, PAX1 activated a panel of phosphatases, including DUSP1, 5, and 6, and inhibited EGF/MAPK signaling. PAX1 also interacted with SET1B, increasing histone H3K4 methylation and DNA demethylation of numerous phosphatase-encoding genes. Furthermore, hypermethylated PAX1 associated with poor prognosis in cervical cancer. Taken together, this study reveals, for the first time, the functional relevance of PAX1 in cancer biology, and further supports the prospect of targeting multifold oncogenic kinase cascades, which jointly contribute to multiresistance, via epigenetic reactivation of PAX1.