Structure characterization of intrinsically disordered proteins (IDPs) remains a key obstacle in understanding their functional mechanisms. Due to the highly dynamic feature of IDPs, structure ensembles instead of static unique structures are often derived from experimental data. Several state-of-the-art computational methods have been developed to select an optimal ensemble from a pregenerated structure pool, but they suffer from low efficiency for large IDPs. Here we present a matching pursuit genetic algorithm (MPGA) for structure ensemble determination, which takes advantages from both matching pursuit (MP) to reduce the search space and genetic algorithm (GA) to reduce the restriction on constraint types. The MPGA method is validated using a reference ensemble with predefined structures. In comparison with the conventional GA, MPGA takes much less computational time for large IDPs. The utility of the method is demonstrated by application to structure ensemble determination of a mechanosensing protein domain with 306 amino acids. The structure ensemble determined reveals that the N-terminal region 1–240 is more compact than the C-terminal region 240–306. The unique structural feature explains why only a small portion of YXXP tyrosine residues can be phosphorylated easily by kinases in the absence of extension force and why the phosphorylation is force-dependent.
Abstract Background Retrospective analysis and pre-clinical studies suggest that local anesthetics have anti-tumoral effects. However, the association between cancer recurrence and the use of local anesthesia is inconclusive and most reports are based on single local anesthetic results. Methods The biological effects (growth, migration and survival) of four common local anesthetics on esophageal carcinoma cells were compared. Biochemical assays on molecules involved in cell migration and proliferation were analyzed. Results Ropivacaine and bupivacaine significantly inhibited esophageal carcinoma cell migration, at clinically relevant micromolar concentrations. Mepivacaine and lidocaine showed less potent cell migration inhibition than ropivacaine or bupivacaine. All four local anesthetics inhibited cell proliferation. Of note, the effective concentration of anti-proliferative activities requires higher doses. At millimolar concentrations of these local anesthetics, cell apoptosis was moderately affected. Drug combination analysis demonstrated that two of four local anesthetics augmented chemotherapeutic drugs in inhibiting migration. However, all four local anesthetics significantly augmented chemotherapeutic drugs in inhibiting growth and inducing apoptosis. The anti-growth and anti-survival effects of four local anesthetics were attributed to mitochondrial dysfunction and oxidative damage. The anti-migratory effect of local anesthetics is likely through decreasing Rac1 activity. Conclusions Our work demonstrates the differential effects and proposes the mechanisms of local anesthetics on esophageal carcinoma cell migration, growth, survival and chemosensitivity.
Abstract Objective This retrospective study aims to examine the correlation between calcium oxalate (CaOx) stones and common clinical tests, as well as urine ionic composition. Additionally, we aim to develop and implement a personalized column chart model to assess the accuracy and feasibility of using column charts to predict calcium oxalate stones in patients with urinary tract stones. Methods A retrospective analysis was conducted on data from 960 patients who underwent surgery for urinary stones at the First Affiliated Hospital of Soochow University from January 1, 2010, to December 31, 2022. Among these patients, 447 were selected for further analysis based on screening criteria. Multivariate logistic regression analysis was then performed to identify the best predictive features for calcium oxalate stones from the clinical data of the selected patients. A prediction model was developed using these features and presented in the form of a nomogram graph. The performance of the prediction model was assessed using the C-index, calibration curve, and decision curve, which evaluated its discriminative power, calibration, and clinical utility, respectively. Conclusion The nomogram diagram prediction model developed in this study is effective in predicting calcium oxalate stones, which is helpful in screening and early identification of high-risk patients with calcium oxalate urinary tract stones, and may be a guide for urologists in making clinical treatment decisions.
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