Contact Curve Based Simulation of Side Chains from Two Amino Acids in a Protein Molecule

In this paper, an algorithm to compute the contact configuration between the rotating side chains from two amino acids in a protein molecule is proposed. The main chain and side chain parts in one amino acid are considered as two rigidbody parts combined with a revolute joint. While the atom positions in the main chain parts of two amino acids are fixed, the side chains possibly rotate, which can cause the collision between amino acids. On the plane of rotation angle parameters, we find the region for two side chains colliding each other. Then, by extracting the boundary of the region, the contact curve of the amino acids is found, where by using it, the amino acids with rotating side chains can be simulated

Self-care use patterns in the UK, US, Australia, and Japan: a multinational web-based survey

AbstractBackgroundThe trend toward patient- or consumer-centered healthcare has been accelerated by advances in technology, consumer empowerment, and a shift from infectious to chronic diseases. The purpose of this study was to examine the growing self-care market by analyzing self-care patterns.MethodsWe conducted a cross-sectional, web-based survey involving adults from nine major cities in the UK, the USA, Australia, and Japan. This study examined the extent and frequency of self-care, self-care expenditure, sources of self-care information, and reasons for self-care in each country.ResultsThe results showed that the prevalence of self-care was highest in Japan (54.9%), followed by the UK (43.1%), the USA (42.5%), and Australia (40.4%). The primary reason for practicing self-care was “to manage my healthcare myself” (cited by 45.7%, 59.5%, 49.2%, and 4.1% of participants in Australia, Japan, the UK, and the USA, respectively). Significant linear associations were observed between age and the prevalence of self-care in all countries (p<0.05), indicating that self-care prevalence decreased with age in the UK, the USA, and Australia, and increased with age in Japan. The frequency with which self-care was practiced was positively correlated with age in the USA (p<0.05), Australia (p<0.01), and Japan (p<0.05). In addition to acquaintances, internet search engines and information obtained from pharmacies were considered reliable and widely used sources of self-care information.ConclusionWhen developing self-care products or services, healthcare providers and policymakers should consider self-care patterns

Effective gamma-ray sterilization and characterization of conductive polypyrrole biomaterials

Conductive polymers, including polypyrrole (PPy), have been extensively explored to fabricate electrically conductive biomaterials for bioelectrodes and tissue engineering scaffolds. For their in vivo uses, a sterilization method without severe impairment of original material properties and performance is necessary. Gamma-ray radiation has been commonly applied for sterilization of medical products because of its simple and uniform sterilization without heat generation. Herein we describe the first study on gamma-ray sterilization of PPy bioelectrodes and its effects on their characteristics. We irradiated PPy bioelectrodes with different doses (0–75 kGy) of gamma-rays. Gamma-ray irradiation of the PPy (γ-PPy) increased the oxygenation and hydrophilicity of the surfaces. Interestingly, gamma-ray irradiation did not alter the electrical impedances and conductivities of the PPy substrates. Additionally, γ-PPy prepared with various dopants (e.g., para-toluene sulfonate, polystyrene sulfonate, and chlorine) showed the electrochemical properties similar to the non-irradiated control. Gamma-ray irradiation at doses of ≥15 kGy was required for effective sterilization as evidenced by complete eradication of gram positive and negative bacteria. γ-PPy substrates also showed cytocompatibility similar to untreated control PPy, indicating no substantial alteration of cytocompatibility. In conclusion, gamma ray sterilization is a viable method of sterilization of conducting polymer-based biomaterials for biomedical applications

Association between decreased ipsilateral renal function and aggressive behavior in renal cell carcinoma

Background To assess prognostic value of pre-operative ipsilateral split renal function (SRF) on disease-free survival (DFS) and its association with aggressive pathological features in renal cell carcinoma (RCC) patients.  Methods We examined patients registered in SNUG-RCC-Nx who underwent partial or radical nephrectomy at Seoul National University Hospital between January 1, 2010 and December 31, 2020. Patients with the following criteria were excluded from the study. 1) non-kidney origin cancer or benign renal tumor, 2) no pre-operative Tc 99 m-DTPA renal scan, 3) single kidney status or previous partial or radical nephrectomy, and 4) bilateral renal mass. Finally, 1,078 patients were included. Results Among 1,078 patients, 899 (83.4%) showed maintained ipsilateral SRF on DTPA renal scan; 179 patients (16.6%) showed decreased SRF. The decreased SRF group showed significantly large tumor size (maintained vs. decreased SRF; 3.31 ± 2.15 vs. 6.85 ± 3.25, p < 0.001), high Fuhrman grade (grade 3–4) (41.7% vs. 55.6%, p < 0.001), and high T stage (T stage 3–4) (9.0% vs. 20.1%, p < 0.001). Pathological invasive features, including invasion of the renal capsule, perirenal fat, renal sinus fat, vein, and collecting duct system, were associated with low SRF of the ipsilateral kidney. Univariate Cox regression analysis identified higher SSIGN (The stage, size, grade, and necrosis) score and decreased ipsilateral SRF as significant risk factors, while multivariate analysis showed SSIGN (5–7) (hazard ratio [HR] 11.9, p < 0.001) and SSIGN (8–10) (HR 69.2, p < 0.001) were significantly associated with shortened DFS, while decreased ipsilateral SRF (HR 1.75, p = 0.065) showed borderline significance. Kaplan–Meier analysis showed that decreased ipsilateral SRF (< 45%) group had shorter DFS than the other group (median DFS: 90.3 months vs. not reached, p < 0.001). Conclusions Among unilateral RCC patients, those with low ipsilateral SRF showed poor prognosis with pathologically invasive features. Our novel approach may facilitate risk stratification in RCC patients, helping formulate a treatment strategy

Development of Representative Sailing Mode Construction Methodology Using Markov Chain

The strengthening of regulations such as EEXI, EEDI, and CII on ship emissions is underway. Despite their application, objective comparisons of ships are hindered by diverse navigation patterns and varying velocity regulations in different seas and ports. Additionally, a lack of basic data impedes comparisons of the optimal design and objective energy efficiency for ships. To address these issues, representative sailing modes, similar to those in the automobile industry, are needed. However, there is no reference for marine applications. This study introduces a methodology for representative sailing modes using the Markov chain. A hundred candidate sailing modes were created, and representative modes were identified through an evaluation equation. All chi-square values for representative sailing modes are within 1%, indicating significant results. This study’s findings can aid in designing optimized systems for new vessels and computing authorized fuel efficiency for vessels with diverse sailing patterns

Wasserstein filter for variable screening in binary classification in the reproducing kernel Hilbert space

The aim of this paper is to develop a marginal screening method for variable screening in high-dimensional binary classification based on the Wasserstein distance accounting for the distributional difference. Many existing screening methods, such as the two-sample t-test and Kolmogorov test, have been developed under the parametric/nonparametric modeling assumptions to reduce the dimension of the predictors. However, such modeling specifications or nonparametric approaches are associated with the probability measure induced by the predictor in a Euclidean space. While many machine learning methods have successfully found the nonlinear decision boundary in the transformed space, called the reproducing kernel Hilbert space (RKHS), we consider the Wasserstein filter's capacity to detect the distributional difference between two probability measures induced by the nonlinear function of the predictor in the RKHS. Thereby, we can flexibly filter out the non-informative predictors associated with the binary classification, as well as escape the modeling assumptions required in a Euclidean space. We prove that the Wasserstein filter satisfies the sure screening property under some mild conditions. We also demonstrate the advantages of our proposed approach by comparing the finite sample performance of it with those of the existing choices through simulation studies, as well as through application to lung cancer data.</p