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Our results show that melanin from S. ZD4522 calcium reilianum is a natural pigment with good stability that has a great prospect of development and application, providing a theoretical basis and methods for its further processing and development as a functional food.Machine intelligence (MI), including machine learning and deep learning, have been regarded as promising methods to reduce the prohibitively high cost of drug development. However, a dilemma within MI has limited its wide application machine learning models are easier to interpret but yield worse predictive performance than deep learning models. Therefore, we propose a pipeline called Class Imbalance Learning with Bayesian Optimization (CILBO) to improve the performance of machine learning models in drug discovery. To demonstrate the efficacy of the CILBO pipeline, we developed an example model to predict antibacterial candidates. Comparison of the antibacterial prediction performance between our model and a well-known deep learning model published by Stokes et al. suggests that our model can perform as well as the deep learning model in drug activity prediction. The CILBO pipeline we propose provides a simple, alternative approach to accelerate preliminary screenings and decrease the cost of drug discovery.Oral glucose ingestion induces systemic changes of many blood metabolites related not only to glucose, but also other metabolites such as amino acids and lipids through many blood hormones. However, the detailed temporal changes in the concentrations of comprehensive metabolites and hormones over a long time by oral glucose ingestion are uncharacterized. We measured 83 metabolites and 7 hormones in 20 healthy human subjects in response to glucose ingestion. We characterized temporal patterns of blood molecules by four features (i) the decomposability into "amplitude" and "rate" components, (ii) the similarity of temporal patterns among individuals, (iii) the relation of molecules over time among individuals, and (iv) the similarity of temporal patterns among molecules. Glucose and glucose metabolism-related hormones indicated a rapid increase, and citrulline and lipids, which indicated a rapid decrease, returned to fasting levels faster than amino acids. Compared to glucose metabolism-related molecules and lipids, amino acids showed similar temporal patterns among individuals. The four features of temporal patterns of blood molecules by oral glucose ingestion characterize the differences among individuals and among molecules.Due to ligament laxity, bearing dislocation occurs in 1-6% of Oxford Domed Lateral (ODL) replacements with most dislocations occurring medially. Dislocations were studied using a previously built mechanical rig, however testing using the rig was inefficient. The aim of this study was to develop a better tool that was more reliable and efficient. An established robotics software package, the Open Motion Planning Library, was modified to accept the ODL components. Using a robotics path planning algorithm, the mobile bearing was allowed to find a way out from between the femoral and tibial components i.e. to dislocate. Testing assessed a range of clinically relevant positions of the femoral component relative to the tibial component. Dislocations were labelled as medial, lateral, anterior or posterior depending on the dislocation direction. The Distraction to Dislocation (DD) measured the minimum vertical distraction of the femoral component from the tibial component for a dislocation to occur. Results were validated against the mechanical rig. Statistical analysis of medial dislocation showed excellent agreement with an intraclass correlation value of 0.993 (95% CI 0.982-0.998). All DDs from the dislocation analysis tool were within 1 mm of the mechanical rig DDs with results sharing a remarkably similar trend. The robotics dislocation analysis tool output DDs which were marginally higher than the manual mechanical rig 0.50 mm anteriorly, 0.25 mm posteriorly and 0.50 mm laterally. Medially, the computational DD differed on average by 0.09 mm (stand deviation 0.2026 mm). Our study describes the development and validation of a novel robotics dislocation analysis tool, which allows mobile bearing dislocation risk quantification. The tool may also be used to improve surgical implantation parameters and to assess new implant designs that aim to reduce the medial dislocation risk to an acceptable level.Hip fractures are a major cause of morbidity and mortality in the elderly, and incur high health and social care costs. Given projected population ageing, the number of incident hip fractures is predicted to increase globally. As fracture classification strongly determines the chosen surgical treatment, differences in fracture classification influence patient outcomes and treatment costs. We aimed to create a machine learning method for identifying and classifying hip fractures, and to compare its performance to experienced human observers. We used 3659 hip radiographs, classified by at least two expert clinicians. The machine learning method was able to classify hip fractures with 19% greater accuracy than humans, achieving overall accuracy of 92%.Ischemia-reperfusion (IR) injury accelerates myocardial injury sustained during the myocardial ischemic period and thus abrogates the benefit of reperfusion therapy in patients with acute myocardial infarction. We investigated the efficacy of intracoronary ethylenediaminetetraacetic acid (EDTA) administration as an adjunctive treatment to coronary intervention to reduce IR injury in a swine model. We occluded the left anterior descending artery for 1 h. From the time of reperfusion, we infused 50 mL of EDTA-based chelating agent via the coronary artery in the EDTA group and normal saline in the control group. IR injury was identified by myocardial edema on echocardiography. Tetrazolium chloride assay revealed that the infarct size was significantly lower in the EDTA group than in the control group, and the salvage percentage was higher. Electron microscopy demonstrated that the mitochondrial loss in the cardiomyocytes of the infarcted area was significantly lower in the EDTA group than in the control group. Echocardiography after 4 weeks showed that the remodeling of the left ventricle was significantly less in the EDTA group than in the control group end-diastolic dimension 38.8 ± 3.3 mm vs. 43.9 ± 3.7 mm (n = 10, p = 0.0089). Left ventricular ejection fraction was higher in the EDTA group (45.3 ± 10.3 vs. 34.4 ± 11.8, n = 10, respectively, p = 0.031). In a swine model, intracoronary administration of an EDTA chelating agent reduced infarct size, mitochondrial damage, and post-infarct remodeling. This result warrants further clinical study evaluating the efficacy of the EDTA chelating agent in patients with ST-segment elevation myocardial infarction.Previous spectral analysis studies on insomnia have shown inconsistent results due to their heterogeneity and small sample sizes. We compared the difference of electroencephalogram (EEG) spectral power during sleep among participants without insomnia, insomniacs with no hypnotic use, hypnotic users with no insomnia complaints, and hypnotic users with insomnia complaints using the Sleep Heart Health Study data, which is large sample size and has good quality control. The fast Fourier transformation was used to calculate the EEG power spectrum for total sleep duration within contiguous 30-s epochs of sleep. For 1985 participants, EEG spectral power was compared among the groups while adjusting for potential confounding factors that could affect sleep EEG. The power spectra during total sleep differed significantly among the groups in all frequency bands (pcorr  less then  0.001). We found that quantitative EEG spectral power in the beta and sigma bands of total sleep differed (pcorr  less then  0.001) between participants without insomnia and hypnotic users with insomnia complaints after controlling for potential confounders. The higher beta and sigma power were found in the hypnotic users with insomnia complaints than in the non-insomnia participants. This study suggests differences in the microstructures of polysomnography-derived sleep EEG between the two groups.Parkinson's disease (PD) is the neurological disorder showing the greatest rise in prevalence from 1990 to 2016. Despite clinical definition criteria and a tremendous effort to develop objective biomarkers, precise diagnosis of PD is still unavailable at early stage. In recent years, an increasing number of studies have used omic methods to unveil the molecular basis of PD, providing a detailed characterization of potentially pathological alterations in various biological specimens. Metabolomics could provide useful insights to deepen our knowledge of PD aetiopathogenesis, to identify signatures that distinguish groups of patients and uncover responsive biomarkers of PD that may be significant in early detection and in tracking the disease progression and drug treatment efficacy. The present work is the first large metabolomic study based on nuclear magnetic resonance (NMR) with an independent validation cohort aiming at the serum characterization of de novo drug-naive PD patients. Here, NMR is applied to sera from large training and independent validation cohorts of German subjects. Multivariate and univariate approaches are used to infer metabolic differences that characterize the metabolite and the lipoprotein profiles of newly diagnosed de novo drug-naive PD patients also in relation to the biological sex of the subjects in the study, evidencing a more pronounced fingerprint of the pathology in male patients. The presence of a validation cohort allowed us to confirm altered levels of acetone and cholesterol in male PD patients. By comparing the metabolites and lipoproteins levels among de novo drug-naive PD patients, age- and sex-matched healthy controls, and a group of advanced PD patients, we detected several descriptors of stronger oxidative stress.Molecular studies based on the high resolution genetic markers help us to grasp the factor shaping the genetic structure of marine organisms. Ecological factors linking to life history traits have often explained the process of genetic structuring in open and connectable oceanic environments. Besides, population genetic divergence can be affected by fragmented habitat, oceanic current, and past geographical events. In the present study, we demonstrated the genetic differentiation of marine gastropod Monodonta sp. within a narrow range of peripheral oceanic islands, the Ogasawara Islands. Genetic analyses were performed not only with a mitochondrial DNA marker but also with a high-throughput SNPs dataset obtained by ddRAD-seq. The results of the mtDNA analyses did not show genetic divergence among populations, while the SNPs dataset detected population genetic differentiation. Population demographic analyses and gene flow estimation suggested that the genetic structure was formed by sea level fluctuation associated with the past climatic change and regulated by temporal oceanographic conditions. These findings provide important insights into population genetic patterns in open and connectable environments.

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