5,612 research outputs found
Hepatitis C virus NS5A protein down-regulates the expression of spindle gene Aspm through PKR-p38 signaling pathway.
No full textMF-SuP-pKa: multi-fidelity modeling with subgraph pooling mechanism for pKa prediction
No full textAcid-base dissociation constant (pKa) is a key physicochemical parameter in chemical science, especially in organic synthesis and drug discovery. Current methodologies for pKa prediction still suffer from limited applicability domain and lack of chemical insight. Here we present MF-SuP-pKa (Multi-Fidelity modeling with Subgraph Pooling for pKa prediction), a novel pKa prediction model that utilizes subgraph pooling, multi-fidelity learning and data augmentation. In our model, a knowledge-aware subgraph pooling strategy was designed to capture the local and global environments around the ionization sites for micro-pKa prediction. To overcome the scarcity of accurate pKa data, low-fidelity data (computational pKa) was used to fit the high-fidelity data (experimental pKa) through transfer learning. Moreover, we implemented knowledge-guided data augmentation on the pre-training data according to the consistency between acidic pKa and basic pKa. The final MF-SuP-pKa model was constructed by pre-training on the augmented ChEMBL data set and fine-tuning on the DataWarrior data set. The ablation results prove that MF-SuP-pKa gains essential benefits from subgraph pooling, multi-fidelity learning, and data augmentation. Extensive evaluation on the DataWarrior data set and three benchmark data sets shows that MF-SuP-pKa achieves superior performances to the state-of-the-art pKa prediction models while requires much less high-fidelity training data. Compared with Attentive FP, MF-SuP-pKa achieves 23.83% and 20.12% improvement in terms of mean absolute error (MAE) on the acidic and basic sets, respectively
RIC-HSCT for MF/SS
No full textAdvanced-stage mycosis fungoides and Sezary syndrome (MF/SS) have a poor prognosis. Allogeneic hematopoietic stem cell transplantation (HSCT), particularly using a reduced-intensity conditioning (RIC) regimen, is a promising treatment for advanced-stage MF/SS. We performed RIC-HSCT in nine patients with advanced MF/SS. With a median follow-up period of 954days after HSCT, the estimated 3-year overall survival was 85.7% (95% confidence interval, 33.4-97.9%) with no non-relapse mortality. Five patients relapsed after RIC-HSCT; however, in four patients whose relapse was detected only from the skin, persistent complete response was achieved in one patient, and the disease was manageable in other three patients by the tapering of immunosuppressants and donor lymphocyte infusion, suggesting that graft-versus-lymphoma effect and "down-staging" effect from advanced stage to early stage by HSCT improve the prognosis of advanced-stage MF/SS. These results suggest that RIC-HSCT is an effective treatment for advanced MF/SS
Binomial Matrix Factorization for Discrete Collaborative Filtering
No full textMatrix factorization (MF) models have proved efficient and well scalable for collaborative filtering (CF) problems. Many researchers also present the probabilistic interpretation of MF. They usually assume that the factor vectors of users and items are from normal distributions, and so are the ratings when the user and item factors are given. Then they can derive the exact MF algorithm by finding a MAP estimate of the model parameters. In this paper we suggest a new probabilistic perspective on MF for discrete CF problems. We assume that all ratings are from binomial distributions with different preference parameters instead of the original normal distributions. The new interpretation is more reasonable for discrete CF problems since they only allow several legal discrete rating values. We also present two effective algorithms to learn the new model and make predictions. They are applied to the Netflix Prize data set and acquire considerably better accuracy than those of MF.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000287216600131&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Computer Science, Information SystemsEngineering, Electrical & ElectronicEICPCI-S(ISTP)
Whole-body F-18 FDG PET for hepatocellular carcinoma patients after interventional treatment.
No full textLong-term mortality assessment using biological measures among elderly people: ten-year follow-up of 597 healthy elderly cohort in Taiwan
No full textMyocardial infarction without coronary artery stenosis illustrated by 99mTc-pyrophosphate scan, cardiac magnetic resonance imaging, and myocardial perfusion scintigraphy
No full textEffects of diesel exhaust particles on left ventricular function in isoproterenol induced myocardial injury and healthy rats
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