Results 61 to 70 of about 168,165 (319)
Deep Learning for Patient-Specific Kidney Graft Survival Analysis [PDF]
arXiv, 2017 An accurate model of patient-specific kidney graft survival distributions can help to improve shared-decision making in the treatment and care of patients. In this paper, we propose a deep learning method that directly models the survival function instead of estimating the hazard function to predict survival times for graft patients based on the ...
arxiv
Deep Learning Potential of Mean Force between Polymer Grafted Nanoparticles [PDF]
arXiv, 2022 Grafting polymer chains on nanoparticles surfaces is a well-known route to control their self assembly and distribution in a polymer matrix. A wide variety of self assembled structures are achieved by changing the grafting patterns on an individual nanoparticle surface.
arxiv
Inhibitor of DNA binding‐1 is a key regulator of cancer cell vasculogenic mimicry
Molecular Oncology, EarlyView.Elevated expression of transcriptional regulator inhibitor of DNA binding 1 (ID1) promoted cancer cell‐mediated vasculogenic mimicry (VM) through regulation of pro‐angiogenic and pro‐cancerous genes (e.g. VE‐cadherin (CDH5), TIE2, MMP9, DKK1). Higher ID1 expression also increased metastases to the lung and the liver.
Emma J. Thompson +11 more
wiley +1 more source
Molecular Oncology, EarlyView.Breast cancer metastasis is associated with myeloid cell dysregulation and the lung‐specific accumulation of tumor‐supportive Gr1+ cells. Gr1+ cells support metastasis, in part, through a CHI3L1‐mediated mechanism, which can be targeted and inhibited with cargo‐free, polymeric nanoparticles.
Jeffrey A. Ma +9 more
wiley +1 more source
Predictive Capacity of Risk Models in Liver Transplantation
Transplantation Direct, 2019 Background. Several risk models to predict outcome after liver transplantation (LT) have been developed in the last decade. This study compares the predictive performance of 7 risk models. Methods.
Jacob D. de Boer, MD +5 more
doaj +1 more source
Impact of Combinations of Donor and Recipient Ages and Other Factors on Kidney Graft Outcomes
Frontiers in Immunology, 2020 As the availability of kidneys for transplantation continues to be outpaced by its growing demand, there has been an increasing utilization of older deceased donors in the last decades. Considering that definition of factors that influence deceased donor
Maria Gerbase-DeLima +6 more
doaj +1 more source
Penalized Variable Selection for Multi-center Competing Risks Data [PDF]
arXiv, 2016 We consider variable selection in competing risks regression for multi-center data. Our research is motivated by deceased donor kidney transplants, from which recipients would experience graft failure, death with functioning graft (DWFG), or graft survival. The occurrence of DWFG precludes graft failure from happening and therefore is a competing risk.
arxiv
The success and survival of repeat corneal grafts [PDF]
Eye, 1990 The results of 99 second grafts in individual eyes are reported. The five-year survival of these grafts was 49%. Allograft rejection was responsible for the majority of failures, but recurrence of host disease and endothelial decompensation were also important. Glaucoma was an important complication in 38% of eyes.
Arthur D. McG. Steele +3 more
openaire +2 more sources
FEBS Open Bio, EarlyView.Osimertinib reduces angiogenesis and PDL1 expression in in ovo tumors, transforming them into ‘cold tumors’ with lower immune activity. Anatomopathological and transcriptomic analyses highlight its therapeutic impact on tumor biology. This study underscores osimertinib's potential to reshape the tumor microenvironment and provides insights into its ...
David Barthélémy +14 more
wiley +1 more source
Frontiers in Public Health, 2019 Objectives: Patients' characteristics that could influence graft survival may also exhibit non-constant effects over time; therefore, violating the important assumption of the Cox proportional hazard (PH) model.
Okechinyere J. Achilonu +2 more
doaj +1 more source