Results 81 to 90 of about 963,951 (309)

TRAIL‐PEG‐Apt‐PLGA nanosystem as an aptamer‐targeted drug delivery system potential for triple‐negative breast cancer therapy using in vivo mouse model

open access: yesMolecular Oncology, EarlyView.
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat   +8 more
wiley   +1 more source

Block Sampler and Posterior Mode Estimation for A Nonlinear and Non-Gaussian State-Space Model with Correlated Errors [PDF]

open access: yes
This article introduces a new efficient simulation smoother and disturbance smoother for general state-space models where there exists a correlation between error terms of the measurement and state equations.
Toshiaki Watanabe, Yasuhiro Omori
core  

Tumour–host interactions in Drosophila: mechanisms in the tumour micro‐ and macroenvironment

open access: yesMolecular Oncology, EarlyView.
This review examines how tumour–host crosstalk takes place at multiple levels of biological organisation, from local cell competition and immune crosstalk to organism‐wide metabolic and physiological collapse. Here, we integrate findings from Drosophila melanogaster studies that reveal conserved mechanisms through which tumours hijack host systems to ...
José Teles‐Reis, Tor Erik Rusten
wiley   +1 more source

Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models [PDF]

open access: yes
The impact of parameterisation on the simulation efficiency of Bayesian Markov chain Monte Carlo (MCMC) algorithms for two non-Gaussian state space models is examined.
Chris M Strickland   +2 more
core  

Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer

open access: yesMolecular Oncology, EarlyView.
Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson   +9 more
wiley   +1 more source

EDNRB‐dependent endothelin signaling reduces proliferation and promotes proneural‐to‐mesenchymal transition in gliomas

open access: yesMolecular Oncology, EarlyView.
Glioma cells mainly express the endothelin receptor EDNRB, while EDNRA is restricted to a perivascular tumor subpopulation. Endothelin signaling reduces glioma cell proliferation while promoting migration and a proneural‐to‐mesenchymal transition associated with poor prognosis. This pathway activates Ca2+, K+, ERK, and STAT3 signalings and is regulated
Donovan Pineau   +36 more
wiley   +1 more source

A state space model for exponential smoothing with group seasonality [PDF]

open access: yes
We present an approach to improve forecast accuracy by simultaneously forecasting a group of products that exhibit similar seasonal demand patterns. Better seasonality estimates can be made by using information on all products in a group, and using these
Rob J. Hyndman   +3 more
core  

Engineered extracellular vesicles enriched with the miR‐214/199a cluster enhance the efficacy of chemotherapy in ovarian cancer

open access: yesMolecular Oncology, EarlyView.
Loss of the miR‐214/199a cluster is associated with recurrence in ovarian cancer. Engineered small extracellular vesicles (m214‐sEVs) elevate miR‐214‐3p/miR‐199a‐5p in tumor cells, suppress β‐catenin, TLR4, and YKT6 signaling, reprogram tumor‐derived sEV cargo, reduce chemoresistance and migration, and enhance carboplatin efficacy and survival in ...
Weida Wang   +12 more
wiley   +1 more source

Efficient Monte Carlo methods for Bayesian state-space model inference [PDF]

open access: yes
State-space models are widely used to model time series data where the observations depend on a latent process. The latent process consists of a sequence of latent states that evolve according to a specified system process.
Llewellyn, Mary
core   +1 more source

Mixed effect model for absolute log returns of ultra high frequency data [PDF]

open access: yes, 2005
The influence of covariates on absolute log returns of ultra high frequency data is analysed. Therefore we construct a mixed effect model for the absolute log returns. The parameters are estimated in a state space approach.
Haug, Stephan   +3 more
core   +1 more source

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