Results 211 to 220 of about 31,699 (263)
An autologous whole‐tumor‐cell vaccine (rWTC‐MBTA) is evaluated in murine CNS lymphoma. Subcutaneous vaccination activates dendritic cells, broadens T‐cell priming, and drives lymphocyte trafficking to brain tumors, producing durable tumor control. Longitudinal bioluminescence and adoptive‐transfer assays verify CNS engagement. Combination with anti‐PD‐
Yaping Zhang +10 more
wiley +1 more source
This study employs longitudinal fluorescence imaging in transgenic mice to map post‐craniotomy cortical recovery. We identify distinct neuroimmune recovery phases: microglial structural inflammation peaks at ∼10 days, neuronal structural intensity peaks at ∼14 days and correlates with microglial activity, and functional network modularity is most ...
Guihua Xiao +13 more
wiley +1 more source
By integrating single‐nuclei and spatial transcriptomics, this study presents a stereoscopic landscape of maize leaf to Puccinia polysora infection. Epidermal and mesophyll cells initiate primary defenses via RLPs/RLKs and jasmonic acid signaling. Cell‐cell communication analyses further reveal the underlying the dynamics of the underlying immune ...
Qiongqiong Wang +16 more
wiley +1 more source
Single‐Mitochondrion ATP Profiling Directs Discovery of Targetable OXPHOS Dependency in Cancers
MitoATP‐nFCM integrates nano‐flow cytometry with fluorogenic probes (ATP/membrane potential) and antibodies to quantify mitochondrial metabolites and protein expression at single‐organelle resolution, exposing oxidative phosphorylation (OXPHOS)‐driven metabolic rewiring in cancers.
Xu Xiao +7 more
wiley +1 more source
Dimethylsulfoniopropionate (DMSP) is a major marine organosulfur compound central to climate‐relevant dimethyl sulfide (DMS) production. In Halomonas sp. D47, DMSP catabolism is revealed to be coordinated by two transcriptional regulators, AcuR and AcuZ, which control gene expression by sensing DMSP and its metabolites.
Li‐Yuan Zheng +16 more
wiley +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
2011
The interactive tools like blogs, wikis, et cetera, known under the commonly acceptable name Web2.0, led to a new generation of Internet services and applications such as social networks, recommendation systems, reputation systems, et cetera, allowing for public participation in the formation of the content of the Web, and at the same time fueling an ...
Tania Al. Kerkiri, Dimitris Konetas
openaire +2 more sources
The interactive tools like blogs, wikis, et cetera, known under the commonly acceptable name Web2.0, led to a new generation of Internet services and applications such as social networks, recommendation systems, reputation systems, et cetera, allowing for public participation in the formation of the content of the Web, and at the same time fueling an ...
Tania Al. Kerkiri, Dimitris Konetas
openaire +2 more sources
Beyond Collaborative Filtering
Proceedings of the 25th International Conference on World Wide Web, 2016Most Collaborative Filtering (CF) algorithms are optimized using a dataset of isolated user-item tuples. However, in commercial applications recommended items are usually served as an ordered list of several items and not as isolated items. In this setting, inter-item interactions have an effect on the list's Click-Through Rate (CTR) that is ...
Oren Sar Shalom +3 more
openaire +1 more source
Shared collaborative filtering
Proceedings of the fifth ACM conference on Recommender systems, 2011Traditional collaborative filtering (CF) methods suffer from sparse or even cold-start problems, especially for new established recommenders. However, since there are now quite a few recommender systems already existing in good working order, their data should be valuable to the new-start recommenders. This paper proposes shared collaborative filtering
Yu Zhao +3 more
openaire +1 more source
Collaborative competitive filtering
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval, 2011While a user's preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learning recommender models. In particular, existing collaborative filtering (CF) approaches take into account only the binary events of user actions but totally disregard the contexts
Shuang-Hong Yang +4 more
openaire +1 more source
Improving Collaborative Filtering
2021 IV International Conference on Control in Technical Systems (CTS), 2021In this paper, we experiment with a combination of metrics to calculate the similarity when creating collaborative filtering. The Otai Coefficient and Euclidean Distance are used, resulting in a recommender system that produces a satisfactory result.
Jurij A. Morozov +1 more
openaire +1 more source

