Search

Cellular reprogramming through targeting microRNAs (miRNAs) holds promise for regenerative therapy due to their profound regulatory effects in proliferation, differentiation, and function. We hypothesized that transdifferentiation of vascular smooth muscle cells (SMCs) into endothelial cells (ECs) using a miRNA cassette may provide a novel approach for use in vascular disease states associated with endothelial injury or dysfunction. miRNA profiling of SMCs and ECs and iterative combinatorial miRNA transfections of human coronary SMCs revealed a 4-miRNA cassette consisting of miR-143-3p and miR-145-5p inhibitors and miR-146a-5p and miR-181b-5p mimics that efficiently produced induced endothelial cells (iECs). Transcriptome profiling, protein expression, and functional studies demonstrated that iECs exhibit high similarity to ECs. Injected iECs restored blood flow recovery even faster than conventional ECs in a murine hindlimb ischemia model. This study demonstrates that a 4-miRNA cassette is sufficient to reprogram SMCs into ECs and shows promise as a novel regenerative strategy for endothelial repair. © 2022 Federation of American Societies for Experimental Biology.

The purpose of the Strategic Workshop in Information Retrieval in Lorne is to explore the long-range issues of the Information Retrieval field, to recognize challenges that are on - or even over - the horizon, to build consensus on some of the key challenges, and to disseminate the resulting information to the research community. The intent is that this description of open problems will help to inspire researchers and graduate students to address the questions, and will provide funding agencies data to focus and coordinate support for information retrieval research.

There is broad consensus in the field of IR that search is complex in many use cases and applications, both on the Web and in domain-specific collections, and both in our professional and in our daily life. Yet our understanding of complex search tasks, in comparison to simple look up tasks, is fragmented at best. The workshop addressed many open research questions: What are the obvious use cases and applications of complex search? What are essential features of work tasks and search tasks to take into account? And how do these evolve over time? With a multitude of information, varying from introductory to specialized, and from authoritative to speculative or opinionated, when should which sources of information be shown? How does the information seeking process evolve and what are relevant differences between different stages? With complex task and search process management, blending searching, browsing, and recommendations, and supporting exploratory search to sensemaking and analytics, UI and UX design pose an overconstrained challenge. How do we know that our approach is any good? Supporting complex search tasks requires new collaborations across the whole field of IR, and the proposed workshop brought together a diverse group of researchers to work together on one of the greatest challenges of our field. The workshop featured three main elements. First, two keynotes, one on the complexity of meaningful interactive IR evaluation by Mark Hall and one on the types of search complexity encountered in real-world applications by Jussi Karlgren. Second, a lively boaster and poster session in which seven contributed papers were presented. Third, three breakout groups discussed concrete ideas on: (1) search context and tasks, (2) search process, and (3) evaluation of complex search tasks. There was an general feeling that the discussion made progress, and built new connections between related strands of research in IR.

A number of recent studies have investigated the relation be-ween URLs and associated query terms from search engine log files. In [5], the query terms associated with the domain of a URL were used as features for a URL classification task. The idea is that query terms that lead to successful classification of a URL are reliable semantic descriptors of the URL content. We follow up on this work by investigating which properties of a URL and its associated query terms predict the classification success. We construct a number of URL and query properties as predictors and proceed to analyze these in-depth. We conclude that the classification success | and thus the reliability of the query terms as URL descriptors | cannot easily be predicted from properties of the URL and the queries.

Explores the possibility of combining the two principles of ranking according to degree of relevance, and ranking according to probability of relevance, for information retrieval systems, but concludes that, while neither is adequate alone, no single, all-embracing ranking principle can be constructed to replace the two. (Author/VT)

A critical survey of approaches to an information concept for information science, with one or more examples of each approach, is discussed in some detail. (VT)

Stephen Robertson retired from the Microsoft Research Lab in Cambridge during the summer of 2013 after a long career as one of the most influential, well-liked and eminent researchers in Information Retrieval throughout the world.

The purpose of an information retrieval (IR) system is to help users accomplish a task. IR system evaluation should consider both task success and the value of support given over the entire information seeking episode. Relevance-based measurements fail to address these requirements. In this paper, usefulness is proposed as a basis for IR evaluation.

Information retrieval (IR) research has reached a point where it is appropriate to assess progress and to define a research agenda for the next five to ten years. This report summarizes a discussion of IR research challenges that took place at a recent workshop. The attendees of the workshop considered information retrieval research in a range of areas chosen to give broad coverage of topic areas that engage information retrieval researchers. Those areas are retrieval models, cross-lingual retrieval, Web search, user modeling, filtering, topic detection and tracking, classification, summarization, question answering, metasearch, distributed retrieval, multimedia retrieval, information extraction, as well as testbed requirements for future work. The potential use of language modeling techniques in these areas was also discussed. The workshop identified major challenges within each of those areas. The following are recurring themes that ran throughout: • User and context sensitive retrieval • Multi-lingual and multi-media issues • Better target tasks • Improved objective evaluations • Substantially more labeled data • Greater variety of data sources • Improved formal models Contextual retrieval and global information access were identified as particularly important long-term challenges.