Development and evaluation of the environment and communication assessment toolkit with speech-language pathologists.

Communication dysfunction that results from dementia can be exacerbated by environmental barriers such as inadequate lighting, noisy conditions, poor or absent environmental cues, and visual clutter. Speech-language pathologists (SLPs) should address these environmental barriers as part of a comprehensive treatment plan for clients with dementia. The Environment and Communication Assessment Toolkit for Dementia Care (ECAT) was evaluated by SLPs to determine: (1) changes in awareness of environmental factors prior to and after training; (2) impact of the ECAT on practice as measured by changes in the number of environmental modifications recommended and made prior to and after training; (3) utility of the information as measured by the helpfulness, amount of new information, and usefulness of the ECAT; and (4) usability of the ECAT materials based on ease of use. The SLPs used the ECAT with clients with dementia who had functional limitations and required substantial assistance with daily activities. Results indicate that the ECAT is an effective tool for SLPs, providing information about the impact of the environment on communication and supplying sufficient resources to make recommendations and implement effective interventions. The ECAT successfully increased awareness of environmental modifications, influenced the practice of recommending environmental modifications, and had utility in diverse aspects of clinical practice.

The secreted protein discovery initiative (SPDI), a large-scale effort to identify novel human secreted and transmembrane proteins: a bioinformatics assessment.

A large-scale effort, termed the Secreted Protein Discovery Initiative (SPDI), was undertaken to identify novel secreted and transmembrane proteins. In the first of several approaches, a biological signal sequence trap in yeast cells was utilized to identify cDNA clones encoding putative secreted proteins. A second strategy utilized various algorithms that recognize features such as the hydrophobic properties of signal sequences to identify putative proteins encoded by expressed sequence tags (ESTs) from human cDNA libraries. A third approach surveyed ESTs for protein sequence similarity to a set of known receptors and their ligands with the BLAST algorithm. Finally, both signal-sequence prediction algorithms and BLAST were used to identify single exons of potential genes from within human genomic sequence. The isolation of full-length cDNA clones for each of these candidate genes resulted in the identification of >1000 novel proteins. A total of 256 of these cDNAs are still novel, including variants and novel genes, per the most recent GenBank release version. The success of this large-scale effort was assessed by a bioinformatics analysis of the proteins through predictions of protein domains, subcellular localizations, and possible functional roles. The SPDI collection should facilitate efforts to better understand intercellular communication, may lead to new understandings of human diseases, and provides potential opportunities for the development of therapeutics.