Cells receive important regulatory signals from their extracellular matrix (ECM) and the physical property of the ECM regulates important cellular behaviors like cell proliferation, migration and differentiation. A large part of tissue formation and regeneration depends on cellular interaction with its ECM. A comprehensive understanding of the mechanistic biochemical pathway of the ECM components is necessary for the design of a biomaterial scaffold for tissue engineering. Depending on the type of tissue, the ECM requirement might be different and this would influence its downstream intracellular cell signaling. Here, we reviewed the ECM and its signaling pathway by discussing: 1) classification of the ECM into hard, elastic and soft tissue based on its physical properties, 2) proliferation and differentiation control of the ECM, 3) roles of membrane receptor and its intracellular regulation factor, 4) ECM remodeling via inside-out signaling. By providing a comprehensive overview of the ECM's role in mechanotransduction and the self-regulatory effect of cells back on the ECM, we hope to provide a better insight of the physical and biochemical cues from the ECM. A sound understanding on the in vivo ECM has implication on the choice of materials and surface coating of biomimetic scaffolds used for tissue regeneration and therapeutics in a cell-free scaffold.

BACKGROUND Dementia, which presents as cognitive decline in one or more cognitive domains affecting function, is becoming more prevalent. Traditional cognitive screening tools for dementia have their limitations, with emphasis on memory and to a lesser extent on the cognitive domain of executive function. The use of virtual reality (VR) in screening for cognitive function in older person is promising but evidence for its use is sparse. OBJECTIVE The primary aim is to examine the feasibility and acceptability of using VR to screen for cognitive impairment in older person in a primary care setting, through a VR module. The secondary aim is to assess the module’s ability to discriminate between cognitively normal and cognitively impaired participants. METHODS A comparative study was conducted at a public primary care clinic in Singapore, where 60 older persons were recruited based on a cut-off score of 26 using the Montreal Cognitive Assessment (MoCA) scale. They participated in the VR module to assess their learning and memory, perceptual-motor function and executive function. Each participant was evaluated by a total performance score (range: 0 – 700) upon completion. An assisted questionnaire was also administered to assess their perception of and attitude towards VR. RESULTS 37 participants in Group 1 (cognitively normal; MoCA >= 26) and 23 participants in Group 2 (cognitively impaired; MoCA < 26) were assessed. All participants completed the study with a mean total time of 19.1±3.6 minutes in Group 1 and 20.4±3.4 minutes in Group 2. Mean feedback scores ranged from 3.80 to 4.48 (max=5) in favour of VR. The total performance score in Group 1 (552.0±57.2) was higher than in Group 2 (476.1±61.9) (P < .001), and exhibited moderate positive correlation with scores from other cognitive screening tools: Abbreviated Mental Test (AMT) (0.312), Mini-Mental State Examination (MMSE) (0.373) and MoCA (0.427). A ROC curve analysis, relating total performance score to the presence of cognitive impairment, showed an area under curve of 0.821 (95% confidence interval: 0.714 to 0.928). CONCLUSIONS We demonstrated the feasibility of using an VR-based screening tool for cognitive function in older persons in primary care, who were largely in favour of this tool.