Prediction of setup times for an advanced upper limb functional electrical stimulation system

Introduction: Rehabilitation devices take time to don, and longer or unpredictable setup time impacts on usage. This paper reports on the development of a model to predict setup time for upper limb functional electrical stimulation. Methods: Participants’ level of impairment (Fugl Meyer-Upper Extremity Scale), function (Action Research Arm Test) and mental status (Mini Mental Scale) were measured. Setup times for each stage of the setup process and total setup times were recorded. A predictive model of setup time was devised using upper limb impairment and task complexity. Results: Six participants with stroke were recruited, mean age 60 (�17) years and mean time since stroke 9.8 (�9.6) years. Mean Fugl Meyer-Upper Extremity score was 31.1 (�6), Action Research Arm Test 10.4 (�7.9) and Mini Mental Scale 26.1 (�2.7). Linear regression analysis showed that upper limb impairment and task complexity most effectively predicted setup time (51% as compared with 39%) (F(2,21) ¼ 12.782, adjusted R2 ¼ 0.506; p<.05). Conclusions: A model to predict setup time based on upper limb impairment and task complexity accounted for 51% of the variation in setup time. Further studies are required to test the model in real-world settings and to identify other contributing factors

Cross-tissue immune cell analysis reveals tissue-specific adaptations and clonal architecture in humans

Despite their crucial role in health and disease, our knowledge of immune cells within human tissues remains limited. Here, we surveyed the immune compartment of 15 tissues of six deceased adult donors by single-cell RNA sequencing and paired VDJ sequencing. To systematically resolve immune cell heterogeneity across tissues, we developed CellTypist, a machine learning tool for rapid and precise cell type annotation. Using this approach, combined with detailed curation, we determined the tissue distribution of 45 finely phenotyped immune cell types and states, revealing hitherto unappreciated tissue-specific features and clonal architecture of T and B cells. In summary, our multi-tissue approach lays the foundation for identifying highly resolved immune cell types by leveraging a common reference dataset, tissue-integrated expression analysis and antigen receptor sequencing. One Sentence Summary We provide an immune cell atlas, including antigen receptor repertoire profiling, across lymphoid and non-lymphoid human tissues

Use of DNA–Damaging Agents and RNA Pooling to Assess Expression Profiles Associated with BRCA1 and BRCA2 Mutation Status in Familial Breast Cancer Patients

A large number of rare sequence variants of unknown clinical significance have been identified in the breast cancer susceptibility genes, BRCA1 and BRCA2. Laboratory-based methods that can distinguish between carriers of pathogenic mutations and non-carriers are likely to have utility for the classification of these sequence variants. To identify predictors of pathogenic mutation status in familial breast cancer patients, we explored the use of gene expression arrays to assess the effect of two DNA–damaging agents (irradiation and mitomycin C) on cellular response in relation to BRCA1 and BRCA2 mutation status. A range of regimes was used to treat 27 lymphoblastoid cell-lines (LCLs) derived from affected women in high-risk breast cancer families (nine BRCA1, nine BRCA2, and nine non-BRCA1/2 or BRCAX individuals) and nine LCLs from healthy individuals. Using an RNA–pooling strategy, we found that treating LCLs with 1.2 µM mitomycin C and measuring the gene expression profiles 1 hour post-treatment had the greatest potential to discriminate BRCA1, BRCA2, and BRCAX mutation status. A classifier was built using the expression profile of nine QRT–PCR validated genes that were associated with BRCA1, BRCA2, and BRCAX status in RNA pools. These nine genes could distinguish BRCA1 from BRCA2 carriers with 83% accuracy in individual samples, but three-way analysis for BRCA1, BRCA2, and BRCAX had a maximum of 59% prediction accuracy. Our results suggest that, compared to BRCA1 and BRCA2 mutation carriers, non-BRCA1/2 (BRCAX) individuals are genetically heterogeneous. This study also demonstrates the effectiveness of RNA pools to compare the expression profiles of cell-lines from BRCA1, BRCA2, and BRCAX cases after treatment with irradiation and mitomycin C as a method to prioritize treatment regimes for detailed downstream expression analysis

DNA Repair in Human Pluripotent Stem Cells Is Distinct from That in Non-Pluripotent Human Cells

The potential for human disease treatment using human pluripotent stem cells, including embryonic stem cells and induced pluripotent stem cells (iPSCs), also carries the risk of added genomic instability. Genomic instability is most often linked to DNA repair deficiencies, which indicates that screening/characterization of possible repair deficiencies in pluripotent human stem cells should be a necessary step prior to their clinical and research use. In this study, a comparison of DNA repair pathways in pluripotent cells, as compared to those in non-pluripotent cells, demonstrated that DNA repair capacities of pluripotent cell lines were more heterogeneous than those of differentiated lines examined and were generally greater. Although pluripotent cells had high DNA repair capacities for nucleotide excision repair, we show that ultraviolet radiation at low fluxes induced an apoptotic response in these cells, while differentiated cells lacked response to this stimulus, and note that pluripotent cells had a similar apoptotic response to alkylating agent damage. This sensitivity of pluripotent cells to damage is notable since viable pluripotent cells exhibit less ultraviolet light-induced DNA damage than do differentiated cells that receive the same flux. In addition, the importance of screening pluripotent cells for DNA repair defects was highlighted by an iPSC line that demonstrated a normal spectral karyotype, but showed both microsatellite instability and reduced DNA repair capacities in three out of four DNA repair pathways examined. Together, these results demonstrate a need to evaluate DNA repair capacities in pluripotent cell lines, in order to characterize their genomic stability, prior to their pre-clinical and clinical use

Cross-tissue immune cell analysis reveals tissue-specific features in humans.

Despite their crucial role in health and disease, our knowledge of immune cells within human tissues remains limited. We surveyed the immune compartment of 16 tissues from 12 adult donors by single-cell RNA sequencing and VDJ sequencing generating a dataset of ~360,000 cells. To systematically resolve immune cell heterogeneity across tissues, we developed CellTypist, a machine learning tool for rapid and precise cell type annotation. Using this approach, combined with detailed curation, we determined the tissue distribution of finely phenotyped immune cell types, revealing hitherto unappreciated tissue-specific features and clonal architecture of T and B cells. Our multitissue approach lays the foundation for identifying highly resolved immune cell types by leveraging a common reference dataset, tissue-integrated expression analysis, and antigen receptor sequencing.CZI NIH grant ERC grant (Thdefine