Smart Sensing Chairs for Sitting Posture Detection, Classification, and Monitoring: A Comprehensive Review

Incorrect sitting posture, characterized by asymmetrical or uneven positioning of the body, often leads to spinal misalignment and muscle tone imbalance. The prolonged maintenance of such postures can adversely impact well-being and contribute to the development of spinal deformities and musculoskeletal disorders. In response, smart sensing chairs equipped with cutting-edge sensor technologies have been introduced as a viable solution for the real-time detection, classification, and monitoring of sitting postures, aiming to mitigate the risk of musculoskeletal disorders and promote overall health. This comprehensive literature review evaluates the current body of research on smart sensing chairs, with a specific focus on the strategies used for posture detection and classification and the effectiveness of different sensor technologies. A meticulous search across MDPI, IEEE, Google Scholar, Scopus, and PubMed databases yielded 39 pertinent studies that utilized non-invasive methods for posture monitoring. The analysis revealed that Force Sensing Resistors (FSRs) are the predominant sensors utilized for posture detection, whereas Convolutional Neural Networks (CNNs) and Artificial Neural Networks (ANNs) are the leading machine learning models for posture classification. However, it was observed that CNNs and ANNs do not outperform traditional statistical models in terms of classification accuracy due to the constrained size and lack of diversity within training datasets. These datasets often fail to comprehensively represent the array of human body shapes and musculoskeletal configurations. Moreover, this review identifies a significant gap in the evaluation of user feedback mechanisms, essential for alerting users to their sitting posture and facilitating corrective adjustments

Mutations in mitochondrial enzyme GPT2 cause metabolic dysfunction and neurological disease with developmental and progressive features

Mutations that cause neurological phenotypes are highly informative with regard to mechanisms governing human brain function and disease. We report autosomal recessive mutations in the enzyme glutamate pyruvate transaminase 2 (GPT2) in large kindreds initially ascertained for intellectual and developmental disability (IDD). GPT2 [also known as alanine transaminase 2 (ALT2)] is one of two related transaminases that catalyze the reversible addition of an amino group from glutamate to pyruvate, yielding alanine and α-ketoglutarate. In addition to IDD, all affected individuals show postnatal microcephaly and ∼80% of those followed over time show progressive motor symptoms, a spastic paraplegia. Homozygous nonsense p.Arg404* and missense p.Pro272Leu mutations are shown biochemically to be loss of function. The GPT2 gene demonstrates increasing expression in brain in the early postnatal period, and GPT2 protein localizes to mitochondria. Akin to the human phenotype, Gpt2-null mice exhibit reduced brain growth. Through metabolomics and direct isotope tracing experiments, we find a number of metabolic abnormalities associated with loss of Gpt2. These include defects in amino acid metabolism such as low alanine levels and elevated essential amino acids. Also, we find defects in anaplerosis, the metabolic process involved in replenishing TCA cycle intermediates. Finally, mutant brains demonstrate misregulated metabolites in pathways implicated in neuroprotective mechanisms previously associated with neurodegenerative disorders. Overall, our data reveal an important role for the GPT2 enzyme in mitochondrial metabolism with relevance to developmental as well as potentially to neurodegenerative mechanisms.National Institute of Neurological Diseases and Stroke (U.S.) (R01NS035129)United States. National Institutes of Health (R21TW008223)National Cancer Institute (U.S.) (R01CA157996

Refined HLA-DPB1 mismatch with molecular algorithms predicts outcomes in hematopoietic stem cell transplantation

HLA-DPB1 mismatches between donor and recipient are commonly seen in allogeneic hematopoietic stem cell transplantation from an unrelated donor. HLA-DPB1 mismatch, conventionally determined by the similarity of the T-cell epitope (TCE), is associated with an increased risk of acute graft-versus-host disease (GVHD) and a decreased risk of disease relapse. We investigated the clinical impact of HLA-DPB1 molecular mismatch quantified by mismatched eplets (ME) and the Predicted Indirectly Recognizable HLA Epitopes Score (PS) in a cohort of 1,514 patients receiving hematopoietic stem cell transplants from unrelated donors matched at HLA-A, -B, -C, -DRB1/3/4/5, and - DQB1 loci. HLA-DPB1 alloimmunity in the graft-versus-host direction, determined by high graft-versus-host ME/PS, was associated with a reduced risk of relapse (hazard ratio [HR]=0.83, P=0.05 for ME) and increased risk of grade 2-4 acute GVHD (HR=1.44, P<0.001 for ME), whereas high host-versus-graft ME/PS was only associated with an increased risk of grade 2-4 acute GVHD (HR=1.26, P=0.004 for ME). Notably, in the permissive mismatch subgroup classified by TCE grouping, high host-versus-graft ME/PS was associated with an increased risk of relapse (HR=1.36, P=0.026 for ME) and grade 2-4 acute GVHD (HR=1.43, P=0.003 for PS-II). Decision curve analysis showed that graftversus- host ME outperformed other models and provided the best clinical net benefit for the modification of acute GVHD prophylaxis regimens in patients with a high risk of developing clinically significant acute GVHD. In conclusion, molecular assessment of HLA-DPB1 mismatch enables separate prediction of host-versus-graft or graft-versus-host alloresponse quantitatively and allows further refinement of HLA-DPB1 permissiveness as defined by conventional TCE grouping

Concise review:workshop review: understanding and assessing the risks of stem cell-based therapies

The field of stem cell therapeutics is moving ever closer to widespread application in the clinic. However, despite the undoubted potential held by these therapies, the balance between risk and benefit remains difficult to predict. As in any new field, a lack of previous application in man and gaps in the underlying science mean that regulators and investigators continue to look for a balance between minimizing potential risk and ensuring therapies are not needlessly kept from patients. Here, we attempt to identify the important safety issues, assessing the current advances in scientific knowledge and how they may translate to clinical therapeutic strategies in the identification and management of these risks. We also investigate the tools and techniques currently available to researchers during preclinical and clinical development of stem cell products, their utility and limitations, and how these tools may be strategically used in the development of these therapies. We conclude that ensuring safety through cutting-edge science and robust assays, coupled with regular and open discussions between regulators and academic/industrial investigators, is likely to prove the most fruitful route to ensuring the safest possible development of new product