The Effect of Inspiratory Muscle Training on the Thoracic Spine Curve, Inspiratory Volume and Cardio-Respiratory Endurance in Boys with Hyper-kyphosis

Background: Hyper-kyphosis is one of the most common malalignments in adolescent boys and can affect their breathing. Inspiratory muscle training (IMT) may improve the function of the respiratory muscles in adolescents and may influence their skeletal structure as well. So, this study aimed to examine the effects of inspiratory muscle training on the thoracic spine curve, Inspiratory Volume and Cardio-Respiratory Endurance in Hyperkyphotic Boys Methods: This study was a semi experimentally in design, pre and post-test design with a control group. Twenty-two 12-15 boys, with thoracic spine curve more than 49 degrees were randomly divided into control and experimental groups. Both groups performed the same corrective exercise for hyper-kyphosis, the experimental group also performed inspiratory muscle training five days a week using the power breathing device, based on the training protocol. Both groups were evaluated before and after 12 weeks of training in terms of the thoracic spine curve, inspiratory volume, S-index, PIF, and cardio-respiratory endurance. Results: The data analysis showed that the thoracic spine curve decreased significantly in the IMT group (Pvalue=0.025). The IMT group showed significantly increase in inspiratory S-index (T=4.058, Pvalue=0.002), PIF (T=4.06, Pvalue=0.002) and cardio-respiratory endurance (T=2.62, Pvalue=0.050) at posttest in compare to control group. Conclusions: Based on the study findings, it can be concluded that respiratory muscle strengthening alone may not be by itself sufficient for the improvement of Hyper-kyphosis, and corrective exercises can also be recommended along with it. Keywords: Inspiratory Muscle training, Hyper-kyphosis, inspiratory volume, Cardio-respiratory endurance

Molecular and metabolomic characterization of hiPSC-derived cardiac fibroblasts transitioning to myofibroblasts

BackgroundMechanical stress and pathological signaling trigger the activation of fibroblasts to myofibroblasts, which impacts extracellular matrix composition, disrupts normal wound healing, and can generate deleterious fibrosis. Myocardial fibrosis independently promotes cardiac arrhythmias, sudden cardiac arrest, and contributes to the severity of heart failure. Fibrosis can also alter cell-to-cell communication and increase myocardial stiffness which eventually may lead to lusitropic and inotropic cardiac dysfunction. Human induced pluripotent stem cell derived cardiac fibroblasts (hiPSC-CFs) have the potential to enhance clinical relevance in precision disease modeling by facilitating the study of patient-specific phenotypes. However, it is unclear whether hiPSC-CFs can be activated to become myofibroblasts akin to primary cells, and the key signaling mechanisms in this process remain unidentified.ObjectiveWe aim to explore the notable changes in fibroblast phenotype upon passage-mediated activation of hiPSC-CFs with increased mitochondrial metabolism, like primary cardiac fibroblasts.MethodsWe activated the hiPSC-CFs with serial passaging from passage 0 to 3 (P0 to P3) and treatment of P0 with TGFβ1.ResultsPassage-mediated activation of hiPSC-CFs was associated with a gradual induction of genes to initiate the activation of these cells to myofibroblasts, including collagen, periostin, fibronectin, and collagen fiber processing enzymes with concomitant downregulation of cellular proliferation markers. Most importantly, canonical TGFβ1 and Hippo signaling component genes including TAZ were influenced by passaging hiPSC-CFs. Seahorse assay revealed that passaging and TGFβ1 treatment increased mitochondrial respiration, consistent with fibroblast activation requiring increased energy production, whereas treatment with the glutaminolysis inhibitor BPTES completely attenuated this process.ConclusionOur study highlights that the hiPSC-CF passaging enhanced fibroblast activation, activated fibrotic signaling pathways, and enhanced mitochondrial metabolism approximating what has been reported in primary cardiac fibroblasts. Thus, hiPSC-CFs may provide an accurate in vitro preclinical model for the cardiac fibrotic condition, which may facilitate the identification of putative anti-fibrotic therapies, including patient-specific approaches

Automated Planning of Concrete Joint Layouts with 4D-BIM

Concrete pouring represents a major critical path activity that is often affected by design limitations, structural considerations and on-site operational constraints. As such, meticulous planning is required to ensure that both the aesthetic and structural integrity of joints between cast in-situ components is achieved. Failure to adequately plan concrete pouring could lead to structural defects, construction rework or structural instability, all having major financial implications. Given the inherent complexity of large-scale construction projects, the ‘manual planning’ of concrete pouring is a challenging task and prone to human errors. Against this backdrop, this study developed 4D Building Information Management (BIM) approach to facilitate automated concrete joint positioning solution (as a proof of concept) for design professionals and contractors. The study first developed structural model in Revit, then extracted spatial information regarding all construction joints and linked them to dynamic Microsoft (MS) Excel and Matlab spreadsheets using integration facilitated by Dynamo software. Midspan points of each beam as well as floor perimeter information were gathered via codes developed in MS Excel macros. Based on the Excel outputs, Matlab programming was used to determine best concreating starting points and directions, and daily allowed concrete volume, considering limitations due to cold joints. These information were then pushed back to Revit via Dynamo in order to develop daily concrete scheduling. The developed automated programme framework offers a cost-effective and accurate methodology to address the limitations and inefficiencies of traditional methods of designing construction joints and planning pours. This framework extends the body of knowledge by introducing innovative solutions to integrate structural design considerations, constructional procedures and operational aspects for mitigating human error, and providing a novel, yet technically sound, basis for further application of BIM in structural engineering

InPRO: Automated Indoor Construction Progress Monitoring Using Unmanned Aerial Vehicles

In this research, an envisioned automated intelligent robotic solution for automated indoor data collection and inspection that employs a series of unmanned aerial vehicles (UAV), entitled â InPROâ , is presented. InPRO consists of four stages, namely: 1) automated path planning; 2) autonomous UAV-based indoor inspection; 3) automated computer vision-based assessment of progress; and, 4) automated updating of 4D building information models (BIM). The works presented in this thesis address the third stage of InPRO. A series of computer vision-based methods that automate the assessment of construction progress using images captured at indoor sites are introduced. The proposed methods employ computer vision and machine learning techniques to detect the components of under-construction indoor partitions. In particular, framing (studs), insulation, electrical outlets, and different states of drywall sheets (installing, plastering, and painting) are automatically detected using digital images. High accuracy rates, real-time performance, and operation without a priori information are indicators of the methodsâ promising performance.M.A.S

InPRO: Automated Indoor Construction Progress Monitoring Using Unmanned Aerial Vehicles

In this research, an envisioned automated intelligent robotic solution for automated indoor data collection and inspection that employs a series of unmanned aerial vehicles (UAV), entitled â InPROâ , is presented. InPRO consists of four stages, namely: 1) automated path planning; 2) autonomous UAV-based indoor inspection; 3) automated computer vision-based assessment of progress; and, 4) automated updating of 4D building information models (BIM). The works presented in this thesis address the third stage of InPRO. A series of computer vision-based methods that automate the assessment of construction progress using images captured at indoor sites are introduced. The proposed methods employ computer vision and machine learning techniques to detect the components of under-construction indoor partitions. In particular, framing (studs), insulation, electrical outlets, and different states of drywall sheets (installing, plastering, and painting) are automatically detected using digital images. High accuracy rates, real-time performance, and operation without a priori information are indicators of the methodsâ promising performance.M.A.S