Accessory spleen as lead point in intussusception

A 15-year-old boy, who had an episode of abdominal colic 4 years earlier, presented now with a week-long episode of abdominal pain. A computed tomographic scan confirmed the presence of an intussusception. Surprisingly, the surgery identified an accessory spleen as the lead point. At 9 months follow-up, the young boy has had no further abdominal discomfort. This report adds accessory spleen to the list of very rare pathological lead points in intussusception

DeformerNet: Learning Bimanual Manipulation of 3D Deformable Objects

Applications in fields ranging from home care to warehouse fulfillment to surgical assistance require robots to reliably manipulate the shape of 3D deformable objects. Analytic models of elastic, 3D deformable objects require numerous parameters to describe the potentially infinite degrees of freedom present in determining the object's shape. Previous attempts at performing 3D shape control rely on hand-crafted features to represent the object shape and require training of object-specific control models. We overcome these issues through the use of our novel DeformerNet neural network architecture, which operates on a partial-view point cloud of the manipulated object and a point cloud of the goal shape to learn a low-dimensional representation of the object shape. This shape embedding enables the robot to learn a visual servo controller that computes the desired robot end-effector action to iteratively deform the object toward the target shape. We demonstrate both in simulation and on a physical robot that DeformerNet reliably generalizes to object shapes and material stiffness not seen during training. Crucially, using DeformerNet, the robot successfully accomplishes three surgical sub-tasks: retraction (moving tissue aside to access a site underneath it), tissue wrapping (a sub-task in procedures like aortic stent placements), and connecting two tubular pieces of tissue (a sub-task in anastomosis).Comment: Submitted to IEEE Transactions on Robotics (T-RO). 18 pages, 25 figures. arXiv admin note: substantial text overlap with arXiv:2110.0468

A validation study of a smartphone application for functional mobility assessment of the elderly

Background: To minimize the reaction time and position judgment error using stopwatch-timed measures, we developed a smartphone application to measure performance in the five-time sit-to-stand (FTSTS) and timed up-and-go (TUG) tests. Objective: This study aimed to validate this smartphone application by comparing its measurement with a laboratory-based reference condition. Methods: Thirty-two healthy elderly people were asked to perform the FTSTS and TUG tests in a randomized sequence. During the tests, their performance was concurrently measured by the smartphone application and a force sensor installed in the backrest of a chair. The intraclass correlation coefficient [ICC(2,1)] and Blande-Altman analysis were used to calculate the measurement consistency and agreement, respectively, between these two methods. Results: The smartphone application demonstrated excellent measurement consistency with the lab-based reference condition for the FTSTS test [ICC(2,1) = 0.988] and TUG test [ICC(2,1) = 0.946]. We observed a positive bias of 0.27 seconds (95% limits of agreement, -1.22 to 1.76 seconds) for the FTSTS test and 0.48 seconds (95% limits of agreement, -1.66 to 2.63 seconds) for the TUG test. Conclusion: We cross-validated the newly developed smartphone application with the laboratory-based reference condition during the examination of FTSTS and TUG test performance in healthy elderly

Validation and reliability of the Physical Activity Scale for the Elderly in Chinese population

Objectives: Physical Activity Scale for the Elderly (PASE) is a widely used questionnaire in epidemiological studies for assessing the physical activity level of elderly. This study aims to translate and validate PASE in Chinese population. Design: Cross-sectional study. Subjects: Chinese elderly aged 65 or above. Methods: The original English version of PASE was translated into Chinese (PASE-C) following standardized translation procedures. Ninety Chinese elderly aged 65 or above were recruited in the community. Test-retest reliability was determined by comparing the scores obtained from two separate administrations by the intraclass correlation coefficient. Validity was evaluated by Spearman’s rank correlation coefficients between PASE and Medical Outcome Survey 36-Item Short Form Health Survey (SF-36), grip strength, single-leg-stance, 5 times sit-to-stand and 10-m walk. Results: PASE-C demonstrated good test-retest reliability (intraclass correlation coefficient  =0.81). Fair to moderate association were found between PASE-C and most of the subscales of SF-36 (rs=0.285 to 0.578, p<0.01), grip strength (rs=0.405 to 0.426, p<0.001), single-leg-stance (rs =0.470 to 0.548, p<0.001), 5 times sit-to-stand (rs =–0.33, p=0.001) and 10-m walk (rs =–0.281, p=0.007). Conclusion: PASE-C is a reliable and valid instrument for assessing the physical activity level of elderly in Chinese population

Mast cell stabilization alleviates acute lung injury after orthotopic autologous liver transplantation in rats by downregulating inflammation

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Antioxidant N-acetylcysteine attenuates the reduction of brg1 protein expression in the myocardium of type 1 diabetic rats

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Walking with head-mounted virtual and augmented reality devices : effects on position control and gait biomechanics

What was once a science fiction fantasy, virtual reality (VR) technology has evolved and come a long way. Together with augmented reality (AR) technology, these simulations of an alternative environment have been incorporated into rehabilitation treatments. The introduction of head-mounted displays has made VR/AR devices more intuitive and compact, and no longer limited to upper-limb rehabilitation. However, there is still limited evidence supporting the use of VR and AR technology during locomotion, especially regarding the safety and efficacy relating to walking biomechanics. Therefore, the objective of this study is to explore the limitations of such technology through gait analysis. In this study, thirteen participants walked on a treadmill in normal, virtual and augmented versions of the laboratory environment. A series of spatiotemporal parameters and lower-limb joint angles were compared between conditions. The center of pressure (CoP) ellipse area (95% confidence ellipse) was significantly different between conditions (p = 0.002). Pairwise comparisons indicated a significantly greater CoP ellipse area for both the AR (p = 0.002) and VR (p = 0.005) conditions when compared to the normal laboratory condition. Furthermore, there was a significant difference in stride length (p0.082), except for maximum ankle plantarflexion (p = 0.001). These differences in CoP ellipse area indicate that users of head-mounted VR/AR devices had difficulty maintaining a stable position on the treadmill. Also, differences in the gait parameters suggest that users walked with an unusual gait pattern which could potentially affect the effectiveness of gait rehabilitation treatments. Based on these results, position guidance in the form of feedback and the use of specialized treadmills should be considered when using head-mounted VR/AR devices