. High-intensity repetitive training is challenging to provide poststroke. Robotic approaches can facilitate such training by unweighting the limb and/or by improving trajectory control, but the extent to which these types of assistance are necessary is not known. . The purpose of this study was to examine the extent to which robotic path assistance and/or weight support facilitate repetitive 3D movements in high functioning and low functioning subjects with poststroke arm motor impairment relative to healthy controls. . Seven healthy controls and 18 subjects with chronic poststroke right-sided hemiparesis performed 300 repetitions of a 3D circle-drawing task using a 3D Cable-driven Arm Exoskeleton (CAREX) robot. Subjects performed 100 repetitions each with path assistance alone, weight support alone, and path assistance plus weight support in a random order over a single session. Kinematic data from the task were used to compute the normalized error and speed as well as the speed-error relationship. . Low functioning stroke subjects (Fugl-Meyer Scale score = 16.6 ± 6.5) showed the lowest error with path assistance plus weight support, whereas high functioning stroke subjects (Fugl-Meyer Scale score = 59.6 ± 6.8) moved faster with path assistance alone. When both speed and error were considered together, low functioning subjects significantly reduced their error and increased their speed but showed no difference across the robotic conditions. . Robotic assistance can facilitate repetitive task performance in individuals with severe arm motor impairment, but path assistance provides little advantage over weight support alone. Future studies focusing on antigravity arm movement control are warranted poststroke.
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Sensors (Basel)
December 2024
Guangxi Key Laboratory of Machine Vision and Intelligent Control, Wuzhou University, Wuzhou 543000, China.
A high-quality optical path alignment is essential for achieving superior image quality in optical biological microscope (OBM) systems. The traditional automatic alignment methods for OBMs rely heavily on complex masker-detection techniques. This paper introduces an innovative, image-sensor-based optical path alignment approach designed for low-power objective (specifically 4×) automatic OBMs.
View Article and Find Full Text PDFHum Reprod
January 2025
IRSD, Université de Toulouse, INSERM, INRAE, ENVT, Univ Toulouse III-Paul Sabatier (UPS), Toulouse, France.
Study Question: Does a human fallopian tube (HFT) organoid model offer a favourable apical environment for human sperm survival and motility?
Summary Answer: After differentiation, the apical compartment of a new HFT organoid model provides a favourable environment for sperm motility, which is better than commercial media.
What Is Known Already: HFTs are the site of major events that are crucial for achieving an ongoing pregnancy, such as gamete survival and competence, fertilization steps, and preimplantation embryo development. In order to better understand the tubal physiology and tubal factors involved in these reproductive functions, and to improve still suboptimal in vitro conditions for gamete preparation and embryo culture during IVF, we sought to develop an HFT organoid model from isolated adult stem cells to allow spermatozoa co-culture in the apical compartment.
Mol Genet Metab
December 2024
Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA; Texas Children's Hospital, Houston, TX, USA; BCM-CUHK Center of Medical Genetics, Prince of Wales Hospital, Hong Kong, China.
The 3-methylglutaconic aciduria (3-MGA-uria) syndromes comprise a heterogeneous group of inborn errors of metabolism defined biochemically by detectable elevation of 3-methylglutaconic acid (3-MGA) in the urine. In type 1 (or primary) 3-MGA-uria, distal defects in the leucine catabolism pathway directly cause this elevation. Secondary 3-MGA-uria syndromes, however, are unrelated to leucine metabolism-specific defects but share a common biochemical phenotype of elevated 3-MGA.
View Article and Find Full Text PDFMed Teach
January 2025
Department of Medical Education, Dartmouth College Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
Health Professions Education (HPE) assessment is being increasingly impacted by Artificial Intelligence (AI), and institutions, educators, and learners are grappling with AI's ever-evolving complexities, dangers, and potential. This AMEE Guide aims to assist all HPE stakeholders by helping them navigate the assessment uncertainty before them. Although the impetus is AI, the Guide grounds its path in pedagogical theory, considers the range of human responses, and then deals with assessment types, challenges, AI roles as tutor and learner, and required competencies.
View Article and Find Full Text PDFF S Rep
December 2024
Northwell, New Hyde Park, New York.
Devices that function within a network of interconnected systems and are equipped with sensors, software, and tools designed to collect and exchange data are widely known as the Internet of Things (IoT). In recent years, the rapid growth of IoT technology has sparked significant interest in leveraging these systems to enhance healthcare delivery across various medical fields, including fertility care and assisted reproductive technology. The subset of IoT devices applied within the healthcare sector is referred to as the Internet of Medical Things (IoMT).
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