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Background: The present study aimed to validate a recently proposed algorithm for assistance titration during proportional assist ventilation with load-adjustable gain factors, based on a noninvasive estimation of maximum inspiratory pressure (peak P) and inspiratory effort (pressure-time product [PTP] peak P).
Methods: Retrospective analysis of the recordings obtained from 26 subjects ventilated on proportional assist ventilation with load-adjustable gain factors under different conditions, each considered as an experimental case. The estimated inspiratory output (peak P) and effort (PTP-peak P) were compared with the actual-determined by the measurement of transdiaphragmatic pressure- and the derived PTP. Validation of the algorithm was performed by assessing the accuracy of peak P in predicting the actual inspiratory muscle effort and indicating the appropriate level of assist.
Results: In the 63 experimental cases analyzed, a limited agreement was observed between the estimated and the actual inspiratory muscle pressure (-11 to 10 cm HO) and effort (-82 to 125 cm HO × s/min). The sensitivity and specificity of peak P to predict the range of the actual inspiratory effort was 81.2% and 58.1%, respectively. In 49% of experimental cases, the level of assist indicated by the algorithm differed from that indicated by the transdiaphragmatic pressure and PTP.
Conclusions: The proposed algorithm had limited accuracy in estimating inspiratory muscle effort and with indicating the appropriate level of assist.
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http://dx.doi.org/10.4187/respcare.06988 | DOI Listing |
Biol Cybern
September 2025
Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign, 61801, IL, USA.
In this article, a biophysically realistic model of a soft octopus arm with internal musculature is presented. The modeling is motivated by experimental observations of sensorimotor control where an arm localizes and reaches a target. Major contributions of this article are: (i) development of models to capture the mechanical properties of arm musculature, the electrical properties of the arm peripheral nervous system (PNS), and the coupling of PNS with muscular contractions; (ii) modeling the arm sensory system, including chemosensing and proprioception; and (iii) algorithms for sensorimotor control, which include a novel feedback neural motor control law for mimicking target-oriented arm reaching motions, and a novel consensus algorithm for solving sensing problems such as locating a food source from local chemical sensory information (exogenous) and arm deformation information (endogenous).
View Article and Find Full Text PDFJ Am Acad Orthop Surg Glob Res Rev
September 2025
From the Harvard Medical School, Boston, MA (Gabriel, Hines, and Prabhat); the Lenox Hill Hospital, New York, NY (Dr. Ang); and the Boston Children's Hospital, Department of Orthopedic Surgery, Boston, MA (Dr. Liu and Dr. Hogue).
Purpose: The purpose of this study was to develop a comprehensive step-wise management algorithm for Bertolotti syndrome in the pediatric population by conducting a systematic review of the current literature regarding the diagnostic evaluation, nonsurgical and surgical treatment, and outcomes.
Methods: A systematic review of the literature was conducted using PubMed to identify studies focused on the management of Bertolotti syndrome in the pediatric population. Data extraction of clinical presentation, management strategies, imaging, and outcomes was completed.
Radiology
September 2025
Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, MA 02115.
Despite the rapid growth of Food and Drug Administration-cleared artificial intelligence (AI)- and machine learning-enabled medical devices for use in radiology, current tools remain limited in scope, often focusing on narrow tasks and lacking the ability to comprehensively assist radiologists. These narrow AI solutions face limitations in financial sustainability, operational efficiency, and clinical utility, hindering widespread adoption and constraining their long-term value in radiology practice. Recent advances in generative and multimodal AI have expanded the scope of image interpretation, prompting discussions on the development of generalist medical AI.
View Article and Find Full Text PDFJMIR Form Res
September 2025
Department of Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangdong Provincial Geriatrics Institute, No. 106, Zhongshaner Rd, Guangzhou, 510080, China, 86 15920151904.
Background: Point-of-care ultrasonography has become a valuable tool for assessing diaphragmatic function in critically ill patients receiving invasive mechanical ventilation. However, conventional diaphragm ultrasound assessment remains highly operator-dependent and subjective. Previous research introduced automatic measurement of diaphragmatic excursion and velocity using 2D speckle-tracking technology.
View Article and Find Full Text PDFJ Agric Food Chem
September 2025
School of Chemical Engineering and Technology, Zhengzhou University, Zhengzhou 450001, China.
d-Amino acid oxidase from (DAAO) is valuable for pharmaceutical and chemical synthesis due to its high enantioselectivity, but its poor thermostability limits extensive application. This study proposed a synergistic strategy of "sequence consensus design coupled with structure modification" to enhance DAAO thermostability. Through homologous sequence analysis and greedy algorithm-based optimization, a triple mutant M3 (S18T/V7I/Y132F) was obtained, showing a 3.
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