Study Objectives: To describe patterns of prescribing augmentation therapy, and types and rates of adverse events in the National Heart, Lung, and Blood Institute Registry for Individuals with Severe Deficiency of Alpha(1)-Antitrypsin.
Design: Observational cohort study with follow-up visits every 6 to 12 months for up to 7 years.
Measurements: The rate and dosing frequency with which Registry participants were prescribed to receive augmentation therapy by their managing physicians, and the type and frequency of adverse events, classified in two ways: severity of self-reported symptoms, and actions taken as a consequence of the symptom.
Results: Over the course of Registry follow-up, 66% (n = 747) of the participants received augmentation therapy at some time. In keeping with recommendations made in the 1989 American Thoracic Society (ATS) statement, 75% of participants with airflow obstruction at first visit (defined as FEV(1) < 80% predicted) received augmentation therapy within 3 years, though some participants with FEV(1) > or = 80% predicted (14%) also received augmentation therapy. Among those with COPD for whom augmentation therapy was not prescribed, financial constraints were the reported cause in 30%. Observed patterns also varied from approved practice, in that dosing frequencies other than the US Food and Drug Administration-approved, once-weekly regimen were frequently prescribed. The overall rate of reported adverse events was 0.02 per patient-month, with 83% of participants reporting no events. This overall rate was composed of 16% considered mild events, 76% moderate events, and 9% severe events.
Conclusions: We conclude that augmentation therapy was generally well tolerated and, consistent with ATS guidelines, physicians generally did not prescribe augmentation therapy for subjects with FEV(1) > or = 80% predicted. However, the large percentage of subjects with FEV(1) <80% predicted not receiving augmentation therapy and the frequent use of 2- to 3-week or monthly dosing reflects variation of practice from suggested treatment guidelines.
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http://dx.doi.org/10.1378/chest.123.5.1425 | DOI Listing |
J Integr Neurosci
January 2025
Sports, Exercise and Brain Sciences Laboratory, Sports Coaching College, Beijing Sport University, 100084 Beijing, China.
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Ningbo No. 2 Hospital, Ningbo 315099, China.
The two obstacles for treating glioma are the skull and the blood brain-barrier (BBB), the first of which forms a physical shield that increases the difficulties of traditional surgery or radiotherapy, while the latter prevents antitumor drugs reaching tumor sites. To conquer these issues, we take advantage of the high penetrating ability of sonodynamic therapy (SDT), combined with a novel nanocomplex that can easily pass the BBB. Through ultrasonic polymerization, the amphiphilic peptides (CGRRGDS) were self-assembled as a spherical shell encapsulating a sonosensitizer Rose Bengal (RB) and a plant-derived compound, sulforaphane (SFN), to form the nanocomplex SFN@RB@SPM.
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Division of Robotics, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.
Wearable motion capture gloves enable the precise analysis of hand and finger movements for a variety of uses, including robotic surgery, rehabilitation, and most commonly, virtual augmentation. However, many motion capture gloves restrict natural hand movement with a closed-palm design, including fabric over the palm and fingers. In order to alleviate slippage, improve comfort, reduce sizing issues, and eliminate movement restrictions, this paper presents a new low-cost data glove with an innovative open-palm and finger-free design.
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Department of Neurosurgery, "Carol Davila" University of Medicine and Pharmacy, 020021 Bucharest, Romania.
The convergence of Artificial Intelligence (AI) and neuroscience is redefining our understanding of the brain, unlocking new possibilities in research, diagnosis, and therapy. This review explores how AI's cutting-edge algorithms-ranging from deep learning to neuromorphic computing-are revolutionizing neuroscience by enabling the analysis of complex neural datasets, from neuroimaging and electrophysiology to genomic profiling. These advancements are transforming the early detection of neurological disorders, enhancing brain-computer interfaces, and driving personalized medicine, paving the way for more precise and adaptive treatments.
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