Objective: To investigate whether ultrasonographic measurement of the cross-sectional area (CSA) of the intrinsic hand muscles can be used to predict muscle strength in a valid and reliable manner, and to determine if this method can be used for follow-up of patients with peripheral nerve injury between the wrist and elbow.
Design: Repeated-measures cross-sectional study.
Setting: Clinical and academic hospital.
Participants: Healthy adults (n=31) and patients with ulnar and median nerve injuries (n=16) between the wrist and elbow who were visiting the Erasmus Medical Center or Maasstad Hospital were included in the study (N=47).
Interventions: Not applicable.
Main Outcome Measures: Correlation between measured muscle CSA and strength and assessment of inter- and intrarater reliability. Ultrasound and strength measurements of the intrinsic hand muscles were conducted bilaterally. To establish validity, the CSA of 4 muscles (abductor digiti minimi, first dorsal interosseus, abductor pollicis brevis, opponens pollicis) was compared with strength measurements of the same muscles conducted with the Rotterdam Intrinsic Hand Myometer. Repeated measures were conducted to assess inter- and intrarater reliability.
Results: The assessed CSA strongly correlated with strength measurements, with correlations ranging from 0.82 to 0.93 in healthy volunteers and from 0.63 to 0.94 in patients. Test-retest reliability showed excellent intrarater reliability (intraclass correlation coefficient range, 0.99-1.00) in patients and volunteers and good interrater reliability (intraclass correlation coefficient range, 0.88-0.95) in healthy volunteers.
Conclusions: We found that ultrasound is a valid and reliable method to assess the CSA of specific muscles in the hand. Therefore, this technique could be useful to monitor muscle reinnervation in patients suffering from peripheral nerve injury as a valuable addition to strength dynamometers.
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http://dx.doi.org/10.1016/j.apmr.2014.11.014 | DOI Listing |
BMC Geriatr
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School of Medicine, Qom University of Medical Sciences, Qom, Iran.
Introduction: Intrinsic Capacity in integrated geriatric care emphasizes the importance of a thorough functional assessment. Monitoring the intrinsic capacity of older individuals provides standardized and reliable information to prevent early disability. This study assessed the relationship between intrinsic capacity and functional ability in older adults.
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Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China), Hefei University of Technology, Hefei, 230009, Anhui, China.
With the advancement of deep learning models nowadays, they have successfully applied in the semi-supervised medical image segmentation where there are few annotated medical images and a large number of unlabeled ones. A representative approach in this regard is the semi-supervised method based on consistency regularization, which improves model training by imposing consistency constraints (perturbations) on unlabeled data. However, the perturbations in this kind of methods are often artificially designed, which may introduce biases unfavorable to the model learning in the handling of medical image segmentation.
View Article and Find Full Text PDFSci Rep
January 2025
Evolutionary Bioinformatics Laboratory, Department of Crop Sciences, University of Illinois, Urbana, IL, 61801, USA.
Intrinsically disordered regions are flexible regions that complement the typical structured regions of proteins. Little is known however about their evolution. Here we leverage a comparative and evolutionary genomics approach to analyze intrinsic disorder in the structural domains of thousands of proteomes.
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January 2025
School of Economics and Management, China University of Petroleum (East China), Qingdao, 266580, People's Republic of China. Electronic address:
Geopolitical conflicts and other risk events are subtly reshaping the global political and economic landscape, gradually disrupting the balance between economic development and ecological sustainability. Understanding the pathways through which geopolitical risks affect the ecological footprint is crucial for achieving ecological sustainability goals. This study employed dual machine learning models for high-precision analysis to deeply explore the intrinsic patterns of how geopolitical risks impact the ecological footprint.
View Article and Find Full Text PDFAcc Chem Res
January 2025
State Key Laboratory of Organometallic Chemistry, Shanghai Institute of Organic Chemistry, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, China.
ConspectusIn recent years, our research group has dedicated significant effort to the field of asymmetric organometallic electrochemical synthesis (AOES), which integrates electrochemistry with asymmetric transition metal catalysis. On one hand, we have rationalized that organometallic compounds can serve as molecular electrocatalysts (mediators) to reduce overpotentials and enhance both the reactivity and selectivity of reactions. On the other hand, the conditions for asymmetric transition metal catalysis can be substantially improved through electrochemistry, enabling precise modulation of the transition metal's oxidation state by controlling electrochemical potentials and regulating the electron transfer rate via current adjustments.
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