Search

Objective: To determine the factors affecting the performance of the deep cervical flexors (DCFs) in young people using smartphones., Methods: Eighty-six individuals were enrolled in this study. Joint position sense errors, forward head and protracted shoulder posture, DCFs, and the superficial cervical muscles were evaluated. Smartphone Addiction Scale, State-Trait Anxiety Inventory, and International Physical Activity Questionnaire were used., Results: Regression analysis indicated that smartphone addiction and superficial cervical muscle strengths affect the performance of DCFs independently (p < 0.05). SAS was correlated with JPSE-flexion (r = 0.408), DCF activity/performance score (r = -0.453/r = -0.431), forward head posture (r = -0.412), and cervical flexor/extensor muscle strengths (r = -0.313/r = -0.319)., Conclusion: Smartphone addiction and cervical superficial muscles are related to the performance of the DCFs in young people. Using smartphones causes impaired joint position sense in flexion, decreased DCF activity, and forward head posture.

Objective : Compare the gut microbiome composition among individuals with acute spinal cord injury (A-SCI), long-standing SCI (L-SCI), vs. able-bodied (AB) controls. Design : Cross-sectional study. Setting : The University of Alabama at Birmingham. Participants : Seven adults with A-SCI (36 ± 12 years, 2F/5M, C4-T10, and American Spinal Injury Association Impairment Scale [AIS] A-D), 25 with L-SCI (46 ± 13 years, 6F/19M, C4-L1, and AIS A-D), and 25 AB controls (42 ± 13 years, 9F/16M). Methods : Stool samples were collected after a median of 7 days and 18 years after injury in the A-SCI and L-SCI groups, respectively. Gut microbiome composition was analyzed using the 16S rRNA sequencing technique and QIIME software. The abundances of bacteria communities among groups were compared using the Kruskal-Wallis test adjusted for age. Results : Several alpha diversity indices were different among groups (Chao1, Observed species, and Phylogenetic Diversity), but not others (Shannon and Simpson). Beta diversity differed among each pair of groups ( P  < 0.05). A number of microbial communities were differentially abundant among the groups ( P  < 0.05). Conclusion : Our results revealed differences in the gut microbiome composition among groups. Compared to the AB controls, the SCI groups demonstrated microbiome profiles that shared features linked to metabolic syndrome, inflammation-related bowel disorders, depressive disorders, or antibiotics use, whereas the L-SCI group's microbiome included features linked to reduced physical activity compared to the A-SCI and AB controls. Our results provided preliminary data and a scientific foundation for future studies investigating the impact of the gut microbiome composition on long-term health in individuals with SCI.