Background: People with type 2 diabetes mellitus (T2DM) tend to be vulnerable to geriatric syndromes such as sarcopenia and frailty. Reduced physical activity also accompanies sarcopenia and frailty, which is generally typical of patients with T2DM. However, a comprehensive assessment of physical fitness in patients with T2DM has seldom been carried out and verified. This study is thus an attempt to determine the associations among sarcopenia, frailty, and the SFT in diabetic patients and non-diabetic controls to provide a more comprehensive understanding of such associations in future evaluations of T2DM in older individuals. Methods: Sarcopenia, frailty, and the senior fitness test (SFT) were compared between 78 older men with T2DM (66.5 ± 9.0 years) and 48 age-matched normoglycemic controls (65.8 ± 5.3 years) in this case–control study. The skeletal muscle index (SMI), grip strength, and 4-m walk test were employed to assess for sarcopenia. Frailty was evaluated using the Study of Osteoporotic Fractures index (SOF). The SFT comprises five components, including body composition, muscle strength, flexibility, balance, and aerobic endurance. Results: The risk level of sarcopenia was significantly higher (p < 0.05) in the T2DM group as compared to the control group. No significant difference between-group differences were found in SMI and grip strength in the T2DM and control groups. However, the T2DM group showed a significant decrease in gait speed (p < 0.01) in comparison with the control group, as well as significant increases in frailty (p < 0.01) and depression (p < 0.05). With respect to the SFT, obvious elevation in BMI, significant declines in extremity muscle strength (elbow extensor, knee flexor, hip abductor, hip flexor, sit to stand), static/dynamic balance (single leg stand: p < 0.05; up-and-go: p < 0.01) and aerobic endurance (2-min step: p < 0.01; 6-min walk: p < 0.01) were found in the T2DM group. Furthermore, the SOF (OR = 2.638, 95% CI = 1.333–5.221), BMI (OR = 1.193, 95% CI = 1.041–1.368) and up-and-go (OR = 2.089, 95% CI = 1.400–3.117) were found to be positively and significantly associated with T2DM. Conclusions: The findings of this study indicated the importance of countering frailty and maintaining physical fitness, especially dynamic balance, during the early physical deterioration taking place in diabetic patients.

Patients with stroke often use ankle-foot orthoses (AFOs) for gait improvement. 3D printing technology has become a popular tool in recent years for the production of AFOs due to its strengths on customization and rapid manufacturing. However, the porosity of the 3D printed materials affects the kinetic features of these orthoses, leading to its lower-strength than solid ones. The effective elastic modulus of 3D printed material was measured following standard test method to obtain the kinetic features precisely in a finite element simulation. This study demonstrated that the porosity of 3D printed samples using 100% fill density was 11% for PLA and 16% for Nylon. As a result, their effective elastic modulus was reduced to 1/3 and 1/12 of fully solid objects, respectively, leading to a lower stiffness of 3D printed orthoses. A fatigue testing platform was built to verify our finite element model, and the findings of the fatigue test were consistent with the analysis of the finite element model. Further, our AFO has been proven to have a lifespan exceeding 200 thousand steps. Our study highlights the significance of determining the actual porosity of 3D printed samples by calculating the effective elastic modulus, which leads to a more precise finite element simulation and enables reliable prediction of the kinetic features of the AFO. Overall, this study provides valuable insights into the production and optimization of 3D printed AFOs for patients with stroke.

Pulsed electromagnetic fields (PEMFs) have been proposed to treat bone loss. However, time-consuming is the main complaint. A time-saving and effective treatment is of expectation. Previously, we showed a 3 min daily of single pulsed electromagnetic field (SPEMF) accelerated bone formation of long bone defect in mice. Here we compared the effect of SPEMF with PEMF for treating denervation/disuse osteopenic mice. Healthy mice were divided into 3 groups: intact mice (INT), INT + PEMF, and INT + SPEMF. Induced osteopenic mice were divided to osteopenia (IOP), IOP + PEMF, and IOP + SPEMF groups. The PEMF treated groups were subjected to daily 8 h PEMF(15 Hz, 18 G) exposure, while SPEMF treated groups were daily 3 min SPEMF(0.2 Hz, 1 T) exposure. BMD was evaluated every two weeks during the 12 weeks of treatment. Microarchitecture was evaluated on week 12. SPEMF significantly reversed bone loss in IOP mice as early as 6 weeks post-treatment, while PEMF reversed bone loss after 8 weeks. Bone volume was significantly increased in the IOP + PEMF and IOP + SPEMF group. Besides, bone volume and trabecular number of IOP + SPEMF mice were restored to the levels of INT mice in 12 weeks. Our finding suggests SPEMF increased BMD and restored microarchitecture of disuse osteopenic mice to healthy level.

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide, characterized by high incidence and poor survival rates. Glycosylation, a fundamental post-translational modification, influences protein stability, signaling, and tumor progression, with aberrations implicated in immune evasion and metastasis. This study investigates the role of glycosylation-related genes (Glycosylation-RGs) in CRC using machine learning and bioinformatics. Data from The Cancer Genome Atlas (TCGA) and the Molecular Signatures Database (MSigDB) were analyzed to identify 67 differentially expressed Glycosylation-RGs. These genes were used to classify CRC patients into two subgroups with distinct survival outcomes, highlighting their prognostic value. Weighted gene coexpression network analysis (WGCNA) revealed key modules associated with CRC traits, including pathways like glycan biosynthesis and PI3K–Akt signaling. A machine-learning-based prognostic model demonstrated strong predictive performance, stratifying patients into high- and low-risk groups with significant survival differences. Additionally, the model revealed correlations between risk scores and immune cell infiltration, providing insights into the tumor immune microenvironment. Drug sensitivity analysis identified potential therapeutic agents, including Trametinib, SCH772984, and Oxaliplatin, showing differential efficacy between risk groups. These findings enhance our understanding of glycosylation in CRC, identifying it as a critical factor in disease progression and a promising target for future therapeutic strategies.

Purpose: Reduced physical activity is reported in the elderly, especially in institutional residents. Institutionalized older adults exhibit a high prevalence of frailty. In this work, we developed an artificial intelligence of things (AIoT)-based feedback assistive strengthening ergometer (AIFASE), for the physical strengthening of the elderly with intelligent assistance. Methods: We conducted a 12-week intervention in a long-term care facility. In total, 16 participants (84.38 ± 6.0 years; 4 males and 12 females) were recruited with 1:1 randomization of exercise to control groups. The muscle strength of the lower extremities, timed up and go test (TUG), and Short-form Physical Performance Battery (SPPB) of the participants were measured. The AIFASE system allows the clinical staff to record the personal physical performance of the elderly and generates personalized exercise prescriptions accordingly. AIFASE also displays the current usage status of all ergometers and the users’ physiological conditions. The algorithms were developed to generate warning alerts when the training workload was too large by personal physiological detection. AIFASE automatically customized the exercise prescription according to the user’s exercise performance. Results: After a 12-week AIFASE intervention, the intervention group exhibited significant improvements in the strength of the hip flexor, Semi-Tandem Stand, and Tandem Stand. Conclusion: In this study, we developed an AIoT ergometer that delivered customized physical training prescriptions to improve the physical performance of long-term care facility residents. We believe that the application of AIFASE will help improve the quality of institutional care.