Soft Pneumatic Muscles: Revolutionizing Human Assistive Devices with Geometric Design and Intelligent Control.

Soft robotics, a recent advancement in robotics systems, distinguishes itself by utilizing soft and flexible materials like silicon rubber, prioritizing safety during human interaction, and excelling in handling complex or delicate objects. Soft pneumatic actuators, a prevalent type of soft robot, are the focus of this paper. A new geometrical parameter for soft artificial pneumatic muscles is introduced, enabling the prediction of actuation behavior using analytical models based on specific design parameters. The study investigated the impact of the chamber pitch parameter and actuation conditions on the deformation direction and internal stress of three tested soft pneumatic muscle (SPM) models. Simulation involved the modeling of hyperelastic materials using finite element analysis. Additionally, an artificial neural network (ANN) was employed to predict pressure values in three chambers at desired Cartesian positions. The trained ANN model demonstrated exceptional performance. It achieved high accuracy with training, validation, and testing residuals of 99.58%, 99.89%, and 99.79%, respectively. During the validation simulations and neural network results, the maximum errors in the x, y, and z coordinates were found to be 9.3%, 7.83%, and 8.8%, respectively. These results highlight the successful performance and efficacy of the trained ANN model in accurately predicting pressure values for the desired positions in the soft pneumatic muscles.

Correlation of body mass index to Ghrelin and IGF-1 among children with short stature

Abstract Objective: To assess the BMI among children with Growth Hormone Deficiency (GHD) and Idiopathic Short Stature (ISS) and its correlation to ghrelin, Growth Hormone (GH), and Insulin-like Growth Factor-1 (IGF-1) levels. Methods: A cross-sectional descriptive study in which 42 patients attending the Pediatric endocrine clinic were enrolled, allocated into two groups: group I: GHD children; group II: ISS children. Ghrelin, IGF-1 and GH in both groups were measured. Results: Ghrelin was significantly higher among GHD group (p < 0.001). Overall, there was a strong negative correlation between IGF-1 and ghrelin (r = -0.977, p-value = < 0.001) while a moderate positive correlation between ghrelin and BMI (r = 0.419, p-value = 0.006). There was a weak positive non-significant correlation between IGF-1 and BMI (r = 0.276, p-value = 0.077). In GHD group, there was a weak positive non-significant correlation between ghrelin and GHmax measurement (r = 0.052, p-value = 0.824), while a weak negative non-significant correlation between both variables in ISS group (r = -0.243, p-value = 0.288). In GHD group, there was a moderate positive correlation between ghrelin and BMI (r = 0.500, p-value = 0.021), but weak negative non-significant correlation between both variables in ISS group (r = -0.255, p-value = 0.265). Conclusion: There was a negative feedback loop between ghrelin and IGF-1, whereas a positive feedback between ghrelin and BMI. BMI was more affected in the ISS group but was non-signifi-cantly correlated with ghrelin. There was no significant compensatory response of ghrelin suggesting its contribution to the pathogenesis of ISS.

Correlation of body mass index to Ghrelin and IGF-1 among children with short stature.

OBJECTIVE: To assess the BMI among children with Growth Hormone Deficiency (GHD) and Idiopathic Short Stature (ISS) and its correlation to ghrelin, Growth Hormone (GH), and Insulin-like Growth Factor-1 (IGF-1) levels. METHODS: A cross-sectional descriptive study in which 42 patients attending the Pediatric endocrine clinic were enrolled, allocated into two groups: group I: GHD children; group II: ISS children. Ghrelin, IGF-1 and GH in both groups were measured. RESULTS: Ghrelin was significantly higher among GHD group (p < 0.001). Overall, there was a strong negative correlation between IGF-1 and ghrelin (r = -0.977, p-value = < 0.001) while a moderate positive correlation between ghrelin and BMI (r = 0.419, p-value = 0.006). There was a weak positive non-significant correlation between IGF-1 and BMI (r = 0.276, p-value = 0.077). In GHD group, there was a weak positive non-significant correlation between ghrelin and GHmax measurement (r = 0.052, p-value = 0.824), while a weak negative non-significant correlation between both variables in ISS group (r = -0.243, p-value = 0.288). In GHD group, there was a moderate positive correlation between ghrelin and BMI (r = 0.500, p-value = 0.021), but weak negative non-significant correlation between both variables in ISS group (r = -0.255, p-value = 0.265). CONCLUSION: There was a negative feedback loop between ghrelin and IGF-1, whereas a positive feedback between ghrelin and BMI. BMI was more affected in the ISS group but was non-significantly correlated with ghrelin. There was no significant compensatory response of ghrelin suggesting its contribution to the pathogenesis of ISS.

Metabolic effects of antiangiogenic drugs in tumors: therapeutic implications.

Antiangiogenic therapy has become a mainstay of cancer therapeutics, but clinical responses are generally short-term owing to the development of secondary resistance. Tumor starvation by antiangiogenic drugs is largely attributed to increased hypoxia and impaired nutrients supply, suggesting that angiogenesis inhibition causes remarkable metabolic perturbations in the tumor microenvironment. We review here recent acquisitions concerning metabolic effects of angiogenesis blockade in tumors and discuss the possibility that some metabolic features of tumor cells - i.e. their dependency from glucose as primary energy substrate - might affect tumor responses to anti-vascular endothelial growth factor treatment. Moreover, we discuss the hypothesis that anti-angiogenic therapy might foster metabolic evolution of tumors. The therapeutic implications of this hypothesis will be discussed further here.

Evaluation of urinary proepithelin as a potential biomarker for bladder cancer detection and prognosis in Egyptian patients.

BACKGROUND/AIM: Proepithelin is a growth factor that may play a critical role in bladder cancer. Its over-expression in urine of bladder cancer patients gave us the impetus to evaluate its potential suitability as a biomarker for bladder cancer diagnosis and/or prognosis. METHODS: proepithelin was estimated in 86 voided urine samples, including 59 bladder cancer patients and 27 healthy volunteers using quantitative sandwich enzyme immunoassay technique. Urinary proepithelin level was expressed in ng/100 mg creatinine. RESULTS: Urinary proepithelin was significantly higher in bladder cancer patients compared to control subjects (means: 17.5 ± 10 and 8.9 ± 3.5 ng/100 mg creatinine, respectively; p < 0.001), and the test sensitivity and specificity to detect the presence of bladder cancer were 74.6 and 85.2%, respectively. Furthermore, patients with low-grade/non-muscle invasive stages bladder cancer showed significantly lower urinary proepithelin compared to high-grade/non-muscle invasive stages and high-grade/invasive stages ones (means: 11.6 ± 9, 20.2 ± 8.1 and 23.8 ± 11.9 ng/100 mg creatinine, respectively; p= 0.005 and 0.002, respectively). CONCLUSIONS: This preliminary study suggests that urinary proepithelin may be considered as a non-invasive, sensitive, and specific urine-based test for bladder cancer diagnosis and/or prognosis.