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An increase in plantar pressure and skin temperature is commonly associated with an increased risk of diabetic foot ulcers. However, the effect of insoles in reducing plantar temperature has not been commonly studied. The aim was to assess the effect of walking in insoles with different features on plantar temperature. Twenty-six (F/M:18/8) participants-13 with diabetes and 13 healthy, aged 55.67 ± 9.58 years-participated in this study. Skin temperature at seven plantar regions was measured using a thermal camera and reported as the difference between the temperature after walking with an insole for 20 m versus the baseline temperature. The mixed analyses of variance indicated substantial main effects for the Insole Condition, for both the right [Wilks' Lambda = 0.790, F(14, 492) = 4.393, p < 0.01, partial eta squared = 0.111] and left feet [Wilks' Lambda = 0.890, F(14, 492) = 2.103, p < 0.011, partial eta squared = 0.056]. The 2.5 mm-tall dimple insole was shown to be significantly more effective at reducing the temperature in the hallux and third met head regions compared to the 4 mm-tall dimple insole. The insoles showed to be significantly more effective in the diabetes group versus the healthy group, with large effect size for the right [Wilks' Lambda = 0.662, F(14, 492) = 8.037, p < 0.000, Partial eta-squared = 0.186] and left feet [Wilks' Lambda = 0.739, F(14, 492) = 5.727, p < 0.000, Partial eta-squared = 0.140]. This can have important practical implications for designing insoles with a view to decrease foot complications in people with diabetes.

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This paper addresses the critical challenge of detecting, separating, and classifying partial discharges in substations. It proposes two solutions: the first involves developing a signal conditioning system to reduce the sampling requirements for PD detection and increase the signal-to-noise ratio. The second approach uses machine learning techniques to separate and classify PD based on features extracted from the conditioned signal. Three clustering algorithms (K-means, Gaussian Mixture Model (GMM), and Mean-shift) and the Support Vector Machine (SVM) method were used for signal separation and classification. The proposed system effectively reduced high-frequency components up to 50 MHz, improved the signal-to-noise ratio, and effectively separated different sources of partial discharges without losing relevant information. An accuracy of up to 93% was achieved in classifying the partial discharge sources. The successful implementation of the signal conditioning system and the machine learning-based signal separation approach opens avenues for more economical, scalable, and reliable PD monitoring systems.

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The effect of increasing amounts (0%, 25%, 50%, 75%, and 100%) of dietary supplementation with an organic micromineral complex (Fe, Zn, Cu, Mn, and Se) on antioxidant defenses and mineral deposition in tissues of Nile tilapia juveniles was evaluated, where 100% supplementation represented the average adopted by the feed industry in Brazil. Fish (initial weight 23.93 ± 0.80 g) were fed until apparent satiation twice a day for 56 days. The maximum deposition of Fe and Zn in the hepatopancreas occurred in fish given approximately 50% supplementation, whereas the deposition of Mn and Se increased linearly with the inclusion of the complex. The activity of catalase and superoxide dismutase in the hepatopancreas decreased in fish fed the 50% dose, when compared to those not receiving mineral supplementation or those receiving higher doses. Glutathione peroxidase (GPx) activity in the hepatopancreas increased as the dietary Se concentration increased. However, the concentration of metallothionein in the hepatopancreas showed an inverse relationship to the increase in dietary supplementation of the organic mineral complex. There was no relationship between the doses of organic micromineral supplementation and the activities of GPx, reduced glutathione, non-protein thiols, or protein carbonylation. However, diets supplemented with 50% to 100% promoted greater GPx activity when compared to the 0% supplemented diet. Supplementation with intermediate doses of organic microminerals, approximately 50% of that used in commercial tilapia diets, promoted the homeostasis of metal metabolism, especially for Fe and Zn.

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OBJECTIVE: This study aimed to evaluate F release from GICs before and after recharging with F-dentifrices and after aging process. METHODS: Fifteen specimens of GICs (conventional, resin modified, and high viscosity) and composite resin were stored individually in a polystyrene tube containing 2 ml of deionized water (DW), with water replacement every 24 hours. After 15 days, the specimens were treated with a dentifrice suspension (1 : 3 by volume) containing 0 µg F/g (n = 5), 1,100 µg F/g (n = 5), or 5,000 µg F/g (n = 5). After 3 min, the specimens were rinsed and replaced in new tubes with 2 ml of DW. This procedure was performed 2x/day for 2 days. The readings were taken on days 1, 5, 10, and 15 before and after the treatments. A second experiment was performed, using the same specimens of the previous study that were submitted to an aging process (specimens were kept in 2 ml of DW, remaining at 37°C for 36 weeks). Readings using specific electrode for F detection were taken on days 1, 5, 10, and 15 after treatment of the samples as described above. Data were analyzed by ANOVA and Tukey's test with α fixed at 5%. RESULTS: It was observed that the highest release of F for all the GICs occurred on the first day after the treatments, especially when using a high-fluoride dentifrice, with decreasing release over time. Also, although aged GICs still recharge with F treatments, the amount of F released was lower than fresh materials. CONCLUSION: GICs present a high F recharge and release capacity, especially in the first 24 hours and after the treatment with a high-fluoride dentifrice, even after material aging.

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Osteosarcoma is the most common primary malignancy of bone in children and young adults, the highest incidence peak is during adolescence and doesn't have any gender predominance. The main site of metastasis are the lungs and extrapulmonary cases are occasional. The incidence of metastasis in the Central Nervous System (CNS) is 2-6.5%, increase to 10-15% in patients with pulmonary metastases. Therefore, metastatic disease of the CNS is rare and the information on such patients is limited. Here, we describe a case of a 20-year old patient diagnosed with osteosarcoma in the left distal femur stage IIB, he developed pulmonary disease, during palliative chemotherapy experienced relapse to the brain classified as recursive partitioning analysis (RPA) class II, and was treated with external radiotherapy (30 Gy in 10 fractions) and later he had a poor evolution and died.