DeepHealthNet: Adolescent Obesity Prediction System Based on a Deep Learning Framework

Childhood and adolescent obesity rates are a global concern because obesity is associated with chronic diseases and long-term health risks. Artificial intelligence technology has emerged as a promising solution to accurately predict obesity rates and provide personalized feedback to adolescents. This study emphasizes the importance of early identification and prevention of obesity-related health issues. Factors such as height, weight, waist circumference, calorie intake, physical activity levels, and other relevant health information need to be considered for developing robust algorithms for obesity rate prediction and delivering personalized feedback. Hence, by collecting health datasets from 321 adolescents, we proposed an adolescent obesity prediction system that provides personalized predictions and assists individuals in making informed health decisions. Our proposed deep learning framework, DeepHealthNet, effectively trains the model using data augmentation techniques, even when daily health data are limited, resulting in improved prediction accuracy (acc: 0.8842). Additionally, the study revealed variations in the prediction of the obesity rate between boys (acc: 0.9320) and girls (acc: 0.9163), allowing the identification of disparities and the determination of the optimal time to provide feedback. The proposed system shows significant potential in effectively addressing childhood and adolescent obesity

Effects of Berberine and Hwangryunhaedok-Tang on Oral Bioavailability and Pharmacokinetics of Ciprofloxacin in Rats

Hwangryunhaedok-Tang (HR) and berberine-containing single herbs are used to treat bacterial infection and inflammatory diseases in eastern Asia. The combination of berberine-containing herbal medicines and ciprofloxacin can be an excellent antibacterial chemotherapy against multidrug resistance bacteria. To evaluate the pretreatment effect of berberine and HR, vehicle, berberine (25 and 50 mg/kg/day), and HR (1.4 g/kg/day) were daily administered to rats for five consecutive days. On day 6, ciprofloxacin was administered (10 mg/kg, i.v. and 20 mg/kg, p.o.) to rats. To assess cotreatment effect of berberine and ciprofloxacin, berberine (50 mg/kg) and ciprofloxacin (20 mg/kg) were coadministered by single oral gavage. Pharmacokinetic data were estimated by noncompartmental model. Compared with ciprofloxacin alone (control group), coadministration of berberine (50 mg/kg) and ciprofloxacin significantly decreased Cmax of ciprofloxacin (P<0.05). In addition, the pretreatment of berberine (50 mg/kg/day) and HR (1.4 g/kg/day) significantly decreased Cmax and AUC0→∞, compared with control group (P<0.05). The oral bioavailability of ciprofloxacin was reduced by cotreatment of berberine and pretreatment of berberine and HR. Our results suggest that the expression of P-glycoprotein and organic anion and/or organic cation transporters (OAT/OCT) could take a role in reduced oral bioavailability of ciprofloxacin by berberine and HR

SYNGAS PRODUCTION WITH A DUAL FLUIDIZED BED GASIFIER FOR POLYGENERATION

A pilot scale dual fluidized bed gasification system was developed for polygeneration with biomass. The gasification system is designed for supplying syngas for Fischer Tropsch (F-T) synthesis of bio-diesel and power generation with a syngas engine. Characteristics of biomass steam gasification were investigated in a lab scale bubbling fluidized bed, and hydrodynamics of a dual fluidized bed were investigated in a cold flow model. Based on the results from the lab scale test and cold flow model, a pilot scale dual fluidized bed gasifier was designed. In this paper, the developing process of the gasifier and preliminary results of system operation will be presented

Variants of the Distinguished Point Method for Cryptanalytic Time Memory Trade-offs (Full version)

The time memory trade-off (TMTO) algorithm, first introduced by Hellman, is a method for quickly inverting a one-way function, using pre-computed tables. The distinguished point method (DP) is a technique that reduces the number of table lookups performed by Hellman\u27s algorithm. In this paper we propose a new variant of the DP technique, named variable DP (VDP), having properties very different from DP. It has an effect on the amount of memory required to store the pre-computed tables. We also show how to combine variable chain length techniques like DP and VDP with a more recent trade-off algorithm called the rainbow table method

Pulsed Radiofrequency Treatment of Pain Relieving Point in a Soft Tissue

Pulsed radiofrequency (PRF) treatment of nervous tissue has been proposed as a less neurodestructive technique alternative to continuous RF heat lesioning. Recently, clinical reports using PRF have shown favorable effects in the treatment of a variety of focal pain areas, even in non-nervous tissues; however, the mechanism of effect underlying this treatment to non-nervous tissue remains unclear. We report the case of a 67-year-old male who presented with pain reliving point in the posterior neck. The patient had pain in the posterior neck for 3 years. The pain subsided with pressure applied to a point in the posterior neck. There were no specific abnormal findings on laboratory testing and radiologic examinations. After PRF treatment to the pain-relieving point, he had pain relief which lasted more than 5 months

A Dual Inhibitor of the Proteasome Catalytic Subunits LMP2 and Y Attenuates Disease Progression in Mouse Models of Alzheimer\u27s Disease

The immunoproteasome (iP) is a variant of the constitutive proteasome (cP) that is abundantly expressed in immune cells which can also be induced in somatic cells by cytokines such as TNF-α or IFN-γ. Accumulating evidence support that the iP is closely linked to multiple facets of inflammatory response, eventually leading to the development of several iP inhibitors as potential therapeutic agents for autoimmune diseases. Recent studies also found that the iP is upregulated in reactive glial cells surrounding amyloid β (Aβ) deposits in brains of Alzheimer\u27s disease (AD) patients, but the role it plays in the pathogenesis of AD remains unclear. In this study, we investigated the effects of several proteasome inhibitors on cognitive function in AD mouse models and found that YU102, a dual inhibitor of the iP catalytic subunit LMP2 and the cP catalytic subunit Y, ameliorates cognitive impairments in AD mouse models without affecting Aβ deposition. The data obtained from our investigation revealed that YU102 suppresses the secretion of inflammatory cytokines from microglial cells. Overall, this study indicates that there may exist a potential link between LMP2/Y and microglia-mediated neuroinflammation and that inhibition of these subunits may offer a new therapeutic strategy for AD