Creatinine-to-body weight ratio is a predictor of incident diabetes: a population-based retrospective cohort study

Purpose Creatinine to body weight (Cre/BW) ratio is considered the independent risk factor for incident type 2 diabetes mellitus (T2DM), but research on this relationship is limited. The relationship between the Cre/BW ratio and T2DM among Chinse individuals is still ambiguous. This study aimed to evaluate the correlation between the Cre/BW ratio and the risk of T2DM in the Chinese population. Methods This is a retrospective cohort study from a prospectively collected database. We included a total of 200,658 adults free of T2DM at baseline. The risk of incident T2DM according to Cre/BW ratio was estimated using multivariable Cox proportional hazards models, and a two-piece wise linear regression model was developed to find out the threshold effect. Results With a median follow-up of 3.13 ± 0.94 years, a total of 4001 (1.99%) participants developed T2DM. Overall, there was an L-shaped relation of Cre/BW ratio with the risk of incident T2DM (P for non-linearity < 0.001). When the Cre/BW ratio (× 100) was less than 0.86, the risk of T2DM decreased significantly as the Cre/BW ratio increased [0.01 (0.00, 0.10), P < 0.001]. When the Cre/BW ratio (× 100) was between 0.86 and 1.36, the reduction in the risk of developing T2DM was not as significant as before [0.22 (0.12, 0.38), P < 0.001]. In contrast, when the Cre/BW ratio (× 100) was greater than 1.36, the reduction in T2DM incidence became significantly flatter than before [0.73 (0.29,1.8), P = 0.49]. Conclusion There was an L-shaped relation of Cre/BW ratio with incidence of T2DM in general Chinese adults. A negative curvilinear association between Cre/BW ratio and incident T2DM was present, with a saturation effect predicted at 0.86 and 1.36 of Cre/BW ratio (× 100).

Nine-Axis Sensor for Athlete Physical Training Load Characteristics

In order to understand the characteristic data of athletes’ training load, a method based on nine-axis sensor was proposed. Twenty-seven male college athletes were tested twice with a time interval of more than 48 hours. In part 1, participants take the 1 Repetition Maximum (1RM) test. The results show that maximum strength is one of the basic factors to develop the output power of athletes. In the process of skeletal muscle contraction, the curve of speed, force, and power is closely related. When the external load is 10%∼70%, the average power increases with the increase in the average force, it increases with the decrease in the average speed, and at 70%1RM, the average power reaches the peak and then decreases at an inflection point. It is proved that the accurate weight ratio of strength training is the basis of winning athletes, the focus of high level physical coach, and the premise of scientific sports training.

Lung protective effect of Punicalagin on LPS-induced acute lung injury in mice

Background: Punicalagin (Pun) is one of the main bioactive compounds in pomegranate peel, it possesses many properties, including antioxidant, anti-inflammation, and immunosuppressive activities. The study was aimed to investigate the protective effect and mechanisms of Pun on lipopolysaccharide (LPS) induced acute lung injury (ALI) in mice. Methods and Results: Forty-eight BALB/c male mice were used to establish ALI by intratracheal-instilled 2.4 mg/kg LPS, the mice were randomly divided into model and Pun (10, 20, 40 mg/kg) groups. The other twelve mice were intratracheal-instilled same volume of water as control. After 2 h of receiving LPS, mice were administrated drug through intraperitoneal injection. Lung index, histopathological changes, white blood cells and biomarkers in bronchoalveolar lavage fluid (BALF) were analyzed. The protein expression of total and phosphor p65, IκBα, ERK1/2, JNK and p38 in lung tissue was detected. The result showed that Pun could reduce the lung index and wet/dry weight ratio, improve lung histopathological injury. In addition, Pun decreased the inflammation cells and regulated the biomarkers in BALF. Furthermore, Pun dose-dependently reduced the phosphor protein levels of p65, IκBα, ERK1/2, JNK and p38 in lung tissue, which exhibited that the effect of Pun related to MAPKs pathway. More importantly, there is no toxicity was observed in the acute toxicity study of Pun. Conclusion: Pun improves LPS-induced ALI mainly through its anti-inflammatory properties, which is associated with NF-κB and MAPKs signaling pathways. The study implied that Pun maybe a potent agent against ALI in future clinic.

Chenopodium quinoa to Modulate Innate Myeloid Cells in the Induction of Obesity

Complex interactions between innate and adaptive immune effectors are an important component in the induction of obesity. Particularly, different subsets of myeloid cells play key roles in metabolic liver diseases and, therefore, are promising targets for intervention strategies. Chenopodium quinoa seeds constitute a good source of immunonutritional compounds, which help prevent high-fat, diet-enhanced innate immune signaling via TLR4/MyD88 that boosts inflammation. Herein, two metabolic mouse models—wild type (WT) and tributyltin treated (TBT)—were used to examine the effects associated with non-alcoholic fatty liver disease (NAFLD); mice were fed with a high-fat diet (HFD) and administered with wheat or C. quinoa bread. Variations in myeloid cells were obtained from a hemogram analysis, and rt-qPCR (mRNA) served to evaluate macrophage markers (i.e., CD68/CD206 ratio) as well as liver inflammation (i.e., Lyve-1) to gain insights into their selective functional differentiation into metabolically injured livers. Only administration of C. quinoa bread prevented alterations in the liver/body weight ratio either in WT animals or those treated with TBT. These effects were associated with significantly increased variations in the peripheral myeloid cell population. Hepatic mRNA markers revealed that C. quinoa enables a selective functional differentiation and function of intrahepatic monocyte-derived macrophages preserving tissue integrity and function.

An adaptive Dendrite-HDMR metamodeling technique for high dimensional problems

High dimensional model representation (HDMR), decomposing the high-dimensional problem into summands of different order component terms, has been widely researched to work out the dilemma of “curse-of-dimensionality” when using surrogate techniques to approximate high-dimensional problems in engineering design. However, the available one-metamodel-based HDMRs usually encounter the predicament of prediction uncertainty, while current multi-metamodels-based HDMRs cannot provide simple explicit expressions for black-box problems, and have high computational complexity in terms of constructing the model by the explored points and predicting the responses of unobserved locations. Therefore, aimed at such problems, a new stand-alone HDMR metamodeling technique, termed as Dendrite-HDMR, is proposed in this study based on the hierarchical Cut-HDMR and the white-box machine learning algorithm, Dendrite Net. The proposed Dendrite-HDMR not only provides succinct and explicit expressions in the form of Taylor expansion, but also has relatively higher accuracy and stronger stability for most mathematical functions than other classical HDMRs with the assistance of the proposed adaptive sampling strategy, named KKMC, in which k-means clustering algorithm, k-Nearest Neighbor classification algorithm and the maximum curvature information of the provided expression are utilized to sample new points to refine the model. Finally, the Dendrite-HDMR technique is applied to solve the design optimization problem of the solid launch vehicle propulsion system with the purpose of improving the impulse-weight ratio, which represents the design level of the propulsion system.

Dynamic Optimization of Bus Line Schedule in Commuter Corridor Based on Bus IC Card Data

The aim of this study was to explore the bus operating state of the city bus passenger corridor, taking the minimum bus operating cost and passenger travel cost as the objective function, taking passenger flow demand and operating income as the constraint, and considering the average speed change of the bus line in the bus corridor at different times. This paper proposes a dynamic optimization model of bus route schedule based on bus Integrated Circuit Card (IC Card) data. The optimization variable is the departure frequency of the candidate lines. To solve the model, a dynamic departure interval optimization method based on improved Genetic Algorithm (GA) was designed under different decision preferences. The method includes the calibration of generalized cost functions for passengers and bus companies and grasps the characteristics of bus operating speed changes and the design of departure strategies under different decision preferences. The validity and applicability of the proposed method are verified by a numerical example. We mainly carried out the following work: (1) Dynamic analysis of the time dimension of the bus departure interval takes into account the changes in passenger time characteristics during peak periods. (2) Seven schemes of weight ratio of passenger waiting time cost and bus operation cost were designed, and the departure intervals with different benefit orientations of passengers and operators were discussed, respectively, so as to select the corresponding departure schemes for decision makers under different decision preferences. The results show that (1) the total cost of the 7 different weighting schemes is lower than the actual value by 6.90% to 18.20%; (2) when decision makers need to bias the weight to the bus company, the weight ratio α : β between passengers and bus company is 0.25 : 0.75 which works best. The frequency of departures has been reduced by 6, and at the same time, the total optimized cost is reduced by 18.2%; (3) when decision makers need to bias the weight to the passengers, the weight ratio α : β between the passengers and bus company is 0.75 : 0.25 which works best. The frequency of departures has been increased by 19, and at the same time, the total optimized cost is reduced by 17.7%; and (4) when decision makers consider passengers and bus companies equally, the weight ratio α : β between passengers and bus companies is 0.5 : 0.5, the optimization cost is the closest to the actual cost, the optimization cost is reduced by 6.9%, and the frequency of departures has been increased by 5. The results show that the model in this paper provides a new idea for the information mining of bus routes in the research based on the bus IC Card data and provides an effective tool for the management of different operation decision preferences.

ADDITIVE MANUFACTURING PARAMETERS OPTIMIZATION OF Ti6AL4V ELI FOR MEDICAL IMPLANTS

Additive manufacturing (AM) of titanium (Ti) alloys has always fascinated researchers owing to its high strength to weight ratio, biocompatibility, and anticorrosive properties, making Ti alloy an ideal candidate for medical applications. The aim of this paper is to optimize the AM parameters, such as Laser Power (LP), Laser Scan Speed (LSS), and Hatch Space (HS), using Analysis of Variance (ANOVA) and Grey Relational analysis (GRA) for mechanical and surface characteristics like hardness, surface roughness, and contact angle, of Ti6Al4V ELI considering medical implant applications. The input parameters are optimized to have optimum hardness, surface roughness and hydrophilicity required for medical implants.

Development and Evaluation of an In Silico Dermal Absorption Model Relevant for Children

The higher skin surface area to body weight ratio in children and the prematurity of skin in neonates may lead to higher chemical exposure as compared to adults. The objectives of this study were: (i) to provide a comprehensive review of the age-dependent anatomical and physiological changes in pediatric skin, and (ii) to construct and evaluate an age-dependent pediatric dermal absorption model. A comprehensive review was conducted to gather data quantifying the differences in the anatomy and physiology of child and adult skin. Maturation functions were developed for model parameters that were found to be age-dependent. A pediatric dermal absorption model was constructed by updating a MoBi implementation of the Dancik et al. 2013 skin permeation model with these maturation functions. Using a workflow for adult-to-child model extrapolation, the predictive performance of the model was evaluated by comparing its predicted rates of flux of diamorphine, phenobarbital and buprenorphine against experimental observations using neonatal skin. For diamorphine and phenobarbital, the model provided reasonable predictions. The ratios of predicted:observed flux in neonates for diamorphine ranged from 0.55 to 1.40. For phenobarbital, the ratios ranged from 0.93 to 1.26. For buprenorphine, the model showed acceptable predictive performance. Overall, the physiologically based pediatric dermal absorption model demonstrated satisfactory prediction accuracy. The prediction of dermal absorption in neonates using a model-based approach will be useful for both drug development and human health risk assessment.

A study on design optimization for compressor blisks

Bladed disks are important components of gas turbine engine. Rotor disk spool drum assemblies of gas turbine engine constitute 20–25% of total engine weight. Increasing thrust-to-weight ratio and engine life is paramount for designers. Blisk reduces significantly weight of rotor, compared against conventional disks for aero engines. This paper brings out specific challenges faced while re-designing bladed disk into blisks including structural integrity aspects under various operating loads. This paper presents a case study on re-design of typical compressor bladed disk into a blisk, without changing the flow path or airfoil configuration, within space constraints. Weight reduction of rotor disk is carried out using shape optimization technique. Blisk configuration is derived from existing bladed disk general arrangement. This paper describes methodology of weight optimization of blisk using ‘HyperStudy’ tool considering static and dynamic 3D models with ANSYS solver. APDL fatigue life macro is developed for fatigue life prediction, using strain-life approach. In this paper 3D bladed disk, baseline and optimized 3D blisk modal analyses results are used to ensure minimum interferences for engine operating conditions. The developed methodology for optimization can be appreciated by significant weight reduction (30%), while meeting design criteria and increased fatigue life.

General practices to enhance bast fiber composite properties for state of art applications – a review

Composite materials are revolutionizing to realize the demanding needs of aeronautical, automobile, construction, chemical, and biomedical applications. The natural fiber composite is chosen as one of the best choices among composites due to its sustainable goods like eco-friendly nature, better properties and Greenhouse gas (GHG) balance. Furthermore, the bast fiber composites are identified as promising industrial composites based on the availability, strength-to-weight ratio, manufacturing ease, and economics for commercialization. However, product quality and production volume significantly influence commercial adoption of the bast fiber composites. Especially the product quality primarily suffer due to climatic conditions, damage while harvesting, extraction method, retting issues, and extraction location. Consequently, this review aims to provide an overview of the bast fibers & their composites, properties enhancement techniques, overall mechanical behaviours and thermal stability with suitable applications.