Mcconnelldrachmann7625
More than 422 million people worldwide suffered from diabetes mellitus (DM) in 2021. Diabetic foot is one the most critical complications resultant of DM. Foot ulceration and infection are frequently arisen, which are associated with changes in the mechanical properties of the plantar soft tissues, peripheral arterial disease, and sensory neuropathy. Diabetic insoles are currently the mainstay in reducing the risk of foot ulcers by reducing the magnitude of the pressure on the plantar Here, we propose a novel pressure relieving heel pad based on a circular auxetic re-entrant honeycomb structure by using three-dimensional (3D) printing technology to minimize the pressure on the heel, thus reducing the occurrence of foot ulcers. Finite element models (FEMs) are developed to evaluate the structural changes of the developed circular auxetic structure upon exertion of compressive forces. Moreover, the effects of the internal angle of the re-entrant structure on the peak contact force and the mean pressure acting on the heel as well as the contact area between the heel and the pads are investigated through a finite element analysis (FEA). Based on the result from the validated FEMs, the proposed heel pad with an auxetic structure demonstrates a distinct reduction in the peak contact force (∼10%) and the mean pressure (∼14%) in comparison to a conventional diabetic insole (PU foam). The characterized result of the designed circular auxetic structure not only provides new insights into diabetic foot protection, but also the design and development of various impact resistance products.Ventricular arrhythmias are the leading cause of mortality in patients with ischemic heart diseases, such as myocardial infarction (MI). Computational simulation of cardiac electrophysiology provides insights into these arrhythmias and their treatment. However, only sparse information is available on crucial model parameters, for instance, the anisotropic intracellular electrical conductivities. Here, we introduced an approach to estimate these conductivities in normal and MI hearts. We processed and analyzed images from confocal microscopy of left ventricular tissue of a rabbit MI model to generate 3D reconstructions. We derived tissue features including the volume fraction of myocytes (Vmyo), gap junctions-containing voxels (Vgj), and fibrosis (Vfibrosis). We generated models of the intracellular space and intercellular coupling. Applying numerical methods for solving Poisson's equation for stationary electrical currents, we calculated normal (σmyo,n), longitudinal (σmyo,l), and transverse (σmyo,t) intracellular conductivities. Using linear regression analysis, we assessed relationships of conductivities to tissue features. Vgj and Vmyo were reduced in MI vs. control, but Vfibrosis was increased. Both σmyo,l and σmyo,n were lower in MI than in control. Differences of σmyo,t between control and MI were not significant. We found strong positive relationships of σmyo,l with Vmyo and Vgj, and a strong negative relationship with Vfibrosis. The relationships of σmyo,n with these tissue features were similar but less pronounced. Our study provides quantitative insights into the intracellular conductivities in the normal and MI heart. We suggest that our study establishes a framework for the estimation of intracellular electrical conductivities of myocardium with various pathologies.
This study aims to investigate the following aspects i) presence of activity-induced dental modifications (AIDMs) in a medieval population from Pieve di Pava (Siena, central Italy); ii) sex-specific and age-specific distribution of AIDMs in the sample; iii) potential correlations between AIDMs and the traditional activities and cultural habits of rural communities in medieval Italy.
The permanent teeth of 204 individuals buried at Pieve di Pava (10th-12th centuries AD) were systematically examined in order to assess the distribution of five types of AIDM, i.e. lingual surface attrition of the maxillary anterior teeth (LSAMAT), excessive occlusal load, grooving, notching, and chipping.
Prevalence rates of LSAMAT, excessive occlusal load and grooving were low, whereas higher frequencies were recorded for the other types of AIDMs. Prevalence was higher in the male subsample for all the modifications recorded. Overall, the frequencies of AIDMs increased with age.
The very low prevalence of LSAMAT was thouely, the very high prevalence of notching and chipping was taken as indicative of the processing of wool fibers. The sex-specific distribution of these AIDMs suggests that males performed activities involving the use of teeth more frequently than females.Environmental risks caused by emerging per- and polyfluoroalkyl substances (PFASs) have attracted increasing attention. As an important substitute for perfluorooctane sulfonate (PFOS), sodium p-perfluorous nonenoxybenzene sulfonate (OBS) is widely used as a firefighting foam additive and oil recovery agent in China. This study reported the tissue distribution of OBS in KM mice that were administered a dose of OBS at 10 µg/day via daily oral gavage for 7, 14, or 28 days. During exposure, gender-based differences were observed in body weight changes and tissue distribution of OBS. Liver exhibited the highest concentrations (males 12.57 ± 1.80 µg/g; females 11.80 ± 5.32 µg/g) and tissue/blood ratios and contributed more than 50% to the whole-body burden of OBS in both male and female mice, showing its ability to enrich PFASs. Furthermore, there were certain differences in the distribution characteristics of the three OBS isomers. Based on its bioaccumulation potential and widespread use, further studies are required on the human exposure risks of OBS.Phthalates are used as plasticizers in many products used in daily life worldwide. Due to industrial and economic developments, exposure among general population to phthalates may vary geographically and temporally. However, studies are lacking for investigating temporal changes in phthalate exposure in the Japanese population. In the present study, the temporal trends in exposure to various phthalates were assessed among a group of Japanese adult female population over 1993-2016 and derived associated risks. For this purpose, urine samples of healthy Japanese females in Kyoto, Japan (N = 132) collected in 1993, 2000, 2003, 2009, 2011, and 2016, were employed and measured for the concentrations of 18 phthalate metabolites. Over this period, the detection rates of mono(3-carboxypropyl) phthalate (MCPP) and monoisobutyl phthalate (MiBP) decreased, and the geometric means of the urinary concentrations of mono(2-ethyl-5-carboxypentyl) phthalate (MECPP), and mono(2-ethyl-5-oxohexyl) phthalate (MEOHP) showed a significant decreasing trend. Cumulative risk due to exposure to dibutyl phthalate (DBP), diisobutyl phthalate (DiBP), butyl benzyl phthalate (BBP), and di-2-ethylhexyl phthalate (DEHP) showed a dramatic decrease only between 1993 and 2000. The maximum hazard quotient (HQM) was attributed to DEHP in most subjects regardless of sampling year. This study showed the temporal trend of the exposure of Japanese females to several phthalate esters over two decades. As of the late 2010's, DEHP was still the predominant component of phthalate ester exposure in the population. The HI value, however, indicates that direct risk due to phthalate exposure was unlikely among the studied population.Accurately predicting Polyadenylation (Poly(A)) signals isthe key to understand the mechanism of translation regulation and mRNA metabolism. However, existing computational algorithms fail to work well for predicting Poly(A) signals due to the vanishing gradient problem when simply increasing the number of layers. In this work, we devise a spatiotemporal context-aware neural model called ACNet for Poly(A) signal prediction based on co-occurrence embedding. Specifically, genomic sequences of Poly(A) signals are first split into k-mer sequences, and k-mer embeddings are pre-trained based on the co-occurrence matrix information; Then, gated residual networks are devised to fully extract spatial information, which has an excellent ability to control the information flow and ease the problem of vanishing gradients. The gated mechanism generates channel weights by a dilated convolution and aggregates local features by identity connections which are obtained by multi-scale dilated convolutions. Experimental results indicate that our ACNet model outperforms the state-of-the-art prediction methods on various Poly(A) signal data, and an ablation study shows the effectiveness of the design strategy.To combat climate change, reducing carbon emissions from coal consumption in the power sector can be an effective strategy. We developed a price-exogenous mixed integer linear optimization model satisfying both traditional timber demand in Georgia and its neighboring states (Alabama, Florida, North Carolina, South Carolina, and Tennessee) and additional bioenergy demand to replace coal in the power plants of Georgia for 50 years, maximizing social welfare. We used Forest Inventory & Analysis unit level yield of five forest types (planted softwood, natural softwood, upland hardwood, bottomland hardwood, and mixed forest), timber demand, and price information, and developed three scenarios. In the Baseline scenario, traditional annual timber demand (152 million tons of wood) was satisfied with no coal replacement. In Scenario 1, 100% coal (7.34 million tons annually) was replaced using pulpwood only, along with traditional demand. In Scenario 2, also with traditional demand, 100% coal was replaced using pulpwoobout 43% higher compared to baseline.Due to the technological limitations associated with beneficiation technology, large amounts of flotation reagents and heavy metals remain in mineral processing wastewater. Unfortunately, however, no treatment methods are available to mitigate the resulting pollution by them. In this study, a bacterial consortium SDMC (simultaneously degrade butyl xanthate and biomineralize cadmium) was constructed in an effort to simultaneously degrade butyl xanthate (BX) and biomineralize cadmium (Cd) by screening and domesticating two different bacterial species including Hypomicrobium and Sporosarcina. SDMC is efficient in removing the combined pollution due to BX and Cd with a 100% degradation rate for BX and 99% biomineralization rate for Cd within 4 h. Besides, SDMC can tolerate high concentrations of Fe(III) (0-40 mg/L). It has an excellent ability to utilize Fe(III) for enhanced removal of the combined pollutants. SDMC can effectively remove pollutants with a pH range of 6-9. check details Further, we discussed pathways for potential degradation and biomineralization Cd(BX)2-Cd2+, BX-; BX--CS2, butyl perxanthate (BPX); Cd2+-(Ca0.67,Cd0.33)CO3. The removal of the combined pollutants primarily entails decomposition, degradation, and biomineralization, C-O bond cleavage, and microbially induced carbonate precipitation (MICP). SDMC is a simple, efficient, and eco-friendly bifunctional bacterial consortium for effective treatment of BX-Cd combined pollution in mineral processing wastewater.Protecting our environment while maintaining economic growth, requires a delicate balance among interlinked sustainable development policies. In this paper, we examine China's economic industries, including a high-resolution of the country's electricity sector during 2020-2030, using a multi-objective optimization model based on Input-Output analysis. This model, investigates the synergy and trade-offs of sustainable development goals in maximizing employment and GDP while minimizing energy and water consumption, CO2 emissions, and five major pollutants to advance a sustainable industrial structure adjustment pathway for China. Our results reveal that there exists both synergies and trade-offs among multiple objectives, e.g., synergy among goals of minimizing air pollutant emissions and trade-offs between minimizing energy consumption and maximizing employment. Through the planned industrial restructuring period (2020-2030), the GDP, employment, carbon emission, and energy consumption will increase respectively by, 96.