The effect of adipose-derived stem cells on the increased survival of crushed cartilage graft in rabbits

Background: In recent years the use of diced cartilage grafts in reconstructive surgery particulary rhinoplasty have been considered by most plastic surgeons. However, longterm resorption usually occurs. Stem cells are a powerful tool for reconstructive surgery to rebuild and maintain tissue with reduced complications. Since the adipose tissuederived stem cells (ADSCs) can rebuild a wide variety of tissues such as skin, fat, bone and cartilage are used, this is a very good chance for cosmetic surgery. The aim of this study was to examine the effects of adipose-derived stem cells on the viability of diced cartilage grafts. Methods: This interventional study was performed on May 2014 in animal laboratory of Hazrat Fatima Hospital on 10 New Zealand white male rabbits, weighing 2000-2500 grams, approximately 12 to 16 weeks of age. Stem cells was harvested from inguinal adipose tissue of each rabbits. After completely removing the skin and perichondrium, cartilage became divided into two equal pieces using a scalpel. Then place the ear amputation was restored by nylon 4 zero. After weighing cartilages, on either side of the center line on the back of each rabbits, left and right, subcutaneous pocket created equal weight and each piece of cartilage was placed in an envelope. Stem cells were injected in one side and the other side was control. The cartilage weights were recorded both before implantation and after explantation. Evaluation of living chondrocytes was conducted 12 weeks after implantation. Results: The mean difference of cartilage weights was varied between two groups (intervention and control sides), So that the average was significantly higher in stem cell side than that in the control side (P= 0.021). The average number of live chondrocytes was significantly higher in the intervention side than the control side (P< 0.001). Conclusion: Despite the unclear mechanism, these results suggest that adipose-derived stem cells can maintain the viability of diced cartilage. Because adipose-derived stem cells are autologous and easy to harvest, they can be use to improve the long-term outcomes of diced cartilage grafting. © 2016, Tehran University of Medical Sciences. All rights reserved

Magnetic anomalies in the spin chain system, Sr3_3Cu1−x_{1-x}Znx_xIrO6_6

We report the results of ac and dc magnetization (M) and heat-capacity (C) measurements on the solid solution, Sr$_3$Cu$_{1-x}$Zn$_x$IrO$_6$. While the Zn end member is known to form in a rhombohedral pseudo one-dimensional K$_4$CdCl$_6$ structure with an antiferromagnetic ordering temperature of (T$_N$ =) 19 K, the Cu end member has been reported to form in a monoclinically distorted form with a Curie temperature of (T$_C$ =) 19 K. The magnetism of the Zn compound is found to be robust to synthetic conditions and is broadly consistent with the behavior known in the literature. However, we find a lower magnetic ordering temperature (T$_o$) for our Cu compound (~ 13 K), thereby suggesting that T$_o$ is sensitive to synthetic conditions. The Cu sample appears to be in a spin-glass-like state at low temperatures, judged by a frequency dependence of ac magnetic susceptibility and a broadening of the C anomaly at the onset of magnetic ordering, in sharp contrast to earlier proposals. Small applications of magnetic field, however, drive this system to ferromagnetism as inferred from the M data. Small substitutions for Cu/Zn (x = 0.75 or 0.25) significantly depress magnetic ordering; in other words, T$_o$ varies non-monotonically with x (T$_o$ ~ 6, 3 and 4 K for x = 0.25, 0.5, and 0.67 respectively). The plot of inverse susceptibility versus temperature is non-linear in the paramagnetic state as if correlations within (or among) the magnetic chains continuously vary with temperature. The results establishComment: 7 pages, 7 figures, Revte

Whole genome analysis of a schistosomiasis-transmitting freshwater snail

Biomphalaria snails are instrumental in transmission of the human blood fluke Schistosoma mansoni. With the World Health Organization's goal to eliminate schistosomiasis as a global health problem by 2025, there is now renewed emphasis on snail control. Here, we characterize the genome of Biomphalaria glabrata, a lophotrochozoan protostome, and provide timely and important information on snail biology. We describe aspects of phero-perception, stress responses, immune function and regulation of gene expression that support the persistence of B. glabrata in the field and may define this species as a suitable snail host for S. mansoni. We identify several potential targets for developing novel control measures aimed at reducing snail-mediated transmission of schistosomiasis

The global burden of cancer attributable to risk factors, 2010–19: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. METHODS: The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk–outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. FINDINGS: Globally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01–4·94) deaths and 105 million (95·0–116) DALYs for both sexes combined, representing 44·4% (41·3–48·4) of all cancer deaths and 42·0% (39·1–45·6) of all DALYs. There were 2·88 million (2·60–3·18) risk-attributable cancer deaths in males (50·6% [47·8–54·1] of all male cancer deaths) and 1·58 million (1·36–1·84) risk-attributable cancer deaths in females (36·3% [32·5–41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6–28·4) and DALYs by 16·8% (8·8–25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9–42·8] and 33·3% [25·8–42·0]). INTERPRETATION: The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden

A novel agent-based simulation framework for sensing in complex adaptive environments

In this paper, we present a novel formal agent-based simulation framework (FABS). FABS uses formal specification as a means of clear description of wireless sensor networks (WSNs) sensing a complex adaptive environment. This specification model is then used to develop an agent-based model of both the WSN as well as the environment. As proof of concept, we demonstrate the application of FABS to a boids model of self-organized flocking of animals monitored by a random deployment of proximity sensors

High yield super-hydrophobic carbon nanomaterials using cobalt/iron co-catalyst impregnated on powder activated carbon

Synthesis of super-hydrophobic carbonaceous materials is gaining a broader interest by the research community due to its versatile application in separation processes, special coating technologies, and membrane distillation. Carbon nanomaterials (CNMs) may exhibit stable super-hydrophobic character due to their unique physio-chemical features which can be further controlled based on customer requirements by optimizing the process variables. This study deals with the application of a bimetallic catalyst composed of iron (Fe) and cobalt (Co) to synthesize CNMs from powder activated carbon as a precursor. The process parameters were optimized to ensure super-hydrophobic surfaces. Chemical vapor deposition was utilized for the growth of carbon nanomaterials. The impact of input variables on the desired output of yield and contact angle was analyzed. The chemical vapor deposition process was optimized using the response surface methodology based on Box-Behnken design. The proportion of the catalysts and reaction time were the three input explanatory variables whereas the desired response variables were selected as the carbon yield (CY) and contact angle (CA). The synthesized super-hydrophobic materials were characterized using field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), Raman spectroscopy, thermogravimetric analysis (TGA), and contact angle analysis. The comprehensive statistical study of the results led to a significant model and optimization. The highest CY (351%) and CA (173◦ ) were obtained at the optimal loading of 2.5% Fe and 2% Mo with a reaction time of 60 min. The images obtained from FESEM and TEM revealed the presence of two types of CNMs including carbon nanofibers and multiwall carbon nanotubes. Thermogravimetric analysis was carried out to observe the temperature degradation profile of the synthesized sample. Raman spectroscopic analysis was also used to observe the proportion of ordered and disordered carbon content inside the synthesized samples. The improved catalytic super-hydrophobic carbon nanostructured materials production process proposed by this study assures the stability and high yield of the product. © 2021 by the authors. Li-censee MDPI, Basel, Switzerland

Clustering-based average state observer design for large-scale network systems

This paper addresses the aggregated monitoring problem for large-scale network systems with a few dedicated sensors. Full state estimation of such systems is often infeasible due to unobservability and/or computational infeasibility; therefore, through clustering and aggregation, a tractable representation of a network system, called a projected network system, is obtained for designing a minimum-order average state observer. This observer estimates the average states of the clusters, which are identified under explicit consideration of estimation error. Moreover, given the clustering, the proposed observer design algorithm exploits the structure of the estimation error dynamics to achieve computational tractability. Simulations show that the computation of the proposed algorithm is significantly faster than the usual H2/H∞ observer design techniques. On the other hand, compromise on the estimation error characteristics is shown to be marginal