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      Concurrent application of conductive biopolymeric chitosan/ polyvinyl alcohol/ MWCNTs nanofibers, intracellular signaling manipulating molecules and electrical stimulation for more effective cardiac tissue engineering

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          World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions

          Summary Background To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. Methods In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40–80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. Findings Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell's C indices ranging from 0·685 (95% CI 0·629–0·741) to 0·833 (0·783–0·882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a 60-year-old male smoker without diabetes and with systolic blood pressure of 140 mm Hg and total cholesterol of 5 mmol/L ranged from 11% in Andean Latin America to 30% in central Asia. When applied to data from 79 countries (mostly low-income and middle-income countries), the proportion of individuals aged 40–64 years estimated to be at greater than 20% risk ranged from less than 1% in Uganda to more than 16% in Egypt. Interpretation We have derived, calibrated, and validated new WHO risk prediction models to estimate cardiovascular disease risk in 21 Global Burden of Disease regions. The widespread use of these models could enhance the accuracy, practicability, and sustainability of efforts to reduce the burden of cardiovascular disease worldwide. Funding World Health Organization, British Heart Foundation (BHF), BHF Cambridge Centre for Research Excellence, UK Medical Research Council, and National Institute for Health Research.
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            Does the Use of Chitosan Contribute to Oxalate Kidney Stone Formation?

            Chitosan is widely used in the biomedical field due its chemical and pharmacological properties. However, intake of chitosan results in renal tissue accumulation of chitosan and promotes an increase in calcium excretion. On the other hand, the effect of chitosan on the formation of calcium oxalate crystals (CaOx) has not been described. In this work, we evaluated the antioxidant capacity of chitosan and its interference in the formation of CaOx crystals in vitro. Here, the chitosan obtained commercially had its identity confirmed by nuclear magnetic resonance and infrared spectroscopy. In several tests, this chitosan showed low or no antioxidant activity. However, it also showed excellent copper-chelating activity. In vitro, chitosan acted as an inducer mainly of monohydrate CaOx crystal formation, which is more prevalent in patients with urolithiasis. We also observed that chitosan modifies the morphology and size of these crystals, as well as changes the surface charge of the crystals, making them even more positive, which can facilitate the interaction of these crystals with renal cells. Chitosan greatly influences the formation of crystals in vitro, and in vivo analyses should be conducted to assess the risk of using chitosan.
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              Carbon nanotube applications for tissue engineering.

              As the field of tissue engineering advances, new tools for better monitoring and evaluating of engineered tissues along with new biomaterials to direct tissue growth are needed. Carbon nanotubes may be an important tissue engineering material for improved tracking of cells, sensing of microenvironments, delivering of transfection agents, and scaffolding for incorporating with the host's body. Using carbon nanotubes for optical, magnetic resonance and radiotracer contrast agents would provide better means of evaluating tissue formation. In addition, monitoring and altering intra and intercellular processes would be useful for design of better engineered tissues. Carbon nanotubes can also be incorporated into scaffolds providing structural reinforcement as well as imparting novel properties such as electrical conductivity into the scaffolds may aid in directing cell growth. Potential cytotoxic effects associated with carbon nanotubes may be mitigated by chemically functionalizing the surface. Overall, carbon nanotubes may play an integral role as unique biomaterial for creating and monitoring engineered tissue.
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                Author and article information

                Contributors
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                Journal
                Materials Chemistry and Physics
                Materials Chemistry and Physics
                Elsevier BV
                02540584
                January 2021
                January 2021
                : 258
                : 123842
                Article
                10.1016/j.matchemphys.2020.123842
                8cc10fa2-9a57-4c93-add3-224eeba4953b
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

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