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Displaying publications 41 - 44 of 44 in total

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Fulltext Green Metallic Nanoparticles: Biosynthesis to Applications

Chopra H, Bibi S, Singh I, Hasan MM, Khan MS, Yousafi Q, et al.

Front Bioeng Biotechnol, 2022;10:874742.
PMID: 35464722 DOI: 10.3389/fbioe.2022.874742

Current advancements in nanotechnology and nanoscience have resulted in new nanomaterials, which may pose health and environmental risks. Furthermore, several researchers are working to optimize ecologically friendly procedures for creating metal and metal oxide nanoparticles. The primary goal is to decrease the adverse effects of synthetic processes, their accompanying chemicals, and the resulting complexes. Utilizing various biomaterials for nanoparticle preparation is a beneficial approach in green nanotechnology. Furthermore, using the biological qualities of nature through a variety of activities is an excellent way to achieve this goal. Algae, plants, bacteria, and fungus have been employed to make energy-efficient, low-cost, and nontoxic metallic nanoparticles in the last few decades. Despite the environmental advantages of using green chemistry-based biological synthesis over traditional methods as discussed in this article, there are some unresolved issues such as particle size and shape consistency, reproducibility of the synthesis process, and understanding of the mechanisms involved in producing metallic nanoparticles via biological entities. Consequently, there is a need for further research to analyze and comprehend the real biological synthesis-dependent processes. This is currently an untapped hot research topic that required more investment to properly leverage the green manufacturing of metallic nanoparticles through living entities. The review covers such green methods of synthesizing nanoparticles and their utilization in the scientific world.
Retinal degeneration rat model: A study on the structural and functional changes in the retina following injection of sodium iodate

Koh AE, Alsaeedi HA, Rashid MBA, Lam C, Harun MHN, Saleh MFBM, et al.

J. Photochem. Photobiol. B, Biol., 2019 Jul;196:111514.
PMID: 31154277 DOI: 10.1016/j.jphotobiol.2019.111514

Retinal disorders account for a large proportion of ocular disorders that can lead to visual impairment or blindness, and yet our limited knowledge in the pathogenesis and choice of appropriate animal models for new treatment modalities may contribute to ineffective therapies. Although genetic in vivo models are favored, the variable expressivity and penetrance of these heterogeneous disorders can cause difficulties in assessing potential treatments against retinal degeneration. Hence, an attractive alternative is to develop a chemically-induced model that is both cost-friendly and standardizable. Sodium iodate is an oxidative chemical that is used to simulate late stage retinitis pigmentosa and age-related macular degeneration. In this study, retinal degeneration was induced through systemic administration of sodium iodate (NaIO3) at varying doses up to 80 mg/kg in Sprague-Dawley rats. An analysis on the visual response of the rats by electroretinography (ERG) showed a decrease in photoreceptor function with NaIO3 administration at a dose of 40 mg/kg or greater. The results correlated with the TUNEL assay, which revealed signs of DNA damage throughout the retina. Histomorphological analysis also revealed extensive structural lesions throughout the outer retina and parts of the inner retina. Our results provided a detailed view of NaIO3-induced retinal degeneration, and showed that the administration of 40 mg/kg NaIO3 was sufficient to generate disturbances in retinal function. The pathological findings in this model reveal a degenerating retina, and can be further utilized to develop effective therapies for RPE, photoreceptor, and bipolar cell regeneration.
Fulltext Predictors for detecting chronic respiratory diseases in community surveys: A pilot cross-sectional survey in four South and South East Asian low- and middle-income countries

Agarwal D, Hanafi NS, Khoo EM, Parker RA, Ghorpade D, Salvi S, et al.

J Glob Health, 2021;11:04065.
PMID: 34737865 DOI: 10.7189/jogh.11.04065

Background: Our previous scoping review revealed limitations and inconsistencies in population surveys of chronic respiratory disease. Informed by this review, we piloted a cross-sectional survey of adults in four South/South-East Asian low-and middle-income countries (LMICs) to assess survey feasibility and identify variables that predicted asthma or chronic obstructive pulmonary disease (COPD).
Methods: We administered relevant translations of the BOLD-1 questionnaire with additional questions from ECRHS-II, performed spirometry and arranged specialist clinical review for a sub-group to confirm the diagnosis. Using random sampling, we piloted a community-based survey at five sites in four LMICs and noted any practical barriers to conducting the survey. Three clinicians independently used information from questionnaires, spirometry and specialist reviews, and reached consensus on a clinical diagnosis. We used lasso regression to identify variables that predicted the clinical diagnoses and attempted to develop an algorithm for detecting asthma and COPD.
Results: Of 508 participants, 55.9% reported one or more chronic respiratory symptoms. The prevalence of asthma was 16.3%; COPD 4.5%; and 'other chronic respiratory disease' 3.0%. Based on consensus categorisation (n = 483 complete records), "Wheezing in last 12 months" and "Waking up with a feeling of tightness" were the strongest predictors for asthma. For COPD, age and spirometry results were the strongest predictors. Practical challenges included logistics (participant recruitment; researcher safety); misinterpretation of questions due to local dialects; and assuring quality spirometry in the field.
Conclusion: Detecting asthma in population surveys relies on symptoms and history. In contrast, spirometry and age were the best predictors of COPD. Logistical, language and spirometry-related challenges need to be addressed.
Fulltext Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Burstein R, Henry NJ, Collison ML, Marczak LB, Sligar A, Watson S, et al.

Nature, 2019 Oct;574(7778):353-358.
PMID: 31619795 DOI: 10.1038/s41586-019-1545-0

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2-to end preventable child deaths by 2030-we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000-2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations.