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Nanotechnology has played a prominent role in biomedical engineering, offering innovative approaches to numerous treatments. Notable advances have been observed in the development of medical devices, contributing to the advancement of modern medicine. This article briefly discusses key applications of nanotechnology in tissue engineering, controlled drug release systems, biosensors and monitoring, and imaging and diagnosis. The particular emphasis on this theme will result in a better understanding, selection, and technical approach to nanomaterials for biomedical purposes, including biological risks, security, and biocompatibility criteria.

Granular sludge is a promising biotechnology to treat sewage contaminated with pharmaceuticals due to its increased toxicity resistance. In this context, this study evaluated the potential of Ca 2+ as a granulation precursor and how pharmaceutical compounds (loratadine, prednisone, fluconazole, fenofibrate, betamethasone, 17α-ethinyl estradiol, and ketoprofen) affect granulation. Continuous and intermittent dosages of Ca 2+ in the presence and absence of pharmaceuticals were evaluated. The results showed that intermittent addition of Ca 2+ reduces the time for anaerobic sludge granulation, and pharmaceuticals presence did not impair granulation. 10% of the granules presented mean diameters greater than 2.11 mm within 93 days with intermittent Ca 2+ dosage in the pharmaceuticals' presence. In contrast, no granules higher than 2.0 mm were observed with no precursor addition. The pharmaceuticals' toxicity may have created a stress condition for the microbial community, contributing to more EPS production and a greater potential for granulation. It was also verified that pharmaceuticals' presence did not decrease organic matter, total alkalinity, and volatile fatty acids removals. The 16S rRNA gene analysis revealed taxa resistance to recalcitrant compounds when pharmaceuticals were added. Besides, the efficiency of a granular sludge bioreactor (EGSB) was evaluated for pharmaceuticals removal, and betamethasone, fenofibrate, and prednisone were effectively removed.

Background: Genetic progress for fertility and reproduction traits in dairy cattle has been limited due to the low heritability of most indicator traits. Moreover, most of the quantitative trait loci (QTL) and candidate genes associated with these traits remain unknown. In this study, we used 5.6 million imputed DNA sequence variants (single nucleotide polymorphisms, SNPs) for genome-wide association studies (GWAS) of 18 fertility and reproduction traits in Holstein cattle. Aiming to identify pleiotropic variants and increase detection power, multiple-trait analyses were performed using a method to efficiently combine the estimated SNP effects of single-trait GWAS based on a chi-square statistic., Results: There were 87, 72, and 84 significant SNPs identified for heifer, cow, and sire traits, respectively, which showed a wide and distinct distribution across the genome, suggesting that they have relatively distinct polygenic nature. The biological functions of immune response and fatty acid metabolism were significantly enriched for the 184 and 124 positional candidate genes identified for heifer and cow traits, respectively. No known biological function was significantly enriched for the 147 positional candidate genes found for sire traits. The most important chromosomes that had three or more significant QTL identified are BTA22 and BTA23 for heifer traits, BTA8 and BTA17 for cow traits, and BTA4, BTA7, BTA17, BTA22, BTA25, and BTA28 for sire traits. Several novel and biologically important positional candidate genes were strongly suggested for heifer (SOD2, WTAP, DLEC1, PFKFB4, TRIM27, HECW1, DNAH17, and ADAM3A), cow (ANXA1, PCSK5, SPESP1, and JMJD1C), and sire (ELMO1, CFAP70, SOX30, DGCR8, SEPTIN14, PAPOLB, JMJD1C, and NELL2) traits., Conclusions: These findings contribute to better understand the underlying biological mechanisms of fertility and reproduction traits measured in heifers, cows, and sires, which may contribute to improve genomic evaluation for these traits in dairy cattle., (© 2022. The Author(s).)