Biocompatible Nanomaterials for Sustainable Biomedical Applications

We explore the many ways biocompatible nanomaterials may be used in sustainable biomedical settings. Quantum dots are 10 nm in size, carbon nanotubes are 50 nm, iron oxide nanoparticles are 25 nm, gold nanoparticles are 20 nm, and silver nanoparticles are 30 nm. The physicochemical features of these nanomaterials are different from one another. These nanomaterials may encapsulate therapeutic substances, according to drug loading evaluations; for example, gold nanoparticles can hold 15 mg/g of iron oxide, 12 mg/g of silver, 18 mg/g of carbon nanotubes, 20 mg/g of carbon, and 10 mg/g of quantum dots. Nanoparticles of gold (95% vitality after 24 hours), silver (93% viability), iron oxide (97% viability), carbon nanotubes (92% viability), and quantum dots (90% viability) highlight the biocompatibility of these materials. Fluorescence intensities of 1000 AU for gold nanoparticles, 980 AU for silver nanoparticles, 1050 AU for iron oxide nanoparticles, 900 AU for carbon nanotubes, and 1100 AU for quantum dots were observed in in vivo imaging investigations, further demonstrating the potential of these nanomaterials as contrast agents. By conducting thorough assessments and analyses, this study reveals how biocompatible nanomaterials can be used to create long-term biomedical applications, such as molecular imaging and targeted drug delivery, which will improve healthcare solutions and patient outcomes

Assessing the Environmental Impact of Advanced Energy Storage Solutions: A Comparative Lifecycle Analysis

Biodiesel manufacturing from waste cooking oil has emerged as a potential alternative in the search of sustainable energy. This process helps mitigate environmental pollution and reduces reliance on fossil fuels. This research examines the catalytic efficiency of environmentally friendly catalysts in this process, with a specific emphasis on catalysts based on enzymes. It assesses their effectiveness in terms of the production of biodiesel, the rate of the chemical reactions, cost efficiency, and their influence on the environment. Experimental evidence demonstrates that enzyme-based catalysts have enhanced catalytic activity, leading to an average biodiesel production of 90%, outperforming traditional catalysts such as solid acids, bases, and heterogeneous metal catalysts. Moreover, enzyme catalysts exhibit enhanced reaction rates due to their unique enzymatic activity and gentle reaction conditions. The cost study shows that the manufacturing costs for enzyme catalysts are competitive, with an average total cost of $800, which is equivalent to traditional catalysts. Environmental impact evaluation emphasizes the sustainability of enzyme catalysts by demonstrating their lower energy consumption, waste production, and greenhouse gas emissions compared to traditional alternatives. The results highlight the capacity of green catalysts, namely enzyme- based catalysts, to enhance sustainable biodiesel production methods, hence promoting a more eco-friendly and robust energy framework

Whole Genome Sequencing of Mycobacterium tuberculosis Clinical Isolates From India Reveals Genetic Heterogeneity and Region-Specific Variations That Might Affect Drug Susceptibility

Whole genome sequencing (WGS) of Mycobacterium tuberculosis has been constructive in understanding its evolution, genetic diversity and the mechanisms involved in drug resistance. A large number of sequencing efforts from across the globe have revealed genetic diversity among clinical isolates and the genetic determinants for their resistance to anti-tubercular drugs. Considering the high TB burden in India, the availability of WGS studies is limited. Here we present, WGS results of 200 clinical isolates of M. tuberculosis from North India which are categorized as sensitive to first-line drugs, mono-resistant, multi-drug resistant and pre-extensively drug resistant isolates. WGS revealed that 20% of the isolates were co-infected with M. tuberculosis and non-tuberculous mycobacteria species. We identified 12,802 novel genetic variations in M. tuberculosis isolates including 343 novel SNVs in 38 genes which are known to be associated with drug resistance and are not currently used in the diagnostic kits for detection of drug resistant TB. We also identified M. tuberculosis lineage 3 to be predominant in the northern region of India. Additionally, several novel SNVs, which may potentially confer drug resistance were found to be enriched in the drug resistant isolates sampled. This study highlights the significance of employing WGS in diagnosis and for monitoring further development of MDR-TB strains

Characterizing the normal proteome of human ciliary body

BACKGROUND: The ciliary body is the circumferential muscular tissue located just behind the iris in the anterior chamber of the eye. It plays a pivotal role in the production of aqueous humor, maintenance of the lens zonules and accommodation by changing the shape of the crystalline lens. The ciliary body is the major target of drugs against glaucoma as its inhibition leads to a drop in intraocular pressure. A molecular study of the ciliary body could provide a better understanding about the pathophysiological processes that occur in glaucoma. Thus far, no large-scale proteomic investigation has been reported for the human ciliary body. RESULTS: In this study, we have carried out an in-depth LC-MS/MS-based proteomic analysis of normal human ciliary body and have identified 2,815 proteins. We identified a number of proteins that were previously not described in the ciliary body including importin 5 (IPO5), atlastin-2 (ATL2), B-cell receptor associated protein 29 (BCAP29), basigin (BSG), calpain-1 (CAPN1), copine 6 (CPNE6), fibulin 1 (FBLN1) and galectin 1 (LGALS1). We compared the plasma proteome with the ciliary body proteome and found that the large majority of proteins in the ciliary body were also detectable in the plasma while 896 proteins were unique to the ciliary body. We also classified proteins using pathway enrichment analysis and found most of proteins associated with ubiquitin pathway, EIF2 signaling, glycolysis and gluconeogenesis. CONCLUSIONS: More than 95% of the identified proteins have not been previously described in the ciliary body proteome. This is the largest catalogue of proteins reported thus far in the ciliary body that should provide new insights into our understanding of the factors involved in maintaining the secretion of aqueous humor. The identification of these proteins will aid in understanding various eye diseases of the anterior segment such as glaucoma and presbyopia

Widespread somatic L1 retrotransposition occurs early during gastrointestinal cancer evolution

Somatic L1 retrotransposition events have been shown to occur in epithelial cancers. Here, we attempted to determine how early somatic L1 insertions occurred during the development of gastrointestinal (GI) cancers. Using L1-targeted resequencing (L1-seq), we studied different stages of four colorectal cancers arising from colonic polyps, seven pancreatic carcinomas, as well as seven gastric cancers. Surprisingly, we found somatic L1 insertions not only in all cancer types and metastases but also in colonic adenomas, well-known cancer precursors. Some insertions were also present in low quantities in normal GI tissues, occasionally caught in the act of being clonally fixed in the adjacent tumors. Insertions in adenomas and cancers numbered in the hundreds, and many were present in multiple tumor sections, implying clonal distribution. Our results demonstrate that extensive somatic insertional mutagenesis occurs very early during the development of GI tumors, probably before dysplastic growth

Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes

© 2017 Wong et al.; Published by Cold Spring Harbor Laboratory Press. Complementing genome sequence with deep transcriptome and proteome data could enable more accurate assembly and annotation of newly sequenced genomes. Here, we provide a proof-of-concept of an integrated approach for analysis of the genome and proteome of Anopheles stephensi, which is one of the most important vectors of the malaria parasite. To achieve broad coverage of genes, we carried out transcriptome sequencing and deep proteome profiling of multiple anatomically distinct sites. Based on transcriptomic data alone, we identified and corrected 535 events of incomplete genome assembly involving 1196 scaffolds and 868 protein-coding gene models. This proteogenomic approach enabled us to add 365 genes that were missed during genome annotation and identify 917 gene correction events through discovery of 151 novel exons, 297 protein extensions, 231 exon extensions, 192 novel protein start sites, 19 novel translational frames, 28 events of joining of exons, and 76 events of joining of adjacent genes as a single gene. Incorporation of proteomic evidence allowed us to change the designation of more than 87 predicted noncoding RNAs to conventional mRNAs coded by protein-coding genes. Importantly, extension of the newly corrected genome assemblies and gene models to 15 other newly assembled Anopheline genomes led to the discovery of a large number of apparent discrepancies in assembly and annotation of these genomes. Our data provide a framework for how future genome sequencing efforts should incorporate transcriptomic and proteomic analysis in combination with simultaneous manual curation to achieve near complete assembly and accurate annotation of genomes

Cost analysis of nondeterministic probabilistic programs

We consider the problem of expected cost analysis over nondeterministic probabilistic programs, which aims at automated methods for analyzing the resource-usage of such programs. Previous approaches for this problem could only handle nonnegative bounded costs. However, in many scenarios, such as queuing networks or analysis of cryptocurrency protocols, both positive and negative costs are necessary and the costs are unbounded as well. In this work, we present a sound and efficient approach to obtain polynomial bounds on the expected accumulated cost of nondeterministic probabilistic programs. Our approach can handle (a) general positive and negative costs with bounded updates in variables; and (b) nonnegative costs with general updates to variables. We show that several natural examples which could not be handled by previous approaches are captured in our framework. Moreover, our approach leads to an efficient polynomial-time algorithm, while no previous approach for cost analysis of probabilistic programs could guarantee polynomial runtime. Finally, we show the effectiveness of our approach using experimental results on a variety of programs for which we efficiently synthesize tight resource-usage bounds

Cost Analysis of Nondeterministic Probabilistic Programs

We consider the problem of expected cost analysis over nondeterministic probabilistic programs, which aims at automated methods for analyzing the resource-usage of such programs. Previous approaches for this problem could only handle nonnegative bounded costs. However, in many scenarios, such as queuing networks or analysis of cryptocurrency protocols, both positive and negative costs are necessary and the costs are unbounded as well. In this work, we present a sound and efficient approach to obtain polynomial bounds on the expected accumulated cost of nondeterministic probabilistic programs. Our approach can handle (a) general positive and negative costs with bounded updates in variables; and (b) nonnegative costs with general updates to variables. We show that several natural examples which could not be handled by previous approaches are captured in our framework. Moreover, our approach leads to an efficient polynomial-time algorithm, while no previous approach for cost analysis of probabilistic programs could guarantee polynomial runtime. Finally, we show the effectiveness of our approach by presenting experimental results on a variety of programs, motivated by real-world applications, for which we efficiently synthesize tight resource-usage bounds.Comment: A conference version will appear in the 40th ACM Conference on Programming Language Design and Implementation (PLDI 2019

Downregulation of S100 calcium binding protein A9 in esophageal squamous cell carcinoma

The development of esophageal squamous cell carcinoma (ESCC) is poorly understood and the major regulatory molecules involved in the process of tumorigenesis have not yet been identified. We had previously employed a quantitative proteomic approach to identify differentially expressed proteins in ESCC tumors. A total of 238 differentially expressed proteins were identified in that study including S100 calcium binding protein A9 (S100A9) as one of the major downregulated proteins. In the present study, we carried out immunohistochemical validation of S100A9 in a large cohort of ESCC patients to determine the expression and subcellular localization of S100A9 in tumors and adjacent normal esophageal epithelia. Downregulation of S100A9 was observed in 67% (n=192) of 288 different ESCC tumors, with the most dramatic downregulation observed in the poorly differentiated tumors (99/111). Expression of S100A9 was restricted to the prickle and functional layers of normal esophageal mucosa and localized predominantly in the cytoplasm and nucleus whereas virtually no expression was observed in the tumor and stromal cells. This suggests the important role that S100A9 plays in maintaining the differentiated state of epithelium and suggests that its downregulation may be associated with increased susceptibility to tumor formation