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Recently, there has been renewed interest in metabolic therapy for cancer, particularly in amino acid deprivation by enzymes. L-asparaginase was approved for the treatment of acute lymphoblastic leukemia by the U.S. Food and Drug Administration. Arginine deiminase and recombinant human arginase have been developed into clinical trials as potential cancer therapeutic agents for the treatment of arginine-auxotrophic tumors. Moreover, other novel amino acid degrading enzymes, such as glutaminase, methionase, lysine oxidase, phenylalanine ammonia lyase, have been developed for the treatment of malignant cancers. One of the greatest obstacles faced by anticancer drugs is the development of drug resistance, which is reported to be associated with autophagy. Autophagy is an evolutionarily conserved catabolic process that is responsible for the degradation of dysfunctional proteins and organelles. There is a growing body of literature revealing that, in response to metabolism stress, autophagy could be induced by amino acid deprivation. The manipulation of autophagy in combination with amino acid degrading enzymes is actively being investigated as a potential therapeutic approach in preclinical studies. Importantly, shedding light on how autophagy fuels tumor metabolism during amino acid deprivation will enable more potential combinational therapeutic strategies. This study summarizes recent advances, discussing several potential anticancer enzymes, and highlighting the promising combined therapeutic strategy of amino acid degrading enzymes and autophagy modulators in tumors.Introduction Sub-Saharan Africa and other low- and middle-income countries (LMICs) have the highest rates of antimicrobial resistance (AMR) driven by high rates of antimicrobial utilization. This is a concern as AMR appreciably increases morbidity, mortality and costs. Pharmacogenetics (PGx) and precision medicine are emerging approaches to combat AMR. Consequently, as a first step there is a need to assess AMR knowledge and attitudes, and knowledge of PGx, among healthcare professionals and use the findings to guide future interventions. Methodology We conducted a cross-sectional study involving 304 healthcare professionals at tertiary hospitals in Lusaka, Zambia. Structural Equation Modeling (SEM) was used to analyze relationships among latent variables. Results Overall correctness of answers concerning AMR among healthcare professionals was 60.4% (7/11). Knowledge of pharmacogenetics was low (38%). SEM showed that high AMR knowledge score correlated with a positive attitude toward combating AMR (p less then 0.001). Pharmacists had relatively higher AMR knowledge scores (mean = 7.67, SD = 1.1), whereas nurses had lower scores (mean = 5.57, SD = 1.9). A minority of respondents [31.5% (n = 95)] indicated that poor access to local antibiogram data promoted AMR, with the majority [56.5% (n = 190)] responding that poor adherence to prescribed antimicrobials can lead to AMR. Pharmacists had the highest scores for attitude (mean = 5.60, SD = 1.6) whereas nurses had the lowest scores (mean = 4.02, SD = 1.4). Conclusion AMR knowledge and attitudes, as well as knowledge on PGx among healthcare professionals in Zambia, is sub-optimal and has the potential to affect the uptake of precision medicine approaches to reduce AMR rates. Educational and positive behavioral change interventions are required to address this and in future, we will be seeking to introduce these to improve the use of antimicrobials.The coronavirus disease 2019 (COVID-19) has become a deadly pandemic with surging mortality rates and no cure. COVID-19 is caused by the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) with a range of clinical symptoms, including cough, fever, chills, headache, shortness of breath, difficulty breathing, muscle pain, and a loss of smell or taste. Aged individuals with compromised immunity are highly susceptible to COVID-19 and the likelihood of mortality increases with age and the presence of comorbidities such as hypertension, diabetes mellitus, cardiovascular disease, or chronic obstructive pulmonary disease. Emerging evidence suggests that COVID-19 highjacks mitochondria of immune cells, replicates within mitochondrial structures, and impairs mitochondrial dynamics leading to cell death. ABT-199 concentration Mitochondria are the powerhouses of the cell and are largely involved in maintaining cell immunity, homeostasis, and cell survival/death. Increasing evidence suggests that mitochondria from COVID-19 infected cells are highly vulnerable, and vulnerability increases with age. The purpose of our article is to summarize the role of various age-related comorbidities such as diabetes, obesity, and neurological diseases in increasing mortality rates amongst the elderly with COVID-19. Our article also highlights the interaction between coronavirus and mitochondrial dynamics in immune cells. We also highlight the current treatments, lifestyles, and safety measures that can help protect against COVID-19. Further research is urgently needed to understand the molecular mechanisms between the mitochondrial virus and disease progression in COVID-19 patients.Recent investigations demonstrated that genetic factors might play an important role in sporadic Parkinson's disease (sPD). To clarify the specific loci susceptibility to sPD, we analyze the relationship between 30 candidate single nucleotide polymorphisms (SNPs) and sPD in the population of Han ancestry from Chinese mainland (HACM) by using genome-wide association study, sequenom massARRAY, DNA sequence, and biological information analysis. Results showed that the subjects carrying the T allele of rs863108 and rs28499371 exhibited a decreased risk for sPD. The subjects carrying the T allele of rs80315856 exhibited an increased risk for sPD. The A/T genotype of rs863108 and the C/T genotype of rs28499371 were a potential increased risk for sPD, and the G/T genotype of rs80315856 and T/T genotype of rs2270568 were a potential decreased risk for sPD. The minor allele frequency (MAF) of rs80315856 and rs2270568 was higher in sPD. The T allele of rs80315856 and rs2270568 might be a risk locus for sPD. Our data suggested that the alteration of these SNPs might play some roles through changing/affecting LINC01524/LOC105372666, DMRT2/SMARCA2, PLEKHN1, and FLJ23172/FNDC3B genes in the pathogenesis of sPD.
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