Coronaviruses (CoVs) are a large family of viruses that are common in many animal species, including camels, cattle, cats and bats. Animal CoVs, such as Middle East respiratory syndrome-CoV, severe acute respiratory syndrome (SARS)-CoV, and the new virus named SARS-CoV-2, rarely infect and spread among humans. On January 30, 2020, the International Health Regulations Emergency Committee of the World Health Organisation declared the outbreak of the resulting disease from this new CoV called 'COVID-19', as a 'public health emergency of international concern'. This global pandemic has affected almost the whole planet and caused the death of more than 315,131 patients as of the date of this article. In this context, publishers, journals and researchers are urged to research different domains and stop the spread of this deadly virus. The increasing interest in developing artificial intelligence (AI) applications has addressed several medical problems. However, such applications remain insufficient given the high potential threat posed by this virus to global public health. This systematic review addresses automated AI applications based on data mining and machine learning (ML) algorithms for detecting and diagnosing COVID-19. We aimed to obtain an overview of this critical virus, address the limitations of utilising data mining and ML algorithms, and provide the health sector with the benefits of this technique. We used five databases, namely, IEEE Xplore, Web of Science, PubMed, ScienceDirect and Scopus and performed three sequences of search queries between 2010 and 2020. Accurate exclusion criteria This article is part of the Topical Collection on Systems-Level Quality Improvement * A. A.

Renal tubulointerstitium plays an important role in the development and progression of diabetic nephropathy. The aim of this study was to assess serum cystatin C and 2 renal tubular enzymes, neutrophil gelatinase associated lipocalin (NGAL) and N-acetyl-beta-D-glucosaminidase (NAG), as screening markers for early renal dysfunction in patients with type 2 diabetes mellitus (T2DM). ROC curve analysis showed that urinary NAG is the most sensitive marker of microalbuminuria and early renal damage with sensitivity of 83.3%, while serum cystatin C was the most sensitive and specific marker of macroalbuminuria and damage progress with sensitivity of 70.8% and specificity of 83.3% versus 70.6% and 83.3% for uNGAL; and 64.7% and 66.7% for NAG, respectively. Our data indicate that urinary NAG is the most sensitive marker for early renal damage in diabetic patients. However, for damage progress, serum cystatin C is the most sensitive and specific marker for follow-up and monitoring renal dysfunction.

Nitric oxide production is reduced in renal disease, partially due to decreased endothelial nitric oxide production. Evidence indicates that nitric oxide deficiency contributes to cardiovascular events and progression of kidney damage. A polymorphism in intron 4 of the endothelial constitutive nitric oxide synthase (ecNOS) gene is a candidate gene in cardiovascular and renal diseases. We investigated a potential involvement of this polymorphism in chronic renal failure. A case-control study involved 78 children with chronic kidney disease (CKD) and 30 healthy controls. All participants were genotyped for the ecNOS4 polymorphism by the polymerase chain reaction (PCR). Dialyzed (maintenance hemodialysis) and conservative treatment children had significantly higher frequency of the aa genotype and ecNOS4a allele (P<0.05) compared with controls. The combined genotype aa+ab vs. bb comparison validated that a allele is a high-risk allele for end-stage renal disease (ESRD) (P<0.05). Serum nitric oxide level was found to be lower in carriers of the ecNOS 4a allele than in noncarriers (100.29±27.32 vs. 152.73±60.39 μmol/l, P=0.04). Interestingly, 85.95% of the ecNOS 4a allele ESRD patients were found hypertensive in comparison to the 60.67% patients of non noncarriers (bb genotype) (P=0.04). Also, 35.90% of the ecNOS 4a allele ESRD patients were found to have cardiovascular disease in comparison to the 5.13% patients of noncarriers (bb genotype) (P=0.01). On multiple linear regression analysis, a allele was independently associated with hypertension (P=0.03). There was a significantly higher frequency of the ecNOS4a allele carriers among CKD children, both on MHD and conservative treatment than in controls. This suggests that the ecNOS gene polymorphism may be associated with an increased risk of chronic renal failure.

Aim and MethodsWe investigated the association between polymorphisms of the angiotensin converting enzyme-1 (ACE-1) and angiotensin II type one receptor (AT1RA1166C) genes and the causation of renal disease in 76 advanced chronic kidney disease (CKD) pediatric patients undergoing maintenance hemodialysis (MHD) or conservative treatment (CT). Serum ACE activity and creatine kinase-MB fraction (CK-MB) were measured in all groups. Left ventricular mass index (LVMI) was calculated according to echocardiographic measurements. Seventy healthy controls were also genotyped.ResultsThe differences of D allele and DI genotype of ACE were found significant between MHD group and the controls (p = 0.0001). ACE-activity and LVMI were higher in MHD, while CK-MB was higher in CT patients than in all other groups. The combined genotype DD v/s ID+II comparison validated that DD genotype was a high risk genotype for hypertension .~89% of the DD CKD patients were found hypertensive in comparison to ~ 61% of patients of non DD genotype(p = 0.02). The MHD group showed an increased frequency of the C allele and CC genotype of the AT1RA1166C polymorphism (P = 0.0001). On multiple linear regression analysis, C-allele was independently associated with hypertension (P = 0.04).ConclusionACE DD and AT1R A/C genotypes implicated possible roles in the hypertensive state and in renal damage among children with ESRD. This result might be useful in planning therapeutic strategies for individual patients.

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