Alzheimer’s disease (AD) is one of the neurodegenerative disorders, characterized by gradual loss of memory, decline in other cognitive functions and decrease in functional capacity. Increasing age and a positive family history of dementia are the defi nite risk factors of the disease. Molecular analysis of families with early onset of AD (EOAD) has made it possible to identify dominantly acting mutations in genes such as amyloid precursor protein precursor protein and presenilin 1 and 2 (PSEN 1 & PSEN 2). However, the etiology of the late onset of AD (LOAD) is less straightforward than EOAD. The availability of novel genetic tools such as high throughput methods for single nucleotide polymorphism (SNP) genotyping, which simultaneously genotype hundreds of thousands of SNPs using a single SNP array, may facilitate the discovery of genetic infl uences in the disease. These genome-wide association studies have great potential to revolutionize our ability to identify additional genes that contribute to the risk of sporadic AD. It is hoped that the identifi cation of individuals with a high genetic risk of AD will help to develop more rational, cost effective and novel prevention strategies and therapeutic approaches.

Background and Objective: Uric acid is a neuroprotective agent. However, its relationship with ischaemic stroke remains controversial. We analyzed the association between serum uric acid and ischemic stroke and clinical outcome. Methods: The study subject consisted of 550 ischemic stroke patients from the Nizam’s Institute of Health Sciences, Hyderabad, India with 550 matched healthy controls. Serum uric acid levels were estimated, and follow-up interviews conducted with patients. Results: There was a significant association of elevated levels of serum uric acid with stroke and its subtypes except lacunar stroke. Patients with high serum uric acid levels had a significant increased risk of poor outcome. Conclusion: Serum uric acid level is associated with ischemic stroke, and is an independent prognostic factor of poor outcome.

This letter presents an automated obstructive sleep apnoea (OSA) detection method with high accuracy, based on a deep learning framework employing convolutional neural network. The proposed work develops a system that takes single lead electrocardiography signals from patients for analysis and detects the OSA condition of the patient. The results show that the proposed method has some advantages in solving such problems and it outperforms the existing methods significantly. The present scheme eliminates the requirement of separate feature extraction and classification algorithms for the detection of OSA. The proposed network performs both feature learning and classifies the features in a supervised manner. The scheme is computation-intensive, but can achieve very high degree of accuracy—on an average a margin of more than 9% compared to other published literature till date. The method also has a good immunity to the contamination of the signals by noise. Even with pessimistic signal to noise ratio values considered here, the methods already reported are not able to outshine the present method. The software for the algorithm reported here can be a good contender to constitute a module that can be integrated with a portable medical diagnostic system.
Classification ; Electrocardiography ; Humans ; Learning ; Methods ; Noise ; Signal-To-Noise Ratio

The emergence of total drug-resistant tuberculosis (TDRTB) has made the discovery of new therapies for tuberculosis urgent. The cytoplasmic enzymes of peptidoglycan biosynthesis have generated renewed interest as attractive targets for the development of new anti-mycobacterials. One of the cytoplasmic enzymes, uridine diphosphate (UDP)-MurNAc-tripeptide ligase (MurE), catalyses the addition of meso-diaminopimelic acid (m-DAP) into peptidoglycan in Mycobacterium tuberculosis coupled to the hydrolysis of ATP. Mutants of M. tuberculosis MurE were generated by replacing K157, E220, D392, R451 with alanine and N449 with aspartate, and truncating the first 24 amino acid residues at the N-terminus of the enzyme. Analysis of the specific activity of these proteins suggested that apart from the 24 N-terminal residues, the other mutated residues are essential for catalysis. Variations in K(m) values for one or more substrates were observed for all mutants, except the N-terminal truncation mutant, indicating that these residues are involved in binding substrates and form part of the active site structure. These mutant proteins were also tested for their specificity for a wide range of substrates. Interestingly, the mutations K157A, E220A and D392A showed hydrolysis of ATP uncoupled from catalysis. The ATP hydrolysis rate was enhanced by at least partial occupation of the uridine nucleotide dipeptide binding site. This study provides an insight into the residues essential for the catalytic activity and substrate binding of the ATP-dependent MurE ligase. Since ATP-dependent MurE ligase is a novel drug target, the understanding of its function may lead to development of novel inhibitors against resistant forms of M. tuberculosis.
Amino Acid Sequence ; Bacterial Proteins ; chemistry ; genetics ; metabolism ; Catalytic Domain ; Crystallography, X-Ray ; Escherichia coli ; genetics ; Models, Molecular ; Molecular Sequence Data ; Mutation ; Mycobacterium tuberculosis ; enzymology ; Peptide Synthases ; chemistry ; genetics ; metabolism ; Sequence Alignment

INTRODUCTIONRecently, there has been increasing evidence that genetic variation in the angiotensin-converting enzyme (ACE) plays an important role in myocardial infarction. Therefore, the present study was carried out with the aim of investigating the association of the ACE gene insertion/deletion (I /D) polymorphism and its levels in myocardial infarction patients and their first-degree relatives (FDRs).

METHODS206 patients with myocardial infarction, 168 FDRs and 210 control subjects were enrolled in the study. ACE I /D polymorphism was determined using the polymerase chain reaction method. Serum ACE levels were measured using the photometric method.

RESULTSThe DD genotype and ACE activity were significantly higher in patients (p-value is 0.00006 and 0.0001, respectively) and FDRs (p-value is 0.003 and 0.04, respectively) compared with the controls.

CONCLUSIONACE DD genotype and ACE levels are important risk factors for myocardial infarction. This study indicates that the higher frequency of the DD genotype and ACE levels observed in FDRs may increase susceptibility to developing myocardial infarction.

Alleles ; Case-Control Studies ; Chi-Square Distribution ; Confidence Intervals ; Ethnic Groups ; genetics ; Female ; Genetic Predisposition to Disease ; epidemiology ; Genetic Variation ; Genotype ; Humans ; Incidence ; India ; epidemiology ; Male ; Myocardial Infarction ; epidemiology ; genetics ; physiopathology ; Odds Ratio ; Peptidyl-Dipeptidase A ; analysis ; genetics ; Polymorphism, Genetic ; Reference Values