The current population of Colombia has a genetic heterogeneity resulting from different migrations from other continents and within the country. In addition, there are small groups in their territory that have remained isolated and therefore have a different genetic pool in relation to that of the neighbouring urban populations. This population stratification must be considered in forensic analysis, being more complex for markers with marked intercontinental differentiation. In this study, population differentiation in Colombian admixed, native, and Afro-descendant populations was evaluated for a group of 38 indels described for forensic use. Allelic frequencies and parameters of forensic relevance were determined in each of the groups defined based on population differentiation analyses. In addition to the differences found between population groups, the results show that the set of 38 indels analysed could be useful in studies of individual identification in Colombia. The exclusion power presented by this set of markers suggests the need for joint use with other markers, being able to complement the STRs in paternity cases. High levels of both power of discrimination and exclusion were found when complementing the 38 HID-indels with a second multiplex, for a total of 83 indels.
Impaired redox homeostasis is a hallmark of end-stage renal disease (ESRD). Oxidative stress is one of the major risk factors associated with increased cardiovascular complications and mortality in this group. Both increased free radical production and reduced antioxidant activity play role in systemic oxidative stress in these patients. Genetic polymorphisms in genes encoding antioxidative enzymes such as glutathione transferases (GST), superoxide dismutase 2 or glutathione peroxidase 1 influence susceptibility towards chronic kidney disease as well as oxidative phenotype and mortality. Thus, individuals with a homozygous deletion of GSTM1 gene have shorter overall and cardiovascular-specific survival in ESRD. Biomarkers of oxidative stress including advanced oxidation protein products, malondialdehyde and cell adhesion molecules (soluble vascular cell adhesion molecule-1 and soluble intercellular adhesion molecule-1) also demonstrated a significant predictive role in terms of overall and cardiovascular survival in ESRD. Very recently a new approach towards testing proteomic biomarkers of endothelial dysfunction in the uremic milieu has been applied. Namely, biomarkers of oxidative stress and expression of a panel of inflammatory markers were studied in human umbilical vein endothelial cells (HUVECs) incubated in uremic serum. Incubation in uremic serum resulted in changes in the expression of a series of arteriosclerosis and atherosclerosis biomarkers including retinol-binding protein 4, regulated on activation, normal T cell expressed and secreted (RANTES), C-reactive protein, angiogenin, dickkopf-1 and platelet factor 4. The biomarker signature consisting of genomic and proteomic biomarkers could enable better monitoring of cardiovascular risk in ESRD patients and stratification into appropriate treatment groups.
Stress, poses a huge problem in today’s era when our lives have paced up and we are hooked up all the time. It can lead to a spectrum of health problems. Computer aided artificial intelligence systems for diagnosis of stress would enable a more objective and consistent diagnosis and decisions. Several parameters like Body temperature, Blood Pressure, muscle tension and stiffness, and heart rate are clear indicators and can be used by sensors to collect data about an individual and predict his stress levels. This stress creates pernicious effects particularly for employees and business owners. When workers hear artificial intelligence, robotizing the workplace doesn’t lend any relaxation, rather creates a sense of insecurity of losing job. Ironically, AI tools may do the opposite, making the workplace more human and keeping work stress at bay. In today’s workplace, AI tools are gaining traction. Chatbots and messaging interfaces for tasks like customer support, and client follow-up, can effectively cut out the unnecessary workload and reduce the burden. Automated repetitive tasks that employees do daily leave no room for them to relax. Rather, it drains out the energy and leads to stress. AI can automate for them thus enabling the employees to harness their intellect and skill set for building emotional intelligence, and social interactions which AI can never automate. AI enabled wearable devices, can analyse, and monitor behaviour and emotions. This can identify employees battling with stress. AI-led workplace stress management can play a significant role in diagnosis and cure of stress This will be key to workplace stress management, as you strive towards building a happy, productive, and future-ready workforce.
Advances in bioinformatics and high-throughput sequencing technologies have significantly increased our capability to explore the human microbiome. 16S ribosomal RNA (rRNA) is sequenced to understand the taxonomic composition of the human microbiome. In this study, bioinformatics analysis of 16S rRNA sequenced data from diseased (Crohn’s Colitis (CC) or Ulcerative Colitis (UC)) and adjacent healthy colon samples was performed by using Quantitative Insights Into Microbial Ecology (QIIME). Further, considering the race-specific information for these samples, a comparison of colon microbiome differences between African-Americans and Caucasians was performed. As a result, two hundred-eight different bacterial species were characterized. However, only fifty-three bacteria were described at the species level. The fraction of non-detrimental bacteria in diseased CC and UC samples was different from adjacent healthy colon samples. Additionally, the microbiome of diseased samples was dominated by oral bacteria belonging to the Phyla Firmicutes (Streptococcus, Staphylococcus, Peptostreptococcus) and Fusobacteria (Fusobacterium). The results also showed differences in the microbiome between African-Americans and Caucasians, indicating potential research focus on health disparities.
Inflammation is a vital part of the immune system’s response to injury and infection. Chronic inflammation and low grade inflammation has been linked to certain diseases such as heart disease, stroke and obesity, and may also lead to autoimmune disorders, such as rheumatoid arthritis (RA) and lupus (SLE). Researchers are still working to understand the implications of chronic inflammation on the body and the mechanisms involved in the process as well as monitoring outcome of drug treatment. Advances in high-throughput molecular technologies have increased investigations into the utility of transcriptomic, proteomic and metabolomic approaches as diagnostic tools for precision medicine [1,2]. Basic blood tests include readily detectable inflammatory markers and central autoantibodies, however, now deep analysis allow more clinical insight biofluids by proteomic profiling of plasma/ serum, extracellular vesicles and global autoantibody profiling. We present recent concepts and present studies investigating inflammatory diseases as well as low grade inflammatory diseases in different biofluids from plasma to synovial fluid and CSF accessing causalities leading to inflammation and pain in autoimmune diseases. High density protein array with more than 1600 antigen spots now allow subtyping of common autoimmune diseases including RA and SLE demonstrating new proteomic profiling of native autoantigens from patient biofluids [3,4]. Prediction of treatment outcome in low grade inflammatory diseases including obesity may be assessed by proteomic and multiplex analysis [5]. Label-free quantitative shotgun proteomics now enable individualized profiling of subjects providing biomarkers indicative of diagnosis and treatment efficacy. Translational biofluid profiling between systemic and local sites of inflammation e.g. plasma enables biomarker analysis and in-depth insight into disease pathology [6,7].
