Voice Features as the Diagnostic Marker of Autism

The aim of the study is to determine the acoustic features of voice and speech of children with autism spectrum disorders (ASD) as a possible additional diagnostic criterion. The participants in the study were 95 children with ASD aged 5-16 years, 150 typically development (TD) children, and 103 adults – listening to children’s speech samples. Three types of experimental methods for speech analysis were performed: spectrographic, perceptual by listeners, and automatic recognition. In the speech of children with ASD, the pitch values, pitch range, values of frequency and intensity of the third formant (emotional) leading to the “atypical” spectrogram of vowels are higher than corresponding parameters in the speech of TD children. High values of vowel articulation index (VAI) are specific for ASD children’s speech signals. These acoustic features can be considered as diagnostic marker of autism. The ability of humans and automatic recognition of the psychoneurological state of children via their speech is determined.

Biomarkers in a Post-Stroke Population: Allied to Health Care in Brazil

Stroke affects not only the individual, but has significant impacts on the social and family context. Therefore, it is necessary to know the peculiarities of each region, in order to contribute to regional public health policies effectively. Thus, the present study discusses biomarkers in a post-stroke population, admitted to a stroke unit (U-stroke) of reference in the southern region of Brazil. Biomarkers were analyzed, such as age, length of stay, mortality rate, survival time, risk factors and family history of stroke in patients after ischemic stroke. In this studied population, comparing men and women, it was identified that men were more affected than women, and the average age of women affected was higher, as they also had the highest mortality rate and the shortest hospital stay. The risk factors identified here were according to the global scenario; with systemic arterial hypertension (SAH) being the most frequent and those associated with sedentary lifestyle in women the most frequent (dyslipidemia, heart disease and obesity). In view of this, the importance of studies that characterize populations regionally is evident, strengthening the strategic planning of policies in favor of health care.

The Evaluation of New Generation Cardiovascular Risk Markers in Childhood Obesity

Obesity, as excessive fat accumulation in the body, is a global health problem. The prevalence of obesity and its complications increase due to easy access to high-energy food and decreased physical activity. Cardiovascular diseases (CVDs) constitute a significant part of obesity-related morbidity and mortality. Since the effects of obesity on cardiovascular system may start during childhood without clinical findings, elucidating the mechanisms of cardiovascular changes associated with childhood obesity became more important. In this study, we aimed to investigate some biochemical parameters which may be involved in obesity-related pathologic processes of CVDs. One hundred and seventy-seven children were included in the study, and they were divided into four groups based upon WHO criteria and presence of the metabolic syndrome (MetS): children with normal-BMI, obesity, morbid obesity, and MetS. High-sensitive cardiac troponin T (hs-cTnT), cardiac myosin binding protein C (cMyBP-C), trimethylamine N-oxide (TMAO), soluble tumor necrosis factor-like weak inducer (sTWEAK), chromogranin A (CgA), multimerin-2 levels, and other biochemical parameters were measured in serum samples. Anthropometric measurements and clinical findings of the children were recorded. Statistical analyses were performed. Children with normal-BMI had significantly higher CgA levels than children with obesity, morbid obesity, and MetS (p < 0.05). Cardiac MyBP-C levels of children with MetS were significantly higher than of children with normal-BMI and OB children (p < 0.05). There was no significant difference in hs-cTnT, sTWEAK, TMAO and multimerin-2 between the groups (p>0.05). These results suggested that cMyBP-C and CgA molecules may be involved in the pathogenesis of obesity-related CVDs.

Transcriptomics Analysis on Comparing Non-Small Cell Lung Cancer versus Normal Lung, and Early Stage Compared versus Late-Stages of Non-Small Cell Lung Cancer

Lung cancer is one of the most common malignancies and primary cause of death due to cancer worldwide. Non-small cell lung cancer (NSCLC) is the main subtype in which majority of patients present with advanced-stage disease. Herein, we analyzed differentially expressed genes to find potential biomarkers for lung cancer diagnosis as well as prognostic markers. We used transcriptome data from our 2 NSCLC patients and public data (GSE81089) composing of 8 NSCLC and 10 normal lung tissues. Differentially expressed genes (DEGs) between NSCLC and normal tissue and between early-stage and late-stage NSCLC were analyzed by the DESeq2. Pairwise correlation was used to find the DEGs with false discovery rate (FDR) adjusted p-value £ 0.05 and |log2 fold change| ³ 4 for NSCLC versus normal and FDR adjusted p-value £ 0.05 with |log2 fold change| ³ 2 for early versus late-stage NSCLC. Bioinformatic tools were used for functional and pathway analysis. Moreover, the top ten genes in each comparison group were verified the expression and survival analysis via GEPIA. We found 150 up-regulated and 45 down-regulated genes in NSCLC compared to normal tissues. Many immnunoglobulin-related genes e.g., IGHV4-4, IGHV5-10-1, IGHV4-31, IGHV4-61, and IGHV1-69D were significantly up-regulated. 22 genes were up-regulated, and five genes were down-regulated in late-stage compared to early-stage NSCLC. The top five DEGs genes were KRT6B, SPRR1A, KRT13, KRT6A and KRT5. Keratin 6B (KRT6B) was the most significantly increased gene in the late-stage NSCLC. From GEPIA analysis, we concluded that IGHV4-31 and IGKV1-9 might be used as diagnostic biomarkers, while KRT6B and KRT6A might be used as prognostic biomarkers. However, further clinical validation is needed.

A Hybrid Feature Selection and Deep Learning Algorithm for Cancer Disease Classification

Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

HPTLC Fingerprint Profiling of Protorhus longifolia Methanolic Leaf Extract and Qualitative Analysis of Common Biomarkers

Protorhus longifolia is known as a medicinal plant that has been used traditionally to treat various ailments such as hemiplegic paralysis, blood clotting related diseases, diarrhoea, heartburn, etc. The study reports a High-Performance Thin Layer Chromatography (HPTLC) fingerprint profile of Protorhus longifolia methanolic extract and its qualitative analysis of gallic acid, rutin, and quercetin. HPTLC analysis was achieved using CAMAG HPTLC system equipped with CAMAG automatic TLC sampler 4, CAMAG Automatic Developing Chamber 2 (ADC2), CAMAG visualizer 2, CAMAG Thin Layer Chromatography (TLC) scanner and visionCATS CAMAG HPTLC software. Mobile phase comprising toluene, ethyl acetate, formic acid (21:15:3) was used for qualitative analysis of gallic acid and revealed eight peaks while the mobile phase containing ethyl acetate, water, glacial acetic acid, formic acid (100:26:11:11) for qualitative analysis of rutin and quercetin revealed six peaks. HPTLC sillica gel 60 F254 glass plates (10 × 10) were used as the stationary phase. Gallic acid was detected at the Rf = 0.35; while rutin and quercetin were not evident in the extract. Further studies will be performed to quantify gallic acid in Protorhus longifolia leaves and also identify other biomarkers.

Clinical Utility of Salivary Cytokines for Children with Attention Deficit Hyperactivity Disorder

The goal of this study was to examine the possibility of salivary cytokines for the screening of attention deficit hyperactivity disorder (ADHD) in children. We carried out a case-control study, including 19 children with ADHD and 17 healthy children (controls). A multiplex bead array immunoassay was used to conduct a multi-analysis of 27 different salivary cytokines. Six salivary cytokines (interleukin (IL)-1β, IL-8, IL12p70, granulocyte colony-stimulating factor (G-CSF), interferon gamma (IFN-γ), and vascular endothelial growth factor (VEGF)) were significantly associated with the presence of ADHD (p < 0.05). An informative salivary cytokine panel was developed using VEGF by logistic regression analysis (odds ratio: 0.251). Receiver operating characteristic analysis revealed that assessment of a panel using VEGF showed “good” capability for discriminating between ADHD patients and controls (area under the curve: 0.778). ADHD has been hypothesized to be associated with reduced cerebral blood flow in the frontal cortex, due to reduced VEGF levels. Our study highlights the possibility of utilizing differential salivary cytokine levels for point-of-care testing (POCT) of biomarkers in children with ADHD.

Hormones and Mineral Elements Associated with Osteoporosis in Postmenopausal Women in Eastern Slovakia

Osteoporosis is a multifactorial disease that results in reduced quality of life, causes decreased bone strength, and changes in their microarchitecture. Mostly postmenopausal women are at risk. In our study, we measured anthropometric parameters of postmenopausal women (104 women of control group – CG and 105 women of osteoporotic group - OG) and determined TSH hormone levels and PTH as well as mineral elements - Ca, P, Mg and enzyme alkaline phosphatase. Through the correlation analysis in CG, we have found association based on age and BMI, P and Ca, as well as Mg and Ca; in OG we determined interdependence based on an association of age and BMI, age and Ca. Using the Student's t test, we found significantly important differences in biochemical parameters of Mg (p ˂ 0,001) and TSH (p ˂ 0,05) between CG and OG.

miR-200c as a Biomarker for 5-FU Chemosensitivity in Colorectal Cancer

5-FU is a chemotherapeutic agent that has been used in colorectal cancer (CRC) treatment. However, it is usually associated with the acquired resistance, which decreases the therapeutic effects of 5-FU. miR-200c is involved in chemotherapeutic drug resistance, but its mechanism is not fully understood. In this study, the effect of inhibition of miR-200c in sensitivity of HCT-116 CRC cells to 5-FU was evaluated. HCT-116 cells were transfected with LNA-anti- miR-200c for 48 h. mRNA expression of miR-200c was evaluated using quantitative real- time PCR. The protein expression of phosphatase and tensin homolog (PTEN) and E-cadherin were analyzed by western blotting. Annexin V and propidium iodide staining assay were applied for apoptosis detection. The caspase-3 activation was evaluated by an enzymatic assay. The results showed LNA-anti-miR-200c inhibited the expression of PTEN and E-cadherin protein, apoptosis and activation of caspase 3 compared with control cells. In conclusion, these results suggest that miR-200c as a prognostic marker can overcome to 5-FU chemoresistance in CRC.

Microfluidic Paper-Based Electrochemical Biosensor

A low-cost paper-based microfluidic device (PAD) for the multiplex electrochemical determination of glucose, uric acid, and dopamine in biological fluids was developed. Using wax printing, PAD containing a central zone, six channels, and six detection zones was fabricated, and the electrodes were printed on detection zones using pre-made electrodes template. For each analyte, two detection zones were used. The carbon working electrode was coated with chitosan-BSA (and enzymes for glucose and uric acid). To detect glucose and uric acid, enzymatic reactions were employed. These reactions involve enzyme-catalyzed redox reactions of the analytes and produce free electrons for electrochemical measurement. Calibration curves were linear (R² > 0.980) in the range of 0-80 mM for glucose, 0.09–0.9 mM for dopamine, and 0–50 mM for uric acid, respectively. Blood samples were successfully analyzed by the proposed method.

Mutation Analysis of the ATP7B Gene in 43 Vietnamese Wilson’s Disease Patients

Wilson’s disease (WD) is an autosomal recessive disorder of the copper metabolism, which is caused by a mutation in the copper-transporting P-type ATPase (ATP7B). The mechanism of this disease is the failure of hepatic excretion of copper to bile, and leads to copper deposits in the liver and other organs. The ATP7B gene is located on the long arm of chromosome 13 (13q14.3). This study aimed to investigate the gene mutation in the Vietnamese patients with WD, and make a presymptomatic diagnosis for their familial members. Forty-three WD patients and their 65 siblings were identified as having ATP7B gene mutations. Genomic DNA was extracted from peripheral blood samples; 21 exons and exon-intron boundaries of the ATP7B gene were analyzed by direct sequencing. We recognized four mutations ([R723=; H724Tfs*34], V1042Cfs*79, D1027H, and IVS6+3A>G) in the sum of 20 detectable mutations, accounting for 87.2% of the total. Mutation S105* was determined to have a high rate (32.6%) in this study. The hotspot regions of ATP7B were found at exons 2, 16, and 8, and intron 14, in 39.6 %, 11.6 %, 9.3%, and 7 % of patients, respectively. Among nine homozygote/compound heterozygote siblings of the patients with WD, three individuals were determined as asymptomatic by screening mutations of the probands. They would begin treatment after diagnosis. In conclusion, 20 different mutations were detected in 43 WD patients. Of this number, four novel mutations were explored, including [R723=; H724Tfs*34], V1042Cfs*79, D1027H, and IVS6+3A>G. The mutation S105* is the most prevalent and has been considered as a biomarker that can be used in a rapid detection assay for diagnosis of WD patients. Exons 2, 8, and 16, and intron 14 should be screened initially for WD patients in Vietnam. Based on risk profile for WD, genetic testing for presymptomatic patients is also useful in diagnosis and treatment.

The Role of Chemokine Family, CXCL-10 Urine as a Marker Diagnosis of Active Lung Tuberculosis in HIV/AIDS Patients

Human Immunodeficiency Virus (HIV) pandemic increased significantly worldwide. The rise in cases of HIV/AIDS was also followed by an increase in the incidence of opportunistic infection, with tuberculosis being the most opportunistic infection found in HIV/AIDS and the main cause of mortality in HIV/AIDS patients. Diagnosis of tuberculosis in HIV/AIDS patients is often difficult because of the uncommon symptom in HIV/AIDS patients compared to those without the disease. Thus, diagnostic tools are required that are more effective and efficient to diagnose tuberculosis in HIV/AIDS. CXCL-10/IP-10 is a chemokine that binds to the CXCR3 receptor found in HIV/AIDS patients with a weakened immune system. Tuberculosis infection in HIV/AIDS activates chemokine IP-10 in urine, which is used as a marker for diagnosis of infection. The aim of this study was to prove whether IP-10 urine can be a biomarker diagnosis of active lung tuberculosis in HIV-AIDS patients. Design of this study is a cross sectional study involving HIV/AIDS patients with lung tuberculosis as the subject of this study. Forty-seven HIV/AIDS patients with tuberculosis based on clinical and biochemical laboratory were asked to collect urine samples and IP-10/CXCL-10 urine being measured using ELISA method with 18 healthy human urine samples as control. Forty-seven patients diagnosed as HIV/AIDS were included as a subject of this study. HIV/AIDS were more common in male than in women with the percentage in male 85.1% vs. 14.5% of women. In this study, most diagnosed patients were aged 31-40 years old, followed by those 21-30 years, and > 40 years old, with one case diagnosed at age less than 20 years of age. From the result of the urine IP-10 using ELISA method, there was significant increase of the mean value of IP-10 urine in patients with TB-HIV/AIDS co-infection compared to the healthy control with mean 61.05 pg/mL ± 78.01 pg/mL vs. mean 17.2 pg/mL. Based on this research, there was significant increase of urine IP-10/CXCL-10 in active lung tuberculosis with HIV/AIDS compared to the healthy control. From this finding, it is necessary to conduct further research into whether urine IP-10/CXCL-10 plays a significant role in TB-HIV/AIDS co-infection, which can also be used as a biomarker in the early diagnosis of TB-HIV.

Snails and Fish as Pollution Biomarkers in Lake Manzala and Laboratory C: Laboratory Exposed Snails to Chemical Mixtures

Snails are considered as suitable diagnostic organisms for heavy metal–contaminated sites. Biomphalaria alexandrina snails are used in this work as pollution bioindicators after exposure to chemical mixtures consisted of heavy metals (HM); zinc (Zn), copper (Cu) and lead (Pb); and persistent organic pollutants; Decabromodiphenyl ether 98% (D) and Aroclor 1254 (A). The impacts of these tested chemicals, individual and mixtures, on liver and kidney functions, antioxidant enzymes, complete blood picture, and tissue histology were studied. Results showed that Cu was proved to be the highly toxic against snails than Zn and Pb where LC50 values were 1.362, 213.198 and 277.396 ppm, respectively. Also, B. alexandrina snails exposed to the mixture of HM (¼ LC5 Cu, Pb and Zn) showed the highest bioaccumulation of Cu and Zn in their whole tissue, the most significant increase in AST, ALT & ALP activities and the highest significant levels of total protein, albumin and globulin. Results showed significant alterations in CAT activity in snail tissue extracts while snail samples exposed to most experimental tests showed significant increase in GST activity. Snail samples that exposed to HM mixtures showed a significant decrease in total hemocytes count while snail samples that exposed to mixtures containing A & D showed a significant increase in total hemocytes and Hyalinocytes. Histopathological alterations in snail samples exposed to individual HM and their mixtures for 4 weeks showed degeneration, edema, hyper trophy and vaculation in head-foot muscle, degeneration and necrotic changes in the digestive gland and accumulation in most tested organs. Also, the hermaphrodite gland showed mature ova with irregular shape and reduction in sperm number. In conclusion, the resulted damage and alterations in B. alexandrina studied parameters can be used as bioindicators to the presence of pollutants in its habitats.

Toxicological and Histopathological Studies on the Effect of Tartrazine in Male Albino Rats

Tartrazine is an organic azo dyes food additive widely used in foods, drugs, and cosmetics. The present study aimed to investigate the toxic effects of tartrazine on kidneys and liver biomarkers in addition to the investigation of oxidative stress and change of histopathological structure of liver and kidneys in 30 male rats. Tartrazine was orally administrated daily at dose 200 mg/ kg bw (1/ 10 LD50) for sixty days. Serum and tissue samples were collected at the end of the experiment to investigate the underlying mechanism of tartrazine through assessment oxidative stress (Glutathione (GSH), Superoxide dismutase (SOD) and malondialdehyde (MDA) and biochemical markers (alanine aminotransferase (ALT), aspartate aminotransferase (AST), Total protein and Urea). Liver and kidneys tissue were collected and preserved in 10% formalin for histopathological examination. The obtained values were statistically analyzed by one way analysis of variance (ANOVA) followed by multiple comparison test. Biochemical analysis revealed that tartrazine induced significant increase in serum ALT, AST, total protein, urea level compared to control group. Tartrazine showed significant decrease in liver GSH and SOD where their values when compared to control group. Tartrazine induced increase in liver MDA compared to control group. Histopathology of the liver showed diffuse vacuolar degeneration in hepatic parenchyma, the portal area showed sever changes sever in hepatoportal blood vessels and in the bile ducts. The kidneys showed degenerated tubules at the cortex together with mononuclear leucocytes inflammatory cells infiltration. There is perivascular edema with inflammatory cell infiltration surrounding the congested and hyalinized vascular wall of blood vessel. The present study indicates that the subchronic effects of tartrazine have a toxic effect on the liver and kidneys together with induction of oxidative stress by formation of free radicals. Therefore, people should avoid the hazards of consuming tartrazine.

Snails and Fish as Pollution Biomarkers in Lake Manzala and Laboratory B: Lake Manzala Fish

This work aimed to examine Oreochromis niloticus fish from Lake Manzala in Port Said, Dakahlya and Damietta governorates, Egypt, as a bio-indicator for the lake water pollution through recording alterations in their hematological, physiological, and histopathological parameters. All fish samples showed a significant increase in levels of alkaline phosphatase (ALP), creatinine and glutathione-S-transferase (GST); only Dakahlya samples showed a significant increase (p

Metabolomics Profile Recognition for Cancer Diagnostics

Metabolomics has become a rising field of research for various diseases, particularly cancer. Increases or decreases in metabolite concentrations in the human body are indicative of various cancers. Further elucidation of metabolic pathways and their significance in cancer research may greatly spur medicinal discovery. We analyzed the metabolomics profiles of lung cancer. Thirty-three metabolites were selected as significant. These metabolites are involved in 37 metabolic pathways delivered by MetaboAnalyst software. The top pathways are glyoxylate and dicarboxylate pathway (its hubs are formic acid and glyoxylic acid) along with Citrate cycle pathway followed by Taurine and hypotaurine pathway (the hubs in the latter are taurine and sulfoacetaldehyde) and Glycine, serine, and threonine pathway (the hubs are glycine and L-serine). We studied interactions of the metabolites with the proteins involved in cancer-related signaling networks, and developed an approach to metabolomics biomarker use in cancer diagnostics. Our analysis showed that a significant part of lung-cancer-related metabolites interacts with main cancer-related signaling pathways present in this network: PI3K–mTOR–AKT pathway, RAS–RAF–ERK1/2 pathway, and NFKB pathway. These results can be employed for use of metabolomics profiles in elucidation of the related cancer proteins signaling networks.

Automatic Threshold Search for Heat Map Based Feature Selection: A Cancer Dataset Analysis

Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Use of Locomotor Activity of Rainbow Trout Juveniles in Identifying Sublethal Concentrations of Landfill Leachate

Landfill waste is a common problem as it has an economic and environmental impact even if it is closed. Landfill waste contains a high density of various persistent compounds such as heavy metals, organic and inorganic materials. As persistent compounds are slowly-degradable or even non-degradable in the environment, they often produce sublethal or even lethal effects on aquatic organisms. The aims of the present study were to estimate sublethal effects of the Kairiai landfill (WGS: 55°55‘46.74“, 23°23‘28.4“) leachate on the locomotor activity of rainbow trout Oncorhynchus mykiss juveniles using the original system package developed in our laboratory for automated monitoring, recording and analysis of aquatic organisms’ activity, and to determine patterns of fish behavioral response to sublethal effects of leachate. Four different concentrations of leachate were chosen: 0.125; 0.25; 0.5 and 1.0 mL/L (0.0025; 0.005; 0.01 and 0.002 as part of 96-hour LC50, respectively). Locomotor activity was measured after 5, 10 and 30 minutes of exposure during 1-minute test-periods of each fish (7 fish per treatment). The threshold-effect-concentration amounted to 0.18 mL/L (0.0036 parts of 96-hour LC50). This concentration was found to be even 2.8-fold lower than the concentration generally assumed to be “safe” for fish. At higher concentrations, the landfill leachate solution elicited behavioral response of test fish to sublethal levels of pollutants. The ability of the rainbow trout to detect and avoid contaminants occurred after 5 minutes of exposure. The intensity of locomotor activity reached a peak within 10 minutes, evidently decreasing after 30 minutes. This could be explained by the physiological and biochemical adaptation of fish to altered environmental conditions. It has been established that the locomotor activity of juvenile trout depends on leachate concentration and exposure duration. Modeling of these parameters showed that the activity of juveniles increased at higher leachate concentrations, but slightly decreased with the increasing exposure duration. Experiment results confirm that the behavior of rainbow trout juveniles is a sensitive and rapid biomarker that can be used in combination with the system for fish behavior monitoring, registration and analysis to determine sublethal concentrations of pollutants in ambient water. Further research should be focused on software improvement aimed to include more parameters of aquatic organisms’ behavior and to investigate the most rapid and appropriate behavioral responses in different species. In practice, this study could be the basis for the development and creation of biological early-warning systems (BEWS).

Biosensor Design through Molecular Dynamics Simulation

The beginning of 21st century has witnessed new advancements in the design and use of new materials for biosensing applications, from nano to macro, protein to tissue. Traditional analytical methods lack a complete toolset to describe the complexities introduced by living systems, pathological relations, discrete hierarchical materials, cross-phase interactions, and structure-property dependencies. Materiomics – via systematic molecular dynamics (MD) simulation – can provide structureprocess- property relations by using a materials science approach linking mechanisms across scales and enables oriented biosensor design. With this approach, DNA biosensors can be utilized to detect disease biomarkers present in individuals’ breath such as acetone for diabetes. Our wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) has successfully detected trace amount of various chemicals in vapor differentiated by pattern recognition. Here, we present how MD simulation can revolutionize the way of design and screening of DNA aptamers for targeting biomarkers related to oral diseases and oral health monitoring. It demonstrates great potential to be utilized to build a library of DNDA sequences for reliable detection of several biomarkers of one specific disease, and as well provides a new methodology of creating, designing, and applying of biosensors.

Down-Regulated Gene Expression of GKN1 and GKN2 as Diagnostic Markers for Gastric Cancer

Gastric Cancer (GC) has high morbidity and fatality rate in various countries. It is still one of the most frequent and deadly diseases. Gastrokine1 (GKN1) and gastrokine2 (GKN2) genes are highly expressed in the normal stomach epithelium and play important roles in maintaining the integrity and homeostasis of stomach mucosal epithelial cells. In this study, 47 paired samples that were grouped according to the types of gastric cancer and the clinical characteristics of the patients, including gender and average of age. They were investigated with gene expression analysis and mutation screening by monitoring RT-PCR, SSCP and nucleotide sequencing techniques. Both GKN1 and GKN2 genes were observed significantly reduced found by (Wilcoxon signed rank test; p