Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations

Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biology. However, these methods have been less frequently used with empirical population genetics data. In this study, we developed a new combined approach of data analysis using microsatellite marker data from our previous studies of olive populations using machine learning algorithms. Herein, 267 olive accessions of various origins including 21 reference cultivars, 132 local ecotypes, and 37 wild olive specimens from the Iranian plateau, together with 77 of the most represented Mediterranean varieties were investigated using a finely selected panel of 11 microsatellite markers. We organized data in two ‘4-targeted’ and ‘16-targeted’ experiments. A strategy of assaying different machine based analyses (i.e. data cleaning, feature selection, and machine learning classification) was devised to identify the most informative loci and the most diagnostic alleles to represent the population and the geography of each olive accession. These analyses revealed microsatellite markers with the highest differentiating capacity and proved efficiency for our method of clustering olive accessions to reflect upon their regions of origin. A distinguished highlight of this study was the discovery of the best combination of markers for better differentiating of populations via machine learning models, which can be exploited to distinguish among other biological populations.     

GC-MS Based Plasma Metabolomics for Identification of Candidate Biomarkers for Hepatocellular Carcinoma in Egyptian Cohort

This study evaluates changes in metabolite levels in hepatocellular carcinoma (HCC) cases vs. patients with liver cirrhosis by analysis of human blood plasma using gas chromatography coupled with mass spectrometry (GC-MS). Untargeted metabolomic analysis of plasma samples from participants recruited in Egypt was performed using two GC-MS platforms: a GC coupled to single quadruple mass spectrometer (GC-qMS) and a GC coupled to a time-of-flight mass spectrometer (GC-TOFMS). Analytes that showed statistically significant changes in ion intensities were selected using ANOVA models. These analytes and other candidates selected from related studies were further evaluated by targeted analysis in plasma samples from the same participants as in the untargeted metabolomic analysis. The targeted analysis was performed using the GC-qMS in selected ion monitoring (SIM) mode. The method confirmed significant changes in the levels of glutamic acid, citric acid, lactic acid, valine, isoleucine, leucine, alpha tocopherol, cholesterol, and sorbose in HCC cases vs. patients with liver cirrhosis. Specifically, our findings indicate up-regulation of metabolites involved in branched-chain amino acid (BCAA) metabolism. Although BCAAs are increasingly used as a treatment for cancer cachexia, others have shown that BCAA supplementation caused significant enhancement of tumor growth via activation of mTOR/AKT pathway, which is consistent with our results that BCAAs are up-regulated in HCC.     

Unmet need for hypercholesterolemia care in 35 low- and middle-income countries: A cross-sectional study of nationally representative surveys

BackgroundAs the prevalence of hypercholesterolemia is increasing in low- and middle-income countries (LMICs), detailed evidence is urgently needed to guide the response of health systems to this epidemic. This study sought to quantify unmet need for hypercholesterolemia care among adults in 35 LMICs.Methods and findingsWe pooled individual-level data from 129,040 respondents aged 15 years and older from 35 nationally representative surveys conducted between 2009 and 2018. Hypercholesterolemia care was quantified using cascade of care analyses in the pooled sample and by region, country income group, and country. Hypercholesterolemia was defined as (i) total cholesterol (TC) ≥240 mg/dL or self-reported lipid-lowering medication use and, alternatively, as (ii) low-density lipoprotein cholesterol (LDL-C) ≥160 mg/dL or self-reported lipid-lowering medication use. Stages of the care cascade for hypercholesterolemia were defined as follows: screened (prior to the survey), aware of diagnosis, treated (lifestyle advice and/or medication), and controlled (TC <200 mg/dL or LDL-C <130 mg/dL). We further estimated how age, sex, education, body mass index (BMI), current smoking, having diabetes, and having hypertension are associated with cascade progression using modified Poisson regression models with survey fixed effects.High TC prevalence was 7.1% (95% CI: 6.8% to 7.4%), and high LDL-C prevalence was 7.5% (95% CI: 7.1% to 7.9%). The cascade analysis showed that 43% (95% CI: 40% to 45%) of study participants with high TC and 47% (95% CI: 44% to 50%) with high LDL-C ever had their cholesterol measured prior to the survey. About 31% (95% CI: 29% to 33%) and 36% (95% CI: 33% to 38%) were aware of their diagnosis; 29% (95% CI: 28% to 31%) and 33% (95% CI: 31% to 36%) were treated; 7% (95% CI: 6% to 9%) and 19% (95% CI: 18% to 21%) were controlled. We found substantial heterogeneity in cascade performance across countries and higher performances in upper-middle-income countries and the Eastern Mediterranean, Europe, and Americas. Lipid screening was significantly associated with older age, female sex, higher education, higher BMI, comorbid diagnosis of diabetes, and comorbid diagnosis of hypertension. Awareness of diagnosis was significantly associated with older age, higher BMI, comorbid diagnosis of diabetes, and comorbid diagnosis of hypertension. Lastly, treatment of hypercholesterolemia was significantly associated with comorbid hypertension and diabetes, and control of lipid measures with comorbid diabetes. The main limitations of this study are a potential recall bias in self-reported information on received health services as well as diminished comparability due to varying survey years and varying lipid guideline application across country and clinical settings.ConclusionsCascade performance was poor across all stages, indicating large unmet need for hypercholesterolemia care in this sample of LMICs—calling for greater policy and research attention toward this cardiovascular disease (CVD) risk factor and highlighting opportunities for improved prevention of CVD.

Maja Marcus and colleagues use nationally-representative surveys conducted between 2009 and 2018 to investigate the unmet need for hypercholesterolemia care in 35 low- and middle-income countries.     

Transient expression of recombinant tissue plasminogen activator (rt-PA) gene in cucurbit plants using viral vector

Objective

To use a transient expression system to express a truncated human tissue plasminogen activator (K2S) gene in cucurbit plants.

Results

The recombinant tissue plasminogen activator protein (K2S form) was expressed in active form in cucurbit plants. Its molecular weight was 43 kDa. The plant-derived rt-PA was determined using goat anti-rabbit antibody by western blotting. Among the infected lines, the highest expression of rt-PA was 62 ng/100 mg per leaf tissue as measured by ELISA. The enzymatic activity of the plant-derived rt-PA was 0.8 IU/ml.

Conclusions

The K25 form of rt-PA was expressed for the first time using the viral expression system. Plant-derived rt-PA showed similar potency to commercially-available PA.

     

High-pressure processing of apple juice: kinetics of pectin methyl esterase inactivation

High-pressure (HP) inactivation kinetics of pectin methyl esterase (PME) in apple juice were evaluated. Commercial PME was dispensed in clarified apple juice, sealed in dual peel sterilizable plastic bags, and subjected to different high-pressure processing conditions (200-400 MPa, 0-180 min). Residual enzyme activity was determined by a titration method estimating the rate of free carboxyl group released by the enzyme acting on pectin substrate at pH 7.5 (30 degrees C). The effects of pressure level and pressure holding time on enzyme inactivation were significant (p < 0.05). PME from the microbial source was found to be more resistant (p < 0.05) to pressure inactivation than PME from the orange peel. Almost a full decimal reduction in the activity of commercial PME was achieved by HP treatment at 400 MPa for 25 min. Inactivation kinetics were evaluated on the basis of a dual effect model involving a pressure pulse effect and a first-order rate model, and the pressure sensitivity of rate constants was modeled by using the z-value concept.     

Ion annotation-assisted analysis of LC-MS based metabolomic experiment

Background

Analysis of multiple LC-MS based metabolomic studies is carried out to determine overlaps and differences among various experiments. For example, in large metabolic biomarker discovery studies involving hundreds of samples, it may be necessary to conduct multiple experiments, each involving a subset of the samples due to technical limitations. The ions selected from each experiment are analyzed to determine overlapping ions. One of the challenges in comparing the ion lists is the presence of a large number of derivative ions such as isotopes, adducts, and fragments. These derivative ions and the retention time drifts need to be taken into account during comparison.

Results

We implemented an ion annotation-assisted method to determine overlapping ions in the presence of derivative ions. Following this, each ion is represented by the monoisotopic mass of its cluster. This mass is then used to determine overlaps among the ions selected across multiple experiments.

Conclusion

The resulting ion list provides better coverage and more accurate identification of metabolites compared to the traditional method in which overlapping ions are selected on the basis of individual ion mass.

     

Pre-existing diabetes mellitus and adverse pregnancy outcomes

ABSTRACT: BACKGROUND: Pregnancies complicated by pre-existing diabetes mellitus (PDM) are associated with a high rate of adverse outcomes, including an increased miscarriage rate, preterm delivery, preeclampsia, perinatal mortality and congenital malformations; compared to the background population. The objectives of this study are to determine the prevalence of PDM and to investigate the maternal and the neonatal outcomes of women with PDM. METHODS: This is a retrospective cohort study for women who delivered in King Khalid University Hospital (KKUH) during the period of January 1st to the 31st of December 2008. The pregnancy outcomes of the women with PDM were compared to the outcomes of all non-diabetic women who delivered during the same study period. RESULTS: A total of 3157 deliveries met the inclusion criteria. Out of the study population 116 (3.7%) women had PDM. There were 66 (57%) women with T1DM and 50 (43%) women with T2DM. Compared to non-diabetic women those with PGMD were significantly older, of higher parity, and they had more previous miscarriages. Women with PDM were more likely to be delivered by emergency cesarean section (C/S), OR 2.67, 95% confidence intervals (CI) (1.63-4.32), P < 0.001, or elective C/S, OR 6.73, 95% CI (3.99-11.31), P < 0.001. The neonates of the mothers with PDM were significantly heavier, P < 0.001; and more frequently macrosomic; OR 3.97, 95% CI (2.03-7.65), P = 0.002. They more frequently have APGAR scores <7 in 5 minutes, OR 2.61, 95% CI (0.89-7.05), P 0.057 and more likely to be delivered at <37 gestation weeks, OR 2.24, 95% CI (1.37- 3.67), P 0.003. The stillbirth rate was 2.6 times more among the women with PDM group; however the difference did not reach statistical significance, P 0.084. CONCLUSION: PDM is associated with increased risk for C/S delivery, macrosomia, stillbirth, preterm delivery and low APGAR scores at 5 min.     

The role of catecholamines in mesenchymal stem cell fate

Mesenchymal stem cells (MSCs) are multipotent stem cells found in many adult tissues, especially bone marrow (BM) and are capable of differentiation into various lineage cells such as osteoblasts, adipocytes, chondrocytes and myocytes. Moreover, MSCs can be mobilized from connective tissue into circulation and from there to damaged sites to contribute to regeneration processes. MSCs commitment and differentiation are controlled by complex activities involving signal transduction through cytokines and catecholamines. There has been an increasing interest in recent years in the neural system, functioning in the support of stem cells like MSCs. Recent efforts have indicated that the catecholamine released from neural and not neural cells could be affected characteristics of MSCs. However, there have not been review studies of most aspects involved in catecholamines-mediated functions of MSCs. Thus, in this review paper, we will try to describe the current state of catecholamines in MSCs destination and discuss strategies being used for catecholamines for migration of these cells to damaged tissues. Then, the role of the nervous system in the induction of osteogenesis, adipogenesis, chondrogenesis and myogenesis from MSCs is discussed. Recent progress in studies of signaling transduction of catecholamines in determination of the final fate of MSCs is highlighted. Hence, the knowledge of interaction between MSCs with the neural system could be applied towards the development of new diagnostic and treatment alternatives for human diseases.