EA15, MIR22, LINC00472 as diagnostic markers for diabetic kidney disease

This study aimed to investigate the molecular mechanisms of diabetic kidney disease (DKD) and to explore new potential therapeutic strategies and biomarkers for DKD. First we analyzed the differentially expressed changes between patients with DKD and the control group using the chip data in Gene Expression Omnibus (GEO) database. Then the gene chip was subjected to be annotated again, so as to screen long noncoding RNAs (lncRNAs) and study expression differences of these lncRNAs in DKD and controlled samples. At last, the function of the differential lncRNAs was analyzed. A total of 252 lncRNAs were identified, and 14 were differentially expressed. In addition, there were 1,629 differentially expressed messenger RNAs (mRNAs) genes, and proliferation and apoptosis adapter protein 15 (PEA15), MIR22, and long intergenic nonprotein coding RNA 472 ( LINC00472) were significantly differentially expressed in DKD samples. Through functional analysis of the encoding genes coexpressed by the three lncRNAs, we found these genes were mainly enriched in type 1 diabetes and autoimmune thyroid disease pathways, whereas in Gene Ontology (GO) function classification, they were also mainly enriched in the immune response, type I interferon signaling pathways, interferon-γ mediated signaling pathways, and so forth. To summary, we identified EA15, MIR22, and LINC00472 may serve as the potential diagnostic markers of DKD.     

Diagnostic biomarker and therapeutic target applications of miR-326 in cancers: A systematic review

MicroRNAs (miRNAs) are endogenous mediators of RNA interference and have key roles in the modulation of gene expression under healthy, inflamed, stimulated, carcinogenic, or other cells, and tissues of a pathological state. Many studies have proved the association between miRNAs and cancer. The role of miR-326 as a tumor suppressor miRNA in much human cancer confirmed. We will explain the history and the role of miRNAs changes, especially miR-326 in cancers and other pathological conditions. Attuned with these facts, this review highlights recent preclinical and clinical research performed on miRNAs as novel promising diagnostic biomarkers of patients at early stages, prediction of prognosis, and monitoring of the patients in response to treatment. All related publications retrieved from the PubMed database, with keywords such as epigenetic, miRNA, microRNA, miR-326, cancer, diagnostic biomarker, and therapeutic target similar terms from 1899 to 2018 with limitations in the English language. Recently, researchers have focused on the impacts of miRNAs and their association in inflammatory, autoinflammatory, and cancerous conditions. Recent studies have suggested a major pathogenic role in cancers and autoinflammatory diseases. Investigations have explained the role of miRNAs in cancers, autoimmunity, and autoinflammatory diseases, and so on. The miRNA-326 expression has an important role in cancer conditions and other diseases.     

Feeding ecological knowledge: the underutilised power of faecal DNA approaches for carnivore diet analysis

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Introducing “best single template” models as reference baseline for the Continuous Automated Model Evaluation (CAMEO)

Critical blind assessment of structure prediction techniques is crucial for the scientific community to establish the state of the art, identify bottlenecks, and guide future developments. In Critical Assessment of Techniques in Structure Prediction (CASP), human experts assess the performance of participating methods in relation to the difficulty of the prediction task in a biennial experiment on approximately 100 targets. Yet, the development of automated computational modeling methods requires more frequent evaluation cycles and larger sets of data. The “Continuous Automated Model EvaluatiOn (CAMEO)” platform complements CASP by conducting fully automated blind prediction evaluations based on the weekly pre-release of sequences of those structures, which are going to be published in the next release of the Protein Data Bank (PDB). Each week, CAMEO publishes benchmarking results for predictions corresponding to a set of about 20 targets collected during a 4-day prediction window. CAMEO benchmarking data are generated consistently for all methods at the same point in time, enabling developers to cross-validate their method's performance, and referring to their results in publications. Many successful participants of CASP have used CAMEO—either by directly benchmarking their methods within the system or by comparing their own performance to CAMEO reference data. CAMEO offers a variety of scores reflecting different aspects of structure modeling, for example, binding site accuracy, homo-oligomer interface quality, or accuracy of local model confidence estimates. By introducing the "bestSingleTemplate" method based on structure superpositions as a reference for the accuracy of 3D modeling predictions, CAMEO facilitates objective comparison of techniques and fosters the development of advanced methods.     

Predicting CO2 adsorption and reactivity on transition metal surfaces using popular density functional theory methods

ABSTRACT

In this work, with Ni (110) as a model catalyst surface and CO₂ as an adsorbate, a performance study of Density Functional Theory methods (functionals) is performed. CO being a possible intermediate in CO₂ conversion reactions, binding energies of both, CO₂ and CO, are calculated on the Ni surface and are compared with experimental data. OptPBE-vdW functional correctly predicts CO₂ binding energy on Ni (?62?kJ/mol), whereas CO binding energy is correctly predicted by the rPBE-vdW functional (?138?kJ/mol). The difference in computed adsorption energies by different functionals is attributed to the calculation of gas phase CO₂. Three alternate reaction systems based on a different number of C=O double bonds present in the gas phase molecule are considered to replace CO₂. The error in computed adsorption energy is directly proportional to the number of C=O double bonds present in the gas phase molecule. Additionally, both functionals predict similar carbon–oxygen activation barrier (40?kJ/mol) and equivalent C1s shifts for probe species (?2.6?eV for CCH₃ and +1.5?eV CO₃^?), with respect to adsorbed CO₂. Thus, by including a correction factor of 28?kJ/mol for the computed CO₂ gas phase energy, we suggest using rPBE-vdW functional to investigate CO₂ conversion reactions on different metals.     

Influence of non-bonded parameters on the quality of NMR structures: A new force field for NMR structure calculation

The effects of different non-bonded parameters of force fields for NMR structure calculation on the quality of the resulting NMR solution structures were investigated using Interleukin 4 as a model system. NMR structure ensembles were calculated with an ab initio protocol using torsion angle dynamics. The calculations were repeated with five different non-bonded energy functions and parameters. The resulting ensembles were compared with the available X-ray structures, and their quality was assessed with common structure validation programs. In addition, the impact of torsion angle restraints and dihedral energy terms for the sidechains and the backbone was studied. The further improvement of the quality by refinement in explicit solvent was demonstrated. The optimal parameters, including those necessary for water refinement, are available in the new version of the PARALLHDG force field.     

Sampling accuracy of reef resource inventory technique

A new technique called the reef resource inventory (RRI) was developed to map the distribution and abundance of benthos and substratum on reefs. The rapid field sampling technique uses divers to visually estimate the percentage cover of categories of benthos and substratum along 2×20 m plotless strip-transects positioned randomly over the tops, and systematically along the edge of reefs. The purpose of this study was to compare the relative sampling accuracy of the RRI against the line intercept transect technique (LIT), an international standard for sampling reef benthos and substratum. Analysis of paired sampling with LIT and RRI at 51 sites indicated sampling accuracy was not different (P>0.05) for 8 of the 12 benthos and substratum categories used in the study. Significant differences were attributed to small-scale patchiness and cryptic coloration of some benthos; effects associated with sampling a sparsely distributed animal along a line versus an area; difficulties in discriminating some of the benthos and substratum categories; and differences due to visual acuity since LIT measurements were taken by divers close to the seabed whereas RRI measurements were taken by divers higher in the water column. The relative cost efficiency of the RRI technique was at least three times that of LIT for all benthos and substratum categories and as much as 10 times higher for two categories. These results suggest that the RRI can be used to obtain reliable and accurate estimates of relative abundance of broad categories of reef benthos and substratum.

Combined Psychophysiological Assessment of ADHD: A Pilot Study of Bayesian Probability Approach Illustrated by Appraisal of ADHD in Female College Students

Manifestations of ADHD are observed at both psychological and physiological levels and assessed via various psychometric, EEG, and imaging tests. However, no test is 100% accurate in its assessment of ADHD. This study introduces a stochastic assessment combining psychometric tests with previously reported (Consistency Index) and newly developed (Alpha Blockade Index) EEG-based physiological markers of ADHD. The assessment utilizes classical Bayesian inference to refine after each step the probability of ADHD of each individual. In a pilot study involving six college females with ADHD and six matched controls, the assessment achieved correct classification for all ADHD and non-ADHD participants. In comparison, the classification of ADHD versus non-ADHD participants was < 85% for any one of the tests separately. The procedure significantly improved the score separation between ADHD versus non-ADHD groups. The final average probabilities for ADHD were 76% for the ADHD group and 8% for the control group. These probabilities correlated (r = .87) with the Brown ADD scale and (r = .84) with the ADHD-Symptom Inventory used for the screening of the participants. We conclude that, although each separate test was not completely accurate, a combination of several tests classified correctly all ADHD and all non-ADHD participants. The application of the proposed assessment is not limited to the specific tests used in this study--the assessment represents a general paradigm capable of accommodating a variety of ADHD tests into a single diagnostic assessment.