Metabolic effects of glucose deprivation and of various sugars in normal and transformed fibrobalst cell lines.

The sugar composition of the growth medium influenced the $\text{NAD}{}^{\mathrm{+}}\text{NADH}$ ratio, pyruvate and lactate production, and ATP levels in both normal and transformed fibroblast cell lines growing in tissue culture. Removal of glucose led to a rapid three- to fourfold rise in the $\text{NAD}{}^{\mathrm{+}}\text{NADH}$ ratio, followed by a slower decline in the content of ATP. However, there was no change in the adenylate energy charge [$\text{(}\text{ATP}\text{+}\text{1}\text{2}\text{ADP}\text{)/(}\text{ATP + ADP + AMP}\text{)}$] over a 2-h period. The $\text{NAD}{}^{\mathrm{+}}\text{NADH}$ ratio was restored to the original level within 10 s of glucose readdition. The $\text{NAD}{}^{\mathrm{+}}\text{NADH}$ratios in cell lines growing on galactose were as high as for those incubated without sugars; growth on mannose or fructose produced intermediate ratios. There was an inverse relationship between the $\text{NAD}{}^{\mathrm{+}}\text{NADH}$ ratio and pyruvate-lactate production for glucose, fructose and galactose. Thus, all cell lines had a high production of pyruvate and lactate but a low $\text{NAD}{}^{\mathrm{+}}\text{NADH}$ ratio when grown on glucose. In contrast, when galactose served as the sugar source, acid production was low, while the ratio was high. All cell lines had comparable hexokinase activity, and glucose was the best substrate, mannose intermediate and fructose poorest. Hexokinase activity did not correlate with the relative degree of utilization of the sugars. These results suggest that the sugar composition of the growth medium affects the metabolic pattern of a cell line, including the $\text{NAD}{}^{\mathrm{+}}\text{NADH}$ ratio, the ATP content and the production of pyruvate and lactate.     

Shapes and functions of species–area curves (II): a review of new models and parameterizations

This paper has extended and updated my earlier list and analysis of candidate models used in theoretical modelling and empirical examination of species–area relationships (SARs). I have also reviewed trivariate models that can be applied to include a second independent variable (in addition to area) and discussed extensively the justifications for fitting curves to SARs and the choice of model. There is also a summary of the characteristics of several new candidate models, especially extended power models, logarithmic models and parameterizations of the negative-exponential family and the logistic family. I have, moreover, examined the characteristics and shapes of trivariate linear, logarithmic and power models, including combination variables and interaction terms. The choice of models according to best fit may conflict with problems of non-normality or heteroscedasticity. The need to compare parameter estimates between data sets should also affect model choice. With few data points and large scatter, models with few parameters are often preferable. With narrow-scale windows, even inflexible models such as the power model and the logarithmic model may produce good fits, whereas with wider-scale windows where inflexible models do not fit well, more flexible models such as the second persistence (P2) model and the cumulative Weibull distribution may be preferable. When extrapolations and expected shapes are important, one should consider models with expected shapes, e.g. the power model for sample area curves and the P2 model for isolate curves. The choice of trivariate models poses special challenges, which one can more effectively evaluate by inspecting graphical plots.     

Identification of marker genes in Alzheimer's disease using a machine-learning model

Alzheimer''s Disease (AD) is one of the most common causes of dementia, mostly affecting the elderly population. Currently, there is no proper diagnostic tool or method available for the detection of AD. The present study used two distinct data sets of AD genes, which could be potential biomarkers in the diagnosis. The differentially expressed genes (DEGs) curated from both datasets were used for machine learning classification, tissue expression annotation and co-expression analysis. Further, CNPY3, GPR84, HIST1H2AB, HIST1H2AE, IFNAR1, LMO3, MYO18A, N4BP2L1, PML, SLC4A4, ST8SIA4, TLE1 and N4BP2L1 were identified as highly significant DEGs and exhibited co-expression with other query genes. Moreover, a tissue expression study found that these genes are also expressed in the brain tissue. In addition to the earlier studies for marker gene identification, we have considered a different set of machine learning classifiers to improve the accuracy rate from the analysis. Amongst all the six classification algorithms, J48 emerged as the best classifier, which could be used for differentiating healthy and diseased samples. SMO/SVM and Logit Boost further followed J48 to achieve the classification accuracy.     

Spectrum structures and biological functions of 8-mers in the human genome

The spectra of k-mer frequencies can reveal the structures and evolution of genome sequences. We confirmed that the trimodal spectrum of 8-mers in human genome sequences is distinguished only by CG2, CG1 and CG0 8-mer sets, containing 2,1 or 0 CpG, respectively. This phenomenon is called independent selection law. The three types of CG 8-mers were considered as different functional elements. We conjectured that (1) nucleosome binding motifs are mainly characterized by CG1 8-mers and (2) the core structural units of CpG island sequences are predominantly characterized by CG2 8-mers. To validate our conjectures, nucleosome occupied sequences and CGI sequences were extracted, then the sequence parameters were constructed through the information of the three CG 8-mer sets respectively. ROC analysis showed that CG1 8-mers are more preference in nucleosome occupied segments (AUC > 0.7) and CG2 8-mers are more preference in CGI sequences (AUC > 0.99). This validates our conjecture in principle.     

Investigation on the effect of alkyl chain linked mono-thioureas as Jack bean urease inhibitors,SAR, pharmacokinetics ADMET parameters and molecular docking studies

The increasing resistance of pathogens to common antibiotics, as well as the need to control urease activity to improve the yield of soil nitrogen fertilization in agricultural applications, has stimulated the development of novel classes of molecules that target urease as an enzyme. In this context, the newly developed compounds on the basis of 1-heptanoyl-3-arylthiourea family were evaluated for Jack bean urease enzyme inhibition activity to validate their role as potent inhibitors of this enzyme. 1-Heptanoyl-3-arylthioureas were obtained in excellent yield and characterized through spectral and elemental analysis. All the compounds displayed remarkable potency against urease inhibition as compared to thiourea standard. It was found that novel compounds fulfill the criteria of drug-likeness by obeying Lipinski’s rule of five. Particularly compound 4a and 4c can serve as lead molecules in 4D (drug designing discovery and development). Kinetic mechanism and molecular docking studies also carried out to delineate the mode of inhibition and binding affinity of the molecules.     

Human Health Risk Assessment of Soils Contaminated with Metal(loid)s by Using DGT Uptake: A Case Study of a Former Korean Metal Refinery Site

The human health risk of soils contaminated with As, Pb, Cu, and Zn was evaluated based on pseudo-total concentrations of metal(loid)s, the physiologically based extraction test (PBET), and diffusive gradients in thin films (DGT). Non-carcinogenic (NCR) and carcinogenic (CR) risks exceeded the U.S. Environmental Protection Agency criteria under both the residential and non-residential scenarios. Human bioavailable concentrations (PBET) were much lower than pseudo-total concentrations. The Hazardous Index of NCR (HI (NCR)) for the PBET in the studied soils was 67% and 94% less than that for pseudo-total concentration, respectively, under the non-residential and residential scenarios. Similarly, CR for the PBET was also 65% and 93% less for the two soils. The concentration of metal(loid)s accumulated in the DGT resin was highly correlated with the PBET-extractable concentration (R² > 0.649). Therefore, for both the CR and HI (NCR), the DGT-calculated risk was linearly related to the PBET-calculated risk for the studied soils under both scenarios. The results suggest that DGT uptake and PBET-extracted concentrations are good surrogates for risk estimation and that both J1 and J2 soils require remediation before their use for residential or non-residential purposes.     

Ionic liquid-enabled synthesis,cholinesterase inhibitory activity,and molecular docking study of highly functionalized tetrasubstituted pyrrolidines

A small library of novel spiropyrrolidine heterocyclic hybrids has been prepared regioselectively in 1-butyl-3-methylimidazoliumbromide ([bmim]Br) with good to excellent yields using a [3+2] cycloaddition reaction. These synthesized compounds were evaluated as potential agents for treating Alzheimer’s disease. Compound 4b showed the most potent activity, with an IC₅₀ of 7.9 ± 0.25 µM against acetylcholinesterase (AChE). The inhibition mechanisms for the most active compounds on AChE and butyrylcholinesterase (BChE) receptors were elucidated using molecular docking simulations.     

Spectral imaging for precise surgical intervention in Hirschsprung's Disease

We used advanced spectral imaging for intrasurgical decision making in a preclinical study, on a mouse model of Hirschsprung's Disease. Our imaging device sampled areas from normal and abnormal (aganglionic) colon in these animals. Spectral segmentation and classification of the resulting images showed a clear distinction between the normal and aganglionic regions, as confirmed by pathological analysis and use of mutant mice. We developed a simple algorithm that could distinguish normal from aganglionic colon with high spatial resolution and reproducibility, and the following statistics: sensitivity = 97%, specificity = 94%, positive predictive value = 92%, negative predictive value = 98%. These studies showed translational proof of concept that spectral imaging could be used during operations, in real time, to help surgeons precisely distinguish normal from abnormal tissue without requiring traditional biopsy. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)