•Scaling results in major operational losses and operating problems in many industries.•Here, the effect of surface energy on scale formation was systematically studied.•Polar component of surface ...energy is the key factor that controls scale formation.•Minimizing polar sites at the surface-scale interface can reduce scale deposition.•This work provides an alternative approach to scale mitigation compared to current inhibitors.
In this work, we performed a systematic investigation of the effect of surface energy on scale formation. We made a catalogue of smooth substrates with varying surface energies by depositing self-assembled monolayers (SAMs) of functionalized coatings (organosilanes) on glass slides and exposed these substrates to a saturated aqueous solution of CaSO4. The systems reached supersaturation due to evaporation of the aqueous phase over time, resulting in CaSO4 scale formation on the substrates. We show a significant reduction in scale formation with decreasing surface energy. To determine the surface chemistry and elemental composition of the substrates, we characterized them by X-ray photoelectron spectroscopy, and the results of this study were used to explain the effect of chemistry on surface energy. Furthermore, by looking at the contribution of the substrates’ surface energy from polar and apolar components, we demonstrate that the polar component is a key factor governing scale formation on a substrate. Hence, a significant reduction in scale deposition can be achieved by minimizing the polar sites at the surface-scale interface. The proposed approach is distinctive because it studies how changing the surface properties can result in scale mitigation, whereas previous research in the field mostly have focused on developing effective chemical inhibitors to change the solid and liquid properties in the fluid phase. Our findings provide a fundamental understanding of scale formation as a function of surface energy attributes and provide insights for the design of scale-resistant surfaces with potential for technological applications.
The iridoids comprise a large family of distinctive bicyclic monoterpenes that possess a wide range of pharmacological activities, including anticancer, anti-inflammatory, antifungal and ...antibacterial activities. Additionally, certain iridoids are used as sex pheromones in agriculturally important species of aphids, a fact that has underpinned innovative and integrated pest management strategies. To harness the biotechnological potential of this natural product class, the enzymes involved in the biosynthetic pathway must be elucidated. Here we report the discovery of iridoid synthase, a plant-derived enzyme that generates the iridoid ring scaffold, as evidenced by biochemical assays, gene silencing, co-expression analysis and localization studies. In contrast to all known monoterpene cyclases, which use geranyl diphosphate as substrate and invoke a cationic intermediate, iridoid synthase uses the linear monoterpene 10-oxogeranial as substrate and probably couples an initial NAD(P)H-dependent reduction step with a subsequent cyclization step via a Diels-Alder cycloaddition or a Michael addition. Our results illustrate how a short-chain reductase was recruited as cyclase for the production of iridoids in medicinal plants. Furthermore, we highlight the prospects of using unrelated reductases to generate artificial cyclic scaffolds. Beyond the recognition of an alternative biochemical mechanism for the biosynthesis of cyclic terpenes, we anticipate that our work will enable the large-scale heterologous production of iridoids in plants and microorganisms for agricultural and pharmaceutical applications.
Abstract
Background
Previous studies have reported that labeling errors are not uncommon in omics data. Potential outliers may severely undermine the correct classification of patients and the ...identification of reliable biomarkers for a particular disease. Three methods have been proposed to address the problem: sparse label-noise-robust logistic regression (Rlogreg), robust elastic net based on the least trimmed square (enetLTS), and Ensemble. Ensemble is an ensembled classification based on distinct feature selection and modeling strategies. The accuracy of biomarker selection and outlier detection of these methods needs to be evaluated and compared so that the appropriate method can be chosen.
Results
The accuracy of variable selection, outlier identification, and prediction of three methods (Ensemble, enetLTS, Rlogreg) were compared for simulated and an RNA-seq dataset. On simulated datasets, Ensemble had the highest variable selection accuracy, as measured by a comprehensive index, and lowest false discovery rate among the three methods. When the sample size was large and the proportion of outliers was ≤5%, the positive selection rate of Ensemble was similar to that of enetLTS. However, when the proportion of outliers was 10% or 15%, Ensemble missed some variables that affected the response variables.
Overall, enetLTS had the best outlier detection accuracy with false positive rates
<
0.05 and high sensitivity, and enetLTS still performed well when the proportion of outliers was relatively large. With 1% or 2% outliers, Ensemble showed high outlier detection accuracy, but with higher proportions of outliers Ensemble missed many mislabeled samples. Rlogreg and Ensemble were less accurate in identifying outliers than enetLTS. The prediction accuracy of enetLTS was better than that of Rlogreg. Running Ensemble on a subset of data after removing the outliers identified by enetLTS improved the variable selection accuracy of Ensemble.
Conclusions
When the proportion of outliers is ≤5%, Ensemble can be used for variable selection. When the proportion of outliers is > 5%, Ensemble can be used for variable selection on a subset after removing outliers identified by enetLTS. For outlier identification, enetLTS is the recommended method. In practice, the proportion of outliers can be estimated according to the inaccuracy of the diagnostic methods used.
Normal development of cortical circuits, including experience-dependent cortical maturation and plasticity, requires precise temporal regulation of gene expression and molecular signaling. Such ...regulation, and the concomitant impact on plasticity and critical periods, is hypothesized to be disrupted in neurodevelopmental disorders. A protein that may serve such a function is the MET receptor tyrosine kinase, which is tightly regulated developmentally in rodents and primates, and exhibits reduced cortical expression in autism spectrum disorder and Rett Syndrome. We found that the peak of MET expression in developing mouse cortex coincides with the heightened period of synaptogenesis, but is precipitously downregulated prior to extensive synapse pruning and certain peak periods of cortical plasticity. These results reflect a potential on-off regulatory synaptic mechanism for specific glutamatergic cortical circuits in which MET is enriched. In order to address the functional significance of the 'off' component of the proposed mechanism, we created a controllable transgenic mouse line that sustains cortical MET signaling. Continued MET expression in cortical excitatory neurons disrupted synaptic protein profiles, altered neuronal morphology, and impaired visual cortex circuit maturation and connectivity. Remarkably, sustained MET signaling eliminates monocular deprivation-induced ocular dominance plasticity during the normal cortical critical period; while ablating MET signaling leads to early closure of critical period plasticity. The results demonstrate a novel mechanism in which temporal regulation of a pleiotropic signaling protein underlies cortical circuit maturation and timing of cortical critical period, features that may be disrupted in neurodevelopmental disorders.
Microglia populate the early developing brain and mediate pruning of the central synapses. Yet, little is known on their functional significance in shaping the developing cortical circuits. We ...hypothesize that the developing cortical circuits require microglia for proper circuit maturation and connectivity, and as such, ablation of microglia during the cortical critical period may result in a long‐lasting circuit abnormality. We administered PLX3397, a colony‐stimulating factor 1 receptor inhibitor, to mice starting at postnatal day 14 and through P28, which depletes >75% of microglia in the visual cortex (VC). This treatment largely covers the critical period (P19‐32) of VC maturation and plasticity. Patch clamp recording in VC layer 2/3 (L2/3) and L5 neurons revealed increased mEPSC frequency and reduced amplitude, and decreased AMPA/NMDA current ratio, indicative of altered synapse maturation. Increased spine density was observed in these neurons, potentially reflecting impaired synapse pruning. In addition, VC intracortical circuit functional connectivity, assessed by laser scanning photostimulation combined with glutamate uncaging, was dramatically altered. Using two photon longitudinal dendritic spine imaging, we confirmed that spine elimination/pruning was diminished during VC critical period when microglia were depleted. Reduced spine pruning thus may account for increased spine density and disrupted connectivity of VC circuits. Lastly, using single‐unit recording combined with monocular deprivation, we found that ocular dominance plasticity in the VC was obliterated during the critical period as a result of microglia depletion. These data establish a critical role of microglia in developmental cortical synapse pruning, maturation, functional connectivity, and critical period plasticity.
Depletion of microglia during cortical critical period profoundly alters glutamatergic synapse developmental trajectory
Microglia is critical for visual cortex spine pruning, circuit refinement, intracortical connectivity, and critical period plasticity
Low-permeability reservoirs have strong heterogeneity, and the production prediction based on traditional seepage model is not accurate enough. The dynamic capillary-force seepage model can ...characterize the dynamic heterogeneity of seepage and more accurately describe the oil–water flow process. In this paper, the calculation formula of the dynamic capillary force is obtained through a real low-permeability core experiment, and the seepage model of dynamic capillary force is established. Based on the model, the authors quantitatively study the effects of formation pressure, heterogeneity and production speed on dynamic capillary force through numerical solutions. It is found that compared with the traditional static capillary-force seepage model, the dynamic capillary-force seepage model makes the predicted water cut increase and the recovery factor decrease. With the increase in development time, formation pressure and production rate will make the effect of dynamic capillary force more obvious. According to the comparison of heterogeneous reservoir models, results show that the horizontal heterogeneity will strengthen the dynamic capillary-force effect, while the vertical heterogeneity will weaken the dynamic capillary-force effect. In the range of research parameters, the recovery ratio predicted by the dynamic capillary-force seepage model can be reduced by 4.7%. A new oil–water seepage model is proposed, which can characterize the spatial difference and dynamic change of low-permeability reservoirs with time. It is of great significance for describing the remaining oil distribution of low-permeability reservoirs in detail and making decisions on efficient EOR measures.
Motivation: The genetic basis of complex traits often involves the function of multiple genetic factors, their interactions and the interaction between the genetic and environmental factors. ...Gene-environment (G×E) interaction is considered pivotal in determining trait variations and susceptibility of many genetic disorders such as neurodegenerative diseases or mental disorders. Regression-based methods assuming a linear relationship between a disease response and the genetic and environmental factors as well as their interaction is the commonly used approach in detecting G×E interaction. The linearity assumption, however, could be easily violated due to non-linear genetic penetrance which induces non-linear G×E interaction.
Results: In this work, we propose to relax the linear G×E assumption and allow for non-linear G×E interaction under a varying coefficient model framework. We propose to estimate the varying coefficients with regression spline technique. The model allows one to assess the non-linear penetrance of a genetic variant under different environmental stimuli, therefore help us to gain novel insights into the etiology of a complex disease. Several statistical tests are proposed for a complete dissection of G×E interaction. A wild bootstrap method is adopted to assess the statistical significance. Both simulation and real data analysis demonstrate the power and utility of the proposed method. Our method provides a powerful and testable framework for assessing non-linear G×E interaction.
Contact:
cui@stt.msu.edu
Supplementary information:
Supplementary data are available at Bioinformatics online.
Protein arginine methyltransferase 9 (PRMT9) is a recently identified member of the PRMT family, yet its biological function remains largely unknown. Here, by characterizing an intellectual ...disability associated PRMT9 mutation (G189R) and establishing a Prmt9 conditional knockout (cKO) mouse model, we uncover an important function of PRMT9 in neuronal development. The G189R mutation abolishes PRMT9 methyltransferase activity and reduces its protein stability. Knockout of Prmt9 in hippocampal neurons causes alternative splicing of ~1900 genes, which likely accounts for the aberrant synapse development and impaired learning and memory in the Prmt9 cKO mice. Mechanistically, we discover a methylation-sensitive protein-RNA interaction between the arginine 508 (R508) of the splicing factor 3B subunit 2 (SF3B2), the site that is exclusively methylated by PRMT9, and the pre-mRNA anchoring site, a cis-regulatory element that is critical for RNA splicing. Additionally, using human and mouse cell lines, as well as an SF3B2 arginine methylation-deficient mouse model, we provide strong evidence that SF3B2 is the primary methylation substrate of PRMT9, thus highlighting the conserved function of the PRMT9/SF3B2 axis in regulating pre-mRNA splicing.
With the emergence of advanced spatial transcriptomic technologies, there has been a surge in research papers dedicated to analyzing spatial transcriptomics data, resulting in significant ...contributions to our understanding of biology. The initial stage of downstream analysis of spatial transcriptomic data has centered on identifying spatially variable genes (SVGs) or genes expressed with specific spatial patterns across the tissue. SVG detection is an important task since many downstream analyses depend on these selected SVGs. Over the past few years, a plethora of new methods have been proposed for the detection of SVGs, accompanied by numerous innovative concepts and discussions. This article provides a selective review of methods and their practical implementations, offering valuable insights into the current literature in this field.
PDF
