The hydrophobicity of surfactants has been described through different concepts used to guide the formulation of surfactant–water (SW) and surfactant–oil–water (SOW) systems. An integrated framework ...of hydrophobicity indicators could provide a complete tool for surfactant characterization, and insights on how their relationship may influence the overall phase behavior of the system. The hydrophilic–lipophilic difference (HLD) and the characteristic curvature (Cc) parameter, included in the HLD, have been shown to correlate with different hydrophobicity indicators including the hydrophilic–lipophilic balance (HLB), packing factor (Pf), phase inversion temperature (PIT), spontaneous curvature (Ho), surfactant partition (Ko‑w), and the critical micelle concentration (CMC). This work aims to investigate whether the HLD can further describe a concomitant hydrophobicity parameter, the cloud point (CP) of alkyl ethoxylates. After applying group contribution models to calculate the Cc of monodisperse (pure) nonionic alkyl ethoxylates, a linear correlation between the calculated Cc and the CP was observed for pure surfactants with 8 ethylene oxide (EO) units or less. Furthermore, using an apparent equivalent alkane carbon number (EACN) to represent the hydrophobicity of the micelle core, the HLD equation was capable of predicting cloud point temperatures of pure alkyl ethoxylates, typically within 5 °C. Polydisperse surfactants did not follow the linear CP-Cc correlation found for pure surfactants. After treating polydisperse samples using a liquid–liquid extraction procedure used to remove the most hydrophobic components in the mixture, the resulting treated surfactants fell in the correlation line of pure alkyl ethoxylates. A closer look at the partition behavior of these treated surfactants showed that their partition, Cc and cloud point are dominated by the most abundant ethoxymers in the treated surfactant. The HLD also predicted the cloud point depression of treated surfactants with increasing sodium chloride concentration. This work shows how the HLD framework could be extended to predict the behavior of SW systems.
A non-targeted strategy to simultaneously screen for over 100 lipid mediators from ω-6 ARA and ω-3 EPA and DHA fatty acids is presented. The method based on an extensive study of fragmentation ...patterns obtained by SPE-LC-MS/MS analysis-provided fingerprints to comprehensively elucidate and identify lipid mediators in biological samples. Many of these metabolites are associated to metabolic disorders, inflammatory, immune and oxidative stress. The methodology consisted of a three-step procedure. (1) SPE extraction of compounds from plasma and adipose tissue was followed by LC-MS/MS analysis operating in full scan mode. The methodology was validated for a group of 65 metabolites using standards. SPE recoveries ranged from 29-134% and matrix effect from 10-580%. LOD and LOQ ranged from 0.01 to 1765 ng/mL and 0.03 to 5884 ng/mL respectively, similarly than current analytical strategies based on MRM mode. (2) An extensive study of the mass spectra of a wide range of compounds was done to stablish a specific fragmentation pattern. Interestingly, illustrative fragmentations and new specific transitions to identify EPA and DHA lipid mediators have been innovatively established. (3) After analysis, 30 lipid mediators were tentatively identified in plasma and 35 in adipose tissue of rats according to the pre stablished fragmentation patterns. The hypothetical identification of compounds was validated by using reference standards. Around 85-90% of proposed identifications were correctly assigned and only 4 and 3 identifications failed in adipose tissue and plasma, respectively. The method allowed the identification of these metabolites without losing information by the use of predefined ions list. Therefore, the use of full scan mode together with the study of fragmentation patterns provided a novel and stronger analytical tool to study the complete profile of lipid mediators in biological samples than the analysis through MRM based methods. Importantly, no analytical standards were required at this qualitative screening stage and the performance and sensitivity of the assay were very similar to that of a MRM method.
Central nervous system-expressed long non-coding RNAs (lncRNAs) are often located in the genome close to protein coding genes involved in transcriptional control. Such lncRNA-protein coding gene ...pairs are frequently temporally and spatially co-expressed in the nervous system and are predicted to act together to regulate neuronal development and function. Although some of these lncRNAs also bind and modulate the activity of the encoded transcription factors, the regulatory mechanisms controlling co-expression of neighbouring lncRNA-protein coding genes remain unclear. Here, we used high resolution NG Capture-C to map the cis-regulatory interaction landscape of the key neuro-developmental Paupar-Pax6 lncRNA-mRNA locus. The results define chromatin architecture changes associated with high Paupar-Pax6 expression in neurons and identify both promoter selective as well as shared cis-regulatory-promoter interactions involved in regulating Paupar-Pax6 co-expression. We discovered that the TCF7L2 transcription factor, a regulator of chromatin architecture and major effector of the Wnt signalling pathway, binds to a subset of these candidate cis-regulatory elements to coordinate Paupar and Pax6 co-expression. We describe distinct roles for Paupar in Pax6 expression control and show that the Paupar DNA locus contains a TCF7L2 bound transcriptional silencer whilst the Paupar transcript can act as an activator of Pax6. Our work provides important insights into the chromatin interactions, signalling pathways and transcription factors controlling co-expression of adjacent lncRNAs and protein coding genes in the brain.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Intentional mass-casualty incidents (IMCIs) involving motor vehicles (MVs) as weapons represent a growing trend in Western countries. This method has resulted in the highest casualty rates per ...incident within the field of IMCIs. Consequently, there is an urgent requirement for a timely and accurate casualty estimation in MV-induced IMCIs to scale and adjust the necessary health care resources.
The objective of this study is to identify the factors associated with the number of casualties during the initial phase of MV-IMCIs.
This is a retrospective, observational, analytical study on MV-IMCIs world-wide, from 2000-2021. Data were obtained from three different sources: Targeted Automobile Ramming Mass-Casualty Attacks (TARMAC) Attack Database, Global Terrorism Database (GTD), and the vehicle-ramming attack page from the Wikipedia website. Jacobs' formula was used to estimate the population density in the vehicle's route. The primary outcome variables were the total number of casualties (injured and fatalities). Associations between variables were analyzed using Spearman's correlation coefficient and simple linear regression.
Forty-six MV-IMCIs resulted in 1,636 casualties (1,430 injured and 206 fatalities), most of them caused by cars. The most frequent driving pattern was accelerating whilst approaching the target, with an average speed range between four to 130km/h and a distance traveled between ten to 2,260 meters. The people estimated in the MV-IMCI scenes ranged from 36-245,717. A significant positive association was found of the number affected with the estimated crowd in the scene (R
: 0.64; 95% CI, 0.61-0.67; P <.001) and the average vehicle speed (R
: 0.42; 95% CI, 0.40-0.44; P = .004).
The estimated number of people in the affected area and vehicle's average speed are the most significant variables associated with the number of casualties in MV-IMCIs, helping to enable a timely estimation of the casualties.
Understanding and predicting cloud point phenomena is important for the formulation of nonionic surfactant systems, and the design of cloud‐phenomena‐associated separation processes. There have been ...several approaches to fit and predict the cloud point phenomena, in most cases using bulk thermodynamic approaches. In this work, we introduced the hydrophilic–lipophilic‐difference and net‐average‐curvature (HLD‐NAC) as an interfacial (curvature) approach to predict cloud point values at different surfactant concentrations (cloud point curve). The HLD‐NAC method could fully predict the cloud point of alkyl ethoxylate of pure surfactants, typically within 4 °C of the experimental values, using published HLD constants, and the molecular structure of the surfactants. For commercial (polydispersed) surfactants, the same level of accuracy can be achieved if the experimental cloud point at 1 wt.% is used to adjust the HLD values. One additional benefit of using the HLD framework is the ability to predict changes in the cloud point curve with the introduction of electrolytes. While other models can fit the experimental data within 1 °C, the greater uncertainty of the HLD‐NAC (~4 °C) is a reasonable compromise given the simplicity of the approach.
The pluripotent state is traditionally associated with large absolute levels of certain transcription factors such as Nanog and Oct4. Here, we present experimental observations using quantitative ...immunofluorescence that pluripotency in mouse embryonic stem cells (mESCs) is established by specific ratios between Oct4 and Nanog. When cells are grown in 2i conditions, they exhibit uniform levels of pluripotency and this is associated with a high correlation between the levels of Oct4 and Nanog in individual cells. The correlation is lost when cells differentiate. Our results suggest that the correlation between these two factors and the distribution of Oct4/Nanog ratios can be used as quantifiers to distinguish between three subpopulations in an mESC culture: pluripotent, lineage‐primed, and differentiating cells. When we apply these quantifiers to cells with lower levels of Nanog or mutant for β‐Catenin or Tcf3, the results suggest that these cells exhibit higher probability of differentiation. STEM CELLS 2012;30:2683–2691
Pluripotency in embryonic stem cells is maintained through the activity of a small set of transcription factors centred around Oct4 and Nanog, which control the expression of ‘self‐renewal’ and ...‘differentiation’ genes. Here, we combine single‐cell quantitative immunofluorescence microscopy and gene expression analysis, together with theoretical modelling, to investigate how the activity of those factors is regulated. We uncover a key role for post‐translational regulation in the maintenance of pluripotency, which complements the well‐established transcriptional regulatory layer. Specifically, we find that the activity of a network of protein complexes involving Nanog, Oct4, Tcf3, and β‐catenin suffices to account for the behavior of ES cells under different conditions. Our results suggest that the function of the network is to buffer the transcriptional activity of Oct4, which appears to be the main determinant to exit pluripotency. The protein network explains the mechanisms underlying the gain and loss of function in different mutants, and brings us closer to a full understanding of the molecular basis of pluripotency.
The dynamic competition for complex formation between the pluripotency network components Oct4, Nanog, Tcf3, and β‐catenin prevents embryonic stem cell differentiation by controlling the levels of free Oct4.
Synopsis
The dynamic competition for complex formation between the pluripotency network components Oct4, Nanog, Tcf3, and β‐catenin prevents embryonic stem cell differentiation by controlling the levels of free Oct4.
Pluripotency is defined by the ratios between the levels of pluripotency factors rather than by their absolute levels.
Competition between different protein complexes involving Nanog, Oct4, Tcf3, and β‐catenin can account for the ratios associated with pluripotency.
The unstable pluripotency of Nanog mutant cells was shown to depend on the interactions between Oct4 and β‐catenin.
The function of the protein competition network is to control the levels of free Oct4, which are balanced by Nanog and β‐catenin in embryonic stem cells.
Carbonylation is a nonenzymatic irreversible posttranslational protein modification and the main hallmark of protein oxidative damage. Elevated levels of protein carbonyl groups have been detected in ...age-related and metabolic diseases such as obesity, diabetes, Alzheimer, Parkinson, and several other oxidative stress-related maladies. Interestingly, many studies have shown that only a subset of proteins is carbonylated under the conditions of oxidative stress, demonstrating that carbonylation is a highly selective process. As a consequence, identifying and quantifying the disease-induced changes on a certain carbonylome are crucial to understanding the etiology and progression of numerous diseases and then designing adequate prevention/palliation strategies. However, the low abundance of carbonylated proteins in vivo, the enormous diversity of reactive species, and their relative lability make the analysis of carbonylated proteins a challenging task for redox proteomic technology. Therefore, we present a proteomic approach based on the labeling of carbonyls formed in vivo on proteins using the fluorescein 5-thiosemicarbazide (FTSC) tag to detect the subset of carbonylated proteins among a complex mixture of proteins regardless of the nature of carbonyl adduct, isolation and relative quantification of carbonylated proteins in 2D gel electrophoresis, and protein identification by LC-MS/MS analysis. This method has been successfully used for the evaluation of in vivo protein carbonylation in very diverse animal tissues (plasma, liver, kidney, skeletal muscle, and adipose tissue) and species (from fish to mammalian) and has also been applied in different research fields (from food technology to nutrition), demonstrating its robustness and reliability.
This work introduces a simplified methodology for measuring the characteristic curvature (Cc) of commercial alkyl ethoxylate nonionic surfactants using carefully selected reference surfactants and ...oils that produce rapid and well defined separations in salinity scans. The Cc of the commercial reference surfactants was calculated using optimal salinities (
S
*) obtained from solubilization parameter curves, from interfacial tensions (for a selected system), and from emulsion stability tests. The latter provided a fast detection of
S
*, in a matter of minutes. The calibrated Cc of the reference surfactants was subsequently used to measure the Cc of various commercial alkyl ethoxylate surfactants. The combination of mixtures of test and reference surfactants and emulsion stability tests produced reproducible Cc values that could be obtained with simple bottle tests and in a timely manner. The values obtained using this methodology were cross-checked, and proved to be consistent, when using different combinations of reference surfactants and oils, and when conducted by different individuals. The standard deviation of Cc from these measurements was typically ±0.2 Cc units, but it could be as large as 25 % of the Cc value for highly hydrophilic surfactants. After comparing the values of Cc obtained experimentally with values calculated from nominal structures (via a group contribution model) it became clear that there are differences between these values, likely because of the polydispersity of alkyl ethoxylate surfactants.
The maintenance of pluripotency in mouse embryonic stem cells (mESCs) relies on the activity of a transcriptional network that is fuelled by the activity of three transcription factors (Nanog, Oct4 ...and Sox2) and balanced by the repressive activity of Tcf3. Extracellular signals modulate the activity of the network and regulate the differentiation capacity of the cells. Wnt/β-catenin signaling has emerged as a significant potentiator of pluripotency: increases in the levels of β-catenin regulate the activity of Oct4 and Nanog, and enhance pluripotency. A recent report shows that β-catenin achieves some of these effects by modulating the activity of Tcf3, and that this effect does not require its transcriptional activation domain. Here, we show that during self-renewal there is negligible transcriptional activity of β-catenin and that this is due to its tight association with membranes, where we find it in a complex with Oct4 and E-cadherin. Differentiation triggers a burst of Wnt/β-catenin transcriptional activity that coincides with the disassembly of the complex. Our results establish that β-catenin, but not its transcriptional activity, is central to pluripotency acting through a β-catenin/Oct4 complex.
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