The evolutionary novelty of insect defensins: from bacterial killing to toxin neutralization.

Insect host defense comprises two complementary dimensions, microbial killing-mediated resistance and microbial toxin neutralization-mediated resilience, both jointly providing protection against pathogen infections. Insect defensins are a class of effectors of innate immunity primarily responsible for resistance to Gram-positive bacteria. Here, we report a newly originated gene from an ancestral defensin via genetic deletion following gene duplication in Drosophila virilis, which confers an enhanced resilience to Gram-positive bacterial infection. This gene encodes an 18-mer arginine-rich peptide (termed DvirARP) with differences from its parent gene in its pattern of expression, structure and function. DvirARP specifically expresses in D. virilis female adults with a constitutive manner. It adopts a novel fold with a 310 helix and a two CXC motif-containing loop stabilized by two disulfide bridges. DvirARP exhibits no activity on the majority of microorganisms tested and only a weak activity against two Gram-positive bacteria. DvirARP knockout flies are viable and have no obvious defect in reproductivity but they are more susceptible to the DvirARP-resistant Staphylococcus aureus infection than the wild type files, which can be attributable to its ability in neutralization of the S. aureus secreted toxins. Phylogenetic distribution analysis reveals that DvirARP is restrictedly present in the Drosophila subgenus, but independent deletion variations also occur in defensins from the Sophophora subgenus, in support of the evolvability of this class of immune effectors. Our work illustrates for the first time how a duplicate resistance-mediated gene evolves an ability to increase the resilience of a subset of Drosophila species against bacterial infection.

Input integration by the circadian clock exhibits nonadditivity and fold-change detection.

Circadian clocks are synchronized by external timing cues to align with one another and the environment. Various signaling pathways have been shown to independently reset the phase of the clock. However, in the body, circadian clocks are exposed to a multitude of potential timing cues with complex temporal dynamics, raising the question of how clocks integrate information in response to multiple signals. To investigate different modes of signal integration by the circadian clock, we used Circa-SCOPE, a method we recently developed for high-throughput phase resetting analysis. We found that simultaneous exposure to different combinations of known pharmacological resetting agents elicits a diverse range of responses. Often, the response was nonadditive and could not be readily predicted by the response to the individual signals. For instance, we observed that dexamethasone is dominant over other tested inputs. In the case of signals administered sequentially, the background levels of a signal attenuated subsequent resetting by the same signal, but not by signals acting through a different pathway. This led us to examine whether the circadian clock is sensitive to relative rather than absolute levels of the signal. Importantly, our analysis revealed the involvement of a signal-specific fold-change detection mechanism in the clock response. This mechanism likely stems from properties of the signaling pathway that are upstream to the clock. Overall, our findings elucidate modes of input integration by the circadian clock, with potential relevance to clock resetting under both physiological and pathological conditions.

qRAT: an R-based stand-alone application for relative expression analysis of RT-qPCR data.

BACKGROUND: Reverse transcription quantitative real-time PCR (RT-qPCR) is a well-established method for analysing gene expression. Most RT-qPCR experiments in the field of microbiology aim for the detection of transcriptional changes by relative quantification, which means the comparison of the expression level of a specific gene between different samples by the application of a calibration condition and internal reference genes. Due to the numerous data processing procedures and factors that can influence the final result, relative expression analysis and interpretation of RT-qPCR data are still not trivial and often necessitate the use of multiple separate software packages capable of performing specific functions. RESULTS: Here we present qRAT, a stand-alone desktop application based on R that automatically processes raw output data from any qPCR machine using well-established and state-of-the-art statistical and graphical techniques. The ability of qRAT to analyse RT-qPCR data was evaluated using two example datasets generated in our laboratory. The tool successfully completed the procedure in both cases, returning the expected results. The current implementation includes functionalities for parsing, filtering, normalizing and visualisation of relative RT-qPCR data, like the determination of the relative quantity and the fold change of differentially expressed genes as well as the correction of inter-plate variation for multiple-plate experiments. CONCLUSION: qRAT provides a comprehensive, straightforward, and easy-to-use solution for the relative quantification of RT-qPCR data that requires no programming knowledge or additional software installation. All application features are available for free and without requiring a login or registration.

A proteomics approach to decipher a sticky CHO situation.

Chinese hamster ovary (CHO) cells serve as protein therapeutics workhorses, so it is useful to understand what intrinsic properties make certain host cell lines and clones preferable for scale up and production of target proteins. In this study, two CHO host cell lines (H1, H2), and their respective clones were evaluated using comparative TMT-proteomics. The clones obtained from host H1 showed increased productivity (6.8 times higher) in comparison to clones from host H2. Based on fold-change analyses, we observed differential regulation in pathways including cell adhesion, aggregation, and cellular metabolism among others. In particular, the cellular adhesion pathway was downregulated in H1, in which podoplanin, an antiadhesion molecule, was upregulated the most in host H1 and associated clones. Phenotypically, these cells were less likely to aggregate and adhere to surfaces. In addition, enzymes involved in cellular metabolism such as isocitrate dehydrogenase (IDH) and mitochondrial-d-lactate dehydrogenase ( d-LDHm) were also found to be differentially regulated. IDH plays a key role in TCA cycle and isocitrate-alpha-ketoglutarate cycle while d-LDHm aids in the elimination of toxic metabolite methylglyoxal, involved in protein degradation. These findings will enhance our efforts towards understanding why certain CHO cell lines exhibit enhanced performance and perhaps provide future cell engineering targets.

Effect of high variation in transcript expression on identifying differentially expressed genes in RNA-seq analysis.

Great efforts have been made on the algorithms that deal with RNA-seq data to enhance the accuracy and efficiency of differential expression (DE) analysis. However, no consensus has been reached on the proper threshold values of fold change and adjusted p-value for filtering differentially expressed genes (DEGs). It is generally believed that the more stringent the filtering threshold, the more reliable the result of a DE analysis. Nevertheless, by analyzing the impact of both adjusted p-value and fold change thresholds on DE analyses, with RNA-seq data obtained for three different cancer types from the Cancer Genome Atlas (TCGA) database, we found that, for a given sample size, the reproducibility of DE results became poorer when more stringent thresholds were applied. No matter which threshold level was applied, the overlap rates of DEGs were generally lower for small sample sizes than for large sample sizes. The raw read count analysis demonstrated that the transcript expression of the same gene in different samples, whether in tumor groups or in normal groups, showed high variations, which resulted in a drastic fluctuation in fold change values and adjustedp-values when different sets of samples were used. Overall, more stringent thresholds did not yield more reliable DEGs due to high variations in transcript expression; the reliability of DEGs obtained with small sample sizes was more susceptible to these variations. Therefore, less stringent thresholds are recommended for screening DEGs. Moreover, large sample sizes should be considered in RNA-seq experimental designs to reduce the interfering effect of variations in transcript expression on DEG identification.

Role of expression of host cytokines in the pathogenesis of H9N2-PB2 reassortant and non-reassortant H5N1 avian influenza viruses isolated from crows in BALB/c mice.

The present experiment was conducted to study the role of cytokine, chemokine and TLRs responses of H9N2-PB2 reassortant H5N1 virus as compared to non-reassortant H5N1 virus isolated from crows in BALB/c mice. Two groups (12 mice each) of 6-8 weeks old BALB/c mice were intranasally inoculated with 106 EID50/ml of viruses A/crow/India/03CA04/2015 (H9N2-PB2 reassortant H5N1) and A/crow/India/02CA01/2012 (non-reassortant H5N1). At each interval, brain, lung and spleen were collected and relative quantification of cytokines, chemokines and TLRs was done by qPCR. The H9N2-PB2 reassortant H5N1 infected mice brain, the transcripts of TLR7 were significantly higher than other cytokines at 3dpi and KC was significantly upregulated at 7dpi. In non-reassortant H5N1 infected mice brain showed, TLR 7 and IFNα upregulation at 3dpi and IFNγ and TLR7 upregulation at 7dpi. The H9N2-PB2 reassortant H5N1 infected mice lung revealed, IL2 and TLR7 significant upregulation at 3dpi and in non-reassortant H5N1 infected mice, IL6 was significantly upregulated. At 7dpi in H9N2-PB2 reassortant H5N1 virus infected group mice, IL1 and TLR 3 were significantly upregulated in lungs and in non-reassortant group mice, IL1 and TLR7 were significantly upregulated. At 3dpi in H9N2-PB2 reassortant H5N1 virus infected mice spleen, IL4, IFNα, IFNß were significantly downregulated and TLR7 transcript was significantly upregulated. In non-reassortant group mice, IL6, IFNα, IFNß and TLR 3 were significantly upregulated. At 7dpi in H9N2-PB2 reassortant H5N1 virus infected mice spleen, IFNα, IFNß and TLR7 were significantly lower than other cytokines and in non-reassortant group mice, IFNα and IFNß were significantly downregulated. This study concludes that dysregulation of cytokines in lungs and brain might have contributed to the pathogenesis of both the viruses in mice.

Elucidating the impact of cottonseed hydrolysates on CHO cell culture performance through transcriptomic analysis.

In order to evaluate the impact of plant-based hydrolysates on CHO cells, a transcriptomic study was undertaken using cottonseed hydrolysate and Illumina's NextSeq transcriptomics profiling for 2 days of a batch cell culture. While cottonseed hydrolysate extended cell growth and increased antibody titer, significant effects were seen on transcriptomic signatures of supplemented cultures when compared to untreated cultures, evaluated using fold change, gene ontology (GO), and KEGG pathway analysis. Transcription and other factors commonly associated with cell growth such as those of the Atf family and homeobox proteins were upregulated while genes in the Hippo signaling pathway were downregulated. Genes involved in anabolic pathways such as gluconeogenesis and those involving protein folding and translation elongation were upregulated. GO analysis of biological processes for cottonseed-supplemented cultures indicated enrichments in DNA replication, protein processing, and unfolded protein response while molecular functions associated with growth such as GTPases, ATP binding, and aminoacyl t-RNA ligase activity were also enriched. Cellular components associated with structural integrity such as actin cytoskeleton, microtubules, mitochondrion, and Lewy body were enriched. Enriched KEGG pathways include growth-associated pathways such as cell cycle, pI3K-AKT-mTOR, and cancer-related pathways as well as those enhancing glycan metabolism, purine metabolism, amino acid biosynthesis, and protein processing in the endoplasmic reticulum (ER). These transcriptomic profiles provide insights into the roles that hydrolysates such as cottonseed can play in altering CHO cell growth and other physiological characteristics as well as suggesting ways in which CHO cell culture may be modified for enhancing performance in biotechnology applications. KEY POINTS: • Hydrolysate-supplemented cultures increased mammalian cell growth and productivity. • Fold-change analysis revealed upregulation in transcription and translation. • Enriched GOs and KEGG pathways including cell cycle and metabolism were observed.

Effects of neoadjuvant therapies on genetic regulation of targeted pathways in ER+ primary ductal breast carcinoma: A meta-analysis of microarray datasets.

Breast cancer arises as a result of multiple interactions between environmental and genetic factors. Conventionally, breast cancer is treated based on histopathological and clinical features. DNA technologies like the human genome microarray are now partially integrated into clinical practice and are used for developing new "personalized medicines" and "pharmacogenetics" for improving the efficiency and safety of cancer medications. We investigated the effects of four established therapies-for ER+ ductal breast cancer-on the differential gene expression. The therapies included single agent tamoxifen, two-agent docetaxel and capecitabine, or combined three-agents CAF (cyclophosphamide, doxorubicin, and fluorouracil) and CMF (cyclophosphamide, methotrexate, and fluorouracil). Genevestigator 8.1.0 was used to compare five datasets from patients with infiltrating ductal carcinoma, untreated or treated with selected drugs, to those from the healthy control. We identified 74 differentially expressed genes involved in three pathways, i.e., apoptosis (extrinsic and intrinsic), oxidative signaling, and PI3K/Akt signaling. The treatments affected the expression of apoptotic genes (TNFRSF10B [TRAIL], FAS, CASP3/6/7/8, PMAIP1 [NOXA], BNIP3L, BNIP3, BCL2A1, and BCL2), the oxidative stress-related genes (NOX4, XDH, MAOA, GSR, GPX3, and SOD3), and the PI3K/Akt pathway gene (ERBB2 [HER2]). Breast cancer treatments are complex with varying drug responses and efficacy among patients. This necessitates identifying novel biomarkers for predicting the drug response, using available data and new technologies. GSR, NOX4, CASP3, and ERBB2 are potential biomarkers for predicting the treatment response in primary ER+ ductal breast carcinoma.

Selection of Heating Temperatures Improves the Sensitivity of the Proteome Integral Solubility Alteration Assay.

The thermal shift assay is a robust method of discovering protein-ligand interactions by measuring the alterations in protein thermal stability under various conditions. Several thermal shift assays have been developed and their throughput has been advanced greatly by the rapid progress in tandem mass tag-based quantitative proteomics. A recent paper by Gaetani et al. ( J. Proteome Res. 2019, 18 (11), 4027-4037) introduced the proteome integral solubility alteration (PISA) assay, further increasing throughput and simplifying the data analysis. Both ΔSm (a proxy of the difference between areas under the melting curves) and fold changes (ratios between integral samples) are readouts of the PISA assay and positively related to ΔTm (shift in melting temperatures). Here, we show that the magnitudes of these readouts are inherently small in PISA assay, which is a challenge for quantitation. Both simulation and experimental results show that the selection of a subset of heating temperatures ameliorates the small difference problem and improves the sensitivity of the PISA assay.

A systematic evaluation of normalization methods in quantitative label-free proteomics.

To date, mass spectrometry (MS) data remain inherently biased as a result of reasons ranging from sample handling to differences caused by the instrumentation. Normalization is the process that aims to account for the bias and make samples more comparable. The selection of a proper normalization method is a pivotal task for the reliability of the downstream analysis and results. Many normalization methods commonly used in proteomics have been adapted from the DNA microarray techniques. Previous studies comparing normalization methods in proteomics have focused mainly on intragroup variation. In this study, several popular and widely used normalization methods representing different strategies in normalization are evaluated using three spike-in and one experimental mouse label-free proteomic data sets. The normalization methods are evaluated in terms of their ability to reduce variation between technical replicates, their effect on differential expression analysis and their effect on the estimation of logarithmic fold changes. Additionally, we examined whether normalizing the whole data globally or in segments for the differential expression analysis has an effect on the performance of the normalization methods. We found that variance stabilization normalization (Vsn) reduced variation the most between technical replicates in all examined data sets. Vsn also performed consistently well in the differential expression analysis. Linear regression normalization and local regression normalization performed also systematically well. Finally, we discuss the choice of a normalization method and some qualities of a suitable normalization method in the light of the results of our evaluation.

Effect of zinc supplementation on relative expression of immune response genes in neonates with sepsis: A preliminary study.

Background & objectives: Zinc alters gene expression mainly by binding to a site on the transcription factor. Genome-wide expression studies have shown early repression of genes related to zinc and immunity in adult patients with sepsis. The present study was conducted to evaluate the role of zinc supplementation on relative expression of immune response genes in neonatal sepsis. Methods: In the present study, a sample of convenience of 22 neonates each was selected from the zinc supplemented and control groups using random numbers for expression of immune-related genes by zinc supplementation. These neonates with sepsis were earlier randomized into two groups: with and without zinc supplementation in addition to standard antibiotics and supportive care. Relative expression of immune response genes were analyzed for 22 neonates in each group using quantitative real-time PCR for calprotectin (S100A8/A9), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), toll-like receptor-4 (TLR-4), cluster of differentiation 14 (CD14) and lipopolysaccharide-binding protein (LBP) genes. Results: An increase in serum zinc levels was observed in zinc-supplemented group compared to controls. S100A8 gene showed downregulation by three-fold (P <0.001) and S100A9 gene showed upregulation by two-fold (P <0.05) in zinc group compared to controls. CD14 gene showed upregulation by one-fold in zinc-supplemented group compared to controls (P <0.05). No significant fold changes were observed with respect to TNF-α, IL-6, LBP and TLR-4 genes between the two groups. Interpretation & conclusions: The results of our preliminary study showed that the zinc supplementation might modulates the relative expression of immune-related genes involved in sepsis pathway among neonates. However, studies with larger sample size are needed to be done to provide a better picture on the outcome by gene expression in neonatal sepsis by zinc supplementation.

Fold-change detection and scale invariance of cell-cell signaling in social amoeba.

Cell-cell signaling is subject to variability in the extracellular volume, cell number, and dilution that potentially increase uncertainty in the absolute concentrations of the extracellular signaling molecules. To direct cell aggregation, the social amoebae Dictyostelium discoideum collectively give rise to oscillations and waves of cyclic adenosine 3',5'-monophosphate (cAMP) under a wide range of cell density. To date, the systems-level mechanism underlying the robustness is unclear. By using quantitative live-cell imaging, here we show that the magnitude of the cAMP relay response of individual cells is determined by fold change in the extracellular cAMP concentrations. The range of cell density and exogenous cAMP concentrations that support oscillations at the population level agrees well with conditions that support a large fold-change-dependent response at the single-cell level. Mathematical analysis suggests that invariance of the oscillations to density transformation is a natural outcome of combining secrete-and-sense systems with a fold-change detection mechanism.

Sensing relative signal in the Tgf-ß/Smad pathway.

How signaling pathways function reliably despite cellular variation remains a question in many systems. In the transforming growth factor-ß (Tgf-ß) pathway, exposure to ligand stimulates nuclear localization of Smad proteins, which then regulate target gene expression. Examining Smad3 dynamics in live reporter cells, we found evidence for fold-change detection. Although the level of nuclear Smad3 varied across cells, the fold change in the level of nuclear Smad3 was a more precise outcome of ligand stimulation. The precision of the fold-change response was observed throughout the signaling duration and across Tgf-ß doses, and significantly increased the information transduction capacity of the pathway. Using single-molecule FISH, we further observed that expression of Smad3 target genes (ctgf, snai1, and wnt9a) correlated more strongly with the fold change, rather than the level, of nuclear Smad3. These findings suggest that some target genes sense Smad3 level relative to background, as a strategy for coping with cellular noise.

Network meta-analysis correlates with analysis of merged independent transcriptome expression data.

BACKGROUND: Using meta-analysis, high-dimensional transcriptome expression data from public repositories can be merged to make group comparisons that have not been considered in the original studies. Merging of high-dimensional expression data can, however, implicate batch effects that are sometimes difficult to be removed. Removing batch effects becomes even more difficult when expression data was taken using different technologies in the individual studies (e.g. merging of microarray and RNA-seq data). Network meta-analysis has so far not been considered to make indirect comparisons in transcriptome expression data, when data merging appears to yield biased results. RESULTS: We demonstrate in a simulation study that the results from analyzing merged data sets and the results from network meta-analysis are highly correlated in simple study networks. In the case that an edge in the network is supported by multiple independent studies, network meta-analysis produces fold changes that are closer to the simulated ones than those obtained from analyzing merged data sets. Finally, we also demonstrate the practicability of network meta-analysis on a real-world data example from neuroinfection research. CONCLUSIONS: Network meta-analysis is a useful means to make new inferences when combining multiple independent studies of molecular, high-throughput expression data. This method is especially advantageous when batch effects between studies are hard to get removed.

Did cis- and trans-defensins derive from a common ancestor?

Defensins are small, cysteine-rich, cationic antimicrobial peptides, serving as effectors of the innate immune system and modulators of the adaptive immune system. They extensively exist in multicellular organisms and are divided into cis and trans according to their disulfide bridge connectivity patterns. It has been proposed that these two types of defensins convergently originated from different ancestors. Here, we report the discovery of a structural signature involved in the formation of the cysteine-stabilized α-helix/ß-sheet (CSαß) fold of the cis-defensins in some trans-ß-defensins, with only one amino acid indel (CXC vs. CC. C, cysteine; X, any amino acid). The indel of the X residue in the structural signature provides a possible explanation as to why cis- and trans-defensins possess different folds and connectivity patterns of disulfide bridges formed in evolution. Although our attempt to convert the structure type of a present-day trans-defensin with the X residue deleted was unsuccessful due to the low solubility of the synthetic peptide, a combination of data from structural signature, function, and phylogenetic distribution suggests that these defensins may have descended from a common ancestor. In this evolutionary scenario, we propose that a progenitor cis-scaffold might gradually evolve into a trans-defensin after deleting the X residue in specific lineages. This proposal adds a new dimension to more deeply studying the evolutionary relationship of defensins with different folds and of other distantly related proteins.

Clinical biomarker discovery by SWATH-MS based label-free quantitative proteomics: impact of criteria for identification of differentiators and data normalization method.

BACKGROUND: SWATH-MS has emerged as the strategy of choice for biomarker discovery due to the proteome coverage achieved in acquisition and provision to re-interrogate the data. However, in quantitative analysis using SWATH, each sample from the comparison group is run individually in mass spectrometer and the resulting inter-run variation may influence relative quantification and identification of biomarkers. Normalization of data to diminish this variation thereby becomes an essential step in SWATH data processing. In most reported studies, data normalization methods used are those provided in instrument-based data analysis software or those used for microarray data. This study, for the first time provides an experimental evidence for selection of normalization method optimal for biomarker identification. METHODS: The efficiency of 12 normalization methods to normalize SWATH-MS data was evaluated based on statistical criteria in 'Normalyzer'-a tool which provides comparative evaluation of normalization by different methods. Further, the suitability of normalized data for biomarker discovery was assessed by evaluating the clustering efficiency of differentiators, identified from the normalized data based on p-value, fold change and both, by hierarchical clustering in Genesis software v.1.8.1. RESULTS: Conventional statistical criteria identified VSN-G as the optimal method for normalization of SWATH data. However, differentiators identified from VSN-G normalized data failed to segregate test and control groups. We thus assessed data normalized by eleven other methods for their ability to yield differentiators which segregate the study groups. Datasets in our study demonstrated that differentiators identified based on p-value from data normalized with Loess-R stratified the study groups optimally. CONCLUSION: This is the first report of experimentally tested strategy for SWATH-MS data processing with an emphasis on identification of clinically relevant biomarkers. Normalization of SWATH-MS data by Loess-R method and identification of differentiators based on p-value were found to be optimal for biomarker discovery in this study. The study also demonstrates the need to base the choice of normalization method on the application of the data.

Effect of lifelong carnitine supplementation on plasma and tissue carnitine status, hepatic lipid metabolism and stress signalling pathways and skeletal muscle transcriptome in mice at advanced age.

While strong evidence from clinical studies suggests beneficial effects of carnitine supplementation on metabolic health, serious safety concerns associated with carnitine supplementation have been raised from studies in mice. Considering that the carnitine doses in these mice studies were up to 100 times higher than those used in clinical studies, the present study aimed to address possible safety concerns associated with long-term supplementation of a carnitine dose used in clinical trials. Two groups of NMRI mice were fed either a control or a carnitine-supplemented diet (1 g/kg diet) from weaning to 19 months of age, and parameters of hepatic lipid metabolism and stress signalling and skeletal muscle gene expression were analysed in the mice at 19 months of age. Concentrations of free carnitine and acetylcarnitine in plasma and tissues were higher in the carnitine than in the control group (P<0·05). Plasma concentrations of free carnitine and acetylcarnitine were higher in mice at adult age (10 and 15 months) than at advanced age (19 months) (P<0·05). Hepatic mRNA and protein levels of genes involved in lipid metabolism and stress signalling and hepatic and plasma lipid concentrations did not differ between the carnitine and the control group. Skeletal muscle transcriptome analysis in 19-month-old mice revealed only a moderate regulation between carnitine and control group. Lifelong carnitine supplementation prevents an age-dependent impairment of plasma carnitine status, but safety concerns associated with long-term supplementation of carnitine at doses used in clinical trials can be considered as unfounded.

Testing alternatives: the use of adipose-derived mesenchymal stem cells to slow neurodegeneration in a rat model of Parkinson's disease.

Parkinson's disease (PD) is a chronic neurodegenerative disease. Unfortunately, the effectiveness of anti-Parkinson treatments gradually diminishes owing to the progressive degeneration of the dopaminergic terminals. The research described here investigated the effect of adipose-derived mesenchymal stem cells (AD-MSC) versus that of an anti-Parkinson drug in a rat model of Parkinsonism. Forty adult rats were divided into four equal groups, each group receiving a different treatment: vehicle, rotenone, rotenone + AD-MSC, or rotenone + carbidopa/levodopa. Behavioral tests were carried out before and at the end of the treatment and specimens harvested from the midbrain were processed for light and electron microscopy. Genetic expression of glial fibrillary acidic protein (GFAP) and Nestin mRNA was assessed. Expression of the Lamin-B1 and Vimentin genes was measured, along with plasma levels of Angiopoietin-2 and dopamine. Treatment with rotenone induced pronounced motor deficits, as well as neuronal and glial alterations. The AD-MSC group showed improvements in motor function in the live animals and in the microscopic picture presented by their tissues. The fold change of both genes (GFAP and Nestin) decreased significantly in the AD-MSC and carbidopa/levodopa groups compared to the group with Parkinson's disease. Plasma levels of Angiopoietin-2 and dopamine were significantly increased after treatment (P < 0.001) compared to levels in the rats with Parkinson's disease. AD-MSC reduced neuronal degeneration more efficiently than did the anti-Parkinson drug in a rat model of Parkinsonism.

Hepatitis C virus drug resistance associated substitutions and their clinical relevance: Update 2018.

Nowadays, due to the development of potent Direct-Acting Antiviral Agents (DAAs) that specifically target NS3, NS5A and NS5B viral proteins, several new and highly efficacious options to treat chronic Hepatitis C virus (HCV) infection are available. The natural presence of resistance associated substitutions (RASs), as well as their rapid emergence during incomplete drug-pressure, are intrinsic characteristics of HCV that greatly affect treatment outcome and the chances to achieve a virolgical cure. To date, a high number of RASs in NS3, NS5A, and NS5B have been associated in vivo and/or in vitro with reduced susceptibility to DAAs, but no comprehensive RASs list is available. This review thus provides an updated, systematic overview of the role of RASs to currently approved DAAs or in phase II/III of clinical development against HCV-infection, discriminating their impact in different HCV-genotypes and DAAs, providing assistance for a fruitful use of HCV resistance testing in clinical practice.

Allosteric proteins as logarithmic sensors.

Many sensory systems, from vision and hearing in animals to signal transduction in cells, respond to fold changes in signal relative to background. Responding to fold change requires that the system senses signal on a logarithmic scale, responding identically to a change in signal level from 1 to 3, or from 10 to 30. It is an ongoing search in the field to understand the ways in which a logarithmic sensor can be implemented at the molecular level. In this work, we present evidence that logarithmic sensing can be implemented with a single protein, by means of allosteric regulation. Specifically, we find that mathematical models show that allosteric proteins can respond to stimuli on a logarithmic scale. Next, we present evidence from measurements in the literature that some allosteric proteins do operate in a parameter regime that permits logarithmic sensing. Finally, we present examples suggesting that allosteric proteins are indeed used in this capacity: allosteric proteins play a prominent role in systems where fold-change detection has been proposed. This finding suggests a role as logarithmic sensors for the many allosteric proteins across diverse biological processes.