Application of plasmonic nanomaterials in nanomedicine

Plasmonic nanoparticles are being researched as a noninvasive tool for ultrasensitive diagnostic, spectroscopic and, recently, therapeutic technologies. With particular antibody coatings on nanoparticles, they attach to the abnormal cells of interest (cancer or otherwise). Once attached, nanoparticles can be activated/heated with UV/visible/IR, RF or X-ray pulses, damaging the surrounding area of the abnormal cell to the point of death. Here, we describe an integrated approach to improved plasmonic therapy composed of nanomaterial optimization and the development of a theory for selective radiation nanophotothermolysis of abnormal biological cells with gold nanoparticles and selfassembled nanoclusters. The theory takes into account radiation-induced linear and nonlinear synergistic effects in biological cells containing nanostructures, with focus on optical, thermal, bubble formation and nanoparticle explosion phenomena. On the basis of the developed models, we discuss new ideas and new dynamic modes for cancer treatment by radiation activated nanoheaters, which involve nanocluster aggregation in living cells, microbubbles overlapping around laser-heated intracellular nanoparticles/ clusters, and laser thermal explosion mode of single nanoparticles (‘nanobombs’) delivered to the cells. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/2058

Impact of imputation methods on the amount of genetic variation captured by a single-nucleotide polymorphism panel in soybeans

Background Success in genome-wide association studies and marker-assisted selection depends on good phenotypic and genotypic data. The more complete this data is, the more powerful will be the results of analysis. Nevertheless, there are next-generation technologies that seek to provide genotypic information in spite of great proportions of missing data. The procedures these technologies use to impute genetic data, therefore, greatly affect downstream analyses. This study aims to (1) compare the genetic variance in a single-nucleotide polymorphism panel of soybean with missing data imputed using various methods, (2) evaluate the imputation accuracy and post-imputation quality associated with these methods, and (3) evaluate the impact of imputation method on heritability and the accuracy of genome-wide prediction of soybean traits. The imputation methods we evaluated were as follows: multivariate mixed model, hidden Markov model, logical algorithm, k-nearest neighbor, single value decomposition, and random forest. We used raw genotypes from the SoyNAM project and the following phenotypes: plant height, days to maturity, grain yield, and seed protein composition. Results We propose an imputation method based on multivariate mixed models using pedigree information. Our methods comparison indicate that heritability of traits can be affected by the imputation method. Genotypes with missing values imputed with methods that make use of genealogic information can favor genetic analysis of highly polygenic traits, but not genome-wide prediction accuracy. The genotypic matrix captured the highest amount of genetic variance when missing loci were imputed by the method proposed in this paper. Conclusions We concluded that hidden Markov models and random forest imputation are more suitable to studies that aim analyses of highly heritable traits while pedigree-based methods can be used to best analyze traits with low heritability. Despite the notable contribution to heritability, advantages in genomic prediction were not observed by changing the imputation method. We identified significant differences across imputation methods in a dataset missing 20 % of the genotypic values. It means that genotypic data from genotyping technologies that provide a high proportion of missing values, such as GBS, should be handled carefully because the imputation method will impact downstream analysis

Hyperglycaemia does not increase perfusion deficits after focal cerebral ischaemia in male Wistar rats

Background: Hyperglycaemia is associated with a worse outcome in acute ischaemic stroke patients; yet the pathophysiological mechanisms of hyperglycaemia-induced damage are poorly understood. We hypothesised that hyperglycaemia at the time of stroke onset exacerbates ischaemic brain damage by increasing the severity of the blood flow deficit. Methods: Adult, male Wistar rats were randomly assigned to receive vehicle or glucose solutions prior to permanent middle cerebral artery occlusion. Cerebral blood flow was assessed semi-quantitatively either 1 h after middle cerebral artery occlusion using 99mTc-D, L-hexamethylpropyleneamine oxime (99mTc-HMPAO) autoradiography or, in a separate study, using quantitative pseudo-continuous arterial spin labelling for 4 h after middle cerebral artery occlusion. Diffusion weighted imaging was performed alongside pseudo-continuous arterial spin labelling and acute lesion volumes calculated from apparent diffusion coefficient maps. Infarct volume was measured at 24 h using rapid acquisition with refocused echoes T2-weighted magnetic resonance imaging. Results: Glucose administration had no effect on the severity of ischaemia when assessed by either 99mTc-HMPAO autoradiography or pseudo-continuous arterial spin labelling perfusion imaging. In comparison to the vehicle group, apparent diffusion coefficient–derived lesion volume 2–4 h post-middle cerebral artery occlusion and infarct volume 24 h post-middle cerebral artery occlusion were significantly greater in the glucose group. Conclusions: Hyperglycaemia increased acute lesion and infarct volumes but there was no evidence that the acute blood flow deficit was exacerbated. The data reinforce the conclusion that the detrimental effects of hyperglycaemia are rapid, and that treatment of post-stroke hyperglycaemia in the acute period is essential but the mechanisms of hyperglycaemia-induced harm remain unclear

The thermal decomposition of esters, polyesters and related substances

In the first section of the thesis a study was made of the vapour-phase decomposition of the ester cyclohexyl benzoate. The ester was pyrolysed in a flow reactor system at temperatures between 30

Genome-Wide Identification of Allele-Specific Expression (ASE) in Response to Marek’s Disease Virus Infection Using Next Generation Sequencing.

Background Marek’s disease (MD), a T cell lymphoma induced by the highly oncogenic α-herpesvirus Marek’s disease virus (MDV), is the main chronic infectious disease concern threatening the poultry industry. Enhancing genetic resistance to MD in commercial poultry is an attractive method to augment MD vaccines, which is currently the control method of choice. In order to optimally implement this control strategy through marker-assisted selection (MAS) and to gain biological information, it is necessary to identify specific genes that influence MD incidence. Methods A genome-wide screen for allele-specific expression (ASE) in response to MDV infection was conducted. The highly inbred ADOL chicken lines 6 (MD resistant) and 7 (MD susceptible) were inter-mated in reciprocal crosses and half of the progeny challenged with MDV. Splenic RNA pools at a single time after infection for each treatment group point were generated, sequenced using a next generation sequencer, then analyzed for allele-specific expression (ASE). To validate and extend the results, Illumina GoldenGate assays for selected cSNPs were developed and used on all RNA samples from all 6 time points following MDV challenge. Results RNA sequencing resulted in 11-13+ million mappable reads per treatment group, 1.7+ Gb total sequence, and 22,655 high-confidence cSNPs. Analysis of these cSNPs revealed that 5360 cSNPs in 3773 genes exhibited statistically significant allelic imbalance. Of the 1536 GoldenGate assays, 1465 were successfully scored with all but 19 exhibiting evidence for allelic imbalance. Conclusions ASE is an efficient method to identify potentially all or most of the genes influencing this complex trait. The identified cSNPs can be further evaluated in resource populations to determine their allelic direction and size of effect on genetic resistance to MD as well as being directly implemented in genomic selection programs. The described method, although demonstrated in inbred chicken lines, is applicable to all traits in any diploid species, and should prove to be a simple method to identify the majority of genes controlling any complex trait

Genome-Wide Identification and Quantification of cis- and trans-Regulated Genes Responding to Marek’s Disease Virus Infection via Analysis of Allele-Specific Expression

Marek’s disease (MD) is a commercially important neoplastic disease of chickens caused by Marek’s disease virus (MDV), a naturally occurring oncogenic alphaherpesvirus. Selecting for increased genetic resistance to MD is a control strategy that can augment vaccinal control measures. To identify high-confidence candidate MD resistance genes, we conducted a genome-wide screen for allele-specific expression (ASE) amongst F1 progeny of two inbred chicken lines that differ substantially in MD resistance. High throughput sequencing was initially used to profile transcriptomes from pools of uninfected and infected individuals at 4 days post-infection to identify any genes showing ASE in response to MDV infection. RNA sequencing identified 22,655 single nucleotide polymorphisms (SNPs) of which 5,360 in 3,773 genes exhibited significant allelic imbalance. Illumina GoldenGate assays were subsequently used to quantify regulatory variation controlled at the gene (cis) and elsewhere in the genome (trans) by examining differences in expression between F1 individuals and artificial F1 RNA pools over six time periods in 1,536 of the most significant SNPs identified by RNA sequencing. Allelic imbalance as a result of cis-regulatory changes was confirmed in 861 of the 1,233 GoldenGate assays successfully examined. Furthermore we have identified seven genes that display trans-regulation only in infected animals and ∼500 SNP that show a complex interaction between cis- and trans-regulatory changes. Our results indicate ASE analyses are a powerful approach to identify regulatory variation responsible for differences in transcript abundance in genes underlying complex traits. And the genes with SNPs exhibiting ASE provide a strong foundation to further investigate the causative polymorphisms and genetic mechanisms for MD resistance. Finally, the methods used here for identifying specific genes and SNPs have practical implications for applying marker-assisted selection to complex traits that are difficult to measure in agricultural species, when expression differences are expected to control a portion of the phenotypic variance

Transcriptomic Analysis of Peritoneal Cells in a Mouse Model of Sepsis: Confirmatory and Novel Results in Early and Late Sepsis.

Background The events leading to sepsis start with an invasive infection of a primary organ of the body followed by an overwhelming systemic response. Intra-abdominal infections are the second most common cause of sepsis. Peritoneal fluid is the primary site of infection in these cases. A microarray-based approach was used to study the temporal changes in cells from the peritoneal cavity of septic mice and to identify potential biomarkers and therapeutic targets for this subset of sepsis patients. Results We conducted microarray analysis of the peritoneal cells of mice infected with a non-pathogenic strain of Escherichia coli. Differentially expressed genes were identified at two early (1 h, 2 h) and one late time point (18 h). A multiplexed bead array analysis was used to confirm protein expression for several cytokines which showed differential expression at different time points based on the microarray data. Gene Ontology based hypothesis testing identified a positive bias of differentially expressed genes associated with cellular development and cell death at 2 h and 18 h respectively. Most differentially expressed genes common to all 3 time points had an immune response related function, consistent with the observation that a few bacteria are still present at 18 h. Conclusions Transcriptional regulators like PLAGL2, EBF1, TCF7, KLF10 and SBNO2, previously not described in sepsis, are differentially expressed at early and late time points. Expression pattern for key biomarkers in this study is similar to that reported in human sepsis, indicating the suitability of this model for future studies of sepsis, and the observed differences in gene expression suggest species differences or differences in the response of blood leukocytes and peritoneal leukocytes

Genetic Resources, Genome Mapping and Evolutionary Genomics of the Pig (Sus scrofa)

The pig, a representative of the artiodactyla clade, is one of the first animals domesticated, and has become an important agriculture animal as one of the major human nutritional sources of animal based protein. The pig is also a valuable biomedical model organism for human health. The pig's importance to human health and nutrition is reflected in the decision to sequence its genome (3X). As an animal species with its wild ancestors present in the world, the pig provides a unique opportunity for tracing mammalian evolutionary history and defining signatures of selection resulting from both domestication and natural selection. Completion of the pig genome sequencing project will have significant impacts on both agriculture and human health. Following the pig whole genome sequence drafts, along with large-scale polymorphism data, it will be possible to conduct genome sweeps using association mapping, and identify signatures of selection. Here, we provide a description of the pig genome sequencing project and perspectives on utilizing genomic technologies to exploit pig genome evolution and the molecular basis for phenotypic traits for improving pig production and health

Comparison and Contrast of Genes and Biological Pathways Responding to Marek’s Disease Virus Infection Using Allele-Specific Expression and Differential Expression in Broiler and Layer Chickens.

Background Marek’s disease (MD) is a commercially important neoplastic disease of chickens caused by the Marek’s disease virus (MDV), a naturally occurring oncogenic alphaherpesvirus. Enhancing MD genetic resistance is desirable to augment current vaccines and other MD control measures. High throughput sequencing was used to profile splenic transcriptomes from individual F1 progeny infected with MDV at 4 days of age from both outbred broilers (meat-type) and inbred layer (egg-type) chicken lines that differed in MD genetic resistance. The resulting information was used to identify SNPs, genes, and biological pathways exhibiting allele-specific expression (ASE) in response to MDV infection in each type of chicken. In addition, we compared and contrasted the results of pathway analyses (ASE and differential expression (DE)) between chicken types to help inform on the biological response to MDV infection. Results With 7 individuals per line and treatment group providing high power, we identified 6,132 single nucleotide polymorphisms (SNPs) in 4,768 genes and 4,528 SNPs in 3,718 genes in broilers and layers, respectively, that exhibited ASE in response to MDV infection. Furthermore, 548 and 434 genes in broilers and layers, respectively, were found to show DE following MDV infection. Comparing the datasets, only 72 SNPs and 850 genes for ASE and 20 genes for DE were common between the two bird types. Although the chicken types used in this study were genetically different, at the pathway level, both TLR receptor and JAK/STAT signaling pathways were enriched as well as exhibiting a high proportion of ASE genes, especially at the beginning of both above mentioned regulatory pathways. Conclusions RNA sequencing with adequate biological replicates is a powerful approach to identify high confidence SNPs, genes, and pathways that are associated with transcriptional response to MDV infection. In addition, the SNPs exhibiting ASE in response to MDV infection provide a strong foundation for determining the extent to which variation in expression influences MD incidence plus yield genetic markers for genomic selection. However, given the paucity of overlap among ASE SNP sets (broilers vs. layers), it is likely that separate screens need to be incorporated for each population. Finally, comparison of gene lists obtained between these two diverse chicken types indicate the TLR and JAK/STAT signaling are conserved when responding to MDV infection and may be altered by selection of genes exhibiting ASE found at the start of each pathway

Stroke penumbra defined by an MRI-based oxygen challenge technique: 2. Validation based on the consequences of reperfusion

Magnetic resonance imaging (MRI) with oxygen challenge (T2* OC) uses oxygen as a metabolic biotracer to define penumbral tissue based on CMRO2 and oxygen extraction fraction. Penumbra displays a greater T2* signal change during OC than surrounding tissue. Since timely restoration of cerebral blood flow (CBF) should salvage penumbra, T2* OC was tested by examining the consequences of reperfusion on T2* OC-defined penumbra. Transient ischemia (109±20 minutes) was induced in male Sprague-Dawley rats (n=8). Penumbra was identified on T2*-weighted MRI during OC. Ischemia and ischemic injury were identified on CBF and apparent diffusion coefficient maps, respectively. Reperfusion was induced and scans repeated. T2 for final infarct and T2* OC were run on day 7. T2* signal increase to OC was 3.4% in contralateral cortex and caudate nucleus and was unaffected by reperfusion. In OC-defined penumbra, T2* signal increased by 8.4%±4.1% during ischemia and returned to 3.25%±0.8% following reperfusion. Ischemic core T2* signal increase was 0.39%±0.47% during ischemia and 0.84%±1.8% on reperfusion. Penumbral CBF increased from 41.94±13 to 116.5±25 mL per 100 g per minute on reperfusion. On day 7, OC-defined penumbra gave a normal OC response and was located outside the infarct. T2* OC-defined penumbra recovered when CBF was restored, providing further validation of the utility of T2* OC for acute stroke management