Insights into the influences of carboxymethyl-β-cyclodextrin on DNA formulations characteristics and gene transfection efficiency

BACKGROUND Gene therapy is an expanding field and it can treat genetic and acquired diseases. OBJECTIVE It was found that formulations with DNA: CM-β-CD (Carboxymethyl-beta-cyclodextrin): Pluronic-F127 1:3:3 and 1:3 DNA: CM-β-CD are the most stable formulations indicating high incorporation of DNA within CM-β -CD. METHOD Gel electrophoresis revealed DNA with low CM-β -CD concentration has formed a more stable complex. Samples 1:3 DNA: CM-β-CD and 1:3:3 DNA: CM-β-CD: Pluronic-127 show no DNA fragment, suggesting good condensation of DNA inside cyclodextrin cavity. RESULTS This was confirmed by fluorescence data where fluorescence intensity was reduced for samples DNA: CM-β-CD 1:3. Overall, the findings showed that Carboxymethyl-beta-cyclodextrin (as a novel non-viral gene vector) was able to provide condensation and protection to the DNA, with and without Pluronic-F127, at low concentration. CONCLUSION pDNA/CM-β-CD complex has not only shown to be able to transfect COS 7 and SHSY5Y cell lines, but it gives a higher transfection efficiency than that produced by the TransIT-LT1 commercial transfection reagent

Investigating the mechanisms of methotrexate neurotoxicity in patients with childhood leukaemia and long-term survivors.

Background/Objectives Adverse neurological events are common (4-20%) during treatment for pediatric acute lymphoblastic leukaemia (ALL) and include seizures, stroke like syndrome and leukoencephalopathy. In addition, chronic neurotoxicity is emerging as a worrying late effect of treatment with long-term survivors experiencing decreased executive function, processing speed and memory function. Survivors are also at increased risk of experiencing learning difficulties, social withdrawal issues and inattention hyperactivity disorders. Methotrexate, an anti-folate chemotherapy agent, is a mainstay of pediatric leukemia treatment regimens globally and is widely implicated as a cause of these neurological side effects. We hypothesise that methotrexate disrupts DNA methylation via effects on S-adenosyl methionine, a key metabolic component that has previously been described to regulate genes involved in myelination. Design/Methods Using both the oligodendrocytic-like cell line MO3.13 and glial cells derived from induced pluripotent stem cells (iPSC) treated with methotrexate, we assayed for changes in DNA methylation and effects on gene expression using whole-genome methylation arrays and RNAseq, respectively. Genes with corresponding methylation and expression changes were selected for further studies of expression by real-time qPCR and assessment of protein levels. Results We identified DNA methylation and corresponding expression changes in genes involved in neurodevelopmental pathways and neurological disorders. Of particular interest was dose-dependent demethylation and increased gene expression of IRS1, a vital component of insulin signalling pathways that is highly expressed in neural tissue and implicated in regulating cognitive performance. We also detected altered DNA methylation within the PLP1 gene, which encodes the most prevalent protein component of myelin. We found that methotrexate treatment in iPSC-derived oligodendrocytes resulted in increased PLP1 methylation associated with a reduction in PLP1 transcript levels as well as PLP1 protein levels. Conclusions Our work provides insight as to the biological mechanisms behind methotrexate-induced neurological side effects for the first time and implicates altered insulin signalling and myelination pathways as a potential causative factor in neurotoxicity. Further work including the use of animal models is warranted for advancing these results towards informing clinical practice

Differentiation of Human Embryonic Stem Cells to Sympathetic Neurons: A Potential Model for Understanding Neuroblastoma Pathogenesis

Background and Aims: Previous studies modelling human neural crest differentiation from stem cells have resulted in a low yield of sympathetic neurons. Our aim was to optimise a method for the differentiation of human embryonic stem cells (hESCs) to sympathetic neuron-like cells (SN) to model normal human SNS development. Results: Using stromal-derived inducing activity (SDIA) of PA6 cells plus BMP4 and B27 supplements, the H9 hESC line was differentiated to neural crest stem-like cells and SN-like cells. After 7 days of PA6 cell coculture, mRNA expression of SNAIL and SOX-9 neural crest specifier genes and the neural marker peripherin (PRPH) increased. Expression of the pluripotency marker OCT 4 decreased, whereas TP53 and LIN28B expression remained high at levels similar to SHSY5Y and IMR32 neuroblastoma cell lines. A 5-fold increase in the expression of the catecholaminergic marker tyrosine hydroxylase (TH) and the noradrenergic marker dopamine betahydroxylase (DBH) was observed by day 7 of differentiation. Fluorescence-activated cell sorting for the neural crest marker p75, enriched for cells expressing p75, DBH, TH, and PRPH, was more specific than p75 neural crest stem cell (NCSC) microbeads. On day 28 post p75 sorting, dual immunofluorescence identified sympathetic neurons by PRPH and TH copositivity cells in 20% of the cell population. Noradrenergic sympathetic neurons, identified by copositivity for both PHOX2B and DBH, were present in 9.4% ± 5.5% of cells. Conclusions: We have optimised a method for noradrenergic SNS development using the H9 hESC line to improve our understanding of normal human SNS development and, in a future work, the pathogenesis of neuroblastoma

Replication of Associations of Genetic Loci Outside the HLA Region With Susceptibility to Anti-Cyclic Citrullinated Peptide-Negative Rheumatoid Arthritis

OBJECTIVE: Genetic polymorphisms within the HLA region explain only a modest proportion of anti-cyclic citrullinated peptide (anti-CCP)-negative rheumatoid arthritis (RA) heritability. However, few non-HLA markers have been identified so far. This study was undertaken to replicate the associations of anti-CCP-negative RA with non-HLA genetic polymorphisms demonstrated in a previous study. METHODS: The Rheumatoid Arthritis Consortium International densely genotyped 186 autoimmune-related regions in 3,339 anti-CCP-negative RA patients and 15,870 controls across 6 different populations using the Illumina ImmunoChip array. We performed a case-control replication study of the anti-CCP-negative markers with the strongest associations in that discovery study, in an independent cohort of anti-CCP-negative UK RA patients. Individuals from the arcOGEN Consortium and Wellcome Trust Case Control Consortium were used as controls. Genotyping in cases was performed using Sequenom MassArray technology. Genome-wide data from controls were imputed using the 1000 Genomes Phase I integrated variant call set release version 3 as a reference panel. RESULTS: After genotyping and imputation quality control procedures, data were available for 15 non-HLA single-nucleotide polymorphisms in 1,024 cases and 6,348 controls. We confirmed the known markers ANKRD55 (meta-analysis odds ratio [OR] 0.80; P = 2.8 × 10(-13) ) and BLK (OR 1.13; P = 7.0 × 10(-6) ) and identified new and specific markers of anti-CCP-negative RA (prolactin [PRL] [OR 1.13; P = 2.1 × 10(-6) ] and NFIA [OR 0.85; P = 2.5 × 10(-6) ]). Neither of these loci is associated with other common, complex autoimmune diseases. CONCLUSION: Anti-CCP-negative RA and anti-CCP-positive RA are genetically different disease subsets that only partially share susceptibility factors. Genetic polymorphisms located near the PRL and NFIA genes represent examples of genetic susceptibility factors specific for anti-CCP-negative RA

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Modelling of the effect of ELMs on fuel retention at the bulk W divertor of JET

Effect of ELMs on fuel retention at the bulk W target of JET ITER-Like Wall was studied with multi-scale calculations. Plasma input parameters were taken from ELMy H-mode plasma experiment. The energetic intra-ELM fuel particles get implanted and create near-surface defects up to depths of few tens of nm, which act as the main fuel trapping sites during ELMs. Clustering of implantation-induced vacancies were found to take place. The incoming flux of inter-ELM plasma particles increases the different filling levels of trapped fuel in defects. The temperature increase of the W target during the pulse increases the fuel detrapping rate. The inter-ELM fuel particle flux refills the partially emptied trapping sites and fills new sites. This leads to a competing effect on the retention and release rates of the implanted particles. At high temperatures the main retention appeared in larger vacancy clusters due to increased clustering rate

An assessment of nitrogen concentrations from spectroscopic measurements in the JET and ASDEX upgrade divertor

The impurity concentration in the tokamak divertor plasma is a necessary input for predictive scaling of divertor detachment, however direct measurements from existing tokamaks in different divertor plasma conditions are limited. To address this, we have applied a recently developed spectroscopic N II line ratio technique for measuring the N concentration in the divertor to a range of H-mode and L-mode plasma from the ASDEX Upgrade and JET tokamaks, respectively. The results from both devices show that as the power crossing the separatrix, P$_{sep}$, is increased under otherwise similar core conditions (e.g. density), a higher N concentration is required to achieve the same detachment state. For example, the N concentrations at the start of detachment increase from ≈2% to ≈9% as Psep is increased from ≈2.5 MW to ≈7 MW. These results tentatively agree with scaling law predictions (e.g. Goldston et al.) motivating a further study examining the parameters which affect the N concentration required to reach detachment. Finally, the N concentrations from spectroscopy and the ratio of D and N gas valve fluxes agree within experimental uncertainty only when the vessel surfaces are fully-loaded with N

Impact of fast ions on density peaking in JET: fluid and gyrokinetic modeling

The effect of fast ions on turbulent particle transport, driven by ion temperature gradient (ITG)/ trapped electron mode turbulence, is studied. Two neutral beam injection (NBI) heated JET discharges in different regimes are analyzed at the radial position ρ$_{t}$=0.6, one of them an L-mode and the other one an H-mode discharge. Results obtained from the computationally efficient fluid model EDWM and the gyro-fluid model TGLF are compared to linear and nonlinear gyrokinetic GENE simulations as well as the experimentally obtained density peaking. In these models, the fast ions are treated as a dynamic species with a Maxwellian background distribution. The dependence of the zero particle flux density gradient (peaking factor) on fast ion density, temperature and corresponding gradients, is investigated. The simulations show that the inclusion of a fast ion species has a stabilizing influence on the ITG mode and reduces the peaking of the main ion and electron density profiles in the absence of sources. The models mostly reproduce the experimentally obtained density peaking for the L-mode discharge whereas the H-mode density peaking is significantly underpredicted, indicating the importance of the NBI particle source for the H-mode density profile

Current Research into Applications of Tomography for Fusion Diagnostics

Retrieving spatial distribution of plasma emissivity from line integrated measurements on tokamaks presents a challenging task due to ill-posedness of the tomography problem and limited number of the lines of sight. Modern methods of plasma tomography therefore implement a-priori information as well as constraints, in particular some form of penalisation of complexity. In this contribution, the current tomography methods under development (Tikhonov regularisation, Bayesian methods and neural networks) are briefly explained taking into account their potential for integration into the fusion reactor diagnostics. In particular, current development of the Minimum Fisher Regularisation method is exemplified with respect to real-time reconstruction capability, combination with spectral unfolding and other prospective tasks