In Vitro Inhibition of Histamine Release Behavior of Cetirizine Intercalated into Zn/Al- and Mg/Al-Layered Double Hydroxides

The intercalation of cetirizine into two types of layered double hydroxides, Zn/Al and Mg/Al, has been investigated by the ion exchange method to form CTZAN and CTMAN nanocomposites, respectively. The basal spacing of the nanocomposites were expanded to 31.9 Å for CTZAN and 31.2 Å for CTMAN, suggesting that cetirizine anion was intercalated into Layered double hydroxides (LDHs) and arranged in a tilted bilayer fashion. A Fourier transform infrared spectroscopy (FTIR) study supported the formation of both the nanocomposites, and the intercalated cetirizine is thermally more stable than its counterpart in free state. The loading of cetirizine in the nanocomposite was estimated to be about 57.2% for CTZAN and 60.7% CTMAN. The cetirizine release from the nanocomposites show sustained release manner and the release rate of cetirizine from CTZAN and CTMAN nanocomposites at pH 7.4 is remarkably lower than that at pH 4.8, presumably due to the different release mechanism. The inhibition of histamine release from RBL2H3 cells by the free cetirizine is higher than the intercalated cetirizine both in CTZAN and CTMAN nanocomposites. The viability in human Chang liver cells at 1000 μg/mL for CTZAN and CTMAN nanocomposites are 74.5 and 91.9%, respectively

TIMMA-R : an R package for predicting synergistic multi-targeted drug combinations in cancer cell lines or patient-derived samples

Network pharmacology-based prediction of multi-targeted drug combinations is becoming a promising strategy to improve anticancer efficacy and safety. We developed a logic-based network algorithm, called Target Inhibition Interaction using Maximization and Minimization Averaging (TIMMA), which predicts the effects of drug combinations based on their binary drug-target interactions and single-drug sensitivity profiles in a given cancer sample. Here, we report the R implementation of the algorithm (TIMMA-R), which is much faster than the original MATLAB code. The major extensions include modeling of multiclass drug-target profiles and network visualization. We also show that the TIMMA-R predictions are robust to the intrinsic noise in the experimental data, thus making it a promising high-throughput tool to prioritize drug combinations in various cancer types for follow-up experimentation or clinical applications.Peer reviewe

Sustained release formulation of an anti-tuberculosis drug based on para-amino salicylic acid-zinc layered hydroxide nanocomposite

Background: Tuberculosis (TB), is caused by the bacteria, Mycobacterium tuberculosis and its a threat to humans since centuries. Depending on the type of TB, its treatment can last for 6-24 months which is a major cause for patients non-compliance and treatment failure. Many adverse effects are associated with the currently available TB medicines, and there has been no new anti-tuberculosis drug on the market for more than 50 year, as the drug development is very lengthy and budget consuming process.Development of the biocompatible nano drug delivery systems with the ability to minimize the side effects of the drugs, protection of the drug from enzymatic degradation. And most importantly the drug delivery systems which can deliver the drug at target site would increase the therapeutic efficacy. Nanovehicles with their tendency to release the drug in a sustained manner would result in the bioavalibilty of the drugs in the body for a longer period of time and this would reduce the dosing frequency in drug administration. The biocompatible nanovehicles with the properties like sustained release of drug of the target site, protection of the drug from physio-chemical degradation, reduction in dosing frequency, and prolong bioavailability of drug in the body would result in the shortening of the treatment duration. All of these factors would improve the patient compliance with chemotherapy of TB.Result: An anti-tuberculosis drug, 4-amino salicylic acid (4-ASA) was successfully intercalated into the interlamellae of zinc layered hydroxide (ZLH) via direct reaction with zinc oxide suspension. The X-ray diffraction patterns and FTIR analyses indicate that the molecule was successfully intercalated into the ZLH interlayer space with an average basal spacing of 24 Å. Furthermore, TGA and DTG results show that the drug 4-ASA is stabilized in the interlayers by electrostatic interaction. The release of 4-ASA from the nanocomposite was found to be in a sustained manner. The nanocomposite treated with normal 3T3 cells shows it reduces cell viability in a dose- and time-dependent manner.Conclusions: Sustained release formulation of the nanocomposite, 4-ASA intercalated into zinc layered hydroxides, with its ease of preparation, sustained release of the active and less-toxic to the cell is a step forward for a more patient-friendly chemotherapy of Tuberculosis

The prognostic value of p53 mutation in pediatric marrow hypoplasia

<p>Abstract</p> <p>Background</p> <p>The tumor suppressor gene p53 is involved in the control of cell proliferation, particularly in stressed cells. p 53 gene mutations are the most frequent genetic event found in human cancers. Fanconi Anemia (FA) is the most common representative of inherited bone marrow failure syndromes (IBMFS) with a leukemic propensity. P 53 DNA alteration has not been studied before in Egyptian children with FA.</p> <p>Patients and methods</p> <p>we investigated p53 mutation in the bone marrow and peripheral blood of forty children, FA (n = 10), acquired aplastic anemia (AAA) (n = 10), and immune thrombocytopenia (ITP) as a control (n = 20), using real-time PCR by TaqMan probe assay</p> <p>Results</p> <p>Mutation of p53 gene was demonstrated in the BM of 90% (9/10) of children with FA, compared to 10% (1/10) in AAA (p < 0.001), while, no p53 DNA mutation was seen in the control group. A positive correlation between DNA breakage and presence of p53 mutation was seen in FA (p < 0.02, r0.81).</p> <p>Conclusion</p> <p>mutation of p53 gene in hypoplastic marrow especially FA may represent an early indicator of significant DNA genetic alteration with cancer propensity.</p

Cytokeratin expression during mouse embryonic and early postnatal mammary gland development

Cytokeratins are intermediate filament proteins found in most epithelial cells including the mammary epithelium. Specific cytokeratin expression has been found to mark different epithelial cell lineages and also to associate with putative mammary stem/progenitor cells. However, a comparative analysis of the expression of cytokaratins during embryonic and postnatal mammary development is currently lacking. Moreover, it is not clear whether the different classes of putative mammary stem/progenitor cells exist during embryonic development. Here, we use double/triple-label immunofluorescence and immunohistochemistry to systematically compare the expression of cytokeratin 5 (K5), cytokeratin 6 (K6), cytokeratin 8 (K8), cytokeratin 14 (K14) and cytokeratin 19 (K19) in embryonic and early postnatal mouse mammary glands. We show that K6+ and K8+/K14+ putative mammary progenitor cells arise during embryogenesis with distinct temporal and spatial distributions. Moreover, we describe a transient disconnection of the expression of K5 and K14, two cytokeratins that are often co-expressed, during the first postnatal weeks of mammary development. Finally, we report that cytokeratin expression in cultured primary mammary epithelial cells mimics that during the early stages of postnatal mammary development. These studies demonstrate an embryonic origin of putative mammary stem/progenitor cells. Moreover, they provide additional insights into the use of specific cytokeratins as markers of mammary epithelial differentiation, or the use of their promoters to direct gene overexpression or ablation in genetic studies of mouse mammary development

A novel signalling screen demonstrates that CALR mutations activate essential MAPK signalling and facilitate megakaryocyte differentiation.

Most MPN patients lacking JAK2 mutations harbour somatic CALR mutations that are thought to activate cytokine signalling although the mechanism is unclear. To identify kinases important for survival of CALR-mutant cells we developed a novel strategy (KISMET) which utilises the full range of kinase selectivity data available from each inhibitor and thus takes advantage of off-target noise that limits conventional siRNA or inhibitor screens. KISMET successfully identified known essential kinases in haematopoietic and non-haematopoietic cell lines and identified the MAPK pathway as required for growth of the CALR-mutated MARIMO cells. Expression of mutant CALR in murine or human haematopoietic cell lines was accompanied by MPL-dependent activation of MAPK signalling, and MPN patients with CALR mutations showed increased MAPK activity in CD34-cells, platelets and megakaryocytes. Although CALR mutations resulted in protein instability and proteosomal degradation, mutant CALR was able to enhance megakaryopoiesis and pro-platelet production from human CD34+ progenitors. These data link aberrant MAPK activation to the MPN phenotype and identify it as a potential therapeutic target in CALR-mutant positive MPNs.Leukemia accepted article preview online, 14 October 2016. doi:10.1038/leu.2016.280.Work in the Green lab is supported by Leukemia and Lymphoma Research, Cancer Research UK, the NIHR Cambridge Biomedical Research Centre, the Cambridge Experimental Cancer Medicine Centre and the Leukemia & Lymphoma Society of America. WW is supported by the Austrian Science Foundation (J 3578-B21). CGA is supported by Kay Kendall Leukaemia Fund clinical research fellowship. UM is supported by a Cancer Research UK Clinician Scientist Fellowship. Work in the Huntly lab is supported by the European Research Council, the MRC (UK), Bloodwise, the Cambridge NIHR funded BRC, KKLF and a WT/MRC Stem Cell centre grant. Work in the Green and Huntly Labs is supported by core support grants by the Wellcome Trust to the Cambridge Institute for Medical Research (100140/z/12/z) and Wellcome Trust-MRC Cambridge Stem Cell Institute (097922/Z/11/Z)

Predicting Diabetic Nephropathy Using a Multifactorial Genetic Model

AIMS: The tendency to develop diabetic nephropathy is, in part, genetically determined, however this genetic risk is largely undefined. In this proof-of-concept study, we tested the hypothesis that combined analysis of multiple genetic variants can improve prediction. METHODS: Based on previous reports, we selected 27 SNPs in 15 genes from metabolic pathways involved in the pathogenesis of diabetic nephropathy and genotyped them in 1274 Ashkenazi or Sephardic Jewish patients with Type 1 or Type 2 diabetes of >10 years duration. A logistic regression model was built using a backward selection algorithm and SNPs nominally associated with nephropathy in our population. The model was validated by using random "training" (75%) and "test" (25%) subgroups of the original population and by applying the model to an independent dataset of 848 Ashkenazi patients. RESULTS: The logistic model based on 5 SNPs in 5 genes (HSPG2, NOS3, ADIPOR2, AGER, and CCL5) and 5 conventional variables (age, sex, ethnicity, diabetes type and duration), and allowing for all possible two-way interactions, predicted nephropathy in our initial population (C-statistic = 0.672) better than a model based on conventional variables only (C = 0.569). In the independent replication dataset, although the C-statistic of the genetic model decreased (0.576), it remained highly associated with diabetic nephropathy (χ(2) = 17.79, p<0.0001). In the replication dataset, the model based on conventional variables only was not associated with nephropathy (χ(2) = 3.2673, p = 0.07). CONCLUSION: In this proof-of-concept study, we developed and validated a genetic model in the Ashkenazi/Sephardic population predicting nephropathy more effectively than a similarly constructed non-genetic model. Further testing is required to determine if this modeling approach, using an optimally selected panel of genetic markers, can provide clinically useful prediction and if generic models can be developed for use across multiple ethnic groups or if population-specific models are required

The Quantum Mitochondrion and Optimal Health

A sufficiently complex set of molecules, if subject to perturbation, will self-organise and show emergent behaviour. If such a system can take on information it will become subject to natural selection. This could explain how self-replicating molecules evolved into life and how intelligence arose. A pivotal step in this evolutionary process was of course the emergence of the eukaryote and the advent of the mitochondrion, which both enhanced energy production per cell and increased the ability to process, store and utilise information. Recent research suggest that from its inception life embraced quantum effects such as “tunnelling” and “coherence” while competition and stressful conditions provided a constant driver for natural selection. We believe that the biphasic adaptive response to stress described by hormesis – a process that captures information to enable adaptability, is central to this whole process. Critically, hormesis could improve mitochondrial quantum efficiency, improving the ATP/ROS ratio, while inflammation, which is tightly associated with the aging process, might do the opposite. This all suggests that to achieve optimal health and healthy ageing, one has to sufficiently stress the system to ensure peak mitochondrial function, which itself could reflect selection of optimum efficiency at the quantum level

The complex genetic landscape of familial MDS and AML reveals pathogenic germline variants.

The inclusion of familial myeloid malignancies as a separate disease entity in the revised WHO classification has renewed efforts to improve the recognition and management of this group of at risk individuals. Here we report a cohort of 86 acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) families with 49 harboring germline variants in 16 previously defined loci (57%). Whole exome sequencing in a further 37 uncharacterized families (43%) allowed us to rationalize 65 new candidate loci, including genes mutated in rare hematological syndromes (ADA, GP6, IL17RA, PRF1 and SEC23B), reported in prior MDS/AML or inherited bone marrow failure series (DNAH9, NAPRT1 and SH2B3) or variants at novel loci (DHX34) that appear specific to inherited forms of myeloid malignancies. Altogether, our series of MDS/AML families offer novel insights into the etiology of myeloid malignancies and provide a framework to prioritize variants for inclusion into routine diagnostics and patient management