Bacterial heat shock protein genes during induction chemotherapy in pediatric patients with acute lymphoblastic leukemia.

Background: Heat shock proteins (HSP) protect cancer cells. Gastrointestinal bacteria contain HSP genes and can release extracellular vesicles which act as biological shuttles. Stress from treatment may result in a microbial community with more HSP genes, which could contribute to circulating HSP levels. Methods: The authors examined the abundance of five bacterial HSP genes pre-treatment and during induction in stool sequences from 30 pediatric acute lymphoblastic leukemia patients. Results: Decreased mean HTPG counts (p = 0.0024) pre-treatment versus induction were observed. During induction, HTPG, Shannon diversity and Bacteroidetes decreased (p = 7.5e-4; 1.1e-3; 8.6e-4), while DNAK and Firmicutes increased (p = 6.9e-3; 9.2e-4). Conclusion: Understanding microbial HSP gene community changes with treatment is the first step in determining if bacterial HSPs are important to the tumor microenvironment and leukemia treatment.

Metabolome Changes With Diet-Induced Remission in Pediatric Crohn's Disease.

BACKGROUND & AIMS: The Crohn's disease (CD) exclusion diet (CDED) plus partial enteral nutrition (PEN) and exclusive enteral nutrition (EEN) both induce remission in pediatric CD. CDED+PEN is better tolerated and able to sustain remission. We characterized the changes in fecal metabolites induced by CDED+PEN and EEN and their relationship with remission. METHODS: A total of 216 fecal metabolites were measured in 80 fecal samples at week (W) 0, W6, and W12, of children with mild to moderate CD in a prospective randomized trial comparing CDED+PEN vs EEN. The metabolites were measured using liquid chromatography coupled to mass spectrometry. Metagenome Kyoto Encyclopedia of Genes and Genomes Orthology analysis was performed to investigate the differential functional gene abundance involved in specific metabolic pathways. Data were analyzed according to clinical outcome of remission (W6_rem), no remission (W6_nr), sustained remission (W12_sr), and nonsustained (W12_nsr) remission. RESULTS: A decrease in kynurenine and succinate synthesis and an increase in N-α-acetyl-arginine characterized CDED+PEN W6_rem, whereas changes in lipid metabolism characterized EEN W6_rem, especially reflected by lower levels in ceramides. In contrast, fecal metabolites in EEN W6_nr were comparable to baseline/W0 samples. CDED+PEN W6_rem children maintained metabolome changes through W12. In contrast, W12_nsr children in the EEN group, who resumed a free diet after week 6, did not. The metabolome of CDED+PEN differed from EEN in the purine, pyrimidine, and sphingolipid pathways. A significant differential abundance in several genes involved in these pathways was detected. CONCLUSION: CDED+PEN- and EEN-induced remission are associated with significant changes in inflammatory bowel disease-associated metabolites such as kynurenine, ceramides, amino acids, and others. Sustained remission with CDED+PEN, but not EEN, was associated with persistent changes in metabolites. CLINICALTRIALS: gov, Number NCT01728870.

Harnessing DNA Nanotechnology and Chemistry for Applications in Photonics and Electronics.

Many photonic and electronic devices rely on nanotechnology and nanofabrication, but DNA-based approaches have yet to make a significant commercial impact in these fields even though DNA molecules are now well-established as versatile building blocks for nanostructures. As we describe here, DNA molecules can be chemically modified with a wide variety of functional groups enabling nanocargoes to be attached at precisely determined locations. DNA nanostructures can also be used as templates for the growth of inorganic structures. Together, these factors enable the use of DNA nanotechnology for the construction of many novel devices and systems. In this topical review, we discuss four case studies of potential applications in photonics and electronics: carbon nanotube transistors, devices for quantum computing, artificial electromagnetic materials, and enzymatic fuel cells. We conclude by speculating about the barriers to the exploitation of these technologies in real-world settings.

The impact of the host intestinal microbiome on carcinogenesis and the response to chemotherapy.

The microbiome consists of all microbes present on and within the human body. An unbalanced, or 'dysbiotic' intestinal microbiome is associated with inflammatory bowel disease, diabetes and some cancer types. Drug treatment can alter the intestinal microbiome composition. Additionally, some chemotherapeutics interact with microbiome components, leading to changes in drug safety and/or efficacy. The intestinal microbiome is a modifiable target, using strategies such as antibiotic treatment, fecal microbial transplantation or probiotic administration. Understanding the impact of the microbiome on the safety and efficacy of cancer treatment may result in improved treatment outcome. The present review seeks to summarize relevant research and look to the future of cancer treatment, where the intestinal microbiome is recognized as an actionable treatment target.

Lay abstract The microbiome describes all of the microorganisms (including bacteria, viruses and fungi) that are normally present on and inside the human body. Some diseases, including cancer, can be caused or worsened by an 'unbalanced' or 'unhealthy' gut microbiome. Some drugs that are given to people who have cancer can change the microbiome. Importantly, components of the gut microbiome can also change how a cancer drug will work in someone. We can change the microbiome in certain ways, like by giving someone antibiotics. Understanding how the microbiome influences the way anticancer drugs work is important because it could help us understand how to make cancer treatment safer and more effective. This review article summarizes available research on the impact of the microbiome on cancer treatment.

Guiding the folding pathway of DNA origami.

DNA origami is a robust assembly technique that folds a single-stranded DNA template into a target structure by annealing it with hundreds of short 'staple' strands. Its guiding design principle is that the target structure is the single most stable configuration. The folding transition is cooperative and, as in the case of proteins, is governed by information encoded in the polymer sequence. A typical origami folds primarily into the desired shape, but misfolded structures can kinetically trap the system and reduce the yield. Although adjusting assembly conditions or following empirical design rules can improve yield, well-folded origami often need to be separated from misfolded structures. The problem could in principle be avoided if assembly pathway and kinetics were fully understood and then rationally optimized. To this end, here we present a DNA origami system with the unusual property of being able to form a small set of distinguishable and well-folded shapes that represent discrete and approximately degenerate energy minima in a vast folding landscape, thus allowing us to probe the assembly process. The obtained high yield of well-folded origami structures confirms the existence of efficient folding pathways, while the shape distribution provides information about individual trajectories through the folding landscape. We find that, similarly to protein folding, the assembly of DNA origami is highly cooperative; that reversible bond formation is important in recovering from transient misfoldings; and that the early formation of long-range connections can very effectively enforce particular folds. We use these insights to inform the design of the system so as to steer assembly towards desired structures. Expanding the rational design process to include the assembly pathway should thus enable more reproducible synthesis, particularly when targeting more complex structures. We anticipate that this expansion will be essential if DNA origami is to continue its rapid development and become a reliable manufacturing technology.

Crohn's Disease Exclusion Diet Plus Partial Enteral Nutrition Induces Sustained Remission in a Randomized Controlled Trial.

BACKGROUND & AIMS: Exclusive enteral nutrition (EEN) is recommended for children with mild to moderate Crohn's disease (CD), but implementation is challenging. We compared EEN with the CD exclusion diet (CDED), a whole-food diet coupled with partial enteral nutrition (PEN), designed to reduce exposure to dietary components that have adverse effects on the microbiome and intestinal barrier. METHODS: We performed a 12-week prospective trial of children with mild to moderate CD. The children were randomly assigned to a group that received CDED plus 50% of calories from formula (Modulen, Nestlé) for 6 weeks (stage 1) followed by CDED with 25% PEN from weeks 7 to 12 (stage 2) (n = 40, group 1) or a group that received EEN for 6 weeks followed by a free diet with 25% PEN from weeks 7 to 12 (n = 38, group 2). Patients were evaluated at baseline and weeks 3, 6, and 12 and laboratory tests were performed; 16S ribosomal RNA gene (V4V5) sequencing was performed on stool samples. The primary endpoint was dietary tolerance. Secondary endpoints were intention to treat (ITT) remission at week 6 (pediatric CD activity index score below 10) and corticosteroid-free ITT sustained remission at week 12. RESULTS: Four patients withdrew from the study because of intolerance by 48 hours, 74 patients (mean age 14.2 ± 2.7 years) were included for remission analysis. The combination of CDED and PEN was tolerated in 39 children (97.5%), whereas EEN was tolerated by 28 children (73.6%) (P = .002; odds ratio for tolerance of CDED and PEN, 13.92; 95% confidence interval [CI] 1.68-115.14). At week 6, 30 (75%) of 40 children given CDED plus PEN were in corticosteroid-free remission vs 20 (59%) of 34 children given EEN (P = .38). At week 12, 28 (75.6%) of 37 children given CDED plus PEN were in corticosteroid-free remission compared with 14 (45.1%) of 31 children given EEN and then PEN (P = .01; odds ratio for remission in children given CDED and PEN, 3.77; CI 1.34-10.59). In children given CDED plus PEN, corticosteroid-free remission was associated with sustained reductions in inflammation (based on serum level of C-reactive protein and fecal level of calprotectin) and fecal Proteobacteria. CONCLUSION: CDED plus PEN was better tolerated than EEN in children with mild to moderate CD. Both diets were effective in inducing remission by week 6. The combination CDED plus PEN induced sustained remission in a significantly higher proportion of patients than EEN, and produced changes in the fecal microbiome associated with remission. These data support use of CDED plus PEN to induce remission in children with CD. Clinicaltrials.gov no: NCT01728870.

Biophysical characterisation of DNA origami nanostructures reveals inaccessibility to intercalation binding sites.

Intercalation of drug molecules into synthetic DNA nanostructures formed through self-assembled origami has been postulated as a valuable future method for targeted drug delivery. This is due to the excellent biocompatibility of synthetic DNA nanostructures, and high potential for flexible programmability including facile drug release into or near to target cells. Such favourable properties may enable high initial loading and efficient release for a predictable number of drug molecules per nanostructure carrier, important for efficient delivery of safe and effective drug doses to minimise non-specific release away from target cells. However, basic questions remain as to how intercalation-mediated loading depends on the DNA carrier structure. Here we use the interaction of dyes YOYO-1 and acridine orange with a tightly-packed 2D DNA origami tile as a simple model system to investigate intercalation-mediated loading. We employed multiple biophysical techniques including single-molecule fluorescence microscopy, atomic force microscopy, gel electrophoresis and controllable damage using low temperature plasma on synthetic DNA origami samples. Our results indicate that not all potential DNA binding sites are accessible for dye intercalation, which has implications for future DNA nanostructures designed for targeted drug delivery.

The Business of DNA Nanotechnology: Commercialization of Origami and Other Technologies.

It is often argued that DNA nanotechnology has a multitude of possible applications. However, despite great advances in the understanding of the fundamental principles of the field, to date, there has been comparatively little commercial activity. Analysis of patent applications and company case studies suggests that this is now starting to change. The number of patent application filings is increasing, and new companies are being formed to exploit technologies based on nanoscale structures and devices made from DNA. There are parallels between the commercial developments in this field and those observed in other areas of innovation. Further commercialization is expected and new players will emerge.

Improved inference of site-specific positive selection under a generalized parametric codon model when there are multinucleotide mutations and multiple nonsynonymous rates.

BACKGROUND: An excess of nonsynonymous substitutions, over neutrality, is considered evidence of positive Darwinian selection. Inference for proteins often relies on estimation of the nonsynonymous to synonymous ratio (ω = dN/dS) within a codon model. However, to ease computational difficulties, ω is typically estimated assuming an idealized substitution process where (i) all nonsynonymous substitutions have the same rate (regardless of impact on organism fitness) and (ii) instantaneous double and triple (DT) nucleotide mutations have zero probability (despite evidence that they can occur). It follows that estimates of ω represent an imperfect summary of the intensity of selection, and that tests based on the ω > 1 threshold could be negatively impacted. RESULTS: We developed a general-purpose parametric (GPP) modelling framework for codons. This novel approach allows specification of all possible instantaneous codon substitutions, including multiple nonsynonymous rates (MNRs) and instantaneous DT nucleotide changes. Existing codon models are specified as special cases of the GPP model. We use GPP models to implement likelihood ratio tests for ω > 1 that accommodate MNRs and DT mutations. Through both simulation and real data analysis, we find that failure to model MNRs and DT mutations reduces power in some cases and inflates false positives in others. False positives under traditional M2a and M8 models were very sensitive to DT changes. This was exacerbated by the choice of frequency parameterization (GY vs. MG), with rates sometimes > 90% under MG. By including MNRs and DT mutations, accuracy and power was greatly improved under the GPP framework. However, we also find that over-parameterized models can perform less well, and this can contribute to degraded performance of LRTs. CONCLUSIONS: We suggest GPP models should be used alongside traditional codon models. Further, all codon models should be deployed within an experimental design that includes (i) assessing robustness to model assumptions, and (ii) investigation of non-standard behaviour of MLEs. As the goal of every analysis is to avoid false conclusions, more work is needed on model selection methods that consider both the increase in fit engendered by a model parameter and the degree to which that parameter is affected by un-modelled evolutionary processes.

Sleep Disturbance and Cognitive Dysfunction in Multiple Sclerosis: a Systematic Review.

PURPOSE OF REVIEW: The present review summarizes recent research on the association between sleep disturbance and cognitive dysfunction in MS. Assessment methodology, domain-specific associations between sleep disturbance and cognitive dysfunction, and implications for future research and treatment are discussed. RECENT FINDINGS: All 12 studies included in this review found significant associations between sleep disturbance and cognitive dysfunction; however, results varied considerably depending on the assessment method used and the cognitive domain assessed. Self-reported sleep disturbance generally predicted self-report but not objective measures of cognitive dysfunction. Objective sleep measures (e.g., polysomnography, actigraphy) generally predicted objective impairments in processing speed and attention; however, objective sleep disturbance was more variable in predicting performance in other cognitive domains (e.g., memory, executive function). Sleep disturbance may help predict future cognitive decline in MS. Results highlight the need to integrate sleep assessment into routine MS care. Interventions aimed treating sleep disturbance may offer promise for improving cognitive dysfunction in MS.

Diagnostic and Clinical Utility of the GAD-2 for Screening Anxiety Symptoms in Individuals With Multiple Sclerosis.

OBJECTIVE: To assess the diagnostic and clinical utility of the 2-item Generalized Anxiety Disorder Scale (GAD-2) for screening anxiety symptoms in individuals with multiple sclerosis (MS). DESIGN: Cross-sectional. SETTING: University-affiliated MS neurology and rehabilitation center. PARTICIPANTS: The sample comprised adults (N=99) (ages 19-72; mean ± SD=46.2±13.0; 75% women) with a physician-confirmed MS diagnosis who were receiving care in a university-affiliated MS center. Disease durations ranged from 1 to 37 years (mean ± SD=10.7±8.4). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Participants completed the 7-item Generalized Anxiety Disorder Scale (GAD-7) and GAD-2. Internal consistency was calculated for both measures. Area under the receiver operating characteristics curve (AUC), the 95% confidence interval for the AUC, and Youden's J were calculated to determine the optimal GAD-2 cutoff score for identifying clinically significant anxiety symptoms, as defined by the previously validated GAD-7 cutoff score of ≥8. RESULTS: Internal consistency was excellent for the GAD-7 (Cronbach α=.91) and acceptable for the GAD-2 (α=.77), and the measures were highly correlated (r=.94). The GAD-2 had excellent overall accuracy for identifying clinically significant anxiety symptoms (AUC=0.97; 95% confidence interval, 0.94-1.00). A GAD-2 cutoff score of ≥3 provided an optimal balance of good sensitivity (0.87) and excellent specificity (0.92) for detecting clinically significant anxiety symptoms. Alternatively, a cutoff score of ≥2 provided excellent sensitivity (1.00) and fair specificity (0.76). CONCLUSIONS: The GAD-2 is a clinically useful and psychometrically valid tool for screening anxiety symptoms in MS rehabilitation and neurology care settings. Importantly, this tool has the potential to identify individuals with MS who are at risk for anxiety disorders and who may benefit from rehabilitation psychology interventions to ultimately improve functioning and quality of life.

Towards a Bioelectronic Computer: A Theoretical Study of a Multi-Layer Biomolecular Computing System That Can Process Electronic Inputs.

DNA molecular machines have great potential for use in computing systems. Since Adleman originally introduced the concept of DNA computing through his use of DNA strands to solve a Hamiltonian path problem, a range of DNA-based computing elements have been developed, including logic gates, neural networks, finite state machines (FSMs) and non-deterministic universal Turing machines. DNA molecular machines can be controlled using electrical signals and the state of DNA nanodevices can be measured using electrochemical means. However, to the best of our knowledge there has as yet been no demonstration of a fully integrated biomolecular computing system that has multiple levels of information processing capacity, can accept electronic inputs and is capable of independent operation. Here we address the question of how such a system could work. We present simulation results showing that such an integrated hybrid system could convert electrical impulses into biomolecular signals, perform logical operations and take a decision, storing its history. We also illustrate theoretically how the system might be able to control an autonomous robot navigating through a maze. Our results suggest that a system of the proposed type is technically possible but for practical applications significant advances would be required to increase its speed.

Synergistic Biomineralization Phenomena Created by a Combinatorial Nacre Protein Model System.

In the nacre or aragonite layer of the mollusk shell, proteomes that regulate both the early stages of nucleation and nano-to-mesoscale assembly of nacre tablets from mineral nanoparticle precursors exist. Several approaches have been developed to understand protein-associated mechanisms of nacre formation, yet we still lack insight into how protein ensembles or proteomes manage nucleation and crystal growth. To provide additional insights, we have created a proportionally defined combinatorial model consisting of two nacre-associated proteins, C-RING AP7 (shell nacre, Haliotis rufescens) and pseudo-EF hand PFMG1 (oyster pearl nacre, Pinctada fucata), whose individual in vitro mineralization functionalities are well-documented and distinct from one another. Using scanning electron microscopy, flow cell scanning transmission electron microscopy, atomic force microscopy, Ca(II) potentiometric titrations, and quartz crystal microbalance with dissipation monitoring quantitative analyses, we find that both nacre proteins are functionally active within the same mineralization environments and, at 1:1 molar ratios, synergistically create calcium carbonate mesoscale structures with ordered intracrystalline nanoporosities, extensively prolong nucleation times, and introduce an additional nucleation event. Further, these two proteins jointly create nanoscale protein aggregates or phases that under mineralization conditions further assemble into protein-mineral polymer-induced liquid precursor-like phases with enhanced ACC stabilization capabilities, and there is evidence of intermolecular interactions between AP7 and PFMG1 under these conditions. Thus, a combinatorial model system consisting of more than one defined biomineralization protein dramatically changes the outcome of the in vitro biomineralization process.

A Robust ANOVA Approach to Estimating a Phylogeny from Multiple Genes.

In this article, we address the issue of estimating the phylogenetic tree based on sequence data across a set of genes. Recognizing that the individual gene trees may not all share the same evolutionary history due to lateral gene transfer or differences in rates of evolution for instance, we develop a robust algorithm for tree estimation based on pairwise distances computed gene by gene. A robust analysis of variance (ANOVA) is used to combine the distances across all genes giving a summary distance for all genes. The tree can then be constructed using any distance method such as BIONJ. Using the weights from the robust ANOVA, we can then identify the outlying genes and taxa for further examination. As the method is based on distances, computation is much faster than maximum likelihood on the concatenated genes. It is also very straightforward to carry out a bootstrap analysis using standard methods for regression models. We test our methods in a comprehensive simulation study and apply them to three data sets recently analyzed in the literature.

Seasonal assemblages and short-lived blooms in coastal north-west Atlantic Ocean bacterioplankton.

Temperate oceans are inhabited by diverse and temporally dynamic bacterioplankton communities. However, the role of the environment, resources and phytoplankton dynamics in shaping marine bacterioplankton communities at different time scales remains poorly constrained. Here, we combined time series observations (time scales of weeks to years) with molecular analysis of formalin-fixed samples from a coastal inlet of the north-west Atlantic Ocean to show that a combination of temperature, nitrate, small phytoplankton and Synechococcus abundances are best predictors for annual bacterioplankton community variability, explaining 38% of the variation. Using Bayesian mixed modelling, we identified assemblages of co-occurring bacteria associated with different seasonal periods, including the spring bloom (e.g. Polaribacter, Ulvibacter, Alteromonadales and ARCTIC96B-16) and the autumn bloom (e.g. OM42, OM25, OM38 and Arctic96A-1 clades of Alphaproteobacteria, and SAR86, OM60 and SAR92 clades of Gammaproteobacteria). Community variability over spring bloom development was best explained by silicate (32%)--an indication of rapid succession of bacterial taxa in response to diatom biomass--while nanophytoplankton as well as picophytoplankton abundance explained community variability (16-27%) over the transition into and out of the autumn bloom. Moreover, the seasonal structure was punctuated with short-lived blooms of rare bacteria including the KSA-1 clade of Sphingobacteria related to aromatic hydrocarbon-degrading bacteria.

BiomeNet: a Bayesian model for inference of metabolic divergence among microbial communities.

Metagenomics yields enormous numbers of microbial sequences that can be assigned a metabolic function. Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic subnetworks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. Through this framework, the model can capture nested structures within the data. BiomeNet is unique in modeling each metagenome sample as a mixture of complex metabolic systems (metabosystems). The metabosystems are composed of mixtures of tightly connected metabolic subnetworks. BiomeNet differs from other unsupervised methods by allowing researchers to discriminate groups of samples through the metabolic patterns it discovers in the data, and by providing a framework for interpreting them. We describe a collapsed Gibbs sampler for inference of the mixture weights under BiomeNet, and we use simulation to validate the inference algorithm. Application of BiomeNet to human gut metagenomes revealed a metabosystem with greater prevalence among inflammatory bowel disease (IBD) patients. Based on the discriminatory subnetworks for this metabosystem, we inferred that the community is likely to be closely associated with the human gut epithelium, resistant to dietary interventions, and interfere with human uptake of an antioxidant connected to IBD. Because this metabosystem has a greater capacity to exploit host-associated glycans, we speculate that IBD-associated communities might arise from opportunist growth of bacteria that can circumvent the host's nutrient-based mechanism for bacterial partner selection.

Modelling DNA origami self-assembly at the domain level.

We present a modelling framework, and basic model parameterization, for the study of DNA origami folding at the level of DNA domains. Our approach is explicitly kinetic and does not assume a specific folding pathway. The binding of each staple is associated with a free-energy change that depends on staple sequence, the possibility of coaxial stacking with neighbouring domains, and the entropic cost of constraining the scaffold by inserting staple crossovers. A rigorous thermodynamic model is difficult to implement as a result of the complex, multiply connected geometry of the scaffold: we present a solution to this problem for planar origami. Coaxial stacking of helices and entropic terms, particularly when loop closure exponents are taken to be larger than those for ideal chains, introduce interactions between staples. These cooperative interactions lead to the prediction of sharp assembly transitions with notable hysteresis that are consistent with experimental observations. We show that the model reproduces the experimentally observed consequences of reducing staple concentration, accelerated cooling, and absent staples. We also present a simpler methodology that gives consistent results and can be used to study a wider range of systems including non-planar origami.

p53 and Pten control neural and glioma stem/progenitor cell renewal and differentiation.

Glioblastoma (GBM) is a highly lethal brain tumour presenting as one of two subtypes with distinct clinical histories and molecular profiles. The primary GBM subtype presents acutely as a high-grade disease that typically harbours mutations in EGFR, PTEN and INK4A/ARF (also known as CDKN2A), and the secondary GBM subtype evolves from the slow progression of a low-grade disease that classically possesses PDGF and TP53 events. Here we show that concomitant central nervous system (CNS)-specific deletion of p53 and Pten in the mouse CNS generates a penetrant acute-onset high-grade malignant glioma phenotype with notable clinical, pathological and molecular resemblance to primary GBM in humans. This genetic observation prompted TP53 and PTEN mutational analysis in human primary GBM, demonstrating unexpectedly frequent inactivating mutations of TP53 as well as the expected PTEN mutations. Integrated transcriptomic profiling, in silico promoter analysis and functional studies of murine neural stem cells (NSCs) established that dual, but not singular, inactivation of p53 and Pten promotes an undifferentiated state with high renewal potential and drives increased Myc protein levels and its associated signature. Functional studies validated increased Myc activity as a potent contributor to the impaired differentiation and enhanced renewal of NSCs doubly null for p53 and Pten (p53(-/-) Pten(-/-)) as well as tumour neurospheres (TNSs) derived from this model. Myc also serves to maintain robust tumorigenic potential of p53(-/-) Pten(-/-) TNSs. These murine modelling studies, together with confirmatory transcriptomic/promoter studies in human primary GBM, validate a pathogenetic role of a common tumour suppressor mutation profile in human primary GBM and establish Myc as an important target for cooperative actions of p53 and Pten in the regulation of normal and malignant stem/progenitor cell differentiation, self-renewal and tumorigenic potential.

Diagnosis and management of a herpes nipple infection that resulted in neonatal HSV encephalitis.

We present a case of a primigravida in her 30s who had a caesarean delivery of dichorionic diamniotic twins at 33 weeks of gestation. Her postpartum course was complicated by a herpes simplex virus (HSV) infection of her nipple, found after her neonates were diagnosed with HSV encephalitis. She was evaluated at her 3-week postpartum visit and reported that her neonates were concurrently admitted to the neonatal intensive care unit with disseminated neonatal HSV-1. The patient and her partner were in a monogamous relationship with no known history of HSV. Physical examination demonstrated a vertical fissure on the face of her right nipple and a small cluster of vesicles on her left hand. PCR swabs of the lesions were positive for HSV-1 at both locations. The patient was started on oral valacyclovir 1000 mg two times per day, topical acyclovir ointment applied 4-6 times per day and mupirocin ointment applied 3 times per day to her breast with resolution of her breast lesions. She was able to continue expressing her breastmilk with the help of a pump and then resumed breastfeeding once her infection was cleared. Her infants recovered after prolonged parenteral antiviral therapy with age-appropriate development at follow-up.