Reduced haemodynamic response in the ageing visual cortex measured by absolute fNIRS

The effect of healthy ageing on visual cortical activation is still to be fully explored. This study aimed to elucidate whether the haemodynamic response (HDR) of the visual cortex altered as a result of ageing. Visually normal (healthy) participants were presented with a simple visual stimulus (reversing checkerboard). Full optometric screening was implemented to identify two age groups: younger adults (n = 12, mean age 21) and older adults (n = 13, mean age 71). Frequency-domain Multi-distance (FD-MD) functional Near-Infrared Spectroscopy (fNIRS) was used to measure absolute changes in oxygenated [HbO] and deoxygenated [HbR] haemoglobin concentrations in the occipital cortices. Utilising a slow event-related design, subjects viewed a full field reversing checkerboard with contrast and check size manipulations (15 and 30 minutes of arc, 50% and 100% contrast). Both groups showed the characteristic response of increased [HbO] and decreased [HbR] during stimulus presentation. However, older adults produced a more varied HDR and often had comparable levels of [HbO] and [HbR] during both stimulus presentation and baseline resting state. Younger adults had significantly greater concentrations of both [HbO] and [HbR] in every investigation regardless of the type of stimulus displayed (p<0.05). The average variance associated with this age-related effect for [HbO] was 88% and [HbR] 91%. Passive viewing of a visual stimulus, without any cognitive input, showed a marked age-related decline in the cortical HDR. Moreover, regardless of stimulus parameters such as check size, the HDR was characterised by age. In concurrence with present neuroimaging literature, we conclude that the visual HDR decreases as healthy ageing proceeds

Treatment of refractory epilepsy with natalizumab in a patient with multiple sclerosis. Case report

Background. Multiple sclerosis (MS) is considered an autoimmune disease of the central nervous system and therapeutic inhibition of leukocyte migration with natalizumab, an anti-alpha4 integrin antibody, is highly effective in patients with MS. Recent studies performed in experimental animal models with relevance to human disease suggested a key role for blood-brain barrier damage and leukocyte trafficking mechanisms also in the pathogenesis of epilepsy. In addition, vascular alterations and increased leukocyte accumulation into the brain were recently documented in patients with refractory epilepsy independently on the disease etiology. Case report. Here we describe the clinical course of a 24-year-old patient with MS in whom abrupt tonic-clonic generalized seizures manifested at disease onset. Although MS had a more favorable course, treatment with glatiramer acetate and antiepileptic drugs for 7 years had no control on seizure generation and the patient developed severe refractory epilepsy. Interestingly, generalized seizures preceded new MS relapses suggesting that seizure activity may contribute to MS worsening creating a positive feedback loop between the two disease conditions. Notably, treatment with natalizumab for 12 months improved MS condition and led to a dramatic reduction of seizures. Conclusion. Our case report suggests that inhibition of leukocyte adhesion may represent a new potential therapeutic approach in epilepsy and complement the traditional therapy with anti-epileptic drugs

Cell-selective labeling using amino acid precursors for proteomic studies of multicellular environments.

We report a technique to selectively and continuously label the proteomes of individual cell types in coculture, named cell type-specific labeling using amino acid precursors (CTAP). Through transgenic expression of exogenous amino acid biosynthesis enzymes, vertebrate cells overcome their dependence on supplemented essential amino acids and can be selectively labeled through metabolic incorporation of amino acids produced from heavy isotope-labeled precursors. When testing CTAP in several human and mouse cell lines, we could differentially label the proteomes of distinct cell populations in coculture and determine the relative expression of proteins by quantitative mass spectrometry. In addition, using CTAP we identified the cell of origin of extracellular proteins secreted from cells in coculture. We believe that this method, which allows linking of proteins to their cell source, will be useful in studies of cell-cell communication and potentially for discovery of biomarkers

Time to Recurrence and Survival in Serous Ovarian Tumors Predicted from Integrated Genomic Profiles

Serous ovarian cancer (SeOvCa) is an aggressive disease with differential and often inadequate therapeutic outcome after standard treatment. The Cancer Genome Atlas (TCGA) has provided rich molecular and genetic profiles from hundreds of primary surgical samples. These profiles confirm mutations of TP53 in ∼100% of patients and an extraordinarily complex profile of DNA copy number changes with considerable patient-to-patient diversity. This raises the joint challenge of exploiting all new available datasets and reducing their confounding complexity for the purpose of predicting clinical outcomes and identifying disease relevant pathway alterations. We therefore set out to use multi-data type genomic profiles (mRNA, DNA methylation, DNA copy-number alteration and microRNA) available from TCGA to identify prognostic signatures for the prediction of progression-free survival (PFS) and overall survival (OS). prediction algorithm and applied it to two datasets integrated from the four genomic data types. We (1) selected features through cross-validation; (2) generated a prognostic index for patient risk stratification; and (3) directly predicted continuous clinical outcome measures, that is, the time to recurrence and survival time. We used Kaplan-Meier p-values, hazard ratios (HR), and concordance probability estimates (CPE) to assess prediction performance, comparing separate and integrated datasets. Data integration resulted in the best PFS signature (withheld data: p-value = 0.008; HR = 2.83; CPE = 0.72).We provide a prediction tool that inputs genomic profiles of primary surgical samples and generates patient-specific predictions for the time to recurrence and survival, along with outcome risk predictions. Using integrated genomic profiles resulted in information gain for prediction of outcomes. Pathway analysis provided potential insights into functional changes affecting disease progression. The prognostic signatures, if prospectively validated, may be useful for interpreting therapeutic outcomes for clinical trials that aim to improve the therapy for SeOvCa patients

DOGS: Reaction-Driven de novo Design of Bioactive Compounds

We present a computational method for the reaction-based de novo design of drug-like molecules. The software DOGS (Design of Genuine Structures) features a ligand-based strategy for automated ‘in silico’ assembly of potentially novel bioactive compounds. The quality of the designed compounds is assessed by a graph kernel method measuring their similarity to known bioactive reference ligands in terms of structural and pharmacophoric features. We implemented a deterministic compound construction procedure that explicitly considers compound synthesizability, based on a compilation of 25'144 readily available synthetic building blocks and 58 established reaction principles. This enables the software to suggest a synthesis route for each designed compound. Two prospective case studies are presented together with details on the algorithm and its implementation. De novo designed ligand candidates for the human histamine H4 receptor and γ-secretase were synthesized as suggested by the software. The computational approach proved to be suitable for scaffold-hopping from known ligands to novel chemotypes, and for generating bioactive molecules with drug-like properties

Transcriptome Analysis of the Hippocampal CA1 Pyramidal Cell Region after Kainic Acid-Induced Status Epilepticus in Juvenile Rats

Molecular mechanisms involved in epileptogenesis in the developing brain remain poorly understood. The gene array approach could reveal some of the factors involved by allowing the identification of a broad scale of genes altered by seizures. In this study we used microarray analysis to reveal the gene expression profile of the laser microdissected hippocampal CA1 subregion one week after kainic acid (KA)-induced status epilepticus (SE) in 21-day-old rats, which are developmentally roughly comparable to juvenile children. The gene expression analysis with the Chipster software generated a total of 1592 differently expressed genes in the CA1 subregion of KA-treated rats compared to control rats. The KEGG database revealed that the identified genes were involved in pathways such as oxidative phosporylation (26 genes changed), and long-term potentiation (LTP; 18 genes changed). Also genes involved in Ca2+ homeostasis, gliosis, inflammation, and GABAergic transmission were altered. To validate the microarray results we further examined the protein expression for a subset of selected genes, glial fibrillary protein (GFAP), apolipoprotein E (apo E), cannabinoid type 1 receptor (CB1), Purkinje cell protein 4 (PEP-19), and interleukin 8 receptor (CXCR1), with immunohistochemistry, which confirmed the transcriptome results. Our results showed that SE resulted in no obvious CA1 neuronal loss, and alterations in the expression pattern of several genes during the early epileptogenic phase were comparable to previous gene expression studies of the adult hippocampus of both experimental epileptic animals and patients with temporal lobe epilepsy (TLE). However, some changes seem to occur after SE specifically in the juvenile rat hippocampus. Insight of the SE-induced alterations in gene expression and their related pathways could give us hints for the development of new target-specific antiepileptic drugs that interfere with the progression of the disease in the juvenile age group

Cost-effectiveness of novel vaccines for tuberculosis control: a decision analysis study

<p>Abstract</p> <p>Background</p> <p>The development of a successful new tuberculosis (TB) vaccine would circumvent many limitations of current diagnostic and treatment practices. However, vaccine development is complex and costly. We aimed to assess the potential cost effectiveness of novel vaccines for TB control in a sub-Saharan African country - Zambia - relative to the existing strategy of directly observed treatment, short course (DOTS) and current level of bacille Calmette-Guérin (BCG) vaccination coverage.</p> <p>Methods</p> <p>We conducted a decision analysis model-based simulation from the societal perspective, with a 3% discount rate and all costs expressed in 2007 US dollars. Health outcomes and costs were projected over a 30-year period, for persons born in Zambia (population 11,478,000 in 2005) in year 1. Initial development costs for single vaccination and prime-boost strategies were prorated to the Zambian share (0.398%) of global BCG vaccine coverage for newborns. Main outcome measures were TB-related morbidity, mortality, and costs over a range of potential scenarios for vaccine efficacy.</p> <p>Results</p> <p>Relative to the status quo strategy, a BCG replacement vaccine administered at birth, with 70% efficacy in preventing rapid progression to TB disease after initial infection, is estimated to avert 932 TB cases and 422 TB-related deaths (prevention of 199 cases/100,000 vaccinated, and 90 deaths/100,000 vaccinated). This would result in estimated net savings of $3.6 million over 30 years for 468,073 Zambians born in year 1 of the simulation. The addition of a booster at age 10 results in estimated savings of$5.6 million compared to the status quo, averting 1,863 TB cases and 1,011 TB-related deaths (prevention of 398 cases/100,000 vaccinated, and of 216 deaths/100,000 vaccinated). With vaccination at birth alone, net savings would be realized within 1 year, whereas the prime-boost strategy would require an additional 5 years to realize savings, reflecting a greater initial development cost.</p> <p>Conclusions</p> <p>Investment in an improved TB vaccine is predicted to result in considerable cost savings, as well as a reduction in TB morbidity and TB-related mortality, when added to existing control strategies. For a vaccine with waning efficacy, a prime-boost strategy is more cost-effective in the long term.</p

Self-organization of developing embryo using scale-invariant approach

<p>Abstract</p> <p>Background</p> <p>Self-organization is a fundamental feature of living organisms at all hierarchical levels from molecule to organ. It has also been documented in developing embryos.</p> <p>Methods</p> <p>In this study, a scale-invariant power law (SIPL) method has been used to study self-organization in developing embryos. The SIPL coefficient was calculated using a centro-axial skew symmetrical matrix (CSSM) generated by entering the components of the Cartesian coordinates; for each component, one CSSM was generated. A basic square matrix (BSM) was constructed and the determinant was calculated in order to estimate the SIPL coefficient. This was applied to developing <it>C. elegans </it>during early stages of embryogenesis. The power law property of the method was evaluated using the straight line and Koch curve and the results were consistent with fractal dimensions (fd). Diffusion-limited aggregation (DLA) was used to validate the SIPL method.</p> <p>Results and conclusion</p> <p>The fractal dimensions of both the straight line and Koch curve showed consistency with the SIPL coefficients, which indicated the power law behavior of the SIPL method. The results showed that the ABp sublineage had a higher SIPL coefficient than EMS, indicating that ABp is more organized than EMS. The fd determined using DLA was higher in ABp than in EMS and its value was consistent with type 1 cluster formation, while that in EMS was consistent with type 2.</p

In quest of a systematic framework for unifying and defining nanoscience

This article proposes a systematic framework for unifying and defining nanoscience based on historic first principles and step logic that led to a “central paradigm” (i.e., unifying framework) for traditional elemental/small-molecule chemistry. As such, a Nanomaterials classification roadmap is proposed, which divides all nanomatter into Category I: discrete, well-defined and Category II: statistical, undefined nanoparticles. We consider only Category I, well-defined nanoparticles which are >90% monodisperse as a function of Critical Nanoscale Design Parameters (CNDPs) defined according to: (a) size, (b) shape, (c) surface chemistry, (d) flexibility, and (e) elemental composition. Classified as either hard (H) (i.e., inorganic-based) or soft (S) (i.e., organic-based) categories, these nanoparticles were found to manifest pervasive atom mimicry features that included: (1) a dominance of zero-dimensional (0D) core–shell nanoarchitectures, (2) the ability to self-assemble or chemically bond as discrete, quantized nanounits, and (3) exhibited well-defined nanoscale valencies and stoichiometries reminiscent of atom-based elements. These discrete nanoparticle categories are referred to as hard or soft particle nanoelements. Many examples describing chemical bonding/assembly of these nanoelements have been reported in the literature. We refer to these hard:hard (H-n:H-n), soft:soft (S-n:S-n), or hard:soft (H-n:S-n) nanoelement combinations as nanocompounds. Due to their quantized features, many nanoelement and nanocompound categories are reported to exhibit well-defined nanoperiodic property patterns. These periodic property patterns are dependent on their quantized nanofeatures (CNDPs) and dramatically influence intrinsic physicochemical properties (i.e., melting points, reactivity/self-assembly, sterics, and nanoencapsulation), as well as important functional/performance properties (i.e., magnetic, photonic, electronic, and toxicologic properties). We propose this perspective as a modest first step toward more clearly defining synthetic nanochemistry as well as providing a systematic framework for unifying nanoscience. With further progress, one should anticipate the evolution of future nanoperiodic table(s) suitable for predicting important risk/benefit boundaries in the field of nanoscience