Parallel synthesis and high throughput dissolution testing of biodegradable polyanhydride copolymers

We have demonstrated that polycondensation reactions can be carried out in a combinatorial fashion and that the polymer library can be screened at high throughput using a rapid prototyping technique to fabricate multiwell substrates. A linearly varying compositional library of 100 different biodegradable polyanhydride random copolymers that are promising carriers for controlled drug delivery was designed, fabricated, and characterized by IR microscopy within a few hours. The polyanhydride copolymer library was based on 1,6-bis(p-carboxyphenoxy)hexane (CPH) and sebacic anhydride (SA) and was characterized with infrared microspectroscopy to determine the composition within each well. Since degradation and release rates depend on copolymer composition, we also developed new high-throughput methods to investigate drug release from this library of copolymers by designing specific wells for each task. A subset of this library was chosen, and a substrate was designed and fabricated to enable the synthesis and monitoring of dye dissolution from a range of polyanhydride copolymers in a parallel fashion using a CCD camera. Multisample substrates were fabricated with a novel rapid prototyping method that consists of an organic solvent-resistant array of 10 x 10 microwells of 2-μL volume each. The libraries were deposited with a custom-built liquid dispensing system consisting of a series of computer-controlled volume-dispensing pumps and XYZ motion stages. The parallel dye dissolution study displayed a decreasing rate of release with increasing CPH content. This result agrees with previously published data for dye release from poly(CPH-co-SA) copolymers. The methodology described in this work is amenable to numerous applications in the arenas of high-throughput polymer synthesis and characterization

Non-replication of an association of CTNNBL1 polymorphisms and obesity in a population of Central European ancestry

<p>Abstract</p> <p>Background</p> <p>A recent genome-wide association (GWA) study of U.S. Caucasians suggested that eight single nucleotide polymorphisms (SNPs) in <it>CTNNBL1 </it>are associated with obesity and increased fat mass. We analysed the respective SNPs in data from our previously published GWA for early onset obesity (case-control design), in GWA data from a population-based cohort of adults, and in an independent family-based obesity study. We investigated whether variants in <it>CTNNBL1 </it>(including rs6013029) and in three other genes (<it>SH3PXD2B</it>, <it>SLIT3 </it>and <it>FLJ42133</it>,) were associated with obesity.</p> <p>Methods</p> <p>The GWA studies were carried out using Affymetrix^®SNP Chips with approximately 500,000 markers each. In the families, SNP rs6013029 was genotyped using the TaqMan^®allelic discrimination assay. The German case-control GWA included 487 extremely obese children and adolescents and 442 healthy lean individuals. The adult GWA included 1,644 individuals from a German population-based study (KORA). The 775 independent German families consisted of extremely obese children and adolescents and their parents.</p> <p>Results</p> <p>We found no evidence for an association of the reported variants in <it>CTNNBL1 </it>with early onset obesity or increased BMI. Further, in our family-based study we found no evidence for over-transmission of the rs6013029 risk-allele T to obese children. Additionally, we found no evidence for an association of <it>SH3PXD2B</it>, <it>SLIT3 and FLJ42133 </it>variants in our two GWA samples.</p> <p>Conclusion</p> <p>We detected no confirmation of the recent association of variants in <it>CTNNBL1 </it>with obesity in a population of Central European ancestry.</p

Computational Models of Classical Conditioning guest editors’ introduction

In the present special issue, the performance of current computational models of classical conditioning was evaluated under three requirements: (1) Models were to be tested against a list of previously agreed-upon phenomena; (2) the parameters were fixed across simulations; and (3) the simulations used to test the models had to be made available. These requirements resulted in three major products: (a) a list of fundamental classical-conditioning results for which there is a consensus about their reliability; (b) the necessary information to evaluate each of the models on the basis of its ordinal successes in accounting for the experimental data; and (c) a repository of computational models ready to generate simulations. We believe that the contents of this issue represent the 2012 state of the art in computational modeling of classical conditioning and provide a way to find promising avenues for future model development

An intercomparison study of four different techniques for measuring the chemical composition of nanoparticles

Currently, the complete chemical characterization of nanoparticles (< 100 nm) represents an analytical challenge, since these particles are abundant in number but have negligible mass. Several methods for particle-phase characterization have been recently developed to better detect and infer more accurately the sources and fates of sub-100 nm particles, but a detailed comparison of different approaches is missing. Here we report on the chemical composition of secondary organic aerosol (SOA) nanoparticles from experimental studies of α-pinene ozonolysis at −50, −30, and −10 ∘C and intercompare the results measured by different techniques. The experiments were performed at the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). The chemical composition was measured simultaneously by four different techniques: (1) thermal desorption–differential mobility analyzer (TD–DMA) coupled to a NO$^-_3$ chemical ionization–atmospheric-pressure-interface–time-of-flight (CI–APi–TOF) mass spectrometer, (2) filter inlet for gases and aerosols (FIGAERO) coupled to an I$^−$ high-resolution time-of-flight chemical ionization mass spectrometer (HRToF-CIMS), (3) extractive electrospray Na$^+$ ionization time-of-flight mass spectrometer (EESI-TOF), and (4) offline analysis of filters (FILTER) using ultra-high-performance liquid chromatography (UHPLC) and heated electrospray ionization (HESI) coupled to an Orbitrap high-resolution mass spectrometer (HRMS). Intercomparison was performed by contrasting the observed chemical composition as a function of oxidation state and carbon number, by estimating the volatility and comparing the fraction of volatility classes, and by comparing the thermal desorption behavior (for the thermal desorption techniques: TD–DMA and FIGAERO) and performing positive matrix factorization (PMF) analysis for the thermograms. We found that the methods generally agree on the most important compounds that are found in the nanoparticles. However, they do see different parts of the organic spectrum. We suggest potential explanations for these differences: thermal decomposition, aging, sampling artifacts, etc. We applied PMF analysis and found insights of thermal decomposition in the TD–DMA and the FIGAERO

Allosteric Regulation of Fibronectin/α5β1 Interaction by Fibronectin-Binding MSCRAMMs

Citation: Liang, X. W., Garcia, B. L., Visai, L., Prabhakaran, S., Meenan, N. A. G., Potts, J. R., . . . Hook, M. (2016). Allosteric Regulation of Fibronectin/alpha(5)beta(1) Interaction by Fibronectin-Binding MSCRAMMs. Plos One, 11(7), 17. doi:10.1371/journal.pone.0159118Adherence ofmicrobes to host tissues is a hallmark of infectious disease and is often mediated by a class of adhesins termed MSCRAMMs (Microbial Surface Components Recognizing Adhesive Matrix Molecules). Numerous pathogens express MSCRAMMs that specifically bind the heterodimeric human glycoprotein fibronectin (Fn). In addition to roles in adhesion, Fn-binding MSCRAMMs exploit physiological Fn functions. For example, several pathogens can invade host cells by a mechanism whereby MSCRAMM-bound Fn bridges interaction with alpha(5)beta(1) integrin. Here, we investigate two Fn-binding MSCRAMMs, FnBPA (Staphylococcus aureus) and BBK32 (Borrelia burgdorferi) to probe structure-activity relationships of MSCRAMM-induced Fn/alpha(5)beta(1) integrin activation. Circular dichroism, fluorescence resonance energy transfer, and dynamic light scattering techniques uncover a conformational rearrangement of Fn involving domains distant from the MSCRAMM binding site. Surface plasmon resonance experiments demonstrate a significant enhancement of Fn/alpha(5)beta(1) integrin affinity in the presence of FnBPA or BBK32. Detailed kinetic analysis of these interactions reveal that this change in affinity can be attributed solely to an increase in the initial Fn/alpha(5)beta(1) on-rate and that this rate-enhancement is dependent on high-affinity Fn-binding by MSCRAMMs. These data implicate MSCRAMM-induced perturbation of specific intramolecular contacts within the Fn heterodimer resulting in activation by exposing previously cryptic alpha(5)beta(1) interaction motifs. By correlating structural changes in Fn to a direct measurement of increased Fn/alpha(5)beta(1) affinity, this work significantly advances our understanding of the structural basis for the modulation of integrin function by Fn-binding MSCRAMMs

Synergistic HNO3_{3}–H2_{2}SO4_{4}–NH3_{3} upper tropospheric particle formation

New particle formation in the upper free troposphere is a major global source of cloud condensation nuclei (CCN)$^{1,2,3,4}$. However, the precursor vapours that drive the process are not well understood. With experiments performed under upper tropospheric conditions in the CERN CLOUD chamber, we show that nitric acid, sulfuric acid and ammonia form particles synergistically, at rates that are orders of magnitude faster than those from any two of the three components. The importance of this mechanism depends on the availability of ammonia, which was previously thought to be efficiently scavenged by cloud droplets during convection. However, surprisingly high concentrations of ammonia and ammonium nitrate have recently been observed in the upper troposphere over the Asian monsoon region5,6. Once particles have formed, co-condensation of ammonia and abundant nitric acid alone is sufficient to drive rapid growth to CCN sizes with only trace sulfate. Moreover, our measurements show that these CCN are also highly efficient ice nucleating particles—comparable to desert dust. Our model simulations confirm that ammonia is efficiently convected aloft during the Asian monsoon, driving rapid, multi-acid HNO$_{3}$–H$_{2}$SO$_{4}$–NH$_{3}$ nucleation in the upper troposphere and producing ice nucleating particles that spread across the mid-latitude Northern Hemisphere

A Rescorla-Wagner Drift-Diffusion Model of Conditioning and Timing

Computational models of classical conditioning have made significant contributions to the theoretic understanding of associative learning, yet they still struggle when the temporal aspects of conditioning are taken into account. Interval timing models have contributed a rich variety of time representations and provided accurate predictions for the timing of responses, but they usually have little to say about associative learning. In this article we present a unified model of conditioning and timing that is based on the influential Rescorla-Wagner conditioning model and the more recently developed Timing Drift-Diffusion model. We test the model by simulating 10 experimental phenomena and show that it can provide an adequate account for 8, and a partial account for the other 2. We argue that the model can account for more phenomena in the chosen set than these other similar in scope models: CSC-TD, MS-TD, Learning to Time and Modular Theory. A comparison and analysis of the mechanisms in these models is provided, with a focus on the types of time representation and associative learning rule used

Amyloid and tau pathology associations with personality traits, neuropsychiatric symptoms, and cognitive lifestyle in the preclinical phases of sporadic and autosomal dominant Alzheimer’s disease

Background Major prevention trials for Alzheimer’s disease (AD) are now focusing on multidomain lifestyle interventions. However, the exact combination of behavioral factors related to AD pathology remains unclear. In 2 cohorts of cognitively unimpaired individuals at risk of AD, we examined which combinations of personality traits, neuropsychiatric symptoms, and cognitive lifestyle (years of education or lifetime cognitive activity) related to the pathological hallmarks of AD, amyloid-β, and tau deposits. Methods A total of 115 older adults with a parental or multiple-sibling family history of sporadic AD (PREVENT-AD [PRe-symptomatic EValuation of Experimental or Novel Treatments for AD] cohort) underwent amyloid and tau positron emission tomography and answered several questionnaires related to behavioral attributes. Separately, we studied 117 mutation carriers from the DIAN (Dominant Inherited Alzheimer Network) study group cohort with amyloid positron emission tomography and behavioral data. Using partial least squares analysis, we identified latent variables relating amyloid or tau pathology with combinations of personality traits, neuropsychiatric symptoms, and cognitive lifestyle. Results In PREVENT-AD, lower neuroticism, neuropsychiatric burden, and higher education were associated with less amyloid deposition (p = .014). Lower neuroticism and neuropsychiatric features, along with higher measures of openness and extraversion, were related to less tau deposition (p = .006). In DIAN, lower neuropsychiatric burden and higher education were also associated with less amyloid (p = .005). The combination of these factors accounted for up to 14% of AD pathology. Conclusions In the preclinical phase of both sporadic and autosomal dominant AD, multiple behavioral features were associated with AD pathology. These results may suggest potential pathways by which multidomain interventions might help delay AD onset or progression

The role of APOBEC3B in lung tumor evolution and targeted cancer therapy resistance

In this study, the impact of the apolipoprotein B mRNA-editing catalytic subunit-like (APOBEC) enzyme APOBEC3B (A3B) on epidermal growth factor receptor (EGFR)-driven lung cancer was assessed. A3B expression in EGFR mutant (EGFRmut) non-small-cell lung cancer (NSCLC) mouse models constrained tumorigenesis, while A3B expression in tumors treated with EGFR-targeted cancer therapy was associated with treatment resistance. Analyses of human NSCLC models treated with EGFR-targeted therapy showed upregulation of A3B and revealed therapy-induced activation of nuclear factor kappa B (NF-κB) as an inducer of A3B expression. Significantly reduced viability was observed with A3B deficiency, and A3B was required for the enrichment of APOBEC mutation signatures, in targeted therapy-treated human NSCLC preclinical models. Upregulation of A3B was confirmed in patients with NSCLC treated with EGFR-targeted therapy. This study uncovers the multifaceted roles of A3B in NSCLC and identifies A3B as a potential target for more durable responses to targeted cancer therapy.</p