Photocatalytic oxidation of methane over silver decorated zinc oxide nanocatalysts

The search for active catalysts that efficiently oxidize methane under ambient conditions remains a challenging task for both C1 utilization and atmospheric cleansing. Here, we show that when the particle size of zinc oxide is reduced down to the nanoscale, it exhibits high activity for methane oxidation under simulated sunlight illumination, and nano silver decoration further enhances the photo-activity via the surface plasmon resonance. The high quantum yield of 8% at wavelengths \u3c 400 nm and over 0.1% at wavelengths ¿ 470 nm achieved on the silver decorated zinc oxide nanostructures shows great promise for atmospheric methane oxidation. Moreover, the nano-particulate composites can efficiently photo-oxidize other small molecular hydrocarbons such as ethane, propane and ethylene, and in particular, can dehydrogenize methane to generate ethane, ethylene and so on. On the basis of the experimental results, a two-step photocatalytic reaction process is suggested to account for the methane photo-oxidation

Smokers' Likelihood to Engage With Information and Misinformation on Twitter About the Relative Harms of e-Cigarette Use:Results From a Randomized Controlled Trial

BACKGROUND: Information and misinformation on the internet about e-cigarette harms may increase smokers’ misperceptions of e-cigarettes. There is limited research on smokers’ engagement with information and misinformation about e-cigarettes on social media. OBJECTIVE: This study assessed smokers’ likelihood to engage with—defined as replying, retweeting, liking, and sharing—tweets that contain information and misinformation and uncertainty about the harms of e-cigarettes. METHODS: We conducted a web-based randomized controlled trial among 2400 UK and US adult smokers who did not vape in the past 30 days. Participants were randomly assigned to view four tweets in one of four conditions: (1) e-cigarettes are as harmful or more harmful than smoking, (2) e-cigarettes are completely harmless, (3) uncertainty about e-cigarette harms, or (4) control (physical activity). The outcome measure was participants’ likelihood of engaging with tweets, which comprised the sum of whether they would reply, retweet, like, and share each tweet. We fitted Poisson regression models to predict the likelihood of engagement with tweets among 974 Twitter users and 1287 non-Twitter social media users, adjusting for covariates and stratified by UK and US participants. RESULTS: Among Twitter users, participants were more likely to engage with tweets in condition 1 (e-cigarettes are as harmful or more harmful than smoking) than in condition 2 (e-cigarettes are completely harmless). Among other social media users, participants were more likely to likely to engage with tweets in condition 1 than in conditions 2 and 3 (e-cigarettes are completely harmless and uncertainty about e-cigarette harms). CONCLUSIONS: Tweets stating information and misinformation that e-cigarettes were as harmful or more harmful than smoking regular cigarettes may receive higher engagement than tweets indicating e-cigarettes were completely harmless. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number (ISRCTN) 16082420; https://doi.org/10.1186/ISRCTN1608242

Stress State Evaluation by an Improved Support Vector Machine

Effective methods of evaluation of the psychological pressure can detect and assess realtime stress states, warning people to pay necessary attention to their health. This study is focused on the stress assessment issue using an improved support vector machine (SVM) algorithm on the base of surface electromyographic signals. After the samples were clustered, the cluster results were given to the loss function of the SVM to screen training samples. With the imbalance amongst the training samples after screening, a weight was given to the loss function to reduce the prediction tendentiousness of the classifier and, therefore, to decrease the error of the training sample and make up for the influence of the unbalanced samples. This improved the algorithm, increased the classification accuracy from 73.79% to 81.38%, and reduced the running time from 1973.1 to 540.2 sec. Experimental results show that this algorithm can help to effectively avoid the influence of individual differences on a stress appraisal effect and to reduce the computational complexity during the training phase of the classifierЕфективні методи визначення ступеня психологічного тиску можуть забезпечувати виявлення та оцінку стресових станів у реальному часі, примушуючи людей приділяти необхідну увагу їх здоров’ю. Метою нашого дослідження було оцінити стан стресу з використанням покращеного методу опорних векторів (SVM), базуючись на відведенні поверхневих електроміограм. Після того, як зразки даних були кластеризовані, результати передавалися до функції розділення SVM для того, щоб представити тренувальні зразки. Після встановлення дисбалансу між тренувальними зразками після скринінга для функції розділення надавався параметр ваги для зменшення тенденційності прогнозування класифікатора і, таким чином, зменшення похибки тренувального зразка і впливу незбалансованих зразків. Це покращувало алгоритм, підвищувало точність класифікації від 73.79 до 81.38 % та зменшувало час обробки від 1973.1 до 540.2 с. Результати експериментів показали, що даний алгоритм може допомогти ефективно уникнути впливу індивідуальних відмінностей на оцінювання стресу та зменшити складність комп’ютерних розрахунків у перебігу тренувальної фази діяльності класифікатора

Targeting Ovarian Cancer and Endothelium with an Allosteric PTP4A3 Phosphatase Inhibitor

Overexpression of protein tyrosine phosphatase PTP4A oncoproteins is common in many human cancers and is associated with poor patient prognosis and survival. We observed elevated levels of PTP4A3 phosphatase in 79% of human ovarian tumor samples, with significant overexpression in tumor endothelium and pericytes. Furthermore, PTP4A phosphatases appear to regulate several key malignant processes, such as invasion, migration, and angiogenesis, suggesting a pivotal regulatory role in cancer and endothelial signaling pathways. While phosphatases are attractive therapeutic targets, they have been poorly investigated because of a lack of potent and selective chemical probes. In this study, we disclose that a potent, selective, reversible, and noncompetitive PTP4A inhibitor, JMS-053, markedly enhanced microvascular barrier function after exposure of endothelial cells to vascular endothelial growth factor or lipopolysaccharide. JMS-053 also blocked the concomitant increase in RhoA activation and loss of Rac1. In human ovarian cancer cells, JMS-053 impeded migration, disrupted spheroid growth, and decreased RhoA activity. Importantly, JMS-053 displayed anticancer activity in a murine xenograft model of drug resistant human ovarian cancer. These data demonstrate that PTP4A phosphatases can be targeted in both endothelial and ovarian cancer cells, and confirm that RhoA signaling cascades are regulated by the PTP4A family

A small-molecule inhibitor of the aberrant transcription factor CBFβ-SMMHC delays leukemia in mice

This is the author’s version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in Science on 2015 February 13; 347(6223): 779–784, DOI: 10.1126/science.aaa0314.Acute myeloid leukemia (AML) is the most common form of adult leukemia. The transcription factor fusion CBFβ-SMMHC (core binding factor β and the smooth-muscle myosin heavy chain), expressed in AML with the chromosome inversion inv(16)(p13q22), outcompetes wild-type CBFβ for binding to the transcription factor RUNX1, deregulates RUNX1 activity in hematopoiesis, and induces AML. Current inv(16) AML treatment with nonselective cytotoxic chemotherapy results in a good initial response but limited long-term survival. Here, we report the development of a protein-protein interaction inhibitor, AI-10-49, that selectively binds to CBFβ-SMMHC and disrupts its binding to RUNX1. AI-10-49 restores RUNX1 transcriptional activity, displays favorable pharmacokinetics, and delays leukemia progression in mice. Treatment of primary inv(16) AML patient blasts with AI-10-49 triggers selective cell death. These data suggest that direct inhibition of the oncogenic CBFβ-SMMHC fusion protein may be an effective therapeutic approach for inv(16) AML, and they provide support for transcription factor targeted therapy in other cancers

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder

Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders

Personality is influenced by genetic and environmental factors1 and associated with mental health. However, the underlying genetic determinants are largely unknown. We identified six genetic loci, including five novel loci2,3, significantly associated with personality traits in a meta-analysis of genome-wide association studies (N = 123,132–260,861). Of these genomewide significant loci, extraversion was associated with variants in WSCD2 and near PCDH15, and neuroticism with variants on chromosome 8p23.1 and in L3MBTL2. We performed a principal component analysis to extract major dimensions underlying genetic variations among five personality traits and six psychiatric disorders (N = 5,422–18,759). The first genetic dimension separated personality traits and psychiatric disorders, except that neuroticism and openness to experience were clustered with the disorders. High genetic correlations were found between extraversion and attention-deficit– hyperactivity disorder (ADHD) and between openness and schizophrenia and bipolar disorder. The second genetic dimension was closely aligned with extraversion–introversion and grouped neuroticism with internalizing psychopathology (e.g., depression or anxiety)

Somatostatin analogues for receptor targeted photodynamic therapy

Photodynamic therapy (PDT) is an established treatment modality, used mainly for anticancer therapy that relies on the interaction of photosensitizer, light and oxygen. For the treatment of pathologies in certain anatomical sites, improved targeting of the photosensitizer is necessary to prevent damage to healthy tissue. We report on a novel dual approach of targeted PDT (vascular and cellular targeting) utilizing the expression of neuropeptide somatostatin receptor (sst2) on tumor and neovascular-endothelial cells. We synthesized two conjugates containing the somatostatin analogue [Tyr3]-octreotate and Chlorin e6 (Ce6): Ce6-K3-[Tyr3]-octreotate (1) and Ce6-[Tyr3]-octreotate-K3-[Tyr3]-octreotate (2). Investigation of the uptake and photodynamic activity of conjugates in-vitro in human erythroleukemic K562 cells showed that conjugation of [Tyr3]-octreotate with Ce6 in conjugate 1 enhances uptake (by a factor 2) in cells over-expressing sst2 compared to wild-type cells. Co-treatment with excess free Octreotide abrogated the phototoxicity of conjugate 1 indicative of a specific sst2-mediated effect. In contrast conjugate 2 showed no receptor-mediated effect due to its high hydrophobicity. When compared with un-conjugated Ce6, the PDT activity of conjugate 1 was lower. However, it showed higher photostability which may compensate for its lower phototoxicity. Intra-vital fluorescence pharmacokinetic studies of conjugate 1 in rat skin-fold observation chambers transplanted with sst2+ AR42J acinar pancreas tumors showed significantly different uptake profiles compared to free Ce6. Co-treatment with free Octreotide significantly reduced conjugate uptake in tumor tissue (by a factor 4) as well as in the chamber neo-vasculature. These results show that conjugate 1 might have potential as an in-vivo sst2 targeting photosensitizer conjugate

High-throughput screening for industrial enzyme production hosts by droplet microfluidics

A high-throughput method for single cell screening by microfluidic droplet sorting is applied to a whole-genome mutated yeast cell library yielding improved production hosts of secreted industrial enzymes. The sorting method is validated by enriching a yeast strain 14 times based on its a-amylase production, close to the theoretical maximum enrichment. Furthermore, a 105 member yeast cell library is screened yielding a clone with a more than 2-fold increase in a-amylase production. The increase in enzyme production results from an improvement of the cellular functions of the production host in contrast to previous droplet-based directed evolution that has focused on improving enzyme protein structure. In the workflow presented, enzyme producing single cells are encapsulated in 20 pL droplets with a fluorogenic reporter substrate. The coupling of a desired phenotype (secreted enzyme concentration) with the genotype (contained in the cell) inside a droplet enables selection of single cells with improved enzyme production capacity by droplet sorting. The platform has a throughput over 300 times higher than that of the current industry standard, an automated microtiter plate screening system. At the same time, reagent consumption for a screening experiment is decreased a million fold, greatly reducing the costs of evolutionary engineering of production strains

ESPRIT: estimating species richness using large collections of 16S rRNA pyrosequences

Recent metagenomics studies of environmental samples suggested that microbial communities are much more diverse than previously reported, and deep sequencing will significantly increase the estimate of total species diversity. Massively parallel pyrosequencing technology enables ultra-deep sequencing of complex microbial populations rapidly and inexpensively. However, computational methods for analyzing large collections of 16S ribosomal sequences are limited. We proposed a new algorithm, referred to as ESPRIT, which addresses several computational issues with prior methods. We developed two versions of ESPRIT, one for personal computers (PCs) and one for computer clusters (CCs). The PC version is used for small- and medium-scale data sets and can process several tens of thousands of sequences within a few minutes, while the CC version is for large-scale problems and is able to analyze several hundreds of thousands of reads within one day. Large-scale experiments are presented that clearly demonstrate the effectiveness of the newly proposed algorithm. The source code and user guide are freely available at http://www.biotech.ufl.edu/people/sun/esprit.html