Orientation Dependence of the Ionization of CO and NO in an Intense Femtosecond Two-Color Laser Field

Two-color (800- and 400-nm) short (45-fs) linearly polarized pulses are used to ionize and dissociate CO and NO. The emission of Cq+, Nq+, and O⁺ fragments indicates that the higher ionization rate occurs when the peak electric field points from C to O in CO and from N to O in NO. This preferred direction is in agreement with that predicted by Stark-corrected strong-field-approximation calculations

Specific xylan activity revealed for AA9 Lytic Polysaccharide Monooxygenases of the thermophilic fungus Malbranchea cinnamomea by functional characterization

The thermophilic biomass-degrader\ua0Malbranchea cinnamomea\ua0exhibits poor growth on cellulose but excellent growth on hemicelluloses as the sole carbon source. This is surprising considering that its genome encodes eight lytic polysaccharide monooxygenases (LPMOs) from auxiliary activity family 9 (AA9), enzymes known for their high potential in accelerating cellulose depolymerization. We characterized four of the eight (M. cinnamomea\ua0AA9s)\ua0McAA9s, namely,\ua0McAA9A,\ua0McAA9B,\ua0McAA9F, and\ua0McAA9H, to gain a deeper understanding about their roles in the fungus. The characterized\ua0McAA9s were active on hemicelluloses, including xylan, glucomannan, and xyloglucan, and furthermore, in accordance with transcriptomics data, differed in substrate specificity. Of the\ua0McAA9s,\ua0McAA9H is unique, as it preferentially cleaves residual xylan in phosphoric acid-swollen cellulose (PASC). Moreover, when exposed to cellulose-xylan blends,\ua0McAA9H shows a preference for xylan and for releasing (oxidized) xylooligosaccharides. The cellulose dependence of the xylan activity suggests that a flat conformation, with rigidity similar to that of cellulose microfibrils, is a prerequisite for productive interaction between xylan and the catalytic surface of the LPMO.\ua0McAA9H showed a similar trend on xyloglucan, underpinning the suggestion that LPMO activity on hemicelluloses strongly depends on the polymers’ physicochemical context and conformation. Our results support the notion that LPMO multiplicity in fungal genomes relates to the large variety of copolymeric polysaccharide arrangements occurring in the plant cell wall

Exploring the feasibility of introducing triple artemisinin-based combination therapy in the malaria treatment policy in Vietnam

BACKGROUND: This study investigates the processes regarding changing malaria treatment policies in Vietnam. Moreover, it explores the feasibility of introducing triple artemisinin-based combination therapy (TACT) in Vietnam to support the national malaria control and elimination plan. METHODS: Data were collected via 12 in-depth interviews with key stakeholders, combined with a review of policy documents. RESULTS: TACT is considered as a useful backup strategy in case future treatment failures with current artemisinin-based combination therapy (ACT) would occur. Moreover, TACT is also considered as a promising strategy to prevent the re-establishment of malaria. However, regulatory procedures and implementation timelines for TACT were expected to be lengthy. Therefore, strategies to engage national decision-makers, regulators, and suppliers should be initiated soon, stipulating the benefits of TACT deployment. In Vietnam, a procedure to apply for an import permit without registration that has previously been applied to the introduction of artesunate-pyronaridine was proposed to accelerate the introduction of TACT. Global-level support through the World Health Organization recommendations and prequalification were considered critical for supporting the introduction of TACT in Vietnam. CONCLUSIONS: Appropriate approach strategies and early stakeholder engagement will be needed to accelerate the introduction of TACT in Vietnam

Multiparameter analysis of naevi and primary melanomas identifies a subset of naevi with elevated markers of transformation

Here we have carried out a multiparameter analysis using a panel of 28 immunohistochemical markers to identify markers of transformation from benign and dysplastic naevus to primary melanoma in three separate cohorts totalling 279 lesions. We have identified a set of eight markers that distinguish naevi from melanoma. None of markers or parameters assessed differentiated benign from dysplastic naevi. Indeed, the naevi clustered tightly in terms of their immunostaining patterns whereas primary melanomas showed more diverse staining patterns. A small subset of histopathologically benign lesions had elevated levels of multiple markers associated with melanoma, suggesting that these represent naevi with an increased potential for transformation to melanoma

On the Impact of Dataset Size: A Twitter Classification Case Study

The recent advent and evolution of deep learning models and pre-trained embedding techniques have created a breakthrough in supervised learning. Typically, we expect that adding more labeled data improves the predictive performance of supervised models. On the other hand, collecting more labeled data is not an easy task due to several difficulties, such as manual labor costs, data privacy, and computational constraint. Hence, a comprehensive study on the relation between training set size and the classification performance of different methods could be essentially useful in the selection of a learning model for a specific task. However, the literature lacks such a thorough and systematic study. In this paper, we concentrate on this relationship in the context of short, noisy texts from Twitter. We design a systematic mechanism to comprehensively observe the performance improvement of supervised learning models with the increase of data sizes on three well-known Twitter tasks: sentiment analysis, informativeness detection, and information relevance. Besides, we study how significantly better the recent deep learning models are compared to traditional machine learning approaches in the case of various data sizes. Our extensive experiments show (a) recent pre-trained models have overcome big data requirements, (b) a good choice of text representation has more impact than adding more data, and (c) adding more data is not always beneficial in supervised learning

Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems

Background: Variable selection on high throughput biological data, such as gene expression or single nucleotide polymorphisms (SNPs), becomes inevitable to select relevant information and, therefore, to better characterize diseases or assess genetic structure. There are different ways to perform variable selection in large data sets. Statistical tests are commonly used to identify differentially expressed features for explanatory purposes, whereas Machine Learning wrapper approaches can be used for predictive purposes. In the case of multiple highly correlated variables, another option is to use multivariate exploratory approaches to give more insight into cell biology, biological pathways or complex traits.Results: A simple extension of a sparse PLS exploratory approach is proposed to perform variable selection in a multiclass classification framework.Conclusions: sPLS-DA has a classification performance similar to other wrapper or sparse discriminant analysis approaches on public microarray and SNP data sets. More importantly, sPLS-DA is clearly competitive in terms of computational efficiency and superior in terms of interpretability of the results via valuable graphical outputs. sPLS-DA is available in the R package mixOmics, which is dedicated to the analysis of large biological data sets

Identification of the population density of a species model with nonlocal diffusion and nonlinear reaction

The identification of the population density of a logistic equation backwards in time associated with nonlocal diffusion and nonlinear reaction, motivated by biology and ecology fields, is investigated. The diffusion depends on an integral average of the population density whilst the reaction term is a global or local Lipschitz function of the population density. After discussing the ill-posedness of the problem, we apply the quasi-reversibility method to construct stable approximation problems. It is shown that the regularized solutions stemming from such method not only depend continuously on the final data, but also strongly converge to the exact solution in L²-norm. New error estimates together with stability results are obtained. Furthermore, numerical examples are provided to illustrate the theoretical results

Host Transcription Profile in Nasal Epithelium and Whole Blood of Hospitalized Children Under 2 Years of Age With Respiratory Syncytial Virus Infection.

BACKGROUND: Most insights into the cascade of immune events after acute respiratory syncytial virus (RSV) infection have been obtained from animal experiments or in vitro models. METHODS: In this study, we investigated host gene expression profiles in nasopharyngeal (NP) swabs and whole blood samples during natural RSV and rhinovirus (hRV) infection (acute versus early recovery phase) in 83 hospitalized patients <2 years old with lower respiratory tract infections. RESULTS: Respiratory syncytial virus infection induced strong and persistent innate immune responses including interferon signaling and pathways related to chemokine/cytokine signaling in both compartments. Interferon-α/β, NOTCH1 signaling pathways and potential biomarkers HIST1H4E, IL7R, ISG15 in NP samples, or BCL6, HIST2H2AC, CCNA1 in blood are leading pathways and hub genes that were associated with both RSV load and severity. The observed RSV-induced gene expression patterns did not differ significantly in NP swab and blood specimens. In contrast, hRV infection did not as strongly induce expression of innate immunity pathways, and significant differences were observed between NP swab and blood specimens. CONCLUSIONS: We conclude that RSV induced strong and persistent innate immune responses and that RSV severity may be related to development of T follicular helper cells and antiviral inflammatory sequelae derived from high activation of BCL6

Analysis of a simulated microarray dataset: Comparison of methods for data normalisation and detection of differential expression (Open Access publication)

Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed. Methods of comparing the normalised data are also abundant, and no clear consensus has yet been reached. The purpose of this paper was to compare those methods used by the EADGENE network on a very noisy simulated data set. With the a priori knowledge of which genes are differentially expressed, it is possible to compare the success of each approach quantitatively. Use of an intensity-dependent normalisation procedure was common, as was correction for multiple testing. Most variety in performance resulted from differing approaches to data quality and the use of different statistical tests. Very few of the methods used any kind of background correction. A number of approaches achieved a success rate of 95% or above, with relatively small numbers of false positives and negatives. Applying stringent spot selection criteria and elimination of data did not improve the false positive rate and greatly increased the false negative rate. However, most approaches performed well, and it is encouraging that widely available techniques can achieve such good results on a very noisy data set

Strategies for deploying triple artemisinin-based combination therapy in the Greater Mekong Subregion

Background This is a qualitative study to identify implementation challenges for deploying triple artemisinin-based combination therapy (TACT) in the Greater Mekong Subregion (GMS) of Southeast Asia and to explore strategies to overcome these challenges. Methods In-depth interviews were conducted in three countries that have repeatedly been confronted with ACT failures: Cambodia, Vietnam, and Lao PDR. Thirty-nine key stakeholders in the healthcare systems in these countries were interviewed. One participatory workshop was conducted in Cambodia, where scenarios for potential TACT deployment were discussed. Results The results section is organized around four strategic themes that emerged from the data: policy support, data and evidence, logistics and operation, and downstream engagement. The study revealed that countries in the GMS currently rely on ACT to eliminate Plasmodium falciparum malaria by 2025. TACT is, however, considered to be a useful backup strategy in case of future treatment failures and to prevent the re-establishment of malaria. The study showed that a major challenge ahead is to engage decision makers and healthcare providers into deploying TACT, given the low case incidence of falciparum malaria in the GMS. Interview respondents were also skeptical whether healthcare providers would be willing to engage in new therapies for a disease they hardly encounter anymore. Hence, elaborate information dissemination strategies were considered appropriate and these strategies should especially target village malaria workers. Respondents proposed several regulatory and programmatic strategies to anticipate the formation of TACT markets in the GMS. These strategies include early dossier submission to streamline regulatory procedures, early stakeholder engagement strategies to shorten implementation timelines, and inclusion of TACT as second-line therapy to accelerate their introduction in case they are urgently needed. Conclusions This paper presents a qualitative study to identify implementation challenges for deploying TACT in the GMS and to explore strategies to overcome these challenges. The findings could benefit researchers and decision makers in strategizing towards potential future deployment of TACT in the GMS to combat artemisinin and partner drug resistance