Dataset of Targeted Metabolite Analysis for Five Taxanes of Hellenic Taxus baccata L. Populations

Novel primary sources of one of the world’s leading anticancer agent, paclitaxel, as well as of other antineoplastic taxanes such as 10-deacetylbaccatin-III, are needed to meet an increasing demand. Among the Taxus species the promise of Taxus baccata L. (European or English yew) has been documented. In this study, the metabolite analysis of two marginal T. baccata populations in Greece (Mt. Cholomon and Mt. Olympus), located at the southeastern edge of the species natural distribution, are being explored. A targeted liquid chromatography – mass spectrometry (LC-MS/MS) analysis was used to determine the content of 10-deacetylbaccatin III, baccatin III, 10-deacetyltaxol, paclitaxel and cephalomannine in the needles of each of the populations from three sampling periods (spring, summer and winter). This is the first survey to generate a taxane targeted metabolite data set, since it derives from Hellenic natural populations that have not been explored before. Furthermore, it has used an extensive sample design in order to evaluate chemodiversity at the population level. The analysis revealed significant levels of chemodiversity within and among the investigated populations and significant seasonal variation that could be exploited for the selection of superior germplasm native to Greece, for yew plantations and further exploitation which is necessary for the production of important taxanes.

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Potential value of the current mental health monitoring of children in state care in England

BJPsych Open ◽

10.1192/bjo.2018.70 ◽

2018 ◽

Vol 4 (6) ◽

pp. 486-491 ◽

Cited By ~ 3

Author(s):

Christine Cocker ◽

Helen Minnis ◽

Helen Sweeting

Keyword(s):

Mental Health ◽

Missing Data ◽

Mental Health Problems ◽

Population Level ◽

Cross Sectional ◽

Data Set ◽

Looked After Children ◽

Education Data ◽

Sample Attrition ◽

Aggregate Population

BackgroundRoutine screening to identify mental health problems in English looked-after children has been conducted since 2009 using the Strengths and Difficulties Questionnaire (SDQ).AimsTo investigate the degree to which data collection achieves screening aims (identifying scale of problem, having an impact on mental health) and the potential analytic value of the data set.MethodDepartment for Education data (2009–2017) were used to examine: aggregate, population-level trends in SDQ scores in 4/5- to 16/17-year-olds; representativeness of the SDQ sample; attrition in this sample.ResultsMean SDQ scores (around 50% ‘abnormal’ or ‘borderline’) were stable over 9 years. Levels of missing data were high (25–30%), as was attrition (28% retained for 4 years). Cross-sectional SDQ samples were not representative and longitudinal samples were biased.ConclusionsMental health screening appears justified and the data set has research potential, but the English screening programme falls short because of missing data and inadequate referral routes for those with difficulties.Declaration of interestNone.

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Genetic variation in the dietary sucrose modulation of enzyme activities in Drosophila melanogaster

Genetics Research ◽

10.1017/s0016672300026094 ◽

1984 ◽

Vol 43 (3) ◽

pp. 307-321 ◽

Cited By ~ 27

Author(s):

Billy W. Geer ◽

Cathy C. Laurie-Ahlberg

Keyword(s):

Drosophila Melanogaster ◽

Genetic Variation ◽

Enzyme Activities ◽

Glycogen Synthesis ◽

Krebs Cycle ◽

Natural Populations ◽

Substitution Lines ◽

Chromosome Substitution Lines ◽

High Sucrose Diet ◽

Selection Of

SUMMARYGenetic variation in the modulating effect of dietary sucrose was assessed in Drosophila melanogaster by examining 27 chromosome substitution lines coisogenic for the X and second chromosomes and possessing different third isogenic chromosomes derived from natural populations. An increase in the concentration of sucrose from 0·1% to 5% in modified Sang's medium C significantly altered the activities of 11 of 15 enzyme activities in third instar larvae, indicating that dietary sucrose modulates many, but not all, of the enzymes of D. melanogaster. A high sucrose diet promoted high activities of enzymes associated with lipid and glycogen synthesis and low activities of enzymes of the glycolytic and Krebs cycle pathways, reflecting the physiological requirements of the animal. Analyses of variance revealed significant genetic variation in the degrees to which sucrose modulated several enzyme activities. Analysis of correlations revealed some relationships between enzymes in the genetic effects on the modulation process. These observations suggest that adaptive evolutionary change may depend in part on the selection of enzyme activity modifiers that are distributed throughout the genome.

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Data Set for the Reporting of Malignant Odontogenic Tumors: Explanations and Recommendations of the Guidelines From the International Collaboration on Cancer Reporting

Archives of Pathology & Laboratory Medicine ◽

10.5858/arpa.2018-0417-sa ◽

2018 ◽

Vol 143 (5) ◽

pp. 587-592 ◽

Cited By ~ 1

Author(s):

Pieter J. Slootweg ◽

Edward W. Odell ◽

Daniel Baumhoer ◽

Roman Carlos ◽

Keith D. Hunter ◽

...

Keyword(s):

International Collaboration ◽

Case Series ◽

Initial Step ◽

Odontogenic Tumors ◽

Data Set ◽

Expert Opinions ◽

Organ Systems ◽

Standardized Reporting ◽

Selection Of ◽

Cancer Reporting

A data set has been developed for the reporting of excisional biopsies and resection specimens for malignant odontogenic tumors by members of an expert panel working on behalf of the International Collaboration on Cancer Reporting, an international organization established to unify and standardize reporting of cancers. Odontogenic tumors are rare, which limits evidence-based support for designing a scientifically sound data set for reporting them. Thus, the selection of reportable elements within the data set and considering them as either core or noncore is principally based on evidence from malignancies affecting other organ systems, limited case series, expert opinions, and/or anecdotal reports. Nevertheless, this data set serves as the initial step toward standardized reporting on malignant odontogenic tumors that should evolve over time as more evidence becomes available and functions as a prompt for further research to provide such evidence.

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Electric Boosting and Energy Recovery Systems for Engine Downsizing

Energies ◽

10.3390/en12244636 ◽

2019 ◽

Vol 12 (24) ◽

pp. 4636 ◽

Cited By ~ 5

Author(s):

Mamdouh Alshammari ◽

Fuhaid Alshammari ◽

Apostolos Pesyridis

Keyword(s):

Fuel Economy ◽

Energy Recovery ◽

Passenger Cars ◽

Pros And Cons ◽

Boosting Method ◽

Increasing Demand ◽

Selection Of

Due to the increasing demand for better fuel economy and increasingly stringent emissions regulations, engine manufacturers have paid attention towards engine downsizing as the most suitable technology to meet these requirements. This study sheds light on the technology currently available or under development that enables engine downsizing in passenger cars. Pros and cons, and any recently published literature of these systems, will be considered. The study clearly shows that no certain boosting method is superior. Selection of the best boosting method depends largely on the application and complexity of the system.

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A Proposed Heuristic Optimization Algorithm for Detecting Network Attacks

The Academic Research Community Publication ◽

10.21625/archive.v2i4.397 ◽

2019 ◽

Vol 2 (4) ◽

pp. 530

Author(s):

Amr Hassan Yassin ◽

Hany Hamdy Hussien

Keyword(s):

Neural Network ◽

Heuristic Algorithms ◽

Feed Forward Neural Network ◽

Data Set ◽

Network Attacks ◽

Security Issues ◽

Proposed Model ◽

Network Intrusions ◽

Attack Patterns ◽

Selection Of

Due to the exponential growth of E-Business and computing capabilities over the web for a pay-for-use groundwork, the risk factors regarding security issues also increase rapidly. As the usage increases, it becomes very difficult to identify malicious attacks since the attack patterns change. Therefore, host machines in the network must continually be monitored for intrusions since they are the final endpoint of any network. The purpose of this work is to introduce a generalized neural network model that has the ability to detect network intrusions. Two recent heuristic algorithms inspired by the behavior of natural phenomena, namely, the particle swarm optimization (PSO) and gravitational search (GSA) algorithms are introduced. These algorithms are combined together to train a feed forward neural network (FNN) for the purpose of utilizing the effectiveness of these algorithms to reduce the problems of getting stuck in local minima and the time-consuming convergence rate. Dimension reduction focuses on using information obtained from NSL-KDD Cup 99 data set for the selection of some features to discover the type of attacks. Detecting the network attacks and the performance of the proposed model are evaluated under different patterns of network data.

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Perspectives from animal demography on incorporating evolutionary mechanism into plant population dynamics

10.1101/420869 ◽

2018 ◽

Author(s):

Maria Paniw

Keyword(s):

Environmental Change ◽

Evolutionary Dynamics ◽

Natural Populations ◽

Population Level ◽

Plant Population ◽

Future Research ◽

Phenotypic Traits ◽

Plant Population Dynamics ◽

Future Research Agenda ◽

Powerful Approach

AbstractWith a growing number of long-term, individual-based data on natural populations available, it has become increasingly evident that environmental change affects populations through complex, simultaneously occurring demographic and evolutionary processes. Analyses of population-level responses to environmental change must therefore integrate demography and evolution into one coherent framework. Integral projection models (IPMs), which can relate genetic and phenotypic traits to demographic and population-level processes, offer a powerful approach for such integration. However, a rather artificial divide exists in how plant and animal population ecologists use IPMs. Here, I argue for the integration of the two sub-disciplines, particularly focusing on how plant ecologists can diversify their toolset to investigate selection pressures and eco-evolutionary dynamics in plant population models. I provide an overview of approaches that have applied IPMs for eco-evolutionary studies and discuss a potential future research agenda for plant population ecologists. Given an impending extinction crisis, a holistic look at the interacting processes mediating population persistence under environmental change is urgently needed.

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Counter-Interception and Counter-Exploitation Features of Noise Radar Technology

Remote Sensing ◽

10.3390/rs13224509 ◽

2021 ◽

Vol 13 (22) ◽

pp. 4509

Author(s):

Gaspare Galati ◽

Gabriele Pavan ◽

Kubilay Savci ◽

Christoph Wasserzier

Keyword(s):

Information Theory ◽

Technological Progress ◽

A Priori ◽

A Priori Knowledge ◽

Noise Radar ◽

Low Probability ◽

Increasing Demand ◽

Signal Processors ◽

Function Information ◽

Selection Of

In defense applications, the main features of radars are the Low Probability of Intercept (LPI) and the Low Probability of Exploitation (LPE). The counterpart uses more and more capable intercept receivers and signal processors thanks to the ongoing technological progress. Noise Radar Technology (NRT) is probably a very effective answer to the increasing demand for operational LPI/LPE radars. The design and selection of the radiated waveforms, while respecting the prescribed spectrum occupancy, has to comply with the contrasting requirements of LPI/LPE and of a favorable shape of the ambiguity function. Information theory seems to be a “technologically agnostic” tool to attempt to quantify the LPI/LPE capability of noise waveforms with little, or absent, a priori knowledge of the means and the strategies used by the counterpart. An information theoretical analysis can lead to practical results in the design and selection of NRT waveforms.

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Automatic Misinformation Detection About COVID-19 in Brazilian Portuguese WhatsApp Messages

10.5753/sbbd_estendido.2021.18173 ◽

2021 ◽

Author(s):

Antônio Diogo Forte Martins ◽

José Maria Monteiro ◽

Javam Machado

Keyword(s):

Machine Learning ◽

Social Networks ◽

Brazilian Portuguese ◽

Primary Sources ◽

Learning Methods ◽

Data Set ◽

Machine Learning Methods

During the coronavirus pandemic, the problem of misinformation arose once again, quite intensely, through social networks. In Brazil, one of the primary sources of misinformation is the messaging application WhatsApp. However, due to WhatsApp's private messaging nature, there still few methods of misinformation detection developed specifically for this platform. In this context, the automatic misinformation detection (MID) about COVID-19 in Brazilian Portuguese WhatsApp messages becomes a crucial challenge. In this work, we present the COVID-19.BR, a data set of WhatsApp messages about coronavirus in Brazilian Portuguese, collected from Brazilian public groups and manually labeled. Then, we are investigating different machine learning methods in order to build an efficient MID for WhatsApp messages. So far, our best result achieved an F1 score of 0.774 due to the predominance of short texts. However, when texts with less than 50 words are filtered, the F1 score rises to 0.85.

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Comparative analysis of the ftness of Drosophila virilis lines contrasting in response to stress

Vavilov Journal of Genetics and Breeding ◽

10.18699/vj18.455 ◽

2019 ◽

Vol 22 (8) ◽

pp. 1090-1096

Author(s):

E. K. Karpova ◽

I. Yu. Rauschenbach ◽

N. E. Gruntenko

Keyword(s):

Heat Stress ◽

Natural Populations ◽

Population Level ◽

Stress Reaction ◽

Egg Laying ◽

Drosophila Virilis ◽

Gonadotropic Hormone ◽

Adverse Conditions ◽

Low Intensity ◽

Response To Stress

One of the crucial elements contributing to the adaptation of organisms to unfavorable environmental conditions is the reaction of stress. The study of its genetic control and role in adaptation to unfavorable conditions are of special interest. The juvenile hormone (JH) acts as a gonadotropic hormone in adult insects controlling the development of the ovaries, inducing vitellogenesis and oviposition. It was shown that a decrease in JH degradation in individuals reacting to adverse conditions by stress reaction (Rindividuals) causes delay in egg laying and seems to allow the population to “wait out” the unfavorable conditions, thereby contributing to the adaptation at the population level. However, monitoring natural populations of D. melanogaster for the capability of stress reaction demonstrated that they have a high percentage of individuals incapable of it (NRindividuals). The study of reproductive characteristics of R and NRindividuals showed that under normal conditions Rindividuals have the advantage of procreating oﬀspring. Under unfavorable conditions, if the stressor is intense enough, NRindividuals die, but if its intensity is low, then they, unlike Rindividuals, continue to produce oﬀspring. Based on these data, it was hypothesized that the balance of R and NRalleles in the population ensures its adaptation under frequent stresses of low intensity. To verify the hypothesis by an experiment, the ftness characteristics (lifespan, fecundity) of the R and NR lines of D. virilis were studied under normal conditions and under regular heat stress of various frequency.

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Multivariate analysis of quantitative traits can effectively classify rapeseed germplasm

Genetika ◽

10.2298/gensr1402545j ◽

2014 ◽

Vol 46 (2) ◽

pp. 545-559 ◽

Cited By ~ 1

Author(s):

Mirjana Jankulovska ◽

Sonja Ivanovska ◽

Ana Marjanovic-Jeromela ◽

Snjezana Bolaric ◽

Ljupcho Jankuloski ◽

...

Keyword(s):

Regression Analysis ◽

Vegetative Growth ◽

Quantitative Traits ◽

Principal Component ◽

Breeding Program ◽

Oil Yield ◽

Growth Duration ◽

Data Set ◽

Combined Application ◽

Selection Of

In this study, the use of different multivariate approaches to classify rapeseed genotypes based on quantitative traits has been presented. Tree regression analysis, PCA analysis and two-way cluster analysis were applied in order todescribe and understand the extent of genetic variability in spring rapeseed genotype by trait data. The traits which highly influenced seed and oil yield in rapeseed were successfully identified by the tree regression analysis. Principal predictor for both response variables was number of pods per plant (NP). NP and 1000 seed weight could help in the selection of high yielding genotypes. High values for both traits and oil content could lead to high oil yielding genotypes. These traits may serve as indirect selection criteria and can lead to improvement of seed and oil yield in rapeseed. Quantitative traits that explained most of the variability in the studied germplasm were classified using principal component analysis. In this data set, five PCs were identified, out of which the first three PCs explained 63% of the total variance. It helped in facilitating the choice of variables based on which the genotypes? clustering could be performed. The two-way cluster analysissimultaneously clustered genotypes and quantitative traits. The final number of clusters was determined using bootstrapping technique. This approach provided clear overview on the variability of the analyzed genotypes. The genotypes that have similar performance regarding the traits included in this study can be easily detected on the heatmap. Genotypes grouped in the clusters 1 and 8 had high values for seed and oil yield, and relatively short vegetative growth duration period and those in cluster 9, combined moderate to low values for vegetative growth duration and moderate to high seed and oil yield. These genotypes should be further exploited and implemented in the rapeseed breeding program. The combined application of these multivariate methods can assist in deciding how, and based on which traits to select the genotypes, especially in early generations, at the beginning of a breeding program.

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