Patterns of genomic and phenomic diversity in wine and table grapes.

Grapes are one of the most economically and culturally important crops worldwide, and they have been bred for both winemaking and fresh consumption. Here we evaluate patterns of diversity across 33 phenotypes collected over a 17-year period from 580 table and wine grape accessions that belong to one of the world's largest grape gene banks, the grape germplasm collection of the United States Department of Agriculture. We find that phenological events throughout the growing season are correlated, and quantify the marked difference in size between table and wine grapes. By pairing publicly available historical phenotype data with genome-wide polymorphism data, we identify large effect loci controlling traits that have been targeted during domestication and breeding, including hermaphroditism, lighter skin pigmentation and muscat aroma. Breeding for larger berries in table grapes was traditionally concentrated in geographic regions where Islam predominates and alcohol was prohibited, whereas wine grapes retained the ancestral smaller size that is more desirable for winemaking in predominantly Christian regions. We uncover a novel locus with a suggestive association with berry size that harbors a signature of positive selection for larger berries. Our results suggest that religious rules concerning alcohol consumption have had a marked impact on patterns of phenomic and genomic diversity in grapes

The cognitive development from childhood to adolescence of low birthweight children born after medically assisted reproduction-a UK longitudinal cohort study.

BACKGROUND: Previous research has documented that children conceived through medically assisted reproduction (MAR) are at increased risk of poor birth outcomes, such as low birthweight (LBW), which are risk factors for stunted longer-term cognitive development. However, parents who undergo MAR to conceive have, on average, advantaged socioeconomic backgrounds which could compensate for the negative effects of being born LBW. Previous studies have not analysed whether the negative effects of LBW are attenuated among MAR conceived children. METHODS: We draw on the UK Millennium Cohort Study (sweeps 1-6) which contains a sub-sample of (N = 396) MAR-conceived children. The dependent variable measures cognitive ability at around ages 3, 5, 7, 11 and 14. We examine the cognitive development of four groups of children: MAR-conceived low birthweight (MAR LBW); MAR-conceived non-low birthweight (MAR NLBW); naturally conceived low birthweight (NC LBW); naturally conceived non-low birthweight (NC NLBW). We estimate the two following linear regression models for each sweep: (i) a baseline model to examine the unadjusted association between cognitive development and low birthweight by mode of conception; and (ii) a model adjusted by socio-demographic family characteristics. RESULTS: In baseline models, MAR LBW children [age 3: β  =  0.021, 95% confidence interval (CI): -0.198, 0.241; age 5: β  =  0.21, 95% CI: 0.009, 0.418; age 7: β  =  0.163, 95% CI: -0.148, 0.474; age 11: β  =  0.003, 95% CI: -0.318, 0.325; age 14: β  =  0.156, 95% CI: -0.205, 0.517], on average perform similarly in cognitive ability relative to NC NLBW at all ages, and display higher cognitive scores than NC LBW children until age 7. When we account for family characteristics, differences are largely attenuated and become close to zero at age 14. CONCLUSIONS: Despite the higher incidence of LBW among MAR compared with NC children, they do not seem to experience any disadvantage in their cognitive development compared with naturally conceived children. This finding is likely explained by the fact that, on average, MAR children are born to socioeconomically advantaged parents

Evaluation of distributed denial of service attacks detection in software defined networks

Software-defined networking (SDN) revolutionizes networking by separating control logic and data forwarding, enhancing security against threats like distributed denial of service (DDoS) attacks. These attacks flood control plane bandwidth, causing SDN network failures. Recent studies emphasize the efficacy of machine learning (ML) and statistical approaches in identifying and mitigating these security risks. However, there has been a lack of focus on employing ensembling techniques, amalgamating diverse ML models, selecting pertinent features, and utilizing oversampling techniques to balance categorical data. Our study evaluates 20 machine-learning models, emphasizing feature engineering and addressing class imbalance using synthetic minority oversampling technique (SMOTE). The results indicate that ensemble methods such as light gradient boosting machine (LGBM) classifier, random forest classifier, XGB classifier, decision tree classifier obtained near-perfect scores (almost 100%) across all metrics, suggesting potential overfitting. Conversely, models like AdaBoost classifier, k-neighbors classifier, and support vector classifier (SVC) exhibited slightly lower (99%) but realistic performance, underscoring the intricacy of accurate prediction in cybersecurity. Simpler models, including logistic regression, linear discriminant analysis, and Gaussian naive Bayes, demonstrated moderate to low accuracy, approximately around 70%. These findings stress the imperative need for a nuanced approach in the selection and fine-tuning of ML models to ensure effective DDoS detection in SDN environments.

Transcriptome profiling of grapevine seedless segregants during berry development reveals candidate genes associated with berry weight

Indexación: Web of Science; PubMedBackground Berry size is considered as one of the main selection criteria in table grape breeding programs. However, this is a quantitative and polygenic trait, and its genetic determination is still poorly understood. Considering its economic importance, it is relevant to determine its genetic architecture and elucidate the mechanisms involved in its expression. To approach this issue, an RNA-Seq experiment based on Illumina platform was performed (14 libraries), including seedless segregants with contrasting phenotypes for berry weight at fruit setting (FST) and 6–8 mm berries (B68) phenological stages. Results A group of 526 differentially expressed (DE) genes were identified, by comparing seedless segregants with contrasting phenotypes for berry weight: 101 genes from the FST stage and 463 from the B68 stage. Also, we integrated differential expression, principal components analysis (PCA), correlations and network co-expression analyses to characterize the transcriptome profiling observed in segregants with contrasting phenotypes for berry weight. After this, 68 DE genes were selected as candidate genes, and seven candidate genes were validated by real time-PCR, confirming their expression profiles. Conclusions We have carried out the first transcriptome analysis focused on table grape seedless segregants with contrasting phenotypes for berry weight. Our findings contributed to the understanding of the mechanisms involved in berry weight determination. Also, this comparative transcriptome profiling revealed candidate genes for berry weight which could be evaluated as selection tools in table grape breeding programs.http://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-016-0789-

Genetic structure and domestication history of the grape

The grape is one of the earliest domesticated fruit crops and, since antiquity, it has been widely cultivated and prized for its fruit and wine. Here, we characterize genome-wide patterns of genetic variation in over 1,000 samples of the domesticated grape, Vitis vinifera subsp. vinifera, and its wild relative, V. vinifera subsp. sylvestris from the US Department of Agriculture grape germ-plasm collection. We find support for a Near East origin of vinifera and present evidence of introgression from local sylvestris as the grape moved into Europe. High levels of genetic diversity and rapid linkage disequilibrium (LD) decay have been maintained in vinifera, which is consistent with a weak domestication bottleneck followed by thousands of years of widespread vegetative propagation. The considerable genetic diversity within vinifera, however, is contained within a complex network of close pedigree relationships that has been generated by crosses among elite cultivars. We show that first-degree relationships are rare between wine and table grapes and among grapes from geographically distant regions. Our results suggest that although substantial genetic diversity has been maintained in the grape subsequent to domestication, there has been a limited exploration of this diversity. We propose that the adoption of vegetative propagation was a double-edged sword: Although it provided a benefit by ensuring true breeding cultivars, it also discouraged the generation of unique cultivars through crosses. The grape currently faces severe pathogen pressures, and the long-term sustainability of the grape and wine industries will rely on the exploitation of the grape's tremendous natural genetic diversity

Probabilistic Neural Network based Approach for Handwritten Character Recognition

In this paper, recognition system for totally unconstrained handwritten characters for south Indian language of Kannada is proposed. The proposed feature extraction technique is based on Fourier Transform and well known Principal Component Analysis (PCA). The system trains the appropriate frequency band images followed by PCA feature extraction scheme. For subsequent classification technique, Probabilistic Neural Network (PNN) is used. The proposed system is tested on large database containing Kannada characters and also tested on standard COIL-20 object database and the results were found to be better compared to standard techniques

Neighborhood Structure-Based Model for Multilingual Arbitrarily-Oriented Text Localization in Images/Videos.

The text matter in an image or a video provides more important clue and semantic information of the particular event in the actual situation. Text localization task stands an interesting and challenging research-oriented process in the zone of image processing due to irregular alignments, brightness, degradation, and complexbackground. The multilingual textual information has different types of geometrical shapes and it makes further complex to locate the text information. In this work, an effective model is presented to locate the multilingual arbitrary oriented text. The proposed method developed a neighborhood structure model to locate the text region. Initially, the maxmin cluster is applied along with 3X3 sliding window to sharpen the text region. The neighborhood structure creates the boundary for every component using normal deviation calculated from the sharpened image. Finally, the double stroke structure model is employed to locate the accurate text region. The presented model is analyzed on five standard datasets such as NUS, arbitrarily oriented text, Hua's, MRRC and real-time video dataset with performance metrics such as recall, precision, and f-measure

Understanding the excess COVID-19 burden among immigrants in Norway

Background: We aim to use intermarriage as a measure to disentangle the role of exposure to virus, susceptibility and care in differences in burden of COVID-19, by comparing rates of COVID-19 infections between immigrants married to a native and to another immigrant. Methods: Using data from the Norwegian emergency preparedness, register participants (N=2 312 836) were linked with their registered partner and categorized based on own and partner's country of birth. From logistic regressions, odds ratios (OR) of COVID-19 infection (15 June 2020-01 June 2021) and related hospitalization were calculated adjusted for age, sex, municipality, medical risk, occupation, household income, education and crowded housing. Results: Immigrants were at increased risk of COVID-19 and related hospitalization regardless of their partners being immigrant or not, but immigrants married to a Norwegian-born had lower risk than other immigrants. Compared with intramarried Norwegian-born, odds of COVID-19 infection was higher among persons in couples with one Norwegian-born and one immigrant from Europe/USA/Canada/Oceania (OR 1.42-1.46) or Africa/Asia/Latin-America (OR 1.91-2.01). Odds of infection among intramarried immigrants from Africa/Asia/Latin-America was 4.92. For hospitalization, the corresponding odds were slightly higher. Conclusion: Our study suggests that the excess burden of COVID-19 among immigrants is explained by differences in exposure and care rather than susceptibility. Keywords: COVID-19; Norway; hospitalization; immigrant; infection; register data.Understanding the excess COVID-19 burden among immigrants in NorwaypublishedVersio

Citotoksičnost, inhibicija agregacije trombocita i antioksidativna aktivnost ekstrakata biljke Curcuma amada Roxb.

Mango ginger (Curcuma amada Roxb.) is a unique spice having morphological resemblance to ginger but imparts raw mango flavour. The sequential extraction of mango ginger rhizome powder was carried out using hexane, chloroform, ethyl acetate, acetone, methanol and water. The phenolic content was the highest in methanol extract, followed by acetone, ethyl acetate and water extracts. Among these, chloroform extract exhibited high lipid peroxidation inhibitory activity and metal chelating activity, whereas ethyl acetate extract showed high DPPH radical scavenging activity and superoxide radical scavenging activity. Mango ginger extracts also showed potential platelet aggregation inhibitory activity and cytotoxicity properties.Curcuma amada Roxb. jedinstveni je začin jer morfološki nalikuje đumbiru, a po okusu je sličan mangu. Provedena je sekvencijska ekstrakcija praha dobivenog od rizoma te biljke pomoću heksana, kloroforma, etilnog acetata, acetona, metanola i vode. Udjel fenola bio je najveći u ekstraktu dobivenom pomoću metanola, zatim acetona i etilnog acetata, a najmanji u vodenom ekstraktu. Ekstrakt dobiven pomoću kloroforma imao je najveću sposobnost inhibicije peroksidacije lipida i keliranja metala, a onaj dobiven pomoću etilnog acetata najbolje svojstvo uklanjanja DPPH i superoksidnih radikala. Ekstrakti biljke Curcuma amada Roxb. imali su i sposobnost inhibicije agregacije trombocita te citotoksična svojstva