Sequence of the Sugar Pine Megagenome Stevens, Kristian A; Wegrzyn, Jill L; Zimin, Aleksey ...
Genetics (Austin),
12/2016, Letnik:
204, Številka:
4
Journal Article
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Until very recently, complete characterization of the megagenomes of conifers has remained elusive. The diploid genome of sugar pine (Pinus lambertiana Dougl.) has a highly repetitive, 31 billion bp ...genome. It is the largest genome sequenced and assembled to date, and the first from the subgenus Strobus, or white pines, a group that is notable for having the largest genomes among the pines. The genome represents a unique opportunity to investigate genome "obesity" in conifers and white pines. Comparative analysis of P. lambertiana and P. taeda L. reveals new insights on the conservation, age, and diversity of the highly abundant transposable elements, the primary factor determining genome size. Like most North American white pines, the principal pathogen of P. lambertiana is white pine blister rust (Cronartium ribicola J.C. Fischer ex Raben.). Identification of candidate genes for resistance to this pathogen is of great ecological importance. The genome sequence afforded us the opportunity to make substantial progress on locating the major dominant gene for simple resistance hypersensitive response, Cr1 We describe new markers and gene annotation that are both tightly linked to Cr1 in a mapping population, and associated with Cr1 in unrelated sugar pine individuals sampled throughout the species' range, creating a solid foundation for future mapping. This genomic variation and annotated candidate genes characterized in our study of the Cr1 region are resources for future marker-assisted breeding efforts as well as for investigations of fundamental mechanisms of invasive disease and evolutionary response.
Trade credit and SME profitability Martínez-Sola, Cristina; García-Teruel, Pedro J.; Martínez-Solano, Pedro
Small business economics,
03/2014, Letnik:
42, Številka:
3
Journal Article
Recenzirano
Financial literature discusses the motives for trade credit provision by suppliers in depth. However, there is no empirical evidence of the effect of granting trade credit on the profitability of ...small and medium-sized firms. We examine the profitability implications of providing financing to customers for a sample of 11,337 Spanish manufacturing SMEs during the 2000-2007 period. This article also examines the differences in the profitability of trade credit according to financial, operational, and commercial motives. The findings suggest that managers can improve firm profitability by increasing their investment in receivables and that the effect is greater for financially unconstrained firms (larger and more liquid firms), for firms with volatile demand, and for firms with bigger market shares.
Summary
Over the last 20 years, global production of Persian walnut (Juglans regia L.) has grown enormously, likely reflecting increased consumption due to its numerous benefits to human health. ...However, advances in genome‐wide association (GWA) studies and genomic selection (GS) for agronomically important traits in walnut remain limited due to the lack of powerful genomic tools. Here, we present the development and validation of a high‐density 700K single nucleotide polymorphism (SNP) array in Persian walnut. Over 609K high‐quality SNPs have been thoroughly selected from a set of 9.6 m genome‐wide variants, previously identified from the high‐depth re‐sequencing of 27 founders of the Walnut Improvement Program (WIP) of University of California, Davis. To validate the effectiveness of the array, we genotyped a collection of 1284 walnut trees, including 1167 progeny of 48 WIP families and 26 walnut cultivars. More than half of the SNPs (55.7%) fell in the highest quality class of ‘Poly High Resolution’ (PHR) polymorphisms, which were used to assess the WIP pedigree integrity. We identified 151 new parent‐offspring relationships, all confirmed with the Mendelian inheritance test. In addition, we explored the genetic variability among cultivars of different origin, revealing how the varieties from Europe and California were differentiated from Asian accessions. Both the reconstruction of the WIP pedigree and population structure analysis confirmed the effectiveness of the Applied Biosystems™ Axiom™ J. regia 700K SNP array, which initiates a novel genomic and advanced phase in walnut genetics and breeding.
Abstract Breast cancer is the most frequently diagnosed cancer in women. Using historical patient information stored in clinical datasets, data mining and machine learning approaches can be applied ...to predict the survival of breast cancer patients. A common drawback is the absence of information, i.e., missing data, in certain clinical trials. However, most standard prediction methods are not able to handle incomplete samples and, then, missing data imputation is a widely applied approach for solving this inconvenience. Therefore, and taking into account the characteristics of each breast cancer dataset, it is required to perform a detailed analysis to determine the most appropriate imputation and prediction methods in each clinical environment. This research work analyzes a real breast cancer dataset from Institute Portuguese of Oncology of Porto with a high percentage of unknown categorical information (most clinical data of the patients are incomplete), which is a challenge in terms of complexity. Four scenarios are evaluated: (I) 5-year survival prediction without imputation and 5-year survival prediction from cleaned dataset with (II) Mode imputation, (III) Expectation-Maximization imputation and (IV) K -Nearest Neighbors imputation. Prediction models for breast cancer survivability are constructed using four different methods: K -Nearest Neighbors, Classification Trees, Logistic Regression and Support Vector Machines. Experiments are performed in a nested ten-fold cross-validation procedure and, according to the obtained results, the best results are provided by the K -Nearest Neighbors algorithm: more than 81% of accuracy and more than 0.78 of area under the Receiver Operator Characteristic curve, which constitutes very good results in this complex scenario.
Private family firms, generations and bank debt Díaz‐Díaz, Nieves Lidia; García‐Teruel, Pedro J.; Martínez‐Solano, Pedro
Accounting and finance (Parkville),
09/2023, Letnik:
63, Številka:
3
Journal Article
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Abstract
This paper focuses on the use of bank debt by private family firms and whether it is higher for the first generations of family businesses than for their descendants and subsequent ...generations. We use a unique hand‐collected data set of 4,041 private Spanish firms for the years 2004 to 2013. We find statistical evidence that family‐controlled firms make greater use of bank credit. Moreover, we show that first‐generation family firms acquire more bank debt than those of second and subsequent generations. Furthermore, during financial crises, family‐controlled firms were subjected to less rationing, with increased bank financing for first generations.
Abstract Objectives Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. This work evaluates the ...performance of several statistical and machine learning imputation methods that were used to predict recurrence in patients in an extensive real breast cancer data set. Materials and methods Imputation methods based on statistical techniques, e.g., mean, hot-deck and multiple imputation, and machine learning techniques, e.g., multi-layer perceptron (MLP), self-organisation maps (SOM) and k-nearest neighbour (KNN), were applied to data collected through the “El Álamo-I” project, and the results were then compared to those obtained from the listwise deletion (LD) imputation method. The database includes demographic, therapeutic and recurrence-survival information from 3679 women with operable invasive breast cancer diagnosed in 32 different hospitals belonging to the Spanish Breast Cancer Research Group (GEICAM). The accuracies of predictions on early cancer relapse were measured using artificial neural networks (ANNs), in which different ANNs were estimated using the data sets with imputed missing values. Results The imputation methods based on machine learning algorithms outperformed imputation statistical methods in the prediction of patient outcome. Friedman’s test revealed a significant difference ( p = 0.0091 ) in the observed area under the ROC curve (AUC) values, and the pairwise comparison test showed that the AUCs for MLP, KNN and SOM were significantly higher ( p = 0.0053 , p = 0.0048 and p = 0.0071 , respectively) than the AUC from the LD-based prognosis model. Conclusion The methods based on machine learning techniques were the most suited for the imputation of missing values and led to a significant enhancement of prognosis accuracy compared to imputation methods based on statistical procedures.
The availability of a complete peach genome assembly and three different peach genome sequences created by our group provide new opportunities for application of genomic data and can improve the ...power of the classical Quantitative Trait Loci (QTL) approaches to identify candidate genes for peach disease resistance. Brown rot caused by Monilinia spp., is the most important fungal disease of stone fruits worldwide. Improved levels of peach fruit rot resistance have been identified in some cultivars and advanced selections developed in the UC Davis and USDA breeding programs. Whole genome sequencing of the Pop-DF parents lead to discovery of high-quality SNP markers for QTL genome scanning in this experimental population. Pop-DF created by crossing a brown rot moderately resistant cultivar 'Dr. Davis' and a brown rot resistant introgression line, 'F8,1-42', derived from an initial almond × peach interspecific hybrid, was evaluated for brown rot resistance in fruit of harvest maturity over three seasons. Using the SNP linkage map of Pop-DF and phenotypic data collected with inoculated fruit, a genome scan for QTL identified several SNP markers associated with brown rot resistance. Two of these QTLs were placed on linkage group 1, covering a large (physical) region on chromosome 1. The genome scan for QTL and SNP effects predicted several candidate genes associated with disease resistance responses in other host-pathogen systems. Two potential candidate genes, ppa011763m and ppa026453m, may be the genes primarily responsible for M. fructicola recognition in peach, activating both PAMP-triggered immunity (PTI) and effector-triggered immunity (ETI) responses. Our results provide a foundation for further genetic dissection, marker assisted breeding for brown rot resistance, and development of peach cultivars resistant to brown rot.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Infection by the SARS-Cov-2 virus produces in humans a disease of highly variable and unpredictable severity. The presence of frequent genetic single nucleotide polymorphisms (SNPs) in the population ...might lead to a greater susceptibility to infection or an exaggerated inflammatory response. SARS-CoV-2 requires the presence of the ACE2 protein to enter in the cell and ACE2 is a regulator of the renin-angiotensin system. Accordingly, we studied the associations between 8 SNPs from AGTR1, ACE2 and ACE genes and the severity of the disease produced by the SARS-Cov-2 virus.
318 (aged 59.6±17.3 years, males 62.6%) COVID-19 patients were grouped based on the severity of symptoms: Outpatients (n = 104, 32.7%), hospitalized on the wards (n = 73, 23.0%), Intensive Care Unit (ICU) (n = 84, 26.4%) and deceased (n = 57, 17.9%). Comorbidity data (diabetes, hypertension, obesity, lung disease and cancer) were collected for adjustment. Genotype distribution of 8 selected SNPs among the severity groups was analyzed.
Four SNPs in ACE2 were associated with the severity of disease. While rs2074192 andrs1978124showed a protector effectassuming an overdominant model of inheritance (G/A vs. GG-AA, OR = 0.32, 95%CI = 0.12-0.82; p = 0.016 and A/G vs. AA-GG, OR = 0.37, 95%CI: 0.14-0.96; p = 0.038, respectively); the SNPs rs2106809 and rs2285666were associated with an increased risk of being hospitalized and a severity course of the disease with recessive models of inheritance (C/C vs. T/C-T/T, OR = 11.41, 95% CI: 1.12-115.91; p = 0.012) and (A/A vs. GG-G/A, OR = 12.61, 95% CI: 1.26-125.87; p = 0.0081). As expected, an older age (OR = 1.47), male gender (OR = 1.98) and comorbidities (OR = 2.52) increased the risk of being admitted to ICU or death vs more benign outpatient course. Multivariable analysis demonstrated the role of the certain genotypes (ACE2) with the severity of COVID-19 (OR: 0.31, OR 0.37 for rs2074192 and rs1978124, and OR = 2.67, OR = 2.70 for rs2106809 and rs2285666, respectively). Hardy-Weinberg equilibrium in hospitalized group for I/D SNP in ACE was not showed (p<0.05), which might be due to the association with the disease. No association between COVID-19 disease and the different AGTR1 SNPs was evidenced on multivariable, nevertheless the A/A genotype for rs5183 showed an higher hospitalization risk in patients with comorbidities.
Different genetic variants in ACE2 were associated with a severe clinical course and death groups of patients with COVID-19. ACE2 common SNPs in the population might modulate severity of COVID-19 infection independently of other known markers like gender, age and comorbidities.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The present work studies the influence of waste fish oil, palm oil and waste frying oil as raw material on biodiesel properties. The experimental planning was executed through acid esterification ...(6:1 methanol to oil ratio, 1wt.% sulfuric acid, at 60°C, 1h) followed by transesterification (9:1 methanol to oil ratio, 0.5wt.% sodium hydroxide, at 60°C for 1h). Biodiesel samples showed yield higher than 82%, reaching 90% for palm oil (33.3wt.%) and waste frying oil (66.7wt.%) biodiesel. FAME content was higher than 92.3% and had a maximum of 98.5% for waste fish oil (33.3wt.%) and palm oil (66.7wt.%) biodiesel. Special cubic models were used to fit experimental data, and were optimized by response surface methodology and multi-objective optimization. Viscosity (4.3mm2/s) and COM (2.5°C) were minimized when pure fish oil was used as raw material, whereas IP maximum (22.0h) was found for palm oil biodiesel. Multi-objective optimization evidenced that although the use of the pure oils as feedstock presented more advantages to biodiesel properties, the waste fish oil (42.1wt.%) and waste frying oil (57.9wt.%) mix is beneficial, if the aim is IP (20%) and COM (80%) improvement.
•Biodiesel production from mixtures of waste fish oil, palm oil and waste frying oil•A simplex centroid design and statistical modeling were performed.•High biodiesel yield and FAME content were obtained for all the oil mixtures assayed.•Fuel properties such as viscosity, oxidative stability and COM were optimized.•A Pareto Front was generated using weighted-sum multi-objective optimization.
Amimia is one of the most typical features of Parkinson's disease (PD). However, its significance and correlation with motor and nonmotor symptoms is unknown. The aim of this study is to evaluate the ...association between amimia and motor and nonmotor symptoms, including cognitive status, depression, and quality of life in PD patients. We also tested the blink rate as a potential tool for objectively measuring upper facial bradykinesia.
We prospectively studied amimia in PD patients. Clinical evaluation was performed using the Unified Parkinson's Disease Rating Scale (UPDRS) and timed tests. Cognitive status, depression, and quality of life were assessed using the Parkinson's Disease Cognitive Rating Scale (PD-CRS), the 16-Item Quick Inventory of Depressive Symptomatology (QIDS-SR16), and the PDQ-39, respectively. Amimia was clinically evaluated according to item 19 of UPDRS III. Finally, we studied upper facial amimia by measuring resting blink frequency and blink rate during spontaneous conversation.
We included 75 patients. Amimia (item 19 UPDRS III) correlated with motor and total UPDRS (r: 0.529 and 0.551 Spearman), and its rigidity, distal bradykinesia, and motor axial subscores (r: 0.472; r: 0.252, and r: 0.508, respectively); Hoehn and Yahr scale (r: 0.392), timed tests, gait freezing, cognitive status (r: 0.29), and quality of life (r: 0.268) correlated with amimia. Blinking frequency correlated with amimia (measured with item 19 UPDRS), motor and total UPDRS.
Amimia correlates with motor (especially axial symptoms) and cognitive situations in PD. Amimia could be a useful global marker of overall disease severity, including cognitive decline.
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