bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of piston thermal barrier coating roughness on high-load diesel operation
Authors: Gingrich Eric , Tess Michael , Korivi Vamshi , Schihl Peter , Saputo John , Smith Gregory M , Sampath Sanjay , Ghandhi Jaal
Published: December 2019

Thermal barrier coatings of various thickness and surface roughness were applied to the piston crown of a single-cylinder research engine and tested over a range of high-output diesel operating conditions, some near 30 bar gross indicated mean effective pressure. Three yttria-stabilized zirconia coated pistons were compared to a baseline metal piston. At each operating condition, a start-of-injection sweep was conducted to generate efficiency trends and find the optimal combustion phasing. Three variations of pistons coated with a graded-layer thermal barrier coating were tested: (1) 0.185 mm coating thickness with a surface roughness of approximately Ra = 11.8 µm, (2) 0.325 mm thickness with Ra = 11.8 µm, and (3) 0.325 mm thickness with Ra = 6.0 µm. Both coated pistons with Ra = 11.8 µm did not show any statistically significant improvement to engine performance when compared to the metal baseline piston, but did produce higher filter smoke numbers. The coated piston with Ra = 6.0 µm and 0.325 mm showed an increase of gross indicated thermal efficiency of up to 3.5% (relative) compared to the metal baseline piston for operating conditions comparable to standard engine operation and a reduction of filter smoke number back to the metal baseline. The increase in efficiency was found to correlate with additional late-cycle apparent heat release and a reduction in in-cylinder heat transfer. The very high-output conditions showed statistically insignificant changes in performance or heat transfer, which may have been related to the long injection duration used for these cases targeting outside of the piston bowl.
Social and personal resources and adaptive and non-adaptive strategies for coping with stress in a group of socially maladjusted youths
Authors: Konaszewski Karol , Niesiobędzka Małgorzata , Kolemba Marcin
Published: December 2019

This article is the result of an empirical research project analysing the relationship between the resources of socially maladjusted youth and their strategies for coping with stress. The research was focused on non-formal functional support from family members and two types of personal resources – resilience and a sense of coherence – in forming tendencies to take advantage of adaptive and non-adaptive strategies for coping with stress. The research participants consisted of young, socially maladjusted people who have been directed to attendance centres, youth sociotherapy centres, and youth educational centres all over Poland ( N = 468). Structural equation modelling was used to verify the basic hypotheses. The observed data confirmed most of the assumptions. The sense of family support was positively related to an adaptive strategy and, contrary to expectations, to a non-adaptive strategy. The family support experienced not only had a direct impact on intensifying adaptive and non-adaptive strategies but also influenced coping with the use of personal resources. The impact of family resources on resilience and the sense of coherence were similar, but the relationship of a sense of coherence was weaker than the relationship of resilience with an adaptive strategy. Resilience turned out to be the strongest predictor of an adaptive strategy. The relationship between resilience and a non-adaptive strategy was insignificant, but a sense of coherence worked in favour of planning, positively reinterpreting the situation and actively undertaking actions focused on the problem, and at the same time lowered the tendency to release emotions and self-blame.
Gypsum efflorescence on clay brick masonry: Analysis of potential efflorescence origins
Authors: Janssen Hans , Chwast Jacek , Elsen Jan
Published: December 2019

Gypsum efflorescence on clay brick masonry is a growing problem, leading to a persistent grey-white staining of masonry facades. Gypsum efflorescence has been reported in the United Kingdom, the Netherlands and Belgium, with a specific occurrence on masonry facades erected over the last few decades. This article investigates the origin of this recent occurrence of gypsum efflorescence, with accelerated testing of the gypsum efflorescence sensitivity of separate and combined masonry components. It is demonstrated that both brick and mortar may provide a gypsum source, respectively, via the dissolution of anhydrite and the carbonation of ettringite. Neither does however directly result in gypsum efflorescence, as the released gypsum commonly subfloresces below the brick surface. The efflorescence is instead triggered by mortar admixtures, the application of which has indeed risen strongly in recent decades. Avoiding gypsum efflorescence on clay brick masonry hence requires an inert alternative for the mortar admixtures.
Reliability analysis for electrical power systems based on importance measures
Authors: Liu Fangyu , Dui Hongyan , Li Ziyue
Published: December 2019

With the introduction of reliability engineering, electrical power system reliability has become an important basis for decision-making in the power industry. Two operation cases of electrical power systems are considered in this article. When the system is in an ordinary way, the influence between two system components will affect the importance measure of one component. When some component is in maintenance, preventive maintenance for working components and corrective maintenance for failed components can be executed simultaneously to enhance electrical power system performance. In view of the above two cases, two importance measures are proposed to effectively guide the preventive maintenance, aiming to improve the system performance within a limited budget. Reliability analysis procedure and methods applied toward the two importance measures are then developed and illustrated with the analysis on a Dual Element Spot Network system with double power supplies and double loads. Finally, a strategy for preventive maintenance is proposed by ranking the importance of these components.
Isolation of Antibiotic 3R,5R-Dihydroxyhexanoate Polymers From Endophytic Fungi
Authors: Morehouse Nicholas J. , Flewelling Andrew J. , Johnson John A. , Gray Christopher A.
Published: December 2019

The extracts of two isolates in our library of fungal endophytes, Annulohypoxylon multiforme (TC2-046) from the medicinal plant Juniperus communis and a sterile filamentous isolate (KP1-131DD) from the marine alga Scytosiphon lomentaria, displayed similar antimicrobial bioactivity profiles with notable high activity against Staphylococcus aureus. Bioassay-guided fractionation led to the isolation of poly(3 R,5 R-dihydroxyhexanoic acid) oligomers ranging from the trimer to the 29-mer that exhibited significant and selective inhibition of S. aureus and Mycobacterium tuberculosis H37Ra in vitro.
Effect of iron and silica nanoparticles’ size on in vitro human skin binding and penetration
Authors: Jung Eui , Hui Xiaoying , Zhu Hanjiang , Zhang Alissa , Wang Wei , Buchholz Bruce , Maibach Howard
Published: December 2019

This in vitro skin study determined absorption, diffusion, and binding rates of four [14C]-labeled nanoparticles (NPs): 12 nm Fe3O4, 32 nm Fe3O4@SiO2, 33 nm SiO2, and 78 nm SiO2 in each layer of human cadaver skin. In vitro microdialysis device and flow-through skin diffusion system were used to measure the binding affinity to the stratum corneum (SC) and permeability into/through skin layer of the four NPs with different physical–chemical properties, respectively, in short (30 min) and/or long (24 hours) exposures. Results show that NP size is an important factor affecting NP percutaneous absorption. The 12 nm Fe3O4 NPs reached the SC and viable epidermis; 32 nm Fe3O4@SiO2 core/shell NPs only reached SC. However, 33 nm and 78 nm silica NPs did not permeate SC. Similar patterns were observed for NP binding affinity to SC and dermatopharmacokinetic analysis using the tape stripping method. The binding affinity determination may be a useful method to efficiently screen skin penetration of NPs.
Solvent-Free Catalytic Oxidation of Benzyl Alcohol over Au-Pd Bimetal Deposited on TiO2: Comparison of Rutile, Brookite, and Anatase
Authors: Li Xiaoliang , Feng Jiangjiang , Sun Jia , Wang Zhe , Zhao Wei
Published: December 2019

TiO2 (P25)-supported Au-Pd bimetal nanoparticles displayed excellent performance in the solvent-free benzyl alcohol catalytic oxidation. However, little research attention has been paid to investigate the effects of TiO2 form on the catalytic activity of Au-Pd/TiO2. In the present research, rutile, brookite, and anatase TiO2 were successfully synthesized and subsequently applied as the carrier to load Au-Pd nanoparticles by the deposition-precipitation method. The experimental results indicated that the benzyl alcohol conversion employing the rutile TiO2-supported Au-Pd catalyst is higher than the conversion of anatase and brookite TiO2-loaded Au-Pd catalysts. However, the Au-Pd/TiO2-rutile displayed the lowest and highest selectivity toward benzaldehyde and toluene, respectively. ICP-AES, XRD, XPS, and TEM were conducted to characterize these catalysts. The corresponding experimental results revealed that the excellent performance of Au-Pd/TiO2-rutile catalyst was attributed to both the smaller Au-Pd nanoparticle size distribution and the higher concentrations of Oα and Pd2+ species on the catalyst surface. In the recycle experiments, the Au-Pd/TiO2-rutile catalyst displayed lower reaction stability compared with the Au-Pd/TiO2-anatase and Au-Pd/TiO2-brookite, which might be due to the coverage of larger amount of aldehyde products on the surface.
Current basis and future directions of zebrafish nutrigenomics
Authors: Williams Michael B. , Watts Stephen A.
Published: December 2019

This review investigates the current state of nutrigenomics in the zebrafish animal models. The zebrafish animal model has been used extensively in the study of disease onset and progression and associated molecular changes. In this review, we provide a synopsis of nutrigenomics using the zebrafish animal model. Obesity and dyslipidemia studies describe the genomics of dietary-induced obesity in relation to high-fat/high-calorie diets. Inflammation and cardiovascular studies describe dietary effects on the expression of acute inflammatory markers and resulting chronic inflammatory issues including atherosclerosis. We also evaluated the genomic response to bioactive dietary compounds associated with metabolic disorders. Carbohydrate metabolism and β-cell function studies describe the impacts of high-carbohydrate dietary challenges on nutritional programming. We also report tumorigenesis in relation to dietary carcinogen exposure studies that can result in permanent genomic changes. Vitamin and mineral deficiency studies demonstrate transgenerational genomic impacts of micronutrients in the diet and temporal expression changes. Circadian rhythm studies describe the relation between metabolism and natural temporal cycles of gene expression that impacts health. Bone formation studies describe the role of dietary composition that influences bone reabsorption regulation. Finally, this review provides future directions in the use of the zebrafish model for nutrigenomic and nutrigenetic research.
Manage with care: the frailty of self-connections in the European airport network
Authors: Cattaneo Mattia , Malighetti Paolo , Paleari Stefano , Redondi Renato
Published: December 2019

This study evaluates the attractiveness of self-hubbing in terms of the (a) symmetry of itineraries and the consequences for passengers in the case of missed flights. We compute the most attractive European origin-destination (O-D) pairs through self-connection and evaluate their robustness by estimating the expected delays relative to connecting times and the travel options available when a connection is missed.

Results show that the potential of self-connecting markets is reduced when accounting for asymmetrical travel options and the consequences for travelers in the case of missed flights. In terms of frequencies, self-connecting passengers are, on average, found to have fewer alternatives to complete a given O-D pair than in the case of alliance-based connections (− 33%). Our findings moderate the confidence of past evidence on self-hubbing in light of the concrete reliability of self-connections for passengers. The itinerary choice made by passengers inevitably depends on the evaluation of travel quality attributes related to the (a) symmetry of the itineraries and the costs incurred through missed connections.
ki67 nuclei detection and ki67-index estimation: a novel automatic approach based on human vision modeling
Authors: Barricelli Barbara Rita , Casiraghi Elena , Gliozzo Jessica , Huber Veronica , Leone Biagio Eugenio , Rizzi Alessandro , Vergani Barbara
Published: December 2019

Background

The protein ki67 (pki67) is a marker of tumor aggressiveness, and its expression has been proven to be useful in the prognostic and predictive evaluation of several types of tumors. To numerically quantify the pki67 presence in cancerous tissue areas, pathologists generally analyze histochemical images to count the number of tumor nuclei marked for pki67. This allows estimating the ki67-index, that is the percentage of tumor nuclei positive for pki67 over all the tumor nuclei. Given the high image resolution and dimensions, its estimation by expert clinicians is particularly laborious and time consuming. Though automatic cell counting techniques have been presented so far, the problem is still open.

Results

In this paper we present a novel automatic approach for the estimations of the ki67-index. The method starts by exploiting the STRESS algorithm to produce a color enhanced image where all pixels belonging to nuclei are easily identified by thresholding, and then separated into positive (i.e. pixels belonging to nuclei marked for pki67) and negative by a binary classification tree. Next, positive and negative nuclei pixels are processed separately by two multiscale procedures identifying isolated nuclei and separating adjoining nuclei. The multiscale procedures exploit two Bayesian classification trees to recognize positive and negative nuclei-shaped regions.

Conclusions

The evaluation of the computed results, both through experts’ visual assessments and through the comparison of the computed indexes with those of experts, proved that the prototype is promising, so that experts believe in its potential as a tool to be exploited in the clinical practice as a valid aid for clinicians estimating the ki67-index. The MATLAB source code is open source for research purposes.
Rearrangement analysis of multiple bacterial genomes
Authors: Noureen Mehwish , Tada Ipputa , Kawashima Takeshi , Arita Masanori
Published: December 2019

Background

Genomes are subjected to rearrangements that change the orientation and ordering of genes during evolution. The most common rearrangements that occur in uni-chromosomal genomes are inversions (or reversals) to adapt to the changing environment. Since genome rearrangements are rarer than point mutations, gene order with sequence data can facilitate more robust phylogenetic reconstruction. Helicobacter pylori is a good model because of its unique evolution in niche environment.

Results

We have developed a method to identify genome rearrangements by comparing almost-conserved genes among closely related strains. Orthologous gene clusters, rather than the gene sequences, are used to align the gene order so that comparison of large number of genomes becomes easier. Comparison of 72 Helicobacter pylori strains revealed shared as well as strain-specific reversals, some of which were found in different geographical locations.

Conclusion

Degree of genome rearrangements increases with time. Therefore, gene orders can be used to study the evolutionary relationship among species and strains. Multiple genome comparison helps to identify the strain-specific as well as shared reversals. Identification of the time course of rearrangements can provide insights into evolutionary events.
Identification of infectious disease-associated host genes using machine learning techniques
Authors: Barman Ranjan Kumar , Mukhopadhyay Anirban , Maulik Ujjwal , Das Santasabuj
Published: December 2019

Background

With the global spread of multidrug resistance in pathogenic microbes, infectious diseases emerge as a key public health concern of the recent time. Identification of host genes associated with infectious diseases will improve our understanding about the mechanisms behind their development and help to identify novel therapeutic targets.

Results

We developed a machine learning techniques-based classification approach to identify infectious disease-associated host genes by integrating sequence and protein interaction network features. Among different methods, Deep Neural Networks (DNN) model with 16 selected features for pseudo-amino acid composition (PAAC) and network properties achieved the highest accuracy of 86.33% with sensitivity of 85.61% and specificity of 86.57%. The DNN classifier also attained an accuracy of 83.33% on a blind dataset and a sensitivity of 83.1% on an independent dataset. Furthermore, to predict unknown infectious disease-associated host genes, we applied the proposed DNN model to all reviewed proteins from the database. Seventy-six out of 100 highly-predicted infectious disease-associated genes from our study were also found in experimentally-verified human-pathogen protein-protein interactions (PPIs). Finally, we validated the highly-predicted infectious disease-associated genes by disease and gene ontology enrichment analysis and found that many of them are shared by one or more of the other diseases, such as cancer, metabolic and immune related diseases.

Conclusions

To the best of our knowledge, this is the first computational method to identify infectious disease-associated host genes. The proposed method will help large-scale prediction of host genes associated with infectious-diseases. However, our results indicated that for small datasets, advanced DNN-based method does not offer significant advantage over the simpler supervised machine learning techniques, such as Support Vector Machine (SVM) or Random Forest (RF) for the prediction of infectious disease-associated host genes. Significant overlap of infectious disease with cancer and metabolic disease on disease and gene ontology enrichment analysis suggests that these diseases perturb the functions of the same cellular signaling pathways and may be treated by drugs that tend to reverse these perturbations. Moreover, identification of novel candidate genes associated with infectious diseases would help us to explain disease pathogenesis further and develop novel therapeutics.
Biomedical named entity recognition using deep neural networks with contextual information
Authors: Cho Hyejin , Lee Hyunju
Published: December 2019

Background

In biomedical text mining, named entity recognition (NER) is an important task used to extract information from biomedical articles. Previously proposed methods for NER are dictionary- or rule-based methods and machine learning approaches. However, these traditional approaches are heavily reliant on large-scale dictionaries, target-specific rules, or well-constructed corpora. These methods to NER have been superseded by the deep learning-based approach that is independent of hand-crafted features. However, although such methods of NER employ additional conditional random fields (CRF) to capture important correlations between neighboring labels, they often do not incorporate all the contextual information from text into the deep learning layers.

Results

We propose herein an NER system for biomedical entities by incorporating n-grams with bi-directional long short-term memory (BiLSTM) and CRF; this system is referred to as a contextual long short-term memory networks with CRF (CLSTM). We assess the CLSTM model on three corpora: the disease corpus of the National Center for Biotechnology Information (NCBI), the BioCreative II Gene Mention corpus (GM), and the BioCreative V Chemical Disease Relation corpus (CDR). Our framework was compared with several deep learning approaches, such as BiLSTM, BiLSTM with CRF, GRAM-CNN, and BERT. On the NCBI corpus, our model recorded an F-score of 85.68% for the NER of diseases, showing an improvement of 1.50% over previous methods. Moreover, although BERT used transfer learning by incorporating more than 2.5 billion words, our system showed similar performance with BERT with an F-scores of 81.44% for gene NER on the GM corpus and a outperformed F-score of 86.44% for the NER of chemicals and diseases on the CDR corpus. We conclude that our method significantly improves performance on biomedical NER tasks.

Conclusion

The proposed approach is robust in recognizing biological entities in text.
Population genetic structure and habitat connectivity for jaguar (Panthera onca) conservation in Central Belize
Authors: Menchaca Angelica , Rossi Natalia A. , Froidevaux Jeremy , Dias-Freedman Isabela , Caragiulo Anthony , Wultsch Claudia , Harmsen Bart , Foster Rebecca , de la Torre J. Antonio , Medellin Rodrigo A. , Rabinowitz Salisa , Amato George
Published: December 2019

Background

Connectivity among jaguar (Panthera onca) populations will ensure natural gene flow and the long-term survival of the species throughout its range. Jaguar conservation efforts have focused primarily on connecting suitable habitat in a broad-scale. Accelerated habitat reduction, human-wildlife conflict, limited funding, and the complexity of jaguar behaviour have proven challenging to maintain connectivity between populations effectively. Here, we used non-invasive genetic sampling and individual-based conservation genetic analyses to assess genetic diversity and levels of genetic connectivity between individuals in the Cockscomb Basin Wildlife Sanctuary and the Maya Forest Corridor. We used expert knowledge and scientific literature to develop models of landscape permeability based on circuit theory with fine-scale landscape features as ecosystem types, distance to human settlements and roads to predict the most probable jaguar movement across central Belize.

Results

We used 12 highly polymorphic microsatellite loci to identify 50 individual jaguars. We detected high levels of genetic diversity across loci (HE = 0.61, HO = 0.55, and NA = 9.33). Using Bayesian clustering and multivariate models to assess gene flow and genetic structure, we identified one single group of jaguars (K = 1). We identified critical areas for jaguar movement that fall outside the boundaries of current protected areas in central Belize. We detected two main areas of high landscape permeability in a stretch of approximately 18 km between Sittee River Forest Reserve and Manatee Forest Reserve that may increase functional connectivity and facilitate jaguar dispersal from and to Cockscomb Basin Wildlife Sanctuary. Our analysis provides important insights on fine-scale genetic and landscape connectivity of jaguars in central Belize, an area of conservation concern.

Conclusions

The results of our study demonstrate high levels of relatively recent gene flow for jaguars between two study sites in central Belize. Our landscape analysis detected corridors of expected jaguar movement between the Cockscomb Basin Wildlife Sanctuary and the Maya Forest Corridor. We highlight the importance of maintaining already established corridors and consolidating new areas that further promote jaguar movement across suitable habitat beyond the boundaries of currently protected areas. Continued conservation efforts within identified corridors will further maintain and increase genetic connectivity in central Belize.
Identification of self-interacting proteins by integrating random projection classifier and finite impulse response filter
Authors: Chen Zhan-Heng , You Zhu-Hong , Li Li-Ping , Wang Yan-Bin , Qiu Yu , Hu Peng-Wei
Published: December 2019

Background

Identification of protein-protein interactions (PPIs) is crucial for understanding biological processes and investigating the cellular functions of genes. Self-interacting proteins (SIPs) are those in which more than two identical proteins can interact with each other and they are the specific type of PPIs. More and more researchers draw attention to the SIPs detection, and several prediction model have been proposed, but there are still some problems. Hence, there is an urgent need to explore a efficient computational model for SIPs prediction.

Results

In this study, we developed an effective model to predict SIPs, called RP-FIRF, which merges the Random Projection (RP) classifier and Finite Impulse Response Filter (FIRF) together. More specifically, each protein sequence was firstly transformed into the Position Specific Scoring Matrix (PSSM) by exploiting Position Specific Iterated BLAST (PSI-BLAST). Then, to effectively extract the discriminary SIPs feature to improve the performance of SIPs prediction, a FIRF method was used on PSSM. The R’classifier was proposed to execute the classification and predict novel SIPs. We evaluated the performance of the proposed RP-FIRF model and compared it with the state-of-the-art support vector machine (SVM) on human and yeast datasets, respectively. The proposed model can achieve high average accuracies of 97.89 and 97.35% using five-fold cross-validation. To further evaluate the high performance of the proposed method, we also compared it with other six exiting methods, the experimental results demonstrated that the capacity of our model surpass that of the other previous approaches.

Conclusion

Experimental results show that self-interacting proteins are accurately well-predicted by the proposed model on human and yeast datasets, respectively. It fully show that the proposed model can predict the SIPs effectively and sufficiently. Thus, RP-FIRF model is an automatic decision support method which should provide useful insights into the recognition of SIPs.
A novel algorithm for alignment of multiple PPI networks based on simulated annealing
Authors: Hu Jialu , He Junhao , Li Jing , Gao Yiqun , Zheng Yan , Shang Xuequn
Published: December 2019

Proteins play essential roles in almost all life processes. The prediction of protein function is of significance for the understanding of molecular function and evolution. Network alignment provides a fast and effective framework to automatically identify functionally conserved proteins in a systematic way. However, due to the fast growing genomic data, interactions and annotation data, there is an increasing demand for more accurate and efficient tools to deal with multiple PPI networks. Here, we present a novel global alignment algorithm NetCoffee2 based on graph feature vectors to discover functionally conserved proteins and predict function for unknown proteins. To test the algorithm performance, NetCoffee2 and three other notable algorithms were applied on eight real biological datasets. Functional analyses were performed to evaluate the biological quality of these alignments. Results show that NetCoffee2 is superior to existing algorithms IsoRankN, NetCoffee and multiMAGNA++ in terms of both coverage and consistency. The binary and source code are freely available under the GNU GPL v3 license at https://github.com/screamer/NetCoffee2.
Genomic selection for non-key traits in radiata pine when the documented pedigree is corrected using DNA marker information
Authors: Li Yongjun , Klápště Jaroslav , Telfer Emily , Wilcox Phillip , Graham Natalie , Macdonald Lucy , Dungey Heidi S.
Published: December 2019

Background

Non-key traits (NKTs) in radiata pine (Pinus radiataD. Don) refer to traits other than growth, wood density and stiffness, but still of interest to breeders. Branch-cluster frequency, stem straightness, external resin bleeding and internal checking are examples of such traits and are targeted for improvement in radiata pine research programmes. Genomic selection can be conducted before the performance of selection candidates is available so that generation intervals can be reduced. Radiata pine is a species with a long generation interval, which if reduced could significantly increase genetic gain per unit of time. The aim of this study was to evaluate the accuracy and predictive ability of genomic selection and its efficiency over traditional forward selection in radiata pine for the following NKTs: branch-cluster frequency, stem straightness, internal checking, and external resin bleeding.

Results

Nine hundred and eighty-eight individuals were genotyped using exome capture genotyping by sequencing (GBS) and 67,168 single nucleotide polymorphisms (SNPs) used to develop genomic estimated breeding values (GEBVs) with genomic best linear unbiased prediction (GBLUP). The documented pedigree was corrected using a subset of 704 SNPs. The percentage of trio parentage confirmed was about 49% and about 50% of parents were re-assigned. The accuracy of GEBVs was 0.55–0.75 when using the documented pedigree and 0.61–0.80 when using the SNP-corrected pedigree. A higher percentage of additive genetic variance was explained and a higher predictive ability was observed when using the SNP-corrected pedigree than using the documented pedigree. With the documented pedigree, genomic selection was similar to traditional forward selection when assuming a generation interval of 17 years, but worse than traditional forward selection when assuming a generation interval of 14 years. After the pedigree was corrected, genomic selection led to 37–115% and 13–77% additional genetic gain over traditional forward selection when generation intervals of 17 years and 14 years were assumed, respectively.

Conclusion

It was concluded that genomic selection with a pedigree corrected by SNP information was an efficient way of improving non-key traits in radiata pine breeding.
Molecular cytogenetic characterization of wheat–Elymus repens chromosomal translocation lines with resistance to Fusarium head blight and stripe rust
Authors: Gong Biran , Zhu Wei , Li Sanyue , Wang Yuqi , Xu Lili , Wang Yi , Zeng Jian , Fan Xing , Sha Lina , Zhang Haiqin , Qi Pengfei , Huang Lin , Chen Guoyue , Zhou Yonghong , Kang Houyang
Published: December 2019

Background

Fusarium head blight (FHB) caused by the fungus Fusarium graminearum Schwabe and stripe rust caused by Puccinia striiformis f. sp. tritici are devastating diseases that affect wheat production worldwide. The use of disease-resistant genes and cultivars is the most effective means of reducing fungicide applications to combat these diseases. Elymus repens (2n = 6x = 42, StStStStHH) is a potentially useful germplasm of FHB and stripe rust resistance for wheat improvement.

Results

Here, we report the development and characterization of two wheat–E. repens lines derived from the progeny of common wheat–E. repens hybrids. Cytological studies indicated that the mean chromosome configuration of K15–1192-2 and K15–1194-2 at meiosis were 2n = 42 = 0.86 I + 17.46 II (ring) + 3.11 II (rod) and 2n = 42 = 2.45 I + 14.17 II (ring) + 5.50 II (rod) + 0.07 III, respectively. Genomic and fluorescence in situ hybridization karyotyping and simple sequence repeats markers revealed that K15–1192-2 was a wheat–E. repens 3D/?St double terminal chromosomal translocation line. Line K15–1194-2 was identified as harboring a pair of 7DS/?StL Robertsonian translocations and one 3D/?St double terminal translocational chromosome. Further analyses using specific expressed sequence tag-SSR markers confirmed that the wheat–E. repens translocations involved the 3St chromatin in both lines. Furthermore, compared with the wheat parent Chuannong16, K15–1192-2 and K15–1194-2 expressed high levels of resistance to FHB and stripe rust pathogens prevalent in China.

Conclusions

Thus, this study has determined that the chromosome 3St of E. repens harbors gene(s) highly resistant to FHB and stripe rust, and chromatin of 3St introgressed into wheat chromosomes completely presented the resistance, indicating the feasibility of using these translocation lines as novel material for breeding resistant wheat cultivars and alien gene mining.
Characterization of a vacuolar sucrose transporter, HbSUT5, from Hevea brasiliensis: involvement in latex production through regulation of intracellular sucrose transport in the bark and laticifers
Authors: Long Xiangyu , Li Heping , Yang Jianghua , Xin Lusheng , Fang Yongjun , He Bin , Huang Debao , Tang Chaorong
Published: December 2019

Background

Sucrose (Suc), as the precursor molecule for rubber biosynthesis inHevea brasiliensis, is transported via phloem-mediated long-distance transport from leaves to laticifers in trunk bark, where latex (cytoplasm of laticifers) is tapped for rubber. In our previous report, six Suc transporter (SUT) genes have been cloned in Hevea tree, among whichHbSUT3is verified to play an active role in Suc loading to the laticifers. In this study, another latex-abundant SUT isoform,HbSUT5, with expressions only inferior toHbSUT3was characterized especially for its roles in latex production.

Results

Both phylogenetic analysis and subcellular localization identify HbSUT5 as a tonoplast-localized SUT protein under the SUT4-clade (=type III). Suc uptake assay in baker’s yeast reveals HbSUT5 to be a typical Suc-H+symporter, but its high affinity for Suc (Km = 2.03 mM at pH 5.5) and the similar efficiency in transporting both Suc and maltose making it a peculiar SUT under the SUT4-clade. At the transcript level, HbSUT5 is abundantly and preferentially expressed in Hevea barks. The transcripts ofHbSUT5are conspicuously decreased both in Hevea latex and bark by two yield-stimulating treatments of tapping and ethephon, the patterns of which are contrary to HbSUT3. Under the ethephon treatment, the Suc level in latex cytosol decreases significantly, but that in latex lutoids (polydispersed vacuoles) changes little, suggesting a role of the decreasedHbSUT5expression in Suc compartmentalization in the lutoids and thus enhancing the Suc sink strength in laticifers.

Conclusions

Our findings provide insights into the roles of a vacuolar sucrose transporter, HbSUT5, in Suc exchange between lutoids and cytosol in rubber-producing laticifers.
A case report of a 40-year-old woman with endomyocardial fibrosis in a non-tropical area: from initial presentation to high urgent heart transplantation
Authors: Wagner Gernot , Haumer Markus , Poelzl Gerhard , Wiedemann Dominik , Kliegel Andreas , Ullrich Robert , Gartlehner Gerald , Zuckermann Andreas , Müller Ludwig , Mayr Harald , Moertl Deddo
Published: December 2019

Background

Endomyocardial fibrosis (EMF) represents the most common cause of restrictive cardiomyopathy worldwide. Despite a high prevalence in tropical regions, it occasionally occurs in patients who have never visited these areas. While researches have proposed various possible triggers for EMF, etiology and pathogenesis remain largely unknown. Diagnosis is based on patient history, heart failure symptoms, and echocardiographic signs of restrictive ventricular filling, atrioventricular valve regurgitation and frequently apical thrombus. Following is a case report of an Austrian patient with EMF who eventually had to undergo a heart transplant. This case report strives to promote awareness for this in non-tropical areas uncommon but nevertheless detrimental disease.

Case presentation

A 40-year-old woman was presented at our emergency department with chest pain and fever up to 38.1° Celsius. Plasma troponin-T levels and inflammatory markers were slightly elevated, but the echocardiogram was without pathological findings. The patient was hospitalized on the suspicion of acute myocarditis and discharged soon after improvement. Eight months later, she was presented again with chest pain and symptoms of heart failure. The echocardiogram showed normal systolic left ventricular (LV) function with LV wall thickening and severe restrictive mitral regurgitation as well as aortic and tricuspid regurgitation. Coronary angiogram was normal but right heart catheterization showed pulmonary hypertension due to left heart disease. Further diagnostic workup with cardiac magnetic resonance imaging revealed subendocardial late enhancement and apical thrombus formation in the left ventricle compatible with the diagnosis of EMF. A comprehensive diagnostic workup showed no evidence of infection, systemic immunologic or hematological disease, in particular hypereosinophilic syndrome. After a multidisciplinary consideration of several therapeutic options, the patient was listed for heart transplantation. On the waiting list, she deteriorated rapidly due to progressive heart failure and finally underwent a heart transplantation. Histological examination confirmed the diagnosis of EMF. Six years after her heart transplantation, the patient was presented in an excellent clinical condition.

Conclusions

Even in non-tropical regions, the diagnosis of EMF should always be considered in restrictive cardiomyopathy. Knowledge of the distinct phenotype of EMF facilitates diagnosis, but comprehensive workup and therapeutic management remain challenging and require a multidisciplinary approach.
Enterococcal periprosthetic joint infection: clinical and microbiological findings from an 8-year retrospective cohort study
Authors: Renz Nora , Trebse Rihard , Akgün Doruk , Perka Carsten , Trampuz Andrej
Published: December 2019

Background

Treatment of enterococcal periprosthetic joint infections (PJI) is challenging due to non-standardized management strategies and lack of biofilm-active antibiotics. The optimal surgical and antimicrobial therapy are unknown. Therefore, we evaluated characteristics and outcome of enterococcal PJI.

Methods

Consecutive patients with enterococcal PJI from two specialized orthopedic institutions were retrospectively analyzed. Both institutions are following the same diagnostic and treatment concepts. The probability of relapse-free survival was estimated using Kaplan-Meier survival curves and compared by log-rank test. Treatment success was defined by absence of relapse or persistence of PJI due to enterococci or death related to enterococcal PJI. Clinical success was defined by the infection-free status, no subsequent surgical intervention for persistent or perioperative infection after re-implantation and no PJI-related death within 3 months.

Results

Included were 75 enterococcal PJI episodes, involving 41 hip, 30 knee, 2 elbow and 2 shoulder prostheses. PJI occurred postoperatively in 61 episodes (81%), hematogenously in 13 (17%) and by contiguous spread in one. E. faecalis grew in 64 episodes, E. faecium in 10 and E. casseliflavus in one episode(s). Additional microorganism(s) were isolated in 38 patients (51%). Enterococci were susceptible to vancomycin in 73 of 75 isolates (97%), to daptomycin in all 75 isolates, and to fosfomycin in 21 of 22 isolates (96%). The outcome data was available for 66 patients (88%). The treatment success after 3 years was 83.7% (95% confidence interval [CI]; 76.1–96.7%) and the clinical success was 67.5% (95% CI; 57.3–80.8%). In 11 patients (17%), a new PJI episode caused by a different pathogen occurred. All failures occurred within 3 years after surgery.

Conclusion

About half of enterococcal PJI were polymicrobial infections. The treatment success was high (84%). All treatment failures occurred within the first 3 years after revision surgery. Interestingly, 17% of patients experienced a new PJI caused by another pathogen at a later stage.

Trial registration

The study was retrospectively registered with the public clinical trial identification NCT0253022 at https://www.clinicaltrials.gov on 15 July 2015.
Child maltreatment, peer victimization, and social anxiety in adulthood: a cross-sectional study in a treatment-seeking sample
Authors: Brühl Antonia , Kley Hanna , Grocholewski Anja , Neuner Frank , Heinrichs Nina
Published: December 2019

Background

Childhood adversities, especially emotional abuse, emotional neglect, and peer victimization are considered to be crucial risk factors for social anxiety disorder (SAD). We investigated whether particular forms of retrospectively recalled childhood adversities are specifically associated with SAD in adulthood or whether we find similar links in other anxiety or depressive disorders.

Methods

Prevalences of adversities assessed with the Childhood Trauma Questionnaire (CTQ) and a questionnaire of stressful social experiences (FBS) were determined in N = 1091 outpatients. Adversity severities among patients with SAD only (n = 25), specific phobia only (n = 18), and generalized anxiety disorder only (n = 19) were compared. Differences between patients with anxiety disorders only (n = 62) and depressive disorders only (n = 239) as well as between SAD with comorbid depressive disorders (n = 143) and SAD only were tested.

Results

None of the adversity types were found to be specifically associated with SAD and severities did not differ among anxiety disorders but patients with depressive disorders reported more severe emotional abuse, physical abuse, and sexual abuse than patients with anxiety disorders. SAD patients with a comorbid depressive disorder also reported more severe adversities across all types compared to SAD only.

Conclusion

Findings indicate that particular forms of recalled childhood adversities are not specifically associated with SAD in adulthood. Previously established links with SAD may be better explained by comorbid depressive symptoms.
Education level and risk of postpartum depression: results from the Japan Environment and Children’s Study (JECS)
Authors:   the Japan Environment and Children’s Study (JECS) Group, Matsumura Kenta , Hamazaki Kei , Tsuchida Akiko , Kasamatsu Haruka , Inadera Hidekuni
Published: December 2019

Background

Lower socioeconomic status is often thought to be associated with an elevated risk of postpartum depression; however, this relationship exhibits noticeable heterogeneity between studies. The present study examined this relationship in Japan.

Methods

Data were obtained from 90,194 mothers in an ongoing birth cohort of the Japan Environment and Children’s Study. Socioeconomic status was assessed based on the mothers’ highest education level during pregnancy. Postpartum depression was identified at 1 and 6 months postpartum based on an Edinburgh Postnatal Depression Scale score of ≥9, and analyses were also performed based on the sub-scores for anxiety, depression, and anhedonia symptoms. Logistic and generalized linear regression model analyses were used to calculate odds ratios for postpartum depression according to education level with the highest education group (≥16 years of education) defined as the reference group, while controlling for covariates in a stepwise fashion.

Results

Univariate analysis revealed that a lower education level was associated with a higher prevalence of postpartum depression and related symptoms. Although these relationships weakened in the fully adjusted models, odds ratios for cases and related symptoms remained significant at 1 and 6 months postpartum. Among three symptom dimensions, the relationship was strongest and weakest in the depressive and anxiety symptoms, respectively.

Conclusions

A lower education level was an independent risk factor for postpartum depression. In view of the low mobility of the education level, this finding suggests the potential importance of collecting information regarding education levels at the earliest opportunity.
Comparing sensitivity to change using the 6-item versus the 17-item Hamilton depression rating scale in the GUIDED randomized controlled trial
Authors: Dunlop Boadie W. , Parikh Sagar V. , Rothschild Anthony J. , Thase Michael E. , DeBattista Charles , Conway Charles R. , Forester Brent P. , Mondimore Francis M. , Shelton Richard C. , Macaluso Matthew , Logan Jennifer , Traxler Paul , Li James , Johnson Holly , Greden John F.
Published: December 2019

Background

Previous research suggests that the 17-item Hamilton Depression Rating Scale (HAM-D17) is less sensitive in detecting differences between active treatment and placebo for major depressive disorder (MDD) than is the HAM-D6 scale, which focuses on six core depression symptoms. Whether HAM-D6 shows greater sensitivity when comparing two active MDD treatment arms is unknown.

Methods

This post hoc analysis used data from the intent-to-treat (ITT) cohort (N = 1541) of the Genomics Used to Improve DEpression Decisions (GUIDED) trial, a rater- and patient-blinded randomized controlled trial. GUIDED compared combinatorial pharmacogenomics-guided care with treatment as usual (TAU) in patients with MDD. Percent of symptom improvement, response rate and remission rate from baseline to week 8 were evaluated using both scales. Analyses were performed for the full cohort and for the subset of patients who at baseline were taking medications predicted by the test to have moderate or significant gene-drug interactions. A Mokken scale analysis was conducted to compare the homogeneity of HAM-D17 with that of HAM-D6.

Results

At week 8, the guided-care arm demonstrated statistically significant benefit over TAU when the HAM-D6 (∆ = 4.4%, p = 0.023) was used as the continuous measure of symptom improvement, but not when using the HAM-D17 (∆ = 3.2%, p = 0.069). Response rates increased significantly for guided-care compared with TAU when evaluated using both HAM-D6 (∆ = 7.0%, p = 0.004) and HAM-D17 (∆ = 6.3%, p = 0.007). Remission rates also were significantly greater for guided-care versus TAU using both measures (HAM-D6 ∆ = 4.6%, p = 0.031; HAM-D17 ∆ = 5.5%, p = 0.005). Patients in the guided-care arm who at baseline were taking medications predicted to have gene-drug interactions showed further increased benefit over TAU at week 8 for symptom improvement (∆ = 7.3%, p = 0.004) response (∆ = 10.0%, p = 0.001) and remission (∆ = 7.9%, p = 0.005) using HAM-D6. All outcomes showed continued improvement through week 24. Mokken scale analysis demonstrated the homogeneity and unidimensionality of HAM-D6, but not of HAM-D17, across treatment arms.

Conclusions

The HAM-D6 scale identified a statistically significant difference in symptom improvement between combinatorial pharmacogenomics-guided care and TAU, whereas the HAM-D17 did not. The demonstrated utility of pharmacogenomics-guided treatment over TAU as detected by the HAM-D6 highlights its value for future biomarker-guided trials comparing active treatment arms.

Trial registration

Clinicaltrials.gov: NCT02109939. Registered 10 April 2014.