Takshan/R1 huggingface dataset:
Comparison of three assembly strategies for a heterozygous seedless grapevine genome assembly.

BACKGROUND: De novo heterozygous assembly is an ongoing challenge requiring improved assembly approaches. In this study, three strategies were used to develop de novo Vitis vinifera 'Sultanina' genome assemblies for comparison with the inbred V. vinifera (PN40024 12X.v2) reference genome and a published Sultanina ALLPATHS-LG assembly (AP). The strategies were: 1) a default PLATANUS assembly (PLAT_d) for direct comparison with AP assembly, 2) an iterative merging strategy using METASSEMBLER to combine PLAT_d and AP assemblies (MERGE) and 3) PLATANUS parameter modifications plus GapCloser (PLAT*_GC). RESULTS: The three new assemblies were greater in size than the AP assembly. PLAT*_GC had the greatest number of scaffolds aligning with a minimum of 95% identity and ≥1000 bp alignment length to V. vinifera (PN40024 12X.v2) reference genome. SNP analysis also identified additional high quality SNPs. A greater number of sequence reads mapped back with zero-mismatch to the PLAT_d, MERGE, and PLAT*_GC (>94%) than was found in the AP assembly (87%) indicating a greater fidelity to the original sequence data in the new assemblies than in AP assembly. A de novo gene prediction conducted using seedless RNA-seq data predicted > 30,000 coding sequences for the three new de novo assemblies, with the greatest number (30,544) in PLAT*_GC and only 26,515 for the AP assembly. Transcription factor analysis indicated good family coverage, but some genes found in the VCOST.v3 annotation were not identified in any of the de novo assemblies, particularly some from  the MYB and ERF families. CONCLUSIONS: The PLAT_d and PLAT*_GC had a greater number of synteny blocks with the V. vinifera (PN40024 12X.v2) reference genome than AP or MERGE. PLAT*_GC provided the most contiguous assembly with only 1.2% scaffold N, in contrast to AP (10.7% N), PLAT_d (6.6% N) and Merge (6.4% N). A PLAT*_GC pseudo-chromosome assembly with chromosome alignment to the reference genome V. vinifera, (PN40024 12X.v2) provides new information for use in seedless grape genetic mapping studies. An annotated de novo gene prediction for the PLAT*_GC assembly, aligned with VitisNet pathways provides new seedless grapevine specific transcriptomic resource that has excellent fidelity with the seedless short read sequence data.
Functional genomics of acclimation and adaptation in response to thermal stress in Daphnia.

BACKGROUND: Gene expression regulation is one of the fundamental mechanisms of phenotypic plasticity and is expected to respond to selection in conditions favoring phenotypic response. The observation that many organisms increase their stress tolerance after acclimation to moderate levels of stress is an example of plasticity which has been long hypothesized to be based on adaptive changes in gene expression. We report genome-wide patterns of gene expression in two heat-tolerant and two heat-sensitive parthenogenetic clones of the zooplankton crustacean Daphnia pulex exposed for three generations to either optimal (18°C) or substressful (28°C) temperature. RESULTS: A large number of genes responded to temperature and many demonstrated a significant genotype-by-environment (GxE) interaction. Among genes with a significant GxE there were approximately equally frequent instances of canalization, i.e. stronger plasticity in heat-sensitive than in heat-tolerant clones, and of enhancement of plasticity along the evolutionary vector toward heat tolerance. The strongest response observed is the across-the-board down-regulation of a variety of genes occurring in heat-tolerant, but not in heat-sensitive clones. This response is particularly obvious among genes involved in core metabolic pathways and those responsible for transcription, translation and DNA repair. CONCLUSIONS: The observed down-regulation of metabolism, consistent with previous findings in yeast and Drosophila, may reflect a general compensatory stress response. The associated down-regulation of DNA repair pathways potentially creates a trade-off between short-term benefits of survival at high temperature and long-term costs of accelerated mutation accumulation.
In vitro activity of ivermectin against Staphylococcus aureus clinical isolates.

Background: Ivermectin is an endectocide against many parasites. Though being a macrocyclic lactone, its activity against bacteria has been less known, possibly due to the fact that micromolar concentrations at tissue levels are required to achieve a therapeutic effect. Among pathogenic bacteria of major medical significance, Staphylococcus aureus cause a number of diseases in a wide variety of hosts including humans and animals. It has been attributed as one of the most pathogenic organisms. The emergence of methicillin resistance has made the treatment of S. aureus even more difficult as it is now resistant to most of the available antibiotics. Thus, search for alternate anti-staphylococcal agents requires immediate attention. Methods: Twenty-one clinical isolates of S. aureus were isolated from bovine milk collected from Lahore and Faisalabad Pakistan. Different anthelmintics including levamisole, albendazole and ivermectin were tested against S. aureus to determine their minimum inhibitory concentrations. This was followed-up by growth curve analysis, spot assay and time-kill kinetics. Results: The results showed that ivermectin but not levamisole or albendazole exhibited a potent anti-staphylococcal activity at the concentrations of 6.25 and 12.5 μg/ml against two isolates. Interestingly, one of the isolate was sensitive while the other was resistant to methicillin/cefoxitin. Conclusions: Our novel findings indicate that ivermectin has an anti-bacterial effect against certain S. aureus isolates. However, to comprehend why ivermectin did not inhibit the growth of all Staphylococci needs further investigation. Nevertheless, we have extended the broad range of known pharmacological effects of ivermectin. As pharmacology and toxicology of ivermectin are well known, its further development as an anti-staphylococcal agent is potentially appealing.
GlycoBase and autoGU: tools for HPLC-based glycan analysis.

SUMMARY: The development of robust high-performance liquid chromatography (HPLC) technologies continues to improve the detailed analysis and sequencing of glycan structures released from glycoproteins. Here, we present a database (GlycoBase) and analytical tool (autoGU) to assist the interpretation and assignment of HPLC-glycan profiles. GlycoBase is a relational database which contains the HPLC elution positions for over 350 2-AB labelled N-glycan structures together with predicted products of exoglycosidase digestions. AutoGU assigns provisional structures to each integrated HPLC peak and, when used in combination with exoglycosidase digestions, progressively assigns each structure automatically based on the footprint data. These tools are potentially very promising and facilitate basic research as well as the quantitative high-throughput analysis of low concentrations of glycans released from glycoproteins. AVAILABILITY: http://glycobase.ucd.ie
Association of cardiovascular system medications with cognitive function and dementia in older adults living in nursing homes in Australia.

OBJECTIVE: To examine associations between cardiovascular system medication use with cognition function and diagnosis of dementia in older adults living in nursing homes in Australia. METHODS: As part of a cross-sectional study of 17 Australian nursing homes examining quality of life and resource use, we examined the association between cognitive impairment and cardiovascular medication use (identified using the Anatomical Therapeutic Classification System) using general linear regression and logistic regression models. People who were receiving end of life care were excluded. RESULTS: Participants included 541 residents with a mean age of 85.5 years (± 8.5), a mean Psychogeriatric Assessment Scale-Cognitive Impairment (PAS-Cog) score of 13.3 (± 7.7), a prevalence of cardiovascular diseases of 44% and of hypertension of 47%. Sixty-four percent of participants had been diagnosed with dementia and 72% had received cardiovascular system medications within the previous 12 months. Regression models demonstrated the use of cardiovascular medications was associated with lower (better) PAS-Cog scores [Coefficient (β) = -3.7; 95% CI: -5.2 to -2.2; P < 0.0001] and a lower probability of a dementia diagnosis (OR = 0.44; 95% CI: 0.26 to 0.75, P = 0.0022). Analysis by subgroups of medications showed cardiac therapy medications (C01), beta blocking agents (C07), and renin-angiotensin system agents (C09) were associated with lower PAS-Cog scores (better cognition) and lower dementia diagnosis probability. CONCLUSIONS: This analysis has demonstrated an association between greater cardiovascular system medication use and better cognitive status among older adults living in nursing homes. In this population, there may be differential access to health care and treatment of cardiovascular risk factors. This association warrants further investigation in large cohort studies.
A mathematical model describing the mechanical kinetics of kinesin stepping.

MOTIVATION: Kinesin is a smart motor protein that steps processively forward and backward along microtubules (MTs). The mechanical kinetics of kinesin affecting its stepping behavior is not fully understood. Here, we propose a mathematical model to study the mechanical kinetics of forward and backward stepping of kinesin motor based on the four-state discrete stochastic model of the motor. RESULTS: Results show that the probabilities of forward and backward stepping can be modeled using the mean probabilities of forward and backward kinetic transitions, respectively. We show that the backward stepping of kinesin motor starts when the probability of adenosine diphosphate (ADP) binding to the motor is much higher than that of adenosine triphosphate (ATP) binding. Furthermore, our results indicate that the backward stepping is related to both ATP hydrolysis and synthesis with rate limiting factor being ATP synthesis. Low rate of ATP synthesis under high backward loads above 10 pN is also suggested as a reason for the detachment of kinesin motor from MT in the kinetic state MTċKinesinċADPċPi. AVAILABILITY AND IMPLEMENTATION: The code for this work is written in Visual C# and is available by request from the authors.
Characterization of the late embryogenesis abundant (LEA) proteins family and their role in drought stress tolerance in upland cotton.

BACKGROUND: Late embryogenesis abundant (LEA) proteins are large groups of hydrophilic proteins with major role in drought and other abiotic stresses tolerance in plants. In-depth study and characterization of LEA protein families have been carried out in other plants, but not in upland cotton. The main aim of this research work was to characterize the late embryogenesis abundant (LEA) protein families and to carry out gene expression analysis to determine their potential role in drought stress tolerance in upland cotton. Increased cotton production in the face of declining precipitation and availability of fresh water for agriculture use is the focus for breeders, cotton being the backbone of textile industries and a cash crop for many countries globally. RESULTS: In this work, a total of 242, 136 and 142 LEA genes were identified in G. hirsutum, G. arboreum and G. raimondii respectively. The identified genes were classified into eight groups based on their conserved domain and phylogenetic tree analysis. LEA 2 were the most abundant, this could be attributed to their hydrophobic character. Upland cotton LEA genes have fewer introns and are distributed in all chromosomes. Majority of the duplicated LEA genes were segmental. Syntenic analysis showed that greater percentages of LEA genes are conserved. Segmental gene duplication played a key role in the expansion of LEA genes. Sixty three miRNAs were found to target 89 genes, such as miR164, ghr-miR394 among others. Gene ontology analysis revealed that LEA genes are involved in desiccation and defense responses. Almost all the LEA genes in their promoters contained ABRE, MBS, W-Box and TAC-elements, functionally known to be involved in drought stress and other stress responses. Majority of the LEA genes were involved in secretory pathways. Expression profile analysis indicated that most of the LEA genes were highly expressed in drought tolerant cultivars Gossypium tomentosum as opposed to drought susceptible, G. hirsutum. The tolerant genotypes have a greater ability to modulate genes under drought stress than the more susceptible upland cotton cultivars. CONCLUSION: The finding provides comprehensive information on LEA genes in upland cotton, G. hirsutum and possible function in plants under drought stress.
Benchmarking of de novo assembly algorithms for Nanopore data reveals optimal performance of OLC approaches.

BACKGROUND: Improved DNA sequencing methods have transformed the field of genomics over the last decade. This has become possible due to the development of inexpensive short read sequencing technologies which have now resulted in three generations of sequencing platforms. More recently, a new fourth generation of Nanopore based single molecule sequencing technology, was developed based on MinION(®) sequencer which is portable, inexpensive and fast. It is capable of generating reads of length greater than 100 kb. Though it has many specific advantages, the two major limitations of the MinION reads are high error rates and the need for the development of downstream pipelines. The algorithms for error correction have already emerged, while development of pipelines is still at nascent stage. RESULTS: In this study, we benchmarked available assembler algorithms to find an appropriate framework that can efficiently assemble Nanopore sequenced reads. To address this, we employed genome-scale Nanopore sequenced datasets available for E. coli and yeast genomes respectively. In order to comprehensively evaluate multiple algorithmic frameworks, we included assemblers based on de Bruijn graphs (Velvet and ABySS), Overlap Layout Consensus (OLC) (Celera) and Greedy extension (SSAKE) approaches. We analyzed the quality, accuracy of the assemblies as well as the computational performance of each of the assemblers included in our benchmark. Our analysis unveiled that OLC-based algorithm, Celera, could generate a high quality assembly with ten times higher N50 & mean contig values as well as one-fifth the number of total number of contigs compared to other tools. Celera was also found to exhibit an average genome coverage of 12 % in E. coli dataset and 70 % in Yeast dataset as well as relatively lesser run times. In contrast, de Bruijn graph based assemblers Velvet and ABySS generated the assemblies of moderate quality, in less time when there is no limitation on the memory allocation, while greedy extension based algorithm SSAKE generated an assembly of very poor quality but with genome coverage of 90 % on yeast dataset. CONCLUSION: OLC can be considered as a favorable algorithmic framework for the development of assembler tools for Nanopore-based data, followed by de Bruijn based algorithms as they consume relatively less or similar run times as OLC-based algorithms for generating assembly, irrespective of the memory allocated for the task. However, few improvements must be made to the existing de Bruijn implementations in order to generate an assembly with reasonable quality. Our findings should help in stimulating the development of novel assemblers for handling Nanopore sequence data.
Influence of inter-observer delineation variability on radiomics stability in different tumor sites.

BACKGROUND: Radiomics is a promising methodology for quantitative analysis and description of radiological images using advanced mathematics and statistics. Tumor delineation, which is still often done manually, is an essential step in radiomics, however, inter-observer variability is a well-known uncertainty in radiation oncology. This study investigated the impact of inter-observer variability (IOV) in manual tumor delineation on the reliability of radiomic features (RF). METHODS: Three different tumor types (head and neck squamous cell carcinoma (HNSCC), malignant pleural mesothelioma (MPM) and non-small cell lung cancer (NSCLC)) were included. For each site, eleven individual tumors were contoured on CT scans by three experienced radiation oncologists. Dice coefficients (DC) were calculated for quantification of delineation variability. RF were calculated with an in-house developed software implementation, which comprises 1404 features: shape (n = 18), histogram (n = 17), texture (n = 137) and wavelet (n = 1232). The IOV of RF was studied using the intraclass correlation coefficient (ICC). An ICC >0.8 indicates a good reproducibility. For the stable RF, an average linkage hierarchical clustering was performed to identify classes of uncorrelated features. RESULTS: Median DC was high for NSCLC (0.86, range 0.57-0.90) and HNSCC (0.72, 0.21-0.89), whereas it was low for MPM (0.26, 0-0.9) indicating substantial IOV. Stability rate of RF correlated with DC and depended on tumor site, showing a high stability in NSCLC (90% of total parameters), acceptable stability in HNSCC (59% of total parameters) and low stability in MPM (36% of total parameters). Shape features showed the weakest stability across all tumor types. Hierarchical clustering revealed 14 groups of correlated and stable features for NSCLC and 6 groups for both HNSCC and MPM. CONCLUSION: Inter-observer delineation variability has a relevant influence on radiomics analysis and is strongly influenced by tumor type. This leads to a reduced number of suitable imaging features.
Multicellular tumor spheroid models to explore cell cycle checkpoints in 3D.

BACKGROUND: MultiCellular Tumor Spheroid (MCTS) mimics the organization of a tumor and is considered as an invaluable model to study cancer cell biology and to evaluate new antiproliferative drugs. Here we report how the characteristics of MCTS in association with new technological developments can be used to explore the regionalization and the activation of cell cycle checkpoints in 3D. METHODS: Cell cycle and proliferation parameters were investigated in Capan-2 spheroids by immunofluorescence staining, EdU incorporation and using cells engineered to express Fucci-red and -green reporters. RESULTS: We describe in details the changes in proliferation and cell cycle parameters during spheroid growth and regionalization. We report the kinetics and regionalized aspects of cell cycle arrest in response to checkpoint activation induced by EGF starvation, lovastatin treatment and etoposide-induced DNA damage. CONCLUSION: Our data present the power and the limitation of spheroids made of genetically modified cells to explore cell cycle checkpoints. This study paves the way for the investigation of molecular aspects and dynamic studies of the response to novel antiproliferative agents in 3D models.
Management of multidrug-resistant Pseudomonas aeruginosa in the intensive care unit: state of the art.

INTRODUCTION: Pseudomonas aeruginosa (PA) is one of the most important causes of healthcare-related infections among Gram-negative bacteria. The best therapeutic approach is controversial, especially for multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains as well as in the setting of most severe patients, such as in the intensive care unit (ICU). Areas covered: This article addresses several points. First, the main microbiological aspects of PA, focusing on its wide array of resistance mechanisms. Second, risk factors and the worse outcome linked to MDR-PA infection. Third, the pharmacological peculiarity of ICU patients, that makes the choice of a proper antimicrobial therapy difficult. Eventually, the current therapeutic options against MDR-PA are reviewed, taking into account the main variables that drive antimicrobial optimization in critically ill patients. Literature search was carried out using Pubmed and Web of Science. Expert commentary: Methodologically rigorous studies are urgently needed to clarify crucial aspects of the treatment against MDR-PA, namely monotherapy versus combination therapy in empiric and targeted settings. In the meanwhile, useful options are represented by newly approved drugs, such as ceftolozane/tazobactam and ceftazidime/avibactam. In critically ill patients, at least as empirical approach, a combination therapy is a prudent choice when a MDR-PA strain is suspected.
Efficient network-guided multi-locus association mapping with graph cuts.

MOTIVATION: As an increasing number of genome-wide association studies reveal the limitations of the attempt to explain phenotypic heritability by single genetic loci, there is a recent focus on associating complex phenotypes with sets of genetic loci. Although several methods for multi-locus mapping have been proposed, it is often unclear how to relate the detected loci to the growing knowledge about gene pathways and networks. The few methods that take biological pathways or networks into account are either restricted to investigating a limited number of predetermined sets of loci or do not scale to genome-wide settings. RESULTS: We present SConES, a new efficient method to discover sets of genetic loci that are maximally associated with a phenotype while being connected in an underlying network. Our approach is based on a minimum cut reformulation of the problem of selecting features under sparsity and connectivity constraints, which can be solved exactly and rapidly. SConES outperforms state-of-the-art competitors in terms of runtime, scales to hundreds of thousands of genetic loci and exhibits higher power in detecting causal SNPs in simulation studies than other methods. On flowering time phenotypes and genotypes from Arabidopsis thaliana, SConES detects loci that enable accurate phenotype prediction and that are supported by the literature. AVAILABILITY: Code is available at http://webdav.tuebingen.mpg.de/u/karsten/Forschung/scones/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Computational prediction of host-pathogen protein-protein interactions.

MOTIVATION: Infectious diseases such as malaria result in millions of deaths each year. An important aspect of any host-pathogen system is the mechanism by which a pathogen can infect its host. One method of infection is via protein-protein interactions (PPIs) where pathogen proteins target host proteins. Developing computational methods that identify which PPIs enable a pathogen to infect a host has great implications in identifying potential targets for therapeutics. RESULTS: We present a method that integrates known intra-species PPIs with protein-domain profiles to predict PPIs between host and pathogen proteins. Given a set of intra-species PPIs, we identify the functional domains in each of the interacting proteins. For every pair of functional domains, we use Bayesian statistics to assess the probability that two proteins with that pair of domains will interact. We apply our method to the Homo sapiens-Plasmodium falciparum host-pathogen system. Our system predicts 516 PPIs between proteins from these two organisms. We show that pairs of human proteins we predict to interact with the same Plasmodium protein are close to each other in the human PPI network and that Plasmodium pairs predicted to interact with same human protein are co-expressed in DNA microarray datasets measured during various stages of the Plasmodium life cycle. Finally, we identify functionally enriched sub-networks spanned by the predicted interactions and discuss the plausibility of our predictions. AVAILABILITY: Supplementary data are available at http://staff.vbi.vt.edu/dyermd/publications/dyer2007a.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.