Takshan/R1 huggingface dataset:
An Overexpressed Q Allele Leads to Increased Spike Density and Improved Processing Quality in Common Wheat (Triticum aestivum).

Spike density and processing quality are important traits in modern wheat production and are controlled by multiple gene loci. The associated genes have been intensively studied and new discoveries have been constantly reported during the past few decades. However, no gene playing a significant role in the development of these two traits has been identified. In the current study, a common wheat mutant with extremely compact spikes and good processing quality was isolated and characterized. A new allele (Qc1 ) of the Q gene (an important domestication gene) responsible for the mutant phenotype was cloned, and the molecular mechanism for the mutant phenotype was studied. Results revealed that Qc1 originated from a point mutation that interferes with the miRNA172-directed cleavage of Q transcripts, leading to its overexpression. It also reduces the longitudinal cell size of rachises, resulting in an increased spike density. Furthermore, Qc1 increases the number of vascular bundles, which suggests a higher efficiency in the transportation of assimilates in the spikes of the mutant than that of wild type. This accounts for the improved processing quality. The effects of Qc1 on spike density and wheat processing quality were confirmed by analyzing nine common wheat mutants possessing four different Qc alleles. These results deepen our understanding of the key roles of Q gene, and provide new insights for the potential application of Qc alleles in wheat quality breeding.
funRiceGenes dataset for comprehensive understanding and application of rice functional genes.

Background: As a main staple food, rice is also a model plant for functional genomic studies of monocots. Decoding of every DNA element of the rice genome is essential for genetic improvement to address increasing food demands. The past 15 years have witnessed extraordinary advances in rice functional genomics. Systematic characterization and proper deposition of every rice gene are vital for both functional studies and crop genetic improvement. Findings: We built a comprehensive and accurate dataset of ∼2800 functionally characterized rice genes and ∼5000 members of different gene families by integrating data from available databases and reviewing every publication on rice functional genomic studies. The dataset accounts for 19.2% of the 39 045 annotated protein-coding rice genes, which provides the most exhaustive archive for investigating the functions of rice genes. We also constructed 214 gene interaction networks based on 1841 connections between 1310 genes. The largest network with 762 genes indicated that pleiotropic genes linked different biological pathways. Increasing degree of conservation of the flowering pathway was observed among more closely related plants, implying substantial value of rice genes for future dissection of flowering regulation in other crops. All data are deposited in the funRiceGenes database (https://funricegenes.github.io/). Functionality for advanced search and continuous updating of the database are provided by a Shiny application (http://funricegenes.ncpgr.cn/). Conclusions: The funRiceGenes dataset would enable further exploring of the crosslink between gene functions and natural variations in rice, which can also facilitate breeding design to improve target agronomic traits of rice.
Merging microarray data from separate breast cancer studies provides a robust prognostic test.

BACKGROUND: There is an urgent need for new prognostic markers of breast cancer metastases to ensure that newly diagnosed patients receive appropriate therapy. Recent studies have demonstrated the potential value of gene expression signatures in assessing the risk of developing distant metastases. However, due to the small sample sizes of individual studies, the overlap among signatures is almost zero and their predictive power is often limited. Integrating microarray data from multiple studies in order to increase sample size is therefore a promising approach to the development of more robust prognostic tests. RESULTS: In this study, by using a highly stable data aggregation procedure based on expression comparisons, we have integrated three independent microarray gene expression data sets for breast cancer and identified a structured prognostic signature consisting of 112 genes organized into 80 pair-wise expression comparisons. A classical likelihood ratio test based on these comparisons, essentially weighted voting, achieves 88.6% sensitivity and 54.6% specificity in an independent external test set of 154 samples. The test is highly informative in assessing the risk of developing distant metastases within five years (hazard ratio 9.3 with 95% CI 2.9-29.9). CONCLUSION: Rank-based features provide a stable way to integrate patient data from separate microarray studies due to invariance to data normalization, and such features can be combined into a useful predictor of distant metastases in breast cancer within a statistical modeling framework which begins to capture gene-gene interactions. Upon further confirmation on large-scale independent data, such prognostic signatures and tests could provide a powerful tool to guide adjuvant systemic treatment that could greatly reduce the cost of breast cancer treatment, both in terms of toxic side effects and health care expenditures.
Flipped classroom improves student learning in health professions education: a meta-analysis.

BACKGROUND: The use of flipped classroom approach has become increasingly popular in health professions education. However, no meta-analysis has been published that specifically examines the effect of flipped classroom versus traditional classroom on student learning. This study examined the findings of comparative articles through a meta-analysis in order to summarize the overall effects of teaching with the flipped classroom approach. We focused specifically on a set of flipped classroom studies in which pre-recorded videos were provided before face-to-face class meetings. These comparative articles focused on health care professionals including medical students, residents, doctors, nurses, or learners in other health care professions and disciplines (e.g., dental, pharmacy, environmental or occupational health). METHOD: Using predefined study eligibility criteria, seven electronic databases were searched in mid-April 2017 for relevant articles. Methodological quality was graded using the Medical Education Research Study Quality Instrument (MERSQI). Effect sizes, heterogeneity estimates, analysis of possible moderators, and publication bias were computed using the COMPREHENSIVE META-ANALYSIS software. RESULTS: A meta-analysis of 28 eligible comparative studies (between-subject design) showed an overall significant effect in favor of flipped classrooms over traditional classrooms for health professions education (standardized mean difference, SMD = 0.33, 95% confidence interval, CI = 0.21-0.46, p < 0.001), with no evidence of publication bias. In addition, the flipped classroom approach was more effective when instructors used quizzes at the start of each in-class session. More respondents reported they preferred flipped to traditional classrooms. CONCLUSIONS: Current evidence suggests that the flipped classroom approach in health professions education yields a significant improvement in student learning compared with traditional teaching methods.
Antitumor effects and biomarkers of activity of AZD0530, a Src inhibitor, in pancreatic cancer.

PURPOSE: To determine the efficacy of AZD0530, an orally active small molecule Src inhibitor, in human pancreatic cancer xenografts and to seek biomarkers predictive of activity. EXPERIMENTAL DESIGN: Sixteen patient-derived pancreatic cancer xenografts from the PancXenoBank collection at Johns Hopkins were treated with AZD0530 (50 mg/kg/day, p.o.) for 28 days. Baseline gene expression profiles of differently expressed genes in 16 tumors by Affymetrix U133 Plus 2.0 gene array were used to predict AZD0530 sensitivity in an independent group of eight tumors using the K-Top Scoring Pairs (K-TSP) method. RESULTS: Three patient tumors of 16 were found to be sensitive to AZD0530, defined as tumor growth <50% compared with control tumors (100%). Western blot and/or immunohistochemistry results showed that AZD0530 administration resulted in the down-regulation of Src, FAK, p-FAK, p-paxillin, p-STAT-3, and XIAP in sensitive tumor xenografts compared with control tumors. The K-TSP classifier identified one gene pair (LRRC19 and IGFBP2) from the 16 training cases based on a decision rule. The classifier achieved 100% and 83.3% of sensitivity and specificity in an independent test set that consists of eight xenograft cases. CONCLUSIONS: AZD0530 treatment significantly inhibits the tumor growth in a subset of human pancreatic tumor xenografts. One gene pair (LRRC19 and IGFBP2) identified by the K-TSP classifier has high predictive power for AZD0530 sensitivity, suggesting the potential for this gene pair as biomarker for pancreatic tumor sensitivity to AZD0530.
An outer approximation method for the road network design problem.

Best investment in the road infrastructure or the network design is perceived as a fundamental and benchmark problem in transportation. Given a set of candidate road projects with associated costs, finding the best subset with respect to a limited budget is known as a bilevel Discrete Network Design Problem (DNDP) of NP-hard computationally complexity. We engage with the complexity with a hybrid exact-heuristic methodology based on a two-stage relaxation as follows: (i) the bilevel feature is relaxed to a single-level problem by taking the network performance function of the upper level into the user equilibrium traffic assignment problem (UE-TAP) in the lower level as a constraint. It results in a mixed-integer nonlinear programming (MINLP) problem which is then solved using the Outer Approximation (OA) algorithm (ii) we further relax the multi-commodity UE-TAP to a single-commodity MILP problem, that is, the multiple OD pairs are aggregated to a single OD pair. This methodology has two main advantages: (i) the method is proven to be highly efficient to solve the DNDP for a large-sized network of Winnipeg, Canada. The results suggest that within a limited number of iterations (as termination criterion), global optimum solutions are quickly reached in most of the cases; otherwise, good solutions (close to global optimum solutions) are found in early iterations. Comparative analysis of the networks of Gao and Sioux-Falls shows that for such a non-exact method the global optimum solutions are found in fewer iterations than those found in some analytically exact algorithms in the literature. ( ii) Integration of the objective function among the constraints provides a commensurate capability to tackle the multi-objective (or multi-criteria) DNDP as well.
Psychosocial factors associated with change in pain and disability outcomes in chronic low back pain patients treated by physiotherapist: A systematic review.

Background: Almost 80% of people have low back pain at least once in their life. Clinical guidelines emphasize the use of conservative physiotherapy and the importance of staying active. While the psychological factors predicting poor recovery following surgical intervention are understood, the psychosocial factors associated with poor outcomes following physiotherapy have yet to be identified. Methods: Electronic searches of PubMed, Medline, CINAHL, PsycINFO and EBSCO were conducted using terms relating to psychosocial factors, chronic low back pain, disability and physiotherapy. Papers examining the relationship between psychosocial factors and pain and disability outcomes following physiotherapy were included. Two reviewers selected, appraised and extracted studies independently. Results: In total, 10 observational studies were identified that suggested an association between fear of movement, depression, self-efficacy and catastrophizing in modifying pain and disability outcomes following physiotherapy. Discussion: Although limited by methodological shortcomings of included studies, and heterogeneity of physiotherapy interventions and measures of disability and psychosocial outcomes, the findings are consistent with other research in the context of back pain and physiotherapy, which suggest an association between psychosocial factors, including fear of movement, catastrophizing and self-efficacy and pain and disability outcomes in chronic low back pain patients treated by physiotherapist. However, a direct relationship cannot be concluded from this study. Conclusion: Findings suggest an association between psychosocial factors, including fear of movement, catastrophizing and self-efficacy and pain and disability outcomes in chronic low back pain patients treated by physiotherapist, which warrants further study.
Long non-coding RNAs as an Epigenetic Regulator in Human Cancers.

Recent studies have demonstrated the important multiple roles of long non-coding RNAs (lncRNAs) during oncogenic transformation. Because the coding genome accounts for a small amount of total DNA, and many mutations leading to cancer occur in the non-coding genome, it is plausible that the dysregulation of such non-coding transcribes might also affect tumor phenotypes. Indeed, to date, lncRNAs have been reported to affect diverse biological processes through the regulation of mRNA stability, RNA splicing, chromatin structure, and miRNA-mediated gene regulation by acting as miRNA sponges. Furthermore, accumulating studies have demonstrated the roles of lncRNAs in tumorigenesis; however, the precise mechanisms of many lncRNAs are still under investigation. Here, we discuss recently reported mechanistic insights into how lncRNAs regulate gene expression and contribute to tumorigenesis via interactions with other regulatory molecules. We have especially highlighted the role of Taurine Upregulated Gene 1 (TUG1), which was recently reported to have biological functions related to gene regulation, and discuss the future clinical implications of lncRNAs in cancer treatments. This article is protected by copyright. All rights reserved.
Development of an integrated genomic classifier for a novel agent in colorectal cancer: approach to individualized therapy in early development.

BACKGROUND: A plethora of agents is in early stages of development for colorectal cancer (CRC), including those that target the insulin-like growth factor I receptor (IGFIR) pathway. In the current environment of numerous cancer targets, it is imperative that patient selection strategies be developed with the intent of preliminary testing in the latter stages of phase I trials. The goal of this study was to develop and characterize predictive biomarkers for an IGFIR tyrosine kinase inhibitor, OSI-906, that could be applied in CRC-specific studies of this agent. METHODS: Twenty-seven CRC cell lines were exposed to OSI-906 and classified according to IC(50) value as sensitive (<or=1.5 micromol/L) or resistant (>5 micromol/L). Cell lines were subjected to immunoblotting and immunohistochemistry for effector proteins, IGFIR copy number by fluorescence in situ hybridization, KRAS/BRAF/phosphoinositide 3-kinase mutation status, and baseline gene array analysis. The most sensitive and resistant cell lines were used for gene array and pathway analyses, along with shRNA knockdown of highly ranked genes. The resulting integrated genomic classifier was then tested against eight human CRC explants in vivo. RESULTS: Baseline gene array data from cell lines and xenografts were used to develop a k-top scoring pair (k-TSP) classifier, which, in combination with IGFIR fluorescence in situ hybridization and KRAS mutational status, was able to predict with 100% accuracy a test set of patient-derived CRC xenografts. CONCLUSIONS: These results indicate that an integrated approach to the development of individualized therapy is feasible and should be applied early in the development of novel agents, ideally in conjunction with late-stage phase I trials.
Integrated preclinical and clinical development of mTOR inhibitors in pancreatic cancer.

BACKGROUND: The purpose of this work was to determine the efficacy of inhibiting mammalian target of rapamycin (mTOR) in pancreatic cancer preclinical models and translate preclinical observations to the clinic. METHODS: Temsirolimus (20 mg Kg(-1) daily) was administered to freshly generated pancreatic cancer xenografts. Tumour growth inhibition was determined after 28 days. Xenografts were characterised at baseline by gene expression and comparative genomic hybridisation. Patients with advanced, gemcitabine-resistant pancreatic cancer were treated with sirolimus (5 mg daily). The primary end point was 6-month survival rate (6mSR). Correlative studies included immunohistochemistry assessment of pathway expression in baseline tumours, drug pharmacokinetics (PKs), response assessment by FDG-PET and pharmacodynamic effects in peripheral-blood mononuclear cells (PBMCs). RESULTS: In all, 4 of 17 xenografts (23%) responded to treatment. Sensitive tumours were characterised by gene copy number variations and overexpression of genes leading to activation of the PI3K/Akt/mTOR pathway. Activation of p70S6K correlated with drug activity in the preclinical studies. Sirolimus was well tolerated in the clinic, showed predictable PKs, exerted pathway inhibition in post-treatment PBMCs and resulted in a 6mSR of 26%. No correlation, however, was found between activated p70S6K in tumour tissues and anti-tumour effects. CONCLUSION: Sirolimus activity in pancreatic cancer was marginal and not predicted by the selected biomarker.
The Landscape of Circular RNA Expression Profiles in Papillary Thyroid Carcinoma Based on RNA Sequencing.

BACKGROUND/AIMS: Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. However, the molecular mechanisms responsible for its tumorigenesis and progression remain largely unknown. Circular RNA (circRNA) is a novel type of noncoding RNA that can serve as an ideal biomarker due to its stability. Recent evidence suggests that circRNAs play important roles in tumorigenesis. This study aims to investigate circRNA expression profiles and their potential biological functions in PTC. METHODS: High-throughput RNA sequencing was used to assess circRNA expression profiles in PTC, and quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate dysregulated circRNAs. Receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic value of circRNAs for PTC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were employed to determine the biological functions of differentially expressed circRNAs. Bioinformatic analyses were applied to predict interactions between circRNAs and microRNAs (miRNAs), and a circRNA-miRNA-mRNA network was constructed using Cytoscape software. RESULTS: We identified a number of differentially expressed circRNAs in PTC tissues compared with paired normal thyroid tissues, with chr5: 160757890-160763776-, chr12: 40696591-40697936+, chr7: 22330794-22357656-, and chr21: 16386665-16415895- being upregulated, and chr7: 91924203-91957214+, chr2: 179514891-179516047-, chr9: 16435553-16437522-, and chr22: 36006931-36007153- being downregulated. These findings were confirmed by qRT-PCR, and ROC curves indicated that they can serve as potential biomarkers for PTC. GO and KEGG pathway analyses showed that some of these circRNAs are related to cancers. Additionally, bioinformatic analyses revealed a potential competing-endogenous-RNA-regulating network among circRNAs, miRNAs, and mRNAs. CONCLUSIONS: Our study results depict the landscape of circRNA expression profiles in PTC and also provide potential biomarkers for PTC. Further functional and mechanistic studies of these circRNAs may improve our understanding of PTC tumorigenesis.
Gene array and fluorescence in situ hybridization biomarkers of activity of saracatinib (AZD0530), a Src inhibitor, in a preclinical model of colorectal cancer.

PURPOSE: To evaluate the efficacy of saracatinib (AZD0530), an oral Src inhibitor, in colorectal cancer (CRC) and to identify biomarkers that predict antitumor activity. EXPERIMENTAL DESIGN: Twenty-three CRC cell lines were exposed to saracatinib, and baseline gene expression profiles of three sensitive and eight resistant cell lines in vitro and in vivo were used to predict saracatinib sensitivity in an independent group of 10 human CRC explant tumors using the gene array K-Top Scoring Pairs (K-TSP) method. In addition, fluorescence in situ hybridization (FISH) and immunoblotting determined both Src gene copy number and activation of Src, respectively. RESULTS: Two of 10 explant tumors were determined to be sensitive to saracatinib. The K-TSP classifier (TOX>GLIS2, TSPAN7>BCAS4, and PARD6G>NXN) achieved 70% (7 of 10) accuracy on the test set. Evaluation of Src gene copy number by FISH showed a trend toward significance (P = 0.066) with respect to an increase in Src gene copy and resistance to saracatinib. Tumors sensitive to saracatinib showed an increase in the activation of Src and FAK when compared with resistant tumors. CONCLUSIONS: Saracatinib significantly decreased tumor growth in a subset of CRC cell lines and explants. A K-TSP classifier (TOX>GLIS2, TSPAN7>BCAS4, and PARD6G>NXN) was predictive for sensitivity to saracatinib. In addition, increased activation of the Src pathway was associated with sensitivity to saracatinib. These results suggest that FISH, a K-TSP classifier, and activation of the Src pathway have potential in identifying CRC patients that would potentially benefit from treatment with saracatinib.