Takshan/R1 huggingface dataset:
LncmiRSRN: identification and analysis of long non-coding RNA related miRNA sponge regulatory network in human cancer.

Motivation: MicroRNAs (miRNAs) are small non-coding RNAs with the length of ∼22 nucleotides. miRNAs are involved in many biological processes including cancers. Recent studies show that long non-coding RNAs (lncRNAs) are emerging as miRNA sponges, playing important roles in cancer physiology and development. Despite accumulating appreciation of the importance of lncRNAs, the study of their complex functions is still in its preliminary stage. Based on the hypothesis of competing endogenous RNAs (ceRNAs), several computational methods have been proposed for investigating the competitive relationships between lncRNAs and miRNA target messenger RNAs (mRNAs). However, when the mRNAs are released from the control of miRNAs, it remains largely unknown as to how the sponge lncRNAs influence the expression levels of the endogenous miRNA targets. Results: We propose a novel method to construct lncRNA related miRNA sponge regulatory networks (LncmiRSRNs) by integrating matched lncRNA and mRNA expression profiles with clinical information and putative miRNA-target interactions. Using the method, we have constructed the LncmiRSRNs for four human cancers (glioblastoma multiforme, lung cancer, ovarian cancer and prostate cancer). Based on the networks, we discover that after being released from miRNA control, the target mRNAs are normally up-regulated by the sponge lncRNAs, and only a fraction of sponge lncRNA-mRNA regulatory relationships and hub lncRNAs are shared by the four cancers. Moreover, most sponge lncRNA-mRNA regulatory relationships show a rewired mode between different cancers, and a minority of sponge lncRNA-mRNA regulatory relationships conserved (appearing) in different cancers may act as a common pivot across cancers. Besides, differential and conserved hub lncRNAs may act as potential cancer drivers to influence the cancerous state in cancers. Functional enrichment and survival analysis indicate that the identified differential and conserved LncmiRSRN network modules work as functional units in biological processes, and can distinguish metastasis risks of cancers. Our analysis demonstrates the potential of integrating expression profiles, clinical information and miRNA-target interactions for investigating lncRNA regulatory mechanism. Availability and implementation: LncmiRSRN is freely available (https://github.com/zhangjunpeng411/LncmiRSRN). Supplementary information: Supplementary data are available at Bioinformatics online.
Triple-negative breast cancer and PTEN (phosphatase and tensin homologue) loss are predictors of BRCA1 germline mutations in women with early-onset and familial breast cancer, but not in women with isolated late-onset breast cancer.

INTRODUCTION: Given that breast cancers in germline BRCA1 carriers are predominantly estrogen-negative and triple-negative, it has been suggested that women diagnosed with triple-negative breast cancer (TNBC) younger than 50 years should be offered BRCA1 testing, regardless of family cancer characteristics. However, the predictive value of triple-negative breast cancer, when taken in the context of personal and family cancer characteristics, is unknown. The aim of this study was to determine whether TNBC is a predictor of germline BRCA1 mutations, in the context of multiple predictive factors. METHODS: Germline mutations in BRCA1 and BRCA2 were analyzed by Sanger sequencing and multiple ligation-dependent probe amplification (MLPA) analysis in 431 women from the Malaysian Breast Cancer Genetic Study, including 110 women with TNBC. Logistic regression was used to identify and to estimate the predictive strength of major determinants. Estrogen receptor (ER) and phosphatase and tensin homologue (PTEN) status were assessed and included in a modified Manchester scoring method. RESULTS: Our study in an Asian series of TNBC patients demonstrated that 27 (24.5%) of 110 patients have germline mutations in BRCA1 (23 of 110) and BRCA2 (four of 110). We found that among women diagnosed with breast cancer aged 36 to 50 years but with no family history of breast or ovarian cancer, the prevalence of BRCA1 and BRCA2 mutations was similar in TNBC (8.5%) and non-TNBC patients (6.7%). By contrast, in women diagnosed with breast cancer, younger than 35 years, with no family history of these cancers, and in women with a family history of breast cancer, the prevalence of mutations was higher in TNBC compared with non-TNBC (28.0% and 9.9%; P = 0.045; and 42.1% and 14.2%; P < 0.0001, respectively]. Finally, we found that incorporation of estrogen-receptor and TNBC status improves the sensitivity of the Manchester Scoring method (42.9% to 64.3%), and furthermore, incorporation of PTEN status further improves sensitivity (42.9% to 85.7%). CONCLUSIONS: We found that TNBC is an important criterion for highlighting women who may benefit from genetic testing, but that this may be most useful for women with early-onset breast cancer (35 years or younger) or with a family history of cancers. Furthermore, addition of TNBC and PTEN status improves the sensitivity of the Manchester scoring method and may be particularly important in the Asian context, where risk-assessment models underestimate the number of mutation carriers.
Comparison of platelet-albumin-bilirubin (PALBI), albumin-bilirubin (ALBI), and child-pugh (CP) score for predicting of survival in advanced hcc patients receiving radiotherapy (RT).

Purpose: This work evaluated the prognostic performance of Child-Pugh (CP), albumin-bilirubin (ALBI) and platelet-albumin-bilirubin (PALBI) scores in hepatocellular carcinoma (HCC) patients undergoing radiotherapy (RT). Results: The study included 174 consecutive patients with 63% at CP A5 (n = 110) and 34% at CP A6 (n = 64). The median ALBI score was -2.39 (range: -3.61 to -1.41) with 34.5% at grade A1 (n = 60) and 65.5% at grade A2 (n = 114). The median PALBI score was -2.39 (range -3.39 to -1.24) with 33.3% at grade 1 (n = 58), 41.4% at grade 2 (n = 72) and 25.3% at grade 3 (n = 44). With a median follow-up of 21.7 months, the median OS of the entire cohort was 22.2 months. OS was significantly associated with the PALBI grade (p = 0.002) and for the ALBI grade (p = 0.00495), but not for the CP score (p = 0.46). The PALBI grade has a significantly higher AUC compared than the ALBI grade or CP scores in predicting OS. The PALBI grade was predictive of CP score decline ≥2 (20% grade 3 vs. 5.3% grade 1/2 p = 0.05) but the ALBI and CP scores were not. Conclusion: Among CP A HCC patients receiving radiotherapy, the PALBI and ALBI grade maybe a better prognostic tool than the CP score. The role of PALBI in predicting liver toxicity warranted further exploration. Methods: We retrospectively reviewed HCC patients treated with individualized hypo-fractionated radiotherapy (IHRT) using stereotactic technique from 2006 to 2015. We collected CP, ALBI and PALBI scores prior to treatment and analyzed their correlation with overall survival (OS) and liver toxicity.
In silico cancer research towards 3R.

BACKGROUND: Improving our understanding of cancer and other complex diseases requires integrating diverse data sets and algorithms. Intertwining in vivo and in vitro data and in silico models are paramount to overcome intrinsic difficulties given by data complexity. Importantly, this approach also helps to uncover underlying molecular mechanisms. Over the years, research has introduced multiple biochemical and computational methods to study the disease, many of which require animal experiments. However, modeling systems and the comparison of cellular processes in both eukaryotes and prokaryotes help to understand specific aspects of uncontrolled cell growth, eventually leading to improved planning of future experiments. According to the principles for humane techniques milestones in alternative animal testing involve in vitro methods such as cell-based models and microfluidic chips, as well as clinical tests of microdosing and imaging. Up-to-date, the range of alternative methods has expanded towards computational approaches, based on the use of information from past in vitro and in vivo experiments. In fact, in silico techniques are often underrated but can be vital to understanding fundamental processes in cancer. They can rival accuracy of biological assays, and they can provide essential focus and direction to reduce experimental cost. MAIN BODY: We give an overview on in vivo, in vitro and in silico methods used in cancer research. Common models as cell-lines, xenografts, or genetically modified rodents reflect relevant pathological processes to a different degree, but can not replicate the full spectrum of human disease. There is an increasing importance of computational biology, advancing from the task of assisting biological analysis with network biology approaches as the basis for understanding a cell's functional organization up to model building for predictive systems. CONCLUSION: Underlining and extending the in silico approach with respect to the 3Rs for replacement, reduction and refinement will lead cancer research towards efficient and effective precision medicine. Therefore, we suggest refined translational models and testing methods based on integrative analyses and the incorporation of computational biology within cancer research.
Health care professionals' neckties as a source of transmission of bacteria to patients: a systematic review.

BACKGROUND: There is growing concern that neckties worn by health care professionals may contribute to infections contracted in health care settings. We evaluated the evidence for health-care-associated infections resulting from neckties and whether the evidence is sufficient to warrant a tieless policy in Canada. METHODS: We performed a systematic review to determine whether neckties worn by health care professionals colonize harmful pathogenic bacteria and whether they contribute to the spread of infection to patients in the inpatient or outpatient setting. We searched PubMed (1966 to 2017) and Embase (1974 to 2017). The level of evidence was appraised according to the Oxford Centre for Evidence-Based Medicine levels of evidence. We evaluated the quality of evidence and the risk of bias using the Jadad scale or the Newcastle-Ottawa Scale. RESULTS: We screened 1675 citations, of which 6 were ultimately included in the systematic review. Only 1 study gave level 1b evidence (randomized controlled trial). Neckties were more likely than shirt pockets to colonize bacteria. There is limited evidence that neckties may be contaminated with pathogenic bacteria (e.g., methicillin-resistant Staphylococcus aureus) and very limited evidence that contaminated neckties may transmit bacteria (in a controlled experimental setting to a mannequin). INTERPRETATION: There is no evidence of increased rates of health-care-associated infections related to the wearing of neckties by health care professionals. There is weak evidence that neckties are contaminated with pathogenic (and nonpathogenic) bacteria. The level of evidence was weak and the studies were heterogeneous. Evidence to support the need for a tieless dress code policy is lacking.
The null hypothesis of GSEA, and a novel statistical model for competitive gene set analysis.

Motivation: Competitive gene set analysis intends to assess whether a specific set of genes is more associated with a trait than the remaining genes. However, the statistical models assumed to date to underly these methods do not enable a clear cut formulation of the competitive null hypothesis. This is a major handicap to the interpretation of results obtained from a gene set analysis. Results: This work presents a hierarchical statistical model based on the notion of dependence measures, which overcomes this problem. The two levels of the model naturally reflect the modular structure of many gene set analysis methods. We apply the model to show that the popular GSEA method, which recently has been claimed to test the self-contained null hypothesis, actually tests the competitive null if the weight parameter is zero. However, for this result to hold strictly, the choice of the dependence measures underlying GSEA and the estimators used for it is crucial. Contact: bdebrabant@health.sdu.dk. Supplementary information: Supplementary material is available at Bioinformatics online.