In this task, you are given an abstract of article. Your task is to generate label "True" if abstract is structured, otherwise generate "False". A structured abstract is composed of a topic sentence (or key sentence), relevant supporting sentences, and a closing (or transition) sentence. This structure is key to keeping your abstract focused on the main idea and creating a clear and concise image.

Q: OBJECTIVES Non-celiac wheat sensitivity (NCWS) is defined as a reaction to ingested wheat after exclusion of celiac disease and wheat allergy. As its pathogenesis is incompletely understood, we evaluated the inflammatory response in the rectal mucosa of patients with well-defined NCWS.
METHODS The prospective study included 22 patients with irritable bowel syndrome (IBS)-like clinical presentation, diagnosed with NCWS by double-blind placebo-controlled challenge. Eight IBS patients not improving on wheat-free diet were used as controls. Two weeks after oral challenge was performed with 80 grams of wheat daily, cells were isolated from rectal biopsies and thoroughly characterized by fluorescence-activated cell sorting analysis for intracellular cytokines and surface markers.
RESULTS Rectal biopsies from wheat-challenged NCWS patients showed that a significant mucosal CD45(+) infiltrate consisted of CD3(+) and CD3(-) lymphocytes, with the latter spontaneously producing more interferon (IFN)- than IBS controls. About 30% of IFN--producing CD45(+) cells were T-bet(+), CD56(-), NKP44(-), and CD117(-), defining them as a type-1 innate lymphoid cells (ILC1). IFN--producing ILC1 cells significantly decreased in 10 patients analyzed 2 weeks after they resumed a wheat-free diet.
CONCLUSIONS These data indicate that, in patients with active NCWS, IFN--producing ILC1 cells infiltrate rectal mucosa and support a role for this innate lymphoid cell population in the pathogenesis of NCWS.

A: True
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Q: Expression quantitative trait loci (eQTL) mapping aims to determine genomic regions that regulate gene transcription. Expression QTL is used to study the regulatory structure of normal tissues and to search for genetic factors in complex diseases such as cancer, diabetes, and cystic fibrosis. A modern eQTL dataset contains millions of SNPs and thousands of transcripts measured for hundreds of samples. This makes the analysis computationally complex as it involves independent testing for association for every transcript-SNP pair. The heavy computational burden makes eQTL analysis less popular, often forces analysts to restrict their attention to just a subset of transcripts and SNPs. As larger genotype and gene expression datasets become available, the demand for fast tools for eQTL analysis increases. We present a new method for fast eQTL analysis via linear models, called Matrix eQTL. Matrix eQTL can model and test for association using both linear regression and ANOVA models. The models can include covariates to account for such factors as population structure, gender, and clinical variables. It also supports testing of heteroscedastic models and models with correlated errors. In our experiment on large datasets Matrix eQTL was thousands of times faster than the existing popular software for QTL/eQTL analysis. Matrix eQTL is implemented as both Matlab and R packages and thus can easily be run on Windows, Mac OS, and Linux systems. The software is freely available at the following address: http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL

A: False
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Q: BACKGROUND Individuals with severely impaired lung function have an increased risk of lung cancer. Whether milder reductions in forced expiratory volume in 1 second (FEV(1)) also increase the risk of lung cancer is controversial. Moreover, there is little consensus on whether men and women have similar risks for lung cancer for similar decreases in FEV(1).
METHODS A search was conducted of PubMed and EMBASE from January 1966 to January 2005 and studies that examined the relationship between FEV1 and lung cancer were identified. The search was limited to studies that were population based, employed a prospective design, were large in size (> or = 5000 participants), and adjusted for cigarette smoking status.
RESULTS Twenty eight abstracts were identified, six of which did not report FEV1 and eight did not adjust for smoking. Included in this report are four studies that reported FEV1 in quintiles. The risk of lung cancer increased with decreasing FEV1. Compared with the highest quintile of FEV1 (> 100% of predicted), the lowest quintile of FEV1 (< approximately 70% of predicted) was associated with a 2.23 fold (95% confidence interval (CI) 1.73 to 2.86) increase in the risk for lung cancer in men and a 3.97 fold increase in women (95% CI 1.93 to 8.25). Even relatively small decrements in FEV1 ( approximately 90% of predicted) increased the risk for lung cancer by 30% in men (95% CI 1.05 to 1.62) and 2.64 fold in women (95% CI 1.30 to 5.31).
CONCLUSION Reduced FEV1 is strongly associated with lung cancer. Even a relatively modest reduction in FEV1 is a significant predictor of lung cancer, especially among women.

A:
True
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