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.

Input: Consider Input: Environmental factors and host genetics interact to control the gut microbiota, which may have a role in the development of obesity and insulin resistance. TLR2-deficient mice, under germ-free conditions, are protected from diet-induced insulin resistance. It is possible that the presence of gut microbiota could reverse the phenotype of an animal, inducing insulin resistance in an animal genetically determined to have increased insulin sensitivity, such as the TLR2 KO mice. In the present study, we investigated the influence of gut microbiota on metabolic parameters, glucose tolerance, insulin sensitivity, and signaling of TLR2-deficient mice. We investigated the gut microbiota (by metagenomics), the metabolic characteristics, and insulin signaling in TLR2 knockout (KO) mice in a non-germ free facility. Results showed that the loss of TLR2 in conventionalized mice results in a phenotype reminiscent of metabolic syndrome, characterized by differences in the gut microbiota, with a 3-fold increase in Firmicutes and a slight increase in Bacteroidetes compared with controls. These changes in gut microbiota were accompanied by an increase in LPS absorption, subclinical inflammation, insulin resistance, glucose intolerance, and later, obesity. In addition, this sequence of events was reproduced in WT mice by microbiota transplantation and was also reversed by antibiotics. At the molecular level the mechanism was unique, with activation of TLR4 associated with ER stress and JNK activation, but no activation of the IKK-IB-NFB pathway. Our data also showed that in TLR2 KO mice there was a reduction in regulatory T cell in visceral fat, suggesting that this modulation may also contribute to the insulin resistance of these animals. Our results emphasize the role of microbiota in the complex network of molecular and cellular interactions that link genotype to phenotype and have potential implications for common human disorders involving obesity, diabetes, and even other immunological disorders.

Output: False

Input: Consider Input: Missense mutations in the nucleotide-binding oligomerization domain (NOD)-like receptor pyrin domain containing family of gene 12 (Nlrp12) are associated with periodic fever syndromes and atopic dermatitis in humans. Here, we have demonstrated a crucial role for NLRP12 in negatively regulating pathogenic T cell responses. Nlrp12(-/-) mice responded to antigen immunization with hyperinflammatory T cell responses. Furthermore, transfer of CD4(+)CD45RB(hi)Nlrp12(-/-) T cells into immunodeficient mice led to more severe colitis and atopic dermatitis. NLRP12 deficiency did not, however, cause exacerbated ascending paralysis during experimental autoimmune encephalomyelitis (EAE); instead, Nlrp12(-/-) mice developed atypical neuroinflammatory symptoms that were characterized by ataxia and loss of balance. Enhanced T-cell-mediated interleukin-4 (IL-4) production promotes the development of atypical EAE disease in Nlrp12(-/-) mice. These results define an unexpected role for NLRP12 as an intrinsic negative regulator of T-cell-mediated immunity and identify altered NF-B regulation and IL-4 production as key mediators of NLRP12-associated disease.

Output: False

Input: Consider Input: OBJECTIVE Impulsivity and inattention related to attention deficit hyperactivity disorder (ADHD) may increase food intake and, consequently, weight gain. However, findings on the association between obesity/overweight and ADHD are mixed. The authors conducted a meta-analysis to estimate this association.
METHOD A broad range of databases was searched through Aug. 31, 2014. Unpublished studies were also obtained. Study quality was rated with the Newcastle-Ottawa Scale. Random-effects models were used.
RESULTS Forty-two studies that included a total of 728,136 individuals (48,161 ADHD subjects; 679,975 comparison subjects) were retained. A significant association between obesity and ADHD was found for both children (odds ratio=1.20, 95% CI=1.05-1.37) and adults (odds ratio=1.55, 95% CI=1.32-1.81). The pooled prevalence of obesity was increased by about 70% in adults with ADHD (28.2%, 95% CI=22.8-34.4) compared with those without ADHD (16.4%, 95% CI=13.4-19.9), and by about 40% in children with ADHD (10.3%, 95% CI=7.9-13.3) compared with those without ADHD (7.4%, 95% CI=5.4-10.1). The significant association between ADHD and obesity remained when limited to studies 1) reporting odds ratios adjusted for possible confounding factors; 2) diagnosing ADHD by direct interview; and 3) using directly measured height and weight. Gender, study setting, study country, and study quality did not moderate the association between obesity and ADHD. ADHD was also significantly associated with overweight. Individuals medicated for ADHD were not at higher risk of obesity.
CONCLUSIONS This study provides meta-analytic evidence for a significant association between ADHD and obesity/overweight. Further research should address possible underlying mechanisms and the long-term effects of ADHD treatments on weight in individuals with both ADHD and obesity.
Output: True