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raven44099/annotation_gui_230315_deconstruct_d.ipynb

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annotation_gui_230315_deconstruct_d.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/raven44099/d23f46ac4860c76da4fd2d4f8787766d/annotation_gui_230315_deconstruct_d.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "3gas2YIpI-0B"
},
"source": [
"# 1. preparations"
],
"id": "3gas2YIpI-0B"
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"id": "8eeadd62-c339-4c5c-9107-df0b4331b9d3",
"cellView": "form"
},
"outputs": [],
"source": [
"#@title import libs\n",
"import ipywidgets as widgets\n",
"from ipywidgets import Button, GridBox, Layout, ButtonStyle, HBox, VBox, Label, Text, HTML\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"import functools\n",
"\n",
"from google.colab import output\n",
"output.enable_custom_widget_manager() # because this sometimes changes stuff.\n",
"\n",
"!mkdir /content/session/\n",
"pathXX = '/content'"
],
"id": "8eeadd62-c339-4c5c-9107-df0b4331b9d3"
},
{
"cell_type": "markdown",
"metadata": {
"id": "7DYbFSqX0jHU"
},
"source": [
"# 2. <font color ='gold'> raw data </font>"
],
"id": "7DYbFSqX0jHU"
},
{
"cell_type": "code",
"source": [
"#@title my_doc = {...json...}\n",
"my_doc = {'id': '3222897',\n",
" 'infons': {'license': 'author_manuscript'},\n",
" 'passages': [{'offset': 0,\n",
" 'infons': {'article-id_doi': '10.1016/j.cmet.2008.08.014',\n",
" 'article-id_manuscript': 'NIHMS73535',\n",
" 'article-id_pmc': '3222897',\n",
" 'article-id_pmid': '18840364',\n",
" 'fpage': '333',\n",
" 'issue': '4',\n",
" 'license': '\\n This file is available for text mining. It may also be used consistent with the principles of fair use under the copyright law.\\n ',\n",
" 'lpage': '341',\n",
" 'name_0': 'surname:Banks;given-names:Alexander S.',\n",
" 'name_1': 'surname:Kon;given-names:Ning',\n",
" 'name_2': 'surname:Knight;given-names:Colette',\n",
" 'name_3': 'surname:Matsumoto;given-names:Michihiro',\n",
" 'name_4': 'surname:Gutiérrez-Juárez;given-names:Roger',\n",
" 'name_5': 'surname:Rossetti;given-names:Luciano',\n",
" 'name_6': 'surname:Gu;given-names:Wei',\n",
" 'name_7': 'surname:Accili;given-names:Domenico',\n",
" 'section_type': 'TITLE',\n",
" 'type': 'front',\n",
" 'volume': '8',\n",
" 'year': '2011'},\n",
" 'text': 'SirT1 gain-of-function increases energy efficiency and prevents diabetes in mice',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 81,\n",
" 'infons': {'section_type': 'ABSTRACT', 'type': 'abstract_title_1'},\n",
" 'text': 'Summary',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 89,\n",
" 'infons': {'section_type': 'ABSTRACT', 'type': 'abstract'},\n",
" 'text': 'In yeast, worms and flies, an extra copy of the gene encoding the Sirtuin Sir2 increases metabolic efficiency, as does administration of polyphenols like resveratrol, thought to act through Sirtuins. But evidence that Sirtuin gain-of-function results in increased metabolic efficiency in mammals is limited. We generated transgenic mice with moderate overexpression of SirT1, designed to mimic the Sirtuin gain-of-function that improves metabolism in C.elegans. These mice exhibit normal insulin sensitivity, but decreased food intake and locomotor activity, resulting in decreased energy expenditure. However, in various models of insulin resistance and diabetes, SirT1 transgenics display improved glucose tolerance due to decreased hepatic glucose production and increased adiponectin levels, without changes in body weight or composition. We conclude that SirT1 gain-of-function primes the organism for metabolic adaptation to insulin resistance, increasing hepatic insulin sensitivity and decreasing whole-body energy requirements. These findings have important implications for Sirtuin-based therapies in humans.',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 1208,\n",
" 'infons': {'section_type': 'INTRO', 'type': 'title_1'},\n",
" 'text': 'Introduction',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 1221,\n",
" 'infons': {'section_type': 'INTRO', 'type': 'paragraph'},\n",
" 'text': 'The increased prevalence of obesity and diabetes, with the attendant increase in morbidity and mortality, pose a substantial therapeutic challenge. Genetic screens in lower organisms provide evidence that gain-of-function of the deacetylase Sir2 results in beneficial metabolic effects and lifespan extension. Sirtuin agonists increase metabolic efficiency in rodents through a mechanism bearing similarity with calorie restriction. However, the specificity of these compounds remains undefined.',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 1717,\n",
" 'infons': {'section_type': 'INTRO', 'type': 'paragraph'},\n",
" 'text': 'The function of mammalian Sir2α (also known as SirT1) in metabolism is controversial. Two models of SirT1 gain-of-function in either pancreatic β cells or adipocytes and brain result in improved insulin secretion and sensitivity, respectively. But increasing SirT1 expression in liver impairs glucose tolerance, and resveratrol increases glucose production by hepatoma cells. Thus, it remains unclear whether chronic, ubiquitous SirT1 activation ultimately benefits or impairs metabolic control.',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 2220,\n",
" 'infons': {'section_type': 'INTRO', 'type': 'paragraph'},\n",
" 'text': 'To address this question, we developed transgenic mice designed to mimic the chromosomal duplication leading to moderate gain-of-function that improves metabolism in C.elegans. In the latter organism, Sir2 function requires the FoxO1 ortholog daf-16. Thus, in our studies we sought to address whether SirT1 gain-of-function mediates its effects through FoxO1.',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 2580,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'title_1'},\n",
" 'text': 'Results',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 2588,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'title_2'},\n",
" 'text': 'Generation and analysis of SirT1 Transgenic Mice',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 2637,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'paragraph'},\n",
" 'text': 'To test the hypothesis that SirT1 participates in the regulation of metabolism, we generated BAC transgenic mice overexpressing SirT1 (SirT1 Bacterial Artificial Chromosome Overexpressor, SirBACO). SirBACO mice were born in Mendelian ratios and displayed no gross anatomical or reproductive defects. SirT1 levels were two- to threefold higher than control littermates, except in the spleen (~seven-fold higher), and distribution patterns were indistinguishable from those of the endogenous protein in all tissues examined (Figure 1A–1B). SirT1 overexpression was preserved when SirBACO mice were backcrossed onto the db/db background (Figure 1C). To probe the transgene’s function, we intercrossed SirBACO with Sirt1−/− mice. The transgene readily rescued developmental defects and postnatal lethality of Sirt1−/− mice (data not shown). These findings are consistent the generation of a mouse model of SirT1 gain-of-function.',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 3575,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'title_2'},\n",
" 'text': 'Altered energy balance in SirBACO Mice',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 3614,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'paragraph'},\n",
" 'text': 'We carried out a metabolic characterization of SirBACO mice on a standard diet. Serum metabolite levels–including insulin and glucose–were normal (Table S1), as was the response to intraperitoneal glucose or insulin challenge tests (Figure 2A–2B). However, we detected a ~30% increase in plasma adiponectin levels (Table S1).',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 3946,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'paragraph'},\n",
" 'text': 'In C.elegans and D.melanogaster, increased Sir2 mimics the effects of calorie restriction to extend lifespan. In mammals, prolonged calorie restriction decreases energy expenditure and increases metabolic efficiency by decreasing O2 consumption. To determine whether SirT1 overexpression reproduces these sub-phenotypes, we carried out indirect calorimetry experiments. SirBACO mice demonstrated a coordinate ~15% decrease in O2 consumption and CO2 production (Figure 2C and data not shown). Due to the combined fall in VO2 and VCO2, the respiratory quotient (RQ = VCO2/VO2) was unchanged (Figure 2D). In addition, spontaneous locomotor activity decreased by 33.6 ± 1.4% (Figure 2E), more markedly during the dark phase.',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 4668,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'paragraph'},\n",
" 'text': 'To investigate differences in basal metabolic rate, we compared the energy expenditure required for locomotor activity. SirBACO mice had decreased resting energy expenditure, but no differences at higher activity levels (Figure S1). Body weight and composition were similar in SirBACO mice and non-transgenic littermates (Figure 2F). Food intake decreased by 15 ± 1.3% in SirBACO mice (Figure 2G), consistent with the preservation of normal body weight, in the face of decreased metabolic rate and activity.',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 5177,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'paragraph'},\n",
" 'text': 'In response to 24-hr food deprivation SirBACO mice showed a normal drop in RQ, reflecting increased fat oxidation (not shown). These data indicate that, although hypometabolic, SirBACO mice have normal rates of fatty acid oxidation. They also exhibited lower body temperature than control littermates under fed and fasted conditions (Figure 2H), but did not display changes in blood pressure or heart rate (Figure S2), suggesting that the effect on body temperature is secondary to decreased locomotion.',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 5681,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'title_2'},\n",
" 'text': 'SirBACO mice are protected from insulin-resistant diabetes',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 5740,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'paragraph'},\n",
" 'text': 'We next asked whether SirT1 overexpression affects the susceptibility to insulin resistance and diabetes in environmental and genetic models of these conditions. When SirBACO mice on an inbred C57BL/6J background were placed on a HFD or backcrossed onto db/db mice, they showed lower blood glucose and plasma insulin levels (Figures 3A–3B and Table S1) and better glucose tolerance (Figure 3C) than non-transgenic controls, despite similar body weight (Figure S3A), weight gain during the diet (Figure 3D), and body fat content (Figure 3E). We provisionally conclude that SirT1 overexpression does not improve glucose tolerance per se, but prevents the adverse effects of obesity on glucose metabolism.',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 6445,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'title_2'},\n",
" 'text': 'Catalytically inactive SirT1 fails to protect aging mice from glucose intolerance',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 6527,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'paragraph'},\n",
" 'text': 'To assess the specificity of these findings, we carried out glucose tolerance tests in aging transgenic mice expressing a catalytically inactive SirT1 transgene (H355Y). Unlike SirBACO mice, SirT1H355Y transgenics showed no differences in glucose tolerance from control littermates, demonstrating that SirT1 catalytic activity is required for its insulin-sensitizing effects (Figure S3B).',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 6916,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'title_2'},\n",
" 'text': 'Normal energy expenditure in diabetes-resistant SirBACO mice',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
" {'offset': 6977,\n",
" 'infons': {'section_type': 'RESULTS', 'type': 'paragraph'},\n",
" 'text': 'Based on the decrease of food intake and energy expenditure in SirBACO mice, we wanted to determine whether the transgenes ’ ability to improve glucose homeostasis in diabetes models could be explained by changes in physical activity or metabolic rate. In both the HFD and db/db model of insulin-resistant diabetes, body weight and composition were similar between SirT1 transgenic and non-transgenic mice (Figure 3D–3E). In contrast to the findings in SirBACO mice on a normal diet (Figure 2), there were no differences in metabolic rate, spontaneous locomotor activity, or food intake in SirBACO mice on a HFD or crossed onto db/db compared to littermate controls (Figure 3F-3G and data not shown). We conclude that SirT1 promotes a state of increased energy efficiency that protects against insulin resistance and hyperglycemia.',\n",
" 'sentences': [],\n",
" 'annotations': [],\n",
" 'relations': []},\n",
"],\n",
" 'annotations': [],\n",
" 'relations': []}"
],
"metadata": {
"cellView": "form",
"id": "QZCedyEGycAZ"
},
"id": "QZCedyEGycAZ",
"execution_count": 2,
"outputs": []
},
{
"cell_type": "code",
"source": [
"#@title dataframe source\n",
"tsv_string = '''\tpassage\tsentence_id\ts_position\tp_position\n",
"SirT1_0\t0\t0\t[0, 5]\t[0, 5]\n",
"gain_0\t0\t0\t[6, 10]\t[6, 10]\n",
"-_0\t0\t0\t[10, 11]\t[10, 11]\n",
"of_0\t0\t0\t[11, 13]\t[11, 13]\n",
"-_1\t0\t0\t[13, 14]\t[13, 14]\n",
"function_0\t0\t0\t[14, 22]\t[14, 22]\n",
"increases_0\t0\t0\t[23, 32]\t[23, 32]\n",
"energy_0\t0\t0\t[33, 39]\t[33, 39]\n",
"efficiency_0\t0\t0\t[40, 50]\t[40, 50]\n",
"and_0\t0\t0\t[51, 54]\t[51, 54]\n",
"prevents_0\t0\t0\t[55, 63]\t[55, 63]\n",
"diabetes_0\t0\t0\t[64, 72]\t[64, 72]\n",
"in_0\t0\t0\t[73, 75]\t[73, 75]\n",
"mice_0\t0\t0\t[76, 80]\t[76, 80]\n",
"Summary_0\t1\t0\t[0, 7]\t[0, 7]\n",
"In_0\t2\t0\t[0, 2]\t[0, 2]\n",
"yeast_0\t2\t0\t[3, 8]\t[3, 8]\n",
",_0\t2\t0\t[8, 9]\t[8, 9]\n",
"worms_0\t2\t0\t[10, 15]\t[10, 15]\n",
"and_1\t2\t0\t[16, 19]\t[16, 19]\n",
"flies_0\t2\t0\t[20, 25]\t[20, 25]\n",
",_1\t2\t0\t[25, 26]\t[25, 26]\n",
"an_0\t2\t0\t[27, 29]\t[27, 29]\n",
"extra_0\t2\t0\t[30, 35]\t[30, 35]\n",
"copy_0\t2\t0\t[36, 40]\t[36, 40]\n",
"of_1\t2\t0\t[41, 43]\t[41, 43]\n",
"the_0\t2\t0\t[44, 47]\t[44, 47]\n",
"gene_0\t2\t0\t[48, 52]\t[48, 52]\n",
"encoding_0\t2\t0\t[53, 61]\t[53, 61]\n",
"the_1\t2\t0\t[62, 65]\t[62, 65]\n",
"Sirtuin_0\t2\t0\t[66, 73]\t[66, 73]\n",
"Sir2_0\t2\t0\t[74, 78]\t[74, 78]\n",
"increases_1\t2\t0\t[79, 88]\t[79, 88]\n",
"metabolic_0\t2\t0\t[89, 98]\t[89, 98]\n",
"efficiency_1\t2\t0\t[99, 109]\t[99, 109]\n",
",_2\t2\t0\t[109, 110]\t[109, 110]\n",
"as_0\t2\t0\t[111, 113]\t[111, 113]\n",
"does_0\t2\t0\t[114, 118]\t[114, 118]\n",
"administration_0\t2\t0\t[119, 133]\t[119, 133]\n",
"of_2\t2\t0\t[134, 136]\t[134, 136]\n",
"polyphenols_0\t2\t0\t[137, 148]\t[137, 148]\n",
"like_0\t2\t0\t[149, 153]\t[149, 153]\n",
"resveratrol_0\t2\t0\t[154, 165]\t[154, 165]\n",
",_3\t2\t0\t[165, 166]\t[165, 166]\n",
"thought_0\t2\t0\t[167, 174]\t[167, 174]\n",
"to_0\t2\t0\t[175, 177]\t[175, 177]\n",
"act_0\t2\t0\t[178, 181]\t[178, 181]\n",
"through_0\t2\t0\t[182, 189]\t[182, 189]\n",
"Sirtuins_0\t2\t0\t[190, 198]\t[190, 198]\n",
"._0\t2\t0\t[198, 199]\t[198, 199]\n",
"But_0\t2\t1\t[0, 3]\t[200, 203]\n",
"evidence_0\t2\t1\t[4, 12]\t[204, 212]\n",
"that_0\t2\t1\t[13, 17]\t[213, 217]\n",
"Sirtuin_1\t2\t1\t[18, 25]\t[218, 225]\n",
"gain_1\t2\t1\t[26, 30]\t[226, 230]\n",
"-_2\t2\t1\t[30, 31]\t[230, 231]\n",
"of_3\t2\t1\t[31, 33]\t[231, 233]\n",
"-_3\t2\t1\t[33, 34]\t[233, 234]\n",
"function_1\t2\t1\t[34, 42]\t[234, 242]\n",
"results_0\t2\t1\t[43, 50]\t[243, 250]\n",
"in_1\t2\t1\t[51, 53]\t[251, 253]\n",
"increased_0\t2\t1\t[54, 63]\t[254, 263]\n",
"metabolic_1\t2\t1\t[64, 73]\t[264, 273]\n",
"efficiency_2\t2\t1\t[74, 84]\t[274, 284]\n",
"in_2\t2\t1\t[85, 87]\t[285, 287]\n",
"mammals_0\t2\t1\t[88, 95]\t[288, 295]\n",
"is_0\t2\t1\t[96, 98]\t[296, 298]\n",
"limited_0\t2\t1\t[99, 106]\t[299, 306]\n",
"._1\t2\t1\t[106, 107]\t[306, 307]\n",
"We_0\t2\t2\t[0, 2]\t[308, 310]\n",
"generated_0\t2\t2\t[3, 12]\t[311, 320]\n",
"transgenic_0\t2\t2\t[13, 23]\t[321, 331]\n",
"mice_1\t2\t2\t[24, 28]\t[332, 336]\n",
"with_0\t2\t2\t[29, 33]\t[337, 341]\n",
"moderate_0\t2\t2\t[34, 42]\t[342, 350]\n",
"overexpression_0\t2\t2\t[43, 57]\t[351, 365]\n",
"of_4\t2\t2\t[58, 60]\t[366, 368]\n",
"SirT1_1\t2\t2\t[61, 66]\t[369, 374]\n",
",_4\t2\t2\t[66, 67]\t[374, 375]\n",
"designed_0\t2\t2\t[68, 76]\t[376, 384]\n",
"to_1\t2\t2\t[77, 79]\t[385, 387]\n",
"mimic_0\t2\t2\t[80, 85]\t[388, 393]\n",
"the_2\t2\t2\t[86, 89]\t[394, 397]\n",
"Sirtuin_2\t2\t2\t[90, 97]\t[398, 405]\n",
"gain_2\t2\t2\t[98, 102]\t[406, 410]\n",
"-_4\t2\t2\t[102, 103]\t[410, 411]\n",
"of_5\t2\t2\t[103, 105]\t[411, 413]\n",
"-_5\t2\t2\t[105, 106]\t[413, 414]\n",
"function_2\t2\t2\t[106, 114]\t[414, 422]\n",
"that_1\t2\t2\t[115, 119]\t[423, 427]\n",
"improves_0\t2\t2\t[120, 128]\t[428, 436]\n",
"metabolism_0\t2\t2\t[129, 139]\t[437, 447]\n",
"in_3\t2\t2\t[140, 142]\t[448, 450]\n",
"C_0\t2\t2\t[143, 144]\t[451, 452]\n",
"._2\t2\t2\t[144, 145]\t[452, 453]\n",
"elegans_0\t2\t2\t[145, 152]\t[453, 460]\n",
"._3\t2\t2\t[152, 153]\t[460, 461]\n",
"These_0\t2\t3\t[0, 5]\t[462, 467]\n",
"mice_2\t2\t3\t[6, 10]\t[468, 472]\n",
"exhibit_0\t2\t3\t[11, 18]\t[473, 480]\n",
"normal_0\t2\t3\t[19, 25]\t[481, 487]\n",
"insulin_0\t2\t3\t[26, 33]\t[488, 495]\n",
"sensitivity_0\t2\t3\t[34, 45]\t[496, 507]\n",
",_5\t2\t3\t[45, 46]\t[507, 508]\n",
"but_0\t2\t3\t[47, 50]\t[509, 512]\n",
"decreased_0\t2\t3\t[51, 60]\t[513, 522]\n",
"food_0\t2\t3\t[61, 65]\t[523, 527]\n",
"intake_0\t2\t3\t[66, 72]\t[528, 534]\n",
"and_2\t2\t3\t[73, 76]\t[535, 538]\n",
"locomotor_0\t2\t3\t[77, 86]\t[539, 548]\n",
"activity_0\t2\t3\t[87, 95]\t[549, 557]\n",
",_6\t2\t3\t[95, 96]\t[557, 558]\n",
"resulting_0\t2\t3\t[97, 106]\t[559, 568]\n",
"in_4\t2\t3\t[107, 109]\t[569, 571]\n",
"decreased_1\t2\t3\t[110, 119]\t[572, 581]\n",
"energy_1\t2\t3\t[120, 126]\t[582, 588]\n",
"expenditure_0\t2\t3\t[127, 138]\t[589, 600]\n",
"._4\t2\t3\t[138, 139]\t[600, 601]\n",
"However_0\t2\t4\t[0, 7]\t[602, 609]\n",
",_7\t2\t4\t[7, 8]\t[609, 610]\n",
"in_5\t2\t4\t[9, 11]\t[611, 613]\n",
"various_0\t2\t4\t[12, 19]\t[614, 621]\n",
"models_0\t2\t4\t[20, 26]\t[622, 628]\n",
"of_6\t2\t4\t[27, 29]\t[629, 631]\n",
"insulin_1\t2\t4\t[30, 37]\t[632, 639]\n",
"resistance_0\t2\t4\t[38, 48]\t[640, 650]\n",
"and_3\t2\t4\t[49, 52]\t[651, 654]\n",
"diabetes_1\t2\t4\t[53, 61]\t[655, 663]\n",
",_8\t2\t4\t[61, 62]\t[663, 664]\n",
"SirT1_2\t2\t4\t[63, 68]\t[665, 670]\n",
"transgenics_0\t2\t4\t[69, 80]\t[671, 682]\n",
"display_0\t2\t4\t[81, 88]\t[683, 690]\n",
"improved_0\t2\t4\t[89, 97]\t[691, 699]\n",
"glucose_0\t2\t4\t[98, 105]\t[700, 707]\n",
"tolerance_0\t2\t4\t[106, 115]\t[708, 717]\n",
"due_0\t2\t4\t[116, 119]\t[718, 721]\n",
"to_2\t2\t4\t[120, 122]\t[722, 724]\n",
"decreased_2\t2\t4\t[123, 132]\t[725, 734]\n",
"hepatic_0\t2\t4\t[133, 140]\t[735, 742]\n",
"glucose_1\t2\t4\t[141, 148]\t[743, 750]\n",
"production_0\t2\t4\t[149, 159]\t[751, 761]\n",
"and_4\t2\t4\t[160, 163]\t[762, 765]\n",
"increased_1\t2\t4\t[164, 173]\t[766, 775]\n",
"adiponectin_0\t2\t4\t[174, 185]\t[776, 787]\n",
"levels_0\t2\t4\t[186, 192]\t[788, 794]\n",
",_9\t2\t4\t[192, 193]\t[794, 795]\n",
"without_0\t2\t4\t[194, 201]\t[796, 803]\n",
"changes_0\t2\t4\t[202, 209]\t[804, 811]\n",
"in_6\t2\t4\t[210, 212]\t[812, 814]\n",
"body_0\t2\t4\t[213, 217]\t[815, 819]\n",
"weight_0\t2\t4\t[218, 224]\t[820, 826]\n",
"or_0\t2\t4\t[225, 227]\t[827, 829]\n",
"composition_0\t2\t4\t[228, 239]\t[830, 841]\n",
"._5\t2\t4\t[239, 240]\t[841, 842]\n",
"We_1\t2\t5\t[0, 2]\t[843, 845]\n",
"conclude_0\t2\t5\t[3, 11]\t[846, 854]\n",
"that_2\t2\t5\t[12, 16]\t[855, 859]\n",
"SirT1_3\t2\t5\t[17, 22]\t[860, 865]\n",
"gain_3\t2\t5\t[23, 27]\t[866, 870]\n",
"-_6\t2\t5\t[27, 28]\t[870, 871]\n",
"of_7\t2\t5\t[28, 30]\t[871, 873]\n",
"-_7\t2\t5\t[30, 31]\t[873, 874]\n",
"function_3\t2\t5\t[31, 39]\t[874, 882]\n",
"primes_0\t2\t5\t[40, 46]\t[883, 889]\n",
"the_3\t2\t5\t[47, 50]\t[890, 893]\n",
"organism_0\t2\t5\t[51, 59]\t[894, 902]\n",
"for_0\t2\t5\t[60, 63]\t[903, 906]\n",
"metabolic_2\t2\t5\t[64, 73]\t[907, 916]\n",
"adaptation_0\t2\t5\t[74, 84]\t[917, 927]\n",
"to_3\t2\t5\t[85, 87]\t[928, 930]\n",
"insulin_2\t2\t5\t[88, 95]\t[931, 938]\n",
"resistance_1\t2\t5\t[96, 106]\t[939, 949]\n",
",_10\t2\t5\t[106, 107]\t[949, 950]\n",
"increasing_0\t2\t5\t[108, 118]\t[951, 961]\n",
"hepatic_1\t2\t5\t[119, 126]\t[962, 969]\n",
"insulin_3\t2\t5\t[127, 134]\t[970, 977]\n",
"sensitivity_1\t2\t5\t[135, 146]\t[978, 989]\n",
"and_5\t2\t5\t[147, 150]\t[990, 993]\n",
"decreasing_0\t2\t5\t[151, 161]\t[994, 1004]\n",
"whole_0\t2\t5\t[162, 167]\t[1005, 1010]\n",
"-_8\t2\t5\t[167, 168]\t[1010, 1011]\n",
"body_1\t2\t5\t[168, 172]\t[1011, 1015]\n",
"energy_2\t2\t5\t[173, 179]\t[1016, 1022]\n",
"requirements_0\t2\t5\t[180, 192]\t[1023, 1035]\n",
"._6\t2\t5\t[192, 193]\t[1035, 1036]\n",
"These_1\t2\t6\t[0, 5]\t[1037, 1042]\n",
"findings_0\t2\t6\t[6, 14]\t[1043, 1051]\n",
"have_0\t2\t6\t[15, 19]\t[1052, 1056]\n",
"important_0\t2\t6\t[20, 29]\t[1057, 1066]\n",
"implications_0\t2\t6\t[30, 42]\t[1067, 1079]\n",
"for_1\t2\t6\t[43, 46]\t[1080, 1083]\n",
"Sirtuin_3\t2\t6\t[47, 54]\t[1084, 1091]\n",
"-_9\t2\t6\t[54, 55]\t[1091, 1092]\n",
"based_0\t2\t6\t[55, 60]\t[1092, 1097]\n",
"therapies_0\t2\t6\t[61, 70]\t[1098, 1107]\n",
"in_7\t2\t6\t[71, 73]\t[1108, 1110]\n",
"humans_0\t2\t6\t[74, 80]\t[1111, 1117]\n",
"._7\t2\t6\t[80, 81]\t[1117, 1118]\n",
"Introduction_0\t3\t0\t[0, 12]\t[0, 12]\n",
"The_0\t4\t0\t[0, 3]\t[0, 3]\n",
"increased_2\t4\t0\t[4, 13]\t[4, 13]\n",
"prevalence_0\t4\t0\t[14, 24]\t[14, 24]\n",
"of_8\t4\t0\t[25, 27]\t[25, 27]\n",
"obesity_0\t4\t0\t[28, 35]\t[28, 35]\n",
"and_6\t4\t0\t[36, 39]\t[36, 39]\n",
"diabetes_2\t4\t0\t[40, 48]\t[40, 48]\n",
",_11\t4\t0\t[48, 49]\t[48, 49]\n",
"with_1\t4\t0\t[50, 54]\t[50, 54]\n",
"the_4\t4\t0\t[55, 58]\t[55, 58]\n",
"attendant_0\t4\t0\t[59, 68]\t[59, 68]\n",
"increase_0\t4\t0\t[69, 77]\t[69, 77]\n",
"in_8\t4\t0\t[78, 80]\t[78, 80]\n",
"morbidity_0\t4\t0\t[81, 90]\t[81, 90]\n",
"and_7\t4\t0\t[91, 94]\t[91, 94]\n",
"mortality_0\t4\t0\t[95, 104]\t[95, 104]\n",
",_12\t4\t0\t[104, 105]\t[104, 105]\n",
"pose_0\t4\t0\t[106, 110]\t[106, 110]\n",
"a_0\t4\t0\t[111, 112]\t[111, 112]\n",
"substantial_0\t4\t0\t[113, 124]\t[113, 124]\n",
"therapeutic_0\t4\t0\t[125, 136]\t[125, 136]\n",
"challenge_0\t4\t0\t[137, 146]\t[137, 146]\n",
"._8\t4\t0\t[146, 147]\t[146, 147]\n",
"Genetic_0\t4\t1\t[0, 7]\t[148, 155]\n",
"screens_0\t4\t1\t[8, 15]\t[156, 163]\n",
"in_9\t4\t1\t[16, 18]\t[164, 166]\n",
"lower_0\t4\t1\t[19, 24]\t[167, 172]\n",
"organisms_0\t4\t1\t[25, 34]\t[173, 182]\n",
"provide_0\t4\t1\t[35, 42]\t[183, 190]\n",
"evidence_1\t4\t1\t[43, 51]\t[191, 199]\n",
"that_3\t4\t1\t[52, 56]\t[200, 204]\n",
"gain_4\t4\t1\t[57, 61]\t[205, 209]\n",
"-_10\t4\t1\t[61, 62]\t[209, 210]\n",
"of_9\t4\t1\t[62, 64]\t[210, 212]\n",
"-_11\t4\t1\t[64, 65]\t[212, 213]\n",
"function_4\t4\t1\t[65, 73]\t[213, 221]\n",
"of_10\t4\t1\t[74, 76]\t[222, 224]\n",
"the_5\t4\t1\t[77, 80]\t[225, 228]\n",
"deacetylase_0\t4\t1\t[81, 92]\t[229, 240]\n",
"Sir2_1\t4\t1\t[93, 97]\t[241, 245]\n",
"results_1\t4\t1\t[98, 105]\t[246, 253]\n",
"in_10\t4\t1\t[106, 108]\t[254, 256]\n",
"beneficial_0\t4\t1\t[109, 119]\t[257, 267]\n",
"metabolic_3\t4\t1\t[120, 129]\t[268, 277]\n",
"effects_0\t4\t1\t[130, 137]\t[278, 285]\n",
"and_8\t4\t1\t[138, 141]\t[286, 289]\n",
"lifespan_0\t4\t1\t[142, 150]\t[290, 298]\n",
"extension_0\t4\t1\t[151, 160]\t[299, 308]\n",
"._9\t4\t1\t[160, 161]\t[308, 309]\n",
"Sirtuin_4\t4\t2\t[0, 7]\t[310, 317]\n",
"agonists_0\t4\t2\t[8, 16]\t[318, 326]\n",
"increase_1\t4\t2\t[17, 25]\t[327, 335]\n",
"metabolic_4\t4\t2\t[26, 35]\t[336, 345]\n",
"efficiency_3\t4\t2\t[36, 46]\t[346, 356]\n",
"in_11\t4\t2\t[47, 49]\t[357, 359]\n",
"rodents_0\t4\t2\t[50, 57]\t[360, 367]\n",
"through_1\t4\t2\t[58, 65]\t[368, 375]\n",
"a_1\t4\t2\t[66, 67]\t[376, 377]\n",
"mechanism_0\t4\t2\t[68, 77]\t[378, 387]\n",
"bearing_0\t4\t2\t[78, 85]\t[388, 395]\n",
"similarity_0\t4\t2\t[86, 96]\t[396, 406]\n",
"with_2\t4\t2\t[97, 101]\t[407, 411]\n",
"calorie_0\t4\t2\t[102, 109]\t[412, 419]\n",
"restriction_0\t4\t2\t[110, 121]\t[420, 431]\n",
"._10\t4\t2\t[121, 122]\t[431, 432]\n",
"However_1\t4\t3\t[0, 7]\t[433, 440]\n",
",_13\t4\t3\t[7, 8]\t[440, 441]\n",
"the_6\t4\t3\t[9, 12]\t[442, 445]\n",
"specificity_0\t4\t3\t[13, 24]\t[446, 457]\n",
"of_11\t4\t3\t[25, 27]\t[458, 460]\n",
"these_0\t4\t3\t[28, 33]\t[461, 466]\n",
"compounds_0\t4\t3\t[34, 43]\t[467, 476]\n",
"remains_0\t4\t3\t[44, 51]\t[477, 484]\n",
"undefined_0\t4\t3\t[52, 61]\t[485, 494]\n",
"._11\t4\t3\t[61, 62]\t[494, 495]\n",
"The_1\t5\t0\t[0, 3]\t[0, 3]\n",
"function_5\t5\t0\t[4, 12]\t[4, 12]\n",
"of_12\t5\t0\t[13, 15]\t[13, 15]\n",
"mammalian_0\t5\t0\t[16, 25]\t[16, 25]\n",
"Sir2α_0\t5\t0\t[26, 31]\t[26, 31]\n",
"(_0\t5\t0\t[32, 33]\t[32, 33]\n",
"also_0\t5\t0\t[33, 37]\t[33, 37]\n",
"known_0\t5\t0\t[38, 43]\t[38, 43]\n",
"as_1\t5\t0\t[44, 46]\t[44, 46]\n",
"SirT1_4\t5\t0\t[47, 52]\t[47, 52]\n",
")_0\t5\t0\t[52, 53]\t[52, 53]\n",
"in_12\t5\t0\t[54, 56]\t[54, 56]\n",
"metabolism_1\t5\t0\t[57, 67]\t[57, 67]\n",
"is_1\t5\t0\t[68, 70]\t[68, 70]\n",
"controversial_0\t5\t0\t[71, 84]\t[71, 84]\n",
"._12\t5\t0\t[84, 85]\t[84, 85]\n",
"Two_0\t5\t1\t[0, 3]\t[86, 89]\n",
"models_1\t5\t1\t[4, 10]\t[90, 96]\n",
"of_13\t5\t1\t[11, 13]\t[97, 99]\n",
"SirT1_5\t5\t1\t[14, 19]\t[100, 105]\n",
"gain_5\t5\t1\t[20, 24]\t[106, 110]\n",
"-_12\t5\t1\t[24, 25]\t[110, 111]\n",
"of_14\t5\t1\t[25, 27]\t[111, 113]\n",
"-_13\t5\t1\t[27, 28]\t[113, 114]\n",
"function_6\t5\t1\t[28, 36]\t[114, 122]\n",
"in_13\t5\t1\t[37, 39]\t[123, 125]\n",
"either_0\t5\t1\t[40, 46]\t[126, 132]\n",
"pancreatic_0\t5\t1\t[47, 57]\t[133, 143]\n",
"β_0\t5\t1\t[58, 59]\t[144, 145]\n",
"cells_0\t5\t1\t[60, 65]\t[146, 151]\n",
"or_1\t5\t1\t[66, 68]\t[152, 154]\n",
"adipocytes_0\t5\t1\t[69, 79]\t[155, 165]\n",
"and_9\t5\t1\t[80, 83]\t[166, 169]\n",
"brain_0\t5\t1\t[84, 89]\t[170, 175]\n",
"result_0\t5\t1\t[90, 96]\t[176, 182]\n",
"in_14\t5\t1\t[97, 99]\t[183, 185]\n",
"improved_1\t5\t1\t[100, 108]\t[186, 194]\n",
"insulin_4\t5\t1\t[109, 116]\t[195, 202]\n",
"secretion_0\t5\t1\t[117, 126]\t[203, 212]\n",
"and_10\t5\t1\t[127, 130]\t[213, 216]\n",
"sensitivity_2\t5\t1\t[131, 142]\t[217, 228]\n",
",_14\t5\t1\t[142, 143]\t[228, 229]\n",
"respectively_0\t5\t1\t[144, 156]\t[230, 242]\n",
"._13\t5\t1\t[156, 157]\t[242, 243]\n",
"But_1\t5\t2\t[0, 3]\t[244, 247]\n",
"increasing_1\t5\t2\t[4, 14]\t[248, 258]\n",
"SirT1_6\t5\t2\t[15, 20]\t[259, 264]\n",
"expression_0\t5\t2\t[21, 31]\t[265, 275]\n",
"in_15\t5\t2\t[32, 34]\t[276, 278]\n",
"liver_0\t5\t2\t[35, 40]\t[279, 284]\n",
"impairs_0\t5\t2\t[41, 48]\t[285, 292]\n",
"glucose_2\t5\t2\t[49, 56]\t[293, 300]\n",
"tolerance_1\t5\t2\t[57, 66]\t[301, 310]\n",
",_15\t5\t2\t[66, 67]\t[310, 311]\n",
"and_11\t5\t2\t[68, 71]\t[312, 315]\n",
"resveratrol_1\t5\t2\t[72, 83]\t[316, 327]\n",
"increases_2\t5\t2\t[84, 93]\t[328, 337]\n",
"glucose_3\t5\t2\t[94, 101]\t[338, 345]\n",
"production_1\t5\t2\t[102, 112]\t[346, 356]\n",
"by_0\t5\t2\t[113, 115]\t[357, 359]\n",
"hepatoma_0\t5\t2\t[116, 124]\t[360, 368]\n",
"cells_1\t5\t2\t[125, 130]\t[369, 374]\n",
"._14\t5\t2\t[130, 131]\t[374, 375]\n",
"Thus_0\t5\t3\t[0, 4]\t[376, 380]\n",
",_16\t5\t3\t[4, 5]\t[380, 381]\n",
"it_0\t5\t3\t[6, 8]\t[382, 384]\n",
"remains_1\t5\t3\t[9, 16]\t[385, 392]\n",
"unclear_0\t5\t3\t[17, 24]\t[393, 400]\n",
"whether_0\t5\t3\t[25, 32]\t[401, 408]\n",
"chronic_0\t5\t3\t[33, 40]\t[409, 416]\n",
",_17\t5\t3\t[40, 41]\t[416, 417]\n",
"ubiquitous_0\t5\t3\t[42, 52]\t[418, 428]\n",
"SirT1_7\t5\t3\t[53, 58]\t[429, 434]\n",
"activation_0\t5\t3\t[59, 69]\t[435, 445]\n",
"ultimately_0\t5\t3\t[70, 80]\t[446, 456]\n",
"benefits_0\t5\t3\t[81, 89]\t[457, 465]\n",
"or_2\t5\t3\t[90, 92]\t[466, 468]\n",
"impairs_1\t5\t3\t[93, 100]\t[469, 476]\n",
"metabolic_5\t5\t3\t[101, 110]\t[477, 486]\n",
"control_0\t5\t3\t[111, 118]\t[487, 494]\n",
"._15\t5\t3\t[118, 119]\t[494, 495]\n",
"To_0\t6\t0\t[0, 2]\t[0, 2]\n",
"address_0\t6\t0\t[3, 10]\t[3, 10]\n",
"this_0\t6\t0\t[11, 15]\t[11, 15]\n",
"question_0\t6\t0\t[16, 24]\t[16, 24]\n",
",_18\t6\t0\t[24, 25]\t[24, 25]\n",
"we_0\t6\t0\t[26, 28]\t[26, 28]\n",
"developed_0\t6\t0\t[29, 38]\t[29, 38]\n",
"transgenic_1\t6\t0\t[39, 49]\t[39, 49]\n",
"mice_3\t6\t0\t[50, 54]\t[50, 54]\n",
"designed_1\t6\t0\t[55, 63]\t[55, 63]\n",
"to_4\t6\t0\t[64, 66]\t[64, 66]\n",
"mimic_1\t6\t0\t[67, 72]\t[67, 72]\n",
"the_7\t6\t0\t[73, 76]\t[73, 76]\n",
"chromosomal_0\t6\t0\t[77, 88]\t[77, 88]\n",
"duplication_0\t6\t0\t[89, 100]\t[89, 100]\n",
"leading_0\t6\t0\t[101, 108]\t[101, 108]\n",
"to_5\t6\t0\t[109, 111]\t[109, 111]\n",
"moderate_1\t6\t0\t[112, 120]\t[112, 120]\n",
"gain_6\t6\t0\t[121, 125]\t[121, 125]\n",
"-_14\t6\t0\t[125, 126]\t[125, 126]\n",
"of_15\t6\t0\t[126, 128]\t[126, 128]\n",
"-_15\t6\t0\t[128, 129]\t[128, 129]\n",
"function_7\t6\t0\t[129, 137]\t[129, 137]\n",
"that_4\t6\t0\t[138, 142]\t[138, 142]\n",
"improves_1\t6\t0\t[143, 151]\t[143, 151]\n",
"metabolism_2\t6\t0\t[152, 162]\t[152, 162]\n",
"in_16\t6\t0\t[163, 165]\t[163, 165]\n",
"C_1\t6\t0\t[166, 167]\t[166, 167]\n",
"._16\t6\t0\t[167, 168]\t[167, 168]\n",
"elegans_1\t6\t0\t[168, 175]\t[168, 175]\n",
"._17\t6\t0\t[175, 176]\t[175, 176]\n",
"In_1\t6\t1\t[0, 2]\t[177, 179]\n",
"the_8\t6\t1\t[3, 6]\t[180, 183]\n",
"latter_0\t6\t1\t[7, 13]\t[184, 190]\n",
"organism_1\t6\t1\t[14, 22]\t[191, 199]\n",
",_19\t6\t1\t[22, 23]\t[199, 200]\n",
"Sir2_2\t6\t1\t[24, 28]\t[201, 205]\n",
"function_8\t6\t1\t[29, 37]\t[206, 214]\n",
"requires_0\t6\t1\t[38, 46]\t[215, 223]\n",
"the_9\t6\t1\t[47, 50]\t[224, 227]\n",
"FoxO1_0\t6\t1\t[51, 56]\t[228, 233]\n",
"ortholog_0\t6\t1\t[57, 65]\t[234, 242]\n",
"daf_0\t6\t1\t[66, 69]\t[243, 246]\n",
"-_16\t6\t1\t[69, 70]\t[246, 247]\n",
"16_0\t6\t1\t[70, 72]\t[247, 249]\n",
"._18\t6\t1\t[72, 73]\t[249, 250]\n",
"Thus_1\t6\t2\t[0, 4]\t[251, 255]\n",
",_20\t6\t2\t[4, 5]\t[255, 256]\n",
"in_17\t6\t2\t[6, 8]\t[257, 259]\n",
"our_0\t6\t2\t[9, 12]\t[260, 263]\n",
"studies_0\t6\t2\t[13, 20]\t[264, 271]\n",
"we_1\t6\t2\t[21, 23]\t[272, 274]\n",
"sought_0\t6\t2\t[24, 30]\t[275, 281]\n",
"to_6\t6\t2\t[31, 33]\t[282, 284]\n",
"address_1\t6\t2\t[34, 41]\t[285, 292]\n",
"whether_1\t6\t2\t[42, 49]\t[293, 300]\n",
"SirT1_8\t6\t2\t[50, 55]\t[301, 306]\n",
"gain_7\t6\t2\t[56, 60]\t[307, 311]\n",
"-_17\t6\t2\t[60, 61]\t[311, 312]\n",
"of_16\t6\t2\t[61, 63]\t[312, 314]\n",
"-_18\t6\t2\t[63, 64]\t[314, 315]\n",
"function_9\t6\t2\t[64, 72]\t[315, 323]\n",
"mediates_0\t6\t2\t[73, 81]\t[324, 332]\n",
"its_0\t6\t2\t[82, 85]\t[333, 336]\n",
"effects_1\t6\t2\t[86, 93]\t[337, 344]\n",
"through_2\t6\t2\t[94, 101]\t[345, 352]\n",
"FoxO1_1\t6\t2\t[102, 107]\t[353, 358]\n",
"._19\t6\t2\t[107, 108]\t[358, 359]\n",
"Results_0\t7\t0\t[0, 7]\t[0, 7]\n",
"Generation_0\t8\t0\t[0, 10]\t[0, 10]\n",
"and_12\t8\t0\t[11, 14]\t[11, 14]\n",
"analysis_0\t8\t0\t[15, 23]\t[15, 23]\n",
"of_17\t8\t0\t[24, 26]\t[24, 26]\n",
"SirT1_9\t8\t0\t[27, 32]\t[27, 32]\n",
"Transgenic_0\t8\t0\t[33, 43]\t[33, 43]\n",
"Mice_0\t8\t0\t[44, 48]\t[44, 48]\n",
"To_1\t9\t0\t[0, 2]\t[0, 2]\n",
"test_0\t9\t0\t[3, 7]\t[3, 7]\n",
"the_10\t9\t0\t[8, 11]\t[8, 11]\n",
"hypothesis_0\t9\t0\t[12, 22]\t[12, 22]\n",
"that_5\t9\t0\t[23, 27]\t[23, 27]\n",
"SirT1_10\t9\t0\t[28, 33]\t[28, 33]\n",
"participates_0\t9\t0\t[34, 46]\t[34, 46]\n",
"in_18\t9\t0\t[47, 49]\t[47, 49]\n",
"the_11\t9\t0\t[50, 53]\t[50, 53]\n",
"regulation_0\t9\t0\t[54, 64]\t[54, 64]\n",
"of_18\t9\t0\t[65, 67]\t[65, 67]\n",
"metabolism_3\t9\t0\t[68, 78]\t[68, 78]\n",
",_21\t9\t0\t[78, 79]\t[78, 79]\n",
"we_2\t9\t0\t[80, 82]\t[80, 82]\n",
"generated_1\t9\t0\t[83, 92]\t[83, 92]\n",
"BAC_0\t9\t0\t[93, 96]\t[93, 96]\n",
"transgenic_2\t9\t0\t[97, 107]\t[97, 107]\n",
"mice_4\t9\t0\t[108, 112]\t[108, 112]\n",
"overexpressing_0\t9\t0\t[113, 127]\t[113, 127]\n",
"SirT1_11\t9\t0\t[128, 133]\t[128, 133]\n",
"(_1\t9\t0\t[134, 135]\t[134, 135]\n",
"SirT1_12\t9\t0\t[135, 140]\t[135, 140]\n",
"Bacterial_0\t9\t0\t[141, 150]\t[141, 150]\n",
"Artificial_0\t9\t0\t[151, 161]\t[151, 161]\n",
"Chromosome_0\t9\t0\t[162, 172]\t[162, 172]\n",
"Overexpressor_0\t9\t0\t[173, 186]\t[173, 186]\n",
",_22\t9\t0\t[186, 187]\t[186, 187]\n",
"SirBACO_0\t9\t0\t[188, 195]\t[188, 195]\n",
")._0\t9\t0\t[195, 197]\t[195, 197]\n",
"SirBACO_1\t9\t1\t[0, 7]\t[198, 205]\n",
"mice_5\t9\t1\t[8, 12]\t[206, 210]\n",
"were_0\t9\t1\t[13, 17]\t[211, 215]\n",
"born_0\t9\t1\t[18, 22]\t[216, 220]\n",
"in_19\t9\t1\t[23, 25]\t[221, 223]\n",
"Mendelian_0\t9\t1\t[26, 35]\t[224, 233]\n",
"ratios_0\t9\t1\t[36, 42]\t[234, 240]\n",
"and_13\t9\t1\t[43, 46]\t[241, 244]\n",
"displayed_0\t9\t1\t[47, 56]\t[245, 254]\n",
"no_0\t9\t1\t[57, 59]\t[255, 257]\n",
"gross_0\t9\t1\t[60, 65]\t[258, 263]\n",
"anatomical_0\t9\t1\t[66, 76]\t[264, 274]\n",
"or_3\t9\t1\t[77, 79]\t[275, 277]\n",
"reproductive_0\t9\t1\t[80, 92]\t[278, 290]\n",
"defects_0\t9\t1\t[93, 100]\t[291, 298]\n",
"._20\t9\t1\t[100, 101]\t[298, 299]\n",
"SirT1_13\t9\t2\t[0, 5]\t[300, 305]\n",
"levels_1\t9\t2\t[6, 12]\t[306, 312]\n",
"were_1\t9\t2\t[13, 17]\t[313, 317]\n",
"two_0\t9\t2\t[18, 21]\t[318, 321]\n",
"-_19\t9\t2\t[21, 22]\t[321, 322]\n",
"to_7\t9\t2\t[23, 25]\t[323, 325]\n",
"threefold_0\t9\t2\t[26, 35]\t[326, 335]\n",
"higher_0\t9\t2\t[36, 42]\t[336, 342]\n",
"than_0\t9\t2\t[43, 47]\t[343, 347]\n",
"control_1\t9\t2\t[48, 55]\t[348, 355]\n",
"littermates_0\t9\t2\t[56, 67]\t[356, 367]\n",
",_23\t9\t2\t[67, 68]\t[367, 368]\n",
"except_0\t9\t2\t[69, 75]\t[369, 375]\n",
"in_20\t9\t2\t[76, 78]\t[376, 378]\n",
"the_12\t9\t2\t[79, 82]\t[379, 382]\n",
"spleen_0\t9\t2\t[83, 89]\t[383, 389]\n",
"(~_0\t9\t2\t[90, 92]\t[390, 392]\n",
"seven_0\t9\t2\t[92, 97]\t[392, 397]\n",
"-_20\t9\t2\t[97, 98]\t[397, 398]\n",
"fold_0\t9\t2\t[98, 102]\t[398, 402]\n",
"higher_1\t9\t2\t[103, 109]\t[403, 409]\n",
"),_0\t9\t2\t[109, 111]\t[409, 411]\n",
"and_14\t9\t2\t[112, 115]\t[412, 415]\n",
"distribution_0\t9\t2\t[116, 128]\t[416, 428]\n",
"patterns_0\t9\t2\t[129, 137]\t[429, 437]\n",
"were_2\t9\t2\t[138, 142]\t[438, 442]\n",
"indistinguishable_0\t9\t2\t[143, 160]\t[443, 460]\n",
"from_0\t9\t2\t[161, 165]\t[461, 465]\n",
"those_0\t9\t2\t[166, 171]\t[466, 471]\n",
"of_19\t9\t2\t[172, 174]\t[472, 474]\n",
"the_13\t9\t2\t[175, 178]\t[475, 478]\n",
"endogenous_0\t9\t2\t[179, 189]\t[479, 489]\n",
"protein_0\t9\t2\t[190, 197]\t[490, 497]\n",
"in_21\t9\t2\t[198, 200]\t[498, 500]\n",
"all_0\t9\t2\t[201, 204]\t[501, 504]\n",
"tissues_0\t9\t2\t[205, 212]\t[505, 512]\n",
"examined_0\t9\t2\t[213, 221]\t[513, 521]\n",
"(_2\t9\t2\t[222, 223]\t[522, 523]\n",
"Figure_0\t9\t2\t[223, 229]\t[523, 529]\n",
"1A_0\t9\t2\t[230, 232]\t[530, 532]\n",
"–_0\t9\t2\t[232, 233]\t[532, 533]\n",
"1B_0\t9\t2\t[233, 235]\t[533, 535]\n",
")._1\t9\t2\t[235, 237]\t[535, 537]\n",
"SirT1_14\t9\t3\t[0, 5]\t[538, 543]\n",
"overexpression_1\t9\t3\t[6, 20]\t[544, 558]\n",
"was_0\t9\t3\t[21, 24]\t[559, 562]\n",
"preserved_0\t9\t3\t[25, 34]\t[563, 572]\n",
"when_0\t9\t3\t[35, 39]\t[573, 577]\n",
"SirBACO_2\t9\t3\t[40, 47]\t[578, 585]\n",
"mice_6\t9\t3\t[48, 52]\t[586, 590]\n",
"were_3\t9\t3\t[53, 57]\t[591, 595]\n",
"backcrossed_0\t9\t3\t[58, 69]\t[596, 607]\n",
"onto_0\t9\t3\t[70, 74]\t[608, 612]\n",
"the_14\t9\t3\t[75, 78]\t[613, 616]\n",
"db_0\t9\t3\t[79, 81]\t[617, 619]\n",
"/_0\t9\t3\t[81, 82]\t[619, 620]\n",
"db_1\t9\t3\t[82, 84]\t[620, 622]\n",
"background_0\t9\t3\t[85, 95]\t[623, 633]\n",
"(_3\t9\t3\t[96, 97]\t[634, 635]\n",
"Figure_1\t9\t3\t[97, 103]\t[635, 641]\n",
"1C_0\t9\t3\t[104, 106]\t[642, 644]\n",
")._2\t9\t3\t[106, 108]\t[644, 646]\n",
"To_2\t9\t4\t[0, 2]\t[647, 649]\n",
"probe_0\t9\t4\t[3, 8]\t[650, 655]\n",
"the_15\t9\t4\t[9, 12]\t[656, 659]\n",
"transgene_0\t9\t4\t[13, 22]\t[660, 669]\n",
"’_0\t9\t4\t[22, 23]\t[669, 670]\n",
"s_0\t9\t4\t[23, 24]\t[670, 671]\n",
"function_10\t9\t4\t[25, 33]\t[672, 680]\n",
",_24\t9\t4\t[33, 34]\t[680, 681]\n",
"we_3\t9\t4\t[35, 37]\t[682, 684]\n",
"intercrossed_0\t9\t4\t[38, 50]\t[685, 697]\n",
"SirBACO_3\t9\t4\t[51, 58]\t[698, 705]\n",
"with_3\t9\t4\t[59, 63]\t[706, 710]\n",
"Sirt1_0\t9\t4\t[64, 69]\t[711, 716]\n",
"−/−_0\t9\t4\t[69, 72]\t[716, 719]\n",
"mice_7\t9\t4\t[73, 77]\t[720, 724]\n",
"._21\t9\t4\t[77, 78]\t[724, 725]\n",
"The_2\t9\t5\t[0, 3]\t[726, 729]\n",
"transgene_1\t9\t5\t[4, 13]\t[730, 739]\n",
"readily_0\t9\t5\t[14, 21]\t[740, 747]\n",
"rescued_0\t9\t5\t[22, 29]\t[748, 755]\n",
"developmental_0\t9\t5\t[30, 43]\t[756, 769]\n",
"defects_1\t9\t5\t[44, 51]\t[770, 777]\n",
"and_15\t9\t5\t[52, 55]\t[778, 781]\n",
"postnatal_0\t9\t5\t[56, 65]\t[782, 791]\n",
"lethality_0\t9\t5\t[66, 75]\t[792, 801]\n",
"of_20\t9\t5\t[76, 78]\t[802, 804]\n",
"Sirt1_1\t9\t5\t[79, 84]\t[805, 810]\n",
"−/−_1\t9\t5\t[84, 87]\t[810, 813]\n",
"mice_8\t9\t5\t[88, 92]\t[814, 818]\n",
"(_4\t9\t5\t[93, 94]\t[819, 820]\n",
"data_0\t9\t5\t[94, 98]\t[820, 824]\n",
"not_0\t9\t5\t[99, 102]\t[825, 828]\n",
"shown_0\t9\t5\t[103, 108]\t[829, 834]\n",
")._3\t9\t5\t[108, 110]\t[834, 836]\n",
"These_2\t9\t6\t[0, 5]\t[837, 842]\n",
"findings_1\t9\t6\t[6, 14]\t[843, 851]\n",
"are_0\t9\t6\t[15, 18]\t[852, 855]\n",
"consistent_0\t9\t6\t[19, 29]\t[856, 866]\n",
"the_16\t9\t6\t[30, 33]\t[867, 870]\n",
"generation_0\t9\t6\t[34, 44]\t[871, 881]\n",
"of_21\t9\t6\t[45, 47]\t[882, 884]\n",
"a_2\t9\t6\t[48, 49]\t[885, 886]\n",
"mouse_0\t9\t6\t[50, 55]\t[887, 892]\n",
"model_0\t9\t6\t[56, 61]\t[893, 898]\n",
"of_22\t9\t6\t[62, 64]\t[899, 901]\n",
"SirT1_15\t9\t6\t[65, 70]\t[902, 907]\n",
"gain_8\t9\t6\t[71, 75]\t[908, 912]\n",
"-_21\t9\t6\t[75, 76]\t[912, 913]\n",
"of_23\t9\t6\t[76, 78]\t[913, 915]\n",
"-_22\t9\t6\t[78, 79]\t[915, 916]\n",
"function_11\t9\t6\t[79, 87]\t[916, 924]\n",
"._22\t9\t6\t[87, 88]\t[924, 925]\n",
"Altered_0\t10\t0\t[0, 7]\t[0, 7]\n",
"energy_3\t10\t0\t[8, 14]\t[8, 14]\n",
"balance_0\t10\t0\t[15, 22]\t[15, 22]\n",
"in_22\t10\t0\t[23, 25]\t[23, 25]\n",
"SirBACO_4\t10\t0\t[26, 33]\t[26, 33]\n",
"Mice_1\t10\t0\t[34, 38]\t[34, 38]\n",
"We_2\t11\t0\t[0, 2]\t[0, 2]\n",
"carried_0\t11\t0\t[3, 10]\t[3, 10]\n",
"out_0\t11\t0\t[11, 14]\t[11, 14]\n",
"a_3\t11\t0\t[15, 16]\t[15, 16]\n",
"metabolic_6\t11\t0\t[17, 26]\t[17, 26]\n",
"characterization_0\t11\t0\t[27, 43]\t[27, 43]\n",
"of_24\t11\t0\t[44, 46]\t[44, 46]\n",
"SirBACO_5\t11\t0\t[47, 54]\t[47, 54]\n",
"mice_9\t11\t0\t[55, 59]\t[55, 59]\n",
"on_0\t11\t0\t[60, 62]\t[60, 62]\n",
"a_4\t11\t0\t[63, 64]\t[63, 64]\n",
"standard_0\t11\t0\t[65, 73]\t[65, 73]\n",
"diet_0\t11\t0\t[74, 78]\t[74, 78]\n",
"._23\t11\t0\t[78, 79]\t[78, 79]\n",
"Serum_0\t11\t1\t[0, 5]\t[80, 85]\n",
"metabolite_0\t11\t1\t[6, 16]\t[86, 96]\n",
"levels_2\t11\t1\t[17, 23]\t[97, 103]\n",
"–_1\t11\t1\t[23, 24]\t[103, 104]\n",
"including_0\t11\t1\t[24, 33]\t[104, 113]\n",
"insulin_5\t11\t1\t[34, 41]\t[114, 121]\n",
"and_16\t11\t1\t[42, 45]\t[122, 125]\n",
"glucose_4\t11\t1\t[46, 53]\t[126, 133]\n",
"–_2\t11\t1\t[53, 54]\t[133, 134]\n",
"were_4\t11\t1\t[54, 58]\t[134, 138]\n",
"normal_1\t11\t1\t[59, 65]\t[139, 145]\n",
"(_5\t11\t1\t[66, 67]\t[146, 147]\n",
"Table_0\t11\t1\t[67, 72]\t[147, 152]\n",
"S1_0\t11\t1\t[73, 75]\t[153, 155]\n",
"),_1\t11\t1\t[75, 77]\t[155, 157]\n",
"as_2\t11\t1\t[78, 80]\t[158, 160]\n",
"was_1\t11\t1\t[81, 84]\t[161, 164]\n",
"the_17\t11\t1\t[85, 88]\t[165, 168]\n",
"response_0\t11\t1\t[89, 97]\t[169, 177]\n",
"to_8\t11\t1\t[98, 100]\t[178, 180]\n",
"intraperitoneal_0\t11\t1\t[101, 116]\t[181, 196]\n",
"glucose_5\t11\t1\t[117, 124]\t[197, 204]\n",
"or_4\t11\t1\t[125, 127]\t[205, 207]\n",
"insulin_6\t11\t1\t[128, 135]\t[208, 215]\n",
"challenge_1\t11\t1\t[136, 145]\t[216, 225]\n",
"tests_0\t11\t1\t[146, 151]\t[226, 231]\n",
"(_6\t11\t1\t[152, 153]\t[232, 233]\n",
"Figure_2\t11\t1\t[153, 159]\t[233, 239]\n",
"2A_0\t11\t1\t[160, 162]\t[240, 242]\n",
"–_3\t11\t1\t[162, 163]\t[242, 243]\n",
"2B_0\t11\t1\t[163, 165]\t[243, 245]\n",
")._4\t11\t1\t[165, 167]\t[245, 247]\n",
"However_2\t11\t2\t[0, 7]\t[248, 255]\n",
",_25\t11\t2\t[7, 8]\t[255, 256]\n",
"we_4\t11\t2\t[9, 11]\t[257, 259]\n",
"detected_0\t11\t2\t[12, 20]\t[260, 268]\n",
"a_5\t11\t2\t[21, 22]\t[269, 270]\n",
"~_0\t11\t2\t[23, 24]\t[271, 272]\n",
"30_0\t11\t2\t[24, 26]\t[272, 274]\n",
"%_0\t11\t2\t[26, 27]\t[274, 275]\n",
"increase_2\t11\t2\t[28, 36]\t[276, 284]\n",
"in_23\t11\t2\t[37, 39]\t[285, 287]\n",
"plasma_0\t11\t2\t[40, 46]\t[288, 294]\n",
"adiponectin_1\t11\t2\t[47, 58]\t[295, 306]\n",
"levels_3\t11\t2\t[59, 65]\t[307, 313]\n",
"(_7\t11\t2\t[66, 67]\t[314, 315]\n",
"Table_1\t11\t2\t[67, 72]\t[315, 320]\n",
"S1_1\t11\t2\t[73, 75]\t[321, 323]\n",
")._5\t11\t2\t[75, 77]\t[323, 325]\n",
"In_2\t12\t0\t[0, 2]\t[0, 2]\n",
"C_2\t12\t0\t[3, 4]\t[3, 4]\n",
"._24\t12\t0\t[4, 5]\t[4, 5]\n",
"elegans_2\t12\t0\t[5, 12]\t[5, 12]\n",
"and_17\t12\t0\t[13, 16]\t[13, 16]\n",
"D_0\t12\t0\t[17, 18]\t[17, 18]\n",
"._25\t12\t0\t[18, 19]\t[18, 19]\n",
"melanogaster_0\t12\t0\t[19, 31]\t[19, 31]\n",
",_26\t12\t0\t[31, 32]\t[31, 32]\n",
"increased_3\t12\t0\t[33, 42]\t[33, 42]\n",
"Sir2_3\t12\t0\t[43, 47]\t[43, 47]\n",
"mimics_0\t12\t0\t[48, 54]\t[48, 54]\n",
"the_18\t12\t0\t[55, 58]\t[55, 58]\n",
"effects_2\t12\t0\t[59, 66]\t[59, 66]\n",
"of_25\t12\t0\t[67, 69]\t[67, 69]\n",
"calorie_1\t12\t0\t[70, 77]\t[70, 77]\n",
"restriction_1\t12\t0\t[78, 89]\t[78, 89]\n",
"to_9\t12\t0\t[90, 92]\t[90, 92]\n",
"extend_0\t12\t0\t[93, 99]\t[93, 99]\n",
"lifespan_1\t12\t0\t[100, 108]\t[100, 108]\n",
"._26\t12\t0\t[108, 109]\t[108, 109]\n",
"In_3\t12\t1\t[0, 2]\t[110, 112]\n",
"mammals_1\t12\t1\t[3, 10]\t[113, 120]\n",
",_27\t12\t1\t[10, 11]\t[120, 121]\n",
"prolonged_0\t12\t1\t[12, 21]\t[122, 131]\n",
"calorie_2\t12\t1\t[22, 29]\t[132, 139]\n",
"restriction_2\t12\t1\t[30, 41]\t[140, 151]\n",
"decreases_0\t12\t1\t[42, 51]\t[152, 161]\n",
"energy_4\t12\t1\t[52, 58]\t[162, 168]\n",
"expenditure_1\t12\t1\t[59, 70]\t[169, 180]\n",
"and_18\t12\t1\t[71, 74]\t[181, 184]\n",
"increases_3\t12\t1\t[75, 84]\t[185, 194]\n",
"metabolic_7\t12\t1\t[85, 94]\t[195, 204]\n",
"efficiency_4\t12\t1\t[95, 105]\t[205, 215]\n",
"by_1\t12\t1\t[106, 108]\t[216, 218]\n",
"decreasing_1\t12\t1\t[109, 119]\t[219, 229]\n",
"O2_0\t12\t1\t[120, 122]\t[230, 232]\n",
"consumption_0\t12\t1\t[123, 134]\t[233, 244]\n",
"._27\t12\t1\t[134, 135]\t[244, 245]\n",
"To_3\t12\t2\t[0, 2]\t[246, 248]\n",
"determine_0\t12\t2\t[3, 12]\t[249, 258]\n",
"whether_2\t12\t2\t[13, 20]\t[259, 266]\n",
"SirT1_16\t12\t2\t[21, 26]\t[267, 272]\n",
"overexpression_2\t12\t2\t[27, 41]\t[273, 287]\n",
"reproduces_0\t12\t2\t[42, 52]\t[288, 298]\n",
"these_1\t12\t2\t[53, 58]\t[299, 304]\n",
"sub_0\t12\t2\t[59, 62]\t[305, 308]\n",
"-_23\t12\t2\t[62, 63]\t[308, 309]\n",
"phenotypes_0\t12\t2\t[63, 73]\t[309, 319]\n",
",_28\t12\t2\t[73, 74]\t[319, 320]\n",
"we_5\t12\t2\t[75, 77]\t[321, 323]\n",
"carried_1\t12\t2\t[78, 85]\t[324, 331]\n",
"out_1\t12\t2\t[86, 89]\t[332, 335]\n",
"indirect_0\t12\t2\t[90, 98]\t[336, 344]\n",
"calorimetry_0\t12\t2\t[99, 110]\t[345, 356]\n",
"experiments_0\t12\t2\t[111, 122]\t[357, 368]\n",
"._28\t12\t2\t[122, 123]\t[368, 369]\n",
"SirBACO_6\t12\t3\t[0, 7]\t[370, 377]\n",
"mice_10\t12\t3\t[8, 12]\t[378, 382]\n",
"demonstrated_0\t12\t3\t[13, 25]\t[383, 395]\n",
"a_6\t12\t3\t[26, 27]\t[396, 397]\n",
"coordinate_0\t12\t3\t[28, 38]\t[398, 408]\n",
"~_1\t12\t3\t[39, 40]\t[409, 410]\n",
"15_0\t12\t3\t[40, 42]\t[410, 412]\n",
"%_1\t12\t3\t[42, 43]\t[412, 413]\n",
"decrease_0\t12\t3\t[44, 52]\t[414, 422]\n",
"in_24\t12\t3\t[53, 55]\t[423, 425]\n",
"O2_1\t12\t3\t[56, 58]\t[426, 428]\n",
"consumption_1\t12\t3\t[59, 70]\t[429, 440]\n",
"and_19\t12\t3\t[71, 74]\t[441, 444]\n",
"CO2_0\t12\t3\t[75, 78]\t[445, 448]\n",
"production_2\t12\t3\t[79, 89]\t[449, 459]\n",
"(_8\t12\t3\t[90, 91]\t[460, 461]\n",
"Figure_3\t12\t3\t[91, 97]\t[461, 467]\n",
"2C_0\t12\t3\t[98, 100]\t[468, 470]\n",
"and_20\t12\t3\t[101, 104]\t[471, 474]\n",
"data_1\t12\t3\t[105, 109]\t[475, 479]\n",
"not_1\t12\t3\t[110, 113]\t[480, 483]\n",
"shown_1\t12\t3\t[114, 119]\t[484, 489]\n",
")._6\t12\t3\t[119, 121]\t[489, 491]\n",
"Due_0\t12\t4\t[0, 3]\t[492, 495]\n",
"to_10\t12\t4\t[4, 6]\t[496, 498]\n",
"the_19\t12\t4\t[7, 10]\t[499, 502]\n",
"combined_0\t12\t4\t[11, 19]\t[503, 511]\n",
"fall_0\t12\t4\t[20, 24]\t[512, 516]\n",
"in_25\t12\t4\t[25, 27]\t[517, 519]\n",
"VO2_0\t12\t4\t[28, 31]\t[520, 523]\n",
"and_21\t12\t4\t[32, 35]\t[524, 527]\n",
"VCO2_0\t12\t4\t[36, 40]\t[528, 532]\n",
",_29\t12\t4\t[40, 41]\t[532, 533]\n",
"the_20\t12\t4\t[42, 45]\t[534, 537]\n",
"respiratory_0\t12\t4\t[46, 57]\t[538, 549]\n",
"quotient_0\t12\t4\t[58, 66]\t[550, 558]\n",
"(_9\t12\t4\t[67, 68]\t[559, 560]\n",
"RQ_0\t12\t4\t[68, 70]\t[560, 562]\n",
"=_0\t12\t4\t[71, 72]\t[563, 564]\n",
"VCO2_1\t12\t4\t[73, 77]\t[565, 569]\n",
"/_1\t12\t4\t[77, 78]\t[569, 570]\n",
"VO2_1\t12\t4\t[78, 81]\t[570, 573]\n",
")_1\t12\t4\t[81, 82]\t[573, 574]\n",
"was_2\t12\t4\t[83, 86]\t[575, 578]\n",
"unchanged_0\t12\t4\t[87, 96]\t[579, 588]\n",
"(_10\t12\t4\t[97, 98]\t[589, 590]\n",
"Figure_4\t12\t4\t[98, 104]\t[590, 596]\n",
"2D_0\t12\t4\t[105, 107]\t[597, 599]\n",
")._7\t12\t4\t[107, 109]\t[599, 601]\n",
"In_4\t12\t5\t[0, 2]\t[602, 604]\n",
"addition_0\t12\t5\t[3, 11]\t[605, 613]\n",
",_30\t12\t5\t[11, 12]\t[613, 614]\n",
"spontaneous_0\t12\t5\t[13, 24]\t[615, 626]\n",
"locomotor_1\t12\t5\t[25, 34]\t[627, 636]\n",
"activity_1\t12\t5\t[35, 43]\t[637, 645]\n",
"decreased_3\t12\t5\t[44, 53]\t[646, 655]\n",
"by_2\t12\t5\t[54, 56]\t[656, 658]\n",
"33_0\t12\t5\t[57, 59]\t[659, 661]\n",
"._29\t12\t5\t[59, 60]\t[661, 662]\n",
"6_0\t12\t5\t[60, 61]\t[662, 663]\n",
"±_0\t12\t5\t[62, 63]\t[664, 665]\n",
"1_0\t12\t5\t[64, 65]\t[666, 667]\n",
"._30\t12\t5\t[65, 66]\t[667, 668]\n",
"4_0\t12\t5\t[66, 67]\t[668, 669]\n",
"%_2\t12\t5\t[67, 68]\t[669, 670]\n",
"(_11\t12\t5\t[69, 70]\t[671, 672]\n",
"Figure_5\t12\t5\t[70, 76]\t[672, 678]\n",
"2E_0\t12\t5\t[77, 79]\t[679, 681]\n",
"),_2\t12\t5\t[79, 81]\t[681, 683]\n",
"more_0\t12\t5\t[82, 86]\t[684, 688]\n",
"markedly_0\t12\t5\t[87, 95]\t[689, 697]\n",
"during_0\t12\t5\t[96, 102]\t[698, 704]\n",
"the_21\t12\t5\t[103, 106]\t[705, 708]\n",
"dark_0\t12\t5\t[107, 111]\t[709, 713]\n",
"phase_0\t12\t5\t[112, 117]\t[714, 719]\n",
"._31\t12\t5\t[117, 118]\t[719, 720]\n",
"To_4\t13\t0\t[0, 2]\t[0, 2]\n",
"investigate_0\t13\t0\t[3, 14]\t[3, 14]\n",
"differences_0\t13\t0\t[15, 26]\t[15, 26]\n",
"in_26\t13\t0\t[27, 29]\t[27, 29]\n",
"basal_0\t13\t0\t[30, 35]\t[30, 35]\n",
"metabolic_8\t13\t0\t[36, 45]\t[36, 45]\n",
"rate_0\t13\t0\t[46, 50]\t[46, 50]\n",
",_31\t13\t0\t[50, 51]\t[50, 51]\n",
"we_6\t13\t0\t[52, 54]\t[52, 54]\n",
"compared_0\t13\t0\t[55, 63]\t[55, 63]\n",
"the_22\t13\t0\t[64, 67]\t[64, 67]\n",
"energy_5\t13\t0\t[68, 74]\t[68, 74]\n",
"expenditure_2\t13\t0\t[75, 86]\t[75, 86]\n",
"required_0\t13\t0\t[87, 95]\t[87, 95]\n",
"for_2\t13\t0\t[96, 99]\t[96, 99]\n",
"locomotor_2\t13\t0\t[100, 109]\t[100, 109]\n",
"activity_2\t13\t0\t[110, 118]\t[110, 118]\n",
"._32\t13\t0\t[118, 119]\t[118, 119]\n",
"SirBACO_7\t13\t1\t[0, 7]\t[120, 127]\n",
"mice_11\t13\t1\t[8, 12]\t[128, 132]\n",
"had_0\t13\t1\t[13, 16]\t[133, 136]\n",
"decreased_4\t13\t1\t[17, 26]\t[137, 146]\n",
"resting_0\t13\t1\t[27, 34]\t[147, 154]\n",
"energy_6\t13\t1\t[35, 41]\t[155, 161]\n",
"expenditure_3\t13\t1\t[42, 53]\t[162, 173]\n",
",_32\t13\t1\t[53, 54]\t[173, 174]\n",
"but_1\t13\t1\t[55, 58]\t[175, 178]\n",
"no_1\t13\t1\t[59, 61]\t[179, 181]\n",
"differences_1\t13\t1\t[62, 73]\t[182, 193]\n",
"at_0\t13\t1\t[74, 76]\t[194, 196]\n",
"higher_2\t13\t1\t[77, 83]\t[197, 203]\n",
"activity_3\t13\t1\t[84, 92]\t[204, 212]\n",
"levels_4\t13\t1\t[93, 99]\t[213, 219]\n",
"(_12\t13\t1\t[100, 101]\t[220, 221]\n",
"Figure_6\t13\t1\t[101, 107]\t[221, 227]\n",
"S1_2\t13\t1\t[108, 110]\t[228, 230]\n",
")._8\t13\t1\t[110, 112]\t[230, 232]\n",
"Body_0\t13\t2\t[0, 4]\t[233, 237]\n",
"weight_1\t13\t2\t[5, 11]\t[238, 244]\n",
"and_22\t13\t2\t[12, 15]\t[245, 248]\n",
"composition_1\t13\t2\t[16, 27]\t[249, 260]\n",
"were_5\t13\t2\t[28, 32]\t[261, 265]\n",
"similar_0\t13\t2\t[33, 40]\t[266, 273]\n",
"in_27\t13\t2\t[41, 43]\t[274, 276]\n",
"SirBACO_8\t13\t2\t[44, 51]\t[277, 284]\n",
"mice_12\t13\t2\t[52, 56]\t[285, 289]\n",
"and_23\t13\t2\t[57, 60]\t[290, 293]\n",
"non_0\t13\t2\t[61, 64]\t[294, 297]\n",
"-_24\t13\t2\t[64, 65]\t[297, 298]\n",
"transgenic_3\t13\t2\t[65, 75]\t[298, 308]\n",
"littermates_1\t13\t2\t[76, 87]\t[309, 320]\n",
"(_13\t13\t2\t[88, 89]\t[321, 322]\n",
"Figure_7\t13\t2\t[89, 95]\t[322, 328]\n",
"2F_0\t13\t2\t[96, 98]\t[329, 331]\n",
")._9\t13\t2\t[98, 100]\t[331, 333]\n",
"Food_0\t13\t3\t[0, 4]\t[334, 338]\n",
"intake_1\t13\t3\t[5, 11]\t[339, 345]\n",
"decreased_5\t13\t3\t[12, 21]\t[346, 355]\n",
"by_3\t13\t3\t[22, 24]\t[356, 358]\n",
"15_1\t13\t3\t[25, 27]\t[359, 361]\n",
"±_1\t13\t3\t[28, 29]\t[362, 363]\n",
"1_1\t13\t3\t[30, 31]\t[364, 365]\n",
"._33\t13\t3\t[31, 32]\t[365, 366]\n",
"3_0\t13\t3\t[32, 33]\t[366, 367]\n",
"%_3\t13\t3\t[33, 34]\t[367, 368]\n",
"in_28\t13\t3\t[35, 37]\t[369, 371]\n",
"SirBACO_9\t13\t3\t[38, 45]\t[372, 379]\n",
"mice_13\t13\t3\t[46, 50]\t[380, 384]\n",
"(_14\t13\t3\t[51, 52]\t[385, 386]\n",
"Figure_8\t13\t3\t[52, 58]\t[386, 392]\n",
"2G_0\t13\t3\t[59, 61]\t[393, 395]\n",
"),_3\t13\t3\t[61, 63]\t[395, 397]\n",
"consistent_1\t13\t3\t[64, 74]\t[398, 408]\n",
"with_4\t13\t3\t[75, 79]\t[409, 413]\n",
"the_23\t13\t3\t[80, 83]\t[414, 417]\n",
"preservation_0\t13\t3\t[84, 96]\t[418, 430]\n",
"of_26\t13\t3\t[97, 99]\t[431, 433]\n",
"normal_2\t13\t3\t[100, 106]\t[434, 440]\n",
"body_2\t13\t3\t[107, 111]\t[441, 445]\n",
"weight_2\t13\t3\t[112, 118]\t[446, 452]\n",
",_33\t13\t3\t[118, 119]\t[452, 453]\n",
"in_29\t13\t3\t[120, 122]\t[454, 456]\n",
"the_24\t13\t3\t[123, 126]\t[457, 460]\n",
"face_0\t13\t3\t[127, 131]\t[461, 465]\n",
"of_27\t13\t3\t[132, 134]\t[466, 468]\n",
"decreased_6\t13\t3\t[135, 144]\t[469, 478]\n",
"metabolic_9\t13\t3\t[145, 154]\t[479, 488]\n",
"rate_1\t13\t3\t[155, 159]\t[489, 493]\n",
"and_24\t13\t3\t[160, 163]\t[494, 497]\n",
"activity_4\t13\t3\t[164, 172]\t[498, 506]\n",
"._34\t13\t3\t[172, 173]\t[506, 507]\n",
"In_5\t14\t0\t[0, 2]\t[0, 2]\n",
"response_1\t14\t0\t[3, 11]\t[3, 11]\n",
"to_11\t14\t0\t[12, 14]\t[12, 14]\n",
"24_0\t14\t0\t[15, 17]\t[15, 17]\n",
"-_25\t14\t0\t[17, 18]\t[17, 18]\n",
"hr_0\t14\t0\t[18, 20]\t[18, 20]\n",
"food_1\t14\t0\t[21, 25]\t[21, 25]\n",
"deprivation_0\t14\t0\t[26, 37]\t[26, 37]\n",
"SirBACO_10\t14\t0\t[38, 45]\t[38, 45]\n",
"mice_14\t14\t0\t[46, 50]\t[46, 50]\n",
"showed_0\t14\t0\t[51, 57]\t[51, 57]\n",
"a_7\t14\t0\t[58, 59]\t[58, 59]\n",
"normal_3\t14\t0\t[60, 66]\t[60, 66]\n",
"drop_0\t14\t0\t[67, 71]\t[67, 71]\n",
"in_30\t14\t0\t[72, 74]\t[72, 74]\n",
"RQ_1\t14\t0\t[75, 77]\t[75, 77]\n",
",_34\t14\t0\t[77, 78]\t[77, 78]\n",
"reflecting_0\t14\t0\t[79, 89]\t[79, 89]\n",
"increased_4\t14\t0\t[90, 99]\t[90, 99]\n",
"fat_0\t14\t0\t[100, 103]\t[100, 103]\n",
"oxidation_0\t14\t0\t[104, 113]\t[104, 113]\n",
"(_15\t14\t0\t[114, 115]\t[114, 115]\n",
"not_2\t14\t0\t[115, 118]\t[115, 118]\n",
"shown_2\t14\t0\t[119, 124]\t[119, 124]\n",
")._10\t14\t0\t[124, 126]\t[124, 126]\n",
"These_3\t14\t1\t[0, 5]\t[127, 132]\n",
"data_2\t14\t1\t[6, 10]\t[133, 137]\n",
"indicate_0\t14\t1\t[11, 19]\t[138, 146]\n",
"that_6\t14\t1\t[20, 24]\t[147, 151]\n",
",_35\t14\t1\t[24, 25]\t[151, 152]\n",
"although_0\t14\t1\t[26, 34]\t[153, 161]\n",
"hypometabolic_0\t14\t1\t[35, 48]\t[162, 175]\n",
",_36\t14\t1\t[48, 49]\t[175, 176]\n",
"SirBACO_11\t14\t1\t[50, 57]\t[177, 184]\n",
"mice_15\t14\t1\t[58, 62]\t[185, 189]\n",
"have_1\t14\t1\t[63, 67]\t[190, 194]\n",
"normal_4\t14\t1\t[68, 74]\t[195, 201]\n",
"rates_0\t14\t1\t[75, 80]\t[202, 207]\n",
"of_28\t14\t1\t[81, 83]\t[208, 210]\n",
"fatty_0\t14\t1\t[84, 89]\t[211, 216]\n",
"acid_0\t14\t1\t[90, 94]\t[217, 221]\n",
"oxidation_1\t14\t1\t[95, 104]\t[222, 231]\n",
"._35\t14\t1\t[104, 105]\t[231, 232]\n",
"They_0\t14\t2\t[0, 4]\t[233, 237]\n",
"also_1\t14\t2\t[5, 9]\t[238, 242]\n",
"exhibited_0\t14\t2\t[10, 19]\t[243, 252]\n",
"lower_1\t14\t2\t[20, 25]\t[253, 258]\n",
"body_3\t14\t2\t[26, 30]\t[259, 263]\n",
"temperature_0\t14\t2\t[31, 42]\t[264, 275]\n",
"than_1\t14\t2\t[43, 47]\t[276, 280]\n",
"control_2\t14\t2\t[48, 55]\t[281, 288]\n",
"littermates_2\t14\t2\t[56, 67]\t[289, 300]\n",
"under_0\t14\t2\t[68, 73]\t[301, 306]\n",
"fed_0\t14\t2\t[74, 77]\t[307, 310]\n",
"and_25\t14\t2\t[78, 81]\t[311, 314]\n",
"fasted_0\t14\t2\t[82, 88]\t[315, 321]\n",
"conditions_0\t14\t2\t[89, 99]\t[322, 332]\n",
"(_16\t14\t2\t[100, 101]\t[333, 334]\n",
"Figure_9\t14\t2\t[101, 107]\t[334, 340]\n",
"2H_0\t14\t2\t[108, 110]\t[341, 343]\n",
"),_4\t14\t2\t[110, 112]\t[343, 345]\n",
"but_2\t14\t2\t[113, 116]\t[346, 349]\n",
"did_0\t14\t2\t[117, 120]\t[350, 353]\n",
"not_3\t14\t2\t[121, 124]\t[354, 357]\n",
"display_1\t14\t2\t[125, 132]\t[358, 365]\n",
"changes_1\t14\t2\t[133, 140]\t[366, 373]\n",
"in_31\t14\t2\t[141, 143]\t[374, 376]\n",
"blood_0\t14\t2\t[144, 149]\t[377, 382]\n",
"pressure_0\t14\t2\t[150, 158]\t[383, 391]\n",
"or_5\t14\t2\t[159, 161]\t[392, 394]\n",
"heart_0\t14\t2\t[162, 167]\t[395, 400]\n",
"rate_2\t14\t2\t[168, 172]\t[401, 405]\n",
"(_17\t14\t2\t[173, 174]\t[406, 407]\n",
"Figure_10\t14\t2\t[174, 180]\t[407, 413]\n",
"S2_0\t14\t2\t[181, 183]\t[414, 416]\n",
"),_5\t14\t2\t[183, 185]\t[416, 418]\n",
"suggesting_0\t14\t2\t[186, 196]\t[419, 429]\n",
"that_7\t14\t2\t[197, 201]\t[430, 434]\n",
"the_25\t14\t2\t[202, 205]\t[435, 438]\n",
"effect_0\t14\t2\t[206, 212]\t[439, 445]\n",
"on_1\t14\t2\t[213, 215]\t[446, 448]\n",
"body_4\t14\t2\t[216, 220]\t[449, 453]\n",
"temperature_1\t14\t2\t[221, 232]\t[454, 465]\n",
"is_2\t14\t2\t[233, 235]\t[466, 468]\n",
"secondary_0\t14\t2\t[236, 245]\t[469, 478]\n",
"to_12\t14\t2\t[246, 248]\t[479, 481]\n",
"decreased_7\t14\t2\t[249, 258]\t[482, 491]\n",
"locomotion_0\t14\t2\t[259, 269]\t[492, 502]\n",
"._36\t14\t2\t[269, 270]\t[502, 503]\n",
"SirBACO_12\t15\t0\t[0, 7]\t[0, 7]\n",
"mice_16\t15\t0\t[8, 12]\t[8, 12]\n",
"are_1\t15\t0\t[13, 16]\t[13, 16]\n",
"protected_0\t15\t0\t[17, 26]\t[17, 26]\n",
"from_1\t15\t0\t[27, 31]\t[27, 31]\n",
"insulin_7\t15\t0\t[32, 39]\t[32, 39]\n",
"-_26\t15\t0\t[39, 40]\t[39, 40]\n",
"resistant_0\t15\t0\t[40, 49]\t[40, 49]\n",
"diabetes_3\t15\t0\t[50, 58]\t[50, 58]\n",
"We_3\t16\t0\t[0, 2]\t[0, 2]\n",
"next_0\t16\t0\t[3, 7]\t[3, 7]\n",
"asked_0\t16\t0\t[8, 13]\t[8, 13]\n",
"whether_3\t16\t0\t[14, 21]\t[14, 21]\n",
"SirT1_17\t16\t0\t[22, 27]\t[22, 27]\n",
"overexpression_3\t16\t0\t[28, 42]\t[28, 42]\n",
"affects_0\t16\t0\t[43, 50]\t[43, 50]\n",
"the_26\t16\t0\t[51, 54]\t[51, 54]\n",
"susceptibility_0\t16\t0\t[55, 69]\t[55, 69]\n",
"to_13\t16\t0\t[70, 72]\t[70, 72]\n",
"insulin_8\t16\t0\t[73, 80]\t[73, 80]\n",
"resistance_2\t16\t0\t[81, 91]\t[81, 91]\n",
"and_26\t16\t0\t[92, 95]\t[92, 95]\n",
"diabetes_4\t16\t0\t[96, 104]\t[96, 104]\n",
"in_32\t16\t0\t[105, 107]\t[105, 107]\n",
"environmental_0\t16\t0\t[108, 121]\t[108, 121]\n",
"and_27\t16\t0\t[122, 125]\t[122, 125]\n",
"genetic_0\t16\t0\t[126, 133]\t[126, 133]\n",
"models_2\t16\t0\t[134, 140]\t[134, 140]\n",
"of_29\t16\t0\t[141, 143]\t[141, 143]\n",
"these_2\t16\t0\t[144, 149]\t[144, 149]\n",
"conditions_1\t16\t0\t[150, 160]\t[150, 160]\n",
"._37\t16\t0\t[160, 161]\t[160, 161]\n",
"When_0\t16\t1\t[0, 4]\t[162, 166]\n",
"SirBACO_13\t16\t1\t[5, 12]\t[167, 174]\n",
"mice_17\t16\t1\t[13, 17]\t[175, 179]\n",
"on_2\t16\t1\t[18, 20]\t[180, 182]\n",
"an_1\t16\t1\t[21, 23]\t[183, 185]\n",
"inbred_0\t16\t1\t[24, 30]\t[186, 192]\n",
"C57BL_0\t16\t1\t[31, 36]\t[193, 198]\n",
"/_2\t16\t1\t[36, 37]\t[198, 199]\n",
"6J_0\t16\t1\t[37, 39]\t[199, 201]\n",
"background_1\t16\t1\t[40, 50]\t[202, 212]\n",
"were_6\t16\t1\t[51, 55]\t[213, 217]\n",
"placed_0\t16\t1\t[56, 62]\t[218, 224]\n",
"on_3\t16\t1\t[63, 65]\t[225, 227]\n",
"a_8\t16\t1\t[66, 67]\t[228, 229]\n",
"HFD_0\t16\t1\t[68, 71]\t[230, 233]\n",
"or_6\t16\t1\t[72, 74]\t[234, 236]\n",
"backcrossed_1\t16\t1\t[75, 86]\t[237, 248]\n",
"onto_1\t16\t1\t[87, 91]\t[249, 253]\n",
"db_2\t16\t1\t[92, 94]\t[254, 256]\n",
"/_3\t16\t1\t[94, 95]\t[256, 257]\n",
"db_3\t16\t1\t[95, 97]\t[257, 259]\n",
"mice_18\t16\t1\t[98, 102]\t[260, 264]\n",
",_37\t16\t1\t[102, 103]\t[264, 265]\n",
"they_0\t16\t1\t[104, 108]\t[266, 270]\n",
"showed_1\t16\t1\t[109, 115]\t[271, 277]\n",
"lower_2\t16\t1\t[116, 121]\t[278, 283]\n",
"blood_1\t16\t1\t[122, 127]\t[284, 289]\n",
"glucose_6\t16\t1\t[128, 135]\t[290, 297]\n",
"and_28\t16\t1\t[136, 139]\t[298, 301]\n",
"plasma_1\t16\t1\t[140, 146]\t[302, 308]\n",
"insulin_9\t16\t1\t[147, 154]\t[309, 316]\n",
"levels_5\t16\t1\t[155, 161]\t[317, 323]\n",
"(_18\t16\t1\t[162, 163]\t[324, 325]\n",
"Figures_0\t16\t1\t[163, 170]\t[325, 332]\n",
"3A_0\t16\t1\t[171, 173]\t[333, 335]\n",
"–_4\t16\t1\t[173, 174]\t[335, 336]\n",
"3B_0\t16\t1\t[174, 176]\t[336, 338]\n",
"and_29\t16\t1\t[177, 180]\t[339, 342]\n",
"Table_2\t16\t1\t[181, 186]\t[343, 348]\n",
"S1_3\t16\t1\t[187, 189]\t[349, 351]\n",
")_2\t16\t1\t[189, 190]\t[351, 352]\n",
"and_30\t16\t1\t[191, 194]\t[353, 356]\n",
"better_0\t16\t1\t[195, 201]\t[357, 363]\n",
"glucose_7\t16\t1\t[202, 209]\t[364, 371]\n",
"tolerance_2\t16\t1\t[210, 219]\t[372, 381]\n",
"(_19\t16\t1\t[220, 221]\t[382, 383]\n",
"Figure_11\t16\t1\t[221, 227]\t[383, 389]\n",
"3C_0\t16\t1\t[228, 230]\t[390, 392]\n",
")_3\t16\t1\t[230, 231]\t[392, 393]\n",
"than_2\t16\t1\t[232, 236]\t[394, 398]\n",
"non_1\t16\t1\t[237, 240]\t[399, 402]\n",
"-_27\t16\t1\t[240, 241]\t[402, 403]\n",
"transgenic_4\t16\t1\t[241, 251]\t[403, 413]\n",
"controls_0\t16\t1\t[252, 260]\t[414, 422]\n",
",_38\t16\t1\t[260, 261]\t[422, 423]\n",
"despite_0\t16\t1\t[262, 269]\t[424, 431]\n",
"similar_1\t16\t1\t[270, 277]\t[432, 439]\n",
"body_5\t16\t1\t[278, 282]\t[440, 444]\n",
"weight_3\t16\t1\t[283, 289]\t[445, 451]\n",
"(_20\t16\t1\t[290, 291]\t[452, 453]\n",
"Figure_12\t16\t1\t[291, 297]\t[453, 459]\n",
"S3A_0\t16\t1\t[298, 301]\t[460, 463]\n",
"),_6\t16\t1\t[301, 303]\t[463, 465]\n",
"weight_4\t16\t1\t[304, 310]\t[466, 472]\n",
"gain_9\t16\t1\t[311, 315]\t[473, 477]\n",
"during_1\t16\t1\t[316, 322]\t[478, 484]\n",
"the_27\t16\t1\t[323, 326]\t[485, 488]\n",
"diet_1\t16\t1\t[327, 331]\t[489, 493]\n",
"(_21\t16\t1\t[332, 333]\t[494, 495]\n",
"Figure_13\t16\t1\t[333, 339]\t[495, 501]\n",
"3D_0\t16\t1\t[340, 342]\t[502, 504]\n",
"),_7\t16\t1\t[342, 344]\t[504, 506]\n",
"and_31\t16\t1\t[345, 348]\t[507, 510]\n",
"body_6\t16\t1\t[349, 353]\t[511, 515]\n",
"fat_1\t16\t1\t[354, 357]\t[516, 519]\n",
"content_0\t16\t1\t[358, 365]\t[520, 527]\n",
"(_22\t16\t1\t[366, 367]\t[528, 529]\n",
"Figure_14\t16\t1\t[367, 373]\t[529, 535]\n",
"3E_0\t16\t1\t[374, 376]\t[536, 538]\n",
")._11\t16\t1\t[376, 378]\t[538, 540]\n",
"We_4\t16\t2\t[0, 2]\t[541, 543]\n",
"provisionally_0\t16\t2\t[3, 16]\t[544, 557]\n",
"conclude_1\t16\t2\t[17, 25]\t[558, 566]\n",
"that_8\t16\t2\t[26, 30]\t[567, 571]\n",
"SirT1_18\t16\t2\t[31, 36]\t[572, 577]\n",
"overexpression_4\t16\t2\t[37, 51]\t[578, 592]\n",
"does_1\t16\t2\t[52, 56]\t[593, 597]\n",
"not_4\t16\t2\t[57, 60]\t[598, 601]\n",
"improve_0\t16\t2\t[61, 68]\t[602, 609]\n",
"glucose_8\t16\t2\t[69, 76]\t[610, 617]\n",
"tolerance_3\t16\t2\t[77, 86]\t[618, 627]\n",
"per_0\t16\t2\t[87, 90]\t[628, 631]\n",
"se_0\t16\t2\t[91, 93]\t[632, 634]\n",
",_39\t16\t2\t[93, 94]\t[634, 635]\n",
"but_3\t16\t2\t[95, 98]\t[636, 639]\n",
"prevents_1\t16\t2\t[99, 107]\t[640, 648]\n",
"the_28\t16\t2\t[108, 111]\t[649, 652]\n",
"adverse_0\t16\t2\t[112, 119]\t[653, 660]\n",
"effects_3\t16\t2\t[120, 127]\t[661, 668]\n",
"of_30\t16\t2\t[128, 130]\t[669, 671]\n",
"obesity_1\t16\t2\t[131, 138]\t[672, 679]\n",
"on_4\t16\t2\t[139, 141]\t[680, 682]\n",
"glucose_9\t16\t2\t[142, 149]\t[683, 690]\n",
"metabolism_4\t16\t2\t[150, 160]\t[691, 701]\n",
"._38\t16\t2\t[160, 161]\t[701, 702]\n",
"Catalytically_0\t17\t0\t[0, 13]\t[0, 13]\n",
"inactive_0\t17\t0\t[14, 22]\t[14, 22]\n",
"SirT1_19\t17\t0\t[23, 28]\t[23, 28]\n",
"fails_0\t17\t0\t[29, 34]\t[29, 34]\n",
"to_14\t17\t0\t[35, 37]\t[35, 37]\n",
"protect_0\t17\t0\t[38, 45]\t[38, 45]\n",
"aging_0\t17\t0\t[46, 51]\t[46, 51]\n",
"mice_19\t17\t0\t[52, 56]\t[52, 56]\n",
"from_2\t17\t0\t[57, 61]\t[57, 61]\n",
"glucose_10\t17\t0\t[62, 69]\t[62, 69]\n",
"intolerance_0\t17\t0\t[70, 81]\t[70, 81]\n",
"To_5\t18\t0\t[0, 2]\t[0, 2]\n",
"assess_0\t18\t0\t[3, 9]\t[3, 9]\n",
"the_29\t18\t0\t[10, 13]\t[10, 13]\n",
"specificity_1\t18\t0\t[14, 25]\t[14, 25]\n",
"of_31\t18\t0\t[26, 28]\t[26, 28]\n",
"these_3\t18\t0\t[29, 34]\t[29, 34]\n",
"findings_2\t18\t0\t[35, 43]\t[35, 43]\n",
",_40\t18\t0\t[43, 44]\t[43, 44]\n",
"we_7\t18\t0\t[45, 47]\t[45, 47]\n",
"carried_2\t18\t0\t[48, 55]\t[48, 55]\n",
"out_2\t18\t0\t[56, 59]\t[56, 59]\n",
"glucose_11\t18\t0\t[60, 67]\t[60, 67]\n",
"tolerance_4\t18\t0\t[68, 77]\t[68, 77]\n",
"tests_1\t18\t0\t[78, 83]\t[78, 83]\n",
"in_33\t18\t0\t[84, 86]\t[84, 86]\n",
"aging_1\t18\t0\t[87, 92]\t[87, 92]\n",
"transgenic_5\t18\t0\t[93, 103]\t[93, 103]\n",
"mice_20\t18\t0\t[104, 108]\t[104, 108]\n",
"expressing_0\t18\t0\t[109, 119]\t[109, 119]\n",
"a_9\t18\t0\t[120, 121]\t[120, 121]\n",
"catalytically_0\t18\t0\t[122, 135]\t[122, 135]\n",
"inactive_1\t18\t0\t[136, 144]\t[136, 144]\n",
"SirT1_20\t18\t0\t[145, 150]\t[145, 150]\n",
"transgene_2\t18\t0\t[151, 160]\t[151, 160]\n",
"(_23\t18\t0\t[161, 162]\t[161, 162]\n",
"H355Y_0\t18\t0\t[162, 167]\t[162, 167]\n",
")._12\t18\t0\t[167, 169]\t[167, 169]\n",
"Unlike_0\t18\t1\t[0, 6]\t[170, 176]\n",
"SirBACO_14\t18\t1\t[7, 14]\t[177, 184]\n",
"mice_21\t18\t1\t[15, 19]\t[185, 189]\n",
",_41\t18\t1\t[19, 20]\t[189, 190]\n",
"SirT1H355Y_0\t18\t1\t[21, 31]\t[191, 201]\n",
"transgenics_1\t18\t1\t[32, 43]\t[202, 213]\n",
"showed_2\t18\t1\t[44, 50]\t[214, 220]\n",
"no_2\t18\t1\t[51, 53]\t[221, 223]\n",
"differences_2\t18\t1\t[54, 65]\t[224, 235]\n",
"in_34\t18\t1\t[66, 68]\t[236, 238]\n",
"glucose_12\t18\t1\t[69, 76]\t[239, 246]\n",
"tolerance_5\t18\t1\t[77, 86]\t[247, 256]\n",
"from_3\t18\t1\t[87, 91]\t[257, 261]\n",
"control_3\t18\t1\t[92, 99]\t[262, 269]\n",
"littermates_3\t18\t1\t[100, 111]\t[270, 281]\n",
",_42\t18\t1\t[111, 112]\t[281, 282]\n",
"demonstrating_0\t18\t1\t[113, 126]\t[283, 296]\n",
"that_9\t18\t1\t[127, 131]\t[297, 301]\n",
"SirT1_21\t18\t1\t[132, 137]\t[302, 307]\n",
"catalytic_0\t18\t1\t[138, 147]\t[308, 317]\n",
"activity_5\t18\t1\t[148, 156]\t[318, 326]\n",
"is_3\t18\t1\t[157, 159]\t[327, 329]\n",
"required_1\t18\t1\t[160, 168]\t[330, 338]\n",
"for_3\t18\t1\t[169, 172]\t[339, 342]\n",
"its_1\t18\t1\t[173, 176]\t[343, 346]\n",
"insulin_10\t18\t1\t[177, 184]\t[347, 354]\n",
"-_28\t18\t1\t[184, 185]\t[354, 355]\n",
"sensitizing_0\t18\t1\t[185, 196]\t[355, 366]\n",
"effects_4\t18\t1\t[197, 204]\t[367, 374]\n",
"(_24\t18\t1\t[205, 206]\t[375, 376]\n",
"Figure_15\t18\t1\t[206, 212]\t[376, 382]\n",
"S3B_0\t18\t1\t[213, 216]\t[383, 386]\n",
")._13\t18\t1\t[216, 218]\t[386, 388]\n",
"Normal_0\t19\t0\t[0, 6]\t[0, 6]\n",
"energy_7\t19\t0\t[7, 13]\t[7, 13]\n",
"expenditure_4\t19\t0\t[14, 25]\t[14, 25]\n",
"in_35\t19\t0\t[26, 28]\t[26, 28]\n",
"diabetes_5\t19\t0\t[29, 37]\t[29, 37]\n",
"-_29\t19\t0\t[37, 38]\t[37, 38]\n",
"resistant_1\t19\t0\t[38, 47]\t[38, 47]\n",
"SirBACO_15\t19\t0\t[48, 55]\t[48, 55]\n",
"mice_22\t19\t0\t[56, 60]\t[56, 60]\n",
"Based_0\t20\t0\t[0, 5]\t[0, 5]\n",
"on_5\t20\t0\t[6, 8]\t[6, 8]\n",
"the_30\t20\t0\t[9, 12]\t[9, 12]\n",
"decrease_1\t20\t0\t[13, 21]\t[13, 21]\n",
"of_32\t20\t0\t[22, 24]\t[22, 24]\n",
"food_2\t20\t0\t[25, 29]\t[25, 29]\n",
"intake_2\t20\t0\t[30, 36]\t[30, 36]\n",
"and_32\t20\t0\t[37, 40]\t[37, 40]\n",
"energy_8\t20\t0\t[41, 47]\t[41, 47]\n",
"expenditure_5\t20\t0\t[48, 59]\t[48, 59]\n",
"in_36\t20\t0\t[60, 62]\t[60, 62]\n",
"SirBACO_16\t20\t0\t[63, 70]\t[63, 70]\n",
"mice_23\t20\t0\t[71, 75]\t[71, 75]\n",
",_43\t20\t0\t[75, 76]\t[75, 76]\n",
"we_8\t20\t0\t[77, 79]\t[77, 79]\n",
"wanted_0\t20\t0\t[80, 86]\t[80, 86]\n",
"to_15\t20\t0\t[87, 89]\t[87, 89]\n",
"determine_1\t20\t0\t[90, 99]\t[90, 99]\n",
"whether_4\t20\t0\t[100, 107]\t[100, 107]\n",
"the_31\t20\t0\t[108, 111]\t[108, 111]\n",
"transgenes_0\t20\t0\t[112, 122]\t[112, 122]\n",
"’_1\t20\t0\t[123, 124]\t[123, 124]\n",
"ability_0\t20\t0\t[125, 132]\t[125, 132]\n",
"to_16\t20\t0\t[133, 135]\t[133, 135]\n",
"improve_1\t20\t0\t[136, 143]\t[136, 143]\n",
"glucose_13\t20\t0\t[144, 151]\t[144, 151]\n",
"homeostasis_0\t20\t0\t[152, 163]\t[152, 163]\n",
"in_37\t20\t0\t[164, 166]\t[164, 166]\n",
"diabetes_6\t20\t0\t[167, 175]\t[167, 175]\n",
"models_3\t20\t0\t[176, 182]\t[176, 182]\n",
"could_0\t20\t0\t[183, 188]\t[183, 188]\n",
"be_0\t20\t0\t[189, 191]\t[189, 191]\n",
"explained_0\t20\t0\t[192, 201]\t[192, 201]\n",
"by_4\t20\t0\t[202, 204]\t[202, 204]\n",
"changes_2\t20\t0\t[205, 212]\t[205, 212]\n",
"in_38\t20\t0\t[213, 215]\t[213, 215]\n",
"physical_0\t20\t0\t[216, 224]\t[216, 224]\n",
"activity_6\t20\t0\t[225, 233]\t[225, 233]\n",
"or_7\t20\t0\t[234, 236]\t[234, 236]\n",
"metabolic_10\t20\t0\t[237, 246]\t[237, 246]\n",
"rate_3\t20\t0\t[247, 251]\t[247, 251]\n",
"._39\t20\t0\t[251, 252]\t[251, 252]\n",
"'''"
],
"metadata": {
"cellView": "form",
"id": "hWfUmYIg71Ye"
},
"id": "hWfUmYIg71Ye",
"execution_count": 3,
"outputs": []
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"id": "7WkX4zzTJgg2",
"cellView": "form"
},
"outputs": [],
"source": [
"#@title dataframe preparations\n",
"with open('df_my_doc.tsv', 'w') as f:\n",
" f.write(tsv_string)\n",
"\n",
"df_my_doc = pd.read_csv(pathXX+'/df_my_doc.tsv', sep='\\t', index_col=0, dtype={'sentence_id': 'Int64'})\n",
"\n",
"df_my_doc['s_position'] = df_my_doc['s_position'].apply(lambda x: [int(el) for el in x.strip(\"[]\").split(\",\")])\n",
"df_my_doc['p_position'] = df_my_doc['p_position'].apply(lambda x: [int(el) for el in x.strip(\"[]\").split(\",\")])\n",
"df_restore_point = df_my_doc.copy()"
],
"id": "7WkX4zzTJgg2"
},
{
"cell_type": "markdown",
"metadata": {
"id": "K9PQKiMijyMq"
},
"source": [
"# <font color='brown'>4 Hbox for passage"
],
"id": "K9PQKiMijyMq"
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"id": "SdJ6mhEWjxey",
"cellView": "form"
},
"outputs": [],
"source": [
"#@title Hbox for passage\n",
"def show_passage(btn):\n",
" global df_my_doc, d_sentences_idT\n",
" id_passage = int(btn.description)\n",
" print('fresh ' + str(id_passage))\n",
"\n",
" d_sentences_idT = word_token_to_d_sentences_idT(id_passage)\n",
" make_word_btn_column(id_passage, sentence_from_to,d_sentences_idT)\n",
"\n",
" main.children = word_btns_to_box(df_my_doc, id_passage) \n",
"\n",
" if btn.style.button_color != 'red':\n",
" d_btn_passage[int(btn.description)].style.button_color = 'red'\n",
" else:\n",
" btn.style.button_color = 'gray'\n",
" print('finished')"
],
"id": "SdJ6mhEWjxey"
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0,
"referenced_widgets": [
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},
"id": "WxFn_TuTBZ2R",
"outputId": "398eb162-6790-47b9-857a-63b5a9ae87e0",
"cellView": "form"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"HBox(children=(Button(description='0', layout=Layout(max_width='35px', min_width='35px'), style=ButtonStyle(),…"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "0de5d0f7b9664de48f684c9b6f2f4355"
}
},
"metadata": {
"application/vnd.jupyter.widget-view+json": {
"colab": {
"custom_widget_manager": {
"url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/b3e629b1971e1542/manager.min.js"
}
}
}
}
}
],
"source": [
"#@title Hbox for passage (make box)\n",
"d_btn_passage = {}\n",
"\n",
"def box_of_passage_selection():\n",
" list_btn_passage = []\n",
" for i in range(len(my_doc['passages'])):\n",
" d_btn_passage[i] = Button(description=str(i),\n",
" tooltip = my_doc['passages'][i]['text'],\n",
" layout = {\n",
" 'min_width':'35px',\n",
" 'max_width':'35px',\n",
" }\n",
" )\n",
" d_btn_passage[i].on_click(functools.partial(show_passage,))\n",
" list_btn_passage.append(d_btn_passage[i])\n",
" \n",
" x = HBox(list_btn_passage,layout={'width':'auto'},\n",
" overflow='scroll')\n",
" \n",
" return x\n",
" \n",
"box_of_passage_selection()"
],
"id": "WxFn_TuTBZ2R"
},
{
"cell_type": "markdown",
"metadata": {
"id": "4Ve9GWf6FKlY"
},
"source": [
"# 5. the GUI <mark>. </mark> </code>. <mark> . </mark> . <mark> . </mark>"
],
"id": "4Ve9GWf6FKlY"
},
{
"cell_type": "markdown",
"source": [
"## functions"
],
"metadata": {
"id": "9-iO5hyjiXJ3"
},
"id": "9-iO5hyjiXJ3"
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"id": "vMv7kOXzZ-qd",
"cellView": "form"
},
"outputs": [],
"source": [
"#@title GUI . \\ \\ grid_template_areas\n",
"grid_parameters= {'rows' : 'auto 400px auto auto',\n",
" 'columns': '3% 25% 25% 17% 25%',}\n",
"\n",
"layout_Basic= '''\n",
" \"bar header header header header\"\n",
" \"bar main main main sidebar\"\n",
" \"bar main main main sidebar\"\n",
" \"footer footer footer footer footer\"\n",
" '''\n",
"layout_idE_info = '''\n",
" \"bar header header header header\"\n",
" \"bar main main main sidebar \"\n",
" \"bar main main main info \"\n",
" \"footer footer footer footer footer\"\n",
" '''"
],
"id": "vMv7kOXzZ-qd"
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"id": "pLhwivCbpc-f",
"cellView": "form"
},
"outputs": [],
"source": [
"#@title word_token_to_d_sentences_idT\n",
"\n",
"'''make a dictionary where the key is the sentence_id and the value is a list of the word_ids (token_id)\n",
"e.g. {1: ['I_0', 'have_0', 'lost_0', 'the_0', 'game_0'],\n",
" 2: ['I_1', 'do_0', 'not_0', 'give_0', 'up_0'],\n",
" ....,\n",
" }\n",
"'''\n",
"\n",
"def word_token_to_d_sentences_idT(id_passage):\n",
" dff = df_my_doc.loc[df_my_doc['passage'] == id_passage]\n",
" sentences_as_token = [[]]\n",
" prev_id = 0\n",
" for index, row in dff.iterrows():\n",
" if row['sentence_id'] == prev_id:\n",
" sentences_as_token[-1].append(index)\n",
" else:\n",
" prev_id +=1\n",
" sentences_as_token.append([index])\n",
"\n",
" d_sentences_idT = {key: sentence for key, sentence in enumerate(sentences_as_token)}\n",
" return d_sentences_idT\n",
" "
],
"id": "pLhwivCbpc-f"
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"id": "-gnFlzUIjIIV",
"cellView": "form"
},
"outputs": [],
"source": [
"#@title def make_word_sub_unit\n",
"\n",
"def make_word_sub_unit(new_id_token, memory, sentence_id): \n",
"\n",
" button2 = widgets.IntText(value=0, \n",
" layout = {'width':'40px',\n",
" 'min_width':'20px',\n",
" 'hight': \"15px\"\n",
" }\n",
" )\n",
" setattr(button2, \"id_token\", new_id_token)\n",
" df_my_doc.at[new_id_token,'button2'] = button2\n",
"\n",
" button2_NER = Button(\n",
" tooltip=\"press\",\n",
" layout={'width': '5px', 'height': '15px',\n",
" },\n",
" )\n",
" button2_NER.style.button_color = 'DarkBlue'\n",
" setattr(button2_NER, \"id_token\", new_id_token)\n",
" # button2_NER.on_click(functools.partial(join_NE, memory_NE=memory, sentence_id=sentence_id))\n",
" df_my_doc.at[new_id_token,'button2_NER'] = button2_NER\n",
"\n",
"\n",
" button3 = Button(\n",
" layout={'width': '5px', 'height': '15px'})\n",
" button3.style.button_color = 'Blue'\n",
" setattr(button3, \"id_token\", new_id_token)\n",
" df_my_doc.at[new_id_token,'button3'] = button3\n"
],
"id": "-gnFlzUIjIIV"
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"id": "dXgEuFdpINnS",
"cellView": "form"
},
"outputs": [],
"source": [
"#@title Text-to-button-DataFrame 👢 🏃\n",
"\n",
"'''by going over every word token, making a pd.DataFrame to store all information'''\n",
"def make_word_btn_column(id_passage, sentence_from_to,d_sentences_idT):\n",
" for id_sent, sentence in d_sentences_idT.items():\n",
" for id_token in sentence:\n",
" word = id_token.rpartition('_')[0]\n",
"\n",
" df_my_doc.loc[id_token,'word_btn'] = widgets.Button(description = word,\n",
" layout={'width': 'auto', \"description_width\": \"min-width\"})\n",
"\n",
" # df_my_doc.at[id_token,'word_btn'].on_click(functools.partial(run_word_button_action))\n",
" df_my_doc.at[id_token,'word_btn'].add_class(\"narrow_button\")\n",
" setattr(df_my_doc.at[id_token,'word_btn'], \"id_token\", id_token)\n"
],
"id": "dXgEuFdpINnS"
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"id": "ofcrAW0GWQwm",
"cellView": "form"
},
"outputs": [],
"source": [
"#@title def make_word_sub_unit\n",
"\n",
"def make_word_sub_unit(new_id_token, memory, sentence_id): \n",
"\n",
" button2 = widgets.IntText(value=0, \n",
" )\n",
" setattr(button2, \"id_token\", new_id_token)\n",
" df_my_doc.at[new_id_token,'button2'] = button2\n",
"\n",
" button2_NER = Button(layout={'width': '5px', 'height': '15px'})\n",
" button2_NER.style.button_color = 'DarkBlue'\n",
" setattr(button2_NER, \"id_token\", new_id_token)\n",
" # button2_NER.on_click(functools.partial(join_NE, memory_NE=memory, sentence_id=sentence_id))\n",
" df_my_doc.at[new_id_token,'button2_NER'] = button2_NER\n",
"\n",
"\n",
"def word_btns_to_box(df_my_doc, id_passage):\n",
" lst_per_sentence = []\n",
" lst_new = []\n",
" global lst_new2\n",
"\n",
" id_of_sentence = df_my_doc.iloc[0,df_my_doc.columns.get_loc('sentence_id')]\n",
"\n",
" df_token = df_my_doc.loc[df_my_doc['passage'] == id_passage]\n",
"\n",
" for sentence_id, sentence_idT in sorted(d_sentences_idT.items()):\n",
" for i, id_token in enumerate(sentence_idT):\n",
" row = df_my_doc.loc[id_token,:]\n",
"\n",
" '''STARTING from here'''\n",
" \n",
" make_word_sub_unit(id_token, memory, row['sentence_id'])\n",
" button2, button2_NER = list(df_my_doc.loc[id_token,['button2', 'button2_NER']])\n",
" \n",
" btn_unit_A =VBox([button2_NER])\n",
" # btn_unit = HBox([btn_unit_A]) # \n",
" btn_unit = HBox([button2,btn_unit_A])\n",
" \n",
" '''ENDING here\n",
" \n",
" THIS CODE CAUSES THE ERRORENOUS BEHAVIOUR\n",
" '''\n",
" # word_unit = VBox([row['word_btn'],btn_unit])\n",
" word_unit = VBox([row['word_btn']])\n",
" if row['sentence_id'] != id_of_sentence :\n",
" print(row['sentence_id'])\n",
" lst_new.append(lst_per_sentence)\n",
" lst_per_sentence = []\n",
" id_of_sentence = row['sentence_id']\n",
"\n",
" \n",
" lst_per_sentence.append(word_unit)\n",
" print(str(row['sentence_id']) + ' is last')\n",
" lst_new.append(lst_per_sentence)\n",
" lst_new2 = []#\n",
"\n",
" for i in range(len(lst_new)):\n",
" lst_new2.append(\n",
" HBox(lst_new[i],layout={'flex_flow':'row wrap','width':'auto','border': '1px solid black'})\n",
" )\n",
" lst_new2[i].add_class('sentence_box')\n",
" return lst_new2"
],
"id": "ofcrAW0GWQwm"
},
{
"cell_type": "markdown",
"metadata": {
"id": "Ip8IfDgcMyac"
},
"source": [
"## <font color=\"magenta\"> 5.2 GUI restart"
],
"id": "Ip8IfDgcMyac"
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"id": "ezEoWTG6boq7",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"outputId": "5a5b028b-3038-427f-a254-d8c0b1a16b58"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"0 is last\n"
]
}
],
"source": [
"#@title <mark> the GUI _ _ \n",
"\n",
"sentence_from_to = [0, -1] # means from first to last sentence of the passage.\n",
"id_passage = 0 # passage to display initially.\n",
"d_sentences_idT = word_token_to_d_sentences_idT(id_passage)\n",
"\n",
"make_word_btn_column(id_passage, sentence_from_to,d_sentences_idT)\n",
"memory = {} # is argument in many functions but not used in this code\n",
"lst_new2 = word_btns_to_box(df_my_doc, id_passage)\n",
"\n",
"\n",
"header = VBox([ box_of_passage_selection()],\n",
" layout={'width' :'auto',\n",
" 'grid_area' :'header'})\n",
"\n",
"main = VBox(lst_new2, layout={'flex_flow':'row wrap',\n",
" 'width':'auto', 'grid_area':'main',\n",
" 'max_height':'600px'},overflow='scroll')\n",
"\n",
"GUI = GridBox(children=[header, main,\n",
" ],\n",
" layout={ 'width' : '100%',\n",
" 'grid_template_rows' : grid_parameters['rows'],\n",
" 'grid_template_columns': grid_parameters['columns'],\n",
" 'grid_template_areas' : layout_Basic}\n",
" )"
],
"id": "ezEoWTG6boq7"
},
{
"cell_type": "markdown",
"metadata": {
"id": "D8rAF-z1M6ib"
},
"source": [
"## 5.3 the GUI\n",
"\n",
"Each number will display a different section, however, for some long sections (section 2, 9, ...) they are not displayed if I displayed other sections before.\n",
" For each sentence, it should print the sentence_id (index). For some long sections, some are mistakenly skipped\n",
"\n",
"\n",
"Pressing 2, then 9, then 2 will likely break the GUI. If it doesn't break the GUI, press any other number and then 2 again. After 8 clicks, the GUI almost certainly has broken."
],
"id": "D8rAF-z1M6ib"
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"id": "drqn-LqICYrl",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 455,
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