A Rat Model of Cigarette Smoke Abuse Liability

We sought to develop a rat model of cigarette smoke exposure (CSE) that created cotinine serum levels comparable to those of smokers and induced conditioned place preference (CPP) suggestive of cigarette smoke abuse liability. Rats were exposed to sidestream cigarette smoke delivered semicontinuously for 2 periods of 20 (group S20), 40 (group S40), or 60 (group S60) min daily for 12 wk. Serum cotinine concentration in blood samples was determined at 1 and 20 h after CSE. A biased (black versus white chamber) CPP paradigm was used. In the high CSE group (group S60), serum cotinine at 1 h (250 to 300 ng/mL) was comparable to average cotinine levels reported for addicted smokers (around 300 ng/mL). Cotinine levels at 20 h after CSE were higher than the smoker–nonsmoker cut-off value (greater than 14 ng/mL) in all smoking groups, with the S60 group having the highest levels. All rats preferred the black chamber to the white chamber during the preexposure CPP test. The time spent in the white chamber was increased compared with 0-wk values in group S40 at 8 wk, group S60 at 4 and 8 wk, and the control group at 4 and 8 wk but not at 12 wk; however, the shift in CPP was significantly higher at 8 wk in group S60 compared with other groups. In conclusion, interrupted 2-h daily CSE for 8 wk induced serum cotinine levels in rats comparable to those of smokers and induced CPP suggestive of cigarette smoke abuse liability.Abbreviations: CPP, conditioned place preference; CSE, cigarette smoke exposureThe devastating consequences of smoking on health have been studied extensively in numerous clinical and animal studies over time. This chronic habit leads to dependence on tobacco smoke, with nicotine, a main active ingredient of tobacco products, being recognized as the basic addictive substance.³²The known health benefits of smoking cessation motivate smokers to quit tobacco use. However, unaided efforts usually are unsuccessful, resulting in smoking relapse. The fight against nicotine addiction may be undermined by potential weight gain after smoking cessation, potentially discouraging those attempting to quit smoking and contributing to relapse. During the past few years, research has been focused on 2 main areas of interest toward this direction: understanding the underlying biologic mechanisms related to nicotine addiction to effectively design therapeutic strategies to support those who wish to quit smoking and investigating the hormonal and molecular mechanisms responsible for weight gain after smoking cessation.So far, animal models used to study the consequences of smoking cessation involved the administration of nicotine as a sole agent until addiction was achieved.²³ However, nicotine-administration models do not completely represent the toxic and addictive effects of cigarette smoke, given that smoke contains more than 4000 chemicals whose actions or coactions have not been thoroughly evaluated yet.¹ Cigarette smoke exposure (CSE) animal models have been used in studies investigating the metabolic changes conferred by smoking^10-12 but not in those after its cessation. In toxicity studies, animals are exposed to tobacco smoke for various periods, which depend on the side effect under investigation.^18,25,27 Smoke exposure timetables usually do not involve weekends for practical reasons, and addiction of animals to tobacco smoke is not assessed in current models.In our opinion, an ideal animal model of cigarette smoke abuse liability suitable for the study of smoking cessation resembles the clinical situation in terms of chronic daily inhalation of cigarette smoke sufficient to attain blood nicotine levels comparable to those of smokers and in cessation of the CSE period after achieving tobacco smoke abuse liability. In the present project, we sought to establish such a model in rats by defining the daily timetable of CSE to induce serum levels of cotinine, nicotine''s major proximate metabolite, comparable to those of smokers and by determining the minimum total CSE period required to induce abuse liability to cigarette smoke. We assessed the CSE period by using a biased conditioned place preference (CPP) paradigm.⁸     

Mass spectrometric characterization of human N-acylethanolamine-hydrolyzing acid amidase

N-Acylethanolamine-hydrolyzing acid amidase (NAAA) is a lysosomal enzyme that primarily degrades palmitoylethanolamine (PEA), a lipid amide that inhibits inflammatory responses. We developed a HEK293 cell line stably expressing the NAAA pro-enzyme (zymogen) and a single step chromatographic purification of the protein from the media. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry MALDI-TOF MS analysis of the zymogen (47.7 kDa) treated with peptide-N-glycosidase F (PNGase F) identified 4 glycosylation sites, and acid cleavage of the zymogen into α- and β-subunits (14.6 and 33.3 kDa) activated the enzyme. Size exclusion chromatography estimated the mass of the active enzyme as 45 ± 3 kDa, suggesting formation of an α/β heterodimer. MALDI-TOF MS fingerprinting covered more than 80% of the amino acid sequence, including the N-terminal peptides, and evidence for the lack of a disulfide bond between subunits. The significance of the cysteine residues was established by their selective alkylation resulting in almost complete loss of activity. The purified enzyme was kinetically characterized with PEA and a novel fluorogenic substrate, N-(4-methyl coumarin) palmitamide (PAMCA). The production of sufficient quantities of NAAA and a high throughput assay could be useful in discovering novel inhibitors and determining the structure and function of this enzyme.     

A format for phylogenetic placements

We have developed a unified format for phylogenetic placements, that is, mappings of environmental sequence data (e.g., short reads) into a phylogenetic tree. We are motivated to do so by the growing number of tools for computing and post-processing phylogenetic placements, and the lack of an established standard for storing them. The format is lightweight, versatile, extensible, and is based on the JSON format, which can be parsed by most modern programming languages. Our format is already implemented in several tools for computing and post-processing parsimony- and likelihood-based phylogenetic placements and has worked well in practice. We believe that establishing a standard format for analyzing read placements at this early stage will lead to a more efficient development of powerful and portable post-analysis tools for the growing applications of phylogenetic placement.     

Genetic diversity, structure, and size of an endangered brown bear population threatened by highway construction in the Pindos Mountains, Greece

One of the major negative effects of roads is the creation of barriers to the movement of wildlife, ultimately disconnecting populations and increasing extinction risk. We collected genetic data from a threatened brown bear population in the central part of the Pindos mountain range in northwestern Greece to provide information about this, as yet genetically undescribed, population and to evaluate its status prior to the construction of a major highway. We used noninvasive genetic sampling methods and microsatellite analysis to investigate nuclear genetic diversity, population genetic structure, demographic history, relatedness within the population and estimated effective and total population size. Brown bears in the study area were found to possess a relatively high level of nuclear genetic diversity and low levels of inbreeding; the population did not show any signs of substructuring but seems to have gone through a genetic bottleneck in the recent past. The estimated effective population size was 29, and the total population size estimate obtained by two different methods was 33 and 51 individuals, respectively. Our results indicate a good conservation status of this bear population and provide baseline genetic data for the future evaluation of the effects on bears from the construction of a major highway, for monitoring the genetic status of this and other bear populations in Greece and for assessing gene flow in bear populations in southern Europe.     

Sub-arctic Populations of European Lobster, Homarus gammarus, in Northern Norway

The European lobster is distributed throughout the south and western regions of the Norwegian coast. A previous lobster allozyme investigation (1993) in the Tysfjord region, north of the Arctic Circle demonstrated that the lobster population from this region was genetically different from lobster samples collected in other parts of Norway. More detailed investigation including supplementary extensive sampling and additional allozyme, microsatellite and mtDNA analyses are reported here. This investigation supports the genetic distinctness of the Tysfjord population and shows that this is mainly due to a reduction (60–70%) in gene diversity (observed heterozygosities and number of alleles) compared with lobsters from more southern regions. In addition to the Tysfjord region, the comprehensive sampling also included lobsters found in the adjacent Nordfolda fjord system. Genetic analyses provided evidence for significant differences between the lobster populations of Tysfjord and Nordfolda, even though they are separated by a coastal distance of only 142 km. The two populations were also different with regards to several biological characteristics such as body size. The genetic difference between these two geographically close populations is likely to be due to the local hydrological conditions, preventing larval dispersal between the fjord systems. Assessment of lobster abundance in the north-west region suggests that the sub-arctic lobster populations are geographically isolated.     

Conditioned Medium from Early-Outgrowth Bone Marrow Cells Is Retinal Protective in Experimental Model of Diabetes

Bone marrow-derived cells were demonstrated to improve organ function, but the lack of cell retention within injured organs suggests that the protective effects are due to factors released by the cells. Herein, we tested cell therapy using early outgrowth cells (EOCs) or their conditioned media (CM) to protect the retina of diabetic animal models (type 1 and type 2) and assessed the mechanisms by in vitro study. Control and diabetic (db/db) mice (8 weeks of age) were randomized to receive a unique intravenous injection of 5×10⁵EOCs or 0.25 ml thrice weekly tail-vein injections of 10x concentrated CM and Wystar Kyoto rats rendered diabetic were randomized to receive 0.50 ml thrice weekly tail-vein injections of 10x concentrated CM. Four weeks later, the animals were euthanized and the eyes were enucleated. Rat retinal Müller cells (rMCs) were exposed for 24 h to high glucose (HG), combined or not with EOC-conditioned medium (EOC-CM) from db/m EOC cultures. Diabetic animals showed increase in diabetic retinopathy (DR) and oxidative damage markers; the treatment with EOCs or CM infusions significantly reduced this damage and re-established the retinal function. In rMCs exposed to diabetic milieu conditions (HG), the presence of EOC-CM reduced reactive oxygen species production by modulating the NADPH-oxidase 4 system, thus upregulating SIRT1 activity and deacetylating Lys-310-p65-NFκB, decreasing GFAP and VEGF expressions. The antioxidant capacity of EOC-CM led to the prevention of carbonylation and nitrosylation posttranslational modifications on the SIRT1 molecule, preserving its activity. The pivotal role of SIRT1 on the mode of action of EOCs or their CM was also demonstrated on diabetic retina. These findings suggest that EOCs are effective as a form of systemic delivery for preventing the early molecular markers of DR and its conditioned medium is equally protective revealing a novel possibility for cell-free therapy for the treatment of DR.     

Comprehensible Predictive Modeling Using Regularized Logistic Regression and Comorbidity Based Features

Different studies have demonstrated the importance of comorbidities to better understand the origin and evolution of medical complications. This study focuses on improvement of the predictive model interpretability based on simple logical features representing comorbidities. We use group lasso based feature interaction discovery followed by a post-processing step, where simple logic terms are added. In the final step, we reduce the feature set by applying lasso logistic regression to obtain a compact set of non-zero coefficients that represent a more comprehensible predictive model. The effectiveness of the proposed approach was demonstrated on a pediatric hospital discharge dataset that was used to build a readmission risk estimation model. The evaluation of the proposed method demonstrates a reduction of the initial set of features in a regression model by 72%, with a slight improvement in the Area Under the ROC Curve metric from 0.763 (95% CI: 0.755–0.771) to 0.769 (95% CI: 0.761–0.777). Additionally, our results show improvement in comprehensibility of the final predictive model using simple comorbidity based terms for logistic regression.