The FODRAT study (FOod addiction, DRugs, Alcohol and Tobacco): first data on food addiction prevalence among patients with addiction to drugs, tobacco and alcohol.

OBJECTIVES: The main focus of this study was to evaluate the prevalence of food addiction (FA) in a population of 575 subjects, all affected by drugs, alcohol and/or tobacco addiction. METHODS: Patients were enrolled in Addiction Service Centers and 25 items YFAS questionnaire was administered. Prevalence of FA was studied among patients who already have an addiction and then this prevalence was compared between groups of abusers (by type of substance), comparing mono abusers with polyabusers, as well as regressions by age, BMI, sex, through multiple regression analysis. RESULTS: Prevalence of FA in the sample is 20.17%. Risk of FA increases with the number of substances used (polyabuse). Results show a positive correlation, in addicted people, between BMI values and FA, with significant values (OR 1.08; 95% CI 1.04-1.13; p = 0.006). Age is inversely correlated with FA (OR 0.97; 95% CI 0.95-0.99; p = 0.01). Female sex is positively associated (OR 2.60; 95% CI 1.59-4.27, p = 0.000). No significant association appears with any substance, even if the highest prevalence is recorded among cannabis users (31.03%), and heroin (21.07%), followed by cocaine (18.53%), alcohol (14.49%) and tobacco (11.61%). A comparison between the FA prevalence in our study and that from another study in the Italian general population (11%) shows a significant difference (p < 0.001). CONCLUSIONS: Prevalence of FA among addicted people is greater than in the general population. Risk of FA increases with the increase in number of used substances (polyabuse). Age is inversely correlated with FA. There is a positive and significant correlation between BMI and FA among substance/tobacco abusers. LEVEL OF EVIDENCE: Level V, observational cross-sectional descriptive study.

A genome-wide association study for a proxy of intermuscular fat level in the Italian Large White breed identifies genomic regions affecting an important quality parameter for dry-cured hams.

Intermuscular fat content in protected designations of origin dry-cured hams is a very important meat quality trait that affects the acceptability of the product by the consumers. An excess in intermuscular fat (defined as the level of fat deposition between leg muscles) is a defect that depreciates the final product. In this study we carried out a genome-wide association study for visible intermuscular fat (VIF) of hams in the Italian Large White pig breed. This trait was evaluated on the exposed muscles of green legs in 1122 performance-tested gilts by trained personnel, according to a classification scale useful for routine and cheap evaluation. All animals were genotyped with the Illumina PorcineSNP60 BeadChip. The genome-wide association study identified three QTL regions on porcine chromosome 1 (SSC1; accounting for ~79% of the SNPs below the 5.0E-04 threshold) and SSC2, two on SSC7 and one each on SSC3, SSC6, SSC9, SSC11, SSC13, SSC15, SSC16 and SSC17. The most significant SNP (ALGA0004143 on SSC1 at 77.3 Mb; PFDR  < 0.05), included in the largest QTL region which spanned about 6.8 Mb on SSC1, is located within the glutamate ionotropic receptor kainate type subunit 2 (GRIK2) gene. Functional annotation of all genes included in QTL regions for VIF suggested that intermuscular fat in the Italian Large White breed is a complex trait apparently influenced by complex biological mechanisms also involving obesity-related processes. These QTL target mainly chromosome regions different from those affecting subcutaneous and intramuscular fat deposition.

Genome-wide association study for ham weight loss at first salting in Italian Large White pigs: towards the genetic dissection of a key trait for dry-cured ham production.

Protected designation of origin dry-cured hams are the most important productions of the Italian heavy pig industry. Hams capable of minimal seasoning losses produce better quality dry-cured hams. Ham weight loss during the first 7 days in brine (first salting) is highly correlated with the total loss of weight up to the end of seasoning, and it has quite high heritability (0.30-0.61). For these reasons, ham weight loss at first salting has been included as a meat quality trait in the Italian heavy pig selection program. In this work, we carried out a genome-wide association study for this parameter in the Italian Large White pig breed by genotyping 1365 animals with the Illumina BeadChip PorcineSNP60 chip. A total of 44 single nucleotide polymorphisms (SNPs) had a Pnominal value below 5.0E-04, five of which were below 5.0E-05 and one of them (ALGA0057985 on chromosome 10) was associated with this trait at a PBonferroni threshold of 0.10. These SNPs identified a total of at least 29 putative QTLs that were located on most porcine autosomal chromosomes. This study provides genomic information that could be useful in dissecting this complex trait by identifying potential candidate genes whose function could contribute to understanding the biological mechanisms affecting meat quality for seasoning aptitude.

Ultrafast dynamics in unaligned MWCNTs decorated with metal nanoparticles.

The relaxation dynamics of unaligned multi-walled carbon nanotubes decorated with metallic nanoparticles have been studied by using transient optical measurements. The fast dynamics due to the short-lived free-charge carriers excited by the pump are not affected by the presence of nanoparticles. Conversely, a second long dynamics, absent in bare carbon nanotubes, appears only in the decorated samples. A combination of experiment and theory allows us to ascribe this long dynamics to relaxation channels involving electronic states localized at the tube-nanoparticle interface.

Genome-wide association study for the level of serum electrolytes in Italian Large White pigs.

Calcium, magnesium and phosphorus are essential electrolytes involved in a large number of biological processes. Imbalance of these minerals in blood may indicate clinically relevant conditions and are important in inferring acute or chronic pathologies in humans and animals. In this work, we carried out a genome-wide association study (GWAS) for the level of these three electrolytes in the serum of 843 performance-tested Italian Large White pigs. All pigs were genotyped with the Illumina PorcineSNP60 BeadChip, and GWAS was carried out using genome-wide efficient mixed-model association. For the level of Ca(2+) , eight single nucleotide polymorphisms (SNPs) were significant, considering a false discovery rate (FDR) < 0.05, and another eight were above the moderate association threshold (Pnominal value  < 5.00E-05). These SNPs are distributed in four porcine chromosomes (SSC): SSC8, SSC11, SSC12 and SSC13. In particular, a few putative different signals of association detected on SSC13 and one on SSC12 were in genes or close to genes involved in calcium metabolism (P2RY1, RAP2B, SLC9A9, C3orf58, TSC22D2, PLCH1 and CACNB1). Only one SNP (on SSC7) and six SNPs (on SSC2 and SSC7) showed moderate association with the level of magnesium and phosphorus respectively. The association signals for these two latter minerals might identify genes not known thus far for playing a role in their biological functions and regulations. In conclusion, our GWAS contributed to increased knowledge on the role that calcium, magnesium and phosphorus may play in the genetically determined physiological mechanisms affecting the natural variability of mineral levels in mammalian blood.

Twenty years of artificial directional selection have shaped the genome of the Italian Large White pig breed.

In this study, we investigated at the genome-wide level if 20 years of artificial directional selection based on boar genetic evaluation obtained with a classical BLUP animal model shaped the genome of the Italian Large White pig breed. The most influential boars of this breed (n = 192), born from 1992 (the beginning of the selection program of this breed) to 2012, with an estimated breeding value reliability of >0.85, were genotyped with the Illumina Porcine SNP60 BeadChip. After grouping the boars in eight classes according to their year of birth, filtered single nucleotide polymorphisms (SNPs) were used to evaluate the effects of time on genotype frequency changes using multinomial logistic regression models. Of these markers, 493 had a PBonferroni  < 0.10. However, there was an increasing number of SNPs with a decreasing level of allele frequency changes over time, representing a continuous profile across the genome. The largest proportion of the 493 SNPs was on porcine chromosome (SSC) 7, SSC2, SSC8 and SSC18 for a total of 204 haploblocks. Functional annotations of genomic regions, including the 493 shifted SNPs, reported a few Gene Ontology terms that might underly the biological processes that contributed to increase performances of the pigs over the 20 years of the selection program. The obtained results indicated that the genome of the Italian Large White pigs was shaped by a directional selection program derived by the application of methodologies assuming the infinitesimal model that captured a continuous trend of allele frequency changes in the boar population.

Lentigo Maligna: Keys to Dermoscopic Diagnosis. / Lentigo maligno. Claves en el diagnóstico dermatoscópico.

Dermoscopy is a noninvasive technique that improves accuracy in the diagnosis of cutaneous lesions. The recognition and differential diagnosis of lentigo maligna (LM) and lentigo maligna melanoma (LMM) is challenging, especially in the early stages when there are no distinctive clinical features. Early diagnosis and appropriate treatment can improve prognosis. Several dermoscopic features have been described for LM and LMM. The following 4 criteria in combination have achieved a diagnostic sensitivity of 89% and a specificity of 96%: asymmetric pigmented follicular openings, dark rhomboidal structures, slate gray dots, and slate gray globules. A biopsy is warranted when dermoscopic examination reveals a grayish coloring. For a flat pigmented lesion acquired in adulthood, a histopathological diagnosis of "atypical junctional nevus" is not to be accepted uncritically. LM and LMM can also appear in sites other than the face, and dermoscopy can facilitate their recognition. Dermoscopy is an essential tool for physical examination.

Combined use of principal component analysis and random forests identify population-informative single nucleotide polymorphisms: application in cattle breeds.

The genetic identification of the population of origin of individuals, including animals, has several practical applications in forensics, evolution, conservation genetics, breeding and authentication of animal products. Commercial high-density single nucleotide polymorphism (SNP) genotyping tools that have been recently developed in many species provide information from a large number of polymorphic sites that can be used to identify population-/breed-informative markers. In this study, starting from Illumina BovineSNP50 v1 BeadChip array genotyping data available from 3711 cattle of four breeds (2091 Italian Holstein, 738 Italian Brown, 475 Italian Simmental and 407 Marchigiana), principal component analysis (PCA) and random forests (RFs) were combined to identify informative SNP panels useful for cattle breed identification. From a PCA preselected list of 580 SNPs, RFs were computed using ranking methods (Mean Decrease in the Gini Index and Mean Accuracy Decrease) to identify the most informative 48 and 96 SNPs for breed assignment. The out-of-bag (OOB) error rate for both ranking methods and SNP densities ranged from 0.0 to 0.1% in the reference population. Application of this approach in a test population (10% of individuals pre-extracted from the whole data set) achieved 100% of correct assignment with both classifiers. Linkage disequilibrium between selected SNPs was relevant (r(2) > 0.6) only in few pairs of markers indicating that most of the selected SNPs captured different fractions of variance. Several informative SNPs were in genes/QTL regions that affect or are associated with phenotypes or production traits that might differentiate the investigated breeds. The combination of PCA and RF to perform SNP selection and breed assignment can be easily implemented and is able to identify subsets of informative SNPs useful for population assignment starting from a large number of markers derived by high-throughput genotyping platforms.

A retrospective analysis of allele frequency changes of major genes during 20 years of selection in the Italian Large White pig breed.

In this study, we investigated whether a selection programme based on boar genetic evaluation obtained with a classical BLUP animal model can change allele frequencies in a pig population. All Italian Large White boars born from 1992 to 2012 with estimated breeding value reliability >0.85 (n = 200) were selected among all boars of this breed. Boars were genotyped with markers in major genes (IGF2 intron3-g.3072G>A, MC4R p.D298N, VRTN PRE1 insertion, PRKAG3 p.I199V and FTO g.276T>G). Genotyping data were analysed grouping boars in eight classes according to their year of birth. To evaluate the influence of time on allele frequencies of the genotyped markers, multinomial logistic regression models were computed. Four of five polymorphic sites (IGF2, MC4R, VRTN and FTO) showed significant (p < 0.01) changes in allele frequencies over time due to a progressive and continuous increase of one allele (associated with higher lean meat content, higher average daily gain and favourable feed: gain ratio) and, consequently, decrease of the other one, following the directional selection of the selection programme of this pig breed. The retrospective analysis that was carried out in Italian Large White boars suggests that selection based on methodologies assuming the infinitesimal model is able to modify in a quite short period of time allele frequencies in major genes, increasing the frequency of alleles explaining a relevant (non-infinitesimal) fraction of the overall genetic variability for production traits.

Copy number variants in Italian Large White pigs detected using high-density single nucleotide polymorphisms and their association with back fat thickness.

The aim of this study was to identify copy number variants (CNVs) in Italian Large White pigs and test them for association with back fat thickness (BFT). Within a population of 12 000 performance-tested pigs, two groups of animals with extreme and divergent BFT estimated breeding values (EBVs; 147 with negative and 150 with positive EBVs) were genotyped with the Illumina Porcine SNP60 BeadChip. CNVs were detected with PENNCNV software. We identified a total of 4146 CNV events in 170 copy number variation regions (CNVRs) located on 15 porcine autosomes. Validation of detected CNVRs was carried out (i) by comparing CNVRs already detected by other studies and (ii) by semiquantitative fluorescent multiplex (SQFM) PCR of a few CNVRs. Most of CNVRs detected in Italian Large White pigs (71.2%) were already reported in other pig breeds/populations, and 82.1% of the CNV events detected by PENNCNV were confirmed by SQFM PCR. For each CNVR, we compared the occurrence of CNV events between the pigs of the high and low BFT EBV tails. Sixteen regions showed significance at P < 0.10, and seven were significant at P < 0.05 but were not significant after Bonferroni correction (Fisher's exact test). These results indicated that CNVs could explain a limited fraction of the genetic variability of fat deposition in Italian Large White pigs. However, it was interesting to note that one of these CNVRs encompassed the ZPLD1 gene. In humans, a rare CNV event including this gene is associated with obesity. Studies identifying CNVs in pigs could assist in elucidating the genetic mechanisms underlying human obesity.

A candidate gene association study for nine economically important traits in Italian Holstein cattle.

We genotyped 58 single nucleotide polymorphisms (SNPs) in 25 candidate genes in about 800 Italian Holstein sires. Fifty-six (minor allele frequency >0.02) were used to evaluate their association with single traits: milk yield (MY), milk fat yield (FY), milk protein yield (PY), milk fat percentage (FP), milk protein percentage (PP), milk somatic cell count (MSCC); and complex indexes: longevity, fertility and productivity-functionality type (PFT), using deregressed proofs, after adjustment for familial relatedness. Thirty-two SNPs were significantly associated (proportion of false positives <0.05) with different traits: 16 with MSCC, 15 with PY, 14 with MY, 12 with PFT, eight with longevity, eight with FY, eight with PP, five with FP and two with fertility. In particular, a SNP in the promoter region of the PRLR gene was associated with eight of nine traits. DGAT1 polymorphisms were highly associated with FP and FY. Casein gene markers were associated with several traits, confirming the role of the casein gene cluster in affecting milk yield, milk quality and health traits. Other SNPs in genes located on chromosome 6 were associated with PY, PP, PFT, MY (PPARGC1A) and MSCC (KIT). This latter association may suggest a biological link between the degree of piebaldism in Holstein and immunological functions affecting somatic cell count and mastitis resistance. Other significant SNPs were in the ACACA, CRH, CXCR1, FASN, GH1, LEP, LGB (also known as PAEP), MFGE8, SRC, TG, THRSP and TPH1 genes. These results provide information that can complement QTL mapping and genome-wide association studies in Holstein.

Photoinduced π-π* band gap renormalization in graphite.

As is well-known, the character of the π orbitals is of paramount importance for the chemical properties of the carbon allotropes and their derived compounds. While at equilibrium the nature of these orbitals is well understood, their photoinduced nonequilibrium behavior is under investigation. Here, we demonstrate that when a UV-laser pulse excites a carrier density larger than 10% of the π* density of state in graphite, a renormalization of the π-π* band gap takes place. This result has been achieved by detecting the transient reflectivity and the associated decay time of an infrared probe following the excitation of a UV pump pulse tuned across the π-π* absorption resonance. The pump photon energy at which both the transient reflectivity and the decay time are maximum is downshifted by 500 meV with respect to the relative absorption maximum at equilibrium. This finding is interpreted as a transient π-π* band gap shrinking of similar magnitude, near the M point of the Brillouin zone.

[Mohs micrographic surgery for the treatment of basal cell carcinoma]. / Cirugía micrográfica de Mohs en el tratamiento de carcinoma basocelular.

INTRODUCTION: Basal cell carcinoma accounts for 75% of all nonmelanoma skin cancer. Although various treatment modalities are available, the most frequently used option is surgical excision. Here, we evaluate the efficacy of Mohs micrographic surgery for the treatment of basal cell carcinoma. MATERIAL AND METHODS: A retrospective review of cases of basal cell carcinoma treated with Mohs micrographic surgery between October 2003 and June 2009 was performed using patient records from Hospital Italiano in Buenos Aires, Argentina. RESULTS: A total of 2412 basal cell carcinomas treated with Mohs micrographic surgery were identified; 50.5% were in women and 49.5% in men. The mean age of the patients was 70.7 years (range, 8-100 years). The histologic type of the tumor was solid in 65.3% of cases and in 89% of cases the tumor was located on the head or neck. Ten percent of the tumors were recurrent following previous treatment. A mean of 1.74 Mohs stages were used, with a mean of 3.81 sections. The mean size of the initial defect was 0.86 cm² and the mean final defect was 1.88 cm². The ratio of initial tumor size to final defect was estimated at 1.02. Over a mean follow-up of 32 months, there were 9 cases of tumor recurrence (0.37%). CONCLUSIONS: In our experience, Mohs micrographic surgery is effective for the treatment of high-risk basal cell carcinoma.

A machine learning approach for the identification of population-informative markers from high-throughput genotyping data: application to several pig breeds.

Single nucleotide polymorphisms (SNPs) able to describe population differences can be used for important applications in livestock, including breed assignment of individual animals, authentication of mono-breed products and parentage verification among several other applications. To identify the most discriminating SNPs among thousands of markers in the available commercial SNP chip tools, several methods have been used. Random forest (RF) is a machine learning technique that has been proposed for this purpose. In this study, we used RF to analyse PorcineSNP60 BeadChip array genotyping data obtained from a total of 2737 pigs of 7 Italian pig breeds (3 cosmopolitan-derived breeds: Italian Large White, Italian Duroc and Italian Landrace, and 4 autochthonous breeds: Apulo-Calabrese, Casertana, Cinta Senese and Nero Siciliano) to identify breed informative and reduced SNP panels using the mean decrease in the Gini Index and the Mean Decrease in Accuracy parameters with stability evaluation. Other reduced informative SNP panels were obtained using Delta, Fixation index and principal component analysis statistics, and their performances were compared with those obtained using the RF-defined panels using the RF classification method and its derived Out Of Bag rates and correct prediction proportions. Therefore, the performances of a total of six reduced panels were evaluated. The correct assignment of the animals to its breed was close to 100% for all tested approaches. Porcine chromosome 8 harboured the largest number of selected SNPs across all panels. Many SNPs were included in genomic regions in which previous studies identified signatures of selection or genes (e.g. ESR1, KITL and LCORL) that could contribute to explain, at least in part, phenotypically or economically relevant traits that might differentiate cosmopolitan and autochthonous pig breeds. Random forest used as preselection statistics highlighted informative SNPs that were not the same as those identified by other methods. This might be due to specific features of this machine learning methodology. It will be interesting to explore if the adaptation of RF methods for the identification of selection signature regions could be able to describe population-specific features that are not captured by other approaches.

Preselection statistics and Random Forest classification identify population informative single nucleotide polymorphisms in cosmopolitan and autochthonous cattle breeds.

Commercial single nucleotide polymorphism (SNP) arrays have been recently developed for several species and can be used to identify informative markers to differentiate breeds or populations for several downstream applications. To identify the most discriminating genetic markers among thousands of genotyped SNPs, a few statistical approaches have been proposed. In this work, we compared several methods of SNPs preselection (Delta, F st and principal component analyses (PCA)) in addition to Random Forest classifications to analyse SNP data from six dairy cattle breeds, including cosmopolitan (Holstein, Brown and Simmental) and autochthonous Italian breeds raised in two different regions and subjected to limited or no breeding programmes (Cinisara, Modicana, raised only in Sicily and Reggiana, raised only in Emilia Romagna). From these classifications, two panels of 96 and 48 SNPs that contain the most discriminant SNPs were created for each preselection method. These panels were evaluated in terms of the ability to discriminate as a whole and breed-by-breed, as well as linkage disequilibrium within each panel. The obtained results showed that for the 48-SNP panel, the error rate increased mainly for autochthonous breeds, probably as a consequence of their admixed origin lower selection pressure and by ascertaining bias in the construction of the SNP chip. The 96-SNP panels were generally more able to discriminate all breeds. The panel derived by PCA-chrom (obtained by a preselection chromosome by chromosome) could identify informative SNPs that were particularly useful for the assignment of minor breeds that reached the lowest value of Out Of Bag error even in the Cinisara, whose value was quite high in all other panels. Moreover, this panel contained also the lowest number of SNPs in linkage disequilibrium. Several selected SNPs are located nearby genes affecting breed-specific phenotypic traits (coat colour and stature) or associated with production traits. In general, our results demonstrated the usefulness of Random Forest in combination to other reduction techniques to identify population informative SNPs.

Genome-wide association studies for seven production traits highlight genomic regions useful to dissect dry-cured ham quality and production traits in Duroc heavy pigs.

Protected designation of origin dry-cured hams are obtained from heavy pigs (slaughtered at about 160 kg of live weight). A specific breeding program designed to improve meat quality for this production has included as key traits the level of intermuscular fat between the leg muscles and ham weight loss during the seasoning period together with a balance between fat and lean cuts. In this study we carried out genome-wide association studies for seven traits used in the genetic merit of Italian Duroc heavy pigs, five related to meat and carcass quality traits (visible intermuscular fat, ham weight loss at first salting, backfat thickness, ham weight and lean cuts), and two related to performance and efficiency traits (average daily gain and feed : gain ratio). A total of 573 performance-tested pigs were genotyped with the Illumina PorcineSNP60 BeadChip and genome-wide association analyses were carried out using the Bayes B approach with the 1 Mb window option of GenSel and random residuals for each of the seven traits. Detected windows were supported by independent single nucleotide polymorphism analyses with a linear mixed model (LMM) approach on the same animals for the same traits. A total of 30 windows identifying different quantitative trait loci (QTL) were detected and among those, 27 were confirmed by LMM in one of these traits. Among the confirmed windows, three QTL were reported for visible intermuscular fat, seven for ham weight loss at first salting and five and four for backfat thickness and lean cut, respectively. A total of eight QTL were detected for the other production traits. No overlapping QTL were reported except for one window on porcine chromosome 10 between lean cuts and ham weight that contained the CACNB2 gene that has been already associated with loin marbling score in other Duroc pigs. Several regions contained genes that have been already associated with production traits in other pig breeds, including Duroc lines, related to fat deposition or muscle structure. This work reports, for the first time, genome-wide association study results for several traits in Italian Duroc heavy pigs. These results will be useful to dissect the genetic basis for dry-cured ham production traits that determine the total genetic merit index of Italian Duroc pigs.

Optically induced effective mass renormalization: the case of graphite image potential states.

Many-body interactions with the underlying bulk electrons determine the properties of confined electronic states at the surface of a metal. Using momentum resolved nonlinear photoelectron spectroscopy we show that one can tailor these many-body interactions in graphite, leading to a strong renormalization of the dispersion and linewidth of the image potential state. These observations are interpreted in terms of a basic self-energy model, and may be considered as exemplary for optically induced many-body interactions.