Inference of tobacco and alcohol consumption habits from DNA methylation analysis of blood.

DNA methylation has become a biomarker of great interest in the forensic and clinical fields. In criminal investigations, the study of this epigenetic marker has allowed the development of DNA intelligence tools providing information that can be useful for investigators, such as age prediction. Following a similar trend, when the origin of a sample in a criminal scenario is unknown, the inference of an individual's lifestyle such as tobacco use and alcohol consumption could provide relevant information to help in the identification of DNA donors at the crime scene. At the same time, in the clinical domain, prediction of these trends of consumption could allow the identification of people at risk or better identification of the causes of different pathologies. In the present study, DNA methylation data from the UK AIRWAVE study was used to build two binomial logistic models for the inference of smoking and drinking status. A total of 348 individuals (116 non-smokers, 116 former smokers and 116 smokers) plus a total of 237 individuals (79 non-drinkers, 79 moderate drinkers and 79 drinkers) were used for development of tobacco and alcohol consumption prediction models, respectively. The tobacco prediction model was composed of two CpGs (cg05575921 in AHRR and cg01940273) and the alcohol prediction model three CpGs (cg06690548 in SLC7A11, cg0886875 and cg21294714 in MIR4435-2HG), providing correct classifications of 86.49% and 74.26%, respectively. Validation of the models was performed using leave-one-out cross-validation. Additionally, two independent testing sets were also assessed for tobacco and alcohol consumption. Considering that the consumption of these substances could underlie accelerated epigenetic ageing patterns, the effect of these lifestyles on the prediction of age was evaluated. To do that, a quantile regression model based on previous studies was generated, and the potential effect of tobacco and alcohol consumption with the epigenetic age was assessed. The Wilcoxon test was used to evaluate the residuals generated by the model and no significant differences were observed between the categories analyzed.

The relationship between vertebral compression rates and systemic inflammatory scores in osteoporotic vertebral fractures.

OBJECTIVE: There are many scientific reports on systemic inflammation scores (SIS) associated with decreased bone mineral density in osteoporotic vertebral disease. However, there are no studies on the association of inflammation scores with the risk of collapse in osteoporotic vertebral collapse fractures. The aim of this study was to examine the correlation between the product of platelet and neutrophil counts (PPN), platelet/lymphocyte ratio (PLR), neutrophil/lymphocyte ratio (NLR), and systemic immune inflammation index (SII) derived from complete blood count analysis in cases of osteoporotic vertebral fractures and fracture severity based on vertebral collapse rates. PATIENTS AND METHODS: This study is a retrospective analysis of a cohort of 50 patients aged 50 years or older who presented with osteoporotic vertebral fractures and underwent kyphoplasty at our clinic from 2018 to 2023. The study included both men and women. Computed tomography (CT) and magnetic resonance imaging (MRI) were used to diagnose and differentiate osteoporotic vertebral compression fractures from burst fractures and pathologic fractures. All compression rate measurements were performed with CT. The compression rate of the most affected vertebra (MAV-CR) was calculated. Groups were divided into two categories based on their compression rates: <50% and ≥50%. Initial PPN, PLR, NLR, and SII parameters were used as systemic inflammation scores. RESULTS: No statistically significant differences were found between MAV-CR groups in PPN, PLR, NLR, and SII parameters (p>0.05). No statistically significant correlation was observed between inflammation scores and MAV-CR groups (p>0.05). In this comparison, no significant difference was observed between the selected CBC parameters and the groups divided according to the compression rate (WBC: p=0.725, PC: p=0.069, NC: p=0.732, LC: p=0.513). ROC analysis was performed to analyze the diagnostic tests (AUC=0.372 for PPN, AUC=0.509 for PLR, AUC=0.525 for NLR, and AUC=0.435 for SII). None of the systemic inflammation scores had any predictive value for osteoporotic vertebral collapse fractures. CONCLUSIONS: Although it has been established in the scientific literature that systemic inflammation scores are associated with osteoporotic vertebral fractures, our analysis indicates no statistically significant correlation between the parameters of PPN, PLR, NLR, and SII and the severity of compression fractures in individuals with osteoporotic vertebral fractures. In this study, using systemic inflammation scores as a predictive test for the severity of osteoporotic vertebral fractures does not seem appropriate.

Development of an epigenetic age predictor for costal cartilage with a simultaneous somatic tissue differentiation system.

Age prediction from DNA has been a topic of interest in recent years due to the promising results obtained when using epigenetic markers. Since DNA methylation gradually changes across the individual's lifetime, prediction models have been developed accordingly for age estimation. The tissue-dependence for this biomarker usually necessitates the development of tissue-specific age prediction models, in this way, multiple models for age inference have been constructed for the most commonly encountered forensic tissues (blood, oral mucosa, semen). The analysis of skeletal remains has also been attempted and prediction models for bone have now been reported. Recently, the VISAGE Enhanced Tool was developed for the simultaneous DNA methylation analysis of 8 age-correlated loci using targeted high-throughput sequencing. It has been shown that this method is compatible with epigenetic age estimation models for blood, buccal cells, and bone. Since when dealing with decomposed cadavers or postmortem samples, cartilage samples are also an important biological source, an age prediction model for cartilage has been generated in the present study based on methylation data collected using the VISAGE Enhanced Tool. In this way, we have developed a forensic cartilage age prediction model using a training set composed of 109 samples (19-74 age range) based on DNA methylation levels from three CpGs in FHL2, TRIM59 and KLF14, using multivariate quantile regression which provides a mean absolute error (MAE) of ± 4.41 years. An independent testing set composed of 72 samples (19-75 age range) was also analyzed and provided an MAE of ± 4.26 years. In addition, we demonstrate that the 8 VISAGE markers, comprising EDARADD, TRIM59, ELOVL2, MIR29B2CHG, PDE4C, ASPA, FHL2 and KLF14, can be used as tissue prediction markers which provide reliable blood, buccal cells, bone, and cartilage differentiation using a developed multinomial logistic regression model. A training set composed of 392 samples (n = 87 blood, n = 86 buccal cells, n = 110 bone and n = 109 cartilage) was used for building the model (correct classifications: 98.72%, sensitivity: 0.988, specificity: 0.996) and validation was performed using a testing set composed of 192 samples (n = 38 blood, n = 36 buccal cells, n = 46 bone and n = 72 cartilage) showing similar predictive success to the training set (correct classifications: 97.4%, sensitivity: 0.968, specificity: 0.991). By developing both a new cartilage age model and a tissue differentiation model, our study significantly expands the use of the VISAGE Enhanced Tool while increasing the amount of DNA methylation-based information obtained from a single sample and a single forensic laboratory analysis. Both models have been placed in the open-access Snipper forensic classification website.

Epigenetic age estimation in saliva and in buccal cells.

Age estimation based on epigenetic markers is a DNA intelligence tool with the potential to provide relevant information for criminal investigations, as well as to improve the inference of age-dependent physical characteristics such as male pattern baldness or hair color. Age prediction models have been developed based on different tissues, including saliva and buccal cells, which show different methylation patterns as they are composed of different cell populations. On many occasions in a criminal investigation, the origin of a sample or the proportion of tissues is not known with certainty, for example the provenance of cigarette butts, so use of combined models can provide lower prediction errors. In the present study, two tissue-specific and seven age-correlated CpG sites were selected from publicly available data from the Illumina HumanMethylation 450 BeadChip and bibliographic searches, to help build a tissue-dependent, and an age-prediction model, respectively. For the development of both models, a total of 184 samples (N = 91 saliva and N = 93 buccal cells) ranging from 21 to 86 years old were used. Validation of the models was performed using either k-fold cross-validation and an additional set of 184 samples (N = 93 saliva and N = 91 buccal cells, 21-86 years old). The tissue prediction model was developed using two CpG sites (HUNK and RUNX1) based on logistic regression that produced a correct classification rate for saliva and buccal swab samples of 88.59 % for the training set, and 83.69 % for the testing set. Despite these high success rates, a combined age prediction model was developed covering both saliva and buccal cells, using seven CpG sites (cg10501210, LHFPL4, ELOVL2, PDE4C, HOXC4, OTUD7A and EDARADD) based on multivariate quantile regression giving a median absolute error (MAE): ± 3.54 years and a correct classification rate ( %CP±PI) of 76.08 % for the training set, and an MAE of ± 3.66 years and a %CP±PI of 71.19 % for the testing set. The addition of tissue-of origin as a co-variate to the model was assessed, but no improvement was detected in age predictions. Finally, considering the limitations usually faced by forensic DNA analyses, the robustness of the model and the minimum recommended amount of input DNA for bisulfite conversion were evaluated, considering up to 10 ng of genomic DNA for reproducible results. The final multivariate quantile regression age predictor based on the models we developed has been placed in the open-access Snipper forensic classification website.

A common epigenetic clock from childhood to old age.

Forensic age estimation is a DNA intelligence tool that forms an important part of Forensic DNA Phenotyping. Criminal cases with no suspects or with unsuccessful matches in searches on DNA databases; human identification analyses in mass disasters; anthropological studies or legal disputes; all benefit from age estimation to gain investigative leads. Several age prediction models have been developed to date based on DNA methylation. Although different DNA methylation technologies as well as diverse statistical methods have been proposed, most of them are based on blood samples and mainly restricted to adult age ranges. In the current study, we present an extended age prediction model based on 895 evenly distributed Spanish DNA blood samples from 2 to 104 years old. DNA methylation levels were detected using Agena Bioscience EpiTYPER® technology for a total of seven CpG sites located at seven genomic regions: ELOVL2, ASPA, PDE4C, FHL2, CCDC102B, MIR29B2CHG and chr16:85395429 (GRCh38). The accuracy of the age prediction system was tested by comparing three statistical methods: quantile regression (QR), quantile regression neural network (QRNN) and quantile regression support vector machine (QRSVM). The most accurate predictions were obtained when using QRNN or QRSVM (mean absolute prediction error, MAE of ± 3.36 and ± 3.41, respectively). Validation of the models with an independent Spanish testing set (N = 152) provided similar accuracies for both methods (MAE: ± 3.32 and ± 3.45, respectively). The main advantage of using quantile regression statistical tools lies in obtaining age-dependent prediction intervals, fitting the error to the estimated age. An additional analysis of dimensionality reduction shows a direct correlation of increased error and a reduction of correct classifications as the training sample size is reduced. Results indicated that a minimum sample size of six samples per year-of-age covered by the training set is recommended to efficiently capture the most inter-individual variability..

Multifunctional cationic surfactants with a labile amide linker as efficient antifungal agents-mechanisms of action.

Our research aimed to expand the knowledge of relationships between the structure of multifunctional cationic dicephalic surfactants with a labile linker-N,N-bis[3,3-(dimethylamine)propyl]alkylamide dihydrochlorides and N,N-bis[3,3-(trimethylammonio)propyl]alkylamide dibromides (alkyl: n-C9H19, n-C11H23, n-C13H27, n-C15H31)-and their possible mechanism of action on fungal cells using the model organism Saccharomyces cerevisiae. General studies performed on surfactants suggest that in most cases, their main mechanism of action is based on perforation of the cell membranes and cell disruption. Experiments carried out in this work with cationic dicephalic surfactants seem to modify our understanding of this issue. It was found that the investigated compounds did not cause perforation of the cell membrane and could only interact with it, increasing its permeability. The surfactants tested can probably penetrate inside the cells, causing numerous morphological changes, and contribute to disorders in the lipid metabolism of the cell resulting in the formation of lipid droplet aggregates. This research also showed that the compounds cause severe oxidative stress within the cells studied, including increased production of superoxide anion radicals and mitochondrial oxidative stress. Dicephalic cationic surfactants due to their biodegradability do not accumulate in the environment and in the future may be used as effective antifungal compounds in industry as well as medicine, which will be environmentally friendly. KEY POINTS: • Dicephalic cationic surfactants do not induce disruption of the cell membrane. • Surfactants could infiltrate into the cells and cause accumulation of lipids. • Surfactants could cause acute oxidative stress in yeast cells. • Compounds present multimodal mechanism of action. Graphical abstract.

A Comparison of Forensic Age Prediction Models Using Data From Four DNA Methylation Technologies.

Individual age estimation can be applied to criminal, legal, and anthropological investigations. DNA methylation has been established as the biomarker of choice for age prediction, since it was observed that specific CpG positions in the genome show systematic changes during an individual's lifetime, with progressive increases or decreases in methylation levels. Subsequently, several forensic age prediction models have been reported, providing average age prediction error ranges of ±3-4 years, using a broad spectrum of technologies and underlying statistical analyses. DNA methylation assessment is not categorical but quantitative. Therefore, the detection platform used plays a pivotal role, since quantitative and semi-quantitative technologies could potentially result in differences in detected DNA methylation levels. In the present study, we analyzed as a shared sample pool, 84 blood-based DNA controls ranging from 18 to 99 years old using four different technologies: EpiTYPER®, pyrosequencing, MiSeq, and SNaPshotTM. The DNA methylation levels detected for CpG sites from ELOVL2, FHL2, and MIR29B2 with each system were compared. A restricted three CpG-site age prediction model was rebuilt for each system, as well as for a combination of technologies, based on previous training datasets, and age predictions were calculated accordingly for all the samples detected with the previous technologies. While the DNA methylation patterns and subsequent age predictions from EpiTYPER®, pyrosequencing, and MiSeq systems are largely comparable for the CpG sites studied, SNaPshotTM gives bigger differences reflected in higher predictive errors. However, these differences can be reduced by applying a z-score data transformation.

Inelastic scattering dynamics of naphthalene and 2-octanone on highly oriented pyrolytic graphite.

The inelastic scattering dynamics of the isobaric molecules, naphthalene (C10H8) and 2-octanone (C8H16O), on highly oriented pyrolytic graphite (HOPG) have been investigated as part of a broader effort to inform the inlet design of a mass spectrometer for the analysis of atmospheric gases during a flyby mission through the atmosphere of a planet or moon. Molecular beam-surface scattering experiments were conducted, and the scattered products were detected with the use of a rotatable mass spectrometer detector. Continuous, supersonic beams were prepared, with average incident translational energies, ⟨Ei⟩, of 247.3 kJ mol-1 and 538.2 kJ mol-1 for naphthalene and 268.6 kJ mol-1 and 433.8 kJ mol-1 for 2-octanone. These beams were directed toward an HOPG surface, held at 530 K, at incident angles, θi, of 30°, 45°, and 70°, and scattered products were detected as functions of their translational energies and scattering angles. The scattering dynamics of both molecules are very similar and mimic the scattering of atoms and small molecules on rough surfaces, where parallel momentum is not conserved, suggesting that the dynamics are dominated by a corrugated interaction potential between the incident molecule and the surface. The effective corrugation of the molecule-surface interaction is apparently caused by the structure of the incident molecule and the consequent myriad available energy transfer pathways between the molecule and the surface during a complex collision event. In addition, the HOPG surface contributes to the corrugation of the interaction potential because it can absorb significant energy from collisions with incident molecules that have high mass and incident energy. Small differences in the scattering dynamics of the two molecules are inferred to arise from the details of the molecule-surface interaction potential, with 2-octanone exhibiting dynamics that suggest a slightly stronger interaction with the surface than naphthalene. These results add to a growing body of work on the scattering dynamics of organic molecules on HOPG, from which insight into the hypervelocity sampling and analysis of such molecules may be obtained.

Tracking age-correlated DNA methylation markers in the young.

DNA methylation is the most extensively studied epigenetic signature, with a large number of studies reporting age-correlated CpG sites in overlapping genes. However, most of these studies lack sample coverage of individuals under 18 years old and therefore little is known about the progression of DNA methylation patterns in children and adolescents. In the present study we aimed to select candidate age-correlated DNA methylation markers based on public datasets from Illumina BeadChip arrays and previous publications, then to explore the resulting markers in 209 blood samples from donors aged between 2 to 18 years old using the EpiTYPER® DNA methylation analysis system. Results from our analyses identified six genes highly correlated with age in the young, in particular the gene KCNAB3, which indicates its potential as a highly informative and specific age biomarker for childhood and adolescence. We outline a preliminary age prediction model based on quantile regression that uses data from the six CpG sites most strongly correlated with age ranges extended to include children and adolescents.

Comparing student and staff perceptions of the "Educational Climate" in Spanish Dental Schools using the Dundee Ready Education Environment Measure.

OBJECTIVE: To compare the perceptions of students and teachers of the "Educational Climate" (EC) in Spanish public dental schools. METHODS: A group of 1064 students and 354 teachers from six Spanish public dental schools responded to the DREEM questionnaire. This has 50 items grouped into five subscales: perception of learning (Learning); perception of teachers (Teachers); academic self-perceptions (Academic); perception of the atmosphere in the faculty (Atmosphere); and social self-perceptions (Social). The DREEM scale provides results for each item, each subscale and the overall EC. RESULTS: The EC scores were 123.2 (61.6%) for the students and 134.1 (67.0%) for the teachers (P<.001). The scores of the students and teachers for the subscales were, respectively: 27.9 (58.1%) and 30.2 (63.0 %) for Learning (P<.001); 26.8 (60.9%) and 32.6 (74.1%) for Teachers (P<.001); 20.7 (64.7%) and 20.5 (64.0%) for Academic (P=.333); 29.9 (62.3%) and 33.7 (70.3%) for Atmosphere (P<.001); and 17.9 (64.0%) and 16.9 (60.5%) for Social (P<.001). The students identified six problematic items (12.0 %) compared to only two (4.0 %) highlighted by the teachers. CONCLUSION: The students and teachers considered the EC to be "more positive than negative" in Spanish public dental schools; and the different subscales to be "positive and acceptable." The teachers did, however, evaluate the EC, and specifically the learning-teaching process, more positively than their students, identifying fewer problematic educational aspects. Both groups agreed on the need to: improve support systems for students who suffer from stress and reduce teaching based on "factual learning."

Cytokine-based Predictive Models to Estimate the Probability of Chronic Periodontitis: Development of Diagnostic Nomograms.

Although a distinct cytokine profile has been described in the gingival crevicular fluid (GCF) of patients with chronic periodontitis, there is no evidence of GCF cytokine-based predictive models being used to diagnose the disease. Our objectives were: to obtain GCF cytokine-based predictive models; and develop nomograms derived from them. A sample of 150 participants was recruited: 75 periodontally healthy controls and 75 subjects affected by chronic periodontitis. Sixteen mediators were measured in GCF using the Luminex 100™ instrument: GMCSF, IFNgamma, IL1alpha, IL1beta, IL2, IL3, IL4, IL5, IL6, IL10, IL12p40, IL12p70, IL13, IL17A, IL17F and TNFalpha. Cytokine-based models were obtained using multivariate binary logistic regression. Models were selected for their ability to predict chronic periodontitis, considering the different role of the cytokines involved in the inflammatory process. The outstanding predictive accuracy of the resulting smoking-adjusted models showed that IL1alpha, IL1beta and IL17A in GCF are very good biomarkers for distinguishing patients with chronic periodontitis from periodontally healthy individuals. The predictive ability of these pro-inflammatory cytokines was increased by incorporating IFN gamma and IL10. The nomograms revealed the amount of periodontitis-associated imbalances between these cytokines with pro-inflammatory and anti-inflammatory effects in terms of a particular probability of having chronic periodontitis.

Elevated Levels of Procalcitonin and Interleukin-6 are Linked with Postoperative Complications in Cardiac Surgery.

BACKGROUND: Cardiac surgery-associated acute kidney injury is a frequent and serious postoperative complication of cardiac surgery and is associated with an increased risk of morbidity, mortality, and length stay. In this study, we hypothesized that persistent elevation in inflammation in the first 48 h might be a powerful predictor of clinical outcome. Our aim was to elucidate the usefulness of interleukin-6 and procalcitonin postoperative levels in predicting mortality and renal complications in cardiac surgery patients. METHODS: A total of 122 cardiac surgery patients were enrolled. Procalcitonin and interleukin-6 concentrations were measured on the second postoperative day, and their levels were evaluated versus a number of conditions and endpoints. RESULTS: Procalcitonin has a good predictive value for adverse renal outcome (p < 0.05). Interleukin-6 has a good predictive value for 30 days and overall mortality in cardiac surgery population (p < 0.05). We did not observe a significant difference in procalcitonin and interleukin-6 levels among patients with different types of surgery and different extracorporeal circulation time, but the levels of both the molecules increase significantly depending on number of transfusions received by patients (p < 0.01). CONCLUSION: We speculated that procalcitonin and interleukin-6 could be two effective biomarkers. There is a possibility of having a combined inflammatory multi-biomarker panel, with procalcitonin for predicting renal outcome and interleukin-6 for predicting mortality.

Incidence, recurrence and cost of hyperglycaemic crises requiring emergency treatment in Andalusia, Spain.

AIMS: Hyperglycaemic crises (diabetic ketoacidosis and hyperosmolar hyperglycaemic state) are medical emergencies in people with diabetes. We aimed to determine their incidence, recurrence and economic impact. METHODS: An observational study of hyperglycaemic crises cases using the database maintained by the out-of-hospital emergency service, the Healthcare Emergency Public Service (EPES) during 2012. The EPES provides emergency medical services to the total population of Andalusia, Spain (8.5 million inhabitants) and records data on the incidence, resource utilization and cost of out-of-hospital medical care. Direct costs were estimated using public prices for health services updated to 2012. RESULTS: Among 1 137 738 emergency calls requesting medical assistance, 3157 were diagnosed with hyperglycaemic crises by an emergency coordinator, representing 2.9 cases per 1000 persons with diabetes [95% confidence intervals (CI) 2.8 to 3.0]. The incidence of diabetic ketoacidosis was 2.5 cases per 1000 persons with diabetes (95% CI 2.4 to 2.6) and the incidence of hyperosmolar hyperglycaemic state was 0.4 cases per 1000 persons with diabetes (95% CI 0.4 to 0.5). In total, 17.7% (n = 440) of people had one or more hyperglycaemic crisis. The estimated total direct cost was €4 662 151, with a mean direct cost per episode of €1476.8 ± 217.8. CONCLUSIONS: Hyperglycaemic crises require high resource utilization of emergency medical services and have a significant economic impact on the health system.

Can we use the 6-minute step test instead of the 6-minute walking test? An observational study.

OBJECTIVE: To verify whether or not heart rate is maintained below the calculated submaximal level in healthy, sedentary subjects when they perform the 6-minute step test (6MST) and the 6-minute walking test (6MWT), and to compare the maximal heart rate achieved by the subjects at the end of each test. DESIGN: Observational, cross-sectional study. SETTING: One tertiary centre. PARTICIPANTS: Two hundred and fifty-three participants from a pool of 330 healthy and sedentary subjects between 20 and 80 years of age. INTERVENTIONS: Both the 6MWT and the 6MST were performed in accordance with the American Thoracic Society's statement. Dyspnoea, blood pressure, oxygen saturation and heart rate were measured before and after each test. RESULTS: Mean heart rate immediately after the 6MST was significantly higher than mean heart rate immediately after the 6MWT {125 [standard deviation (SD) 19] vs 111 (SD 17) beats/minute; mean difference 13 (95% confidence interval of the difference 10 to 16); P<0.001}. Moreover, mean heart rate during (3minutes after commencement) the 6MST [118 (SD 18) beats/minute] was statistically higher than mean heart rate at the end of the 6MWT [111 (SD 18) beats/minute; P<0.001]. None of the subjects achieved the calculated submaximal heart rate. CONCLUSIONS: The 6MST and 6MWT are safe and produce submaximal effort in healthy participants. However, they are not interchangeable, and the 6MST requires more energy than the 6MWT.

Development of a methylation marker set for forensic age estimation using analysis of public methylation data and the Agena Bioscience EpiTYPER system.

Individual age estimation has the potential to provide key information that could enhance and extend DNA intelligence tools. Following predictive tests for externally visible characteristics developed in recent years, prediction of age could guide police investigations and improve the assessment of age-related phenotype expression patterns such as hair colour changes and early onset of male pattern baldness. DNA methylation at CpG positions has emerged as the most promising DNA tests to ascertain the individual age of the donor of a biological contact trace. Although different methodologies are available to detect DNA methylation, EpiTYPER technology (Agena Bioscience, formerly Sequenom) provides useful characteristics that can be applied as a discovery tool in localized regions of the genome. In our study, a total of twenty-two candidate genomic regions, selected from the assessment of publically available data from the Illumina HumanMethylation 450 BeadChip, had a total of 177 CpG sites with informative methylation patterns that were subsequently investigated in detail. From the methylation analyses made, a novel age prediction model based on a multivariate quantile regression analysis was built using the seven highest age-correlated loci of ELOVL2, ASPA, PDE4C, FHL2, CCDC102B, C1orf132 and chr16:85395429. The detected methylation levels in these loci provide a median absolute age prediction error of ±3.07years and a percentage of prediction error relative to the age of 6.3%. We report the predictive performance of the developed model using cross validation of a carefully age-graded training set of 725 European individuals and a test set of 52 monozygotic twin pairs. The multivariate quantile regression age predictor, using the CpG sites selected in this study, has been placed in the open-access Snipper forensic classification website.

Incidence and care-related costs of severe hypoglycaemia requiring emergency treatment in Andalusia (Spain): the PAUEPAD project.

AIMS: Hypoglycaemia is a serious medical emergency. The need for emergency medical service care and the costs of hypoglycaemic emergencies are not completely known. METHODS: This was a retrospective observational study using Public Company for Health Emergencies (EPES) data for hypoglycaemia in 2012. The EPES provides emergency medical services to the entire population of Andalusia, Spain (8.5 million people). Data on event type, onsite treatments, emergency room visits or hospitalization were collected. Medical costs were estimated using the public rates for healthcare services. RESULTS: From a total of 1 137 738 emergency calls that requested medical assistance, 8683 had a primary diagnosis of hypoglycaemia (10.34 per 10 000 person-years). The incidence of severe hypoglycaemic episodes requiring emergency treatment in the estimated population with diabetes was 80 episodes per 10 000 person-years. A total of 7479 episodes (86%) required an emergency team to visit the patient's residence. The majority of cases (64%) were addressed in the residence, although 1784 (21%) cases were transferred to hospital. A total of 5564 events (65%) involved patients aged > 65 years. Overall mortality was 0.32% (28 cases). The total annual cost of attending a hypoglycaemic episode was €6 093 507, leading to an estimated mean direct cost per episode of €702 ± 565. Episodes that required hospital treatment accounted for 49% of the total costs. CONCLUSIONS: Hypoglycaemia is a common medical emergency that is associated with high emergency medical service utilization, resulting in a significant economic impact on the health system.

Concurrent interspecies and clonal dissemination of OXA-48 carbapenemase.

Several isolates of four different carbapenemase-producing Enterobacteriaceae species were recovered from a patient hospitalized for 4 months in a teaching hospital in Madrid. These species comprised seven Klebsiella pneumoniae belonging to ST15, four Escherichia coli belonging to ST2531, two Serratia marcescens and one Citrobacter freundii. This patient was the index case of a small outbreak of four patients infected and/or colonized by carbapenemase-producing K. pneumoniae. Molecular results identified the bla(OXA-48) gene in all Enterobacteriaceae isolates from the index case and in all isolates from the other three patients, suggesting intra- and interpatient dissemination. Our results highlight the great ability of OXA-48 carbapenemase to spread among different enterobacterial species by both clonal and nonclonal dissemination.

Exploring iris colour prediction and ancestry inference in admixed populations of South America.

New DNA-based predictive tests for physical characteristics and inference of ancestry are highly informative tools that are being increasingly used in forensic genetic analysis. Two eye colour prediction models: a Bayesian classifier - Snipper and a multinomial logistic regression (MLR) system for the Irisplex assay, have been described for the analysis of unadmixed European populations. Since multiple SNPs in combination contribute in varying degrees to eye colour predictability in Europeans, it is likely that these predictive tests will perform in different ways amongst admixed populations that have European co-ancestry, compared to unadmixed Europeans. In this study we examined 99 individuals from two admixed South American populations comparing eye colour versus ancestry in order to reveal a direct correlation of light eye colour phenotypes with European co-ancestry in admixed individuals. Additionally, eye colour prediction following six prediction models, using varying numbers of SNPs and based on Snipper and MLR, were applied to the study populations. Furthermore, patterns of eye colour prediction have been inferred for a set of publicly available admixed and globally distributed populations from the HGDP-CEPH panel and 1000 Genomes databases with a special emphasis on admixed American populations similar to those of the study samples.