Oral quinolones versus intravenous ß-lactam for the treatment of acute focal bacterial nephritis: a retrospective cohort study.

BACKGROUND: Evidence regarding the best antibiotic regimen and the route of administration to treat acute focal bacterial nephritis (AFBN) is scarce. The aim of the present study was to compare the effectiveness of intravenous (IV) ß-lactam antibiotics versus oral quinolones. METHODS: This is a retrospective single centre study of patients diagnosed with AFBN between January 2017 and December 2018 in Hospital Universitari Vall d'Hebron, Barcelona (Spain). Patients were identified from the diagnostic codifications database. Patients treated with oral quinolones were compared with those treated with IV ß-lactam antibiotics. Therapeutic failure was defined as death, relapse, or evolution to abscess within the first 30 days. RESULTS: A total of 264 patients fulfilled the inclusion criteria. Of those, 103 patients (39%) received oral ciprofloxacin, and 70 (26.5%) IV ß-lactam. The most common isolated microorganism was Escherichia coli (149, 73.8%) followed by Klebsiella pneumoniae (26, 12.9%). Mean duration of treatment was 21.3 days (SD 7.9). There were no statistical differences regarding therapeutic failure between oral quinolones and IV ß-lactam treatment (6.6% vs. 8.7%, p = 0.6). Out of the 66 patients treated with intravenous antibiotics, 4 (6.1%) experienced an episode of phlebitis and 1 patient (1.5%) an episode of catheter-related bacteraemia. CONCLUSIONS: When susceptible, treatment of AFBN with oral quinolones is as effective as IV ß-lactam treatment with fewer adverse events.

Exploring the independent association of employment status to cancer survivors' health-related quality of life.

BACKGROUND: Having a job has been associated with better Health-Related Quality of Life (HRQOL) in cancer survivors. However, the sociodemographic and disease-related profiles characterizing the survivors being employed and those having better HRQOL largely overlap. The present study aims to discern the degree to which employment status is independently associated with cancer survivors' HRQOL or if it mainly reflects the impact of other sociodemographic and cancer-related variables. METHODS: Cross-sectional study on a heterogeneous sample of 772 working-age survivors of adult-onset cancer. An instrument specifically designed to assess HRQOL in cancer survivors and Multivariate Variance Analysis (MANOVA) were used. RESULTS: Survival phase, cancer type, and employment status showed the main effects on cancer survivors' HRQOL. In particular, being employed (vs unemployed) had the greatest positive association with HRQOL, affecting ten of the twelve HRQOL domains considered. Also, interaction effects highlighted the role of age (younger) and marital status (single) as risk factors for a greater negative impact of variables affecting the survivor's HRQOL. CONCLUSIONS: The application of a multivariate methodology sheds new light on two relevant issues for the cancer survivor's HRQOL: (i) the existence of differences between diagnostic groups that are not attributed to other variables such as sex, and (ii) the important and independent role that employment status plays. Comprehensive cancer survivorship care should focus more on high-risk groups and include having a job as an essential aspect to consider and prompt. The fact that the employment status is susceptible to change represents a valuable opportunity to care for the wellbeing of this population.

Positive prostate biopsy following radiotherapy can predict metastasis-free survival in localized prostate cancer.

BACKGROUND/AIMS: To determine the impact of post-treatment biopsy results on 10-year metastasis-free survival (MFS), overall survival (OS) and cause-specific survival (CSS) in localized prostate cancer (PCa) patients treated with high-dose radiotherapy (RT). MATERIALS/METHODS: Retrospective analysis of 232 patients with T1c-T3bN0M0 PCa who underwent a prostate biopsy 24-36 months after high-dose RT. Biopsies were categorized as positive biopsy (PB) if H&E staining showed evidence of residual malignancy and negative biopsy (NB) if no malignant cells were present. Kaplan-Meier estimates of 10-year MFS, OS and CSS rates were calculated for each group and Cox proportional-hazards models were used to estimate the hazard ratios. The median follow-up was 124 months (range 26-267). RESULTS: Sixty-two of 232 (26.7%) patients had post-treatment positive biopsies (PB). A positive post-treatment biopsy was significantly associated with a lower 10-year MFS (78.4% vs. 95.4%, p = 0.001, HR: 3.9, 95% CI: 1.8-8.3). Although patients with PB had worse outcomes that those with NB, we could not show a statistically significant difference in OS (81.0% vs. 87.9%, p = 0.282, HR: 1.3, 95% CI: 0.7-2.3) or CSS (96.2% vs. 99.4% (p = 0.201, HR. 2.4, 95% CI: 0.6-9.7). After multivariate analysis, the strongest predictor of MFS was the post-treatment biopsy status (p < 0.001, HR: 5.4, 95% CI 2.26-12.85) followed by Gleason score (p = 0.002, HR: 2.24, 95% CI 1.33-3.79). CONCLUSION: A positive biopsy following RT can predict MFS in localized prostate cancer. These data highlight the relevance of achieving a local control and support the use of aggressive local therapeutic interventions for PCa.

ITEMAS ontology for healthcare technology innovation.

BACKGROUND: The Platform for Innovation in Medical and Health Technologies (ITEMAS) is a network of 66 healthcare centres focused on fostering innovation in medical and health technologies as an essential tool for increasing the sustainability of the Spanish healthcare system. The present research is focused on defining a formal representation that details the most relevant concepts associated with the creation and adoption of innovative medical technology in the Spanish healthcare system. METHODS: The methodology applied is based on the methontology process, including peer-review identification and selection of concepts from the ITEMAS innovation indicators and innovation management system standards. This stage was followed by an iterative validation process. Concepts were then conceptualised, formalised and implemented in an ontology. RESULTS: The ontology defined describes how relationships between employees, organisations, projects and ideas can be applied to generate results that are transferrable to the market, general public and scientific forums. Overall, we identified 136 concepts, 138 object properties and 30 properties in a five-level hierarchy. The ontology was tested and validated as an appropriate framework for calculating the ITEMAS innovation indicators. CONCLUSIONS: The consensus concepts were expressed in the form of an ontology to be used as a single communication format between the members of the ITEMAS network. Healthcare centres can compare their innovation results and obtain a better understanding of their innovation context based on the reasoning techniques of artificial intelligence. As a result, they can benefit from advanced analytical capabilities to define the most appropriate innovation policies for each centre based on the common experience of the large number of healthcare centres involved. The results can be used to create a map of agents and knowledge to show capabilities, projects and services provided by each of the participating centres. The ontology could also be applied as an instrument to match needs with existing projects and capabilities from the community of organisations working in healthcare technology innovation.

Two different critical regimes enclosed in the Bean-Rodbell model and their implications for the field dependence and universal scaling of the magnetocaloric effect.

In the last few years power laws and universal scaling have been extensively used to study the field dependence of the magnitudes involved in the magnetocaloric effect of materials. They are key tools which allow us to compare the performing properties of different materials regardless of their nature, processing or experimental conditions during measurements. It was proved that power laws and universal scaling are a direct consequence of critical phenomena in the neighborhood of phase transitions. However, there remains some controversy about the reliability of these procedures. In this work we use the well-known Bean-Rodbell model to confirm that these features are unmistakably related to the critical behavior of the continuous phase transitions. In this specific model, universal scaling occurs either at a purely mean field second order transition or at a tricritical point. Finally, we analyze in detail if the universal scaling is compatible with materials at the tricitical point, making a comprehensive comparison with available experimental data from the literature. We conclude that it is really difficult to know with full certainty if a sample really is in the tricritical regime.

Effect of sonic and ultrasonic activation on organic tissue dissolution from simulated grooves in root canals using sodium hypochlorite and EDTA.

AIM: To compare soft-tissue dissolution by sodium hypochlorite, with an EDTA intermediate rinse, with or without activation with passive ultrasonic activation (PUI) or sonic activation using the Endoactivator (EA) or Eddy tips (ED). METHODOLOGY: The root canals of eighty-three human maxillary central incisors were chemo-mechanically prepared and the teeth split. A standardized longitudinal intracanal groove was created in one of the root halves. Eighty-three porcine palatal mucosa samples were collected, adapted to fit into the grooves and weighed. The re-assembled specimens were randomly divided into four experimental groups (n = 20), based on the final rinse: no activation; EA; PUI; ED, using 2.5% sodium hypochlorite, with an EDTA intermediate rinse. A control group (n = 3) was irrigated with distilled water without activation. The solutions were delivered using a syringe and needle 2 mm from working length. Total irrigation time was 150 s, including 60 s of activation in the specific groups. The study was carried out at 36 ± 2 °C. The porcine palatal mucosa samples were weighed after completion of the assays. Student paired t-test and anova were used to assess the intra- and intergroup weight changes. The multiple comparisons were evaluated using Bonferroni correction (α = 0.05). RESULTS: Weight loss occurred in all experimental groups. Irrigant activation resulted in greater weight loss when compared to the nonactivated group [vs. EA (P = 0.001); vs. PUI (P < 0.001); vs. ED (P < 0.001)]. No significant differences were found amongst the different activation systems. CONCLUSIONS: Activation increased the tissue-dissolving activity of irrigants from artificial grooves in root canals of maxillary central incisors.

Prognostic value of glomerular filtration rate estimation equations in acute heart failure with preserved versus reduced ejection fraction.

AIMS: Renal function is an important prognostic factor in heart failure. The aim of this study was to compare the predictive value of estimated renal function calculated by the Chronic Kidney Disease-Epidemiology Collaboration equation (CKD-EPI) and the abbreviated Modification of Diet in Renal Disease (MDRD-4) equation for long-term all-cause mortality in patients admitted for acute decompensated heart failure (ADHF) with both preserved ejection fraction (HF-PEF) and reduced ejection fraction (HF-REF). METHODS AND RESULTS: We evaluated patients included in the Spanish National Registry of Heart Failure (RICA). RICA is a multicentre, prospective, cohort study that included patients admitted to the Internal Medicine units with ADHF. Estimated glomerular filtration rate (eGFR) was calculated with CKD-EPI and MDRD-4 equations. A total of 1805 patients admitted for ADHF were studied (52% women; median age 80 years, interquartile range 73.9-84.6 years); of these, 1044 (58%) had HF-PEF. eGFR values were lower with the CKD-EPI formula than with the MDRD-4 formula (51 ml/min/1.73 m(2) vs. 55.7 ml/min/1.73 m(2) ; p < 0.001). The two formulas provided independent prognostic information over long-term follow-up, in both HF-PEF and HF-REF patients. However, in HF-PEF patients, CKD-EPI equation was associated with a significant improvement in reclassification analyses (net reclassification improvement 6.78%; p = 0.009). CONCLUSIONS: In this clinical cohort of ADHF patients, eGFR as calculated by both the CKD-EPI and the MDRD-4 formulas offered similar prognostic information, irrespective of ejection fraction status, but in HF-PEF patients specifically, the CKD-EPI formula seems to improve clinical risk stratification as compared with MDRD-4.

[Adherence to recommendations to reduce the risk of Sudden infant Death Syndrome]. / Evaluación de la adherencia a las recomendaciones para disminuir el riesgo de Síndrome de Muerte Súbita del lactante.

INTRODUCTION: Recommendations for Sudden Infant Death Syndrome (SIDS) are available, although it is uncertain the degree of adherence to these measures. The aim of the study is to assess the adherence to recommendations to reduce the risk of SIDS, seeking factors associated to the noncompliance with these recommendations. PATIENTS AND METHOD: 468 infants were enrolled in two maternity hospitals, one public and one private. Postpartum and 4-month assessments were performed. A questionnaire was used adapting a model validated by the International Child Care Practices Study. RESULTS: Adherence to obstetric recommendations was higher (75.4%) than to pediatric recommendations (53.3%). Regarding pediatric recommendations, a compliance decrease was detected after 4 months. Follow-ups showed decrease in breastfeeding (p < 0.001 84.9% vs 48.6%) and supine position (61.2% vs 21.2%, p < 0.001). CONCLUSIONS: The decreased adherence to recommendations for SIDS prevention was mainly observed in younger and less educated women, who were not in a relationship and living in poor housing quality and crowded environments.

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.

Performance comparison of a previously validated microhaplotype panel and a forensic STR panel for DNA mixture analysis.

Short Tandem Repeats (STRs) are the most widespread markers in forensic genetics. However, STR stutter peaks can mask alleles from a minor contributor when analysing mixtures, hindering the interpretation of complex profiles. In this study we compared the performance of a previously described panel of microhaplotypes (MHs), an alternative type of forensic marker, against a standard STR kit. The parameters evaluated included: capability of determining the minimum number of contributors in the mixture; percentages of allele drop-outs and drop-ins; retrieval of alleles belonging to the minor contributor, and estimation of likelihood ratio (LR) values. In addition, the capacity of EuroForMix software to estimate each donor's percentage of contribution was tested, as well as the impact on results when using manually, or automatically prepared libraries. The MH panel showed better performance than STRs for the detection of 2-contributor mixtures, but the lower degree of polymorphism per MH marker hindered the task of deconvolution with multiple contributors. MHs presented higher drop-in rates and lower drop-out rates, a higher capability to recover the minor contributor's alleles and provided higher LR values than STRs, likely due to the much higher number of loci combined in the panel. Estimations of contributor ratios using EuroForMix showed promising results and marginal differences were found in these values between manually and automatically prepared libraries. Overall, results showed that the mixture detection performance of the MH panel was better or equal to the standard forensic autosomal STR panel, indicating microhaplotypes are informative markers for this purpose.

Exploring legal age estimation using DNA methylation.

Minors (subjects under the legal age, established at this study at 18 years) benefit from a series of legal rights created to protect them and guarantee their welfare. However, throughout the world there are many minors who have no way to prove they are underaged, leading to a great interest in predicting legal age with the highest possible accuracy. Current methods, mainly involving X-ray analysis, are highly invasive, so new methods to predict legal age are being studied, such as DNA methylation. To further such studies, we created two age prediction models based on five epigenetic markers: cg21572722 (ELOVL2), cg02228185 (ASPA), cg06639320 (FHL2), cg19283806 (CCDC102B) and cg07082267 (no associated gene), that were analysed in blood samples to determine possible limitations regarding DNA methylation as an effective tool for legal age estimation. A wide age range prediction model was created using a broad set of samples (14-94 years) yielding a mean absolute error (MAE) of ±4.32 years. A second model, the constrained age prediction model, was created using a reduced range of samples (14-25 years) yielding an MAE of ±1.54 years. Both models, in addition to Horvath's Skin & Blood epigenetic clock, were evaluated using a test set comprising 732 pairs of 18-year-old twins (N=426 monozygotic (MZ) and N=306 dizygotic (DZ) pairs), representing a relevant age of study. Through analysis of the two former age prediction models, we found that constraining the age of the samples forming the training set around the desired age of study significantly reduced the prediction error (from MAE: ±4.07 and ±4.27 years for MZ and DZ twins, respectively; to ±1.31 and ±1.3 years). However, despite low prediction errors, DNA methylation models are still prone to classify same-aged individuals in different categories (minors or adults), despite each sample belonging to the same twin pair. Additional evaluation of Horvath's Skin & Blood model (391 CpGs) led to similar results in terms of age prediction errors than if using only five epigenetic markers (MAE: ±1.87 and ±1.99 years for MZ and DZ twins, respectively).

A case-control study suggests that the CCR6 locus is not involved in the susceptibility to giant cell arteritis.

OBJECTIVES: Polymorphisms of the CC chemokine receptor 6 (CCR6) gene have been recently reported to be associated with a number of autoimmune diseases. We aimed to investigate the possible influence of CCR6 rs3093024 gene variant in the susceptibility to and clinical expression of GCA. METHODS: The CCR6 polymorphism rs3093024 was genotyped in a total of 463 Spanish patients diagnosed with biopsy-proven GCA and 920 healthy controls using a TaqMan® allelic discrimination assay. PLINK software was used for the statistical analyses. RESULTS: No significant association between this CCR6 variant and GCA was observed (p=0.42, OR=0.94, CI95% 0.79-1.10). Similarly, when patients were stratified according to the specific clinical features of GCA such as polymyalgia rheumatica, visual ischaemic manifestations or irreversible occlusive disease, no statistical significant difference was detected either between the case subgroups and the control set or between GCA patients with and without the specific features of the disease. CONCLUSIONS: Our results suggest that the CCR6 rs3093024 polymorphism may not play a relevant role in the GCA pathophysiology.

Ultrafast dynamics of the ns (n = 3,4) and 3d Rydberg states of O2.

The ultrafast dynamics of the lowest optically accessible Rydberg states of molecular oxygen (O2) has been studied by time resolved transient ionization. The process was triggered by the absorption of two pump photons in the 304 nm-220 nm range which corresponds to an energy range of 8.2 eV-11.3 eV, and probed by ionization with photons at 800 nm. From the analysis of the experimental data different time constants ranging from a few femtoseconds to hundreds of picoseconds were found. The identification of the states responsible for the measured lifetimes revealed important facts about the dynamics of the Rydberg states in this energy range, underlying the importance of the coupling between Rydberg and valence states in the relaxation mechanisms of the molecule.

Adapting an established Ampliseq microhaplotype panel to nanopore sequencing through direct PCR.

We have adapted an established Ampliseq microhaplotype panel for nanopore sequencing with the Oxford Nanopore Technologies (ONT) system, as a cost-effective and highly scalable solution for forensic genetics applications. For this purpose, we designed a protocol combining direct PCR amplification from unextracted DNA with ONT library construction and sequencing using the MinION device and workflow. The analysis of reference samples at input amounts of 5-10 ng of DNA demonstrates stable coverage patterns, allele balance, and strand bias, reaching profile completeness and concordance rates of ∼95%. Similar levels were achieved when using direct-PCR from blood, buccal and semen swabs. Dilution series results indicate sensitivity is maintained down to 250 pg of input DNA, and informative profiles are produced down to 62.5 pg. Finally, we demonstrated the forensic utility of the nanopore workflow by analyzing two third degree pedigrees that showed low likelihood ratio values after the analysis of an extended panel of 38 STRs, achieving likelihood ratios 2-3 orders of magnitude higher when testing with the MinION-based haplotype data.

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.

Development and evaluations of the ancestry informative markers of the VISAGE Enhanced Tool for Appearance and Ancestry.

The VISAGE Enhanced Tool for Appearance and Ancestry (ET) has been designed to combine markers for the prediction of bio-geographical ancestry plus a range of externally visible characteristics into a single massively parallel sequencing (MPS) assay. We describe the development of the ancestry panel markers used in ET, and the enhanced analyses they provide compared to previous MPS-based forensic ancestry assays. As well as established autosomal single nucleotide polymorphisms (SNPs) that differentiate sub-Saharan African, European, East Asian, South Asian, Native American, and Oceanian populations, ET includes autosomal SNPs able to efficiently differentiate populations from Middle East regions. The ability of the ET autosomal ancestry SNPs to distinguish Middle East populations from other continentally defined population groups is such that characteristic patterns for this region can be discerned in genetic cluster analysis using STRUCTURE. Joint cluster membership estimates showing individual co-ancestry that signals North African or East African origins were detected, or cluster patterns were seen that indicate origins from central and Eastern regions of the Middle East. In addition to an augmented panel of autosomal SNPs, ET includes panels of 85 Y-SNPs, 16 X-SNPs and 21 autosomal Microhaplotypes. The Y- and X-SNPs provide a distinct method for obtaining extra detail about co-ancestry patterns identified in males with admixed backgrounds. This study used the 1000 Genomes admixed African and admixed American sample sets to fully explore these enhancements to the analysis of individual co-ancestry. Samples from urban and rural Brazil with contrasting distributions of African, European, and Native American co-ancestry were also studied to gauge the efficiency of combining Y- and X-SNP data for this purpose. The small panel of Microhaplotypes incorporated in ET were selected because they showed the highest levels of haplotype diversity amongst the seven population groups we sought to differentiate. Microhaplotype data was not formally combined with single-site SNP genotypes to analyse ancestry. However, the haplotype sequence reads obtained with ET from these loci creates an effective system for de-convoluting two-contributor mixed DNA. We made simple mixture experiments to demonstrate that when the contributors have different ancestries and the mixture ratios are imbalanced (i.e., not 1:1 mixtures) the ET Microhaplotype panel is an informative system to infer ancestry when this differs between the contributors.

Magnetic multilayers as a way to increase the magnetic field responsiveness of magnetocaloric materials.

The magnetocaloric response of Ni-Cu based multilayers has been studied with the aim of optimizing their magnetic field dependence. In contrast to the behavior of single phase materials, whose peak magnetic entropy change follows a power law with exponents close to 0.75, multilayering leads to exponents of -1 for an extended temperature span close to the transition temperature. This demonstrates that nanostructuring can be a good strategy to enhance the magnetic field responsiveness of magnetocaloric materials.

Desorption and ablation regimes in UV-MALDI: the critical fluence.

Although MALDI is a widely used technique, there is so far no theoretical description able to reproduce some critical aspects of the experimental results. For example, there is experimental as well as theoretical controversy regarding the minimum laser fluence, i.e., the so-called fluence threshold (F T), required to evaporate a sample. Furthermore, although the different processes involved in ion production have been the focus of many investigations, the fact is that the primary process for ion formation in MALDI is not desorption but ablation. In this work, we present a new phenomenological approach for understanding MALDI results based on a simple, but physically intuitive, idea consisting of limiting the laser-matter interaction process to three layers. This description allows us to consider the different processes that dominate ion formation, i.e., heat dissipation, as well as the different existing regimes. Concretely, we present the results for three different matrices, i.e., DHB, ferulic acid (FA) and α-cyano-4-hydroxycinnamic acid (CHCA), in the limit of low fluence. The simulations we carried out show great qualitative and pseudo-quantitative agreement with the experimental results. Also, based on the simulation results, it is possible to distinguish clearly between the two dominant regimes, i.e., desorption and ablation, and it is possible, therefore, to estimate the critical fluence (F C) that defines the transition from one regime to another.

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..