Multi-adductomics: Advancing mass spectrometry techniques for comprehensive exposome characterization.

Adductomics, an emerging field within the 'omics sciences, focuses on the formation and prevalence of DNA, RNA, and protein adducts induced by endogenous and exogenous agents in biological systems. These modifications often result from exposure to environmental pollutants, dietary components, and xenobiotics, impacting cellular functions and potentially leading to diseases such as cancer. This review highlights advances in mass spectrometry (MS) that enhance the detection of these critical modifications and discusses current and emerging trends in adductomics, including developments in MS instrument use, screening techniques, and the study of various biomolecular modifications from mono-adducts to complex hybrid crosslinks between different types of biomolecules. The review also considers challenges, including the need for specialized MS spectra databases and multi-omics integration, while emphasizing techniques to distinguish between exogenous and endogenous modifications. The future of adductomics possesses significant potential for enhancing our understanding of health in relation to environmental exposures and precision medicine.

Longitudinal Exposomics in a Multiomic Wellness Cohort Reveals Distinctive and Dynamic Environmental Chemical Mixtures in Blood.

Chemical exposomes can now be comprehensively measured in human blood, but knowledge of their variability and longitudinal stability is required for robust application in cohort studies. Here, we applied high-resolution chemical exposomics to plasma of 46 adults, each sampled 6 times over 2 years in a multiomic cohort, resulting in 276 individual exposomes. In addition to quantitative analysis of 83 priority target analytes, we discovered and semiquantified substances that have rarely or never been reported in humans, including personal care products, pesticide transformation products, and polymer additives. Hierarchical cluster analysis for 519 confidently annotated substances revealed unique and distinctive coexposures, including clustered pesticides, poly(ethylene glycols), chlorinated phenols, or natural substances from tea and coffee; interactive heatmaps were publicly deposited to support open exploration of the complex (meta)data. Intraclass correlation coefficients (ICC) for all annotated substances demonstrated the relatively low stability of the exposome compared to that of proteome, microbiome, and endogenous small molecules. Implications are that the chemical exposome must be measured more frequently than other omics in longitudinal studies and four longitudinal exposure types are defined that can be considered in study design. In this small cohort, mixed-effect models nevertheless revealed significant associations between testosterone and perfluoroalkyl substances, demonstrating great potential for longitudinal exposomics in precision health research.

Short-term risk of fracture is increased by deficits in cortical and trabecular bone microarchitecture independent of DXA BMD and FRAX: bone microarchitecture international consortium (BoMIC) prospective cohorts.

Identifying individuals at risk for short-term fracture is essential to offer prompt beneficial treatment, especially since many fractures occur in those without osteoporosis by DXA-aBMD. We evaluated whether deficits in bone microarchitecture and density predict short-term fracture risk independent of the clinical predictors, DXA-BMD and FRAX. We combined data from eight cohorts to conduct a prospective study of bone microarchitecture at the distal radius and tibia (by HR-pQCT) and 2-year incidence of fracture (non-traumatic and traumatic) in 7327 individuals (4824 women, 2503 men, mean 69 ± 9 years). We estimated sex-specific hazard ratios (HR) for associations between bone measures and 2-year fracture incidence, adjusted for age, cohort, height and weight, and then additionally adjusted for femoral neck (FN) aBMD or FRAX for major osteoporotic fracture. Only 7% of study participants had FN T-score ≤ -2.5, whereas 53% had T-scores between -1.0 to -2.5 and 37% had T-scores ≥-1.0. Two-year cumulative fracture incidence was 4% (296/7327). Each SD decrease in radius cortical bone measures increased fracture risk by 38%-76% for women and men. After additional adjustment for FN-aBMD, risks remained increased by 28%-61%. Radius trabecular measures were also associated with 2-year fracture risk independently of FN-aBMD in women (HRs range: 1.21 per SD for trabecular separation to 1.55 for total vBMD). Decreased failure load was associated with increased fracture risk in both women and men (FN-aBMD ranges of adjusted HR = 1.47-2.42). Tibia measurement results were similar to radius results. Findings were also similar when models were adjusted for FRAX. In older adults, failure load and HR-pQCT measures of cortical and trabecular bone microarchitecture and density with strong associations to short-term fractures improved fracture prediction beyond aBMD and FRAX. Thus, HR-pQCT may be a useful adjunct to traditional assessment of short-term fracture risk in older adults, including those with T-scores above the osteoporosis range.

Identifying individuals at risk for short-term fracture (within 2-years) is essential to offer prompt treatment. We examined bone microarchitecture at arm and lower leg for prediction of short-term fractures in 7327 older adults, independent of the common clinical practice measures ­ DXA-BMD and FRAX. After adjusting for other factors, we found that measures of failure load, cortical and trabecular bone microarchitecture and density predicted short-term risk of fracture beyond the usual clinical measures of DXA and FRAX. These measures of bone that indicate deficits in microarchitecture may be a useful adjunct to traditional assessment of fracture risk in older adults.

Microarchitectural analysis of the metacarpophalangeal joint using HR-pQCT in patients with rheumatoid arthritis: A comparison with healthy controls.

OBJECTIVE: To investigate which joint microarchitectural parameters measured by high-resolution peripheral quantitative computed tomography (HR-pQCT) serve as imaging markers for rheumatoid arthritis (RA). METHODS: The second and third metacarpophalangeal (MCP) joints of 50 patients with RA and 50 healthy controls (HCs) (aged 50-79 years, all females) were scanned using a HR-pQCT. Joint space, trabecular bone microarchitecture, and erosion were measured and compared between RA patients and HCs. RESULTS: There were no differences in joint space parameters between RA patients and HCs. For bone microarchitecture, RA patients had lower trabecular bone mineral density (127 vs. 167 mg/cm3), thinner trabecular thickness (0.20 vs. 0.21 mm), fewer trabecular number (1.49 vs. 1.55 /mm), more rod-like structure (1.68 vs. 1.23), and poorer trabecular connectivity (4.51 vs. 5.72 /mm3) than HCs. Regarding erosion, RA patients had a higher number of erosions per joint (36/100 vs. 18/100), larger volume (4.62 vs. 1.89 mm3), and longer width (2.40 vs. 1.82 mm) and longer length (2.34 vs. 1.64 mm) than HCs. Most of the erosions in HCs were <5 mm3 in volume (95 %) and located on the radial side (85 %). When erosions <5 mm3 were compared between RA patients and HCs, there were no differences in their location or morphology. CONCLUSIONS: Deterioration of bone microarchitecture and existences of erosions >5 mm3 in the MCP joints are sensitive imaging markers of RA. Erosions <5 mm3 in RA patients may include not only early pathological erosion but also physiological erosion because even HCs can have erosions <5 mm3.

Combining High-Resolution Mass Spectrometry and Chemiluminescence Analysis to Characterize the Composition and Fate of Total N-Nitrosamines in Wastewater Treatment Plants.

Monitoring the prevalence and persistence of N-nitrosamines and their precursors in wastewater treatment plants (WWTPs) and effluent-receiving aquatic compartments is a priority for utilities practicing wastewater recycling or exploiting wastewater-impacted source waters. In this work, we developed an analytical framework that combines liquid chromatography-high-resolution mass spectrometry (LC-HRMS) with acidic triiodide-chemiluminescence analysis to characterize the composition and fate of total N-nitrosamines (TONO) and their precursors along the treatment trains of eight WWTPs in New York. Through the parallel application of LC-HRMS and chemiluminescence methods, the TONO scores for 41 N-nitrosamines containing structurally diverse substituents on their amine nitrogen were derived based on their solid-phase extraction recoveries and conversion efficiencies to nitric oxide. Correcting the compositional analysis of TONO using the TONO scores of target N-nitrosamines refined the assessment of the reduction or accumulation of TONO and their precursors across treatment steps in WWTPs. Nontargeted analysis prioritized seven additional N-nitrosamines for confirmation by reference standards, including three previously uncharacterized species: N-nitroso-tert-butylphenylamine, N-nitroso-2-pyrrolidinmethanol, and N-nitrosodesloratadine, although they only served as minor components of TONO. Overall, our study establishes an adaptable methodological framework for advancing the quantitative and qualitative analysis of specific and unknown components of TONO across water treatment and reuse scenarios.

Identification and quantitative analysis of genotoxic impurities in rifampicin: Development and validation of a targeted LC-MS/MS method for 1-amino-4-methylpiperazine.

Rifampicin, essential for long-term tuberculosis treatment, requires rigorous control of non-therapeutic impurities due to their potential adverse, including mutagenic effects. Reports on control strategies for genotoxic impurities in rifampicin have been limited. This study introduced an analytical method to identify potential genotoxic impurities from the synthesis of raw materials. The structure of the 25-deacetyl-23-acetyl-rifampicin genotoxic impurity was confirmed using nuclear magnetic resonance, high-resolution mass spectrometry (HRMS), and high-performance liquid chromatography (HPLC). An HPLC-HRMS method was established and validated for detecting another genotoxic impurity, 1-amino-4-methylpiperazine, adhering to the International Council on Harmonization guidelines, which include specificity, linearity, detection and quantification limits, accuracy, precision, and robustness. These developments improve the quality control strategy for genotoxic impurities in rifampicin, ensuring product safety.

In-silico exploration of Attukal Kizhangu L. compounds: Promising candidates for periodontitis treatment.

A medicinal pteridophyte known as Attukal Kizhangu L. has been used to cure patients for centuries by administering plant parts based on conventional and common practices. Regarding its biological functions, significant use and advancement have been made. Extract of Attukal Kizhangu L. is the subject of the current study, which uses network pharmacology as its foundation. Three targeted compounds such as α-Lapachone, Dihydrochalcone, and Piperine were chosen for additional research from the 17 Phytoconstituents that were filtered out by the Coupled UPLC-HRMS study since they followed to Lipinski rule and showed no toxicity. The pharmacokinetics and physicochemical properties of these targeted compounds were analyzed by using three online web servers pkCSM, Swiss ADME, and Protox-II. This is the first in silico study to document these compound's effectiveness against the standard drug DOX in treating Periodontitis. The Swiss target prediction database was used to retrieve the targets of these compounds. DisGeNET and GeneCards were used to extract the targets of periodontitis. The top five hub genes were identified by Cytoscape utilizing the protein-protein interaction of common genes, from which two hub genes and three binding proteins of collagenase enzymes were used for further studies AA2, PGE2, PI2, TNFA, and PGP. The minimal binding energy observed in molecular docking, indicative of the optimal docking score, corresponds to the highest affinity between the protein and ligand. To corroborate the findings of the docking study, molecular dynamics (MD) simulations, and MMPBSA calculations were conducted for the complexes involving AA2-α-LPHE, AA2-DHC, and AA2-PPR. This research concluded that AA2-DHC was the most stable complex among the investigated interactions, surpassing the stability of the other complexes examined in comparison with the standard drug DOX. Overall, the findings supported the promotion of widespread use of Attukal Kizhangu L. in clinics as a potential therapeutic agent or may be employed for the treatment of acute and chronic Periodontitis.

An optimized method for PFAS analysis using HR-CS-GFMAS via GaF detection.

The analysis of per- and polyfluoroalkyl substances (PFAS) via sum parameters like extractable organic fluorine (EOF) in combination with high resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) is highly promising regarding fluorine sensitivity and selectivity. However, the HR-CS-GFMAS method includes several drying and heating steps which can lead to losses of volatile PFAS before the molecular formation step using e.g., GaF formation. Hence, the method leads to a strong discrimination of PFAS within the EOF depending on their physical/chemical properties and is therefore associated with reduced accuracy. To reduce this discrepancy and to indicate realistic PFAS pollution values, an optimization of the HR-CS-GFMAS method for PFAS analysis is needed. Hence, we determined fluorine response factors of several PFAS with different physical/chemical properties upon application of systematic optimization steps. We could therefore improve the method's sensitivity for PFAS analysis using a modifier drying pre-treatment step followed by a sequential injection of sample solutions. The highest improvement in sensitivity of volatile PFAS was shown upon addition of a Mg modifier during drying pre-treatment. Thereby, during optimization the relative standard deviation of fluorine response factors could be reduced from 55 % (initial method) to 27 % (optimized method) leading to a more accurate determination of organofluorine sum parameters. The method provides an instrumental LOD and LOQ of ß(F) 1.71 µg/L and 5.13 µg/L, respectively. Further validation aimed to investigate several matrix effects with respect to water matrices. Here, substance-specific behavior was observed. For example, perfluorooctanoic acid (PFOA) which was used as calibrator, showed signal suppressions upon high chloride concentrations (>50 mg/L). Hence, a thorough separation of Cl from analytes during sample preparation is needed for accurate sum parameter analysis.

High-resolution quadrupole improves spectral purity and reduces interference from non-target ions in isobaric multiplexed quantitative proteomics.

BACKGROUND: Mass spectrometry (MS)-based proteomics is a powerful tool for identifying and quantifying proteins. However, chimeric spectra caused by the fragmentation of multiple precursors within the same isolation window impair the accuracy of peptide identification and isobaric mass tag-based quantification. While there have been advances in computational deconvolution of chimeric spectra and methods to further separate the peptides by ion mobility or through MSn, the use of narrower isolation windows to decrease the fraction of chimeric species remains to be fully explored. RESULTS: We present results obtained on a SCIEX TripleTOF instrument where the quadrupole was optimized and tuned for precursor isolation at 0.1 Da (FWHH). Using a three-proteome model (trypsin digest of protein lysates from yeast, human and E. coli) and 8-plex iTRAQ labeling to document the interference effect, we investigated the impact of co-fragmentation on spectral purity, identification accuracy and quantification accuracy. The narrow quadrupole isolation window significantly improved the spectral purity and reduced the interference of non-target precursors on quantification accuracy. The high-resolution isolation strategy also reduced the number of false identifications caused by chimeric spectra. While these improvements came at the cost of sensitivity loss, combining high-resolution isolation with other advanced techniques, including ion mobility, may result in improved accuracy in identification and quantification. SIGNIFICANCE: Compared to standard-resolution quadrupole isolation (0.7 Da), high-resolution quadrupole isolation (0.1 Da) significantly improved the spectral purity and quantification accuracy while reducing the number of potential false identifications caused by chimeric spectra, thus showing excellent potential for further development to analyze clinical proteomics samples, for which high accuracy is essential.

Pharmaceutical metabolite identification in lettuce (Lactuca sativa) and earthworms (Eisenia fetida) using liquid chromatography coupled to high-resolution mass spectrometry and in silico spectral library.

Pharmaceuticals released into the aquatic and soil environments can be absorbed by plants and soil organisms, potentially leading to the formation of unknown metabolites that may negatively affect these organisms or contaminate the food chain. The aim of this study was to identify pharmaceutical metabolites through a triplet approach for metabolite structure prediction (software-based predictions, literature review, and known common metabolic pathways), followed by generating in silico mass spectral libraries and applying various mass spectrometry modes for untargeted LC-qTOF analysis. Therefore, Eisenia fetida and Lactuca sativa were exposed to a pharmaceutical mixture (atenolol, enrofloxacin, erythromycin, ketoprofen, sulfametoxazole, tetracycline) under hydroponic and soil conditions at environmentally relevant concentrations. Samples collected at different time points were extracted using QuEChERS and analyzed with LC-qTOF in data-dependent (DDA) and data-independent (DIA) acquisition modes, applying both positive and negative electrospray ionization. The triplet approach for metabolite structure prediction yielded a total of 3762 pharmaceutical metabolites, and an in silico mass spectral library was created based on these predicted metabolites. This approach resulted in the identification of 26 statistically significant metabolites (p < 0.05), with DDA + and DDA - outperforming DIA modes by successfully detecting 56/67 sample type:metabolite combinations. Lettuce roots had the highest metabolite count (26), followed by leaves (6) and earthworms (2). Despite the lower metabolite count, earthworms showed the highest peak intensities, closely followed by roots, with leaves displaying the lowest intensities. Common metabolic reactions observed included hydroxylation, decarboxylation, acetylation, and glucosidation, with ketoprofen-related metabolites being the most prevalent, totaling 12 distinct metabolites. In conclusion, we developed a high-throughput workflow combining open-source software with LC-HRMS for identifying unknown metabolites across various sample types.

A Study of High-Resolution Ultrasound and Magnetic Resonance Imaging Findings in Shoulder Joint Pain at a Tertiary Care Hospital in Central India.

Objective This study aims to investigate the diagnostic efficacy of high-resolution ultrasound (USG) and magnetic resonance imaging (MRI) in patients with shoulder joint pain at a tertiary care hospital in Central India. Methods This cross-sectional study was conducted at Acharya Vinoba Bhave Rural Hospital from 2021 to 2024. The study population consisted of patients with shoulder pain, without fractures, who were evaluated using USG and MRI. Participants with infective arthritis, rheumatoid arthritis, previous shoulder surgery, or contraindications for MRI were excluded. Data were recorded and analyzed using Microsoft Excel (Microsoft Corporation, Redmond, Washington) and R 4.2.0 software (The R Foundation, Vienna, Austria). Sensitivity, specificity, and receiver operating characteristic (ROC) curves were used to compare the diagnostic performance of USG and MRI. Results A total of 80 patients were included, with 49 (61%) males and 31 (39%) females. The MRI findings showed supraspinatus partial tears in 44 (55%) cases, complete tears in 10 (12.5%), and various other shoulder pathologies. USG detected supraspinatus partial tears in 16 (19.5%) and complete tears in seven (8.8%). Kappa statistics indicated moderate to high agreement between USG and MRI for several pathologies, with near-perfect agreement for complete tears. Conclusion High-resolution USG is a valuable tool for the initial assessment of shoulder joint pain, providing reliable diagnostic information with high agreement levels with MRI for complete tears and certain shoulder conditions. MRI remains indispensable for comprehensive evaluation, particularly for partial tears and complex pathologies.

High-resolution carbon emission mapping and spatial-temporal analysis based on multi-source geographic data: A case study in Xi'an City, China.

Cities, contributing over 70% of global emissions, are key areas for climate change mitigation. Heterogeneity within cities determines the need for spatialized urban emissions reduction policies. However, few studies have attempted to characterize the spatial distribution of carbon emissions at the urban scale. To address this issue, a novel mapping method was proposed, using Xi'an as an example to explore the spatial distribution of carbon emissions at the city scale. Firstly, multiple geospatial open-source data, such as point of interest (POI), road networks, and land use, were utilized to identify the locations of emission sources. High-resolution carbon emission distributions were then mapped by allocating emissions based on the Intergovernmental Panel on Climate Change (IPCC) methodology. The study employed Global Moran's I to analyze the changes in spatial heterogeneity at different resolutions. Additionally, the Local Indicators of Spatial Association index (LISA) and Standard Deviation Ellipses (SDE) were adopted to examine the spatiotemporal characteristics of carbon emissions in Xi'an. The results show that carbon emissions at Xi'an City rises from 45.112 million tons to 72.701 million tons between 2010 and 2021. The construction of multi-scale carbon emissions spatial distributions, with a resolution of up to 30 m, allowed for a more detailed characterization of carbon emissions, especially in urban fringe areas. In addition, the results indicate that urban carbon emissions exhibit the strongest spatial autocorrelation at a resolution of 350 m. The study can provide a reference for the development of regional carbon emission reduction policies and spatial planning. In addition, the proposed spatialized method of city carbon emissions depends on open-source data, which allows it to have the potential for application in other cities.

Fine classification of rice fields in high-resolution remote sensing images.

Fine-grained management of rice fields can enhance the yield and quality of rice crops. Challenges in achieving fine classification include interference from similar vegetation, the irregularity of natural field shapes, and complex scale variations. This paper introduces Rice Attention Cascade Network (RACNet), for the fine classification of rice fields in high-resolution satellite remote sensing imagery. The network employs the Hybrid Task Cascade network as the base framework and uses spectral and indices mixed multimodal data as input to reinforce the feature differentiation of similar vegetation. Initially, a Channel Attention Deformable-ResNet (CAD-ResNet) was designed to enhance the feature representation of rice on different channels. Deformable convolution improves the ability of CAD-ResNet to capture irregular field shapes. Then, to address the issue of complex scale changes, the multi-scale features extracted by the CAD-ResNet are progressively fused using an Asymptotic Feature Pyramid, reducing the loss of scale information between non-adjacent layers. Experiments on the Meishan rice dataset show that the proposed method is capable of accurate instance segmentation for fragmented or irregularly shaped rice fields. The evaluation metric AP50 of RACNet reaches 50.8%.

High-resolution ultrasound and superb microvascular imaging findings in a case of post-COVID-19 vaccine parsonage-turner syndrome with multiple nerves involvement.

Parsonage-Turner syndrome (PTS) is an idiopathic condition that may be triggered by vaccination against SARS-CoV-2. High-resolution ultrasound can support the diagnosis and monitoring of PTS patients by demonstrating specific nerve abnormalities. The recently implemented superb microvascular imaging technology can help stratify the prognosis of these patients, with the potential to contribute to the clinical management of PTS.

Artificial intelligence-based quantification of pulmonary HRCT (AIqpHRCT) for the evaluation of interstitial lung disease in patients with inflammatory rheumatic diseases.

High-resolution computed tomography (HRCT) is important for diagnosing interstitial lung disease (ILD) in inflammatory rheumatic disease (IRD) patients. However, visual ILD assessment via HRCT often has high inter-reader variability. Artificial intelligence (AI)-based techniques for quantitative image analysis promise more accurate diagnostic and prognostic information. This study evaluated the reliability of artificial intelligence-based quantification of pulmonary HRCT (AIqpHRCT) in IRD-ILD patients and verified IRD-ILD quantification using AIqpHRCT in the clinical setting. Reproducibility of AIqpHRCT was verified for each typical HRCT pattern (ground-glass opacity [GGO], non-specific interstitial pneumonia [NSIP], usual interstitial pneumonia [UIP], granuloma). Additional, 50 HRCT datasets from 50 IRD-ILD patients using AIqpHRCT were analysed and correlated with clinical data and pulmonary lung function parameters. AIqpHRCT presented 100% agreement (coefficient of variation = 0.00%, intraclass correlation coefficient = 1.000) regarding the detection of the different HRCT pattern. Furthermore, AIqpHRCT data showed an increase of ILD from 10.7 ± 28.3% (median = 1.3%) in GGO to 18.9 ± 12.4% (median = 18.0%) in UIP pattern. The extent of fibrosis negatively correlated with FVC (ρ=-0.501), TLC (ρ=-0.622), and DLCO (ρ=-0.693) (p < 0.001). GGO measured by AIqpHRCT also significant negatively correlated with DLCO (ρ=-0.699), TLC (ρ=-0.580) and FVC (ρ=-0.423). For the first time, the study demonstrates that AIpqHRCT provides a highly reliable method for quantifying lung parenchymal changes in HRCT images of IRD-ILD patients. Further, the AIqpHRCT method revealed significant correlations between the extent of ILD and lung function parameters. This highlights the potential of AIpqHRCT in enhancing the accuracy of ILD diagnosis and prognosis in clinical settings, ultimately improving patient management and outcomes.

Post-mortem Interval estimate based on dental pulp: A histomorphology approach.

Estimating the post-mortem interval (PMI) of human remains based on the histomorphology of dental pulp parameters is promising, but available evidence is scarce and sometimes contradictory without a scientific model. The aim of the study is to characterise the histomorphological changes of dental pulp associated with the decomposition of human remains by a qualitative and quantitative approach. The main aim is to establish a correlation based on post-mortem (PM) dental pulp histomorphology and the PMI, and whether pulp degradation could be an available medico-legal tool for PMI estimation beyond the first week after death (late PMI). The eligible sample consisted of 27 sound teeth from 16 healthy patients aged 16 to 72 years due to orthodontic or oral surgery treatment, to create PMI's simulating the death of the subject as the time elapsed from tooth avulsion. Data collected from patients (sex, date of birth, tooth position, date and hour of the avulsion, date and hour of pulp extraction) were anonymised in accordance with the requirements of Faculty of Dental Medicine of the University of Lisbon. The sample was divided into 9 groups of 3 teeth according to different PMI sets from T0 (baseline) up to 2 weeks (T0, 7, 12, 24, 36, 48, and 72 hours, 1 and 2 weeks). All the dental samples were stored at room temperature up to the time of pulp extraction and then prepared with haematoxylin and eosin stain. High-resolution microscopy was performed to obtain histological images. An operator performed the qualitative evaluation of blood vessels, collagen fibres, and the extra-cellular matrix (ECM) in PM pulps and measured the variation in cells/nuclei density by counting 6 different ROIs (Regions of Interest) for each pulp manually and automatically (quantitative analysis). Qualitative results showed that the degeneration of dental pulp appears 7 hours after death but histological changes in vessels, fibres, and ECM in PM dental pulp are characterised by high variability, consequently it is not possible to generalise the results for early PMIs. Quantitative measurements proved that cell count cannot be standardised due to the presence of superimposed layers of cells and nuclei fragmentation. Odontoblasts did not demonstrate evidence of cellular or nuclear lysis up to 14 PM suggesting their applicability in late PMIs. Future research will focus on late PMIs and different techniques of tooth preparation.

A reliable method to prepare milligram size environmental samples to quantify metal(loid)s by high-resolution graphite furnace atomic absorption spectrometry.

We searched for an extraction method that would allow a precise quantification of metal(loid)s in milligram-size samples using high-resolution graphite furnace atomic absorption spectrometry (HR-GFAAS). We digested biological (DORM-4, DOLT-5 and TORT-3) and sediment (MESS-4) certified reference materials (CRMs) using nitric acid in a drying oven, aqua regia in a drying oven, or nitric acid in a microwave. In addition, we digested MESS-4 using a mixture of nitric and hydrofluoric acids in a drying oven. We also evaluated the effect of sample size (100 and 200 mg) on the extraction efficiency. Nitric acid extraction in a drying oven yielded the greatest recovery rates for all metal(loid)s in all tested CRMs (80.0 %-100.0 %) compared with the other extraction methods tested (67.3 %-99.2 %). In most cases, the sample size did not have a significant effect on the extraction efficiency. Therefore, we conclude that nitric acid digestion in a drying oven is a reliable extraction method for milligram-size samples to quantify metal(loid)s with HR-GFAAS. This validated method could provide substantial benefits to environmental quality monitoring programs by significantly reducing the time and costs required for sample collection, storage, transport and preparation, as well as the amount of hazardous chemicals used during sample extraction and analysis. •Sample digestion with nitric acid in a drying oven yielded the greatest recovery rates of metal(loid)s from biological and sediment certified reference materials.•The recovery rates of metal(loid)s from biological and sediment certified reference materials using nitric acid digestion in a drying oven ranged from 73 % to 100 %.•Digestion with nitric acid in a drying oven is a simple and reliable method to extract small size environmental samples for metal(loid)s quantification by high-resolution graphite furnace atomic absorption spectrometry.

Nocturnal Gastroesophageal Reflux and Sleep Depth in Healthy Adults, as Measured by Portable High-Resolution Manometry, Esophageal pH, and Electroencephalography.

BACKGROUND: The primary mechanism of diurnal gastroesophageal reflux (GER) is transient lower esophageal sphincter relaxation (TLESR) in both healthy persons and patients with gastroesophageal reflux disease (GERD). However, few studies have examined nocturnal GER. Using portable high-resolution manometry (HRM), esophageal pH, and electroencephalography (EEG), we investigated the association of onset of nocturnal GER with sleep depth in healthy Japanese adults. METHODS: We recruited ten healthy men (mean age 33.5 ± 4.2 years) with no reflux symptoms, no history of surgery, and no current medication use. HRM and an esophageal pH catheter were inserted in the evening. The participants returned home after consuming a test meal, and EEG was placed at home before bedtime to measure sleep depth. RESULTS: The main mechanism underlying nocturnal GER was TLESR (15/17 episodes: 88.2%). The rate of TLESR with nocturnal GER during sleep was high (51.9%, 27/52 episodes). Sleep depth during TLESR was 44.2% (23/52 times) awake and 34.6% (18/52 times) shallow sleep (N1-2). Sleep depth during TLESR with nocturnal GER was 74.0% (20/27 time) awake and 18.5% (5/27 times) shallow sleep (N1-2). CONCLUSION: The primary mechanism underlying nocturnal GER was TLESR in healthy Japanese men. TLESR and TLESR with nocturnal GER were more frequent during awakenings and shallow sleep.

Simulating block-scale flood inundation and streamflow using the WRF-Hydro model in the New York City metropolitan area.

This study assesses the performance of the Weather Research and Forecasting-Hydrological modeling system (WRF-Hydro) in the simulation of street-scale flood inundation. The case study is the Hackensack River Watershed in New Jersey, US, which is part of the operational Stevens Flood Advisory System (SFAS), a one-way coupled hydrodynamic-hydrologic system that currently uses the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) to simulate streamflow. The performance of the 50-m gridded WRF-Hydro model was assessed for potential integration into the operational SFAS system. The model was calibrated with the dynamically dimensioned search algorithm using streamflow observations. The model performance was assessed using (i) streamflow observations, (ii) USGS HWMs, and (iii) crowdsourced data on street inundation. Results show that WRF-Hydro outperformed the HEC-HMS model. WRF-Hydro over and underestimated flood inundation extent due to the inaccuracy of the synthetic rating curves and the modeling structure errors. An agreement was noticed between WRF-Hydro and crowdsourced data on flood extent.

A pilot study on post-mortem determination of drug abuse on dental tissues.

BACKGROUND: Post-mortem toxicology constantly deals with the research of reliable alternative matrices to be applied in case of highly damaged corpses (such us carbonized, skeletonized, human remains, etc.). Teeth represent a promising alternative matrix since dental tissues are endowed by different features, resistance and stability after death. SCOPE: Since scant literature reported on the pharmacokinetics and mechanism of incorporation of xenobiotics into dental tissues, this pilot research aims to investigate whether in the pulp can be detected the same substances found in blood in drug related death cases. Secondly, the study is addressed to disclose the possible deposit of drugs in dental hard tissues (dentine and/or enamel), thus contributing to reconstruct the drug abuse history (timing, e.g.). MATERIALS AND METHODS: The study experimented with a novel method to separately analyse dental enamel, dentin, and pulp, applied to 10 teeth collected during autopsies of drug-related deaths along with blood and hair samples for classic toxicological analyses. Each tooth was prepared by "pulverization technique" and then analysed by gas chromatography paired with mass spectrometry (GC-MS) and ultra high performance liquid chromatography coupled to high resolution mass spectrometry (UHPLC/HR-MS) for searching cocaine, opiates, and metabolites. The results were then compared with those obtained from blood and hair samples. RESULTS: Preliminary results demonstrated that teeth differ from any other classic matrix (blood and hairs) since the qualitative correspondence of the detected substances between pulp and blood as well as dental hard tissues and hair suggests that they can be useful in post-mortem evaluation as a unique matrix for both acute and chronic assumptions of drugs. The mechanism of accumulation of substances in mineralized dental tissues emerged the most significant result, being influenced by the type of molecule and the method of assumption. The main limitation of this study is the limited availability of the sample and the absence of anamnestic information of the time, rates and method of drug assumption during life. Further research is necessary to systematically investigate the distribution of different substances within the different tissues of the tooth.