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Environment International Jun 2024The National Academies of Sciences, Engineering, and Medicine recommends per- and polyfluoroalkyl substance (PFAS) blood testing for patients with risk of elevated...
The National Academies of Sciences, Engineering, and Medicine recommends per- and polyfluoroalkyl substance (PFAS) blood testing for patients with risk of elevated exposure, and the Agency for Toxic Substances and Disease Registry (ATSDR) suggests PFAS blood testing based on exposure. Barriers to PFAS blood testing include cost, access to labs, and evolving laboratory methods. We quantify water and serum PFAS levels among a highly-exposed cohort in an area with groundwater contaminated by historical agricultural biosolid application. We compare the gold standard PFAS serum test with a commercial test and results from a one-compartment toxicokinetic model. Participants were adults (n = 30) whose household (n = 19) water had levels of the sum of six PFAS > 500 ng/L. Serum PFAS were measured using liquid chromatography-tandem mass spectrometry. Demographic and water consumption data were collected via telephone. Serum PFAS results from the commercial test were accessed via medical record. Statistical analysis included descriptive statistics and bivariate plots of serum levels. Perfluorohexanoic acid, perfluoroheptanoic acid (PFHpA), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorobutanesulfonic acid, perfluorohexanesulfonic acid (PFHxS), and perfluorooctanesulfonic acid (PFOS) were detected in 19 wells, and PFHpA, PFOA, PFNA, perfluorodecanoic acid, perfluoroundecanoic acid, PFHxS, and PFOS were detected in at least 19 participants' serum. In well water, PFOA and PFOS levels had geometric means (GMs) of 1749 ng/L (geometric standard deviation [GSD] 2.4) and 887 ng/L (GSD 19.7), respectively. In serum, PFOA and PFOS had GMs of 116.2 µg/L (GSD 13.5) and 58.3 µg/L (GSD 13.8), respectively. Our results are comparable with and had a wider mix of PFAS than other high-exposure cohorts. There was good agreement between the commercial and gold standard tests for PFOA, PFNA, and PFHxS, and mixed agreement between the gold standard test and modeled predictions, suggesting water-based toxicokinetic models of serum PFAS may be inadequate for assessing exposure in this population.
PubMed: 38941944
DOI: 10.1016/j.envint.2024.108850 -
Biophysical Chemistry Jun 2024Human islet amyloid polypeptide (hIAPP) forms amyloid deposits that contribute to β-cell death in pancreatic islets and are considered a hallmark of Type II diabetes...
Human islet amyloid polypeptide (hIAPP) forms amyloid deposits that contribute to β-cell death in pancreatic islets and are considered a hallmark of Type II diabetes Mellitus (T2DM). Evidence suggests that the early oligomers of hIAPP formed during the aggregation process are the primary pathological agent in islet amyloid induced β-cell death. The self-assembly mechanism of hIAPP, however, remains elusive, largely due to limitations in conventional biophysical techniques for probing the distribution or capturing detailed structures of the early, structurally dynamic oligomers. The advent of Ion-mobility Mass Spectrometry (IM-MS) has enabled the characterisation of hIAPP early oligomers in the gas phase, paving the way towards a deeper understanding of the oligomerisation mechanism and the correlation of structural information with the cytotoxicity of the oligomers. The sensitivity and the rapid structural characterisation provided by IM-MS also show promise in screening hIAPP inhibitors, categorising their modes of inhibition through "spectral fingerprints". This review delves into the application of IM-MS to the dissection of the complex steps of hIAPP oligomerisation, examining the inhibitory influence of metal ions, and exploring the characterisation of hetero-oligomerisation with different hIAPP variants. We highlight the potential of IM-MS as a tool for the high-throughput screening of hIAPP inhibitors, and for providing insights into their modes of action. Finally, we discuss advances afforded by recent advancements in tandem IM-MS and the combination of gas phase spectroscopy with IM-MS, which promise to deliver a more sensitive and higher-resolution structural portrait of hIAPP oligomers. Such information may help facilitate a new era of targeted therapeutic strategies for islet amyloidosis in T2DM.
PubMed: 38941872
DOI: 10.1016/j.bpc.2024.107285 -
Ecotoxicology and Environmental Safety Jun 2024Chromium (Cr) exposure is associated with various respiratory system diseases, but there are limited studies investigating its impact on lung function in young adults....
Chromium (Cr) exposure is associated with various respiratory system diseases, but there are limited studies investigating its impact on lung function in young adults. The Cr exposure-related metabolomic changes are not well elucidated. This study recruited 608 students from a university in Shandong Province, China in 2019. We used cohort design fitted with linear mixed-effects models to assess the association between blood Cr concentration and lung function. In addition, we performed metabolomic and lipidomic analyses of baseline serum samples (N = 582) using liquid chromatography-mass spectrometry. Two-step statistical analysis (analysis of variance and mixed-linear effect model) was used to evaluate the effect of blood Cr exposure on metabolites. We found that blood Cr was associated with decreased lung function in young adults. Each 2-fold increase in blood Cr concentrations was significantly associated with decreased FEV and FVC by 35.26 mL (95 % CI: -60.75, -9.78) and 38.56 mL (95 % CI: -66.60, -10.51), respectively. In the metabolomics analysis, blood Cr exposure was significantly associated with 14 key metabolites. The changed metabolites were mainly enriched in six pathways including lipid metabolism, amino acid metabolism, and cofactor vitamin metabolism. Blood Cr may affect lung function through oxidative stress and inflammation related pathways.
PubMed: 38941662
DOI: 10.1016/j.ecoenv.2024.116594 -
Metabolomics : Official Journal of the... Jun 2024Burkitt lymphoma (BL) is an aggressive non-Hodgkin lymphoma associated with Plasmodium falciparum and Epstein-Barr virus, both of which affect metabolic pathways. The...
INTRODUCTION
Burkitt lymphoma (BL) is an aggressive non-Hodgkin lymphoma associated with Plasmodium falciparum and Epstein-Barr virus, both of which affect metabolic pathways. The metabolomic patterns of BL is unknown.
MATERIALS AND METHODS
We measured 627 metabolites in pre-chemotherapy treatment plasma samples from 25 male children (6-11 years) with BL and 25 cancer-free area- and age-frequency-matched male controls from the Epidemiology of Burkitt Lymphoma in East African Children and Minors study in Uganda using liquid chromatography-tandem mass spectrometry. Unconditional, age-adjusted logistic regression analysis was used to estimate odds ratios (ORs) and their 95% confidence intervals (CIs) for the BL association with 1-standard deviation increase in the log-metabolite concentration, adjusting for multiple comparisons using false discovery rate (FDR) thresholds and Bonferroni correction.
RESULTS
Compared to controls, levels for 42 metabolite concentrations differed in BL cases (FDR < 0.001), including triacylglyceride (18:0_38:6), alpha-aminobutyric acid (AABA), ceramide (d18:1/20:0), phosphatidylcholine ae C40:6 and phosphatidylcholine C38:6 as the top signals associated with BL (ORs = 6.9 to 14.7, P < 2.4✕10). Two metabolites (triacylglyceride (18:0_38:6) and AABA) selected using stepwise logistic regression discriminated BL cases from controls with an area under the curve of 0.97 (95% CI: 0.94, 1.00).
CONCLUSION
Our findings warrant further examination of plasma metabolites as potential biomarkers for BL risk/diagnosis.
Topics: Humans; Burkitt Lymphoma; Child; Uganda; Male; Case-Control Studies; Metabolomics; Metabolome; Female
PubMed: 38940866
DOI: 10.1007/s11306-024-02130-1 -
Journal of Radiation Research Jun 2024The ionizing radiation with high linear energy transfer (LET), such as a heavy ion beam, induces more serious biological effects than low LET ones, such as gamma- and...
The ionizing radiation with high linear energy transfer (LET), such as a heavy ion beam, induces more serious biological effects than low LET ones, such as gamma- and X-rays. This indicates a difference in the DNA damage produced by low and high LET radiations and their biological effects. We have been studying the differences in DNA damage produced by gamma-rays and carbon ion beams. Therefore, we analyze mutations induced by both ionizing radiations to discuss the differences in their biological effects in this study. pUC19 plasmid DNA was irradiated by carbon ion beams in the solution containing 1M dimethyl sulfoxide to mimic a cellular condition. The irradiated DNA was cloned in competent cells of Escherichia coli. The clones harboring some mutations in the region of lacZα were selected, and the sequence alterations were analyzed. A one-deletion mutation is significant in the carbon-irradiated DNA, and the C:G↔T:A transition is minor. On the other hand, the gamma-irradiated DNA shows mainly G:C↔T:A transversion. These results suggest that carbon ion beams produce complex DNA damage, and gamma-rays are prone to single oxidative base damage, such as 8-oxoguanine. Carbon ion beams can also introduce oxidative base damage, and the damage species is 5-hydroxycytosine. This was consistent with our previous results of DNA damage caused by heavy ion beams. We confirmed the causal DNA damage by mass spectrometry for these mutations.
PubMed: 38940734
DOI: 10.1093/jrr/rrae050 -
Bioinformatics (Oxford, England) Jun 2024Tandem mass spectrometry (MS/MS) is a crucial technology for large-scale proteomic analysis. The protein database search or the spectral library search are commonly used...
MOTIVATION
Tandem mass spectrometry (MS/MS) is a crucial technology for large-scale proteomic analysis. The protein database search or the spectral library search are commonly used for peptide identification from MS/MS spectra, which, however, may face challenges due to experimental variations between replicated spectra and similar fragmentation patterns among distinct peptides. To address this challenge, we present SpecEncoder, a deep metric learning approach to address these challenges by transforming MS/MS spectra into robust and sensitive embedding vectors in a latent space. The SpecEncoder model can also embed predicted MS/MS spectra of peptides, enabling a hybrid search approach that combines spectral library and protein database searches for peptide identification.
RESULTS
We evaluated SpecEncoder on three large human proteomics datasets, and the results showed a consistent improvement in peptide identification. For spectral library search, SpecEncoder identifies 1%-2% more unique peptides (and PSMs) than SpectraST. For protein database search, it identifies 6%-15% more unique peptides than MSGF+ enhanced by Percolator, Furthermore, SpecEncoder identified 6%-12% additional unique peptides when utilizing a combined library of experimental and predicted spectra. SpecEncoder can also identify more peptides when compared to deep-learning enhanced methods (MSFragger boosted by MSBooster). These results demonstrate SpecEncoder's potential to enhance peptide identification for proteomic data analyses.
AVAILABILITY AND IMPLEMENTATION
The source code and scripts for SpecEncoder and peptide identification are available on GitHub at https://github.com/lkytal/SpecEncoder. Contact: [email protected].
Topics: Proteomics; Peptides; Humans; Tandem Mass Spectrometry; Databases, Protein; Deep Learning; Software
PubMed: 38940141
DOI: 10.1093/bioinformatics/btae220 -
Bioinformatics (Oxford, England) Jun 2024One of the core problems in the analysis of protein tandem mass spectrometry data is the peptide assignment problem: determining, for each observed spectrum, the peptide...
MOTIVATION
One of the core problems in the analysis of protein tandem mass spectrometry data is the peptide assignment problem: determining, for each observed spectrum, the peptide sequence that was responsible for generating the spectrum. Two primary classes of methods are used to solve this problem: database search and de novo peptide sequencing. State-of-the-art methods for de novo sequencing use machine learning methods, whereas most database search engines use hand-designed score functions to evaluate the quality of a match between an observed spectrum and a candidate peptide from the database. We hypothesized that machine learning models for de novo sequencing implicitly learn a score function that captures the relationship between peptides and spectra, and thus may be re-purposed as a score function for database search. Because this score function is trained from massive amounts of mass spectrometry data, it could potentially outperform existing, hand-designed database search tools.
RESULTS
To test this hypothesis, we re-engineered Casanovo, which has been shown to provide state-of-the-art de novo sequencing capabilities, to assign scores to given peptide-spectrum pairs. We then evaluated the statistical power of this Casanovo score function, Casanovo-DB, to detect peptides on a benchmark of three mass spectrometry runs from three different species. In addition, we show that re-scoring with the Percolator post-processor benefits Casanovo-DB more than other score functions, further increasing the number of detected peptides.
Topics: Databases, Protein; Peptides; Machine Learning; Mass Spectrometry; Algorithms; Sequence Analysis, Protein; Tandem Mass Spectrometry
PubMed: 38940129
DOI: 10.1093/bioinformatics/btae218 -
Annals of Agricultural and... Jun 2024Snow cover serves as a unique indicator of environmental pollution in both urban and rural areas. As a seasonal cover, it accumulates various pollutants emitted into the...
INTRODUCTION AND OBJECTIVE
Snow cover serves as a unique indicator of environmental pollution in both urban and rural areas. As a seasonal cover, it accumulates various pollutants emitted into the atmosphere, thus providing insight into air pollution types and the relative contributions of different pollution sources. The aim of the study is to analyze the distribution of trace elements in snow cover to assess the anthropogenic influence on pollution levels, and better understand ecological threats.
MATERIAL AND METHODS
The study was conducted in rural areas around the village of Wólka in the Lublin Province of eastern Poland, and in urban districts of the city of Lublin, capital of the Province. Samples were analyzed using Inductively Coupled Plasma-Mass Spectrometry, the Enrichment Factor (EF), and ecological risk indices (RI), were calculated to evaluate the contamination and potential ecological risks posed by the metals.
RESULTS
The findings indicate higher concentrations of metals like sodium and iron in urban areas, likely due to road salt use and industrial activity, respectively. Enrichment factors showed significant anthropogenic contributions, particularly for metals like sodium, zinc, and cadmium, which had EF values substantially above natural levels. The potential ecological risk assessment highlighted a considerable ecological threat in urban areas compared to rural settings, primarily due to higher concentrations of metals.
CONCLUSIONS
The variation in metal concentrations between urban and rural snow covers reflects the impact of human activities on local environments. Urban areas showed higher pollution levels, suggesting the need for targeted pollution control policies to mitigate the adverse ecological impacts. This study underscores the importance of continuous monitoring and comprehensive risk assessments to effectively manage environmental pollution.
Topics: Snow; Poland; Environmental Monitoring; Risk Assessment; Metals; Humans; Air Pollutants; Cities; Rural Population
PubMed: 38940104
DOI: 10.26444/aaem/190317 -
Frontiers in Bioscience (Landmark... Jun 2024The senescence marker protein 30 (SMP30) is a calcium-binding protein whose expression decreases with age, and is closely associated with hepatocellular carcinoma (HCC)...
BACKGROUND
The senescence marker protein 30 (SMP30) is a calcium-binding protein whose expression decreases with age, and is closely associated with hepatocellular carcinoma (HCC) development. The primary goal of this study was to examine the mechanistic effect of SMP30 on HCC migration and invasion.
METHODS
Bioinformatic and immunohistochemical approaches were used to examine the expression of SMP30 in HCC tissues and its relationship to patient survival. We investigated the effects of SMP30 expression on HCC cell proliferation, migration, invasion, and cell cycle dynamics. cDNA microarray technology was used to determine the gene expression profile of SK-Hep-1 cells following recombinant SMP30 overexpression to identify genes downstream of SMP30 that regulate HCC cell migration and invasion. We identified SMP30 interacting proteins by affinity purification-mass spectrometry (AP-MS) and co-immunoprecipitation/western blotting (COIP-WB).
RESULTS
SMP30 expression was lower in HCC tissues compared with normal liver tissues, and its expression positively correlated with overall survival in HCC patients. Additionally, SMP30 overexpression effectively blocked the migratory and invasive properties of SK-Hep-1 cells, but did not affect either proliferation rates or cell cycle. cDNA microarray results confirmed that many of the differentially expressed genes identified are involved in the process of epithelial-mesenchymal transition (EMT). AP-MS and COIP-WB experiments confirmed that Rho-associated protein kinase 1 (ROCK1) interacts with SMP30 in SK-Hep-1 cells, and ROCK1 is known to intimately regulate the EMT process.
CONCLUSION
SMP30 inhibits HCC metastasis by influencing the expression of EMT-related proteins after interacting with ROCK1.
Topics: Humans; rho-Associated Kinases; Epithelial-Mesenchymal Transition; Carcinoma, Hepatocellular; Liver Neoplasms; Calcium-Binding Proteins; Neoplasm Invasiveness; Cell Line, Tumor; Cell Movement; Cell Proliferation; Intracellular Signaling Peptides and Proteins; Male; Female; Gene Expression Regulation, Neoplastic
PubMed: 38940025
DOI: 10.31083/j.fbl2906214 -
Frontiers in Bioscience (Elite Edition) Jun 2024Due to the constant and improper use of chemicals, including pesticides, many substances, and their degradation products can accumulate in the soil and negatively affect...
BACKGROUND
Due to the constant and improper use of chemicals, including pesticides, many substances, and their degradation products can accumulate in the soil and negatively affect its organisms.
METHODS
In this study, morphological methods, Gram-staining, and Matrix-Assisted Laser Desorption/Ionzation Time of Flight Mass Spectrometry (MALDI-TOF MS) methods were used to isolate bacteria from agricultural soils, while genetic identification was conducted using 16S rRNA. The density of bacteria was determined using the spectrophotometric method, and the residual amount of cypermethrin was determined and analyzed using Gas chromatograohy-mass spectrometry (GC-MS) methods.
RESULTS
Nine isolates were obtained from various agricultural soils. Isolate No. 3 showed the greatest effectiveness against cypermethrin and was selected for further research. Isolate No. 3 was identified as the strain PDB-3 and was registered in the National Center for Biotechnology Information (NCBI) database (GenBank: OL587509.1). Using this strain, the influence of various external factors on the degradation of cypermethrin was studied. This bacterium demonstrated 100% degradation of cypermethrin in 20 days under optimal conditions (temperature: 30 °C; optical density (OD) = 0.2; cypermethrin concentration: 80 ± 0.02 mg/kg). In addition, PDB-3 changed the original structure of cypermethrin into various intermediate metabolites, such as 2-hydroxy-3-phenoxy benzeneacetonitrile, 3-phenoxybenzaldehyde, 3-phenoxybenzaldehyde, methyl stearate, anethol, citral, and phenol.
CONCLUSIONS
The results obtained using PDB-3 provide the basis for large-scale field trials on the bioremediation of cypermethrin-contaminated soils.
Topics: Pyrethrins; Ochrobactrum; Pesticides; Biodegradation, Environmental; Soil Microbiology; Gas Chromatography-Mass Spectrometry; RNA, Ribosomal, 16S; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
PubMed: 38939915
DOI: 10.31083/j.fbe1602020