Profile Method Research Articles

Prevalence of multiple sclerosis in Brazil: An updated systematic review with meta-analysis.

The prevalence of multiple sclerosis has been increased worldwide. However, no update on the prevalence of multiple sclerosis in Brazil has been conducted since 2015 OBJECTIVE: The aim of the present review is to perform an update of the multiple sclerosis prevalence in Brazil as well as to analyze its current epidemiological profile METHODS: We searched for studies on the multiple sclerosis prevalence in Brazil. The databases researched were Medline (PubMed), Embase, Scielo, Scopus and Web of Science using the keywords "prevalence", "prevalence study", "incidence", "epidemiology", "multiple sclerosis" and "Brazil" RESULTS: Eleven studies were included for descriptive and quantitative analysis. The pooled prevalence of multiple sclerosis in Brazil estimates 14.5 cases per 100.000 inhabitants. It is more prevalent in white people (74 %) and female (76.3 %). The most prevalent clinical form is the relapsing-remitting form (80.2 %), followed by the secondary progressive form (13 %) and by the primary progressive form (6.8 %) CONCLUSION: Although the prevalence of multiple sclerosis in Brazil varies substantially between regions, it is in accordance with what is known in the world. However, there is a lack of recent epidemiological studies of multiple sclerosis in Brazil and more studies are needed for better accuracy and comprehension of its prevalence.

A rapid and simple MALDI-TOF MS lipid profiling method for differentiating Mycobacterium ulcerans from Mycobacterium marinum.

Mycobacterium ulcerans, a slow-growing nontuberculous mycobacterium, causes Buruli ulcer, a neglected tropical disease. Distinguishing M. ulcerans from related species, including Mycobacterium marinum, poses challenges with respect to making accurate identifications. In this study, we developed a rapid and simple identification method based on mycobacterial lipid profiles and used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze the lipid profiles of M. ulcerans (n = 35) and M. marinum (n = 19) isolates. Bacterial colonies pre-cultured on 2% Ogawa egg slants for 2 months were collected, and total lipids were extracted using an MBT Lipid Xtract kit. Spectra were obtained in negative ion mode using a MALDI Biotyper Sirius system, with ClinProTools v3.0 being used to analyze the spectra based on the application of three algorithms (genetic algorithm [GA], supervised neural network [SNN], and quick classifier [QC)]). Cross-validation was performed using a 20% leave-out set randomly selected from the samples. Models generated using GA, SNN, and QC showed cross-validation values of 100%, 100%, and 97.9%, respectively, and all algorithms achieved 100% recognition capability values. Our findings indicate that MALDI-TOF analysis of lipid profiles can accurately differentiate two mycobacterial species (M. ulcerans and M. marinum) that are difficult to distinguish using conventional protein-targeting methods.IMPORTANCEBuruli ulcer, caused by Mycobacterium ulcerans, is a neglected tropical disease. However, distinguishing M. ulcerans from related species, including Mycobacterium marinum, presents certain challenges. In this study, we demonstrate the utility of a rapid yet simple method for differentiating isolates of these mycobacteria based on their lipid profiles using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. This new approach can accurately identify species that are otherwise difficult to distinguish using conventional techniques. This represents a significant diagnostic advance for clinical laboratories, in that it enables a more rapid and precise identification, thereby leading to earlier treatment initiation and more appropriate treatment regimens for infections caused by these bacteria.

A Survey of Heuristics for Profile and Wavefront Reductions

This article surveys heuristic methods for profile and wavefront reductions. These graph layout problems represent a challenge for optimization methods and heuristics especially. The article presents the graph layout problems with their formal definition. It provides an ample perspective of techniques for designing heuristic methods for these graph layout problems but concentrates on the approaches and methodologies that yield high-quality solutions. Thus, this work references the most relevant studies in the associated literature and discusses the current state-of-the-art heuristics for these graph layout problems.

In-situ profiling of glycosylation on single cells with surface plasmon resonance imaging

Cellular glycosylation is crucial for cell recognition, signal transduction, and the development of various diseases, especially in tumor initiation, progression, and metastasis. Current glycosylation profiling methods normally involve laborious sample processing and labeling and lack in-situ quantitative analysis. Here, we present a direct optical method to investigate and quantify the glycan expression on single cells based on lectin-glycan kinetic quantification with plasmonic imaging. Three unlabeled lectins (WGA, SBA, ConA) are employed as probes to bind with specific glycans, and binding kinetics are assessed to determine glycosylation profiles. The result reveals cell-to-cell heterogeneity in glycosylation patterns. To demonstrate the capability of our method, the glycosylation profiling of four distinct cell lines is explored, showing obvious alterations in glycan expression related to tumor initiation, progression, and metastasis. This approach enables direct quantification of glycosylation and binding kinetics, providing insights into tumor cell glycosylation mechanisms and potential applications in disease diagnosis and treatment.

Utilising single‐cell sequencing in clinical nutraceutical research: Recent progress and perspectives

AbstractBackgroundSingle‐cell sequencing technologies have revolutionised pharmaceutical research by providing in‐depth insights into human biology at the single‐cell level. These tools enable researchers to identify rare cell types and analyse cellular diversity within tissues, facilitating the discovery of new therapeutic targets and biomarkers. However, their application in nutraceutical research is still in its early stages.Main BodyUnlike pharmaceuticals, which have well‐defined chemical structures and mechanisms, nutraceuticals are food‐based materials intended for specific medical purposes and often contain complex and diverse food chemicals. These molecules can work synergistically, producing multi‐targeted effects in various tissues. Traditional bulk profiling methods for tissues and tumours do not adequately capture cellular heterogeneity or specific cellular responses to treatments. Therefore, advanced single‐cell sequencing is crucial for dissecting tissues into distinct cell types, helping to clarify the underlying mechanisms at the cellular level. Many derivatives of functional foods have been marketed or assessed, demonstrating health benefits. However, mechanistic insights are lacking, with most current data derived from observational studies or traditional in vitro and in vivo models. Human clinical trials are needed to validate these nutraceutical effects and determine effective and safe dosages. Edible mushrooms have gained attention as nutraceuticals due to their medicinal properties. They have been observed to enhance immunity, reduce inflammation, and combat cancer. These effects have been attributed to their unique bioactive components and historical uses in traditional medicine. Epidemiological studies show that higher consumption of edible mushrooms is linked to a reduced risk of certain cancers.ConclusionIn this review, we share important lessons learned in the design and execution of clinical trials focusing on white button mushrooms as anti‐cancer nutraceuticals. We demonstrate the use of single‐cell RNA sequencing (scRNA‐seq) in nutraceutical research to capture the nuanced biological responses and health effects of dietary foods and their constituents.

Chromatin accessibility provides a window into the genetic etiology of human brain disease.

Neuropsychiatric and neurodegenerative diseases have a significant genetic component. Risk variants often affect the noncoding genome, altering cis-regulatory elements (CREs) and chromatin structure, ultimately impacting gene expression. Chromatin accessibility profiling methods, especially assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq), have been used to pinpoint disease-associated SNPs and link them to affected genes and cell types in the brain. The integration of single-cell technologies with genome-wide association studies (GWAS) and transcriptomic data has further advanced our understanding of cell-specific chromatin dynamics. This review discusses recent findings regarding the role played by chromatin accessibility in brain disease, highlighting the need for high-quality data and rigorous computational tools. Future directions include spatial chromatin studies and CRISPR-based functional validation to bridge genetic discovery and clinical applications, paving the way for targeted gene-regulatory therapies.

Integrating Metagenomic and Culture-Based Techniques to Detect Foodborne Pathogens and Antimicrobial Resistance Genes in Malaysian Produce

Foodborne illnesses pose a significant global health threat, often caused by pathogens like Escherichia coli, Listeria monocytogenes, and Salmonella spp. The emergence of antibiotic-resistant strains further exacerbates food safety challenges. This study combines shotgun metagenomics and culture-based approaches to detect foodborne pathogens and antimicrobial resistance genes (ARGs) in Malaysian produce and meats from the Kinta Valley region. A total of 27 samples comprising vegetables, meats, and fruits were analyzed. Metagenomics provided comprehensive microbial profiles, revealing diverse bacterial communities with species-level taxonomic resolution. Culture-based methods complemented these findings by identifying viable pathogens. Key foodborne pathogens were detected, with Listeria monocytogenes identified in meats and vegetables and Shigella flexneri detected inconsistently between the methods. ARGs analysis highlighted significant resistance to cephalosporins and penams, particularly in raw chicken and vegetable samples, underscoring the potential public health risks. While deli meats and fruits exhibited a lower antimicrobial resistance prevalence, resistant genes linked to E. coli and Salmonella strains were identified. Discrepancies between the methods suggest the need for integrated approaches to improve the pathogen detection accuracy. This study demonstrates the potential of metagenomics in advancing food safety research and supports its adoption as a complementary tool alongside culture-based methods for comprehensive foodborne pathogen surveillance and ARG profiling in Malaysian food systems.

Review and meta-analysis of gene expression biomarkers predictive of chemical-induced genotoxicity in vivo.

There is growing recognition across broad sectors of the toxicology community that gene expression biomarkers have the potential to identify genotoxic and nongenotoxic carcinogens through a weight-of-evidence approach, providing opportunities to reduce reliance on the 2-year bioassay to identify carcinogens. In August 2022, a workshop within the International Workshops on Genotoxicity Testing (IWGT) was held to critically review current methods to identify genotoxicants using various 'omics profiling methods. Here, we describe the findings of a workshop subgroup focused on the state of the science regarding the use of biomarkers to identify chemicals that act as genotoxicants in vivo. A total of 1341 papers were screened to identify those that were most relevant. While six published biomarkers with characterized accuracy were initially examined, four of the six were not considered further, because they had not been tested for classification accuracy using additional sets of chemicals or other transcript profiling platforms. Two independently derived biomarkers used in conjunction with standard computational techniques can identify genotoxic chemicals in vivo (rat liver or both rat and mouse liver) on different gene expression profiling platforms. The biomarkers have predictive accuracies of ≥92%. These biomarkers have the potential to be used in conjunction with other biomarkers in integrated test strategies using short-term rodent exposures to identify genotoxic and nongenotoxic chemicals that cause cancer.

Revealing New Analytical Insights into RNA Complexes: Divalent siRNA Characterization by Liquid Chromatography and Mass Spectrometry.

Accurate characterization of therapeutic RNA, including purity and identity, is critical in drug discovery and development. Here, we utilize denaturing and non-denaturing chromatography for the analysis of ∼25 kDa divalent small interfering RNA (di-siRNA), which comprises a complex 2:1 triplex structure. Ion pair reversed-phase (IPRP) liquid chromatography (LC) experiments with UV absorbance and mass spectrometry (MS) showcase a single denaturing LC method for identity confirmation, impurity profiling, and sequencing with automated MS data interpretation. IPRP, size exclusion chromatography (SEC), and melting temperature (Tm) experiments showcase the need for consideration of chromatographic conditions in evaluating noncovalent siRNA structures─here, low-temperature IPRP experiments (generally considered "non-denaturing") indicate denaturation of the noncovalent complex for certain di-siRNA sequences, while SEC data indicate that di-siRNA aggregation can be vastly underestimated due to sample dilution prior to LC experiments. Furthermore, SEC data critically show the propensity of denatured di-siRNA samples to renature under SEC mobile phase conditions upon exposure to high ionic/salt solutions, corroborated by Tm experiments. This work highlights the need for consideration of the noncovalent nature of certain RNA therapeutics during sample preparation, method development, and analytical characterization and the often sequence-specific strength of complex formation, which may significantly affect analytical results obtained for such molecules. Attention to the highly dynamic nature of the duplex RNA structure, which is heavily influenced by its environment, must be considered during analytical method development.

Ophiolite Association in the Rhodope Massif as indicator of the paleogeographical setting

All ophiolite associations mark epochs of active tectonic movements, which lead to significant petrological processes and modification of the relief of the Earth’s crust. Here we present a geological-petrographical characterization of one ophiolitic associations composed of: a) serpentinites; b) amphibolites-metamorphosed volcanic rocks and tuffs; c) metagabbros and metagabbrodiabases, placed among the Proterozoic metamorphic complex in the Rhodope Massif of Bulgaria on the Balkan Peninsula, South-Eastern Europе. The goal is to clarify the paleogeographical and geological setting during its creation. The methods of lithostratigraphic profiling and correlations on the database of geological field mapping were used, supplemented by microscopic, geochemical and isotopic studies of numerous rock samples. The summarized results confirm a certain stratigraphic level of the Ophiolite Association among the metamorphic complex and a complicated and protracted heterogenetic development, which is typical for the ophiolite associations created in eras of closing oceans, opposite movement of tectonic plates, subduction-obduction environment with appearance of autochthonous Neoproterozoic magmatism. Obducted fragments of serpentinites mark an old erosional continental surface, subsequently covered by transgressively deposited pelitic-carbonate sediments. The general conclusion of our study confirms the concept that the metamorphic complex of the Rhodope Massif represents a unified stratigraphic system consisting of two petrographic groups of different ages, with which we oppose the idea of a trust construction, launched by a group of geologists.

A preliminary evaluation of a fast, low-cost, and high-throughput nucleic acid extraction method for bacterial microbiota profiling in low-microbial biomass samples

The respiratory tract is colonized with low-density microbial communities, which have been shown to impact human respiratory health through microbiota–host interactions. However, a lack of fast and cost-effective nucleic acid extraction method for low-microbial biomass samples hinders investigation of respiratory microbiota. Here, we performed a pilot study to assess the suitability of the NAxtra nucleic acid extraction protocol for profiling bacterial microbiota in respiratory samples. A small number of nasopharyngeal aspirate (n = 8), nasal swab (n = 8), and saliva samples (n = 8) were collected, nucleic acids were isolated using the NAxtra protocol, and 16 S rRNA gene sequencing was performed to characterize bacterial microbiota, which were compared to the same sample types from previous studies using other protocols. The bacterial composition in nasal and saliva samples were consistent with previous reports. Saliva microbiota was significantly richer than nasal microbiota and varied less among individual samples than nasal microbiota. Bacterial composition in nasal samples was distinct from nasopharyngeal aspirates, but closer to saliva samples. A sequencing depth of 50,000 reads/sample was sufficient for microbiota profiling in low biomass respiratory samples. Our pilot study indicates the potential of the NAxtra protocol for bacterial microbiota characterization of low-microbial biomass samples and supports a more comprehensive study to fully evaluate the value of the NAxtra protocol in microbiota research and clinical diagnostics of respiratory pathogens.

A combined proteomic and metabolomic analysis of the early aborted embryonic tissues with maternal COVID-19 infection.

COVID-19 still spreads worldwide, and repeated infections are hard to avoid. Maternal infection during pregnancy is associated with adverse maternal and neonatal outcomes. Our study used a multi-omics profiling method to explore the proteome and metabolome alteration in early embryonic development after COVID-19 infection. A total of 30 chorionic tissues after artificial abortion (15 infection and 15 no-infection samples) were collected, and the UHPLC-MS/MS and LC-MS/MS were applied in the present study. As a result, 311 significantly differentially expressed proteins were identified. The function annotations revealed that the thermogenesis pathway is the most significantly enriched signaling pathway; PRKAG2, IGF1R, and RPS6KB2 were identified as the hub proteins. There were 359 metabolites significantly altered after infection. The functional annotations revealed that amino acid metabolism was significantly affected, especially beta-alanine metabolism, glutamate metabolism, and histidine metabolism pathways. The metabolites in ovarian steroidogenesis showed a down-regulating trend in the infection group. Finally, we combined the results of proteins and metabolomics analysis. The biosynthesis of the cofactors pathway was identified as significantly enriched in both proteomics and metabolomics datasets. Our findings provide a network of protein regulation and metabolite perturbation during early embryonic development with COVID-19 infection. Our findings can provide valuable insights for further exploration of the complex mechanism of COVID-19-associated pregnancy complications and outcomes. SIGNIFICANCE: COVID-19 has developed into the most prominent and deadliest pandemic respiratory disease in the world, and repeated infections are complicated to avoid. COVID-19 infection during pregnancy increases the risk of adverse maternal and neonatal outcomes, such as preterm birth and stillbirth. However, previous studies mainly focused on its effect on pregnant women, such as the clinical characteristics and gestation outcomes. There is no relevant report about the effects of virus infection on embryos in early pregnancy. The effects of COVID-19 infection changes of the proteins and metabolites during early embryonic development are undefined. Our findings provide an association between protein regulation, metabolite perturbation, and COVID-19 infection, which can provide valuable insights for further exploration of the complex mechanism COVID-19 COVID-19-associated pregnancy complications and adverse pregnancy outcomes.

Effects of physical exercise on anxiety depression and emotion regulation in children with attention deficit hyperactivity disorder: a systematic review and meta-analysis.

This systematic review and meta-analysis aimed to comprehensively evaluate the impact of physical exercise interventions on anxiety, depression, and emotional regulation in children diagnosed with attention deficit hyperactivity disorder (ADHD). A comprehensive search was conducted across multiple databases, including Embase, Web of Science (WOS), PubMed, The Cochrane Library, Wanfang Data, VIP Information, and China National Knowledge Infrastructure (CNKI), from their inception up to July 2024. The search aimed to identify randomized controlled trials (RCTs) investigating the impact of physical exercise on anxiety, depression, and emotional regulation in children diagnosed with ADHD. The Physiotherapy Evidence Database (PEDro) scale was employed to assess the quality of the literature, while the revised Cochrane risk-of-bias tool (ROB-2) was used to evaluate the overall risk of bias. The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) profiler method was utilized to further assess the quality of evidence. Meta-analysis, sensitivity analysis, and publication bias testing were performed using Stata 18.0 software. Effect sizes were calculated using the standardized mean difference (SMD) and 95% confidence intervals (CI). The analysis included 18 RCTs, encompassing 830 participants. Physical exercise exhibited a significant positive effect on anxiety (SMD = -0.58, p < 0.05), depression (SMD = -0.57, p < 0.05), and emotional regulation (SMD = 1.03, p < 0.05) in children diagnosed with ADHD. Subgroup analysis revealed that exercise programs with monotypic and mixed modalities, short duration, high frequencies, medium duration, and moderate intensities were the most efficacious in ameliorating anxiety symptoms. The mixed exercise program, when conducted for short duration, with low frequencies, medium duration, and moderate intensity was the most effective in alleviating depression symptoms. Exercise programs featuring mixed modalities, longer duration, moderate to high frequencies, shorter duration, and low intensity yielded the most significant improvements in emotional regulation. Research demonstrates that physical exercise mitigates anxiety and depression and improves emotional regulation in children with ADHD. A dose-response relationship is evident, correlating with the type, duration, intensity, frequency, and overall exercise duration. https://www.crd.york.ac.uk/prospero/, PROSPERO identifier (CRD42024571577).

Magnitude and dynamics of the T-cell response to SARS-CoV-2 infection at both individual and population levels.

T cells are involved in the early identification and clearance of viral infections and also support the development of antibodies by B cells. This central role for T cells makes them a desirable target for assessing the immune response to SARS-CoV-2 infection. Here, we combined two high-throughput immune profiling methods to create a quantitative picture of the T-cell response to SARS-CoV-2. First, at the individual level, we deeply characterized 3 acutely infected and 58 recovered COVID-19 subjects by experimentally mapping their CD8 T-cell response through antigen stimulation to 545 Human Leukocyte Antigen (HLA) class I presented viral peptides. Then, at the population level, we performed T-cell repertoire sequencing on 1,815 samples (from 1,521 COVID-19 subjects) as well as 3,500 controls to identify shared "public" T-cell receptors (TCRs) associated with SARS-CoV-2 infection from both CD8 and CD4 T cells. Collectively, our data reveal that CD8 T-cell responses are often driven by a few immunodominant, HLA-restricted epitopes. As expected, the T-cell response to SARS-CoV-2 peaks about one to two weeks after infection and is detectable for at least several months after recovery. As an application of these data, we trained a classifier to diagnose SARS-CoV-2 infection based solely on TCR sequencing from blood samples, and observed, at 99.8% specificity, high early sensitivity soon after diagnosis (Day 3-7 = 85.1% [95% CI = 79.9-89.7]; Day 8-14 = 94.8% [90.7-98.4]) as well as lasting sensitivity after recovery (Day 29+/convalescent = 95.4% [92.1-98.3]). The approaches described in this work provide detailed insights into the adaptive immune response to SARS-CoV-2 infection, and they have potential applications in clinical diagnostics, vaccine development, and monitoring.

Cooperative Optimization Design Method of Multitrajectory Profile in “Well Factory” for Oil and Gas Development

Summary A “well factory” refers to the arrangement of multiple or even a large number of similar wells on the same platform and the drilling and completion of these wells with standardized equipment and a similar operational approach. The well factory mode can effectively handle the challenges posed by complex terrains in oceans and mountainous areas and achieve economical and efficient development of oil and gas resources. Conventional studies mainly focus on the optimization of a single trajectory or the sequential optimization of multiple trajectories. However, there is a lack of cooperative optimization of multiple trajectories, making it difficult to obtain better design results for well trajectories of the well factory mode. Owing to the complicated interdependencies among the design variables of each trajectory (such as the kickoff point, target section length, well inclination, azimuth, and buildup rate), traditional methods struggle to directly address the cooperative optimization problem. This problem involves collaboration and interaction between different trajectories to achieve common objectives and enhance the overall optimization effectiveness. This study established a multitrajectory profile cooperative optimization design model with the objective of minimizing the overall drilling footage, trajectory complexity, trajectory similarity, and collision risk. Next, a cooperative coevolution (CC) approach was introduced and combined with a directed artificial bee colony (DABC) algorithm to develop a collaborative update strategy for multitrajectory optimization. Finally, the CC-DABC algorithm was tested, and a case study was conducted using the new design method. The results indicated that the new method could effectively handle multitrajectory profile cooperative optimization design for various well layouts, including single-layer, multilayer, and extremely small well-spacing scenarios. The CC-DABC algorithm significantly outperformed other combined algorithms in terms of optimization effectiveness, robustness, and overall search efficiency and exhibited excellent performance under small well spacing conditions. In the case study, the trajectories optimized with the new method had less drilling footage and smaller trajectory complexity than the original designs. Additionally, the anticollision risk and staggered arrangement of the kickoff points between adjacent wells effectively met the engineering requirements, demonstrating the application potential of this new method.

Imaged capillary isoelectric focusing and online mass spectrometry for milk whey protein characterization in dairy products.

Characterizing major bovine milk proteins, including whey and casein, is of significant interest in the dairy industry. The diverse array of protein proteoforms can be different in terms of genetic variation, breed ways, lactation stage, and animal nutritional status. Current routine methods for bovine milk protein profiling are typically based on immunological techniques, infrared spectroscopy, slab gel isoelectric focusing, capillary electrophoresis, and high-performance liquid chromatography. However, there are obvious disadvantages of existing approaches including low throughput, tedious operation, unsatisfactory repeatability, and lack of robust quantitation capability. In this study, we present a novel approach that, for the first time, combines imaged capillary isoelectric focusing with mass spectrometry to separate and characterize whey proteins in milk products. The established method provided a rapid, repeatable, accurate, and simultaneous analysis of α-lactalbumin, β-lactoglobulin A, and β-lactoglobulin B within 10min for diverse bovine milk samples. The methodology was systematically validated regarding repeatability of pI and peak area, sensitivity, linearity and recovery. The integration of high-resolution mass spectrometry with nano-electrospray ionization and icIEF has been pivotal in accurately identifying intact whey proteins in milk products. This approach has significantly enhanced the precise characterization of protein proteoforms in milk.

Sub-Microliter 1H Magnetic Resonance Spectroscopy for InVivo High-Spatial Resolution Metabolite Quantification in the Mouse Brain.

Proton magnetic resonance spectroscopy (MRS) offers a non-invasive, repeatable, and reproducible method for invivo metabolite profiling of the brain and other tissues. However, metabolite fingerprinting by MRS requires high signal-to-noise ratios for accurate metabolite quantification, which has traditionally been limited to large volumes of interest, compromising spatial fidelity. In this study, we introduce a new optimized pipeline that combines LASER MRS acquisition at 11.7 T with a cryogenic coil and advanced offline pre- and post-processing. This approach achieves a signal-to-noise ratio sufficient to reliably quantify 19 distinct metabolites in a volume as small as 0.7 μL within the mouse brain. The resulting high spatial resolution and spectral quality enable the identification of distinct metabolite fingerprints in small, specific regions, as demonstrated by characteristic differences in N-acetylaspartate, glutamate, taurine, and myo-inositol between the motor and somatosensory cortices. We demonstrated a decline in taurine and glutamate in the primary motor cortex between 5 and 11 months of age, against the stability of other metabolites. Further exploitation to cortical layer-specific metabolite fingerprinting of layer I-III to layer VI-V in the primary motor cortex, with the latter showing reduced taurine and phosphoethanolamine levels, demonstrates the potential of this pipeline for detailed invivo metabolite fingerprinting of cortical areas and subareas.

DNA Methylation Analysis by Bisulfite Pyrosequencing of Mouse Embryonic Fibroblasts with Reprogramming Enhanced by Thyroid Hormones.

DNA methylation is a widely studied epigenetic mark which in mammals involves the incorporation of a methyl group to the fifth carbon of cytosines, mainly those belonging to CpG dinucleotides. It has been linked to context-dependent regulatory functions ranging from gene and repetitive DNA silencing to gene body transcriptional activity. Because of its important roles during embryonic development and cell differentiation, DNA methylation can be used to track cell reprogramming by measuring the methylation levels of pluripotency-associated factors. In this scenario, bisulfite pyrosequencing is a simple, robust, and widely used technique which allows for the quantification of DNA methylation levels at small, specific regions of the genome. It involves the amplification and biotin tagging of bisulfite-converted DNA. Single amplified strands are then purified using streptavidin and finally pyrosequenced using a sequencing primer. Thus, it is an ideal method for the quantitative profiling of specific genomic regions, with applications ranging from biomarker discovery and epigenetic clock tracking to omic validation studies.

Calculating Sedimentation Rates of Oxic Pelagic Clays Using Core Top Thorium Isotopes

AbstractOxic pelagic clays are an important component of seafloor sediment that may hold valuable information about past ocean chemistry due to their affinity for and accumulation of biogeochemically important metals. We present a new approach to calculating site‐specific sedimentation rates (SRs) by comparing authigenic sediment thorium isotope compositions (230Th/232Th) to seawater dissolved 230Th/232Th in a suite of deep (&gt;3,000 m) pelagic core sites. We extracted the authigenic sediment fraction using an HHAc leach protocol, which major element chemistry (Al, Mn, Fe, Ti) suggested was less affected by lithogenic contamination than the HCl leach. Four different methods were tested for extracting the appropriate initial 230Th/232Th from seawater: using either the nearest water column station (methods 1 and 2) or a regionally averaged profile (methods 3 and 4) and using either the bottommost profile measurement (methods 1 and 3) or linear regression of the profile and extrapolation to the seafloor (methods 2 and 4). Method 3 outperformed the other methods in reconstructing previously published SRs from pelagic clays in the North Pacific. The new thorium‐based SRs were then combined with estimates from the total sediment thickness on ocean crust and non‐lithogenic cobalt accumulation to determine the best estimates for SRs of oxic pelagic clays. The Pacific has the lowest SR (median 0.28 cm/kyr), while the Atlantic is higher (median 0.46 cm/kyr) and the Indian Ocean is highest (median 0.75 cm/kyr). These new estimates are consistent with the expected spatial patterns of sedimentation, but they revise the absolute SR values downward from available gridded SR maps.

3D STED Imaging of Isolated Arabidopsis thaliana Nuclei.

Microscopy imaging of chromatin offers valuable insights into its spatial organization in the nucleus, a novel epigenetic dimension influencing the genome's functions. Particularly, visualization at the nanoscale in single cells is uniquely complementary to molecular profiling methods averaging chromatin configuration and composition over thousands of cells. How are chromatin and chromosomal domains distributed in relation to gene expression? How variable are these configurations? How do chromatin domains evolve in structure, composition, and distribution during cellular differentiation or cellular responses to environmental stimuli? Super-resolution microscopy techniques, like stimulated emission depletion (STED), are key in answering such questions. However, such imaging techniques are not often used in the field of plant cell biology compared to mammalian counterparts, which has greatly advanced our understanding of the 3D principles in genome organization. In an effort to bridge this gap, we provide a clear guide for isolating, embedding, immunostaining, and STED imaging intact leaf nuclei from Arabidopsis thaliana in 3D.