Prior Extraction Research Articles

403-P: Profiling of Circulating MicroRNAs (miRNAs) Associated with Progression to End Stage Kidney Disease (ESKD) in Diabetes—Preanalytical and Analytical Considerations

Background: miRNAs are short non-coding RNA molecules involved in gene regulation. Previously, we identified 17 plasma miRNAs (8 risk and 9 protective miRNAs) associated with progression to ESKD in diabetes (JASN 2021). Factors that influence the measurement of miRNA concentrations, and thus could impact replication of these findings, including extraction method, miRNA profiling method, and the miRNA source biofluid, have not been investigated. Methods: Plasma and serum were obtained from patients who participated in the Joslin Kidney Study. Extraction-free plasma and serum miRNA profiles were obtained using the HTG EdgeSeq platform. RNA was also extracted from plasma and used to measure miRNAs by RNA sequencing (RNASeq) and quantitative RT-PCR (qRT-PCR). Results: Out of 2,083 miRNAs on the EdgeSeq platform, almost all of them (96%) were detected in plasma without RNA extraction, while only 45% of these miRNAs were detected in RNA extracted from the same plasma specimens. The content of miRNAs detected in extracted RNA was significantly enriched for GC sequences in comparison with miRNAs that were lost during RNA extraction. In the specimens with RNA extracted, significantly lower number of miRNAs were detected by RNASeq or qRT-PCR (31% and 26%, respectively) in comparison with the EdgeSeq platform. Regarding the 17 miRNAs associated with ESKD, many of them had different concentrations in serum samples than in plasma and had lower concentration or were not detected in plasma samples with profiled following RNA extraction. Conclusion: This study demonstrates very strong effects of pre-analytical and analytical factors on concentration of circulating miRNAs. To replicate our findings for 17 circulating miRNAs, it is critical that plasma specimens be used and that miRNAs be measured using the EdgeSeq platform or other platforms that do not require prior extraction of RNA. Disclosure E.Satake: None. Z.Md dom: None. H.Kobayashi: Research Support; Bayer Inc. J.Ricca: None. K.O'neil: None. B.Krolewski: None. M.G.Pezzolesi: Research Support; Renalytix. A.Krolewski: None. Funding National Institutes of Health (DK131061-01)

Size and Concentration of Cell-Free DNA Measured Directly from Blood Plasma, without Prior DNA Extraction.

Cell-free DNA in human blood plasma (cfDNA) is now widely used and studied as a biomarker for several physiological and pathological situations. In addition to genetic and epigenetic alterations that provide information about the presence and the nature of non-constitutive DNA in the body, cfDNA concentration and size distribution may potentially be independent biomarkers suitable for monitoring at-risk patients and therapy efficacy. Here, we describe a simple, in-line, method, which measures cfDNA concentration and size distribution from only a few microliters of plasma without the need to extract and/or concentrate the DNA prior to the analysis. This method is based on a dual hydrodynamic and electrokinetic actuation, adapted for samples containing salts and proteins such as biological fluids. The method provides analytical performances equivalent to those obtained after purification and concentration of cfDNA, with a precision of ∼1% for size features and of 10-20% for the concentrations of the different size fractions. We show that concentration and size distribution of cfDNA analyzed from plasma can differentiate advanced lung cancer patients from healthy controls. This simple and cost-effective method should facilitate further investigations into the potential clinical usefulness of cfDNA size profiling.

Ureteral stent extraction strings in children: Stratifying the risk of post operative urinary tract infection

Ureteral stents facilitate recovery and avoid external drains in pediatric ureteral reconstruction. Extraction strings avoid the need for a secondary cystoscopy and anesthetic. Due to concerns regarding febrile UTIs in children with extraction strings, we retrospectively assessed the relative risk of UTI in children with extraction strings. Our hypothesis was that stents with extraction strings do not increase the risk of UTI after pediatric ureteral reconstruction. Records of all children undergoing pyeloplasty and ureteroureterostomy (UU) from 2014 to 2021 were reviewed. The incidences of UTI, fever, and hospitalization were recorded. 245 patients mean age 6.4 years (163M:82F) underwent pyeloplasty (n=221) or UU (n=24). 42% (n=103) received prophylaxis. Of these, 15% developed UTI versus 5% of those not receiving prophylaxis (p<0.05). 42 females had prior history of UTI, compared to 20 males (p<0.05). 49 patients had an extraction string. Stents with extraction strings were removed on average 0.6 months post-op while others underwent cystoscopic removal on average 1.26 months post-op (p<0.05). 9 (18.4%) required hospitalization for febrile UTI while the stent with extraction string was in place, while only 13 (6.6%) of those without extraction string did (p<0.02). Of the 9 children with a febrile UTI in the extraction string group, 6 had history of prior UTI (46.1%), compared to only 3 (8.3%) without a prior UTI (p<0.05). With no prior UTI, there was no difference in UTI risk between those with (3, 8.3%) and without (8, 6.4%) extraction string (p=0.71). Females with prior UTI and extraction string were more likely to develop UTI than those with prior UTI and no extraction string (p=0.01). There were not enough males with history of UTI to analyze alone. There were 5 (10%) stent dislodgements in the extraction string group, 2 required further intervention with cystoscopy or percutaneous drainage. Extraction strings provide the assurance of drainage while avoiding the need for a second general anesthetic procedure. There is not an increased risk of UTI with extraction string in those without prior history of UTI, but we no longer routinely leave extraction strings if there is history of UTI. Children, particularly females, with prior history of UTI have a significantly increased risk of febrile UTIs associated with the use of extraction strings. Prophylaxis does not seem to reduce this risk. Patients with no prior UTI had no higher risk of UTI with extraction string use for pyeloplasty or UU.

Simultaneous determination of paracetamol and codeine phosphate in pharmaceuticals using molecular absorption spectroscopy and classical least squares method

In this article, a combined method of molecular absorption spectroscopy and classical least squares is used to simultaneously determine paracetamol (PAR) and codeine phosphate (COP) in pharmaceutical samples without the need for prior separation or extraction steps. The absorption spectra of standard solutions and samples were measured in the wavelength range of 210 to 290 nm with a step size of 0.5 nm. The concentrations of PAR and COP in the sample solutions were calculated using a self-made program written in Microsoft Excel 2016 and Visual Basic for Applications (VBA). The reliability of the method was verified through the accuracy and reproducibility of the measurements when analyzing PAR and COP in Effer-Paralmax® Codeine tablets, and comparing the average values of their concentrations in the samples with the standard HPLC method.

Rapid Detection of Benzo[a]pyrene in Extra Virgin Olive Oil Using Fluorescence Spectroscopy.

Extra virgin olive oil (EVOO) should be naturally free of polycyclic aromatic hydrocarbon (PAH) contamination. PAHs are carcinogenic and toxic, and may cause human health and safety problems. This work aims to detect benzo[a]pyrene residues in EVOO using an easily adaptive optical methodology. This approach, which is based on fluorescence spectroscopy, does not require any sample pretreatment or prior extraction of PAH content from the sample, and is reported for the first time herein. The detection of benzo[a]pyrene even at low concentrations in extra virgin olive oil samples demonstrates fluorescence spectroscopy's capability to ensure food safety.

A prior knowledge-driven reference signal extraction network towards measured data in DRM-based passive radar

We propose a novel intelligent reference signal extraction system for DRM-based passive radar. By fully using prior knowledge of the received signal, a pilot conditional reference signal extraction network (PCRSENet) is designed to replace both conventional channel estimation and signal equalization. The PCRSENet estimates the channel state information (CSI) implicitly and outputs reference signals directly. Meanwhile, what makes it challenging to utilize deep learning in reference signal extraction of passive radar is not only the limited measured data but also the truth transmission signals and CSI being unknown. So, the least square (LS) estimator-aided training sets generation method is employed, which obtains the CSI from measured data by LS estimator as prior knowledge and then simulates DRM signals as accurate labels of training sets. We evaluate the proposed method on measured data, and the experimental results show that the proposed method works effectively for target detection in DRM-based passive radar with different working parameters when the training and test sets are in the same transmission mode.

Prior metabolite extraction fully preserves RNAseq quality and enables integrative multi-‘omics analysis of the liver metabolic response to viral infection

ABSTRACT Here, we provide an in-depth analysis of the usefulness of single-sample metabolite/RNA extraction for multi-‘omics readout. Using pulverized frozen livers of mice injected with lymphocytic choriomeningitis virus (LCMV) or vehicle (Veh), we isolated RNA prior (RNA) or following metabolite extraction (MetRNA). RNA sequencing (RNAseq) data were evaluated for differential expression analysis and dispersion, and differential metabolite abundance was determined. Both RNA and MetRNA clustered together by principal component analysis, indicating that inter-individual differences were the largest source of variance. Over 85% of LCMV versus Veh differentially expressed genes were shared between extraction methods, with the remaining 15% evenly and randomly divided between groups. Differentially expressed genes unique to the extraction method were attributed to randomness around the 0.05 FDR cut-off and stochastic changes in variance and mean expression. In addition, analysis using the mean absolute difference showed no difference in the dispersion of transcripts between extraction methods. Altogether, our data show that prior metabolite extraction preserves RNAseq data quality, which enables us to confidently perform integrated pathway enrichment analysis on metabolomics and RNAseq data from a single sample. This analysis revealed pyrimidine metabolism as the most LCMV-impacted pathway. Combined analysis of genes and metabolites in the pathway exposed a pattern in the degradation of pyrimidine nucleotides leading to uracil generation. In support of this, uracil was among the most differentially abundant metabolites in serum upon LCMV infection. Our data suggest that hepatic uracil export is a novel phenotypic feature of acute infection and highlight the usefulness of our integrated single-sample multi-‘omics approach.

68Ga-Prostate-Specific Membrane Antigen PET Radiomics For the Prediction of PostSurgical International Society of Urological Pathology Grade in Patients with Primary Prostate Cancer

INTRODUCTION Radiomics has been proven effective for the characterisation of primary prostate cancer (PCa).1,2 However, the limited interpretability of the proposed models represents one of the major limitations in this field.3,4 This study investigated 68Ga-prostate-specific membrane antigen (PSMA) PET radiomics for the prediction of post-surgical International Society of Urological Pathology (ISUP) grade in patients with primary PCa, ensuring model interpretability. MATERIALS AND METHODS Forty-seven patients with PCa were examined with 68Ga-PSMA PET at the authors’ institution. Those patients were enrolled in this study prior to radical prostatectomy. Images were acquired using either PET/MRI or PET/CT. ISUP grade was available at both biopsy and radical prostatectomy for all patients. A radiologist manually segmented the whole prostate on PET images using the co-registered CT or MRI for anatomical localisation on 3D Slicer software (Brigham and Women’s Hospital, Boston, Massachusetts, USA).5 The whole prostate was used as volume of interest (VOI) to avoid the limitations of radiomics for small volumes.6 VOIs were normalised, resampled, and discretised. A total of 103 image biomarker standardisation initiative-compliant, radiomic features (RF) were extracted using PyRadiomics (Python Software Foundation, Beaverton, Oregon, USA).7 RFs were harmonised with the ComBat method8 to control for the scanner effect, and selected using the minimum redundancy maximum relevance algorithm. Combinations of the four most relevant RFs were used to train 12 radiomics machine learning models for the prediction of post-surgical ISUP ≥4 versus ISUP &lt;4 that were validated by five-fold repeated stratified cross-validation. To ensure that results were not driven by spurious associations, two ad hoc control models were generated. The first one Creative Commons Attribution-Non Commercial 4.0 ● April 2023 ● Urology 37 EAU 2023 • Abstract had SUVmax and VOI volume as input (radiomics baseline), while the other was made by setting to zero all voxel values prior features extraction (PET zeros). Balanced accuracy, sensitivity, specificity, and positive and negative predictive values were collected. The performance of the best developed model was compared with that of ISUP grade biopsy. RESULTS ISUP grade at biopsy was upgraded in 9 out of 47 patients after prostatectomy, resulting in a balanced accuracy of 85.9%; sensitivity of 71.9%; specificity of 100.0%; positive predicted value of 100.0%; and negative predictive value of 62.5%. The best performing radiomic model yielded a balanced accuracy of 87.6%; sensitivity of 88.6%; specificity of 86.7%; positive predicted value of 94.0%; and negative predicted value of 82.5%. All radiomic models trained with at least two RFs (grey level size zone matrix; zone entropy and shape; least axis length) outperformed the control models. Conversely, no significant differences were found for radiomic models trained with two or more RFs (Mann–Whitney U test; p&gt;0.05). See Table 1 for a detailed report of all the generated models’ performance. CONCLUSION These findings support the role of 68Ga-PSMA PET radiomics for the accurate and non-invasive prediction of post-surgical ISUP grade. Future multicentre studies will be needed to establish with certainty the accuracy and reproducibility of the radiomic signature proposed here.

Fabrication of novel electropolymerized conductive polymer of hydrophobic perfluorinated aniline as transducer layer on glassy carbon electrode: application to midazolam as a model drug of benzodiazepines

The objective of this study is to fabricate solid-contact ion selective electrodes (SC-ISEs) that have long term stable potential. Various conducting polymers such as polyaniline and its derivatives have been successfully employed to improve the potential stability in SC-ISEs. Recently, the role of hydrophobicity at the interface between the conducting polymer solid contact and the ion sensing membrane has been investigated and figured out that the hydrophobic interfaces preclude water layer formation that deteriorate the SC-ISEs potential stability and reproducibility. In this work, a hydrophobic polyaniline derivative was fabricated on the surface of a glassy carbon electrode by electropolymerization of perfluorinated aniline monomers in acidic solution. The electropolymerized hydrophobic polymer was characterized by electrochemical impedance spectroscopy and X-ray photoelectron spectroscopy. The fabricated electrode was employed for determination of midazolam—a model drug-in pharmaceutical formulation without prior extraction. The SC-ISEs performance was optimized, and the potential drift was compared to control SC-ISEs, the SC-ISE linear range was 1 × 10–6–1 × 10–2 M, LOD was estimated to be 9.0 × 10–7 M, and potential drift was reduced to 100 μV/h.

A Robust Feature Extraction Method for Underwater Acoustic Target Recognition Based on Multi-Task Learning

Target classification and recognition have always been complex problems in underwater acoustic signal processing because of noise interference and feature instability. In this paper, a robust feature extraction method based on multi-task learning is proposed, which provides an effective solution. Firstly, an MLP-based network model suitable for underwater acoustic signal processing is proposed to optimize feature extraction. Then, multi-task learning is deployed on the model in hard parameter-sharing so that the model can extract anti-noise interference features and embed prior feature extraction knowledge. In the model training stage, the simultaneous training method enables the model to improve the robustness and representation of classification features with the knowledge of different tasks. Furthermore, the optimized classification features are sent to the classification network to complete target recognition. The proposed method is evaluated by the dataset collected in the real environment. The results show that the proposed method effectively improves recognition accuracy and maintains high performance under different noise levels, which is better than popular methods.

Mild isolation and characterization of surface lignin from hydrothermally pretreated lignocellulosic forestry and agro-industrial waste biomass

Within the biorefining concept, the lignocellulosic biomass wastes can serve as feedstock to produce value-added chemicals and fuels. The sustainable valorization of biomass is based on integrated processes that aim to the utilization of “whole biomass”. To this end, the first step of the efficient biomass pretreatment towards selective isolation of cellulose, hemicellulose and lignin, is of paramount importance. Hydrothermal pretreatment of biomass in neat water is a green and well-established process that enhances hemicellulose removal and recovery in the liquid fraction, affording a cellulose and lignin enriched solid which can be enzymatically hydrolyzed to glucose. A simple and efficient method to facilitate the hydrolysis is the prior extraction of the formed “surface” lignin which hinders the action of enzymes. Within this context, in this work, forestry (beechwood sawdust) and agro-industrial (vine prunings, apricot kernel shells) wastes were hydrothermally pretreated in neat water (at 220 °C, 15 min) and the formed surface lignin was extracted via soxhlet or reflux methods under mild conditions, with the use of green solvents (ethanol, acetone). The delignification degree of the pretreated biomass was in the range of 35–67 wt%, depending on the solvent and biomass feedstock. The recovered surface lignins were of high purity and exhibited similar physicochemical and structural characteristics with the organosolv lignin. The fast pyrolysis of surface lignins afforded bio-oils enriched in alkoxy-phenols and oxy-aromatics. The biomass solids recovered after lignin extraction are enriched in cellulose (70%) and exhibit high relative crystallinity and improved textural properties, thus increasing their potential valorization.

Earth Mantle's Isotopic Record of Progressive Chemical Depletion

AbstractMid ocean ridge basalts are partial melts of mantle rocks that have become incompatible element depleted prior to recent sub‐ridge melting. This prior extent of melt extraction and concomitant incompatible element depletion is often inferred from the radiogenic isotope ratios of ridge basalts, such as hafnium and neodymium. However, hafnium isotope ratios by far exceeding those in ridge basalts are observed sporadically in exposed mantle rocks, abyssal peridotites. At least locally, therefore, Earth's mantle has evolved with much larger extents of incompatible element depletion over geologic time periods (108–109 years) than inferred from ridge basalts. Here we show that such “ultra‐depleted” hafnium isotope signatures also characterize peridotites exposed at the Doldrums Fracture Zone in the equatorial Mid Atlantic. These peridotites are closely associated with peridotites characterized by hafnium‐neodymium isotope ratios similar to ridge basalts, but extensive incompatible element depletion. Our results demonstrate that Earth mantle's isotopic record of prior melt extraction is dampened by ubiquitous past and recent reaction with migrating melts. Hence, a better understanding of chemically reactive flow is required for deducing the mantle's rate of incompatible element depletion by recurring processing through melting regions in the shallow mantle, which is the driving force for silicate Earth evolution. Ultimately, better constraining the rate of incompatible element depletion from Earth's mantle is therefore of first‐order importance for understanding our planet's basic mode of operation.

Human Milk: Fast Determination of Docosahexaenoic Acid (DHA)

Human milk provides all the nutrients required by babies during the first six months of their life. Human milk lipids represent the main source of energy, contributing almost 50% of the total energy content. Additionally, fatty acids ensure the correct development of children in the prenatal, postnatal, and infant phases. Docosahexaenoic acid (DHA) is essential for visual and cognitive development, and its presence during childhood can affect long-term health. This study aimed to optimize and validate a methodology for the direct determination of DHA in human milk. We used 20 samples of human milk from lactating women living in the city of Itu, São Paulo, who attended Basic Health Units from September 2019 to September 2020, and a sample of certified reference material from the National Institute of Standards and Technology. The proposed methodology consists of a validated mixed transesterification process without prior lipid extraction, optimized by factorial design. This methodology can be successfully used in human milk samples as it is both precise and accurate. The values of DHA in the sampled milks were similar to those in European countries and lower than those in Asian countries due to diet.

Corneal Higher-Order Aberrations Measurements: Precision of SD-OCT/Placido Topography and Comparison with a Scheimpflug/Placido Topography in Eyes After Small-Incision Lenticule Extraction.

The aim of this study was to evaluate the measurements of corneal higher-order aberrations (HOAs) obtained by a new anterior segment optical coherence tomography (OCT) technique combined with a Placido topographer (the MS-39 device) in eyes with prior small-incision lenticule extraction (SMILE) and compare them to the measurements obtained by a Scheimpflug camera combined with a Placido topographer (the Sirius device). A total of 56 eyes (56 patients) were included in this prospective study. Corneal aberrations were analyzed for the anterior, posterior, and total cornea surfaces. Within-subject standard deviation (Sw), test-retest repeatability (TRT), and intraclass correlation coefficient (ICC) were used to assess the intraobserver repeatability and interobserver reproducibility. The differences were evaluated by paired t-test. Bland-Altman plots and 95% limits of agreement (95% LoA) were used to evaluate the agreement. High repeatability was observed for anterior and total corneal parameters, with Sw value < 0.07, TRT ≤ 0.16, and ICCs > 0.893, but not trefoil. For the posterior corneal parameters, ICCs varied from 0.088 to 0.966. Regarding interobserver reproducibility, all Sw values were ≤ 0.04 and TRT ≤ 0.11. ICCs ranged from 0.846 to 0.989, from 0.432 to 0.972, and from 0.798 to 0.985 for the anterior, total, and posterior corneal aberrations parameters, respectively. The mean difference in all aberrations was ≤ 0.05μm. All parameters showed a narrow 95% LoA. The MS-39 device achieved high precision in both anterior and total corneal measurements; the precision of posterior corneal higher-order RMS, astigmatism II, coma, and trefoil was lower. The two technologies used by the MS-39 and Sirius devices can be used interchangeably for measuring corneal HOAs after SMILE.

MOJI: Character-level convolutional neural networks for Malicious Obfuscated JavaScript Inspection

JavaScript malware is one of the major threats to web security. A big challenge in detecting such malicious JavaScript is obfuscation, which transforms a program code into a harder-to-understand representation while preserving its original functionality. Many malicious JavaScript detection methods perform code abstraction and prior feature extraction to uncover the functionality hidden by obfuscation. However, such preprocessing steps significantly limit the detectors’ efficiency in practical situations. This paper presents Malicious Obfuscated JavaScript Inspector (MOJI), a novel method for malicious JavaScript detection, which requires no code abstraction or prior feature extraction. Instead, our detector directly accepts a sequence of characters in JavaScript code as an input and outputs its maliciousness score. Specifically, we design a character-level convolutional neural network consisting mainly of several 1D convolutional layers and fully connected layers. We evaluate the proposed method on a dataset composed of 24,000 JavaScript codes and show that our method outperforms existing malicious JavaScript detectors in terms of both detection performance and running time. We also provide an analysis of the effect of additional obfuscation on the same dataset. Our results indicate that MOJI is far more robust to obfuscation than the existing methods and commercial antivirus software.

Arterial blood gases in newborn infants: Early extraction without prior clamping versus extraction after delayed clamping

ObjectivesTo compare the postpartum arterial blood gas parameters recorded early before cord clamping and after delayed cord clamping (DCC). To explore adverse effects and complications of the cord blood gas collection technique without clamping. DesignRandomised controlled trial. SettingBirthing room of La Ribera University Hospital (Valencia, Spain). Participants122 full-term infants born between February 2020 and January 2021. Two groups were established: the experimental group (early sampling prior to clamping and sampling again after DCC) and the non-experimental group (sampling only after DCC). Measurements and findingsThe comparison of arterial blood gas parameters was made using the Student t-test, while the Fisher's exact test was used to compare the proportion of the adverse effects recorded. The pH and base excess values in the experimental group were significantly greater when the sampling was performed without prior clamping. No statistically significant differences were observed in relation to pCO2 or the appearance of adverse effects between the two groups. No complications were recorded. Key conclusions and implications for practiceThe pH and base excess values were higher when the arterial blood gas measurements were made prior to performing the umbilical cord clamping than when the sampling was performed after the DCC. Arterial blood gas sampling without prior clamping was found to be safe, since no complications or increased adverse effects were observed. The use of this technique is therefore advised in normal births of full-term infants.

Image-based biomass characterization: Comparison of conventional image processing and a deep learning approach

Due to the increased use of inconsistent low-grade biogenic solid fuels and simultaneously stricter regulatory limitations for biomass combustion, there is a rising demand for suitable methods for an online characterization of fuels to allow for optimal plant operation. Aim of this work is to evaluate two camera-based machine vision approaches using a conventional feature extraction method based classification and a deep learning approach with a convolutional neural network (CNN) to distinguish six types of biogenic solid fuels and 20 fuel mixtures thereof. A comparison of four machine-learning algorithms applied to classify the samples based on all extracted color and texture features reaches a prediction accuracy of 93.5%. An evaluation of the feature performance of single features shows that the selected color features (color thresholds and histogram-based features) are more relevant for distinguishing the fuels than the textural features (Haralick features and features extracted from the frequency domain). Despite the small size of the image dataset, also the CNN achieves a good prediction accuracy of 73.7% for the given classification task. An increase of the number of images by fragmentation leads to a slightly increasing prediction accuracy for the deep learning approach while the accuracy of the conventional features learning approach decreases. Both approaches are suitable to distinguish six typical biogenic solid fuels and achieve high accuracies for the classification of 26 fuels and mixtures. While the feature learning is more accurate for the mentioned classification task, the CNN does not require prior feature extraction and would benefit from a larger dataset. These are promising results for an implementation as an online fuel monitoring in various applications, with further development in the robustness and extensions by means of a broader range of fuel mixtures being required.

Garlic bulb classification by combining Raman spectroscopy and machine learning

The purpose of this study was to demonstrate the utility of combining Raman spectroscopy with machine learning techniques for achieving origin traceability of five garlic bulb species. We collected Raman spectra of garlic bulbs and Raman bands are assigned. After pre-processing, the wavenumbers and intensities of distinct Raman peaks are extracted as the input data for developing the classification model. Our trained model presents an accuracy of 98.97%, a precision of 98.92% and a sensitivity of 98.86%. The results indicate that the artificial prior feature extraction strategy prevents over-fitting due to external variables and improves greatly model accuracy. This study offers a novel classification and origin identification scheme for plant bulbs.

Removal of a leadless pacemaker using a 2.5cc syringe and silk thread during surgical treatment of infective endocarditis

Removal of a leadless pacemaker using a 2.5cc syringe and silk thread during surgical treatment of infective endocarditis

Multi-omics analyses from a single sample: prior metabolite extraction does not alter the 16S rRNA-based characterization of prokaryotic community in a diversity of sample types.

Massive sequencing of the 16S rRNA gene has become a standard first step to describe and compare microbial communities from various samples. Parallel analysis of high numbers of samples makes it relevant to the statistical testing of the influence of natural or experimental factors and variables. However, these descriptions fail to document changes in community or ecosystem functioning. Nontargeted metabolomics are a suitable tool to bridge this gap, yet extraction protocols are different. In this study, prokaryotic community compositions are documented by 16S rRNA gene sequencing after direct DNA extraction or after metabolites extraction followed by DNA extraction. Results obtained using the V3-V4 region on nonaxenic cultures of cyanobacteria, lake water column, biofilm, and gut of wild and lab-reared fish indicate that prior extraction of metabolites does not influence the obtained image of prokaryotic communities. This validates sequential extraction of metabolites followed by DNA as a way to combine 16S rRNA sequencing with metabolome characterization from a single sample. This approach has the potential to complement community structure characterization with a proxy of their functioning, without the uncertainties associated with the use of separate samples.