Brain tumor diagnostic model and dietary effect based on extracellular vesicle microbiome data in serum

The human microbiome has been recently associated with human health and disease. Brain tumors (BTs) are a particularly difficult condition to directly link to the microbiome, as microorganisms cannot generally cross the blood–brain barrier (BBB). However, some nanosized extracellular vesicles (EVs) released from microorganisms can cross the BBB and enter the brain. Therefore, we conducted metagenomic analysis of microbial EVs in both serum (152 BT patients and 198 healthy controls (HC)) and brain tissue (5 BT patients and 5 HC) samples based on the V3–V4 regions of 16S rDNA. We then developed diagnostic models through logistic regression and machine learning algorithms using serum EV metagenomic data to assess the ability of various dietary supplements to reduce BT risk in vivo. Models incorporating the stepwise method and the linear discriminant analysis effect size (LEfSe) method yielded 12 and 29 significant genera as potential biomarkers, respectively. Models using the selected biomarkers yielded areas under the curves (AUCs) >0.93, and the model using machine learning resulted in an AUC of 0.99. In addition, Dialister and [Eubacterium] rectale were significantly lower in both blood and tissue samples of BT patients than in those of HCs. In vivo tests showed that BT risk was decreased through the addition of sorghum, brown rice oil, and garlic but conversely increased by the addition of bellflower and pear. In conclusion, serum EV metagenomics shows promise as a rich data source for highly accurate detection of BT risk, and several foods have potential for mitigating BT risk.Subject terms: Diagnostic markers, Machine learning     

Pyrosequencing‐based strategy for a successful SNP detection in two hypervariable regions: HV‐I/HV‐II of the human mitochondrial displacement loop

Forensic analysis of mitochondrial displacement loop (D‐loop) sequences using Sanger sequencing or SNP detection by minisequencing is well established. Pyrosequencing has become an important alternative because it enables high‐throughput analysis and the quantification of individual mitochondrial DNAs (mtDNAs) in samples originating from more than one individual. DNA typing of the mitochondrial D‐loop region is usually the method of choice if STR analysis fails because of trace amounts of DNA and/or extensive degradation. The main aim of the present work was to optimize the efficiency of pyrosequencing. To do this, 31 SNPs within the hypervariable regions I and II of the D‐loop of human mtDNA were simultaneously analyzed. As a novel approach, we applied two sets of amplification primers for the multiplexing assay. These went in combination with four sequencing primers for pyrosequencing. This method was compared with conventional sequencing of mtDNA from blood and biological trace materials.     

The analysis of uranium-232: comparison of radiochemical techniques and an improved method by alpha spectrometry

Uranium-232 is an isotope of interest for nuclear forensic studies because it can provide information on the irradiation history of a sample of uranium. The isotope is formed in uranium materials through several pathways and is typically found at ultra-trace levels (usually ng/g or smaller) in typical uranium materials. The low abundance of this isotope in irradiated materials makes it very difficult to measure accurately and precisely. Many different methods have been proposed for the analysis of ²³²U using radiochemical methods including alpha and gamma spectrometry. In this paper, literature methods will be discussed and an improved method using alpha spectrometry will be presented. Alpha spectrometry offers a direct analysis technique for measuring ²³²U, with few interferences that can be removed via separations. Results from our improved method will be presented and compared to results obtained from a non-destructive gamma spectrometry method that utilizes an indirect measurement. LA-UR-12-20186.     

Strategies for Natural Products Discovery from Uncultured Microorganisms

Microorganisms are highly regarded as a prominent source of natural products that have significant importance in many fields such as medicine, farming, environmental safety, and material production. Due to this, only tiny amounts of microorganisms can be cultivated under standard laboratory conditions, and the bulk of microorganisms in the ecosystems are still unidentified, which restricts our knowledge of uncultured microbial metabolism. However, they could hypothetically provide a large collection of innovative natural products. Culture-independent metagenomics study has the ability to address core questions in the potential of NP production by cloning and analysis of microbial DNA derived directly from environmental samples. Latest advancements in next generation sequencing and genetic engineering tools for genome assembly have broadened the scope of metagenomics to offer perspectives into the life of uncultured microorganisms. In this review, we cover the methods of metagenomic library construction, and heterologous expression for the exploration and development of the environmental metabolome and focus on the function-based metagenomics, sequencing-based metagenomics, and single-cell metagenomics of uncultured microorganisms.     

Determination of the Nanostructure of Polymer Materials by Electron Paramagnetic Resonance Spectroscopy

Electron paramagnetic resonance (EPR) spectroscopy is one the few methods that can characterize structural features in the range between 0.5 and 5 nm in systems that lack long‐range order. Approaches based on EPR spectroscopy provide good structural contrast even in complex materials, as the sites of interest can be selectively labeled or addressed by suitably functionalized spin probes using well established techniques. This article assesses the EPR experiments available for distance measurements on nanoscales in terms of the accessible distance range, precision, and sensitivity. Recommendations are derived for the proper choice of experiment for a given problem. Both simple and sophisticated methods for data analysis are described and their limitations are evaluated. It is discussed which assumptions must be made to extract a pair correlation function from EPR data. Finally, applications to the study of polymer chain conformation and the structure of ionically functionalized diblock copolymers are highlighted.     

Comparison of thrombus,gut, and oral microbiomes in Korean patients with ST-elevation myocardial infarction: a case–control study

ST-segment elevation myocardial infarction (STEMI) is characterized by thrombotic coronary artery occlusions caused by atherosclerotic plaque rupture. The gut microbiome potentially contributes to the pathogenesis of coronary artery diseases. This study investigated the microbial diversity and composition of coronary thrombi in STEMI patients and the composition of the thrombus microbiome relative to that of the oral and gut microbiomes. A case–control study was performed with 22 STEMI patients and 20 age- and sex-matched healthy controls. Coronary thrombi were acquired from STEMI patients via manual thrombus aspiration during primary coronary intervention. Oral swab and stool samples were collected from both groups, and 16S rRNA sequencing and metagenomic microbiome analyses were performed. Microbial DNA was detected in 4 of 22 coronary thrombi. Proteobacteria (p) and Bacteroidetes (p) were the most abundant phyla. The oral and gut microbiomes significantly differed between patients and healthy controls. The patient group presented microbial dysbiosis, as follows: a higher relative abundance of Proteobacteria (p) and Enterobacteriaceae (f) in the gut microbiome and a lower abundance of Firmicutes (p) and Haemophilus (g) in the oral microbiome. Furthermore, 4 significantly abundant genera were observed in the coronary thrombus in the patients: Escherichia, 1.25%; Parabacteroides, 0.25%; Christensenella, 0.0%; and Bacteroides, 7.48%. The present results indicate that the relative abundance of the gut and oral microbiomes was correlated with that of the thrombus microbiome.Subject terms: Genetics research, Myocardial infarction     

Laser induced breakdown spectroscopy as a tool for discrimination of glass for forensic applications

Materials analysis and characterization can provide important information as evidence in legal proceedings. The potential of laser induced breakdown spectroscopy (LIBS) for the discrimination of glass fragments for forensic applications is presented here. The proposed method is based on the fact that glass materials can be characterized by their unique spectral fingerprint. Taking advantage of the multielement detection capability and minimal to no sample preparation of LIBS, we compared glass spectra from car windows using linear and rank correlation methods. Linear correlation combined with the use of a spectral mask, which eliminates some high-intensity emission lines from the major elements present in glass, provides effective identification and discrimination at a 95% confidence level.     

Building a biological space based on protein sequence similarities and biological ontologies

Assignment of function to protein sequence is a task of growing importance in the life sciences, as new high-throughput sequencing DNA technologies generate ever increasing quantities of genomic and meta-genomic data. Patterns within the sequence space, caused by the evolutionary conservation and assembly of protein domains, make possible the inference of function from sequence similarity. Clustering similar sequences is a useful technique for finding conserved sequences; the CluSTr database is a publicly-available database arranging proteins in a hierarchy structured by similarity. The protein classification tool InterProScan builds on this approach by applying a range of methods to detect proteins that contain signatures indicative of the presence of particular conserved domains. The use of ontologies to describe protein function provides a flexible and abstract language to classify proteins. Together, these techniques can provide an understanding of the shape of the protein space, and can be used to explore the unchartered waters of the emerging metagenomic world.     

The Raw Milk Microbiota from Semi-Subsistence Farms Characteristics by NGS Analysis Method

The aim of this study was to analyze the microbiome of raw milk obtained from three semi-subsistence farms (A, B, and C) located in the Kuyavian-Pomeranian Voivodeship in Poland. The composition of drinking milk was assessed on the basis of 16S rRNA gene sequencing using the Ion Torrent platform. Based on the conducted research, significant changes in the composition of the milk microbiome were found depending on its place of origin. Bacteria belonging to the Bacillus (17.0%), Corynebacterium (12.0%) and Escherichia-Shigella (11.0%) genera were dominant in the milk collected from farm A. In the case of the milk from farm B, the dominant bacteria belonged to the Acinetobacter genus (21.0%), whereas in the sample from farm C, Escherichia-Shigella (24.8%) and Bacillus (10.3%) dominated the microbiome. An analysis was performed using the PICRUSt tool (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) in order to generate a profile of genes responsible for bacterial metabolism. The conducted analysis confirmed the diversity of the profile of genes responsible for bacterial metabolism in all the tested samples. On the other hand, simultaneous analysis of six KEGG Orthologs (KO), which participated in beta-lactam resistance responsible for antibiotic resistance of bacteria, demonstrated that there is no significant relationship between the predicted occurrence of these orthologs and the place of existence of microorganisms. Therefore, it can be supposed that bacterial resistance to beta-lactam antibiotics occurs regardless of the environmental niche, and that the antibiotic resistance maintained in the population is a factor that shapes the functional structure of the microbial consortia.     

Novel liquid-chromatography columns for proteomics research

The enormous interest in proteomics research in recent years has inspired many developments in peptide chromatography. Different strategies have been developed to cope with the vast complexity of proteomics samples, trying to provide sufficient degree of separation to be able to exploit fully the potential of protein identification by mass spectrometry (MS). As reversed-phase liquid chromatography (RPLC) coupled to MS is still the method of choice for the analysis of protein digests, many efforts focus on the development of high-efficiency RP methods (e.g., monolithic columns and ultra-high-performance LC). This can also increase the speed and the sensitivity of the analysis of protein digests.As RPLC-MS alone is unlikely to provide sufficient resolution to unravel the composition of highly complex samples comprehensively, multidimensional methods will remain essential in proteome research. In this area, hydrophilic interaction chromatography (HILIC) seems to be a promising alternative to the traditional strong cation-exchange-based methods. Also, HILIC has found application in the analysis of post-translational modifications (e.g., phosphorylation and glycosylation).This review describes recent developments in LC methods for proteomics research, focusing on advances in column technology and the application of novel column materials. Illustrative examples show the possibilities of the new columns in proteomics research.     

Current perspectives and recommendations for the development of mass spectrometry methods for the determination of allergens in foods

Allergen detection and quantification is an essential part of allergen management as practiced by food manufacturers. Recently, protein MS methods (in particular, multiple reaction monitoring experiments) have begun to be adopted by the allergen detection community to provide an alternative technique to ELISA and PCR methods. MS analysis of proteins in foods provides additional challenges to the analyst, both in terms of experimental design and methodology: (1) choice of analyte, including multiplexing to simultaneously detect several biologically relevant molecules able to trigger allergic reactions; (2) choice of processing stable peptide markers for different target analytes that should be placed in publicly available databases; (3) markers allowing quantification (e.g., through standard addition or isotopically labeled peptide standards); (4) optimization of protease digestion protocols to ensure reproducible and robust method development; and (5) effective validation of methods and harmonization of results through the use of naturally incurred reference materials spanning several types of food matrix.     

Evaluation of energy efficiency fitting functions for HPGe detectors

Numerous and diverse mathematical methods have been used to model the full-energy photopeak (FEP) efficiency-to-energy relationship. All of the methods attempt to approximate this relationship using numerical analysis methods. Sophistication of the mathematics does not guarantee a meaningful and accurate determination of the physical relationships being modeled. This discrepancy stems from the fact that the data being modeled may suffer from spectral and nuclear effects which alter the counts in the full energy photopeak resulting from absorption and attenuation in the active volume of the diode, in the intervening materials between the detector diode and source, within the source itself, and in the shielding around the detector and source. Data must be free of these effects either as a result of acquiring the spectral data in geometries which minimize or eliminate these effects, or by pre-treatment of the net area counts to correct for these effects. If these corrections are not possible, then the choice of mathematical fitting method should be constrained to provide results which are consistent with physical-theoretical considerations of the energy-efficiency relationship being modeled. If possible, the method chosen should also provide a meaningful estimate of the uncertainty associated with the approximation of this function.     

PCR technology for screening and quantification of genetically modified organisms (GMOs)

Although PCR technology has obvious limitations, the potentially high degree of sensitivity and specificity explains why it has been the first choice of most analytical laboratories interested in detection of genetically modified (GM) organisms (GMOs) and derived materials. Because the products that laboratories receive for analysis are often processed and refined, the quality and quantity of target analyte (e.g. protein or DNA) frequently challenges the sensitivity of any detection method. Among the currently available methods, PCR methods are generally accepted as the most sensitive and reliable methods for detection of GM-derived material in routine applications.The choice of target sequence motif is the single most important factor controlling the specificity of the PCR method. The target sequence is normally a part of the modified gene construct, for example a promoter, a terminator, a gene, or a junction between two of these elements. However, the elements may originate from wildtype organisms, they may be present in more than one GMO, and their copy number may also vary from one GMO to another. They may even be combined in a similar way in more than one GMO. Thus, the choice of method should fit the purpose. Recent developments include event-specific methods, particularly useful for identification and quantification of GM content. Thresholds for labelling are now in place in many countries including those in the European Union. The success of the labelling schemes is dependent upon the efficiency with which GM-derived material can be detected. We will present an overview of currently available PCR methods for screening and quantification of GM-derived DNA, and discuss their applicability and limitations. In addition, we will discuss some of the major challenges related to determination of the limits of detection (LOD) and quantification (LOQ), and to validation of methods.     

Imaging the morphology of solvent-free prepared MALDI samples

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry is an important technique to characterize many different materials, including synthetic polymers. MALDI mass spectral data can be used to determine the polymer average molecular weights, repeat units, and end groups. The development of solvent-free sample preparation methods has enabled MALDI to analyze insoluble materials and, interestingly, can provide higher-quality mass spectral data. Although the utility of solvent-free sample preparation for MALDI has been demonstrated, the reasons for its success are only now being discovered. In this study, we use microscopy tools to image samples prepared using solvent-free methods to examine the morphology of these samples. The samples are prepared using a simple vortex method. Our results show that the average particle size of typical MALDI matrices is reduced from their original tens to hundreds of micrometers to hundreds of nanometers. This size reduction of the matrix occurs in one minute using the vortex method. We also observe remarkably smooth and homogeneous sample morphologies for the laser to interrogate, especially considering the relatively crude methods used to prepare our samples.     

External quality assessment schemes for clinical laboratories

 The clinical routine laboratory generally utilizes cheap, easy and rapid measurement procedures ("methods") in order to meet the requirement for the production of many analytical results (500–3000 per day) of hundreds of different types. The measurement procedures are optimized for the analysis of native patients' samples, but are frequently sensitive to deviation of the composition of the matrix from that in normal fresh samples. The inherent lack of stability of patient samples means that control samples need to be stabilized. The method of stabilization is critical. Furthermore, the method of "spiking" samples with pathological material is a matter of concern. Generally, minimally processed patients' samples should be used in external quality assessment (EQA) schemes. Consensus values are currently the most popular for use as a guide to the best results from participating laboratories in EQA schemes; these often work fairly well. However, the uncertainty and traceability of this type of value is unknown, and in some cases may even be misleading, tending to preserve bad routine methods when these are dominant in the participating laboratories. Reference measurement procedure (RMP) values are recommended to provide scientifically based information, to facilitate the proper choice of methods in the routine laboratories, and to validate the suitability of control materials in EQA schemes. The present paper provides selected examples from a study comparing consensus values with RMP values on lyophilized sera, and also presents results on a fresh frozen thawed serum for the study of commutability. Received: 8 November 1995 Accepted: 8 May 1996     

An improved test method for characterising touch properties of porous polymeric materials

A new test method and instrument was developed to provide overall evaluation and characterisation of touch properties of porous polymeric materials. The test method and instrument can simulate the dynamic contact process between human skin and porous polymeric materials and obtain the mechanical and physical performance during contact. In the improved test method, a new measurement principle was proposed, and the mechanical device was redesigned, including surface friction measurement components. Most indices were redefined and the grading and classification methods were studied to give a direct overall evaluation of the touch properties for industrial applications. The objective test results and analysis, subjective evaluation method and prediction model of touch properties are also presented. The improved test method provides an objective measurement of thermal-mechanical properties using a single measuring instrument for new product development and quality control of porous polymeric materials.     

Nuclear forensics—metrological basis for legal defensibility

The admissibility of nuclear forensics measurements and opinions derived from them in US Federal and State courts are based on criteria established by the US Supreme Court in the case of Daubert v. Merrell Dow and the 2000 Amendment of Rule 702 of the Federal Rules of Evidence. These criteria are being addressed by new efforts that include the development of certified reference materials (CRMs) to provide the basis for analytical method development, optimization, calibration, validation, quality control, testing, readiness, and declaration of measurement uncertainties. Quality data is crucial for all stages of the program, from R&D, and database development, to actual casework. Weakness at any point in the program can propagate to reduce the confidence of final conclusions. The new certified reference materials will provide the necessary means to demonstrate a high level of metrological rigor for nuclear forensics evidence and will form a foundation for legally defensible nuclear chemical analysis. The CRMs will allow scientists to devise validated analytical methods, which can be corroborated by independent analytical laboratories. CRMs are required for ISO accreditation of many different analytical techniques which may be employed in the analysis of interdicted nuclear materials.     

Improved STR analysis of degraded DNA from human skeletal remains through in-house MPS-STR panel

DNA analysis of degraded samples and low-copy number DNA derived from skeletal remains, one of the most challenging forensic tasks, is common in disaster victim identification and genetic analysis of historical materials. Massively parallel sequencing (MPS) is a useful technique for STR analysis that enables the sequencing of smaller amplicons compared with conventional capillary electrophoresis (CE), which is valuable for the analysis of degraded DNA. In this study, 92 samples of human skeletal remains (70+ years postmortem) were tested using an in-house MPS-STR system designed for the analysis of degraded DNA. Multiple intrinsic factors of DNA from skeletal remains that affect STR typing were assessed. The recovery of STR alleles was influenced more by DNA input amount for amplification rather than DNA degradation, which may be attributed from the high quantity and quality of libraries prepared for MPS run. In addition, the higher success rate of STR typing was achieved using the MPS-STR system compared with a commercial CE-STR system by providing smaller sized fragments for amplification. The results can provide constructive information for the analysis of degraded sample, and this MPS-STR system will contribute in forensic application with regard to skeletal remain sample investigation.     

Determination of the total selenium in different materials by pixe

The determination of the total selenium in different materials is now a routine task for many laboratories. A few problems, however, still remain concerning the choice of an efficient digestion technique and an accurate and precise detection method. For this purpose, we investigated the action of various reagents used for the wet digestion of different materials. Efficient digestion combined with preconcentration were successfully applied to biological samples. Using PIXE, selenium can be detected at 5 ppb level in a short time. The overall performance of wet digestion and PIXE methods were tested with some standard reference materials.     

Ab Initio Nonadiabatic Dynamics of Semiconductor Materials via Surface Hopping Method

Photoinduced carrier dynamic processes are without doubt the main driving force responsible for the efficient performance of semiconductor nanomaterials in applications like photoconversion and photonics. Nevertheless, establishing theoretical insights into these processes is computationally challenging owing to the multiple factors involved in the processes, namely reaction rate, material surface area, material composition etc. Modelling of photoinduced carrier dynamic processes can be performed via nonadiabatic molecular dynamics (NA-MD) methods, which are methods specifically designed to solve the time-dependent Schrodinger equation with the inclusion of nonadiabatic couplings. Among NA-MD methods, surface hopping methods have been proven to be a mighty tool to mimic the competitive nonadiabatic processes in semiconductor nanomaterials, a worth noticing feature is its exceptional balance between accuracy and computational cost. Consequently, surface hopping is the method of choice for modelling ultrafast dynamics and more complex phenomena like charge separation in Janus transition metal dichalcogenides-based van der Waals heterojunction materials. Covering latest stateof-the-art numerical simulations along with experimental results in the field, this review aims to provide a basic understanding of the tight relation between semiconductor nanomaterials and the proper simulation of their properties via surface hopping methods. Special stress is put on emerging state-ot-the-art techniques. By highlighting the challenge imposed by new materials, we depict emerging creative approaches, including high-level electronic structure methods and NA-MD methods to model nonadiabatic systems with high complexity.