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Elemental analysis: Hair by AAS

Date: Apr 2, 2017

Author:

Atomic absorption spectrometry (AAS) has been used to analyse hair samples from Polish children and adolescents revealing significant differences between metallic elements present in different age groups and between boys and girls.

Read More thumbnail image: Elemental analysis Hair by AAS

Machine learning: Trained with MRI

Date: Apr 1, 2017

Author: David Bradley

US scientists are using a supercomputer to analysis magnetic resonance imaging (MRI) brain scans to find markers for predicting mental illness and dementia prior to onset.

Read More thumbnail image: Machine learning Trained with MRI

Anemones punch holes: Toxins by NMR

Date: Apr 1, 2017

Author: David Bradley

A new approach to constructing a sea anemone toxin makes it plausible to incorporate site-specific isotopic labels for solid-state nuclear magnetic resonance (NMR) spectroscopic structural studies that will ultimately reveal how it functions and provide clues as to the action of other pore-forming proteins.

Read More thumbnail image: Anemones punch holes Toxins by NMR

Graphene for X-rays: Benchtop instruments

Date: Apr 1, 2017

Author: David Bradley

A collaboration between the A*STAR Singapore Institute of Manufacturing Technology (SIMTech) and the Massachusetts Institute of Technology (MIT) in the USA is working towards a versatile, directional X-ray source that exploits the properties of the "two-dimensional" carbon material known as graphene and could be built as a bench-top or even handheld device for a wide range of applications.

Read More thumbnail image: Graphene for X-rays Benchtop instruments

Silver nanoparticles: Fungi to beat bacteria

Date: Apr 1, 2017

Author: David Bradley

Researchers in Brazil and the UK have used UV-Vis spectroscopy, scanning electron microscopy, EDX, and XRD to characterise silver nanoparticles made by soil fungi, with the potential to defeat antibiotic resistant bacteria.

Read More thumbnail image: Silver nanoparticles Fungi to beat bacteria

Disease detector: Early signs visible to infrared

Date: Apr 1, 2017

Author: David Bradley

Fourier transform infrared (FTIR) spectroscopy can detect and characterize the release of sub-micrometre sized microvesicles and how they change in response during the body's immunological response to bacterial infection.

Read More thumbnail image: Disease detector Early signs visible to infrared

Food colourant: Sensor tech

Date: Apr 1, 2017

Author: David Bradley

A material that has been used as a food dye for decades in corn chips and ice cream could be used in novel sensor technology, according to researchers at Georgia Institute of Technology.

Read More thumbnail image: Food colourant Sensor tech

Journal Highlight: Pulmonary MRI of neonates in the intensive care unit using 3D ultrashort echo time and a small footprint MRI system

Date: Mar 27, 2017

Author: spectroscopyNOW

The feasibility of pulmonary MRI of neonatal lung structures in free breathing subjects enabled by combining two novel technologies has been studied using a 3D radial ultrashort echo time pulse sequence and a unique, small-footprint 1.5T MRI scanner design.

Read More thumbnail image: Journal Highlight Pulmonary MRI of neonates in the intensive care unit using 3D ultrashort echo time and a small footprint MRI system

Journal Highlight: Detergents: Friends not foes for high-performance membrane proteomics toward precision medicine

Date: Mar 27, 2017

Author: spectroscopyNOW

This review analyzes detergent properties behind recent proteomic advances and proposes that rational use of detergents may reconcile outstanding membrane proteomics dilemmas, enabling ultradeep coverage and minimal artifacts.

Read More thumbnail image: Journal Highlight Detergents Friends not foes for high-performance membrane proteomics toward precision medicine

Journal Highlight: Classification of lignocellulosic biomass by weighted-covariance factor fuzzy C-means clustering of mid-infrared and near-infrared spectra

Date: Mar 20, 2017

Author: spectroscopyNOW

A weighted-covariance factor fuzzy C-means clustering method combined with bootstrapping has been proposed for analysing the mid-IR and near-IR spectra of small samples of biomass.

Read More thumbnail image: Journal Highlight Classification of lignocellulosic biomass by weighted-covariance factor fuzzy C-means clustering of mid-infrared and near-infrared spectra
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