GenNet framework: interpretable deep learning for predicting phenotypes from genetic data

Fig: Overview of the GenNet framework Applying deep learning in population genomics is challenging because of computational issues and lack of interpretable models. Here, we propose GenNet, a novel open-source deep learning framework for predicting phenotypes from genetic variants. In this framework, interpretable and memory-efficient neural network architectures are constructed by embedding biologically knowledge from public databases, resulting in neural networks that contain only biologically … Continue reading GenNet framework: interpretable deep learning for predicting phenotypes from genetic data

New 3D-printed sensor can detect glyphosate in beverages

A newly developed, low-cost sensor can detect and accurately measure the amount of the widely used and controversial herbicide, glyphosate, in droplets of liquid in a laboratory test. Ultimately, that is the goal for this sensor: to test human samples for monitoring glyphosate exposure, but in the study published in Biosensors and Bioelectronics, researchers first showed the sensor’s potential for testing beverages. Before this new development,methods of … Continue reading New 3D-printed sensor can detect glyphosate in beverages

A novel method for extraction, quantification, and identification of microplastics

The objective of this study was to develop an accessible and accurate analysis method for microplastics that have been unintentionally added to cream cosmetic products. An experiment was performed on three cleansing creams in rich and viscous formulations. A spiked sample was prepared by adding polyethylene (PE) microspheres to the cleansing creams. After removing cosmetic ingredients from the creams using chemical digestion, damage to the … Continue reading A novel method for extraction, quantification, and identification of microplastics

Adding foreign atoms to graphene boosts its properties

Few materials have stolen the limelight like graphene. Since its discovery, graphene has become the go-to for nearly any technology out there, thanks to its exceptional properties such as high surface area, chemical stability, and high mechanical strength and elasticity. However, despite its seemingly limitless applications, graphene’s potential remains underutilized due to several factors, most notably its single-atom thickness, chemical inertness, and the lack of … Continue reading Adding foreign atoms to graphene boosts its properties

Non-magnetic shell coating of magnetic nanoparticles

Biocopatible magnetic nanomaterials have been intensively studied for various applications in biomedicine. They can be remotely controlled over by an external magnetic field, which makes it possible to specifically affect target molecules on the molecular level. Magnetic nanoparticles cytotoxicity depends on acting magnetic field parameters, the most significant of which are magnetic field amplitude, frequency, and the duration of action. In a low frequency alternating magnetic field, they … Continue reading Non-magnetic shell coating of magnetic nanoparticles

Researchers make rechargeable batteries that store six times more charge

An LED light powered by a prototype rechargeable battery using the sodium-chlorine chemistry developed The new so-called alkali metal-chlorine batteries, developed by a team of researchers led by Stanford chemistry Professor Hongjie Dai and doctoral candidate Guanzhou Zhu, relies on the back-and-forth chemical conversion of sodium chloride (Na/Cl2) or lithium chloride (Li/Cl2) to chlorine. When electrons travel from one side of a rechargeable battery to the … Continue reading Researchers make rechargeable batteries that store six times more charge

Scientists develop technology for sustainable next-generation batteries

Lithium-ion batteries are commonly used in many electrical devices, but global lithium resources are rapidly declining and mining operations create a large carbon footprint. Sodium-ion batteries could offer a sustainable alternative which, if optimized, could be used in electric vehicles. However, current models  have yet to match lithium’s energy capacity and pose some safety risks. The key to improving energy capacity in batteries lies in the … Continue reading Scientists develop technology for sustainable next-generation batteries

Perovskite allows a greener fabrication of transistors

Fig: Ion mitigation in perovskite FETs. a) A conventional perovskite FET with a bottom-gate bottom-contact architecture. The S and D denote source and drain electrode, respectively. Mobile cations are represented as “+” signs in red circles, while “−” signs in the perovskite layer represent counter-anions. b) Device operation of the perovskite FET at a negative gate voltage with a negative drain voltage (source is grounded). … Continue reading Perovskite allows a greener fabrication of transistors

Sensitive GSEM-based bionic airflow sensor developed

Airflow sensors based on mechanical deformation mechanism have drawn increasing attention thanks to their excellent flexibility and sensitivity. However, fabricating highly sensitive and self-adaptive airflow sensors via facile and controllable methods remains a challenge. Inspired by the bats’ wing membrane which shows unique airflow sensing capacity, researchers at NIMTE prepared graphene/single-walled nanotubes (SWNTs)-Ecoflex membrane (GSEM), which can be arbitrarily transferred and subsequently adapt to diverse flat/bend and … Continue reading Sensitive GSEM-based bionic airflow sensor developed

Deep learning-based gene selection in comprehensive gene analysis

The selection of genes that are important for obtaining gene expression data is challenging. Here, we developed a deep learning-based feature selection method suitable for gene selection. Our novel deep learning model includes an additional feature-selection layer. After model training, the units in this layer with high weights correspond to the genes that worked effectively in the processing of the networks. Cancer tissue samples and … Continue reading Deep learning-based gene selection in comprehensive gene analysis