Electrolyte-gated transistors for enhanced performance bioelectronics

Nature Reviews Methods Primers, Journal Year: 2021, Volume and Issue: 1(1)

Published: Oct. 7, 2021

Electrolyte-gated transistors (EGTs), capable of transducing biological and biochemical inputs into amplified electronic signals stably operating in aqueous environments, have emerged as fundamental building blocks bioelectronics. In this Primer, the different EGT architectures are described with mechanisms underpinning their functional operation, providing insight key experiments including necessary data analysis validation. Several organic inorganic materials used structures fabrication approaches for an optimal experimental design presented compared. The bio-layers and/or biosystems integrated or interfaced to EGTs, self-organization self-assembly strategies, reviewed. Relevant promising applications discussed, two-dimensional three-dimensional cell monitoring, ultra-sensitive biosensors, electrophysiology, synaptic neuromorphic bio-interfaces, prosthetics robotics. Advantages, limitations possible optimizations also surveyed. Finally, current issues future directions further developments discussed. (EGTs) bioelectronics, which transduce electrical signals. This Primer examines mechanism operation practical considerations related wide range applications.

Language: Английский

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The efficacy of PD-1/PD-L1 blockade in cold cancers and future perspectives

Clinical Immunology, Journal Year: 2021, Volume and Issue: 226, P. 108707 - 108707

Published: March 1, 2021

Language: Английский

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Immunogenomic Landscape of Hematological Malignancies

Cancer Cell, Journal Year: 2020, Volume and Issue: 38(3), P. 380 - 399.e13

Published: July 9, 2020

Language: Английский

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Delineating the conformational landscape of the adenosine A2A receptor during G protein coupling

Cell, Journal Year: 2021, Volume and Issue: 184(7), P. 1884 - 1894.e14

Published: March 19, 2021

Language: Английский

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Feedback between climate change and eutrophication: revisiting the allied attack concept and how to strike back

Inland Waters, Journal Year: 2022, Volume and Issue: 12(2), P. 187 - 204

Published: Jan. 28, 2022

Despite its well-established negative impacts on society and biodiversity, eutrophication continues to be one of the most pervasive anthropogenic influences along freshwater marine continuum. The interaction between climate change, particularly warming, was explicitly focused upon a decade ago by Brian Moss others in "Allied attack: change eutrophication," which called for an integrated response both problems, given their apparent synergy. In this review, we summarise advances theoretical framework empirical research issue analyse current understanding major drivers mechanisms can enhance eutrophication, vice versa, with particular focus shallow lakes. Climate affect nutrient loading through changes at catchment landscape levels affecting hydrological patterns fire frequency temperature effects cycling. Biotic communities interactions also directly indirectly affected leading overall weakening resilience impacts. Increasing evidence now indicates several eutrophying aquatic systems increasingly act as important sources greenhouse gases atmosphere, methane. We highlight potential feedback among cyanobacterial blooms, change. Facing challenges simultaneously is more pressing than ever. Meaningful strong measures waterbody are therefore required if ensure ecosystem safe water supply, conserve decrease carbon footprint freshwaters.

Language: Английский

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Recent advancement in water quality indicators for eutrophication in global freshwater lakes

Environmental Research Letters, Journal Year: 2023, Volume and Issue: 18(6), P. 063004 - 063004

Published: April 26, 2023

Abstract Eutrophication is a major global concern in lakes, caused by excessive nutrient loadings (nitrogen and phosphorus) from human activities likely exacerbated climate change. Present use of indicators to monitor assess lake eutrophication restricted water quality constituents (e.g. total phosphorus, nitrogen) does not necessarily represent environmental changes the anthropogenic influences within lake’s drainage basin. Nutrients interact multiple ways with climate, basin conditions socio-economic development, point-source, diffuse source pollutants), systems. It therefore essential account for complex feedback mechanisms non-linear interactions that exist between nutrients ecosystems assessments. However, lack set holistic understanding challenges such assessments, addition limited monitoring data available. In this review, we synthesize main freshwater basins only include but also sources, biogeochemical pathways responses emissions. We develop new causal network (i.e. links indicators) using DPSIR (drivers-pressure-state-impact-response) framework highlights interrelationships among provides perspective dynamics basins. further review 30 key drivers pressures seven cross-cutting themes: (i) hydro-climatology, (ii) socio-economy, (iii) land use, (iv) characteristics, (v) crop farming livestock, (vi) hydrology management, (vii) fishing aquaculture. This study indicates need more comprehensive systems, guide expansion networks, support integrated assessments manage eutrophication. Finally, proposed can be used managers decision-makers realistic targets sustainable management achieve clean all, line Sustainable Development Goal 6.

Language: Английский

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The brain in motion: How ensemble fluidity drives memory-updating and flexibility

eLife, Journal Year: 2020, Volume and Issue: 9

Published: Dec. 29, 2020

While memories are often thought of as flashbacks to a previous experience, they do not simply conserve veridical representations the past but must continually integrate new information ensure survival in dynamic environments. Therefore, ‘drift’ neural firing patterns, typically construed disruptive ‘instability’ or an undesirable consequence noise, may actually be useful for updating memories. In our view, continual modifications memory reconcile classical theories stable traces with drift. Here we review how updated through recruitment neuronal ensembles on basis excitability and functional connectivity at time learning. Overall, emphasize importance considering static entities, instead flexible network states that reactivate evolve across experience.

Language: Английский

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Advancements in electrochemical biosensing for respiratory virus detection: A review

TrAC Trends in Analytical Chemistry, Journal Year: 2021, Volume and Issue: 139, P. 116253 - 116253

Published: March 12, 2021

Language: Английский

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Using deep neural networks for kinematic analysis: Challenges and opportunities

Journal of Biomechanics, Journal Year: 2021, Volume and Issue: 123, P. 110460 - 110460

Published: May 2, 2021

Kinematic analysis is often performed in a lab using optical cameras combined with reflective markers. With the advent of artificial intelligence techniques such as deep neural networks, it now possible to perform analyses without markers, making outdoor applications feasible. In this paper I summarise 2D markerless approaches for estimating joint angles, highlighting their strengths and limitations. computer science, so-called "pose estimation" algorithms have existed many years. These methods involve training network detect features (e.g. anatomical landmarks) process called supervised learning, which requires "training" images be manually annotated. Manual labelling has several limitations, including labeller subjectivity, requirement knowledge, issues related data quality quantity. Neural networks typically require thousands examples before they can make accurate predictions, so datasets are usually labelled by multiple people, each whom own biases, ultimately affects performance. A recent approach, transfer involves modifying model trained certain task that retains some learned then re-trained new task. This drastically reduce required number images. Although development ongoing, existing systems may already enough applications, e.g. coaching or rehabilitation. Accuracy further improved leveraging novel incorporating realistic physiological constraints, resulting low-cost could deployed both outside lab.

Language: Английский

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EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture

G3 Genes Genomes Genetics, Journal Year: 2021, Volume and Issue: 11(4)

Published: Feb. 6, 2021

Abstract Envirotyping is an essential technique used to unfold the nongenetic drivers associated with phenotypic adaptation of living organisms. Here, we introduce EnvRtype R package, a novel toolkit developed interplay large-scale envirotyping data (enviromics) into quantitative genomics. To start user-friendly pipeline, this package offers: (1) remote sensing tools for collecting (get_weather and extract_GIS functions) processing ecophysiological variables (processWTH function) from raw environmental at single locations or worldwide; (2) characterization by typing environments profiling descriptors quality (env_typing function), in addition gathering covariables as predictive purposes (W_matrix function); (3) identification similarity that can be enviromic-based kernel whole-genome prediction (GP), aimed increasing knowledge genomic best-unbiased predictions (GBLUP) emulating reaction norm effects (get_kernel kernel_model functions). We highlight literature mining concepts fine-tuning parameters each plant species target growing environments. show breeding collects processes it eco-physiologically smart way. Examples its use creating global-scale networks integrating reaction-norm modeling GP are also outlined. conclude provides cost-effective pipeline capable providing high enviromic diverse set genomic-based studies, especially accuracy across untested

Language: Английский

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