Four-Dimensional Electron Microscopy Zewail, Ahmed H.
Science (American Association for the Advancement of Science),
04/2010, Volume:
328, Issue:
5975
Journal Article
Peer reviewed
The discovery of the electron over a century ago and the realization of its dual character have given birth to one of the two most powerful imaging instruments: the electron microscope. The electron ...microscope's ability to resolve three-dimensional (3D) structures on the atomic scale is continuing to affect different fields, including materials science and biology. In this Review, we highlight recent developments and inventions made by introducing the fourth dimension of time in electron microscopy. Today, ultrafast electron microscopy (4D UEM) enables a resolution that is 10 orders of magnitude better than that of conventional microscopes, which are limited by the video-camera rate of recording. After presenting the central concept involved, that of single-electron stroboscopie imaging, we discuss prototypical applications, which include the visualization of complex structures when unfolding on different length and time scales. The developed UEM variant techniques are several, and here we illucidate convergent-beam and near-field imaging, as well as tomography and scanning-pulse microscopy. We conclude with current explorations in imaging of nanomaterials and biostructures and an outlook on possible future directions in space-time, 4D electron microscopy.
The CRISPR-Cas9 RNA-guided DNA endonuclease has contributed to an explosion of advances in the life sciences that have grown from the ability to edit genomes within living cells. In this Review, we ...summarize CRISPR-based technologies that enable mammalian genome editing and their various applications. We describe recent developments that extend the generality, DNA specificity, product selectivity, and fundamental capabilities of natural CRISPR systems, and we highlight some of the remarkable advancements in basic research, biotechnology, and therapeutics science that these developments have facilitated.
CRISPR-based genome-editing technologies provide powerful tools to study basic biology and may lead to new treatments for human disease.
Habit, choice, and addiction Vandaele, Y; Ahmed, S H
Neuropsychopharmacology,
03/2021, Volume:
46, Issue:
4
Journal Article
Peer reviewed
Open access
Addiction was suggested to emerge from the progressive dominance of habits over goal-directed behaviors. However, it is generally assumed that habits do not persist in choice settings. Therefore, it ...is unclear how drug habits may persist in real-world scenarios where this factor predominates. Here, we discuss the poor translational validity of the habit construct, which impedes our ability to determine its role in addiction. New evidence of habitual behavior in a drug choice setting are then described and discussed. Interestingly, habitual preference did not promote drug choice but instead favored abstinence. Here, we propose several clues to reconcile these unexpected results with the habit theory of addiction, and we highlight the need in experimental research to face the complexity of drug addicts' decision-making environments by investigating drug habits in the context of choice and in the presence of cues. On a theoretical level, we need to consider more complex frameworks, taking into account continuous interactions between goal-directed and habitual systems, and alternative decision-making models more representative of real-world conditions.
Janus kinase (JAK) is a family of cytoplasmic non-receptor tyrosine kinases that includes four members, namely JAK1, JAK2, JAK3, and TYK2. The JAKs transduce cytokine signaling through the JAK-STAT ...pathway, which regulates the transcription of several genes involved in inflammatory, immune, and cancer conditions. Targeting the JAK family kinases with small-molecule inhibitors has proved to be effective in the treatment of different types of diseases. In the current review, eleven of the JAK inhibitors that received approval for clinical use have been discussed. These drugs are abrocitinib, baricitinib, delgocitinib, fedratinib, filgotinib, oclacitinib, pacritinib, peficitinib, ruxolitinib, tofacitinib, and upadacitinib. The aim of the current review was to provide an integrated overview of the chemical and pharmacological data of the globally approved JAK inhibitors. The synthetic routes of the eleven drugs were described. In addition, their inhibitory activities against different kinases and their pharmacological uses have also been explained. Moreover, their crystal structures with different kinases were summarized, with a primary focus on their binding modes and interactions. The proposed metabolic pathways and metabolites of these drugs were also illustrated. To sum up, the data in the current review could help in the design of new JAK inhibitors with potential therapeutic benefits in inflammatory and autoimmune diseases.
Activated carbon (AC) is one of the most used materials in dye removal that can be synthesized using different agricultural wastes. In this work, the effects of waste type and pyrolysis temperature ...were investigated. Corn cob and wheat straw were used for preparation of activated carbon by applying 10 % H3PO4 as an activating agent, followed by pyrolysis at 400 or 500 °C and then thermal activation at 800 °C for 10 minutes. Elemental analysis, acid soluble matter, ash content, and calorific value were measured for the prepared samples of AC. Finally, the product was applied for adsorption of Congo Red and Nile Blue dyes from wastewater and the maximum adsorption capacity was found to be 99.56 and 85.23 mg g−1, respectively using a corn cob sample activated at 500 °C.
Activated carbon was prepared using corn cob and wheat straw as the main raw materials that were activated with phosphoric acid, followed by pyrolysis and thermal activation. The pyrolysis step was performed at different temperatures to study the effect of changing the raw materials and pyrolysis temperature on the removal efficiency of Nile Blue and Congo Red dyes from wastewater.
Several multiscale methods account for sub-grid scale features using coarse scale basis functions. For example, in the Multiscale Finite Volume method the coarse scale basis functions are obtained by ...solving a set of local problems over dual-grid cells. We introduce a data-driven approach for the estimation of these coarse scale basis functions. Specifically, we employ a neural network predictor fitted using a set of solution samples from which it learns to generate subsequent basis functions at a lower computational cost than solving the local problems. The computational advantage of this approach is realized for uncertainty quantification tasks where a large number of realizations has to be evaluated. We attribute the ability to learn these basis functions to the modularity of the local problems and the redundancy of the permeability patches between samples. The proposed method is evaluated on elliptic problems yielding very promising results.
We demonstrate that functionalized pyrene derivatives effectively stabilize single- and few-layer graphene flakes in aqueous dispersions. The graphene/stabilizer yield obtained by this method is ...exceptionally high relative to conventional nanomaterial stabilizers such as surfactants or polymers. The mechanism of stabilization by pyrene derivatives is investigated by studying the effects of various parameters on dispersed graphene concentration and stability; these parameters include stabilizer concentration, initial graphite concentration, solution pH, and type and number of functional groups and counterions. The effectiveness of the pyrene derivatives is pH-tunable, as measured by zeta potential, and is also a function of the number of functional groups, the electronegativity of the functional group, the counterion, the relative polarity between stabilizer and solvent, and the distance from the functional group to the basal plane. Even if the dispersion is destabilized by extreme pH or lyophilization, the graphene does not aggregate because the stabilizer remains adsorbed on the surface. These dispersions also show promise for applications in graphene/polymer nanocomposites (examined in this paper), organic solar cells, conductive films, and inkjet-printed electronic devices.
The growth of clean energies and technologies requires a sound financial market, while equity and bond markets are exposed to geopolitical risks. We investigate the response of green equity and green ...bonds to newly develop decomposed measures of geopolitical risks, including geopolitical acts, threats, and narrow and broad measures. To this end, we apply two robust methods; namely, the cross-quantilogram and quantile and quantile (QQ) approaches, to estimate the conditional and unconditional volatility spillovers considering short, medium, and long term. Surprisingly our empirical investigation demonstrates that all measures of geopolitical risk (except geopolitical acts) transmit positive shocks to the green investments (both equity and bonds) from bearish to bullish market states. At the bullish state, green markets respond negatively to the highest quantiles of all measures of geopolitical risks under a long memory. However, the geopolitical acts negatively shock the green bonds and green equity at some extreme quantiles. Our empirical findings are beneficial by transmitting opportunities and preventing risks for investment decision-making in the green markets, considering geopolitical risks.
•We assess the response of green securities to different geopolitical risks measures.•Cross-quantilogram and quantile and quantile (QQ) approaches are applied.•Geopolitical risk measures transmit positive shocks to the green investments.
High loads of suspended sediments in rivers are known to cause detrimental effects to potable water sources, river water quality, irrigation activities, and dam or reservoir operations. For this ...reason, the study of suspended sediment load (SSL) prediction is important for monitoring and damage mitigation purposes. The present study tests and develops machine learning (ML) models, based on the support vector machine (SVM), artificial neural network (ANN) and long short-term memory (LSTM) algorithms, to predict SSL based on 11 different river data sets comprising of streamflow (SF) and SSL data obtained from the Malaysian Department of Irrigation and Drainage. The main objective of the present study is to propose a single model that is capable of accurately predicting SSLs for any river data set within Peninsular Malaysia. The ANN3 model, based on the ANN algorithm and input scenario 3 (inputs consisting of current-day SF, previous-day SF, and previous-day SSL), is determined as the best model in the present study as it produced the best predictive performance for 5 out of 11 of the tested data sets and obtained the highest average RM with a score of 2.64 when compared to the other tested models, indicating that it has the highest reliability to produce relatively high-accuracy SSL predictions for different data sets. Therefore, the ANN3 model is proposed as a universal model for the prediction of SSL within Peninsular Malaysia.
In this review, we highlight the progress made in the development of 4D ultrafast electron diffraction (UED), crystallography (UEC), and microscopy (UEM) with a focus on concepts, methodologies, and ...prototypical applications. The joint atomic-scale resolutions in space and time, and sensitivity reached, make it possible to determine complex transient structures and assemblies in different phases. These applications include studies of isolated chemical reactions (molecular beams), interfaces, surfaces and nanocrystals, self-assembly, and 2D crystalline fatty-acid bilayers. In 4D UEM, we are now able, using timed, single-electron packets, to image nano-to-micro scale structures of materials and biological cells. Future applications of these methods are foreseen across areas of physics, chemistry, and biology.
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