Rae1/YacP, a new endoribonuclease involved in ribosome-dependent mRNA decay in Bacillus subtilis

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Genes implicated in translation control have been associated with autism spectrum disorders (ASDs). However, some important genetic causes of autism, including the 16p11.2 microdeletion, bear no obvious connection to translation. Here, we use proteomics, g ...

Curcuminoids and their complexes continue to attract attention in medicinal chemistry, but little attention has been given to their metabolic derivatives. Here, the first examples of (arene)Ru(II) complexes with curcuminoid metabolites, tetrahydrocurcumin ...

Why are materials with specific characteristics more abundant than others? This is a fundamental question in materials science and one that is traditionally difficult to tackle, given the vastness of compositional and configurational space. We highlight he ...

Cupredoxins are widely occurring copper-binding proteins with a typical Greek-key beta barrel fold. They are generally described as electron carriers that rely on a T1 copper centre coordinated by four ligands provided by the folded polypeptide. The discov ...

Metal-organic frameworks (MOFs) are a rapidly growing class of materials that offer great promise in various applications. However, the synthesis remains challenging: for example, a range of crystal structures can often be accessed from the same building b ...

Polymer brushes have been theoretically described, their behavior under diverse conditions has been modeled, and their preparation via surface-initiated polymerizations (SIPs) has been progressively refined. However, despite three decades of research endea ...

Dense image-based prediction methods have advanced tremendously in recent years. Their remarkable development has been possible due to the ample availability of real-world imagery. While these methods work well on photographs, their abilities do not genera ...

The recent developments of deep learning cover a wide variety of tasks such as image classification, text translation, playing go, and folding proteins. All these successful methods depend on a gradient-based learning algorithm to train a model on massive ...

Due to the subtle balance of intermolecular interactions that govern structure-property relations, predicting the stability of crystal structures formed from molecular building blocks is a highly non-trivial scientific problem. A particularly active and fr ...

Professionals in the building design and operation fields typically look at standards and guidelines as a reliable source of information and guidance with regard to procedural, contractual, and legal scope and requirements that are relevant to accountabili ...

Structure determinationof molecular solids through NMR crystallographyrelies on the generation of a comprehensive set of candidate crystalstructures and on the comparison of chemical shifts computed for thosecandidates with experimental values. Exploring t ...

RNA-binding proteins are instrumental for post-transcriptional gene regulation, controlling all aspects throughout the lifecycle of RNA molecules. However, transcriptome-wide methods to profile RNA-protein interactions in vivo remain technically challengin ...

Many properties of materials, including their dissolution kinetics, hardness, and optical appearance, depend on their structure. Unfortunately, it is often difficult to control the structure of low molecular weight organic compounds that have a high propen ...

The thermal behavior of 3-benzoylpropionic acid (BPA) was investigated using single-crystal and synchrotron powder X-diffraction, as well as differential scanning calorimetry analysis. The study revealed the existence of two subtly distinct structures of B ...

In the third study, the order-disorder phase transition of single-crystal C60 is studied using time-resolved electron microscopy. Solid C60 undergoes a first-order phase transition upon heating to 260 K. This is a structural transition from the low-tempera ...

Minimax-fair machine learning minimizes the error for the worst-off group. However, empirical evidence suggests that when sophisticated models are trained with standard empirical risk minimization (ERM), they often have the same performance on the worst-of ...

The performance of modern object detectors drops when the test distribution differs from the training one. Most of the methods that address this focus on object appearance changes caused by, e.g., different illumination conditions, or gaps between syntheti ...

Barocaloric (BC) materials provide cheaper and more energy efficient alternatives to traditional refrigerants. Some liquid alkanes were recently shown to exhibit a colossal BC effect, matching the entropy changes in commercial vapour-liquid refrigerants. D ...

Parliament dynamics might seem erratic at times. Predicting future voting patterns could support policy design based on the simulation of voting scenarios. The availability of open data on legislative activities and machine learning tools might enable such ...

Structure determination of materials is key to understanding their physical properties. While single-crystal X-ray diffraction is the gold standard for structures displaying long-range order, many materials of interest are polycrystalline and/or disordered ...

Rae1/YacP, a new endoribonuclease involved in ribosome-dependent mRNA decay in Bacillus subtilis

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The autism susceptibility kinase, TAOK2, phosphorylates eEF2 and modulates translation

Ru(II)-Arene Complexes of Curcumin and Bisdesmethoxycurcumin Metabolites

The rule of four: anomalous distributions in the stoichiometries of inorganic compounds

Beyond the coupled distortion model: structural analysis of the single domain cupredoxin AcoP, a green mononuclear copper centre with original features

How Reproducible is the Synthesis of Zr-Porphyrin Metal-Organic Frameworks? An Interlaboratory Study

Opportunities, Challenges, and Pitfalls in Making, Characterizing, and Understanding Polymer Brushes

Dense Image-based Predictions for Comics Analysis

Transformer Models for Vision

A data-driven interpretation of the stability of organic molecular crystals

Thermal Conditions in Indoor Environments: Exploring the Reasoning behind Standard-Based Recommendations

Chemical Shift-Dependent Interaction Maps in Molecular Solids

Efficient and sensitive profiling of RNA–protein interactions using TLC-CLIP

Controlling the crystal structure of succinic acid via microfluidic spray-drying

Melting pseudosymmetry and thermal expansion in 3-benzoylpropionic acid

Direct Observation of the Phase Transition in C60 Fullerene

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

Learning Transformations To Reduce the Geometric Shift in Object Detection

Pressure-freezing of dodecane: exploring the crystal structures, formation kinetics and phase diagrams for colossal barocaloric effects in n-alkanes

Predicting party switching through machine learning and open data

NMR Crystallography in the Big Data Era: New Methods and Applications Powered by Machine Learning