Different responses of MVL neurons when pigeons attend to local versus global information during object classification.

Most prior studies have indicated that pigeons have a tendency to rely on local information for target categorization, yet there is a lack of electrophysiological evidence to support this claim. The mesopallium ventrolaterale (MVL) is believed to play a role in processing both local and global information during visual cognition. The difference between responses of MVL neurons when pigeons are focusing on local versus global information during visual object categorization remain unknown.

KaMLs for Predicting Protein p Values and Ionization States: Are Trees All You Need?

Despite its importance in understanding biology and computer-aided drug discovery, the accurate prediction of protein ionization states remains a formidable challenge. Physics-based approaches struggle to capture the small, competing contributions in the complex protein environment, while machine learning (ML) is hampered by scarcity of experimental data. Here we report the development of p ML (KaML) models based on decision trees and graph attention networks (GAT), exploiting physicochemical understanding and a new experiment p database (PKAD-3) enriched with highly shifted p 's.

Volume of detonation determination based on gaseous products of energetic materials by time resolved LIPS combined with schlieren image.

The safe and fast measurement of volume of detonation (VoD) is always a hard task for macroscale explosion even though it is one of the important parameters to evaluate the explosion performance. Therefore, a promising technology to determine the VoD is highly desirable for evaluation of energetic materials. Herein, a new method of VoD determination based on gaseous products via small dose energetic materials by time correlated laser induced plasma spectroscopy (LIPS) combined with schlieren image was proposed.

Force Field Limitations of All-Atom Continuous Constant pH Molecular Dynamics.

All-atom constant pH molecular dynamics simulations offer a powerful tool for understanding pH-mediated and proton-coupled biological processes. As the protonation equilibria of protein side chains are shifted by electrostatic interactions and desolvation energies, p values calculated from the constant pH simulations may be sensitive to the underlying protein force field and water model. Here we investigated the force field dependence of the all-atom particle mesh Ewald (PME) continuous constant pH (PME-CpHMD) simulations of a mini-protein BBL.

Enhanced Photodetection Performance of InBiSe/ReS Polarization-Sensitive Heterostructure Photodetectors.

Individual anisotropic two-dimensional (2D) materials have been widely applied for developing polarization-sensitive photodetectors, but they often suffer from limitations in photoresponsivity, detection range, etc. To overcome these challenges, van der Waals (vdW) heterostructures created by stacking different 2D materials provide a promising solution to enhance the performance of the photoelectronic device. In this work, a novel polarization-sensitive photodetector is developed by leveraging a heterojunction formed by InBiSe and anisotropic ReS nanoflakes.

Emerging two-dimensional ferromagnetic semiconductors.

Two-dimensional (2D) semiconductors have attracted considerable attention for their potential in extending Moore's law and advancing next-generation electronic devices. Notably, the discovery and development of 2D ferromagnetic semiconductors (FMSs) open exciting opportunities in manipulating both charge and spin, enabling the exploration of exotic properties and the design of innovative spintronic devices. In this review, we aim to offer a comprehensive summary of emerging 2D FMSs, covering their atomic structures, physical properties, preparation methods, growth mechanisms, magnetism modulation techniques, and potential applications.

Free-standing cubic gauche nitrogen stable at 760 K under ambient pressure.

Cubic gauche nitrogen (cg-N) has received wide attention for its exceptionally high energy density and environmental friendliness. However, traditional synthesis methods for cg-N predominantly rely on high-pressure techniques or the utilization of nanoconfined effects using highly toxic and sensitive sodium azide as precursor, which substantially restrict its practical application. On the basis of the first-principles simulations, we found that adsorption of potassium on the cg-N surface exhibits superior stabilization compared to sodium.

Detonation performance and shock sensitivity of energetic material NTO with embedded small molecules: a deep neural network potential accelerated molecular dynamics study.

Accurate description of detonation performance for explosives remains a challenge for current experimental and theoretical methodologies. Herein, we address this issue through combining a multi-scale shock technique and a first-principles based deep neural network potential. This approach enables us to conduct molecular dynamics simulations encompassing over a thousand atoms and extending for several nanoseconds, allowing us to evaluate the detonation performance of the insensitive explosive NTO crystal.

Force Field Limitations of All-Atom Continuous Constant pH Molecular Dynamics.

All-atom constant pH molecular dynamics simulations offer a powerful tool for understanding pH-mediated and proton-coupled biological processes. As the protonation equilibria of protein sidechains are shifted by electrostatic interactions and desolvation energies, p values calculated from the constant pH simulations may be sensitive to the underlying protein force field and water model. Here we investigated the force field dependence of the all-atom particle mesh Ewald (PME) continuous constant pH (PME-CpHMD) simulations of a mini-protein BBL.

The application of metaverse in healthcare.

While metaverse is widely discussed, comprehension of its intricacies remains limited to a select few. Conceptually akin to a three-dimensional embodiment of the Internet, the metaverse facilitates simultaneous existence in both physical and virtual domains. Fundamentally, it embodies a visually immersive virtual environment, striving for authenticity, where individuals engage in real-world activities such as commerce, gaming, social interaction, and leisure pursuits.

The immunotherapy in gastrointestinal stromal tumors.

Using Tyrosine Kinase Inhibitors (TKIs) for gastrointestinal stromal tumors (GIST) has significantly reduced the risk of recurrence and prolonged survival. Immunotherapy has demonstrated efficacy in multiple solid tumors, but its effectiveness in GIST remains uncertain. Although early clinical studies indicate good tolerability of immunotherapy in patients, the efficacy is not as desired.

Machine Learned Classification of Ligand Intrinsic Activities at Human μ-Opioid Receptor.

Opioids are small-molecule agonists of μ-opioid receptor (μOR), while reversal agents such as naloxone are antagonists of μOR. Here, we developed machine learning (ML) models to classify the intrinsic activities of ligands at the human μOR based on the SMILES strings and two-dimensional molecular descriptors. We first manually curated a database of 983 small molecules with measured values at the human μOR.

Advancements in brain-machine interfaces for application in the metaverse.

In recent years, with the shift of focus in metaverse research toward content exchange and social interaction, breaking through the current bottleneck of audio-visual media interaction has become an urgent issue. The use of brain-machine interfaces for sensory simulation is one of the proposed solutions. Currently, brain-machine interfaces have demonstrated irreplaceable potential as physiological signal acquisition tools in various fields within the metaverse.

Laser-induced shock wave two-dimensional extraction technology based on a beam deflection method.

This paper introduces a method for analyzing the spatiotemporal progression of laser-induced shock waves using the beam deflection technique. This method allows for the accurate measurement of the shock wave evolution and can replace high-speed cameras. The results demonstrate the detection signals at various distances and energies, as well as the extraction and reconstruction of the shock wave velocities and propagation trajectories.

Construction and Validation of Novel Ferroptosis-related Risk Score Signature and Prognostic Prediction Nomogram for Patients with Colorectal Cancer.

Colorectal cancer (CRC) has a high morbidity and mortality. Ferroptosis is a phenomenon in which metabolism and cell death are closely related. The role of ferroptosis-related genes in the progression of CRC is still not clear.

Machine Learning Models to Interrogate Proteome-Wide Covalent Ligandabilities Directed at Cysteines.

Machine learning (ML) identification of covalently ligandable sites may accelerate targeted covalent inhibitor design and help expand the druggable proteome space. Here, we report the rigorous development and validation of the tree-based models and convolutional neural networks (CNNs) trained on a newly curated database (LigCys3D) of over 1000 liganded cysteines in nearly 800 proteins represented by over 10,000 three-dimensional structures in the protein data bank. The unseen tests yielded 94 and 93% area under the receiver operating characteristic curves for the tree models and CNNs, respectively.

Machine Learned Classification of Ligand Intrinsic Activities at Human -Opioid Receptor.

Opioids are small-molecule agonists of -opioid receptor (OR), while reversal agents such as naloxone are antagonists of OR. Here we developed machine learning (ML) models to classify the intrinsic activities of ligands at the human OR based on the SMILE strings and two-dimensional molecular descriptors. We first manually curated a database of 983 small molecules with measured values at the human OR.

Why is the Omicron main protease of SARS-CoV-2 less stable than its wild-type counterpart? A crystallographic, biophysical, and theoretical study of the free enzyme and its complex with inhibitor 13b-K.

During the continuing evolution of SARS-CoV-2, the Omicron variant of concern emerged in the second half of 2021 and has been dominant since November that year. Along with its sublineages, it has maintained a prominent role ever since. The Nsp5 main protease (M) of the Omicron virus is characterized by a single dominant mutation, P132H.

Gamma-band-based dynamic functional connectivity in pigeon entopallium during sample presentation in a delayed color matching task.

Birds have developed visual cognitions, especially in discriminating colors due to their four types of cones in the retina. The entopallium of birds is thought to be involved in the processing of color information during visual cognition. However, there is a lack of understanding about how functional connectivity in the entopallium region of birds changes during color cognition, which is related to various input colors.

Correction to: Gamma-band-based dynamic functional connectivity in pigeon entopallium during sample presentation in a delayed color matching task.

[This corrects the article DOI: 10.1007/s11571-022-09916-w.].