Single Domain Research Articles

Direct structural analysis of a single acyl carrier protein domain in fatty acid synthase from the fungus Saccharomyces cerevisiae

Acyl carrier protein (ACP) is the work horse of polyketide (PKS) and fatty acid synthases (FAS) and acts as a substrate shuttling domain in these mega enzymes. In fungi, FAS forms a 2.6 MDa symmetric assembly with six identical copies of FAS1 and FAS2 polypeptides. However, ACP spatial distribution is not restricted by symmetry owing to the long and flexible loops that tether the shuttling domain to its corresponding FAS2 polypeptide. This symmetry breaking has hampered experimental investigation of substrate shuttling route in fungal FAS. Here, we develop a protein engineering and expression method to isolate asymmetric fungal FAS proteins containing odd numbers of ACP domains. Electron cryomicroscopy (cryoEM) observation of the engineered complex reveals a non-uniform distribution of the substrate shuttling domain relative to its corresponding FAS2 polypeptide at 2.9 Å resolution. This work lays the methodological foundation for experimental study of ACP shuttling route in fungi.

Inter-Domain Invariant Cross-Domain Object Detection Using Style and Content Disentanglement for In-Vehicle Images

The accurate detection of relevant vehicles, pedestrians, and other targets on the road plays a crucial role in ensuring the safety of autonomous driving. In recent years, object detectors based on Transformers or CNNs have achieved excellent performance in the fully supervised paradigm. However, when the trained model is directly applied to unfamiliar scenes where the training data and testing data have different distributions statistically, the model’s performance may decrease dramatically. To address this issue, unsupervised domain adaptive object detection methods have been proposed. However, these methods often exhibit decreasing performance when the gap between the source and target domains increases. Previous works mainly focused on utilizing the style gap to reduce the domain gap while ignoring the content gap. To tackle this challenge, we introduce a novel method called IDI-SCD that effectively addresses both the style and content gaps simultaneously. Firstly, the domain gap is reduced by disentangling it into the style gap and content gap, generating corresponding intermediate domains in the meanwhile. Secondly, during training, we focus on one single domain gap at a time to achieve inter-domain invariance. That is, the content gap is tackled while maintaining the style gap, and vice versa. In addition, the style-invariant loss is used to narrow down the style gap, and the mean teacher self-training framework is used to narrow down the content gap. Finally, we introduce a multiscale fusion strategy to enhance the quality of pseudo-labels, which mainly focus on enhancing the detection performance for extreme-scale objects (very large or very small objects). We conduct extensive experiments on four mainstream datasets of in-vehicle images. The experimental results demonstrate the effectiveness of our method and its superiority over most of the existing methods.

Investigation of commercially available resins for the automated flow synthesis of difficult or long peptide sequences

AbstractSolid‐phase peptide synthesis (SPPS) is widely used to produce peptides. Since its invention, the solid support has enabled the elongation of the synthetic peptide chain. As technologies have evolved, the length of peptide chains accessible with SPPS has grown to that of single‐domain proteins. Resins for SPPS have advanced to improve synthesis capabilities as well. The functionalization of solid supports with polyethylene glycol (PEG) is commonly employed in a range of commercially available resins to aid in the ability to synthesize long or difficult sequences. A notable example of a widely used PEG‐based solid support is ChemMatrix® resin; however, this and several similar resins have recently been discontinued. Here, we demonstrate and compare the capabilities of OctaGel™, ProTide®, and TentaGel XV® resins in synthesizing sequences ranging from peptides to single domain proteins using automated fast‐flow peptide synthesis. Our studies indicate that each resin performs well for routine peptide synthesis by automated flow, whereas TentaGel XV resin showed the best performance for synthesis of difficult or long peptide sequences when comparing quality using yield, purity, and real‐time UV absorbance monitoring during synthesis.

I-Sample: Augment Domain Adversarial Adaptation Models for WiFi-based HAR

Recently, using deep learning to achieve WiFi-based human activity recognition (HAR) has drawn significant attention. While capable of achieving accurate identification in a single domain (i.e., training and testing in the same consistent WiFi environment), it would become extremely tough when WiFi environments change significantly. As such, domain adversarial neural networks-based approaches have been proposed to handle such diversities across domains, yet often found to share the same limitation in practice: the imbalance between high-capacity of feature extractors and data insufficiency of source domains. This article proposes i-Sample, an intermediate sample generation-based framework, striving to tackle this issue for WiFi-based HAR. i-Sample is mainly designed as two-stage training, where four data augmentation operations are proposed to train a coarse domain-invariant feature extractor in the first stage. In the second stage, we leverage the gradients of classification error to generate intermediate samples to refine the classifiers together with original samples, making i-Sample also capable to be integrated into most domain adversarial adaptation methods without neural network modification. We have implemented a prototype system to evaluate i-Sample, which shows that i-Sample can effectively augment the performance of nowadays mainstream domain adversarial adaptation models for WiFi-based HAR, especially when source domain data is insufficient.

Preliminary Magnetic Mineralogical Studies of Lake Beloe Sediments (Southern Siberia, Russia)

This article overviews the results of a preliminary magnetic and mineralogical study of the bottom sediments of Lake Beloe (Southern Siberia, Russia). The magnetic and mineralogical properties of the sediments were examined. Their variations were correlated with geological factors. A comprehensive magnetic survey was performed: magnetic susceptibility of samples extracted from three sediment cores was measured; normal remanent magnetization in a continuously increasing external magnetic field of up to 1.5 T was calculated; differential thermomagnetic analysis was carried out based on induced magnetization and scanning electron microscopy (SEM) for certain samples. The magnetic component was divided into three subcomponents based on the normal magnetization curves: ferromagnetic, dia-/paramagnetic, and superparamagnetic. The contribution of each subcomponent to the total magnetization was determined. It was found that the magnetic susceptibility values correlate well across all the studied cores, thus making it possible to compare them. Magnetite and pyrite turned out to be the magnetic minerals distributed throughout almost the entire section. In the Day–Dunlop plot, the studied samples are represented by single-domain (SD) and pseudo–single-domain (PSD) grains. The magnetic components vary consistently along the section, suggesting that the depositional environment underwent substantial changes. Particles similar in composition and morphology to cosmogenic and volcanic spherules were discovered using the SEM method. Based on the obtained results, the boundary between the Pleistocene and Holocene deposits was defined.

In-bulk polarization reversal in lithium tantalate with single charged domain wall

This paper presents the results of the first experimental observation of polarization reversal in the bulk of ferroelectric with a charged domain wall (CDW) under the action of an electric field on the example of a single crystal LiTaO3 plate. A CDW was obtained in the sample bulk at the locus of points with a sign change of the composition gradient which results from sample annealing in lithium rich atmosphere. Imaging of the domain structure in the bulk and its evolution on the surface made it possible to detect anomalous domain kinetics, which represents the growth of ledges on the CDW toward the polar surface. The main stages of the domain structure evolution on the polar surface, including the growth of isolated domains, as well as the formation and decay of the maze domain structure, were revealed. An analysis is made for the time dependence of the area fraction occupied by growing domains. We used a kinetic approach based on the analogy between the growth of domains and crystals to explain the obtained results.

A multi-embedding domain video steganography algorithm based on TU partitioning and intra prediction mode

With High Efficiency Video Coding (HEVC) becoming a popular video coding standard in the world, combing the HEVC with data hiding methods is a complex task. In this paper, a multi-embedded video steganography algorithm based on Intra Prediction Mode (IPM) and Transform Unit (TU) partition is proposed. By analyzing the coding characteristics of the TU partition and the IPM, we select embedded regions that are relatively independent as much as possible. Then, suitable distortion functions are designed for different embedding domains. Using the minimum distortion framework of the STC model to embed messages. The experimental results indicate that the proposed method achieves a maximum embedding capacity 1.5 times larger than that of traditional single domain embedding methods, while maintaining good visual quality.

A novel time-frequency slice extraction method for target recognition and local enhancement of non-stationary signal features

Blind deconvolution can remove the effects of complex paths and extraneous disturbances, thus recovering simple features of the original fault source, and is used extensively in the field of fault diagnosis. However, it can only identify and extract the statistical mean of the fault impact features in a single domain and is unable to simultaneously highlight the local features of the signal in the time-frequency domain. Therefore, the extraction effect of weak fault signals is generally not ideal. In this paper, a new time-frequency slice extraction method is proposed. The method first computes a high temporal resolution spectrum of the signal by short-time Fourier transform to obtain multiple frequency slices with distinct temporal waveforms. Subsequently, the constructed harmonic spectral feature index is used to quantify and target the intensity of feature information in each frequency slice and enhance their fault characteristics using maximum correlation kurtosis deconvolution. Enhancing the local features of selected frequency slice clusters can reduce noise interference and obtain signal components with more obvious fault signatures. Finally, the validity of the method was confirmed by a simulated signal and fault diagnosis of the rolling bearing outer and inner rings was accomplished sequentially. Compared with other common deconvolution methods, the proposed method obtains more accurate and effective results in identifying fault messages.

Globin phylogeny, evolution and function, the newest update.

Our globin census update allows us to refine our vision of globin origin, evolution, and structure to function relationship in the context of the currently accepted tree of life. The modern globin domain originates as a single domain, three-over-three α-helical folded structure before the diversification of the kingdoms of life (Bacteria, Archaea, Eukarya). Together with the diversification of prokaryotes, three monophyletic globin families (M, S, and T) emerged, most likely in Proteobacteria and Actinobacteria, displaying specific sequence and structural features, and spread by vertical and horizontal gene transfer, most probably already present in the last universal common ancestor (LUCA). Non-globin domains were added, and eventually lost again, creating multi-domain structures in key branches of M- (FHb and Adgb) and the vast majority of S globins, which with their coevolved multi-domain architectures, have predominantly "sensor" functions. Single domain T-family globins diverged into four major groups and most likely display functions related to reactive nitrogen and oxygen species (RNOS) chemistry, as well as oxygen storage/transport which drives the evolution of its major branches with their characteristic key distal residues (B10, E11, E7, and G8). M-family evolution also lead to distinctive major types (FHb and Fgb, Ngb, Adgb, GbX vertebrate Gbs), and shows the shift from high oxygen affinity controlled by TyrB10-Gln/AsnE11 likely related to RNOS chemistry in microorganisms, to a moderate oxygen affinity storage/transport function controlled by hydrophobic B10/E11-HisE7 in multicellular animals.

Impact of tissue penetration and albumin binding on design of T cell targeted bispecific agents

Bispecific agents are a rapidly growing class of cancer therapeutics, and immune targeted bispecific agents have the potential to expand functionality well beyond monoclonal antibody agents. Humabodies⁎⁎Humabody® is a registered trademark of Crescendo Biologics Ltd. are fully human single domain antibodies that can be linked in a modular fashion to form multispecific therapeutics. However, the effect of heterogeneous delivery on the efficacy of crosslinking bispecific agents is currently unclear. In this work, we utilize a PSMA-CD137 Humabody with an albumin binding half-life extension (HLE) domain to determine the impact of tissue penetration on T cell activating bispecific agents. Using heterotypic spheroids, we demonstrate that increased tissue penetration results in higher T cell activation at sub-saturating concentrations. Next, we tested the effect of two different albumin binding moieties on tissue distribution using albumin-specific HLE domains with varying affinities for albumin and a non-specific lipophilic dye. The results show that a specific binding mechanism to albumin does not influence tissue penetration, but a non-specific mechanism reduced both spheroid uptake and distribution in the presence of albumin. These results highlight the potential importance of tissue penetration on bispecific agent efficacy and describe how the design parameters including albumin-binding domains can be selected to maximize the efficacy of bispecific agents.

The juxtamembrane linker of synaptotagmin 1 regulates Ca2+ binding via liquid-liquid phase separation

Synaptotagmin (syt) 1, a Ca2+ sensor for synaptic vesicle exocytosis, functions in vivo as a multimer. Syt1 senses Ca2+ via tandem C2-domains that are connected to a single transmembrane domain via a juxtamembrane linker. Here, we show that this linker segment harbors a lysine-rich, intrinsically disordered region that is necessary and sufficient to mediate liquid-liquid phase separation (LLPS). Interestingly, condensate formation negatively regulates the Ca2+-sensitivity of syt1. Moreover, Ca2+ and anionic phospholipids facilitate the observed phase separation, and increases in [Ca2+]i promote the fusion of syt1 droplets in living cells. Together, these observations suggest a condensate-mediated feedback loop that serves to fine-tune the ability of syt1 to trigger release, via alterations in Ca2+ binding activity and potentially through the impact of LLPS on membrane curvature during fusion reactions. In summary, the juxtamembrane linker of syt1 emerges as a regulator of syt1 function by driving self-association via LLPS.

Parametric investigation and optimization of phase change material-based thermal energy storage integrated desiccant coated energy exchanger through physics informed neural networks oriented deep learning approach

To improve the energy exchange abilities, and to enhance indoor air quality, a desiccant-coated energy exchanger (DCEE) is a capable substitute compared to conventional energy exchangers such as fixed beds and desiccant wheels. Thus, accurately predicting the DCEE's physical characteristics is crucial for enhancing the system's performance. Therefore, in the current study, a novel data-driven modeling methodology utilizing physics-informed neural networks (PINNs) is developed to predict the exit parameters of DCEE, like the outlet temperature of cooling water, the outlet temperature of the air, and the outlet-specific humidity of the air. The performance characteristics of DCEE are evaluated using PINN by considering different input parameters. The performance parameters selected for the DCEE performance assessment are dehumidification capacity, thermal coefficient of performance, and heat recovery efficiency. The coated desiccant material chosen for the present study is silica gel. Good agreement is obtained between the PINN and experimental results for both the steady-state and transient cases, proving the PINN method's capability in solving multiple physics-based partial differential equations (PDEs) on a single domain with a maximum discrepancy of ±7.8 %. The developed model is used to obtain the optimal inlet conditions for a given operating condition. Adsorption kinetics of the coated desiccant silica gel revealed that the maximum water uptake capability for the given operating range is 0.345 g.g−1. A case study has been carried out by integrating an industrial waste heat-driven DCEE with a thermal energy storage module (TES) to analyze the energy storage ability during regeneration. A parametric study has been conducted to examine the transfer characteristics of the TES module. Further, the effectiveness of the TES module for five different phase change materials (PCMs) has been assessed. Finally, the seasonal energy efficacy ratio (SEER) of five different PCMs was investigated for 365 days to evaluate year-round performance. The effectiveness of thermal energy storage is maximum for Palmitic acid and minimum for Climsel C48, with corresponding values of 0.73 and 0.37. SEER is the largest for Palmitic acid and lowest for Climsel C48. The values of SEER for Palmitic acid during the summer and winter seasons are 5.489 and 3.31, whereas the values of SEER for Climsel C48 during the summer and winter seasons are 5 and 2.89, respectively.

Highly Ordered Monolayers of μm-Sized Polystyrene Spheres Studied by Grazing-Incidence Small-Angle X-ray Scattering, Simulations, and Geometrical Calculations.

Unraveling the two-dimensional (2D) structural ordering of colloidal particles assembled at a flat surface is essential for understanding and optimizing their physical properties. So far, grazing-incidence small-angle X-ray scattering (GISAXS) has been widely used to determine crystallographic information on 2D self-assembled structures of nanosize objects. However, solving the structure of 2D lattices consisting of micrometer (μm)-sized objects still remains a challenge using scattering methods. Here, a model 2D SCALMS (supported catalytically active liquid metal solution) template is fabricated from μm-sized polystyrene (PS) spheres that form a monolayer on top of the flat solid support. GISAXS patterns of the sample were collected for rotation angles around its surface normal in steps of 3°. For every rotation angle, different Bragg-type interference maxima along the out-of-plane (qz) direction were observed. On the basis of simulations of GISXAS patterns of single domains of ordered particle arrangements using the distorted wave Born approximation (DWBA) and validation against a simple geometrical scattering model, the interference maxima could nicely be interpreted to originate from a monolayer of the μm-sized spherical particles which are arranged in domains of hexagonal 2D paracrystalline order. This novel GISAXS evaluation technique serves as a proof of principle for determining the μm-size periodicity of 2D crystalline domains and demonstrates its potential to spatially resolve the relative orientations of such domains with respect to a reference direction.

Genome-wide identification, characterization, and expression analysis of m6A readers-YTH domain-containing genes in alfalfa

Eukaryotic messenger RNAs (mRNAs) are often modified with methyl groups at the N6 position of adenosine (m6A), and these changes are interpreted by YTH domain-containing proteins to regulate the metabolism of m6A-modified mRNAs. Although alfalfa (Medicago sativa) is an established model organism for forage development, the understanding of YTH proteins in alfalfa is still limited. In the present investigation, 53 putative YTH genes, each encoding a YT521 domain-containing protein, were identified within the alfalfa genome. These genes were categorized into two subfamilies: YTHDF (49 members) and YTHDC (four members). Each subfamily demonstrates analogous motif distributions and domain architectures. Specifically, proteins encoded by MsYTHDF genes incorporate a single domain structure, while those corresponding to MsYTH5, 8, 12, 16 who are identified as members of the MsYTHDC subfamily, exhibit CCCH-type zinc finger repeats at their N-termini. It is also observed that the predicted aromatic cage pocket that binds the m6A residue of MsYTHDC consists of a sequence of two tryptophan residues and one tyrosine residue (WWY). Conversely, in MsYTHDF, the binding pocket comprises two highly conserved tryptophan residues and either one tryptophan residue (WWW) or tyrosine residue (WWY) in MsYTHDF.Through comparative analysis of qRT-PCR data, we observed distinct expression patterns in specific genes under abiotic stress, indicating their potential regulatory roles. Notably, five genes (MsYTH2, 14, 26, 27, 48) consistently exhibit upregulation, and two genes (MsYTH33, 35) are downregulated in response to both cold and salt stress. This suggests a common mechanism among these YTH proteins in response to various abiotic stressors in alfalfa. Further, integrating qRT-PCR with RNA-seq data revealed that MsYTH2, MsYTH14, and MsYTH16 are highly expressed in leaves at various development stages, underscoring their potential roles in regulating the growth of these plant parts. The obtained findings shed further light on the biological functions of MsYTH genes and may aid in the selection of suitable candidate genes for future genetic enhancement endeavors aimed at improving salt and cold tolerance in alfalfa.

Evolution of protein domain repertoires of CALHM6.

Calcium (Ca2+) homeostasis is essential in conducting various cellular processes including nerve transmission, muscular movement, and immune response. Changes in Ca2+concentration in the cytoplasm are significant in bringing about various immune responses such as pathogen clearance and apoptosis. Various key players are involved in calcium homeostasis such as calcium binders, pumps, and channels. Sequence-based evolutionary information has recently been exploited to predict the biophysical behaviors of proteins, giving critical clues about their functionality. Ion channels are reportedly the first channels developed during evolution. Calcium homeostasis modulator protein 6 (CALHM6) is one such channel. Comprised of a single domain called Ca_hom_mod, CALHM6 is a stable protein interacting with various other proteins in calcium regulation. No previous attempt has been made to trace the exact evolutionary events in the domain of CALHM6, leaving plenty of room for exploring its evolution across a wide range of organisms. The current study aims to answer the questions by employing a computational-based strategy that used profile Hidden Markov Models (HMMs) to scan for the CALHM6 domain, integrated the data with a time-calibrated phylogenetic tree using BEAST and Mesquite, and visualized through iTOL. Around 4,000 domains were identified, and 14,000 domain gain, loss, and duplication events were observed at the end which also included various protein domains other than CALHM6. The data were analyzed concerning CALHM6 evolution as well as the domain gain, loss, and duplication of its interacting partners: Calpain, Vinculin, protein S100-A7, Thioredoxin, Peroxiredoxin, and Calmodulin-like protein 5. Duplication events of CALHM6 near higher eukaryotes showed its increasing complexity in structure and function. This in-silico phylogenetic approach applied to trace the evolution of CALHM6 was an effective approach to get a better understanding of the protein CALHM6.

A single domain antibody-based Luminex assay for the detection of SARS-CoV-2 in clinical samples.

Within the past decade, single domain antibodies (sdAbs) have been recognized as unique affinity binding reagents that can be tailored for performance in a variety of immunoassay formats. Luminex MagPlex color-coded magnetic microspheres provide a high-throughput platform that enables multiplexed immunoassays. We developed a MagPlex bead-based assay for the detection of SARS-CoV-2, using sdAbs against SARS-CoV-2 nucleocapsid (N) protein in which we engineered the sdAb capture reagents to orient them on the beads. The oriented sdAbs provided an increase in sensitivity over randomly oriented sdAbs for samples of N diluted in buffer, which also translated into better detection of SARS-CoV-2 in clinical samples. We assessed the specificity of the assay by examining seasonal coronavirus clinical samples. In summary, we provide a proof-of-concept that a bead-based assay using sdAbs to detect SARS-CoV-2 is feasible and future research combining it with other sdAb-coated beads that can detect other viruses may provide a useful diagnostic tool.

Unsupervised CT Metal Artifact Reduction by Plugging Diffusion Priors in Dual Domains.

During the process of computed tomography (CT), metallic implants often cause disruptive artifacts in the reconstructed images, impeding accurate diagnosis. Many supervised deep learning-based approaches have been proposed for metal artifact reduction (MAR). However, these methods heavily rely on training with paired simulated data, which are challenging to acquire. This limitation can lead to decreased performance when applying these methods in clinical practice. Existing unsupervised MAR methods, whether based on learning or not, typically work within a single domain, either in the image domain or the sinogram domain. In this paper, we propose an unsupervised MAR method based on the diffusion model, a generative model with a high capacity to represent data distributions. Specifically, we first train a diffusion model using CT images without metal artifacts. Subsequently, we iteratively introduce the diffusion priors in both the sinogram domain and image domain to restore the degraded portions caused by metal artifacts. Besides, we design temporally dynamic weight masks for the image-domian fusion. The dual-domain processing empowers our approach to outperform existing unsupervised MAR methods, including another MAR method based on diffusion model. The effectiveness has been qualitatively and quantitatively validated on synthetic datasets. Moreover, our method demonstrates superior visual results among both supervised and unsupervised methods on clinical datasets. Codes are available in github.com/DeepXuan/DuDoDp-MAR.

Modern sedimentation in lakes Chukcha and Bezymyanka, Okhotsk coast

Lakes Chukcha (59°31’56” N; 147° 23’07” E) and Bezymyanka (59°29’56” N; 147°21’02” E) located in the Kava-Taui depression, in the norther cost of Sea of Okhotsk. The thickness of the sediments, rock magnetic properties, sedimentation rates in both lakes are different. The surface bottom sediments of Chukcha lake are heterogeneous in grain composition. The rock magnetic properties of surface sediments are controlled by the grain size. The shallow water sandy sediments show the low of MS, Jrs, Js, and high values of Jp while silt have opposite characteristics. Magnetic minerals from silt are single domain with low content of paramagnetic component. The magnetic properties of fine-grained sediments may be associated with the authigenic (hemogenic) iron sulfides and oxides.

Learning Cross-Domain Features With Dual-Path Signal Transformer.

The past decade has witnessed the rapid development of deep neural networks (DNNs) for automatic modulation classification (AMC). However, most of the available works learn signal features from only a single domain via DNNs, which is not reliable enough to work in uncertain and complex electromagnetic environments. In this brief, a new cross-domain signal transformer (CDSiT) is proposed for AMC, to explore the latent association between different domains of signals. By constructing a signal fusion bottleneck (SFB), CDSiT can implicitly fuse and classify signal features with complementary structures in different domains. Extensive experiments are performed on RadioML2016.10A and RadioML2018.01A, and the results show that CDSiT outperforms its counterparts, particularly for some modulation modes that are difficult to classify before. Through ablation experiences, we also verify the effectiveness of each module in CDSiT.

Analysis of electromechanical coupling vibration characteristics of motor-gear system based on bond graph theory

In recent years, there has been a growing demand in the field of engineering systems for research on the vibration response of motor-gear systems under non-steady state conditions. However, conventional modeling and simulation techniques are primarily restricted to systems within a single energy domain. When dealing with intricate electromechanical coupling systems, the modeling process becomes increasingly intricate. Consequently, this study adopts bond graph theory as the foundation for analyzing the vibration characteristics of motor-gear coupling systems. In addressing the vibration issue of the motor-gear transmission system, a nonlinear bond graph model is established that takes into account the time-varying mesh stiffness, static errors, and tooth surface friction, among other nonlinear factors. Then, according to the coupling relationship between motor mechanical systems and electrical systems, the electromechanical coupling dynamic model of the motor-gear system is established using the method of bond graph. In addition, the state equation of the system is derived based on the bond graph model. Finally, the system is simulated using 20-sim software, and the electromechanical coupled vibration characteristics of the simulation results are analyzed. This article lays the foundation for the design and analysis of motor-gear coupling systems and multi-energy domain complex systems.