Structural Discrepancies Research Articles

Stratified burn severity assessment by integrating spaceborne spectral and waveform attributes in Great Xing'an Mountain

Burn severity assessment is critical for understanding the pattern of post-fire vegetation recovery and ecosystem resilience. Previous studies proposed various field criteria (e.g., Composite Burn Index (CBI)) to quantify burn severity from strata level to total site level, yet suffering from surveyors' subjective interpretation across site conditions. High-resolution passive remote sensing allows for more objective assessment based on the strong relation between fire damages and spectral features. Importantly, burn severity generally characterizes differences between forest overstory and understory layers due to their discrepancies in vegetation structures and environmental conditions. Spatially explicit mapping of strata-level burn severity is vital for post-fire forest management and ecological function evaluation. Until now, almost no available spaceborne remote sensing method can concurrently assess overstory and understory burn severity over heterogeneous forests. In this study, we proposed a Hybrid Composite Burn Index (HCBI) that comprehensively indicates the fire-induced spectral and structural changes along the vertical profile by integrating spectral and waveform attributes from both active and passive remote sensing data. Firstly, we introduced two remote sensing-based rating factors namely relative spectral change (RSC) and relative waveform change (RWC), and established HCBI through weighting and scoring the rating factors. Subsequently, we evaluated the effectiveness and generality of overstory, understory, and total site HCBI based on various pairs of simulated remote sensing data of pre-fire and post-fire forest scenes. Thirdly, we derived the spatially discontinuous maps of overstory, understory, and total site HCBI of the Xiushan fire site in Great Xing'an Mountain using WorldView-2 (WV-2) multispectral imagery and Global Ecosystem Dynamics Investigation (GEDI) full-waveform LiDAR data. Finally, we produced wall-to-wall HCBI maps using multiple predictive variables from pre-fire and post-fire Sentinel-2 MultiSpectral Instrument (MSI) images with a Random Forest (RF) algorithm. The predicted overstory, understory, and total site HCBI were validated by field-surveyed CBI. The assessment results based on simulation data showed HCBI was sensitive to the fire damage regardless of burn severity levels and vegetation cover levels (R2 of larger than 0.97 and RMSE of <0.15). The prediction results based on RF models achieved reliable HCBI of the total site, overstory, and understory levels (R2 of around 0.85 and RMSE of around 0.30). We found the wall-to-wall maps of HCBI captured the subtle horizontal and vertical variation even in the case of understory burn alone. We concluded that the newly proposed HCBI can advance the remote sensing-based assessment of stratified burn severity, offering opportunities for making fine-scale forest management decisions.

The Investigation of the Subtle Structural Discrepancies between Oryza Sativa Recombinant and Plasma-Derived Human Serum Albumins to Design a Novel Nanoparticle as a Taxane Delivery System.

To solve the large size faultiness of Oryza sativa recombinant human serum albumin nanoparticle (OsrHSA NP), the structural discrepancies between OsrHSA and plasma-derived human serum albumin (pdHSA) were analyzed deeply in this research. It demonstrated that there were some subtle structural discrepancies located in subdomain IA and IIA between OsrHSA and pdHSA, which included peptide backbone, disulphide bridge and some amino acids. Firstly, the structural discrepancies were investigated through literature comparison, it inferred that the structural discrepancies resulted from the fatty acid (FA) binding to OsrHSA at site 2 of subdomain IA and IIA. To form a cavity for accommodation of FA molecule in OsrHSA, the peptide backbone structure of subdomain IA and IIA would change, accompanied by the conformational transition of disulphide bridges and side chain structure change of some amino acids in subdomain IA and IIA. These alterations induced the exposure of tryptophan (Trp) and tyrosine (Tyr) residues in subdomain IA and IIA and the decrease of net negative charges of molecular surface. The former would promote more OsrHSA molecules aggregate, and the latter would weaken the electrostatic repulsion. As a result, the size of OsrHSA NP was more extensive than that of pdHSA NP (175.84 ± 15.63nm vs. 31.67 ± 1.31nm) when the concentration of Dimethyl Sulphoxide (DMSO) was 30% (v/v). In this study, the experimental scheme of OsrHSA NP preparation was improved. There were two changes in the enhanced preparation scheme: pH 8.2 PBS buffer and 63% DMSO. It indicated that the improved OsrHSA NP carrier was comparable to the pdHSA NP carrier. The size and drug loading of paclitaxel-loaded improved OsrHSA NP were 53.57 ± 3.63nm and 7.25 ± 0.46% (w/w), and those of docetaxel-loaded improved OsrHSA NP were 44.75 ± 2.26nm and 8.43 ± 0.74% (w/w). Moreover, both NPs exhibited good stability for 168h at 7.4 pH values. It is established that the improved OsrHSA NP is comparable to the pdHSA NP as a taxane delivery system.

Investigation of long-term anti-sulfur and deactivation mechanism of monolithic Mn-Fe-Ce/Al2O3 catalysts for NH3-SCR: Changes in physicochemical and adsorption properties

Owing to the different reaction properties and deactivation mechanisms caused by the structural discrepancy of monolithic catalysts, abundant scientific results of powder or granular NH3-SCR catalysts have still not sufficiently robustly applied in recent years. Furthermore, minimal research has been focused on monolithic catalysts. As a result, this work prepared monolithic Mn-Fe-Ce/Al2O3 catalysts by active component impregnation (ACI-Mn-Fe-Ce/Al2O3) and precursor impregnation methods (PI-Mn-Fe-Ce/Al2O3) and investigates the long-term SO2 and H2O resistance of the catalysts. Compared with the PI-Mn-Fe-Ce/Al2O3 catalyst, the monolithic ACI-Mn-Fe-Ce/Al2O3 catalyst showed better performance. The catalytic activity follows a bell-shaped curve with an optimal performance at a drug loading of 5 %. The ACI-Mn-Fe-Ce/Al2O3 catalyst exhibits long-term resistance to SO2 and H2O and can still convert more than 70 % NOx after 168 h of SO2 and H2O resistance test. Characterization of the ACI-Mn-Fe-Ce/Al2O3 catalysts before and after the reaction showed that the reducibility decreased after the reaction, and more Mn4+ was transformed into Mn2+ to weaken the catalytic activity. However, more Fe2+ and Ce3+ were generated during the reaction, increasing the number of oxygen vacancies, oxygen defects, and hydroxyl-like groups, all of which would contribute to a certain extent to counteract the passivation effect of SO2 on the catalysts. In situ DRIFTs analysis shows that the formation of surface sulfates has a minimal effect on the adsorption of NO, but it does affect the adsorption of coordinated NH3 on Lewis acid sites. This work elucidates the deactivation details of Mn-Fe-Ce/Al2O3 catalysts from the perspective of physicochemical properties, which provides a reference for the development of better low-temperature SO2-resistance catalysts for industrial applications.

Adaptive Feature Imputation with Latent Graph for Deep Incomplete Multi-View Clustering

In recent years, incomplete multi-view clustering (IMVC), which studies the challenging multi-view clustering problem on missing views, has received growing research interests. Previous IMVC methods suffer from the following issues: (1) the inaccurate imputation for missing data, which leads to suboptimal clustering performance, and (2) most existing IMVC models merely consider the explicit presence of graph structure in data, ignoring the fact that latent graphs of different views also provide valuable information for the clustering task. To overcome such challenges, we present a novel method, termed Adaptive feature imputation with latent graph for incomplete multi-view clustering (AGDIMC). Specifically, it captures the embbedded features of each view by incorporating the view-specific deep encoders. Then, we construct partial latent graphs on complete data, which can consolidate the intrinsic relationships within each view while preserving the topological information. With the aim of estimating the missing sample based on the available information, we utilize an adaptive imputation layer to impute the embedded feature of missing data by using cross-view soft cluster assignments and global cluster centroids. As the imputation progresses, the portion of complete data increases, contributing to enhancing the discriminative information contained in global pseudo-labels. Meanwhile, to alleviate the negative impact caused by inferior impute samples and the discrepancy of cluster structures, we further design an adaptive imputation strategy based on the global pseudo-label and the local cluster assignment. Experimental results on multiple real-world datasets demonstrate the effectiveness of our method over existing approaches.

Mixed matrix membranes based on morpholinium-functionalized CardoPES and MgAl-LDH: Structures, properties and electrodialysis performance

A simple, inexpensive, and effective method based on the MMMs prepared from morpholinium-functionalized CardoPES and MgAl-LDHs is proposed to improve the ED capabilities of AEMs. The microphase separation and ED performance of mixed matrix AEMs were substantially enhanced by LDH introduction, which was attributed to the surface OH groups of the LDH nanosheets; these interactions induced polymer chain self-assembly. The AEM with 8 % LDH exhibited the highest salt flux (92.5 mg/m2·s) during ED, which was 19.6 % and 14.1 % greater than those of the commercial Type 10 membrane and the mixed matrix AEM, respectively. Hydrogen bonding interactions and the ED capabilities of the AEMs were readily regulated by adjusting the feed ratios of the LDH and morpholinium groups. With increasing LDH content, the Rm and ED performance increased, while the hydrophilicity and mechanical properties initially decreased. When the OH content of an LDH nanosheet was higher than the morpholinium content, as the LDH content increased, the Rm and ED performance decreased, while the hydrophilicity and mechanical properties increased, which may be attributed to internal structural discrepancies between the complete and incomplete core-shell structures of the AEMs caused by different hydrogen bonding patterns.

Biochemical and structural characterization of chlorhexidine as an ATP-assisted inhibitor against type 1 methionyl-tRNA synthetase from Gram-positive bacteria

Methionyl-tRNA synthetase (MetRS) catalyzes the attachment of l-methionine (l-Met) to tRNAMet to generate methionyl-tRNAMet, an essential substrate for protein translation within ribosome. Owing to its indispensable biological function and the structural discrepancies with human counterpart, bacterial MetRS is considered an ideal target for developing antibacterials. Herein, chlorhexidine (CHX) was identified as a potent binder of Staphylococcus aureus MetRS (SaMetRS) through an ATP-aided affinity screening. The co-crystal structure showed that CHX simultaneously occupies the enlarged l-Met pocket (EMP) and the auxiliary pocket (AP) of SaMetRS with its two chlorophenyl groups, while its central hexyl linker swings upwards to interact with some conserved hydrophobic residues. ATP adopts alternative conformations in the active site cavity, and forms ionic bonds and water-mediated hydrogen bonds with CHX. Consistent with this synergistic binding mode, ATP concentration-dependently enhanced the binding affinity of CHX to SaMetRS from 10.2 μM (no ATP) to 0.45 μM (1 mM ATP). While it selectively inhibited two representative type 1 MetRSs from S. aureus and Enterococcus faecalis, CHX did not show significant interactions with three tested type 2 MetRSs, including human cytoplasmic MetRS, in the enzyme inhibition and biophysical binding assays, probably due to the conformational differences between two types of MetRSs at their EMP and AP. Our findings on CHX may inspire the design of MetRS-directed antimicrobials in future.

Distributional Learning for Network Alignment with Global Constraints

Network alignment, pairing corresponding nodes across the source and target networks, plays an important role in many data mining tasks. Extensive studies focus on learning node embeddings across different networks in a unified space. However, these methods have not taken the large structural discrepancy between aligned nodes into account and, thus, are largely confined by the deterministic representations of nodes. In this work, we propose a novel network alignment framework highlighted by distributional learning and globally optimal alignment. By modeling the uncertainty of each node by Gaussian distribution, our framework builds similarity matrices on the Wasserstein distance between distributions and applies Sinkhorn operation, which learns the globally optimal mapping in an end-to-end fashion. We show that each integrated part of the framework contributes to the overall performance. Under a variety of experimental settings, our alignment framework shows superior accuracy and efficiency to the state-of-the-art.

Enhanced residual convolutional domain adaptation network with CBAM for RUL prediction of cross-machine rolling bearing

Remaining useful life (RUL) prediction of rolling bearing is one of the important measures to ensure the reliable operation of mechanical equipment. Most of the existing methods are domain adaptation (DA) based RUL prediction on the same machine with different conditions, but few on cross-machine. DA can cope with the data distribution discrepancy (domain shift) under different machines or other conditions, but the potential negative transfer will affect the effect of DA and prediction performance. Therefore, an enhanced residual convolutional domain adaptation network (ERCDAN) is designed for cross-machine rolling bearing RUL prediction. Firstly, the enhanced residual convolutional module (ERCM) is designed for degradation feature extraction from limited data, and with the convolutional block attention module (CBAM) to enhance the extracted features. Secondly, the DA module with a collaborative full connection structure and attenuation multi-kernel maximum mean discrepancy is designed for mitigating negative transfer to effective domain-invariant feature extraction. Finally, the experimental analysis of cross-machine rolling bearing RUL prediction is conducted on the PHM2012, XJTU-SY, and EBFL datasets. The results show that the proposed method can not only effectively achieve cross-machine RUL prediction, but also has good cross-bearing prediction performance with different conditions on the same machine, reflecting good generalization performance.

Substrate promiscuity of Dicer toward precursors of the let-7 family and their 3′-end modifications

The human let-7 miRNA family consists of thirteen members that play critical roles in many biological processes, including development timing and tumor suppression, and their levels are disrupted in several diseases. Dicer is the endoribonuclease responsible for processing the precursor miRNA (pre-miRNA) to yield the mature miRNA, and thereby plays a crucial role in controlling the cellular levels of let-7 miRNAs. It is well established that the sequence and structural features of pre-miRNA hairpins such as the 5′-phosphate, the apical loop, and the 2-nt 3′-overhang are important for the processing activity of Dicer. Exceptionally, nine precursors of the let-7 family (pre-let-7) contain a 1-nt 3′-overhang and get mono-uridylated in vivo, presumably to allow efficient processing by Dicer. Pre-let-7 are also oligo-uridylated in vivo to promote their degradation and likely prevent their efficient processing by Dicer. In this study, we systematically investigated the impact of sequence and structural features of all human let-7 pre-miRNAs, including their 3′-end modifications, on Dicer binding and processing. Through the combination of SHAPE structural probing, in vitro binding and kinetic studies using purified human Dicer, we show that despite structural discrepancies among pre-let-7 RNAs, Dicer exhibits remarkable promiscuity in binding and cleaving these substrates. Moreover, the 1- or 2-nt 3′-overhang, 3′-mono-uridylation, and 3′-oligo-uridylation of pre-let-7 substrates appear to have little effect on Dicer binding and cleavage rates. Thus, this study extends current knowledge regarding the broad substrate specificity of Dicer and provides novel insight regarding the effect of 3′-modifications on binding and cleavage by Dicer.

Thermal performance of two evacuated tube solar collectors with flat heat pipes

To promote the transition to clean heating methods in rural areas and improve solar energy utilization efficiency, two new types of solar water collectors with evacuated tubes, namely finned and finless collectors, are constructed with multi-channel flat tubes and flat micro-heat pipe arrays, and comparison experiments are conducted. By integrating with multi-channel flat tubes, the micro-heat pipe arrays, which function as the central heat transfer component, are capable of attaining effective thermal transmission. The multi-channel flat tubes have a substantial surface area available for heat transfer with the thermal fluid, while the evacuated tubes exhibit superior thermal insulation performance. The structural discrepancy between the two collectors lies in the presence or absence of louvered fins attached to the flat heat pipes inside the evacuated tubes. The comparative analysis of the two collectors includes time constant, thermal resistance analysis, distribution of temperature, normalized temperature difference, pressure drop, and actual operation effect under different conditions. The average thermal efficiency of the finless collector (59.4 %) is lower than that of the finned collector (78.2 %) on a typical experimental day. Then, further investigations are conducted to explore the effects of heat transfer fluid volume flow rate and inlet temperature on the thermal performance of finned solar water collector. With the heat transfer fluid volume flow rate of 120 L/h and the inlet temperature at 15 °C, the finned collector can achieve its maximum thermal efficiency of 86.4 %.

Rotational spectroscopy of methyl tert-butyl ether with a new Ka band chirped-pulse Fourier transform microwave spectrometer.

Chirped-pulse Fourier transform microwave (CP-FTMW) spectroscopy is a powerful tool for performing broadband gas-phase rotational spectroscopy, and its applications include discovery of new molecules, complex mixture analysis, and exploration of fundamental molecular physics. Here we report the development of a new Ka band (26.5-40 GHz) CP-FTMW spectrometer that is equipped with a pulsed supersonic expansion source and a heated reservoir for low-volatility samples. The spectrometer is built around a 150 W traveling wave tube amplifier and has an instantaneous bandwidth that covers the entire Ka band spectral range. To test the performance of the spectrometer, the rotational spectrum of methyl tert-butyl ether (MTBE), a former gasoline additive and environmental pollutant, has been measured for the first time in this spectral range. Over 1000 spectroscopic transitions have been measured and assigned to the vibrational ground state and a newly-identified torsionally excited state; all transitions were fit using the XIAM program to a root-mean-square deviation of 22 kHz. The spectrum displays internal rotation splitting, nominally forbidden transitions, and an intriguing axis-switching effect between the ground and torsionally excited state that is a consequence of MTBE's extreme near-prolate nature. Finally, the sensitivity of the spectrometer enabled detection of all singly-substituted 13C and 18O isotopologues in natural abundance. This set of isotopic spectra allowed for a partial r0 structure involving the heavy atoms to be derived, resolving a structural discrepancy in the literature between previous microwave and electron diffraction measurements.

Community Preserving Social Recommendation with Cyclic Transfer Learning

Transfer learning-based recommendation mitigates the sparsity of user-item interactions by introducing auxiliary domains. Social influence extracted from direct connections between users typically serves as an auxiliary domain to improve prediction performance. However, direct social connections also face severe data sparsity problems that limit model performance. In contrast, users’ dependency on communities is another valuable social information that has not yet received sufficient attention. Although studies have incorporated community information into recommendation by aggregating users’ preferences within the same community, they seldom capture the structural discrepancies among communities and the influence of structural discrepancies on users’ preferences. To address these challenges, we propose a community-preserving recommendation framework with cyclic transfer learning, incorporating heterogeneous community influence into the rating domain. We analyze the characteristics of the community domain and its inter-influence on the rating domain, and construct link constraints and preference constraints in the community domain. The shared vectors that bridge the rating domain and the community domain are allowed to be more consistent with the characteristics of both domains. Extensive experiments are conducted on four real-world datasets. The results manifest the excellent performance of our approach in capturing real users’ preferences compared with other state-of-the-art methods.

Incorporating 2D porous organic polymer nanosheets into high-temperature proton-exchange membranes for low H3PO4 loss

Phosphoric acid (PA)-doped ion exchange membranes have been recognized as a classical high-temperature proton exchange membrane (HT-PEM) material. Nonetheless, the leaching of PA from membranes occurs progressively during operation, inevitably diminishing overall performance. In this study, we present a novel approach for crafting two-dimensional porous organic polymer nanosheets (NS-POPs) synthesized through nano-interfacial azo-coupling polymerization. The prepared NS-POPs possessed different pore structures with main pore sizes of 0.55 nm and 1.19 nm, which were derived from the discrepancy of monomer structure. Subsequently, the NS-POPs were successfully incorporated into polybenzimidazole to create mixed-matrix membranes due to the good interface compatibility, characterized by homogeneity and stability facilitated by the 2D nature of NS-POPs. As a comparison, POPs with non-2D properties prepared by the solution method cannot be successfully obtained in good MMMs due to poor dispersibility and interface compatibility. Furthermore, the profusion of pore structures and the presence of N/O-rich functional groups in NS-POPs significantly enhance their PA uptake capacity with up to 289 %, consequently boosting proton conductivity. As a result, the composite membrane doped with NS-POPs demonstrated a maximum conductivity of up to 143 mS cm−1 at 180 °C, which is approximately 2.97 times that of pure membrane. And the peak power density of H2/O2 fuel cell based on the composite membrane was 378 mW cm−2, which was higher than PBI. Most significantly, the confinement effect exerted by the small pores in NS-POPs enables composite membranes to maintain a higher PA retention of up to 74 % even after a 48 h of high-temperature and high-humidity treatment. Our study introduces an innovative and straightforward approach to synthesizing porous organic polymer nanosheets. This work not only advances the understanding of the impact of interface compatibility on composite membrane fabrication, but also establishes a versatile technology for modulating pore size and managing PA leaching in HT-PEMs.

Deciphering the Biophysical Properties of Ion Channel Gating Pores by Coumarin-Benzodiazepine Hybrid Derivatives: Selective AMPA Receptor Antagonists.

In the 1980s, the identification of specific pharmacological antagonists played a crucial role in enhancing our comprehension of the physiological mechanisms associated with α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptors (AMPARs). The primary objective of this investigation was to identify specific AMPA receptor antagonists, namely 2,3-benzodiazepines, that function as negative allosteric modulators (NAMs) at distinct locations apart from the glutamate recognition site. These compounds have exhibited a diverse array of anticonvulsant properties. In order to conduct a more comprehensive investigation, the study utilized whole-cell patch-clamp electrophysiology to analyze the inhibitory effect and selectivity of benzodiazepine derivatives that incorporate coumarin rings in relation to AMPA receptors. The study's main objective was to acquire knowledge about the relationship between the structure and activity of the compound and comprehend the potential effects of altering the side chains on negative allosteric modulation. The investigation provided crucial insights into the interaction between eight CD compounds and AMPA receptor subunits. Although all compounds demonstrated effective blockade, CD8 demonstrated the greatest potency and selectivity towards AMPA receptor subunits. The deactivation and desensitization rates were significantly influenced by CD8, CD6, and CD5, distinguishing them from the remaining five chemicals. The differences in binding and inhibition of AMPA receptor subunits can be attributed to structural discrepancies among the compounds. The carboxyl group of CD8, situated at the para position of the phenyl ring, substantially influenced the augmentation of AMPA receptor affinity. The findings of this study highlight the potential of pharmaceutical compounds that specifically target AMPA receptors to facilitate negative allosteric modulation.

A molecular simulation study of the clinical G409V mutant in PINK1 associated with early-onset Parkinson's disease

The serine/threonine kinase PINK1 is responsible for phosphorylating a ubiquitin (Ub)-like domain in an E3 Ub ligase Parkin protein and a Parkin-bound Ub. PINK1 works as a mitochondrial quality control by phosphorylating and activating the E3 ubiquitin ligase Parkin. Recent medicinal study has reported that mutations of Parkin and PINK1 cause defects in mitophagy and induce early-onset Parkinson's disease (EOPD). In this study, we conducted molecular dynamics simulations to investigate the structural discrepancy caused by a clinical G409V mutation in PINK1 kinase domain's A-loop. The Ub phosphorylation begins with PINK1 D362 deprotonating the hydroxyl group of the substrate Ub's S65′ and PINK1's A-loop is responsible for coordinating S65′. On contrary to G409 offering structural plasticity, the replaced, bulky V409 interferes with the alignment of D362-S65′, seriously hampering Ub phosphorylation, leading to the accumulation of damaged mitochondria, and ultimately EOPD. In this study, we predicted the hPINK1WT-UbWT binding mode and detected the structural impact brought by G409V replacement. It is expected the concluded remarks to be beneficial for developing cures to alleviate structural interference and restore PINK1 function.

Molecular engineering and bioimaging applications of C2-alkenyl indole dyes with tunable emission wavelengths covering visible to NIR light

As an important member of dyes, small-molecule fluorescent dyes show indispensable value in biomedical fields. Although various molecular dyes have been developed, full-color dyes covering blue to red region derived from a single chromophore are still in urgent demand. In this work, a series of dyes based on C2-alkenyl indole skeleton were synthesized, namely AI dyes, and their photophysical properties, cytotoxicity, and imaging capacity were verified to be satisfactory. Particularly, the maximal emission wavelengths of these dyes could cover a wide range from visible to NIR light with large Stokes shifts. Besides, the optical and structural discrepancies between the C2- and C3- alkenyl AI dyes were discussed in detail, and the theoretical calculations were conducted to provide insights on such structure–activity relationship. Finally, as a proof-of-concept, a fluorescent probe AI-Py-B capable of imaging endogenous ONOO− was presented, demonstrating the bioimaging potentials of these alkenyl indole dyes. This work is anticipated to open up new possibilities for developing dye engineering and bio-applications of natural indole framework.

Cellular insights of beech leaf disease reveal abnormal ectopic cell division of symptomatic interveinal leaf areas.

The beech leaf disease nematode, Litylenchus crenatae subsp. mccannii, is recognized as a newly emergent nematode species that causes beech leaf disease (BLD) in beech trees (Fagus spp.) in North America. Changes of leaf morphology before emergence from the bud induced by BLD can provoke dramatic effects on the leaf architecture and consequently to tree performance and development. The initial symptoms of BLD appear as dark green, interveinal banding patterns of the leaf. Despite the fast progression of this disease, the cellular mechanisms leading to the formation of such aberrant leaf phenotype remains totally unknown. To understand the cellular basis of BLD, we employed several types of microscopy to provide an exhaustive characterization of nematode-infected buds and leaves. Histological sections revealed a dramatic cell change composition of these nematode-infected tissues. Diseased bud scale cells were typically hypertrophied and showed a high variability of size. Moreover, while altered cell division had no influence on leaf organogenesis, induction of cell proliferation on young leaf primordia led to a dramatic change in cell layer architecture. Hyperplasia and hypertrophy of the different leaf cell layers, coupled with an abnormal proliferation of chloroplasts especially in the mesophyll cell layers, resulted in the typical interveinal leaf banding. These discrepancies in leaf cell structure were depicted by an abnormal rate of cellular division of the leaf interveinal areas infected by the nematode, promoting significant increase of cell size and leaf thickness. The formation of symptomatic BLD leaves is therefore orchestrated by distinct cellular processes, to enhance the value of these feeding sites and to improve their nutrition status for the nematode. Our findings thus uncover relevant cellular events and provide a structural framework to understand this important disease.

Structural discrepancy and domain adversarial fusion network for cross-domain fault diagnosis

The current deep learning-based fault diagnosis methods have achieved excellent classification performance under supervised training, but the existence of domain discrepancy under different working conditions will greatly affect data relationship mining and fault diagnosis accuracy. Graph convolutional network (GCN) with topological structured relationships is excellent in solving these issues. In this paper, structural discrepancy and domain adversarial fusion network (SDDAFN) is proposed to learn deep high-dimensional features and eliminate distribution discrepancy across different domains. In data structure construction, the high-dimensional mapping features are first extracted accurately from the input raw signals by a feature encoder, then the output of encoder is converted into an instance graph through graph construction layer (GCL) for the convenient modeling by multi-channel kernel GCN (MCK-GCN). In network optimization, the classification loss function is introduced to optimize the discrimination boundaries of different fault types, and the integrated loss function based on structural discrepancy and domain adversarial are jointly adopted to minimize the domain distribution discrepancy. Experimental cases show the proposed method outperforms the state-of-the-art methods.

Relation between flexibility and intrinsically disorder regions in thermosensitive TRP channels reveal allosteric effects.

How a protein propagates the conformational changes throughout its structure remains largely unknown. In thermosensitive TRP channels, this allosteric communication is triggered by ligand interaction or in response to temperature changes. Because dynamic allostery suggests a dynamic role of disordered regions, in this work we set out to thoroughly evaluate these regions in six thermosensitive TRP channels. Thus, by contrasting the intrinsic flexibility of the transmembrane region as a function of the degree of disorder in those proteins, we discovered several residues that do not show a direct correlation in both parameters. This kind of structural discrepancy revealed residues that are either reported to be dynamic, functionally relevant or are involved in signal propagation and probably part of allosteric networks. These discrepant, potentially dynamic regions are not exclusive of TRP channels, as this same correlation was found in the Kv Shaker channel.

Simulated space environmental factors of weightlessness, noise and low atmospheric pressure differentially affect the diurnal rhythm and the gut microbiome

The circadian clock extensively regulates physiology and behavior. In space, astronauts encounter many environmental factors that are dramatically different from those on Earth; however, the effects of these factors on circadian rhythms and the mechanisms remain largely unknown. The present study aimed to investigate the changes in the mouse diurnal rhythm and gut microbiome under simulated space capsule conditions, including microgravity, noise and low atmospheric pressure (LAP). Noise and LAP were loaded in the capsule while the conditions in the animal room remained constant. The mice in the capsule showed disturbed locomotor rhythms and faster adaptation to a 6-h phase advance. RNA sequencing of hypothalamus samples containing the suprachiasmatic nucleus (SCN) revealed that microgravity simulated by hind limb unloading (HU) and exposure to noise and LAP led to decreases in the quantities of differentially expressed genes (DEGs), including circadian clock genes. Changes in the rhythmicity of genes implicated in pathways of cardiovascular deconditioning and more concentrated phases were found under HU or noise and LAP. Furthermore, 16S rRNA sequencing revealed dysbiosis in the gut microbiome, and noise and LAP may repress the temporal discrepancy in the microbiome community structure induced by microgravity. Changes in diurnal oscillations were observed in a number of gut bacteria with critical physiological consequences on metabolism and immunodefense. We also found that the superimposition of noise and LAP may repress normal changes in global gene expression and adaptation in the gut microbiome. Our data demonstrate that in addition to microgravity, exposure to noise and LAP affect the robustness of circadian rhythms and the community structure of the gut microbiome, and these factors may interfere with each other in their adaptation to respective conditions. These findings are important for furthering our understanding of the alterations in circadian rhythms in the complex environment of space.