Lipid Isobar and Isomer Imaging Using Nanospray Desorption Electrospray Ionization Combined with Triple Quadrupole Mass Spectrometry.

Mass spectrometry imaging (MSI) is widely used for examining the spatial distributions of molecules in biological samples. Conventional MSI approaches, in which molecules extracted from the sample are distinguished based on their mass-to-charge ratio, cannot distinguish between isomeric species and some closely spaced isobars. To facilitate isobar separation, MSI is typically performed using high-resolution mass spectrometers. Nevertheless, the complexity of the mixture of biomolecules observed in each pixel of the image presents a challenge, even for modern mass spectrometers with the highest resolving power. Herein, we implement nanospray desorption electrospray ionization (nano-DESI) MSI on a triple quadrupole (QqQ) mass spectrometer for the spatial mapping of isobaric and isomeric species in biological tissues. We use multiple reaction monitoring acquisition mode (MRM) with unit mass resolution to demonstrate the performance of this new platform by imaging lipids in mouse brain and rat kidney tissues. We demonstrate that imaging in MRM mode may be used to distinguish between isobaric phospholipids requiring a mass resolving power of 3,800,000. Additionally, we have been able to image eicosanoid isomers, a largely unexplored class of signaling molecules present in tissues at low concentrations, in rat kidney tissue. This new capability substantially enhances the specificity and selectivity of MSI, enabling spatial localization of species that remain unresolved in conventional MSI experiments.

Two-Dimensional SEC-SEC-UV-MALS-dRI Workflow for Streamlined Analysis and Characterization of Biopharmaceuticals.

The emergence of complex biological modalities in the biopharmaceutical industry entails a significant expansion of the current analytical toolbox to address the need to deploy meaningful and reliable assays at an unprecedented pace. Size exclusion chromatography (SEC) is an industry standard technique for protein separation and analysis. Some constraints of traditional SEC stem from its restricted ability to resolve complex mixtures and notoriously long run times while also requiring multiple offline separation conditions on different pore size columns to cover a wider molecular size distribution. Two-dimensional liquid chromatography (2D-LC) is becoming an important tool not only to increase peak capacity but also to tune selectivity in a single online method. Herein, an online 2D-LC framework in which both dimensions utilize SEC columns with different pore sizes is introduced with a goal to increase throughput for biomolecule separation and characterization. In addition to improving the separation of closely related species, this online 2D SEC-SEC approach also facilitated the rapid analysis of protein-based mixtures of a wide molecular size range in a single online experimental run bypassing time-consuming deployment of different offline SEC methods. By coupling the second dimension with multiangle light scattering (MALS) and differential refractive index (dRI) detectors, absolute molecular weights of the separated species were obtained without the use of calibration curves. As illustrated in this report for protein mixtures and vaccine processes, this workflow can be used in scenarios where rapid development and deployment of SEC assays are warranted, enabling bioprocess monitoring, purity assessment, and characterization.

Accelerating Pharmaceutical Process Development with an Acoustic Droplet Ejection-Multiple Reaction Monitoring-Mass Spectrometry Workflow.

Fast-paced pharmaceutical process developments (e.g., high-throughput experimentation, directed evolution, and machine learning) involve the introduction of fast, sensitive, and accurate analytical assays using limited sample volumes. In recent years, acoustic droplet ejection (ADE) coupled with an open port interface has been invented as a sampling technology for mass spectrometry, providing high-throughput nanoliter analytical measurements directly from the standard microplates. Herein, we introduce an ADE-multiple reaction monitoring-mass spectrometry (ADE-MRM-MS) workflow to accelerate pharmaceutical process research and development (PR&D). This systematic workflow outlines the selection of MRM transitions and optimization of assay parameters in a data-driven manner using rapid measurements (1 sample/s). The synergy between ADE sampling and MRM analysis enables analytical assays with excellent sensitivity, selectivity, and speed for PR&D reaction screenings. This workflow was utilized to develop new ADE-MRM-MS assays guiding a variety of industrial processes, including (1) screening of Ni-based catalysts for C-N cross-coupling reaction at 1 Hz and (2) high-throughput regioisomer analysis-enabled enzyme library screening for peptide ligation reaction. ADE-MRM-MS assays were demonstrated to deliver accurate results that are comparable to conventional liquid chromatography (LC) experiments while providing >100-fold throughput enhancement.

Collaborative Enhancement of Consistency and Accuracy in US Diagnosis of Thyroid Nodules Using Large Language Models.

Background Large language models (LLMs) hold substantial promise for medical imaging interpretation. However, there is a lack of studies on their feasibility in handling reasoning questions associated with medical diagnosis. Purpose To investigate the viability of leveraging three publicly available LLMs to enhance consistency and diagnostic accuracy in medical imaging based on standardized reporting, with pathology as the reference standard. Materials and Methods US images of thyroid nodules with pathologic results were retrospectively collected from a tertiary referral hospital between July 2022 and December 2022 and used to evaluate malignancy diagnoses generated by three LLMs-OpenAI's ChatGPT 3.5, ChatGPT 4.0, and Google's Bard. Inter- and intra-LLM agreement of diagnosis were evaluated. Then, diagnostic performance, including accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC), was evaluated and compared for the LLMs and three interactive approaches: human reader combined with LLMs, image-to-text model combined with LLMs, and an end-to-end convolutional neural network model. Results A total of 1161 US images of thyroid nodules (498 benign, 663 malignant) from 725 patients (mean age, 42.2 years ± 14.1 [SD]; 516 women) were evaluated. ChatGPT 4.0 and Bard displayed substantial to almost perfect intra-LLM agreement (κ range, 0.65-0.86 [95% CI: 0.64, 0.86]), while ChatGPT 3.5 showed fair to substantial agreement (κ range, 0.36-0.68 [95% CI: 0.36, 0.68]). ChatGPT 4.0 had an accuracy of 78%-86% (95% CI: 76%, 88%) and sensitivity of 86%-95% (95% CI: 83%, 96%), compared with 74%-86% (95% CI: 71%, 88%) and 74%-91% (95% CI: 71%, 93%), respectively, for Bard. Moreover, with ChatGPT 4.0, the image-to-text-LLM strategy exhibited an AUC (0.83 [95% CI: 0.80, 0.85]) and accuracy (84% [95% CI: 82%, 86%]) comparable to those of the human-LLM interaction strategy with two senior readers and one junior reader and exceeding those of the human-LLM interaction strategy with one junior reader. Conclusion LLMs, particularly integrated with image-to-text approaches, show potential in enhancing diagnostic medical imaging. ChatGPT 4.0 was optimal for consistency and diagnostic accuracy when compared with Bard and ChatGPT 3.5. © RSNA, 2024 Supplemental material is available for this article.

US-based Sequential Algorithm Integrating an AI Model for Advanced Liver Fibrosis Screening.

Background Noninvasive tests can be used to screen patients with chronic liver disease for advanced liver fibrosis; however, the use of single tests may not be adequate. Purpose To construct sequential clinical algorithms that include a US deep learning (DL) model and compare their ability to predict advanced liver fibrosis with that of other noninvasive tests. Materials and Methods This retrospective study included adult patients with a history of chronic liver disease or unexplained abnormal liver function test results who underwent B-mode US of the liver between January 2014 and September 2022 at three health care facilities. A US-based DL network (FIB-Net) was trained on US images to predict whether the shear-wave elastography (SWE) value was 8.7 kPa or higher, indicative of advanced fibrosis. In the internal and external test sets, a two-step algorithm (Two-step#1) using the Fibrosis-4 Index (FIB-4) followed by FIB-Net and a three-step algorithm (Three-step#1) using FIB-4 followed by FIB-Net and SWE were used to simulate screening scenarios where liver stiffness measurements were not or were available, respectively. Measures of diagnostic accuracy were calculated using liver biopsy as the reference standard and compared between FIB-4, SWE, FIB-Net, and European Association for the Study of the Liver guidelines (ie, FIB-4 followed by SWE), along with sequential algorithms. Results The training, validation, and test data sets included 3067 (median age, 42 years [IQR, 33-53 years]; 2083 male), 1599 (median age, 41 years [IQR, 33-51 years]; 1124 male), and 1228 (median age, 44 years [IQR, 33-55 years]; 741 male) patients, respectively. FIB-Net obtained a noninferior specificity with a margin of 5% (P < .001) compared with SWE (80% vs 82%). The Two-step#1 algorithm showed higher specificity and positive predictive value (PPV) than FIB-4 (specificity, 79% vs 57%; PPV, 44% vs 32%) while reducing unnecessary referrals by 42%. The Three-step#1 algorithm had higher specificity and PPV compared with European Association for the Study of the Liver guidelines (specificity, 94% vs 88%; PPV, 73% vs 64%) while reducing unnecessary referrals by 35%. Conclusion A sequential algorithm combining FIB-4 and a US DL model showed higher diagnostic accuracy and improved referral management for all-cause advanced liver fibrosis compared with FIB-4 or the DL model alone. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Ghosh in this issue.

ScCAEs: deep clustering of single-cell RNA-seq via convolutional autoencoder embedding and soft K-means.

Clustering and cell type classification are a vital step of analyzing scRNA-seq data to reveal the complexity of the tissue (e.g. the number of cell types and the transcription characteristics of the respective cell type). Recently, deep learning-based single-cell clustering algorithms become popular since they integrate the dimensionality reduction with clustering. But these methods still have unstable clustering effects for the scRNA-seq datasets with high dropouts or noise. In this study, a novel single-cell RNA-seq deep embedding clustering via convolutional autoencoder embedding and soft K-means (scCAEs) is proposed by simultaneously learning the feature representation and clustering. It integrates the deep learning with convolutional autoencoder to characterize scRNA-seq data and proposes a regularized soft K-means algorithm to cluster cell populations in a learned latent space. Next, a novel constraint is introduced to the clustering objective function to iteratively optimize the clustering results, and more importantly, it is theoretically proved that this objective function optimization ensures the convergence. Moreover, it adds the reconstruction loss to the objective function combining the dimensionality reduction with clustering to find a more suitable embedding space for clustering. The proposed method is validated on a variety of datasets, in which the number of clusters in the mentioned datasets ranges from 4 to 46, and the number of cells ranges from 90 to 30 302. The experimental results show that scCAEs is superior to other state-of-the-art methods on the mentioned datasets, and it also keeps the satisfying compatibility and robustness. In addition, for single-cell datasets with the batch effects, scCAEs can ensure the cell separation while removing batch effects.

Ischemic Heart-Derived Small Extracellular Vesicles Impair Adipocyte Function.

BACKGROUND: Patients with acute myocardial infarction suffer systemic metabolic dysfunction via incompletely understood mechanisms. Adipocytes play critical role in metabolic homeostasis. The impact of acute myocardial infarction upon adipocyte function is unclear. Small extracellular vesicles (sEVs) critically contribute to organ-organ communication. Whether and how small extracellular vesicle mediate post-MI cardiomyocyte/adipocyte communication remain unknown. METHODS: Plasma sEVs were isolated from sham control (Pla-sEVSham) or 3 hours after myocardial ischemia/reperfusion (Pla-sEVMI/R) and incubated with adipocytes for 24 hours. Compared with Pla-sEVSham, Pla-sEVMI/R significantly altered expression of genes known to be important in adipocyte function, including a well-known metabolic regulatory/cardioprotective adipokine, APN (adiponectin). Pla-sEVMI/R activated 2 (PERK-CHOP and ATF6 [transcription factor 6]-EDEM [ER degradation enhancing alpha-mannosidase like protein 1] pathways) of the 3 endoplasmic reticulum (ER) stress pathways in adipocytes. These pathological alterations were also observed in adipocytes treated with sEVs isolated from adult cardiomyocytes subjected to in vivo myocardial ischemia/reperfusion (MI/R) (Myo-sEVMI/R). Bioinformatic/RT-qPCR analysis demonstrates that the members of miR-23-27-24 cluster are significantly increased in Pla-sEVMI/R, Myo-sEVMI/R, and adipose tissue of MI/R animals. Administration of cardiomyocyte-specific miR-23-27-24 sponges abolished adipocyte miR-23-27-24 elevation in MI/R animals, supporting the cardiomyocyte origin of adipocyte miR-23-27-24 cluster. In similar fashion to Myo-sEVMI/R, a miR-27a mimic activated PERK-CHOP and ATF6-EDEM-mediated ER stress. Conversely, a miR-27a inhibitor significantly attenuated Myo-sEVMI/R-induced ER stress and restored APN production. RESULTS: An unbiased approach identified EDEM3 (ER degradation enhancing alpha-mannosidase like protein 3) as a novel downstream target of miR-27a. Adipocyte EDEM3 deficiency phenocopied multiple pathological alterations caused by Myo-sEVMI/R, whereas EDEM3 overexpression attenuated Myo-sEVMI/R-resulted ER stress. Finally, administration of GW4869 or cardiomyocyte-specific miR-23-27-24 cluster sponges attenuated adipocyte ER stress, improved adipocyte endocrine function, and restored plasma APN levels in MI/R animals. CONCLUSIONS: We demonstrate for the first time that MI/R causes significant adipocyte ER stress and endocrine dysfunction by releasing miR-23-27-24 cluster-enriched small extracellular vesicle. Targeting small extracellular vesicle-mediated cardiomyocyte-adipocyte pathological communication may be of therapeutic potential to prevent metabolic dysfunction after MI/R.

Spätzle maintains homeostasis of hemolymph microbiota in Scylla paramamosain through Toll2.

The Toll pathway is crucial for innate immune responses in organisms (including Drosophila and mammals). The Spätzle protein outside of cells acts as a ligand for Toll receptors, enabling the transfer of signals from outside the cell to the inside. However, the function of Spätzle in the immune system of mud crab (Scylla paramamosain) remains unclear. This research discovered a novel Spätzle gene (Sp-Spz) in mud crab, which showed extensive expression in all the tissues that were examined. The RNA interference exhibited the correlation between Sp-Spz and the anti-lipopolysaccharide factors (ALFs). Knockdown of Sp-Spz decreased the expression of Sp-Toll2 but not Sp-Toll1. In Drosophila Schneider 2 cells, Sp-Spz was found interacted with Sp-Toll2. Moreover, the depletion of Sp-Spz caused the separation of hepatic lobules from the basement membrane, resulting in the disruption of the structural coherence of hepatopancreatic cells. Additionally, the knockdown of Sp-Spz resulted in changes to the composition of the hemolymph microbiota, specifically affecting the proportions of different phylum and family levels. The findings indicated that Sp-Spz may promote the synthesis of ALFs via Sp-Toll2, thereby influencing the homeostasis of microbiota in the hemolymph. In this study, novel insights into mud crab immunity are provided.

Development and validation of a prospective study to predict the risk of readmission within 365 days of respiratory failure: based on a random survival forest algorithm combined with COX regression modeling.

BACKGROUND: There is a need to develop and validate a widely applicable nomogram for predicting readmission of respiratory failure patients within 365 days. METHODS: We recruited patients with respiratory failure at the First People's Hospital of Yancheng and the People's Hospital of Jiangsu. We used the least absolute shrinkage and selection operator regression to select significant features for multivariate Cox proportional hazard analysis. The Random Survival Forest algorithm was employed to construct a model for the variables that obtained a coefficient of 0 following LASSO regression, and subsequently determine the prediction score. Independent risk factors and the score were used to develop a multivariate COX regression for creating the line graph. We used the Harrell concordance index to quantify the predictive accuracy and the receiver operating characteristic curve to evaluate model performance. Additionally, we used decision curve analysiso assess clinical usefulness. RESULTS: The LASSO regression and multivariate Cox regression were used to screen hemoglobin, diabetes and pneumonia as risk variables combined with Score to develop a column chart model. The C index is 0.927 in the development queue, 0.924 in the internal validation queue, and 0.922 in the external validation queue. At the same time, the predictive model also showed excellent calibration and higher clinical value. CONCLUSIONS: A nomogram predicting readmission of patients with respiratory failure within 365 days based on three independent risk factors and a jointly developed random survival forest algorithm has been developed and validated. This improves the accuracy of predicting patient readmission and provides practical information for individualized treatment decisions.

Enhancement of Amplified Spontaneous Emission by Electric Field in CsPbBr3 Perovskites.

Perovskite gain materials can sustain continuous-wave lasing at room-temperature. A first step toward the unachieved goal of electrically excited lasing would be an improvement in gain when electrical stimulation is added to the optical. However, to date, electrical stimulation supplementing optical has reduced gain performance. We find that amplified spontaneous emission (ASE) in a CsPbBr3 perovskite light-emitting diode (LED) held under invariant subthreshold optical excitation can be turned on/off by the addition/removal of an electric field. A positive bias voltage leads to a factor of 3 reduction in the optical ASE threshold, the cause of which can be attributed to an enhancement of the radiative rate. The slow components (10 s time scale) of the modulation in the photoluminescence and ASE when the voltage is changed suggest that the relocation of mobile ions trigger the increased radiative rate and observed lowering of ASE thresholds.

Plant associated protists-Untapped promising candidates for agrifood tools.

The importance of host-associated microorganisms and their biotic interactions for plant health and performance has been increasingly acknowledged. Protists, main predators and regulators of bacteria and fungi, are abundant and ubiquitous eukaryotes in terrestrial ecosystems. Protists are considered to benefit plant health and performance, but the community structure and functions of plant-associated protists remain surprisingly underexplored. Harnessing plant-associated protists and other microbes can potentially enhance plant health and productivity and sustain healthy food and agriculture systems. In this review, we summarize the knowledge of multifunctionality of protists and their interactions with other microbes in plant hosts, and propose a future framework to study plant-associated protists and utilize protists as agrifood tools for benefiting agricultural production.

Nano-DESI Mass Spectrometry Imaging of Proteoforms in Biological Tissues with High Spatial Resolution.

Mass spectrometry imaging (MSI) is a powerful tool for label-free mapping of the spatial distribution of proteins in biological tissues. We have previously demonstrated imaging of individual proteoforms in biological tissues using nanospray desorption electrospray ionization (nano-DESI), an ambient liquid extraction-based MSI technique. Nano-DESI MSI generates multiply charged protein ions, which is advantageous for their identification using top-down proteomics analysis. In this study, we demonstrate proteoform mapping in biological tissues with a spatial resolution down to 7 µm using nano-DESI MSI. A substantial decrease in protein signals observed in high-spatial-resolution MSI makes these experiments challenging. We have enhanced the sensitivity of nano-DESI MSI experiments by optimizing the design of the capillary-based probe and the thickness of the tissue section. In addition, we demonstrate that oversampling may be used to further improve spatial resolution at little or no expense to sensitivity. These developments represent a new step in MSI-based spatial proteomics, which complements targeted imaging modalities widely used for studying biological systems.

Community assembly of comammox Nitrospira in coastal wetlands across southeastern China.

Complete ammonia oxidizers (comammox Nitrospira) are ubiquitous in coastal wetland sediments and play an important role in nitrification. Our study examined the impact of habitat modifications on comammox Nitrospira communities in coastal wetland sediments across tropical and subtropical regions of southeastern China. Samples were collected from 21 coastal wetlands in five provinces where native mudflats were invaded by Spartina alterniflora and subsequently converted to aquaculture ponds. The results showed that comammox Nitrospira abundances were mainly influenced by sediment grain size rather than by habitat modifications. Compared to S. alterniflora marshes and native mudflats, aquaculture pond sediments had lower comammox Nitrospira diversity, lower clade A.1 abundance, and higher clade A.2 abundance. Sulfate concentration was the most important factor controlling the diversity of comammox Nitrospira. The response of comammox Nitrospira community to habitat change varied significantly by location, and environmental variables accounted for only 11.2% of the variations in community structure across all sites. In all three habitat types, dispersal limitation largely controlled the comammox Nitrospira community assembly process, indicating the stochastic nature of these sediment communities in coastal wetlands. IMPORTANCE Comammox Nitrospira have recently gained attention for their potential role in nitrification and nitrous oxide (N2O) emissions in soil and sediment. However, their distribution and assembly in impacted coastal wetland are poorly understood, particularly on a large spatial scale. Our study provides novel evidence that the effects of habitat modification on comammox Nitrospira communities are dependent on the location of the wetland. We also found that the assembly of comammox Nitrospira communities in coastal wetlands was mainly governed by stochastic processes. Nevertheless, sediment grain size and sulfate concentration were identified as key variables affecting comammox Nitrospira abundance and diversity in coastal sediments. These findings are significant as they advance our understanding of the environmental adaptation of comammox Nitrospira and how future landscape modifications may impact their abundance and diversity in coastal wetlands.

Plant Species-Driven Distribution of Individual Clades of Comammox Nitrospira in a Subtropical Estuarine Wetland.

Plant species play a crucial role in mediating the activity and community structure of soil microbiomes through differential inputs of litter and rhizosphere exudates, but we have a poor understanding of how plant species influence comammox Nitrospira, a newly discovered ammonia oxidizer with pivotal functionality. Here, we investigate the abundance, diversity, and community structure of comammox Nitrospira underneath five plant species and a bare tidal flat at three soil depths in a subtropical estuarine wetland. Plant species played a critical role in driving the distribution of individual clades of comammox Nitrospira, explaining 59.3% of the variation of community structure. Clade A.1 was widely detected in all samples, while clades A.2.1, A.2.2, A.3 and B showed plant species-dependent distribution patterns. Compared with the native species Cyperus malaccensis, the invasion of Spartina alterniflora increased the network complexity and changed the community structure of comammox Nitrospira, while the invasive effects from Kandelia obovata and Phragmites australis were relatively weak. Soil depths significantly influenced the community structure of comammox Nitrospira, but the effect was much weaker than that from plant species. Altogether, our results highlight the previously unrecognized critical role of plant species in driving the distribution of comammox Nitrospira in a subtropical estuarine wetland.

Non-native Plant Species Invasion Increases the Importance of Deterministic Processes in Fungal Community Assembly in a Coastal Wetland.

Fungal communities are essential to the maintenance of soil multifunctionality. Plant invasion represents a growing challenge for the conservation of soil biodiversity across the globe, but the impact of non-native species invasion on fungal diversity, community structure, and assembly processes remains largely unknown. Here, we examined the diversity, community composition, functional guilds, and assembly process of fungi at three soil depths underneath a native species, three non-native species, and a bare tidal flat from a coastal wetland. Plant species was more important than soil depth in regulating the diversity, community structure, and functional groups of fungi. Non-native species, especially Spartina alterniflora, increased fungal diversity, altered fungal community structure, and increased the relative abundance of saprotrophic and pathogenic fungi in coastal wetland soils. Stochastic processes played a predominant role in driving fungal community assembly, explaining more than 70% of the relative contributions. However, compared to a native species, non-native species, especially S. alterniflora, reduced the relative influence of stochastic processes in fungal community assembly. Collectively, our results provide novel evidence that non-native species can increase fungal diversity, the relative abundance of saprotrophic and pathogenic fungi, and deterministic processes in the assembly of fungi in coastal wetlands, which can expand our knowledge of the dynamics of fungal communities in subtropical coastal wetlands.

Effects of dietary supplementation of Gracilaria lemaneiformis-derived sulfated polysaccharides on the growth, antioxidant capacity, and innate immunity of rabbitfish (Siganus canaliculatus).

The dietary supplementation of red seaweed-derived polysaccharides has been shown to be beneficial to fish and shellfish aquaculture. However, the function of red seaweed (Gracilaria lemaneiformis)-extracted polysaccharide (GLP) on the health status of rabbitfish (Siganus canaliculatus) is still unknown. This study explored the influences of GLP on growth performance, antioxidant activity, and immunity of rabbitfish. Herein, the fish were fed commercial pelleted feed incorporated with the diverse amount of GLP: 0 (control), 0.10 (GLP0.10), and 0.15 g kg-1 (GLP0.15) for 60 days. The results demonstrated that dietary GLP0.15 significantly elevated FBW and WG, while feed utilization efficiency improved (reduced feed conversion ratio and increased protein efficiency ratio) upon GLP0.10 treatment, regarding the control (P < 0.05). Also, dietary administration of GLP0.15 suggestively improved the serum acid phosphatase and lysozyme activity as well as hepatic total antioxidant capacity, catalase, and superoxide dismutase activity. In contrast, GLP0.15decreased the serum alkaline phosphatase, aspartate aminotransferase, alanine aminotransferase, and malonaldehyde activity when compared to the control (P<0.05). Moreover, the lipase (36.08 and 16.46 U/mgprot in GLP0.10 and GLP0.15, respectively) and amylase (0.43 and 0.23 U/mgprot in GLP0.10 and GLP0.15, respectively) activity recorded the maximum values than the control (8.61 and 0.13 U/mgprot, respectively).Further, the intestinal morphometry was developed (such as increased villus length, width, and area) in the fish fed with a GLP-supplemented diet compared to the control. The KEGG pathway analysis unveiled that several differentially expressed genes (DEGs) in control vs. GLP0.10 and control vs. GLP0.15 were associated with metabolic or immune-associated pathways like antigen processing and presentation, phagosome, complement and coagulation cascades, and platelet activation. The DEGs, namely C3, f5, fgb, MHC1, and cfb, were evaluated in control vs. GLP0.10 and C3 and MHC1 in control vs. GLP0.15, suggesting their possible contributions to GLP-regulated immunity. Additionally, the cumulative mortality of rabbitfish after the Vibrio parahaemolyticus challenge was lower in both GLP0.10 (8.88%) and GLP0.15 (11.11%) than in control (33.33%) (P<0.05). Thus, these findings direct the potential use of GLP as an immunostimulant and growth promoter in rabbitfish aquaculture.

House dust mite-induced endoplasmic reticulum stress mediates MUC5AC hypersecretion via TBK1 in airway epithelium.

Purpose: Endoplasmic reticulum (ER) stress regulates mucus hypersecretion, and may activate downstream factors via TBK1 signaling to induce gene expression. However, it remains unclear whether ER stress promotes airway mucus secretion through the TBK1 pathway. We aimed to investigate the role of the TBK1 pathway in the regulation of MUC5AC expression in a mouse model of house dust mite (HDM)-induced allergic asthma. Materials and Methods: Mice with HDM-induced asthma and human bronchial epithelial BEAS-2B cells were treated with amlexanox, an anti-allergy drug (25 µM), or 4-PBA (10 mM). Tissue and cell samples were collected. Tissue samples were stained with hematoxylin and eosin (H&E) or periodic acid Schiff (PAS) to evaluate pathology. Protein expression was analyzed by western blotting and immunofluorescence. Results: Mice exposed to HDM presented ER stress and hypersecretion of mucus Muc5ac from airway epithelial cells (p < 0.001). Similar results were observed in BEAS-2B cells following exposure to HDM. Both in vivo and in vitro studies revealed that HDM-induced ER stress induced MUC5AC overexpression via TBK1 signaling. Amlexanox and 4-PBA markedly reduced mucus production and weakened the TBK1 signal, which mediates MUC5AC hypersecretion. Conclusion: TBK1 plays a pivotal role in HDM-induced ER stress, leading to overproduction of MUC5AC in the asthmatic airway epithelium. The overproduction of MUC5AC can be significantly decreased by inhibiting TBK1 or ER stress using 4-PBA. These findings highlight potential target-specific therapies for patients with chronic allergic asthma.

Electron scattering with ethane adsorbed on rare gas multilayers: Hole transfer, coulomb decay, and ion dissociation.

Positive ion desorption following electron impact dissociative ionization of ethane adsorbed on Ar, Kr, and Xe multilayers has been studied as a function of incident electron energy from threshold to 100 eV. Based on the dependence of ion yields on the identity of the rare gas, it is likely that the majority of ethane molecules undergo indirect ionization following hole transfer from the ionized underlying rare gas. This has also been corroborated by density of states calculations showing the energetic alignment of the outer valence states of ethane and the condensed rare gas ionization energies. Due to the near-resonant nature of charge transfer for single-hole states, the ethane molecular ion is excited to different final ionic states on different rare gases, which leads to differences in ion desorption yields and branching ratios. The quantitative yields increase with increasing ionization energy gap between the rare gas and ethane, in the order Ar > Kr > Xe. The large increase in yields from 25 eV onwards for all rare gases is likely due to the formation and decay of two-hole states on neighboring rare gas and ethane molecules due to interatomic and intermolecular Coulomb decay (ICD) and not electron transfer mediated decay (ETMD). The ICD and ETMD pathways become accessible when the incoming electron has sufficient energy to excite the inner valence ns level of the rare gas to a Rydberg state or ionize it. The experimental findings are supported by calculations of thresholds, density of states for the final configurations of these processes, and coupling strengths for hole transfer between ethane and rare gases. The fragment ion branching ratios vary with energy from threshold to about 35 eV, showing the fragmentation pattern changes with the mode of hole transfer and availability of excess energy. Sigma C-C bonds are more likely to break than C-H bonds in the mid-20 eV range, and this effect is most pronounced for Xe, followed by Kr, and then Ar.

Correlated Dirac-Coulomb-Breit multiconfigurational self-consistent-field methods.

The fully correlated frequency-independent Dirac-Coulomb-Breit Hamiltonian provides the most accurate description of electron-electron interaction before going to a genuine relativistic quantum electrodynamics theory of many-electron systems. In this work, we introduce a correlated Dirac-Coulomb-Breit multiconfigurational self-consistent-field method within the frameworks of complete active space and density matrix renormalization group. In this approach, the Dirac-Coulomb-Breit Hamiltonian is included variationally in both the mean-field and correlated electron treatment. We also analyze the importance of the Breit operator in electron correlation and the rotation between the positive- and negative-orbital space in the no-virtual-pair approximation. Atomic fine-structure splittings and lanthanide contraction in diatomic fluorides are used as benchmark studies to understand the contribution from the Breit correlation.

Shear-wave elastography combined with contrast-enhanced ultrasound algorithm for noninvasive characterization of focal liver lesions.

PURPOSE: To establish shear-wave elastography (SWE) combined with contrast-enhanced ultrasound (CEUS) algorithm (SCCA) and improve the diagnostic performance in differentiating focal liver lesions (FLLs). MATERIAL AND METHODS: We retrospectively selected patients with FLLs between January 2018 and December 2019 at the First Affiliated Hospital of Sun Yat-sen University. Histopathology was used as a standard criterion except for hemangiomas and focal nodular hyperplasia. CEUS with SonoVue (Bracco Imaging) and SCCA combining CEUS and maximum value of elastography with < 20 kPa and > 90 kPa thresholds were used for the diagnosis of FLLs. The diagnostic performance of CEUS and SCCA was calculated and compared. RESULTS: A total of 171 FLLs were included, with 124 malignant FLLs and 47 benign FLLs. The area under curve (AUC), sensitivity, and specificity in detecting malignant FLLs were 0.83, 91.94%, and 74.47% for CEUS, respectively, and 0.89, 91.94%, and 85.11% for SCCA, respectively. The AUC of SCCA was significantly higher than that of CEUS (P = 0.019). Decision curves indicated that SCCA provided greater clinical benefits. The SCCA provided significantly improved prediction of clinical outcomes, with a net reclassification improvement index of 10.64% (P = 0.018) and integrated discrimination improvement of 0.106 (P = 0.019). For subgroup analysis, we divided the FLLs into a chronic-liver-disease group (n = 88 FLLs) and a normal-liver group (n = 83 FLLs) according to the liver background. In the chronic-liver-disease group, there were no differences between the CEUS-based and SCCA diagnoses. In the normal-liver group, the AUC of SCCA and CEUS in the characterization of FLLs were 0.89 and 0.83, respectively (P = 0.018). CONCLUSION: SCCA is a feasible tool for differentiating FLLs in patients with normal liver backgrounds. Further investigations are necessary to validate the universality of this algorithm.