Genome-wide identification, characterization, molecular evolution and expression profiling analysis of scavenger receptors in black rockfish (Sebastes schlegelii).

The scavenger receptors (SRs) gene family is considered as the membrane-associated pattern recognition receptors that plays important roles in the immune responses of organisms. However, there is currently limited research on the systematic identification of the SRs gene family in teleost and their role in the innate immunity of S. schegelii. In this study, we identified and annotated 15 SRs genes in S. schegelii. Through phylogenetic analysis, analysis of conserved domains, gene structure, and motif composition, we found that SRs gene family within different classes were relatively conserved. Additionally, we used qRT-PCR to analyze the expression patterns of SRs genes in immune-related tissues from healthy and Acinetobacter johnsonii-infected S. schegelii. The results showed that SRs genes exhibited different tissue expression patterns and the expression of SRs genes significantly changed after A. johnsonii infection. These results provided a valuable basis for further understanding of the functions of SRs in the innate immune response of S. schegelii.

Total Syntheses of Streptamidine and Klebsazolicin Using Biomimetic On-Resin Ring-Closing Amidine Formation.

Diketopiperazine (DKP) derived cyclic amidine structures widely exist in peptide natural products according to the genome mining result. The largely unknown bioactivity and mode of action are partially caused by the poor availability of the compounds via microbiological and chemical approaches. To tackle this challenge, in this work, we have developed the on-resin ring-closing amidine formation strategy to synthesize peptides containing N-terminal DKP derived cyclic amidine structure, in which the 6-exo-trig cyclization mediated by HgCl2 activation of thioamides was the key step. Leveraging from this new strategy, we finished the total syntheses of streptamidine and klebsazolicin. Meanwhile, eleven klebsazolicin analogues were synthesized for its structure-activity relationship study.

Deep learning driven diagnosis of malignant soft tissue tumors based on dual-modal ultrasound images and clinical indexes.

Background: Soft tissue tumors (STTs) are benign or malignant superficial neoplasms arising from soft tissues throughout the body with versatile pathological types. Although Ultrasonography (US) is one of the most common imaging tools to diagnose malignant STTs, it still has several drawbacks in STT diagnosis that need improving. Objectives: The study aims to establish this deep learning (DL) driven Artificial intelligence (AI) system for predicting malignant STTs based on US images and clinical indexes of the patients. Methods: We retrospectively enrolled 271 malignant and 462 benign masses to build the AI system using 5-fold validation. A prospective dataset of 44 malignant masses and 101 benign masses was used to validate the accuracy of system. A multi-data fusion convolutional neural network, named ultrasound clinical soft tissue tumor net (UC-STTNet), was developed to combine gray scale and color Doppler US images and clinic features for malignant STTs diagnosis. Six radiologists (R1-R6) with three experience levels were invited for reader study. Results: The AI system achieved an area under receiver operating curve (AUC) value of 0.89 in the retrospective dataset. The diagnostic performance of the AI system was higher than that of one of the senior radiologists (AUC of AI vs R2: 0.89 vs. 0.84, p=0.022) and all of the intermediate and junior radiologists (AUC of AI vs R3, R4, R5, R6: 0.89 vs 0.75, 0.81, 0.80, 0.63; p <0.01). The AI system also achieved an AUC of 0.85 in the prospective dataset. With the assistance of the system, the diagnostic performances and inter-observer agreement of the radiologists was improved (AUC of R3, R5, R6: 0.75 to 0.83, 0.80 to 0.85, 0.63 to 0.69; p<0.01). Conclusion: The AI system could be a useful tool in diagnosing malignant STTs, and could also help radiologists improve diagnostic performance.

Investigation on the substrate specificity and N-substitution tolerance of PseF in catalytic transformation of pseudaminic acids to CMP-Pse derivatives.

Pseudaminic acid (Pse) belongs to a class of bacterial non-2-ulosonic acids, and has been implicated in bacterial infection and immune evasion. Various Pse structures with diverse N-substitutions have been identified in pathogenic bacterial strains like Pseudomonas aeruginosa, Campylobacter jejuni, and Acinetobacter baumannii. In this study, we successfully synthesized three new Pse species, including Pse5Ac7Fo, Pse5Ac7(3RHb) and Pse7Fo5(3RHb) using chemical methods. Furthermore, we investigated the substrate specificity of cytidine 5'-monophosphate (CMP)-Pse synthetase (PseF), resulting in the production of N-modified CMP-Pse derivatives (CMP-Pses). It was found that PseF was promiscuous with the Pse substrate and could tolerate different modifications at the two nitrogen atoms. This study provides valuable insights into the incorporation of variable N-substitutions in the Pse biosynthetic pathway.

KpsS1 Mediates the Glycosylation of Pseudaminic Acid in Acinetobacter Baumannii.

Pseudaminic acid (Pse) is found in the polysaccharide structures of the cell surface of various Gram-negative pathogenic bacteria including Acinetobacter baumannii and considered as an important component of cell surface glycans including oligosaccharides and glycoproteins. However, the glycosyltransferase that is responsible for the Pse glycosylation in A. baumannii remains unknown yet. In this study, through comparative genomics analysis of Pse-positive and negative A. baumannii clinical isolates, we identified a potential glycosyltransferase, KpsS1, located right downstream of the Pse biosynthesis genetic locus. Deletion of this gene in an Pse-positive A. baumannii strain, Ab8, impaired the glycosylation of Pse to the surface CPS and proteins, while the gene knockout strain, Ab8ΔkpsS1, could still produce Pse with 2.86 folds higher amount than that of Ab8. Furthermore, impairment of Pse glycosylation affected the morphology and virulence potential of A. baumannii, suggesting the important role of this protein. This study will provide insights into the further understanding of Pse in bacterial physiology and pathogenesis.

Synchronization of inertial complex-valued memristor-based neural networks with time-varying delays.

The synchronization of inertial complex-valued memristor-based neural networks (ICVMNNs) with time-varying delays was explored in the paper with the non-separation and non-reduced approach. Sufficient conditions required for the exponential synchronization of the ICVMNNs were identified with the construction of comprehensive Lyapunov functions and the design of a novel control scheme. The adaptive synchronization was also investigated based on the derived results, which is easier to implement in practice. What's more, a numerical example that verifies the obtained results was presented.

Discovery of a Monoclonal Antibody That Targets Cell-Surface Pseudaminic Acid of Acinetobacter baumannii with Direct Bactericidal Effect.

The therapeutic effects of antibodies include neutralization of pathogens, activation of the host complement system, and facilitation of phagocytosis of pathogens. However, antibody alone has never been shown to exhibit bactericidal activity. In this study, we developed a monoclonal antibody that targets the bacterial cell surface component Pseudaminic acid (Pse). This monoclonal antibody, Pse-MAB1, exhibited direct bactericidal activity on Acinetobacter baumannii strains, even in the absence of the host complements or other immune factors, and was able to confer a protective effect against A. baumannii infections in mice. This study provides new insight into the potential of developing monoclonal antibody-based antimicrobial therapy of multidrug resistant bacterial infections, especially those which occurred among immunocompromised patients.

Selective Peptide Cysteine Manipulation on Demand and Difficult Protein Chemical Synthesis Enabled by Controllable Acidolysis of N,S-Benzylidene Thioacetals.

Although solid-phase peptide synthesis combining with chemical ligation provides a way to build up customized polypeptides in general, many targets are still presenting challenges for the conventional synthetic process, such as hydrophobic proteins. New methods and strategies are still required to overcome these obstacles. In this study, kinetic studies of Cys/Pen ligation and its acidolysis were performed, from which the fast acidolysis of substituted N,S-benzylidene thioacetals (NBTs) was discovered. The study demonstrates the potential of NBTs as a promising Cys switchable protection, facilitating the chemical synthesis of peptides and proteins by efficiently disrupting peptide aggregation. The compatibility of NBTs with other commonly adopted Cys protecting groups and their applications in sequential disulfide bond formation were also investigated. The first chemical synthesis of the native human programmed death ligand 1 immunoglobulin V-like (PD-L1 IgV) domain was achieved using the NBT strategy, showcasing its potential in difficult protein synthesis.

Real-Time Biosynthetic Reaction Monitoring Informs the Mechanism of Action of Antibiotics.

The rapid spread of drug-resistant pathogens and the declining discovery of new antibiotics have created a global health crisis and heightened interest in the search for novel antibiotics. Beyond their discovery, elucidating mechanisms of action has necessitated new approaches, especially for antibiotics that interact with lipidic substrates and membrane proteins. Here, we develop a methodology for real-time reaction monitoring of the activities of two bacterial membrane phosphatases, UppP and PgpB. We then show how we can inhibit their activities using existing and newly discovered antibiotics such as bacitracin and teixobactin. Additionally, we found that the UppP dimer is stabilized by phosphatidylethanolamine, which, unexpectedly, enhanced the speed of substrate processing. Overall, our results demonstrate the potential of native mass spectrometry for real-time biosynthetic reaction monitoring of membrane enzymes, as well as their in situ inhibition and cofactor binding, to inform the mode of action of emerging antibiotics.

A System for Discovering Novel Uricosurics Targeting Urate Transporter 1 Based on In Vitro and In Vivo Modeling.

Hyperuricemia has become a global burden with the increasing prevalence and risk of associated metabolic disorders and cardiovascular diseases. Uricosurics act as a vital urate-lowering therapy by promoting uric acid excretion via the kidneys. However, potent and safe uricosurics are still in urgent demand for use in the clinic. In this study, we aimed to establish in vitro and in vivo models to aid the discovery of novel uricosurics, and to search for potent active compounds, especially targeting urate transporter 1 (URAT1), the major urate transporter in the kidney handling uric acid homeostasis. As a result, for preliminary screening, the in vitro URAT1 transport activity was assessed using a non-isotopic uric acid uptake assay in hURAT1-stably expressed HEK293 cells. The in vivo therapeutic effect was evaluated in a subacute hyperuricemic mouse model (sub-HUA) and further confirmed in a chronic hyperuricemic mouse model (Ch-HUA). By utilizing these models, compound CC18002 was obtained as a potent URAT1 inhibitor, with an IC50 value of 1.69 µM, and favorable uric acid-lowering effect in both sub-HUA and Ch-HUA mice, which was comparable to that of benzbromarone at the same dosage. Moreover, the activity of xanthine oxidoreductase, the key enzyme catalyzing uric acid synthesis, was not altered by CC18002 treatment. Taken together, we have developed a novel screening system, including a cell model targeting URAT1 and two kinds of mouse models, for the discovery of novel uricosurics. Utilizing this system, compound CC18002 was investigated as a candidate URAT1 inhibitor to treat hyperuricemia.

pH-triggered hydrophility-adjustable fluorescent probes for simultaneously imaging lipid droplets and lysosomes and the application in fatty liver detection.

To study the collaboration between lipid droplets (LDs) and lysosomes, and the lipid change in nonalcoholic fatty liver disease (NAFLD), herein two pH-triggered hydrophility-adjustable fluorescent probes (LD-Lyso and LD-Lyso 1) are designed. The mechanism is based on cyclization and ring-opening with thorough consideration of pH and hydrophilic differences between LDs and lysosomes. Both of the two probes exist in ring-opening form and emit red fluorescence in acidic environment, while they exist in cyclized form and the emission is blueshifted in alkaline environment due to reduced conjugate planes. Moreover, LD-Lyso exhibits near infrared fluorescence at 740 nm under ring-opening form, which facilitates further cell, tissue, and in vivo imaging. The cell imaging results show that LD-Lyso can simultaneously target LDs and lysosomes by two different colors. Impressively, LD-Lyso cannot only detect NAFLD tissues from the normal tissue, but also distinguish different degrees of NAFLD tissues and mice, which provides a very promising tool for timely diagnosis of early NAFLD.

SaeR as a novel target for antivirulence therapy against Staphylococcus aureus.

Staphylococcus aureus is a major human pathogen responsible for a wide range of clinical infections. SaeRS is one of the two-component systems in S. aureus that modulate multiple virulence factors. Although SaeR is required for S. aureus to develop an infection, inhibitors have not been reported. Using an in vivo knockdown method, we demonstrated that SaeR is targetable for the discovery of antivirulence agent. HR3744 was discovered through a high-throughput screening utilizing a GFP-Lux dual reporter system driven by saeP1 promoter. The antivirulence efficacy of HR3744 was tested using Western blot, Quantitative Polymerase Chain Reaction, leucotoxicity, and haemolysis tests. In electrophoresis mobility shift assay, HR3744 inhibited SaeR-DNA probe binding. WaterLOGSY-NMR test showed HR3744 directly interacted with SaeR's DNA-binding domain. When SaeR was deleted, HR3744 lost its antivirulence property, validating the target specificity. Virtual docking and mutagenesis were used to confirm the target's specificity. When Glu159 was changed to Asn, the bacteria developed resistance to HR3744. A structure-activity relationship study revealed that a molecule with a slight modification did not inhibit SaeR, indicating the selectivity of HR3744. Interestingly, we found that SAV13, an analogue of HR3744, was four times more potent than HR3744 and demonstrated identical antivirulence properties and target specificity. In a mouse bacteraemia model, both HR3744 and SAV13 exhibited in vivo effectiveness. Collectively, we identified the first SaeR inhibitor, which exhibited in vitro and in vivo antivirulence properties, and proved that SaeR could be a novel target for developing antivirulence drugs against S. aureus infections.

N,O-Benzylidene Acetal Dipeptides (NBDs) Enable the Synthesis of Difficult Peptides via a Kinked Backbone Strategy.

Proteins with highly hydrophobic regions or aggregation-prone sequences are typically difficult targets for chemical synthesis at the current stage, as obtaining such type of peptides via solid-phase peptide synthesis requires sophisticated operations. Herein, we report N,O-benzylidene acetal dipeptides (NBDs) as robust and effective building blocks to allow the direct synthesis of difficult peptides and proteins via a kinked backbone strategy. The effectiveness and easy accessibility of NBDs have been well demonstrated in our chemical syntheses of various challenging peptides and proteins, including chemokine, therapeutic hormones, histone, and glycosylated erythropoietin.

Revealing the extracellular function of HMGB1 N-terminal region acetylation assisted by a protein semi-synthesis approach.

HMGB1 (high-mobility group box 1) is a non-histone chromatin-associated protein that has been widely reported as a representative damage-associated molecular pattern (DAMP) and to play a pivotal role in the proinflammatory process once it is in an extracellular location. Accumulating evidence has shown that HMGB1 undergoes extensive post-translational modifications (PTMs) that actively regulate its conformation, localization, and intermolecular interactions. However, fully characterizing the functional implications of these PTMs has been challenging due to the difficulty in accessing homogeneous HMGB1 with site-specific PTMs of interest. In this study, we developed a streamlined protein semi-synthesis strategy via salicylaldehyde ester-mediated chemical ligations (Ser/Thr ligation and Cys/Pen ligation, STL/CPL). This methodology enabled us to generate a series of N-terminal region acetylated HMGB1 proteins. Further studies revealed that acetylation regulates HMGB1-heparin interaction and modulates HMGB1's stability against thrombin, representing a regulatory switch to control HMGB1's extracellular activity.

Chemical Synthesis of Peptides and Proteins Bearing Base-Labile Post-Translational Modifications: Evolution of the Methods in Four Decades.

The S-palmitoylation on Cys residue and O-acetylation on Ser/Thr residues are two types of base-labile post-translational modifications (PTMs) in cells. The lability of these PTMs to bases and nucleophiles makes the peptides/proteins bearing S-palmitoyl or O-acetyl groups challenging synthetic targets, which cannot be prepared via the standard Fmoc-SPPS and native chemical ligation. In this review, we summarized the efforts towards their preparation in the past 40 years, with the focus on the evolution of synthetic methods.

MIB-ANet: A novel multi-scale deep network for nasal endoscopy-based adenoid hypertrophy grading.

Introduction: To develop a novel deep learning model to automatically grade adenoid hypertrophy, based on nasal endoscopy, and asses its performance with that of E.N.T. clinicians. Methods: A total of 3,179 nasoendoscopic images, including 4-grade adenoid hypertrophy (Parikh grading standard, 2006), were collected to develop and test deep neural networks. MIB-ANet, a novel multi-scale grading network, was created for adenoid hypertrophy grading. A comparison between MIB-ANet and E.N.T. clinicians was conducted. Results: In the SYSU-SZU-EA Dataset, the MIB-ANet achieved 0.76251 F1 score and 0.76807 accuracy, and showed the best classification performance among all of the networks. The visualized heatmaps show that MIB-ANet can detect whether adenoid contact with adjacent tissues, which was interpretable for clinical decision. MIB-ANet achieved at least 6.38% higher F1 score and 4.31% higher accuracy than the junior E.N.T. clinician, with much higher (80× faster) diagnosing speed. Discussion: The novel multi-scale grading network MIB-ANet, designed for adenoid hypertrophy, achieved better classification performance than four classical CNNs and the junior E.N.T. clinician. Nonetheless, further studies are required to improve the accuracy of MIB-ANet.

Childhood maltreatment and midlife cognitive functioning: A longitudinal study of the roles of social support and social isolation.

OBJECTIVE: Negative consequences of childhood maltreatment have been well-documented, including poorer executive functioning and nonverbal reasoning in midlife. However, not all adults with a history of childhood maltreatment manifest these outcomes, suggesting the presence of risk and protective factors. Based on growing empirical support for the importance of social variables in understanding neuropsychological development and functioning, we examined whether social support and social isolation mediate or moderate the effects of childhood maltreatment on cognitive functioning in midlife. METHOD: In the context of a prospective cohort design study, individuals with documented histories of childhood maltreatment (ages 0-11 years) and demographically matched controls were followed up and interviewed in adulthood. Social support and isolation were assessed in young adulthood (Mage = 29), and cognitive functioning was assessed in midlife (Mage = 41). Structural equation modeling was used for mediation and linear regressions for moderation. RESULTS: Childhood maltreatment predicted higher levels of social isolation and lower levels of social support and cognitive functioning. Only social isolation mediated the relationship between childhood maltreatment and midlife cognitive functioning, whereas childhood maltreatment interacted with social support to predict Matrix Reasoning in midlife. Social support was protective for the control group but not for those maltreated. CONCLUSIONS: Social isolation and social support play different roles in understanding how childhood maltreatment impacts midlife cognitive functioning. Greater social isolation predicts greater deficits in cognitive functioning overall, whereas the protective effects of social support are limited to those without a documented history of childhood maltreatment. Clinical implications are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

[Analysis of Carbon Emissions and Influencing Factors in China Based on City Scale].

Assessing regional carbon emissions and their relationship with socio-economic conditions is very important for developing strategies for carbon emission reduction. This study explored the impact of the proportion of non-fossil energy, the land development degree, the urbanization rate of permanent residents, the proportion of secondary industry, per capita GDP, and per capita construction land area on per capita CO2 emissions in 339 prefecture-level and above cities in China (excluding some cities in Xinjiang, Hong Kong, Macao, and Taiwan). A Bayesian belief network modeling carbon emissions was constructed to identify the global effects of various factors on per capita CO2 emissions, and multiscale geographically weighted regression was used to analyze their local effects. The results showed that first, per capita CO2 emissions of cities in China increased from the south to the north and decreased from the eastern coast to the inland region. Second, globally, the sensitivity of per capita CO2 emissions to various factors from high to low was in the order of per capita construction land area>per capita GDP>urbanization rate of permanent residents>land development degree>proportion of secondary industry>proportion of non-fossil energy. Third, locally, the direction of the spatial relationship between each factor and per capita CO2 emissions was consistent with the global relationship, and there was spatial heterogeneity in the strength of the relationship. Finally, clean energy, decarbonization technologies, saving and intensive use of land, and green living were effective ways to achieve the dual-carbon goal.

Learning from pseudo-lesion: a self-supervised framework for COVID-19 diagnosis.

The Coronavirus disease 2019 (COVID-19) has rapidly spread all over the world since its first report in December 2019, and thoracic computed tomography (CT) has become one of the main tools for its diagnosis. In recent years, deep learning-based approaches have shown impressive performance in myriad image recognition tasks. However, they usually require a large number of annotated data for training. Inspired by ground glass opacity, a common finding in COIVD-19 patient's CT scans, we proposed in this paper a novel self-supervised pretraining method based on pseudo-lesion generation and restoration for COVID-19 diagnosis. We used Perlin noise, a gradient noise based mathematical model, to generate lesion-like patterns, which were then randomly pasted to the lung regions of normal CT images to generate pseudo-COVID-19 images. The pairs of normal and pseudo-COVID-19 images were then used to train an encoder-decoder architecture-based U-Net for image restoration, which does not require any labeled data. The pretrained encoder was then fine-tuned using labeled data for COVID-19 diagnosis task. Two public COVID-19 diagnosis datasets made up of CT images were employed for evaluation. Comprehensive experimental results demonstrated that the proposed self-supervised learning approach could extract better feature representation for COVID-19 diagnosis, and the accuracy of the proposed method outperformed the supervised model pretrained on large-scale images by 6.57% and 3.03% on SARS-CoV-2 dataset and Jinan COVID-19 dataset, respectively.

Peptide Stapling through Site-Directed Conjugation of Triazine Moieties to the Tyrosine Residues of a Peptide.

Peptide stapling is a strategy for improving the biological properties of peptides. Herein, we report a novel method for stapling peptides that utilizes bifunctional triazine moieties for two-component conjugation to the phenolic hydroxyl groups of tyrosine, which enables efficient stapling of unprotected peptides. In addition, we applied this strategy to the RGD peptide that can target integrins and demonstrated that the stapled RGD peptide had significantly improved plasma stability and integrin-targeting ability.