Immunization-Elicited Broadly Protective Antibody Reveals Ebolavirus Fusion Loop as a Site of Vulnerability.

While neutralizing antibodies are highly effective against ebolavirus infections, current experimental ebolavirus vaccines primarily elicit species-specific antibody responses. Here, we describe an immunization-elicited macaque antibody (CA45) that clamps the internal fusion loop with the N terminus of the ebolavirus glycoproteins (GPs) and potently neutralizes Ebola, Sudan, Bundibugyo, and Reston viruses. CA45, alone or in combination with an antibody that blocks receptor binding, provided full protection against all pathogenic ebolaviruses in mice, guinea pigs, and ferrets. Analysis of memory B cells from the immunized macaque suggests that elicitation of broadly neutralizing antibodies (bNAbs) for ebolaviruses is possible but difficult, potentially due to the rarity of bNAb clones and their precursors. Unexpectedly, germline-reverted CA45, while exhibiting negligible binding to full-length GP, bound a proteolytically remodeled GP with picomolar affinity, suggesting that engineered ebolavirus vaccines could trigger rare bNAb precursors more robustly. These findings have important implications for developing pan-ebolavirus vaccine and immunotherapeutic cocktails.

Postsynaptic competition between calcineurin and PKA regulates mammalian sleep-wake cycles.

The phosphorylation of synaptic proteins is a significant biochemical reaction that controls the sleep-wake cycle in mammals1-3. Protein phosphorylation in vivo is reversibly regulated by kinases and phosphatases. In this study, we investigate a pair of kinases and phosphatases that reciprocally regulate sleep duration. First, we perform a comprehensive screen of protein kinase A (PKA) and phosphoprotein phosphatase (PPP) family genes by generating 40 gene knockout mouse lines using prenatal and postnatal CRISPR targeting. We identify a regulatory subunit of PKA (Prkar2b), a regulatory subunit of protein phosphatase 1 (PP1; Pppr1r9b) and catalytic and regulatory subunits of calcineurin (also known as PP2B) (Ppp3ca and Ppp3r1) as sleep control genes. Using adeno-associated virus (AAV)-mediated stimulation of PKA and PP1-calcineurin activities, we show that PKA is a wake-promoting kinase, whereas PP1 and calcineurin function as sleep-promoting phosphatases. The importance of these phosphatases in sleep regulation is supported by the marked changes in sleep duration associated with their increased and decreased activities, ranging from approximately 17.3 h per day (PP1 expression) to 4.3 h per day (postnatal CRISPR targeting of calcineurin). Localization signals to the excitatory post-synapse are necessary for these phosphatases to exert their sleep-promoting effects. Furthermore, the wake-promoting effect of PKA localized to the excitatory post-synapse negated the sleep-promoting effect of PP1-calcineurin. These findings indicate that PKA and PP1-calcineurin have competing functions in sleep regulation at excitatory post-synapses.

AptaDB: a comprehensive database integrating aptamer-target interactions.

Aptamers have emerged as research hotspots of the next generation due to excellent performance benefits and application potentials in pharmacology, medicine, and analytical chemistry. Despite the numerous aptamer investigations, the lack of comprehensive data integration has hindered the development of computational methods for aptamers and the reuse of aptamers. A public access database named AptaDB, derived from experimentally validated data manually collected from the literature, was hence developed, integrating comprehensive aptamer-related data, which include six key components: (i) experimentally validated aptamer-target interaction information, (ii) aptamer property information, (iii) structure information of aptamer, (iv) target information, (v) experimental activity information, and (vi) algorithmically calculated similar aptamers. AptaDB currently contains 1350 experimentally validated aptamer-target interactions, 1230 binding affinity constants, 1293 aptamer sequences, and more. Compared to other aptamer databases, it contains twice the number of entries found in available databases. The collection and integration of the above information categories is unique among available aptamer databases and provides a user-friendly interface. AptaDB will also be continuously updated as aptamer research evolves. We expect that AptaDB will become a powerful source for aptamer rational design and a valuable tool for aptamer screening in the future. For access to AptaDB, please visit http://lmmd.ecust.edu.cn/aptadb/.

MetaPredictor: in silico prediction of drug metabolites based on deep language models with prompt engineering.

Metabolic processes can transform a drug into metabolites with different properties that may affect its efficacy and safety. Therefore, investigation of the metabolic fate of a drug candidate is of great significance for drug discovery. Computational methods have been developed to predict drug metabolites, but most of them suffer from two main obstacles: the lack of model generalization due to restrictions on metabolic transformation rules or specific enzyme families, and high rate of false-positive predictions. Here, we presented MetaPredictor, a rule-free, end-to-end and prompt-based method to predict possible human metabolites of small molecules including drugs as a sequence translation problem. We innovatively introduced prompt engineering into deep language models to enrich domain knowledge and guide decision-making. The results showed that using prompts that specify the sites of metabolism (SoMs) can steer the model to propose more accurate metabolite predictions, achieving a 30.4% increase in recall and a 16.8% reduction in false positives over the baseline model. The transfer learning strategy was also utilized to tackle the limited availability of metabolic data. For the adaptation to automatic or non-expert prediction, MetaPredictor was designed as a two-stage schema consisting of automatic identification of SoMs followed by metabolite prediction. Compared to four available drug metabolite prediction tools, our method showed comparable performance on the major enzyme families and better generalization that could additionally identify metabolites catalyzed by less common enzymes. The results indicated that MetaPredictor could provide a more comprehensive and accurate prediction of drug metabolism through the effective combination of transfer learning and prompt-based learning strategies.

admetSAR3.0: a comprehensive platform for exploration, prediction and optimization of chemical ADMET properties.

Absorption, distribution, metabolism, excretion and toxicity (ADMET) properties play a crucial role in drug discovery and chemical safety assessment. Built on the achievements of admetSAR and its successor, admetSAR2.0, this paper introduced the new version of the series, admetSAR3.0, as a comprehensive platform for chemical ADMET assessment, including search, prediction and optimization modules. In the search module, admetSAR3.0 hosted over 370 000 high-quality experimental ADMET data for 104 652 unique compounds, and supplemented chemical structure similarity search function to facilitate read-across. In the prediction module, we introduced comprehensive ADMET endpoints and two new sections for environmental and cosmetic risk assessments, empowering admetSAR3.0 to provide prediction for 119 endpoints, more than double numbers compared to the previous version. Furthermore, the advanced multi-task graph neural network framework offered robust and reliable support for ADMET prediction. In particular, a module named ADMETopt was added to automatically optimize the ADMET properties of query molecules through transformation rules or scaffold hopping. Finally, admetSAR3.0 provides user-friendly interfaces for multiple types of input data, such as SMILES string, chemical structure and batch molecule file, and supports various output types, including digital, chart displays and file downloads. In summary, admetSAR3.0 is anticipated to be a valuable and powerful tool in drug discovery and chemical safety assessment at http://lmmd.ecust.edu.cn/admetsar3/.

Identification of vital chemical information via visualization of graph neural networks.

Qualitative or quantitative prediction models of structure-activity relationships based on graph neural networks (GNNs) are prevalent in drug discovery applications and commonly have excellently predictive power. However, the network information flows of GNNs are highly complex and accompanied by poor interpretability. Unfortunately, there are relatively less studies on GNN attributions, and their developments in drug research are still at the early stages. In this work, we adopted several advanced attribution techniques for different GNN frameworks and applied them to explain multiple drug molecule property prediction tasks, enabling the identification and visualization of vital chemical information in the networks. Additionally, we evaluated them quantitatively with attribution metrics such as accuracy, sparsity, fidelity and infidelity, stability and sensitivity; discussed their applicability and limitations; and provided an open-source benchmark platform for researchers. The results showed that all attribution techniques were effective, while those directly related to the predicted labels, such as integrated gradient, preferred to have better attribution performance. These attribution techniques we have implemented could be directly used for the vast majority of chemical GNN interpretation tasks.

Early human B cell signatures of the primary antibody response to mRNA vaccination.

Messenger RNA (mRNA) vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are highly effective at inducing protective immunity. However, weak antibody responses are seen in some individuals, and cellular correlates of immunity remain poorly defined, especially for B cells. Here we used unbiased approaches to longitudinally dissect primary antibody, plasmablast, and memory B cell (MBC) responses to the two-dose mRNA-1273 vaccine in SARS-CoV-2-naive adults. Coordinated immunoglobulin A (IgA) and IgG antibody responses were preceded by bursts of spike-specific plasmablasts after both doses but earlier and more intensely after dose 2. While antibody and B cell cellular responses were generally robust, they also varied within the cohort and decreased over time after a dose-2 peak. Both antigen-nonspecific postvaccination plasmablast frequency after dose 1 and their spike-specific counterparts early after dose 2 correlated with subsequent antibody levels. This correlation between early plasmablasts and antibodies remained for titers measured at 6 months after vaccination. Several distinct antigen-specific MBC populations emerged postvaccination with varying kinetics, including two MBC populations that correlated with 2- and 6-month antibody titers. Both were IgG-expressing MBCs: one less mature, appearing as a correlate after the first dose, while the other MBC correlate showed a more mature and resting phenotype, emerging as a correlate later after dose 2. This latter MBC was also a major contributor to the sustained spike-specific MBC response observed at month 6. Thus, these plasmablasts and MBCs that emerged after both the first and second doses with distinct kinetics are potential determinants of the magnitude and durability of antibodies in response to mRNA-based vaccination.

SARS-CoV-2 impairs interferon production via NSP2-induced repression of mRNA translation.

Viruses evade the innate immune response by suppressing the production or activity of cytokines such as type I interferons (IFNs). Here we report the discovery of a mechanism by which the SARS-CoV-2 virus coopts an intrinsic cellular machinery to suppress the production of the key immunostimulatory cytokine IFN-ß. We reveal that the SARS-CoV-2 encoded nonstructural protein 2 (NSP2) directly interacts with the cellular GIGYF2 protein. This interaction enhances the binding of GIGYF2 to the mRNA cap-binding protein 4EHP, thereby repressing the translation of the Ifnb1 mRNA. Depletion of GIGYF2 or 4EHP significantly enhances IFN-ß production, which inhibits SARS-CoV-2 replication. Our findings reveal a target for rescuing the antiviral innate immune response to SARS-CoV-2 and other RNA viruses.

SGLT2 inhibitors as a potential therapeutic option for pulmonary hypertension: mechanisms and clinical perspectives.

Pulmonary arterial hypertension (PAH), one subtype of pulmonary hypertension (PH), is a life-threatening condition characterized by pulmonary arterial remodeling, elevated pulmonary vascular resistance, and blood pressure in the pulmonary arteries, leading to right heart failure and increased mortality. The disease is marked by endothelial dysfunction, vasoconstriction, and vascular remodeling. The role of Sodium-Glucose Co-Transporter-2 (SGLT2) inhibitors, a class of medications originally developed for diabetes management, is increasingly being explored in the context of cardiovascular diseases, including PAH, due to their potential to modulate these pathophysiological processes. In this review, we systematically examine the burgeoning evidence from both basic and clinical studies that describe the effects of SGLT2 inhibitors on cardiovascular health, with a special emphasis on PAH. By delving into the complex interactions between these drugs and the potential pathobiology that underpins PH, this study seeks to uncover the mechanistic underpinnings that could justify the use of SGLT2 inhibitors as a novel therapeutic approach for PAH. We collate findings that illustrate how SGLT2 inhibitors may influence the normal function of pulmonary arteries, possibly alleviating the pathological hallmarks of PAH such as inflammation, oxidative stress, aberrant cellular proliferation, and so on. Our review thereby outlines a potential paradigm shift in PAH management, suggesting that these inhibitors could play a crucial role in modulating the disease's progression by targeting the potential dysfunctions that drive it. This comprehensive synthesis of existing research underscores the imperative need for further clinical trials to validate the efficacy of SGLT2 inhibitors in PAH and to integrate them into the therapeutic agents used against this challenging disease.

The regulation of Tfh cell differentiation by ß-hydroxybutyrylation modification of transcription factor Bcl6.

Transcriptional repressor B cell lymphoma 6 (Bcl6) is a major transcription factor involved in Tfh cell differentiation and germinal center response, which is regulated by a variety of biological processes. However, the functional impact of post-translational modifications, particularly lysine ß-hydroxybutyrylation (Kbhb), on Bcl6 remains elusive. In this study, we revealed that Bcl6 is modified by Kbhb to affect Tfh cell differentiation, resulting in the decrease of cell population and cytokine IL-21. Furthermore, the modification sites are identified from enzymatic reactions to be lysine residues at positions 376, 377, and 379 by mass spectrometry, which is confirmed by site-directed mutagenesis and functional analyses. Collectively, our present study provides evidence on the Kbhb modification of Bcl6 and also generates new insights into the regulation of Tfh cell differentiation, which is a starting point for a thorough understanding of the functional involvement of Kbhb modification in the differentiations of Tfh and other T cells.

Downregulation of SMAD4 protects HaCaT cells against UVB-induced damage and oxidative stress through the activation of EMT.

As a member of the SMAD family, SMAD4 plays a crucial role in several cellular biological processes. However, its function in UVB radiation-induced keratinocyte damage is not yet clarified. Our study aims to provide mechanistic insight for the development of future UVB protective therapies and therapeutics involving SMAD4. HaCaT cells were treated with UVB, and the dose dependence and time dependence of UVB were measured. The cell function of UVB-treated HaCaT cells and the activity of epithelial-mesenchymal transition (EMT) after overexpression or silencing of SMAD4 was observed by flow cytometry, quantitative reverse transcription PCR (qRT-PCR) and Western Blots (WB). We found that a significant decrease in SMAD4 was observed in HaCaT cells induced by UVB. Our data confirm SMAD4 as a direct downstream target of miR-664. The down-regulation of SMAD4 preserved the viability of the UVB-treated HaCaT cells by inhibiting autophagy or apoptosis. Furthermore, the silencing of SMAD4 activated the EMT process in UVB-treated HaCaT cells. Down-regulation of SMAD4 plays a protective role in UVB-treated HaCaT cells via the activation of EMT.

Network-Based Methods and Their Applications in Drug Discovery.

Drug discovery is time-consuming, expensive, and predominantly follows the "one drug → one target → one disease" paradigm. With the rapid development of systems biology and network pharmacology, a novel drug discovery paradigm, "multidrug → multitarget → multidisease", has emerged. This new holistic paradigm of drug discovery aligns well with the essence of networks, leading to the emergence of network-based methods in the field of drug discovery. In this Perspective, we initially introduce the concept and data sources of networks and highlight classical methodologies employed in network-based methods. Subsequently, we focus on the practical applications of network-based methods across various areas of drug discovery, such as target prediction, virtual screening, prediction of drug therapeutic effects or adverse drug events, and elucidation of molecular mechanisms. In addition, we provide representative web servers for researchers to use network-based methods in specific applications. Finally, we discuss several challenges of network-based methods and the directions for future development. In a word, network-based methods could serve as powerful tools to accelerate drug discovery.

Antithrombotic therapy at discharge and prognosis in patients with chronic coronary syndrome and atrial fibrillation who underwent PCI: a real-world study.

BACKGROUND: This study aimed to describe the status of antithrombotic therapy at discharge and prognosis in patients with atrial fibrillation (AF) and chronic coronary syndrome (CCS) who underwent percutaneous coronary intervention (PCI). METHODS: This was an observational, prospective study. The primary endpoint was major adverse cardiovascular events (MACE), including all-cause death, myocardial infarction, stroke/transient ischemic attach (TIA), systemic embolism or ischemia-driven revascularization. Bleeding events were collected according to the Thrombolysis in Myocardial Infarction (TIMI) criteria. RESULTS: Between 2017 and 2019, a cohort of 516 patients (mean age 66, [SD 9], of whom 18.4% were female) with AF and CCS who underwent PCI were evaluated, with a median followed-up time of 36 months (Interquartile range: 22-45). MACE events occurred in 13.0% of the patients, while the TIMI bleeding events were observed in 17.4%. Utilization of TAT (triple antithrombotic therapy) (P < 0.001) and oral anticoagulation (OAC) therapy (P < 0.001) increased through years. History of heart failure (HF) (Hazard ratio [HR], 1.744; 95% confidence interval [CI], 1.011-3.038) and TAT (HR, 2.708; 95%CI, 1.653-4.436) had independent associations with MACE events. OAC (HR, 10.378; 95%CI, 6.136-17.555) was identified as a risk factor for bleeding events. A higher creatine clearance (HR, 0.986; 95%CI, 0.974-0.997) was associated with a lower incidence of bleeding events. CONCLUSIONS: Antithrombotic therapy has been improved among patients with AF and CCS who underwent PCI these years. History of HF and TAT were independently associated with MACE events. Higher creatine clearance was protective factor of bleeding events, while OAC was a risk factor for TIMI bleeding events.

Comparative analysis of the immune responses of CcIgZ3 in mucosal tissues and the co-expression of CcIgZ3 and PCNA in the gills of common carp (Cyprinus carpio L.) in response to TNP-LPS.

Fish live in an aquatic environment rich in various microorganisms and pathogens. Fish mucosal-associated lymphoid tissue (MALT) plays a very important role in immune defence. This study was conducted to characterize the immune response mediated by CcIgZ3 in common carp (Cyprinus carpio.) and investigate the proliferating CcIgZ3+ B lymphocytes in gill. We determined the expression of CcIgZ3 in many different tissues of common carp following stimulation by intraperitoneal injection of TNP-LPS (2,4,6-Trinitrophenyl hapten conjugated to lipopolysaccharide) or TNP-KLH (2,4,6-Trinitrophenyl hapten conjugated to Keyhole Limpet Hemocyanin). Compared with TNP-KLH, TNP-LPS can induce greater CcIgZ3 expression in the head kidney, gill and hindgut, especially in the gill. The results indicate that the gill is one of the main sites involved in the immune response mediated by CcIgZ3. To examine the distribution of CcIgZ3+ B lymphocytes, immunohistochemistry (IHC) experiments were performed using a polyclonal antibody against CcIgZ3. The results indicated that CcIgZ3 was detected in the head kidney, hindgut and gill. To further examine whether CcIgZ3+ B lymphocytes proliferate in the gills, proliferating CcIgZ3+ B cells were analysed by immunofluorescence staining using an anti-CcIgZ3 polyclonal antibody and an anti-PCNA monoclonal antibody. CcIgZ3 and PCNA (Proliferating Cell Nuclear Antigen) double-labelled cells in the gills were located within the epithelial cells of the gill filaments of common carp stimulated with TNP-LPS at 3 dps and 7 dps, and relatively more proliferating CcIgZ3+ B cells appeared in the gills of common carp at 7 dps. These data imply that CcIgZ3+ B cells in the gills might be produced by local proliferation following TNP-LPS stimulation. In summary, compared with those in TNP-KLH, CcIgZ3 preferentially affects the gills of common carp following challenge with TNP-LPS. CcIgZ3+ B cells proliferate in the gills to quickly produce the CcIgZ3 antibody. In addition, CcIgZ3+ B cells can be activated to induce a strong immune response very early locally in the gill and produce the antibody CcIgZ3, which helps exert an immune-protective effect. These results suggest that an effective vaccine can be designed to promote production of the mucosal antibody CcIgZ3.

Isovaleryl Sucrose Esters from Atractylodes japonica and Their Cytotoxic Activity.

Cancer represents one of the most significant health challenges currently facing humanity, and plant-derived antitumour drugs represent a prominent class of anticancer medications in clinical practice. Isovaleryl sucrose esters, which are natural constituents, have been identified as having potential antitumour effects. However, the mechanism of action remains unclear. In this study, 12 isovaleryl sucrose ester components, including five new (1-5) and seven known compounds (6-12), were isolated from the roots of Atractylodes japonica. The structures of the compounds were elucidated using 1D and 2D-NMR spectroscopy, complemented by HR-ESI-MS mass spectrometry. The cytotoxic activities of all the compounds against human colon cancer cells (HCT-116) and human lung adenocarcinoma cells (A549) were also evaluated using the CCK8 assay. The results demonstrated that compounds 2, 4, and 6 were moderately inhibitory to HCT-116 cells, with IC50 values of 7.49 ± 0.48, 9.03 ± 0.21, and 13.49 ± 1.45 µM, respectively. Compounds 1 and 6 were moderately inhibitory to A549, with IC50 values of 8.36 ± 0.77 and 7.10 ± 0.52 µM, respectively. Molecular docking revealed that compounds 1-9 exhibited a stronger affinity for FGFR3 and BRAF, with binding energies below -7 kcal/mol. Compound 2 exhibited the lowest binding energy of -10.63 kcal/mol to FGFR3. We screened the compounds with lower binding energies, and the protein-ligand complexes already obtained after molecular docking were subjected to exhaustive molecular dynamics simulation experiments, which simulated the dynamic behaviour of the molecules in close proximity to the actual biological environment, thus providing a deeper understanding of their functions and interaction mechanisms. The present study provides a reference for the development and use of iso-valeryl sucrose esters in the antitumour field.

Charge Shielding-Oriented Design of Zinc-Based Nanoparticle Liquids for Controlled Nanofabrication.

Metal-containing nanoparticles possess nanoscale sizes, but the exploitation of their nanofeatures in nanofabrication processes remains challenging. Herein, we report the realization of a class of zinc-based nanoparticle liquids and their potential for applications in controlled nanofabrication. Utilizing the metal-core charge shielding strategy, we prepared nanoparticles that display glass-to-liquid transition behavior with glass transition temperature far below room temperature (down to -50.9 °C). Theoretical calculations suggest the outer surface of these unusual nanoparticles is almost neutral, thus leading to interparticle interactions weak enough to give them liquefaction characteristics. Such features endow them with extraordinarily high dispersibility and excellent film-forming capabilities. Twenty-two types of nanoparticles synthesized by this strategy have all shown good lithographic properties in the mid-ultraviolet, electron beam, or extreme ultraviolet light, and these nanoparticle liquids have achieved controlled top-down nanofabrication with predesigned 18 or 16 nm patterns. This proposed strategy is synthetically scalable and structurally extensible and is expected to inspire the design of entirely new forms of nanomaterials.

Emergence of correlations in alternating twist quadrilayer graphene.

Alternating twist multilayer graphene (ATMG) has recently emerged as a family of moiré systems that share several fundamental properties with twisted bilayer graphene, and are expected to host similarly strong electron-electron interactions near the magic angle. Here, we study alternating twist quadrilayer graphene (ATQG) samples with twist angles of 1.96° and 1.52°, which are slightly removed from the magic angle of 1.68°. At the larger angle, we find signatures of correlated insulators only when the ATQG is hole doped, and no signatures of superconductivity, and for the smaller angle we find evidence of superconductivity, while signs of the correlated insulators weaken. Our results provide insight into the twist angle dependence of correlated phases in ATMG and shed light on the nature of correlations in the intermediate coupling regime at the edge of the magic angle range where dispersion and interaction are of the same order.

Fibrinogen Deposition on Silicone Oil-Infused Silver-Releasing Urinary Catheters Compromises Antibiofilm and Anti-Encrustation Properties.

Slippery silicone-oil-infused (SOI) surfaces have recently emerged as a promising alternative to conventional anti-infection coatings for urinary catheters to combat biofilm and encrustation formation. Benefiting from the ultralow low hysteresis and slippery behavior, the liquid-like SOI coatings have been found to effectively reduce bacterial adhesion under both static and flow conditions. However, in real clinical settings, the use of catheters may also trigger local inflammation, leading to release of host-secreted proteins, such as fibrinogen (Fgn) that deposits on the catheter surfaces, creating a niche that can be exploited by uropathogens to cause infections. In this work, we report on the fabrication of a silicone oil-infused silver-releasing catheter which exhibited superior durability and robust antibacterial activity in aqueous conditions, reducing biofilm formation of two key uropathogens Escherichia coli and Proteus mirabilis by ∼99%, when compared with commercial all-silicone catheters after 7 days while remaining noncytotoxic toward L929 mouse fibroblasts. After exposure to Fgn, the oil-infused surfaces induced conformational changes in the protein which accelerated adsorption onto the surfaces. The deposited Fgn blocked the interaction of silver with the bacteria and served as a scaffold, which promoted bacterial colonization, resulting in a compromised antibiofilm activity. Fgn binding also facilitated the migration of Proteus mirabilis over the catheter surfaces and accelerated the deposition and spread of crystalline biofilm. Our findings suggest that the use of silicone oil-infused silver-releasing urinary catheters may not be a feasible strategy to combat infections and associated complications arising from severe inflammation.

Low-intensity focused ultrasound stimulation reverses social avoidance behavior in mice experiencing social defeat stress.

The excitatory neurons of the medial prefrontal cortex (mPFC) respond to social stimuli. However, little is known about how the neural activity is altered during social avoidance, and whether it could act as a target of low-intensity focused ultrasound stimulation (LIFUS) to rescue social deficits. The present study aimed to investigate the mechanisms of neuronal activities and inflammatory responses underlying the effect of LIFUS on social avoidance. We found that chronic LIFUS stimulation can effectively improve social avoidance in the defeated mice. Calcium imaging recordings by fiber photometry in the defeated mice showed inhibited ensemble activity during social behaviors. LIFUS instantaneously triggered the mPFC neuronal activities, and chronic LIFUS significantly enhanced their neuronal excitation related to social interactions. We further found that the excessive activation of microglial cells and the overexpression of the inflammation signaling, i.e. Toll-like receptors(TLR4)/nuclear factor-kappaB(NF-КB), in mPFC were significantly inhibited by LIFUS. These results suggest that the LIFUS may inhibit social avoidance behavior by reducing activation of the inflammatory response, increasing neuronal excitation, and protecting the integrity of the neuronal structure in the mPFC. Our findings raised the possibility of LIFUS being applied as novel neuromodulation for social avoidance treatment in neuropsychiatric diseases.

Process optimization of line patterns in extreme ultraviolet lithography using machine learning and a simulated annealing algorithm.

Resolution, line edge/width roughness, and sensitivity (RLS) are critical indicators for evaluating the imaging performance of resists. As the technology node gradually shrinks, stricter indicator control is required for high-resolution imaging. However, current research can improve only part of the RLS indicators of resists for line patterns, and it is difficult to improve the overall imaging performance of resists in extreme ultraviolet lithography. Here, we report a lithographic process optimization system of line patterns, where RLS models are first established by adopting a machine learning method, and then these models are optimized using a simulated annealing algorithm. Finally, the process parameter combination with optimal imaging quality of line patterns can be obtained. This system can control resist RLS indicators, and it exhibits high optimization accuracy, which facilitates the reduction of process optimization time and cost and accelerates the development of the lithography process.