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Background Since the emergence of SARS-CoV-2, the causative agent of COVID-19, the global health landscape has confronted an unprecedented and formidable challenge. The SARS-CoV-2 receptor-binding domain (RBD) is a key antigen in vaccine design. However, its low immunogenicity has been a hurdle, resulting in the production of minimal anti-RBD antibodies even when combined with alum adjuvant. Outer membrane vesicles (OMVs), secreted by Gram-negative bacteria, are nanospherical structures that can display or deliver antigens while also providing adjuvant activity through pathogen-associated molecular patterns (PAMPs). Results In this study, we utilized the SpyTag (ST)/SpyCatcher (SC) bioconjugation system to couple OMV and SARS-CoV-2 RBD in vitro. We successfully prepared a ‘plug-and-display’ nanovaccine OMV-RBD, which demonstrated good safety profiles and promoted the uptake of antigens by DCs and the maturation of BMDCs by activating TLR3 and NOD2 signaling pathways. Both intranasal and intramuscular immunization with OMV-RBD vaccine elicited robust antigen-specific humoral and cellular immune responses. Importantly, the induced antibodies effectively inhibited the binding of RBD to human angiotensin-converting enzyme 2 (hACE2) and neutralized SARS-CoV-2 pseudoviruses. Conclusions This vaccine platform offers an alternative strategy for developing recombinant subunit vaccines against SARS-CoV-2, potentially enhancing immune responses and improving vaccine efficacy. Graphical abstract

As TLR2 agonists, several lipopeptides had been proved to be candidate vaccine adjuvants. In our previous study, lipopeptides mimicking N-terminal structures of the bacterial lipoproteins were also able to promote antigen-specific immune response. However, the structure-activity relationship of lipopeptides as TLR2 agonists is still unclear. Here, 23 synthetic lipopeptides with the same lipid moiety but different peptide sequences were synthesized, and their TLR2 activities in vitro and mucosal adjuvant effects to OVA were evaluated. LP1-14, LP1-30, LP1-34 and LP2-2 exhibited significantly lower cytotoxicity and stronger TLR2 activity compared with Pam 2 CSK 4 , the latter being one of the most potent TLR2 agonists. LP1-34 and LP2-2 assisted OVA to induce more profound specific IgG in sera or sIgA in BALF than Pam 2 CSK 4 . Furthermore, the possibility of LP1-34, LP2-2 and Pam 2 CSK 4 as the mucosal adjuvant for the SARS-CoV-2 recombinant RBD (rRBD) was investigated. Intranasally immunized with rRBD plus either the novel lipopeptide or Pam 2 CSK 4 significantly increased the levels of specific serum and respiratory mucosal IgG and IgA, while rRBD alone failed to induce specific immune response due to its low immunogenicity. The novel lipopeptides, especially LP2-2, significantly increased levels of rRBD-induced SARS-CoV-2 neutralizing antibody in sera, BALF and nasal wash. Finally, Support vector machine (SVM) results suggested that charged residues in lipopeptides might be beneficial to the agonist activity, while lipophilic residues might adversely affect the agonistic activity. Figuring out the relationship between peptide sequence in the lipopeptide and its TLR2 activity may lay the foundation for the rational design of novel lipopeptide adjuvant for COVID-19 vaccine.

Osteoarthritis (OA) is a degenerative disease with a high prevalence in the elderly population, but our understanding of its mechanisms remains incomplete. Analysis of serum exosomal small RNA sequencing data from clinical patients and gene expression data from OA patient serum and cartilage obtained from the GEO database revealed a common dysregulated miRNA, miR-199b-5p. In vitro cell experiments demonstrated that miR-199b-5p inhibits chondrocyte vitality and promotes extracellular matrix degradation. Conversely, inhibition of miR-199b-5p under inflammatory conditions exhibited protective effects against damage. Local viral injection of miR-199b-5p into mice induced a decrease in pain threshold and OA-like changes. In an OA model, inhibition of miR-199b-5p alleviated the pathological progression of OA. Furthermore, bioinformatics analysis and experimental validation identified Gcnt2 and Fzd6 as potential target genes of MiR-199b-5p . Thus, these results indicated that MiR-199b-5p / Gcnt2 and Fzd6 axis might be a novel therapeutic target for the treatment of OA.

Large-area single-crystal monolayers of two-dimensional (2D) materials such as graphene 1 – 3 , hexagonal boron nitride (hBN) 4 – 6 and transition metal dichalcogenides 7 , 8 have been grown. hBN is considered to be the ‘ideal’ dielectric for 2D-materials-based field-effect transistors (FETs), offering the potential for extending Moore’s law 9 , 10 . Although hBN thicker than a monolayer is more desirable as substrate for 2D semiconductors 11 , 12 , highly uniform and single-crystal multilayer hBN growth has yet to be demonstrated. Here we report the epitaxial growth of wafer-scale single-crystal trilayer hBN by a chemical vapour deposition (CVD) method. Uniformly aligned hBN islands are found to grow on single-crystal Ni (111) at early stage and finally to coalesce into a single-crystal film. Cross-sectional transmission electron microscopy (TEM) results show that a Ni 23 B 6 interlayer is formed (during cooling) between the single-crystal hBN film and Ni substrate by boron dissolution in Ni. There are epitaxial relationships between hBN and Ni 23 B 6 and between Ni 23 B 6 and Ni. We also find that the hBN film acts as a protective layer that remains intact during catalytic evolution of hydrogen, suggesting continuous single-crystal hBN. This hBN transferred onto the SiO 2 (300 nm)/Si wafer acts as a dielectric layer to reduce electron doping from the SiO 2 substrate in MoS 2 FETs. Our results demonstrate high-quality single-crystal  multilayered hBN over large areas, which should open up new pathways for making it a ubiquitous substrate for 2D semiconductors. Using a chemical vapour deposition method, it is possible to epitaxially grow wafer-scale single-crystal trilayers of hexagonal boron nitride—an important dielectric for 2D materials—on Ni (111) foils by boron dissolution.

Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.

Major depressive disorder (MDD) is a globally prevalent and highly disabling disease characterized by dysfunction of large-scale brain networks. Previous studies have found that static functional connectivity is not sufficient to reflect the complicated and time-varying properties of the brain. The underlying dynamic interactions between brain functional networks of MDD remain largely unknown, and it is also unclear whether neuroimaging-based dynamic properties are sufficiently robust to discriminate individuals with MDD from healthy controls since the diagnosis of MDD mainly depends on symptom-based criteria evaluated by clinical observation. Resting-state functional magnetic resonance imaging (fMRI) data of 221 MDD patients and 215 healthy controls were shared by REST-meta-MDD consortium. We investigated the spatial-temporal dynamics of MDD using co-activation pattern analysis and made individual diagnoses using support vector machine (SVM). We found that MDD patients exhibited aberrant dynamic properties (such as dwell time, occurrence rate, transition probability, and entropy of Markov trajectories) in some transient networks including subcortical network (SCN), activated default mode network (DMN), de-activated SCN-cerebellum network, a joint network, activated attention network (ATN), and de-activated DMN-ATN, where some dynamic properties were indicative of depressive symptoms. The trajectories of other networks to deactivated DMN-ATN were more accessible in MDD patients. Subgroup analyses also showed subtle dynamic changes in first-episode drug-naïve (FEDN) MDD patients. Finally, SVM achieved preferable accuracies of 84.69%, 76.77%, and 88.10% in discriminating patients with MDD, FEDN MDD, and recurrent MDD from healthy controls with their dynamic metrics. Our findings reveal that MDD is characterized by aberrant dynamic fluctuations of brain network and the feasibility of discriminating MDD patients using dynamic properties, which provide novel insights into the neural mechanism of MDD.

Objectives The current study aimed to investigate the structural and functional connectivity of the subregions of the amygdala in children with Attention Deficit/Hyperactivity Disorder (ADHD) only or comorbid with Oppositional Defiant Disorder (ODD). Methods A total of 354 children with ADHD-only, 161 children with ADHD and ODD (ADHD + ODD), and 100 healthy controls were enrolled. The Child Behavior Checklist (CBCL) and the Behavior Rating Inventory of Executive Function (BRIEF) were filled out by caregivers. Analysis of covariance (ANCOVA) was performed to test group-wise differences in these behavioral measures. A subsample comprising 209 participants underwent a resting-state functional MRI scan and a diffusion-weighted imaging (DWI) scan. Functional connectivity and structural connectivity were calculated using bilateral subregions of the Amygdala as seeds. Between-group voxel-wise comparisons were conducted. Results The ADHD + ODD group had more anxious/depressed moods, more delinquent and aggressive behaviors, more emotional control problems, and more inhibition deficits than the ADHD-only group (all P Bonferroni−corrected < 0.05). Compared with the control and ADHD + ODD groups, the ADHD-only group displayed increased FC strength between the amygdala subregions and the left caudate, left putamen, and frontal cortex. Regarding structural connectivity (SC), the ADHD-only group demonstrated higher streamline density in the left internal capsule, corpus callosum, and the right superior corona radiata. The altered SC was associated with emotional problems in children with ADHD, while the altered FC was associated with other ADHD-related clinical features. Conclusions Altered structural and functional connectivity of the subregions of the amygdala in children with ADHD compared with their healthy counterparts were respectively associated with ADHD-related behavioral and emotional problems. Clinical trial number : not applicable.

We report on the embedded silver (Ag) nanoparticles fabricated by Ag + ion implantation into the Bi 4 Ge 3 O 12 (BGO) crystal. Localized surface plasmon resonance (LSPR) phenomenon has been observed by linear optical absorption spectrum, which is accordance with the expectation based on Mie theory calculation. Further proofs are given by SRIM, TEM and SAED analysis, which explain the slight difference between experiment and calculation. Based on the z-scan system, it is found that the nonlinear optical response is converted from two-photon absorption to three-photon absorption under the 515 nm femtosecond pulse excitation within the LSPR band. The nonlinear absorption coefficient is measured to be ~3.1 × 10 −9  cm/W (two-photon absorption coefficient) and ~8.9 × 10 −14 cm 3 /W 2 (three-photon absorption coefficient) for pure BGO crystal and the sample embedded with Ag nanoparticles (Ag:BGO), respectively. Finally, we have proposed a model to explain the asymmetric nonlinear transmittance, which is in good agreement with the experimental results.

Previous studies in small samples have identified inconsistent cortical abnormalities in major depressive disorder (MDD). Despite genetic influences on MDD and the brain, it is unclear how genetic risk for MDD is translated into spatially patterned cortical vulnerability. Here, we initially examined voxel-wise differences in cortical function and structure using the largest multi-modal MRI data from 1660 MDD patients and 1341 controls. Combined with the Allen Human Brain Atlas, we then adopted transcription-neuroimaging spatial correlation and the newly developed ensemble-based gene category enrichment analysis to identify gene categories with expression related to cortical changes in MDD. Results showed that patients had relatively circumscribed impairments in local functional properties and broadly distributed disruptions in global functional connectivity, consistently characterized by hyper-function in associative areas and hypo-function in primary regions. Moreover, the local functional alterations were correlated with genes enriched for biological functions related to MDD in general (e.g., endoplasmic reticulum stress, mitogen-activated protein kinase, histone acetylation, and DNA methylation); and the global functional connectivity changes were associated with not only MDD-general, but also brain-relevant genes (e.g., neuron, synapse, axon, glial cell, and neurotransmitters). Our findings may provide important insights into the transcriptomic signatures of regional cortical vulnerability to MDD. Our combined large-scale neuroimaging and brain transcriptome study demonstrates genetic substrates underlying cortical functional abnormalities in depression, suggesting transcriptomic decoding of regional cortical vulnerability to depression.

Background Autistic traits (ATs) are frequently reported in children with Attention-Deficit/Hyperactivity Disorder (ADHD). This study aimed to examine ATs in children with ADHD from both behavioral and neuroimaging perspectives. Methods We used the Autism Spectrum Screening Questionnaire (ASSQ) to assess and define subjects with and without ATs. For behavioral analyses, 67 children with ADHD and ATs (ADHD + ATs), 105 children with ADHD but without ATs (ADHD − ATs), and 44 typically developing healthy controls without ATs (HC − ATs) were recruited. We collected resting-state functional magnetic resonance imaging (rs-fMRI) data and analyzed the mean amplitude of low-frequency fluctuation (mALFF) values (an approach used to depict different spontaneous brain activities) in a sub-sample. The imaging features that were shared between ATs and ADHD symptoms or that were unique to one or the other set of symptoms were illustrated as a way to explore the “brain–behavior” relationship. Results Compared to ADHD-ATs, the ADHD + ATs group showed more global impairment in all aspects of autistic symptoms and higher hyperactivity/impulsivity (HI). Partial-correlation analysis indicated that HI was significantly positively correlated with all aspects of ATs in ADHD. Imaging analyses indicated that mALFF values in the left middle occipital gyrus (MOG), left parietal lobe (PL)/precuneus, and left middle temporal gyrus (MTG) might be specifically related to ADHD, while those in the right MTG might be more closely associated with ATs. Furthermore, altered mALFF in the right PL/precuneus correlated with both ADHD and ATs, albeit in diverse directions. Conclusions The co-occurrence of ATs in children with ADHD manifested as different behavioral characteristics and specific brain functional alterations. Assessing ATs in children with ADHD could help us understand the heterogeneity of ADHD, further explore its pathogenesis, and promote clinical interventions.