A modified recombinant adenovirus vector containing dual rabies virus G expression cassettes confers robust and long-lasting humoral immunity in mice, cats, and dogs.

During the COVID-19 epidemic, the incidence of rabies has increased in several countries, especially in remote and disadvantaged areas, due to inadequate surveillance and declining immunization coverage. Multiple vaccinations with inactivated rabies virus vaccines for pre- or post-exposure prophylaxis are considered inefficient, expensive and impractical in developing countries. Herein, three modified human recombinant adenoviruses type 5 designated Adv-RVG, Adv-E1-RVG, and Adv-RVDG, carrying rabies virus G (RVG) expression cassettes in various combinations within E1 or E3 genomic regions, were constructed to serve as rabies vaccine candidates. Adv-RVDG mediated greater RVG expression both in vitro and in vivo and induced a more robust and durable humoral immune response than the rabies vaccine strain SAD-L16, Adv-RVG, and Adv-E1-RVG by more effectively activating the dendritic cells (DCs) - follicular helper T (Tfh) cells - germinal centre (GC) / memory B cells (MBCs) - long-lived plasma cells (LLPCs) axis with 100% survival after a lethal RABV challenge in mice during the 24-week study period. Similarly, dogs and cats immunized with Adv-RVDG showed stronger and longer-lasting antibody responses than those vaccinated with a commercial inactivated rabies vaccine and showed good tolerance to Adv-RVDG. In conclusion, our study demonstrated that simultaneous insertion of protective antigens into the E1 and E3 genomic regions of adenovirus vector can significantly enhance the immunogenicity of adenoviral-vectored vaccines, providing a theoretical and practical basis for the subsequent development of multivalent and multi-conjugated vaccines using recombinant adenovirus platform. Meanwhile, our data suggest Adv-RVDG is a safe, efficient, and economical vaccine for mass-coverage immunization.

Correction: Plasma extracellular vesicle phenotyping for the differentiation of early-stage lung cancer and benign lung diseases.

Correction for 'Plasma extracellular vesicle phenotyping for the differentiation of early-stage lung cancer and benign lung diseases' by Liwen Yuan et al., Nanoscale Horiz., 2023, 8, 746-758, https://doi.org/10.1039/d2nh00570k.

Recent progress of emitting long-wavelength carbon dots and their merits for visualization tracking, target delivery and theranostics.

As a novel strategy for in vivo visualization tracking and monitoring, carbon dots (CDs) emitting long wavelengths (LW, 600-950 nm) have received tremendous attention due to their deep tissue penetration, low photon scattering, satisfactory contrast resolution and high signal-to-background ratios. Although, the mechanism of CDs emitting LW remains controversial and what properties are best for in vivo visualization have not been specifically elucidated, it is more conducive to the in vivo application of LW-CDs through rational design and ingenious synthesis based on the appreciation of the luminescence mechanism. Therefore, this review analyzes the current tracer technologies applied in vivo and their advantages and disadvantages, with emphasis on the physical mechanism of emitting LW fluorescence for in vivo imaging. Subsequently, the general properties and merits of LW-CDs for tracking and imaging are summarized. More importantly, the factors affecting the synthesis of LW-CDs and its luminescence mechanism are highlighted. Simultaneously, the application of LW-CDs for disease diagnosis, integration of diagnosis and therapy are summarized. Finally, the bottlenecks and possible future directions of LW-CDs in visualization tracking and imaging in vivo are detailly discussed.

Machine learning-assisted global DNA methylation fingerprint analysis for differentiating early-stage lung cancer from benign lung diseases.

DNA methylation plays a critical role in the development of human tumors. However, routine characterization of DNA methylation can be time-consuming and labor-intensive. We herein describe a sensitive, simple surface-enhanced Raman spectroscopy (SERS) approach for identifying the DNA methylation pattern in early-stage lung cancer (LC) patients. By comparing SERS spectra of methylated DNA bases or sequences with their counterparts, we identified a reliable spectral marker of cytosine methylation. To move toward clinical applications, we applied our SERS strategy to detect the methylation patterns of genomic DNA (gDNA) extracted from cell line models as well as formalin-fixed paraffin-embedded tissues of early-stage LC and benign lung diseases (BLD) patients. In a clinical cohort of 106 individuals, our results showed distinct methylation patterns in gDNA between early-stage LC (n = 65) and BLD patients (n = 41), suggesting cancer-induced DNA methylation alterations. Combined with partial least square discriminant analysis, early-stage LC and BLD patients were differentiated with an area under the curve (AUC) value of 0.85. We believe that the SERS profiling of DNA methylation alterations, together with machine learning could potentially offer a promising new route toward the early detection of LC.

Plasma extracellular vesicle phenotyping for the differentiation of early-stage lung cancer and benign lung diseases.

The development of a minimally invasive technique for early-stage lung cancer detection is crucial to reducing mortality. Phenotyping of tumor-associated extracellular vesicles (EVs) has the potential for early-stage lung cancer detection, yet remains challenging due to the lack of sensitive, integrated techniques that can accurately detect rare tumor-associated EV populations in blood. Here, we integrated gold core-silver shell nanoparticles and nanoscopic mixing in a microfluidic assay for sensitive phenotypic analysis of EVs directly in plasma without EV pre-isolation. The assay enabled multiplex detection of lung cancer-associated markers PTX3 and THBS1 and canonical EV marker CD63 by surface-enhanced Raman spectroscopy, providing a squared correlation coefficient of 0.97 in the range of 103-107 EVs mL-1 and a limit of detection of 19 EVs mL-1. Significantly, our machine learning-based nanostrategy provided 92.3% sensitivity and 100% specificity in differentiating early-stage lung cancer from benign lung diseases, superior to the CT scan-based lung cancer diagnosis (92.3% sensitivity and 71.4% specificity). Overall, our integrated nanostrategy achieved an AUC value of 0.978 in differentiating between early-stage lung cancer patients (n = 28) and controls consisting of patients with benign lung diseases (n = 23) and healthy controls (n = 26), which showed remarkable diagnostic performance and great clinical potential for detecting the early occurrence of lung cancer.

Core-shell nanosystems designed for effective oral delivery of polypeptide drugs.

The stomach acid degradation, mucus clearance and intestinal epithelial impermeability severely limit the oral delivery of polypeptide drugs. To simultaneously address the three major barriers, novel self-assembled core-shell nanosystems (CA-NPs) were designed. The fabricated shell of citric acid cross-linked carboxymethyl cellulose (CA-CMC) wrapped on core nanoparticles (HA-NPs) maintained the integrity of CA-NPs in the stomach. When CA-NPs passed through the stomach, the CA-CMC shell was gradually degraded to release the core HA-NPs in the intestine. HA-NPs with numerous hydrophilic groups and mannose side chains rapidly penetrated through the mucus layer and efficiently transcellular transported via the glucose transporter (GLUT)-mediated and paracellular transport through reversible opening of tight junctions (TJs) by CA-CMC. The oral bioavailability and therapeutic effects of CA-NPs-loaded polypeptide colistin against Escherichia coli (E. coli) bacteremia in mice were significantly increased compared with the native colistin, respectively. Good safety was observed following oral daily delivery for 14 consecutive days. Thus, CA-NPs may offer a promising strategy for the oral delivery of polypeptide drugs.