KERS-Inspired Nanostructured Mineral Coatings Boost IFN-γ mRNA Therapeutic Index for Antitumor Immunotherapy

Tumor-associated macrophage (TAM) reprogramming is a promising therapeutic approach for cancer immunotherapy; however, its efficacy remains modest due to the low bioactivity of the recombinant cytokines used for TAM reprogramming. mRNA therapeutics are capable of generating fully functional proteins for various therapeutic purposes but accused for its poor sustainability. Inspired by kinetic energy recovery systems (KERS) in hybrid vehicles, a cytokine efficacy recovery system (CERS) is designed to substantially augment the therapeutic index of mRNA-based tumor immunotherapy via a "capture and stabilize" mechanism exerted by a nanostructured mineral coating carrying therapeutic cytokine mRNA. CERS remarkably recycles nearly 40% expressed cytokines by capturing them onto the mineral coating to extend its therapeutic timeframe, further polarizing the macrophages to strengthen their tumoricidal activity and activate adaptive immunity against tumors. Notably, interferon-γ (IFN-γ) produced by CERS exhibits ≈42-fold higher biological activity than recombinant IFN-γ, remarkably decreasing the required IFN-γ dosage for TAM reprogramming. In tumor-bearing mice, IFN-γ cmRNA@CERS effectively polarizes TAMs to inhibit osteosarcoma progression. When combined with the PD-L1 monoclonal antibody, IFN-γ cmRNA@CERS significantly boosts antitumor immune responses, and substantially prevents malignant lung metastases. Thus, CERS-mediated mRNA delivery represents a promising strategy to boost antitumor immunity for tumor treatment.

Nigrospora oryzae Causing Leaf Spot Disease on Chrysanthemum × morifolium Ramat and Screening of Its Potential Antagonistic Bacteria

Chrysanthemum × morifolium Ramat. is a famous perennial herb with medicinal, edible, and ornamental purposes, but the occurrence of plant diseases can reduce its value. A serious disease that caused leaf spots in C. morifolium appeared in 2022 in Tongxiang City, Zhejiang Province, China. The C. morifolium leaves with brown spots were collected and used for pathogen isolation. By completing Koch's postulates, it was proven that the isolate had pathogenicity to infect C. morifolium. It was determined that the pathogen isolated from chrysanthemum leaves was Nigrospora oryzae, through morphology and a multilocus sequence analysis method using a combination of the internal transcribed spacer gene (ITS), beta-tubulin gene (TUB2), and translation elongation factor 1-alpha gene (TEF1-α). This is the first report of C. morifolium disease caused by N. oryzae in the world. Through dual culture assay on PDA plates, 12 strains of bacteria with antagonistic effects were selected from 231 strains from the C. morifolium phyllosphere, among which Bacillus siamensis D65 had the best inhibitory effect on N. oryzae growth. In addition, the components of a strain D65 fermentation broth were profiled by SPME-GC-Q-TOF analysis, providing a foundation for further application and research of biological control.

Intestine epithelial cell-derived extracellular vesicles alleviate inflammation induced by Clostridioides difficile TcdB through the activity of TGF-β1

Background

Clostridioides difficile infection (CDI) has been primarily associated with the toxin B (TcdB), one of the three known protein toxins secreted by C. difficile, which can activate the intestinal immune system and lead to pathological damage. Even though the biological functions of intestine epithelial cell-derived extracellular vesicles (I-Evs) have been well documented, the role of I-Evs in the process of CDI is still unknown.

Objectives

The protective effect of I-Evs against C. difficile TcdB was investigated both in cultured murine colon carcinoma MC38 cells and a mouse model used in this study.

Results

Mouse I-Evs with mean diameter ranging from 100 to 200 nm and a density of 1.09-1.17 g/mL were obtained and confirmed containing the Ev-associated specific surface markers CD63 and TSG101 as well as high level of TGF-β1. In MC38 cells, I-Evs were able to decrease the gene expression of IL-6, TNF-α, IL-1β, and IL-22 induced by C. difficile TcdB, but to increase both the gene expression and protein levels of TGF-β1. I-Evs treatment via intraperitoneal administration alleviates C. difficile TcdB-induced local colon inflammation in mice and increased their survival rate from 50% up to 80%. Furthermore, I-Evs induced an increase in the proportion of CD4+Foxp3+Tregs in vitro and in vivo through a TGF-β1-dependent mechanism by activating the TGF-β1 pathway and prompting phosphorylation of the downstream proteins Smad 2/3.

Conclusion

For the first time, our study demonstrated that I-Evs originated from intestine epithelial cells can alleviate inflammation induced by C. difficile TcdB both in vitro and in vivo. Therefore, I-Evs might be potentially a novel endogenous candidate for effective treatment of CDI.

Meibomian Gland Density: An Effective Evaluation Index of Meibomian Gland Dysfunction Based on Deep Learning and Transfer Learning

We aimed to establish an artificial intelligence (AI) system based on deep learning and transfer learning for meibomian gland (MG) segmentation and evaluate the efficacy of MG density in the diagnosis of MG dysfunction (MGD). First, 85 eyes of 85 subjects were enrolled for AI system-based evaluation effectiveness testing. Then, from 2420 randomly selected subjects, 4006 meibography images (1620 upper eyelids and 2386 lower eyelids) graded by three experts according to the meiboscore were analyzed for MG density using the AI system. The updated AI system achieved 92% accuracy (intersection over union, IoU) and 100% repeatability in MG segmentation after 4 h of training. The processing time for each meibography was 100 ms. We discovered a significant and linear correlation between MG density and ocular surface disease index questionnaire (OSDI), tear break-up time (TBUT), lid margin score, meiboscore, and meibum expressibility score (all p < 0.05). The area under the curve (AUC) was 0.900 for MG density in the total eyelids. The sensitivity and specificity were 88% and 81%, respectively, at a cutoff value of 0.275. MG density is an effective index for MGD, particularly supported by the AI system, which could replace the meiboscore, significantly improve the accuracy of meibography analysis, reduce the analysis time and doctors’ workload, and improve the diagnostic efficiency.

The application framework of big data technology during the COVID-19 pandemic in China

Big data has been reported widely to facilitate epidemic prevention and control in health care during the coronavirus disease 2019 (COVID-19) pandemic. However, there is still a lack of practical experience in applying it to hospital prevention and control. This study is devoted to the practical experience of design and implementation as well as the preliminary results of an innovative big data-driven COVID-19 risk personnel screening management system in a hospital. Our screening system integrates data sources in four dimensions, which includes Health Quick Response (QR) code, abroad travelling history, transportation close contact personnel and key surveillance personnel. Its screening targets cover all patients, care partner and staff who come to the hospital. As of November 2021, nearly 690 000 people and 5.79 million person-time had used automated COVID-19 risk screening and monitoring. A total of 10 376 person-time (0.18%) with abnormal QR code were identified, 242 person-time with abroad travelling history were identified, 925 person-time were marked based on the data of key surveillance personnel, no transportation history personnel been reported and no COVID-19 nosocomial infection occurred in the hospital. Through the application of this system, the hospital's expenditure on manpower and material resources for epidemic prevention and control has also been significantly reduced. Collectively, this study has proved to be an effective and efficient model for the use of digital health technology in response to the COVID-19 pandemic. Based on the data from multiple sources, this system has an irreplaceable role in identifying close contacts or suspicious person, and can significantly reduce the social burden caused by COVID-19, especially the human resources and economic costs of hospital prevention and control. It may provide guidance for clinical epidemic prevention and control in hospitals, as well as for future public health emergencies.