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The coronavirus SARS-CoV-2 has mutated quickly and caused significant global damage. This study characterizes two mRNA vaccines ZSVG-02 (Delta) and ZSVG-02-O (Omicron BA.1), and associating heterologous prime-boost strategy following the prime of a most widely administrated inactivated whole-virus vaccine (BBIBP-CorV). The ZSVG-02-O induces neutralizing antibodies that effectively cross-react with Omicron subvariants. In naïve animals, ZSVG-02 or ZSVG-02-O induce humoral responses skewed to the vaccines targeting strains, but cellular immune responses cross-react to all variants of concern (VOCs) tested. Following heterologous prime-boost regimes, animals present comparable neutralizing antibody levels and superior protection against Delta and Omicron BA.1variants. Single-boost only generated ancestral and omicron dual-responsive antibodies, probably by recall and reshape the prime immunity. New Omicron-specific antibody populations, however, appeared only following the second boost with ZSVG-02-O. Overall, our results support a heterologous boost with ZSVG-02-O, providing the best protection against current VOCs in inactivated virus vaccine-primed populations.

This study aimed to explore the effects of osteogenic growth peptide C-terminal pentapeptide (G36G), and its analog G48A on bone modeling in rats with ovariectomy-induced osteoporosis. Ovariectomized rats were administered PBS (OVX group), risedronate (RISE group), G36G combined with risedronate (36GRI group), G36G (G36G group), or G48A (G48A group). The sham-operation rats (SHAM group) were administered PBS. Serum osteocalcin and IGF-2 levels in the SHAM, OVX, G36G, G48A, and RISE groups were observably lower than the 36GRI group (P < 0.01) and the bone mineral density of the entire femur, distal metaphysis, and lumbar L1–L4 in the 36GRI group were notably increased (P < 0.05). The bending energy of the 36GRI group was prominently higher than the other groups (P < 0.05). Other features measured in the study that provided significant outcomes was the ratio of femora ash weight/dry weigh, parameters of trabecular bone volume (TBV)/total tissue volume, TBV/sponge bone volume, mean trabecular plate thickness, mean trabecular plate space, bone surface, parameters of sfract(s) and sfract(d), tetracycline-labeled, and osteoid surfaces. Bone loss in ovariectomized rats may be partially inhibited by G36G and G48A. A combination treatment with G36G and risedronate may be an effective intervention for osteoporosis.

To solve the problems of difficult to model parameter selections, useful signal extraction and improper-signal decomposition in nonlinear, non-stationary dam displacement time series prediction methods, we propose a new predictive model for grey wolf optimization and variational mode decomposition and long short-term memory (GVLSTM). Firstly, we used the grey wolf optimization (GWO) algorithm to optimize the parameters of variable mode decomposition (VMD), obtaining the optimal parameter combination. Secondly, we used multiscale permutation entropy (MPE) as a standard to select signal screening, determining and recon-structing the effective modal components. Finally, the long short-term memory neural network (LSTM) was used to learn the dam deformation characteristics. The result shows that the GVLSTM model can effectively reduce the estimation deviation of the prediction model. Compared with VMDGRU and VMDANN, the average RMSE and MAE value of each station is increased by 19.11%~28.58% and 27.66%~29.63%, respectively. We used determination (R2) coefficient to judge the performance of the prediction model, and the value of R2 was 0.95~0.97, indicating that our method has good performance in predicting dam deformation. The proposed method has outstanding advantages of high accuracy, reliability, and stability for dam deformation prediction. [ABSTRACT FROM AUTHOR]

The (diphtheria, tetanus, and pertussis [acellular, component] [DTacP]) vaccine is a combined vaccine designed to prevent three potentially fatal diseases including pertussis, tetanus, and diphtheria in both children and adults. We utilized advanced technology to develop a novel DTacP vaccine that was previously unavailable in China. The nonclinical studies were performed to evaluate the immunogenicity, potential toxicity, and local tolerance of the vaccine in animal models. In the immunogenicity study, three batches of the vaccine were intraperitoneally administered to National Institutes of Health (NIH) mice, resulting in 100% seropositivity for all three batches. Additionally, antibody levels notably increased as the immunization dosage increased. In acute toxicity study, no mortality was observed among the animals during the 14‐day observation period, and no abnormalities in clinical signs were reported. Active systemic anaphylaxis assessment in guinea pigs showed no evidence of serious allergic reactions in the vaccine groups. In the repeat‐dose toxicity study, where five intramuscular doses were administered every 2 weeks, gross autopsy and histopathological examination revealed no vaccine‐related systemic pathological changes in rats, with dose site irritant reactions mostly recovered at the end of recovery period. In conclusion, the vaccine demonstrated good local and systemic tolerance, supporting its clinical development. We developed a novel DTacP vaccine that was previously unavailable in China and evaluated the immunogenicity, potential toxicity, and local tolerance of the vaccine in animal models. The seropositivity of vaccines reached 100% in mice. Acute toxicity study, active systemic anaphylaxis study, and repeat‐dose toxicity study showed no clinical signs abnormalities, and moderate irritant reactions were observed and mostly recovered at the end of recovery period. The DTacP vaccine demonstrated good local and systemic tolerance, supporting its clinical development. [ABSTRACT FROM AUTHOR]

The identification of machining processes for low roughness samples is extremely challenging, and a reasonably quick identification of machining processes for low roughness parts is critical for ensuring that the samples are employed under the appropriate conditions and improving work efficiency. In this work, a new identification method of fusion of LIBS spectra and plasma acoustic emission signals (PAESs) with bimodal information is proposed, and the LIBS spectral data and PAES data of nine types of low roughness samples processed by three machining processes, namely horizontal milling, plain grinding, and vertical milling, are recorded and analyzed. The spectral intensities of the primary element Fe and trace element Mn are compared and analyzed. The spectrum intensities of the primary element Fe and trace element Mn, as well as the PAES maximum peak, are compared and examined. Using the PCA-SVM machine learning technique, the three recognition impacts of single LIBS data, single PAES data, and LIBS-PAES bimodal data fusion are examined and compared. At Ra = 0.4 μm and 0.8 μm, vertical milling produces significantly higher spectral intensities than plain grinding and horizontal milling, while horizontal milling produces significantly higher intensities than plain grinding. When the surface roughness of the samples is the same, variations in the machining process cause changes in the PAES. The recognition accuracy was 86.67% for the test set of single LIBS spectral data, 78.89% for the test set of single PAES data, and 97.11% for the training set, and 91.11% for the test set of LIBS-PAES bimodal data fusion, respectively. When compared to single-modal data recognition, bimodal data fusion greatly improves recognition ability, fully reflecting the benefits of bimodal data fusion. Based on the results of this study, it can be preliminarily concluded that the fusion of spectral and acoustic information in laser-induced breakdown spectroscopy detection is very promising for recognizing the surface state of parts in the machining field. [ABSTRACT FROM AUTHOR]