Background: Atopic dermatitis (AD) is a biphasic type of skin inflammation characterized by a predominance of type-2 ­(TH2) and type-1 ­(TH1) helper T cell-biased immune responses at the acute and persistent chronic phases, respectively. The present study was aimed to evaluate the efficacy of Artemisia dubia folium extract (ADFE) on ADlike skin lesions through developing a murine model for acute and chronic stages of AD. To induce acute phase AD, the dorsal skin of BALB/c mice was sensitized twice a week with 1% 2, 4-dinitrochlorobenzene (DNCB), followed by challenge (twice) in the following week with 0.2% DNCB. To induce persistent chronic AD, some mice were challenged twice a week for 4 more weeks. After the second challenge, the dorsal skin was exposed to 3% ADFE (five times per week) for 2 weeks (acute phase) or 4 weeks (persistent chronic phase). Results: The paradigm of ­TH2 or  ­TH1 predominance at the acute and chronic phase, respectively, was observed in this mouse model. During the acute phase, we observed an increased IL-4/IFN-γ ratio in splenic culture supernatants,an increased IgG1/IgG2a ratio in serum, and elevated serum IgE levels; however, the skew toward ­TH2 responses was diminished during the chronic stage. Compared with vehicle controls, ADFE reduced the IL-4/IFN-γ and IgG1/ IgG2a ratios in acute AD, but both ratios increased during the chronic stage. Conclusions Our results suggest that ADFE concomitantly suppresses the ­TH2 predominant response in acute AD, as well as the ­TH1 predominant response in chronic AD. Thus, ADFE is a candidate therapeutic for AD.

To enhance the efficiency of vaccine manufacturing, this study focuses on optimizing the microfluidic conditions and lipid mix ratios of messenger RNA-lipid nanoparticles (mRNA-LNP). Different mRNA-LNP formulations (n = 24) were developed using an I-optimal design, where machine learning tools (XGBoost/Bayesian optimization and self-validated ensemble (SVEM)) were used to optimize the process and predict lipid mix ratio. The investigation included material attributes, their respective ratios, and process attributes. The critical responses like particle size (PS), polydispersity index (PDI), Zeta potential, pKa, heat trend cycle, encapsulation efficiency (EE), recovery ratio, and encapsulated mRNA were evaluated. Overall prediction of SVEM (>97%) was comparably better than that of XGBoost/Bayesian optimization (>94%). Moreover, in actual experimental outcomes, SVEM prediction is close to the actual data as confirmed by the experimental PS (94-96 nm) is close to the predicted one (95-97 nm). The other parameters including PDI and EE were also close to the actual experimental data.

To enhance the efficiency of vaccine manufacturing,this study focuses on optimizing the microfluidic conditions and lipid mix ratios of messenger RNA-lipid nanoparticles(mRNA-LNP).Different mRNA-LNP formulations(n=24)were developed using an I-optimal design,where machine learning tools(XGBoost/Bayesian optimization and self-validated ensemble(SVEM))were used to optimize the process and predict lipid mix ratio.The investigation included material attributes,their respective ratios,and process attributes.The critical responses like particle size(PS),polydispersity index(PDI),Zeta potential,pKa,heat trend cycle,encapsulation efficiency(EE),recovery ratio,and encapsulated mRNA were eval-uated.Overall prediction of SVEM(＞97％)was comparably better than that of XGBoost/Bayesian opti-mization(＞94％).Moreover,in actual experimental outcomes,SVEM prediction is close to the actual data as confirmed by the experimental PS(94-96 nm)is close to the predicted one(95-97 nm).The other parameters including PDI and EE were also close to the actual experimental data.

Background: Occupational hazards in crop farms vary diversely based on different field operations as soil management, harvesting processes, pesticide, or fertilizer application. We aimed at evaluating the immunological status of crop farmers, as limited systematic investigations on immune alteration involved with crop farming have been reported yet. Methods: Immunological parameters including plasma immunoglobulin level, major peripheral immune cells distribution, and level of cytokine production from activated T cell were conducted. Nineteen grape orchard, 48 onion open-field, and 21 rose greenhouse farmers were participated. Results: Significantly low proportion of natural killer (NK) cell, a core cell for innate immunity, was revealed in the grape farmers (19.8 ± 3.3%) in comparison to the onion farmers (26.4 ± 3.1%) and the rose farmers (26.9 ± 2.5%), whereas cytotoxic T lymphocyte proportion was lower in the grape and the onion farmers than the rose farmers. The proportion of NKT cell, an immune cell implicated with allergic response, was significantly higher in the grape (2.3 ± 0.3%) and the onion (1.6 ± 0.8%) farmers compared with the rose farmers (1.0 ± 0.4%). A significantly decreased interferon-gamma:interleukin-13 ratio was observed from ex vivo stimulated peripheral blood mononuclear cells of grape farmers compared with the other two groups. The grape farmers revealed the lowest levels of plasma IgG1 and IgG4, and their plasma IgE level was not significantly different from that of the onion or the rose farmers. Conclusion Our finding suggests the high vulnerability of workplace-mediated allergic immunity in grape orchard farmers followed by open-field onion farmers and then the rose greenhouse farmers.