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The interaction between environmental stressors, such as cold exposure, and immune function significantly impacts human health. Research on effective therapeutic strategies to combat cold-induced immunosuppression is limited, despite its importance. In this study, we aim to investigate whether traditional herbal medicine can counteract cold-induced immunosuppression. We previously demonstrated that cold exposure elevated immunoglobulin G (IgG) levels in mice, similar to the effects of intravenous immunoglobulin (IVIg) treatments. This cold-induced rise in circulating IgG was mediated by the renin–angiotensin–aldosterone system and linked to vascular constriction. In our mouse model, the cold-exposed groups (4 °C) showed significantly elevated plasma IgG levels and reduced bacterial clearance compared with the control groups maintained at room temperature (25 °C), both indicative of immunosuppression. Using this model, with 234 mice divided into groups of 6, we investigated the potential of tanshinone IIA, an active compound in Salvia miltiorrhiza ethanolic root extract (SMERE), in alleviating cold-induced immunosuppression. Tanshinone IIA and SMERE treatments effectively normalized elevated plasma IgG levels and significantly improved bacterial clearance impaired by cold exposure compared with control groups injected with a vehicle control, dimethyl sulfoxide. Notably, bacterial clearance, which was impaired by cold exposure, showed an approximately 50% improvement following treatment, restoring immune function to levels comparable to those observed under normal temperature conditions (25 °C, p < 0.05). These findings highlight the therapeutic potential of traditional herbal medicine in counteracting cold-induced immune dysregulation, offering valuable insights for future strategies aimed at modulating immune function in cold environments. Further research could focus on isolating tanshinone IIA and compounds present in SMERE to evaluate their specific roles in mitigating cold-induced immunosuppression.

Machine learning algorithms can enhance the design and experimental processing of solar cells, resulting in increased conversion efficiency. In this study, we introduce a novel machine learning-based methodology for optimizing the Pareto front of four-terminal (4T) perovskite-copper indium selenide (CIS) tandem solar cells (TSCs). By training a neural network using the Bayesian regularization-backpropagation algorithm via Hammersley sampling, we achieve high prediction accuracy when testing with unseen data through random sampling. This surrogate model not only reduces computational costs but also potentially enhances device performance, increasing from 29.4% to 30.4% while simultaneously reducing material costs for fabrication by 50%. Comparing experimentally fabricated cells with the predicted optimal cells, the latter show a thinner front contact electrode, charge-carrier transport layer, and back contact electrode. Highly efficient perovskite cells identified from the Pareto front have a perovskite layer thickness ranging from 420 to 580 nm. Further analysis reveals the front contact electrode needs to be thin, while the back contact electrode can have a thickness ranging from 100 to 145 nm and still achieve high efficiency. The charge-carrier transport layers play a crucial role in minimizing interface recombination and ensuring unidirectional current flow. The optimal design space suggests thinner electron and hole transport layer thicknesses of 7 nm, down from 23 to 10 nm, respectively. It indicates a balanced charge-carrier extraction is crucial for an optimized perovskite cell. Overall, the presented methodology and optimized design parameters have the potential to enhance the performance of 4T perovskite/CIS TSC while reducing material fabrication costs. [ABSTRACT FROM AUTHOR]

Psychological stress increases risk of gastrointestinal tract diseases. However, the mechanism behind stress-induced gastrointestinal injury is not well understood. The objective of our study is to elucidate the putative mechanism of stress-induced gastrointestinal injury and develop an intervention strategy. To achieve this, we employed the restraint stress mouse model, a well-established method to study the pathophysiological changes associated with psychological stress in mice. By orally administering gut-nonabsorbable Evans blue dye and monitoring its plasma levels, we were able to track the progression of gastrointestinal injury in live mice. Additionally, flow cytometry was utilized to assess the viability, death, and inflammatory status of splenic leukocytes, providing insights into the stress-induced impact on the innate immune system associated with stress-induced gastrointestinal injury. Our findings reveal that neutrophils represent the primary innate immune leukocyte lineage responsible for stress-induced inflammation. Splenic neutrophils exhibited elevated expression levels of the pro-inflammatory cytokine IL-1, cellular reactive oxygen species, mitochondrial burden, and cell death following stress challenge compared to other innate immune cells such as macrophages, monocytes, and dendritic cells. Regulated cell death analysis indicated that NETosis is the predominant stress-induced cell death response among other analyzed regulated cell death pathways. NETosis culminates in the formation and release of neutrophil extracellular traps, which play a crucial role in modulating inflammation by binding to pathogens. Treatment with the NETosis inhibitor GSK484 rescued stress-induced neutrophil extracellular trap release and gastrointestinal injury, highlighting the involvement of neutrophil extracellular traps in stress-induced gastrointestinal inflammation. Our results suggest that neutrophil NETosis could serve as a promising drug target for managing psychological stress-induced gastrointestinal injuries.