Early-life exposure to fine particulate matter (PM₂.₅) is increasingly implicated in the developmental origins of chronic respiratory diseases; however, the underlying molecular mechanisms remain poorly defined. This study employed Weighted Gene Co-expression Network Analysis (WGCNA) to investigate transcriptomic alterations associated with intrauterine and early neonatal PM₂.₅ exposure in the developing murine lung. Microarray data (GSE104656) spanning embryonic (E14.5, E18.5) and postnatal (P40) stages were processed using robust normalization and variance filtering to construct a scale-free co-expression network. Principal component analysis revealed that developmental maturation was the primary driver of global transcriptional variation, with no distinct separation attributable to PM₂.₅ exposure. WGCNA identified biologically relevant gene modules involved in immune and metabolic processes as well as cell cycle regulation, that exhibited strong correlations with developmental progression. Functional enrichment analysis confirmed significant involvement in immune activation, leukocyte adhesion, DNA replication, and chromosomal organisation. Although differential expression analysis under stringent thresholds did not detect significant PM₂.₅-responsive genes, integrative network analysis identified eleven exposure-associated genes embedded within key modules. These genes, including Vnn1, Gprc6a, Mfap1a, Rgs16, and Fpr1, represent highly connected hub nodes implicated in oxidative stress regulation, extracellular matrix remodelling, metabolic signalling, and immune modulation. It was concluded that early-life PM₂.₅ exposure did not globally disrupt lung transcriptomic architecture but selectively perturbs critical hub genes within developmental networks. This targeted sub-network vulnerability provided a mechanistic basis for the developmental programming of COPD susceptibility, linking early environmental insults to long-term respiratory dysfunction.
Highly pathogenic avian influenza viruses (HPAIVs) have become widespread among wildlife including within the Arctic. We summarize histopathological findings for three cases of HPAIV infection among polar bears (Ursus maritimus) inhabiting Alaska, genomically characterize viruses causing disease, and assess probable non-lethal exposures. Polar bears found dead and infected with HPAIVs exhibited meningoencephalomyelitis and neuronal necrosis, consistent with neurologic disease. Genomic sequence information obtained for H5N1 and H5N5 subtype HPAIVs associated with two cases supported epidemiologically independent spillovers. Serologic testing provided evidence for antibodies reactive to H5 and N1 antigens among most polar bears inhabiting Alaska during 2023–2024, consistent with contemporary non-lethal exposures, whereas antibodies were not found among bears sampled during 2013. These data indicate that HPAIV infection may represent an emerging threat to polar bear health within the Alaska Arctic; though, population immunity seems to be building and may protect this species from widespread demographic impacts of disease
Individuals, families, and trusts own a plurality of forest land in the United States, and the decisions made by these landowners have substantial impacts on the ecological, economic, and social benefits their lands provide. Some of the most impactful decisions include when and to whom to sell or leave their forested land, and whether or not to actively manage. Family forest landowners constitute an older population relative to the general population, and, the life expectancy of these landowners is a critical factor determining future land transitions, as well as patterns of management and land use. In this paper, we conduct a survival analysis using life tables and estimate that the average family forest landowner in the USA has a life expectancy of 21.0 additional years and an 89.3% chance of surviving the next five years. Five-year survivorship is a significant predictor of future plans to transfer land, as well as future intentions to actively manage. Additionally, at least in the Northeastern USA, survivorship significantly predicts filing wills and establishing trusts. These results suggest that landowners may be consciously or subconsciously aware of their declining life expectancy and may be taking it into account when making decisions regarding estate planning and land management.
In this work, a hierarchical-linked batch-to-batch optimization based on transfer learning is proposed to realize the effective optimization of a new synthesis process. Optimization efficiency is especially crucial for batch processes to improve the product quality and maximize the economic benefits. The traditional hierarchical optimization method can achieve a better effect, but it may lead to low efficiency since it requires more iterations. To further improve the optimization efficiency of a new batch process with high operational cost, a hierarchical-linked batch-to-batch optimization based on transfer learning is proposed in this work. By introducing the linkage between hierarchies, the available information transmitting between hierarchies is addressed to assist and accelerate the modelling and optimization process. A performance assessment criterion based on the prior knowledge of similar processes is also proposed to further improve the optimization effect. Finally, the performance of the proposed method is verified through a simulation study of the cobalt oxalate synthesis process.
