Abstract Objective The macrophage activation syndrome (MAS) secondary to systemic lupus erythematosus (SLE) is a severe and life-threatening complication. Early diagnosis of MAS is particularly challenging. In this study, machine learning models and diagnostic scoring card were developed to aid in clinical decision-making using clinical characteristics. Methods We retrospectively collected clinical data from 188 patients with either SLE or the MAS secondary to SLE. 13 significant clinical predictor variables were filtered out using the Least Absolute Shrinkage and Selection Operator (LASSO). These variables were subsequently utilized as inputs in five machine learning models. The performance of the models was evaluated using the area under the receiver operating characteristic curve (ROC-AUC), F1 score, and F2 score. To enhance clinical usability, we developed a diagnostic scoring card based on logistic regression (LR) analysis and Chi-Square binning, establishing probability thresholds and stratification for the card. Additionally, this study collected data from four other domestic hospitals for external validation. Results Among all the machine learning models, the LR model demonstrates the highest level of performance in internal validation, achieving a ROC-AUC of 0.998, an F1 score of 0.96, and an F2 score of 0.952. The score card we constructed identifies the probability threshold at a score of 49, achieving a ROC-AUC of 0.994 and an F2 score of 0.936. The score results were categorized into five groups based on diagnostic probability: extremely low (below 5%), low (5–25%), normal (25–75%), high (75–95%), and extremely high (above 95%). During external validation, the performance evaluation revealed that the Support Vector Machine (SVM) model outperformed other models with an AUC value of 0.947, and the scorecard model has an AUC of 0.915. Additionally, we have established an online assessment system for early identification of MAS secondary to SLE. Conclusion Machine learning models can significantly improve the diagnostic accuracy of MAS secondary to SLE, and the diagnostic scorecard model can facilitate personalized probabilistic predictions of disease occurrence in clinical environments.
Emamectin benzoate (EMB) is an antisea lice chemical widely used in the aquaculture that may also unintentionally affect nontarget crustaceans in the environment. Although the adverse effects of this compound are well documented in various species, the full modes of action (MoAs) are still not well characterized. The current study was therefore conducted to characterize the MoAs of EMB and link perturbations of key toxicological pathways to adverse effects in the model freshwater crustacean Daphnia magna. Effects on molting and survival were determined after 48 h exposure to EMB, whereas global transcriptional changes and the ecdysone receptor (EcR) binding potency was determined to characterize the MoA. The results showed that the molting frequency and survival of D. magna decreased in a concentration-dependent manner, and the observed changes could not be attributed to direct interactions with the EcR. Major MoAs such as activation of glutamate-gated chloride channels and gamma-aminobutyric acid signaling, disruption of neuroendocrine regulation of molting, perturbation of energy homeostasis, suppression of DNA repair and induction of programmed cell death were observed by transcriptional analysis and successfully linked to the adverse effects. This study has demonstrated that acute exposure to intermediate and high pM levels of EMB may pose hazards to nontarget crustaceans in the aquatic environment.
Microplastics as emerging contaminants have been detected from peaks to poles. High concerns on the risks of microplastic pollution to humans and ecosystems have therefore been raised in the past decade. While a large number of studies have been conducted to investigate the environmental levels and toxicity of microplastics, the information generated to support risk assessment is fragmented and the coherence between different types of study is largely lacking. Here we introduced the Aggregate Exposure Pathway (AEP), a conceptual framework originally proposed for chemical exposure assessment, to facilitate organization, visualization and evaluation of existing information generated from microplastic research, and to efficiently identify future knowledge and regulatory needs. A putative microplastic AEP network (mpAEP) was developed to demonstrate the concept and model development strategies. Two mpAEP case studies, with polyethylene (PE) as a prototype, were then presented based on existing environmental exposure data collected from the Changjiang Estuary and the East China Sea (Case I), and the Oslo Fjord (Case II), respectively. Weight of evidence (WoE) assessment of the mpAEPs were performed for evaluating the essentiality, theoretical plausibility, empirical evidence and quantitative understanding of the evidence and relationships in the AEPs. Both cases showed moderate/high WoE to support the strength of the models, whereas also displayed clear knowledge gaps, thus providing guidance for future investigations and regulations. The mpAEP framework introduced herein presents a novel strategy for organizing fragmented information from diverse types of microplastic research, enhancing mechanistic understanding of causal relationships and facilitating the development of quantitative prediction models for research and regulation in the future.
YEATS domain containing 4 (YEATS4) is usually amplified and functions as an oncogene in several malignancies, such as colorectum, ovarian, breast and lung. However, the biological role of YEATS4 in hepatocellular carcinoma (HCC) has not yet been discussed. Herein, we found that YEATS4 was significantly upregulated in HCC compared to para-cancerous tissues, and was associated with poor prognosis, large tumor size, poor differentiation and distant metastasis. In addition, YEATS4 promoted HCC cell proliferation and colony formation by binding to and increasing the transcriptional activity of the TCEA1 promoter. Concurrently, upregulation of TCEA1 increased the stability of the DDX3 protein, a member of the DEAD box RNA helicase family, and augmented the proliferative and colony forming ability of HCC cells. Furthermore, YEATS4 accelerated tumor growth in vivo in a xenograft HCC model. Taken together, our study provides evidence for the first time on the potential role of the YEATS4/TCEA1/DDX3 axis in regulating HCC progression, and presents YEATS4 as a promising therapeutic target and prognosis maker for HCC.
Forest bathing is suggested to have beneficial effects on various aspects of human health. Terpenes, isoprene based-phytochemicals emitted from trees, are largely responsible for these beneficial effects of forest bathing. Although the therapeutic effects of terpenes on various diseases have been revealed, their effects on neuronal health have not yet been studied in detail. Here, we screened 16 terpenes that are the main components of Korean forests using Drosophila Alzheimer's disease (AD) models to identify which terpenes have neuroprotective effects. Six out of the 16 terpenes, ρ-cymene, limonene (+), limonene (−), linalool, α-pinene (+), and β-pinene (−), partially suppressed the beta amyloid 42 (Aβ42)-induced rough eye phenotype when fed to Aβ42-expressing flies. Among them, limonene (+) restored the decreased survival of flies expressing Aβ42 in neurons during development. Limonene (+) treatment did not affect Aβ42 accumulation and aggregation, but did cause to decrease cell death, reactive oxygen species levels, extracellular signal-regulated kinase phosphorylation, and inflammation in the brains or the eye imaginal discs of Aβ42-expressing flies. This neuroprotective effect of limonene (+) was not associated with autophagic activity. Our results suggest that limonene (+) has a neuroprotective function against the neurotoxicity of Aβ42 and, thus, is a possible therapeutic reagent for AD.
Ionizing radiation is known to induce oxidative stress and DNA damage as well as epigenetic effects in aquatic organisms. Epigenetic changes can be part of the adaptive responses to protect organisms from radiation-induced damage, or act as drivers of toxicity pathways leading to adverse effects. To investigate the potential roles of epigenetic mechanisms in low-dose ionizing radiation-induced stress responses, an ecologically relevant crustacean, adult Daphnia magna were chronically exposed to low and medium level external 60Co gamma radiation ranging from 0.4, 1, 4, 10, and 40 mGy/h for seven days. Biological effects at the molecular (global DNA methylation, histone modification, gene expression), cellular (reactive oxygen species formation), tissue/organ (ovary, gut and epidermal histology) and organismal (fecundity) levels were investigated using a suite of effect assessment tools. The results showed an increase in global DNA methylation associated with loci-specific alterations of histone H3K9 methylation and acetylation, and downregulation of genes involved in DNA methylation, one-carbon metabolism, antioxidant defense, DNA repair, apoptosis, calcium signaling and endocrine regulation of development and reproduction. Temporal changes of reactive oxygen species (ROS) formation were also observed with an apparent transition from ROS suppression to induction from 2 to 7 days after gamma exposure. The cumulative fecundity, however, was not significantly changed by the gamma exposure. On the basis of the new experimental evidence and existing knowledge, a hypothetical model was proposed to provide in-depth mechanistic understanding of the roles of epigenetic mechanisms in low dose ionizing radiation induced stress responses in D. magna.
While adverse biological effects of acute high-dose ionizing radiation have been extensively investigated, knowledge on chronic low-dose effects is scarce. The aims of the present study were to identify hazards of low-dose ionizing radiation to Daphnia magna using multiomics dose–response modeling and to demonstrate the use of omics data to support an adverse outcome pathway (AOP) network development for ionizing radiation. Neonatal D. magna were exposed to γ radiation for 8 days. Transcriptomic analysis was performed after 4 and 8 days of exposure, whereas metabolomics and confirmative bioassays to support the omics analyses were conducted after 8 days of exposure. Benchmark doses (BMDs, 10% benchmark response) as points of departure (PODs) were estimated for both dose-responsive genes/metabolites and the enriched KEGG pathways. Relevant pathways derived using the BMD modeling and additional functional end points measured by the bioassays were overlaid with a previously published AOP network. The results showed that several molecular pathways were highly relevant to the known modes of action of γ radiation, including oxidative stress, DNA damage, mitochondrial dysfunction, protein degradation, and apoptosis. The functional assays showed increased oxidative stress and decreased mitochondrial membrane potential and ATP pool. Ranking of PODs at the pathway and functional levels showed that oxidative damage related functions had relatively low PODs, followed by DNA damage, energy metabolism, and apoptosis. These were supportive of causal events in the proposed AOP network. This approach yielded promising results and can potentially provide additional empirical evidence to support further AOP development for ionizing radiation.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)