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IntroductionBurns are a global public health problem. Major burns can stimulate the body to enter a stress state, thereby increasing the risk of infection and adversely affecting the patient’s prognosis. Recently, it has been discovered that cuproptosis, a form of cell death, is associated with various diseases. Our research aims to explore the molecular clusters associated with cuproptosis in major burns and construct predictive models.MethodsWe analyzed the expression and immune infiltration characteristics of cuproptosis-related factors in major burn based on the GSE37069 dataset. Using 553 samples from major burn patients, we explored the molecular clusters based on cuproptosis-related genes and their associated immune cell infiltrates. The WGCNA was utilized to identify cluster-specific genes. Subsequently, the performance of different machine learning models was compared to select the optimal model. The effectiveness of the predictive model was validated using Nomogram, calibration curves, decision curves, and an external dataset. Finally, five core genes related to cuproptosis and major burn have been was validated using RT-qPCR.ResultsIn both major burn and normal samples, we determined the cuproptosis-related genes associated with major burns through WGCNA analysis. Through immune infiltrate profiling analysis, we found significant immune differences between different clusters. When K=2, the clustering number is the most stable. GSVA analysis shows that specific genes in cluster 2 are closely associated with various functions. After identifying the cross-core genes, machine learning models indicate that generalized linear models have better accuracy. Ultimately, a generalized linear model for five highly correlated genes was constructed, and validation with an external dataset showed an AUC of 0.982. The accuracy of the model was further verified through calibration curves, decision curves, and modal graphs. Further analysis of clinical relevance revealed that these correlated genes were closely related to time of injury.ConclusionThis study has revealed the intricate relationship between cuproptosis and major burns. Research has identified 15 cuproptosis-related genes that are associated with major burn. Through a machine learning model, five core genes related to cuproptosis and major burn have been selected and validated.

Mammalian blastocyst hatching is an essential prerequisite for successful embryo implantation. As the rate-limiting step of current assisted reproductive technology, understanding the key factors regulating blastocyst hatching would be significantly helpful to improve the performance of the assisted reproductive practice. In early embryo development, the fine-tuned elimination of maternal materials and the balanced protein turnover are inevitable for the competent to hatch and implant into endometrium. Neddylation, a ubiquitination-like protein modification, has been shown to be involved in oocyte maturation and early embryo development. In this study, aiming to discover an unknown role of neddylation in the blastocyst hatching process, we provided functional evidence of neddylation in mammalian embryo quality and blastocyst hatching. Treatment with MLN4924, a specific neddylation inhibitor, lowered the embryo quality and dramatically reduced the hatching rate in mouse blastocysts. The transcriptional profile showed the upregulation of oxidative stress-related genes and aberrant expression of immune-related genes. The elevated oxidative stress was validated by qPCR and markers of apoptosis, DNA damage, reactive oxygen species, and cytoskeleton. Moreover, we found the secreted IL-1β level was reduced in an NF-κB-independent manner, leading to the final poor embryo quality and blastocyst hatching failure. This is the first report of neddylation being of great importance in the mammalian blastocyst hatching process. Further investigations uncovering more detailed molecular mechanisms of neddylation regulation in blastocyst hatching would greatly promote not only the understanding of this crucial biological process but also the clinical application in reproductive centers.

Genetic screening is an important approach for etiology determination and helps to optimize administration protocols in reproductive centers. After the first pathogenic gene of female infertility was reported in 2016, more and more new pathogenic genes were discovered, and we sought to develop an efficient and cost-effective method for genetic screening in patients. In this study, we designed a target-sequencing panel with 22 female infertility-related genes, namely, TUBB8, PATL2, WEE2, and PANX1 and sequenced 68 primary infertility (PI) and recurrent pregnancy loss (RPL) patients. We sequenced 68 samples reaching an average depth of 1559× and detected 3,134 variants. Among them, 62.2% were synonymous single-nucleotide variants (SNVs) and 36.3% were non-synonymous SNVs. The remaining 1.5% are indels (insertions and deletions) and stop-gains. DNAH11 and TUBB8 are the two genes that mutated most frequently. We also found a novel TUBB8 variant (c.898_900del; p.300_300del), proved its loss-of-function mechanism, and profiled the interactome of the wild-type (WT) and mutant TUBB8 proteins. Overall, this target-sequencing method provides an efficient and cost-effective approach for screening in IVF clinics and will support researchers for the discovery of new pathogenic variants.