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Abstract Purpose Colorectal cancer (CRC) is a highly heterogeneous malignancy with an unfavorable prognosis. The purpose of this study was to address the heterogeneity of CRC by categorizing it into ion channel subtypes, and to develop a predictive modeling based on ion channel genes to predict the survival and immunological states of patients with CRC. The model will provide guidance for personalized immunotherapy and drug treatment. Methods A consistent clustering method was used to classify 619 CRC samples based on the expression of 279 ion channel genes. Such a method was allowed to investigate the relationship between molecular subtypes, prognosis, and immune infiltration. Furthermore, a predictive modeling was constructed for ion channels to evaluate the ion channel properties of individual tumors using the least absolute shrinkage and selection operator. The expression patterns of the characteristic genes were validated through molecular biology experiments. The effect of potassium channel tetramerization domain containing 9 (KCTD9) on CRC was verified by cellular functional experiments. Results Four distinct ion channel subtypes were identified in CRC, each characterized by unique prognosis and immune infiltration patterns. Notably, Ion Cluster3 exhibited high levels of immune infiltration and a favorable prognosis, while Ion Cluster4 showed relatively lower levels of immune infiltration and a poorer prognosis. The ion channel score could predict overall survival, with lower scores correlated with longer survival. This score served as an independent prognostic factor and presented an excellent predictive efficacy in the nomogram. In addition, the score was closely related to immune infiltration, immunotherapy response, and chemotherapy sensitivity. Experimental evidence further confirmed that low expression of KCTD9 in tumor tissues was associated with an unfavorable prognosis in patients with CRC. The cellular functional experiments demonstrated that KCTD9 inhibited the proliferation, migration and invasion capabilities of LOVO cells. Conclusions Ion channel subtyping and scoring can effectively predict the prognosis and evaluate the immune microenvironment, immunotherapy response, and drug sensitivity in patients with CRC.

Purpose: Recurrent implantation failure (RIF) is an enormous challenge for in vitro fertilization (IVF) clinicians. An understanding of the molecular mechanisms of RIF helps to predict prognosis and develop new therapeutic strategies. The study is designed to identify diagnostic biomarkers for RIF as well as the potential mechanisms underlying RIF by utilizing public databases together with experimental validation.Methods: Two microarray datasets of RIF patients and the healthy control endometrium were downloaded from the Gene Expression Omnibus (GEO) database. First, differentially expressed microRNAs (miRNAs) (DEMs) were identified and their target genes were predicted. Then, we identified differentially expressed genes (DEGs) and selected hub genes through protein-protein interaction (PPI) analyses. Functional enrichment analyses of DEGs and DEMs were conducted. Furthermore, the key DEMs which targeted these hub genes were selected to obtain the key miRNA–target gene network. The key genes in the miRNA-target gene network were validated by a single-cell RNA-sequencing dataset of endometrium from GEO. Finally, we selected two miRNA–target gene pairs for further experimental validation using dual-luciferase assay and quantitative polymerase chain reaction (qPCR).Results: We identified 49 DEMs between RIF patients and the fertile group and found 136,678 target genes. Then, 325 DEGs were totally used to construct the PPI network, and 33 hub genes were selected. Also, 25 DEMs targeted 16 key DEGs were obtained to establish a key miRNA–target gene network, and 16 key DEGs were validated by a single-cell RNA-sequencing dataset. Finally, the target relationship of hsa-miR-199a-5p-PDPN and hsa-miR-4306-PAX2 was verified by dual-luciferase assay, and there were significant differences in the expression of those genes between the RIF and fertile group by PCR (p < 0.05).Conclusion: We constructed miRNA–target gene regulatory networks associated with RIF which provide new insights regarding the underlying pathogenesis of RIF; hsa-miR-199a-5p-PDPN and hsa-miR-4306-PAX2 could be further explored as potential biomarkers for RIF, and their detection in the endometrium could be applied in clinics to estimate the probability of successful embryo transfer.

The irradiance of powered polymerisation activators for chairside use affects composite resin adhesive curing during the restorative process, whereas radiant accumulated temperature rise relates to clinical safety. Irradiance reduction and high radiant accumulated temperature will compromise the treatment results as there is a lack of curing output efficacy and safety awareness for powered polymerisation activators. Insufficient attention has been paid to the activator's quality control, irradiance attenuation and radiant accumulated temperature excessive temperature rise during its lifetime. The present manuscript has been drafted by the Society of Dental Equipment, Chinese Stomatological Association to fill the quality control gap and guide the quality control process, following tested steps, using a metered radiometer and a thermometer to record the irradiance and radiant accumulated temperature separately. The testing result may indicate the equipment's situation in service and provide information about the irradiance values and performance of the powered polymerisation activator for its usage and maintenance. [ABSTRACT FROM AUTHOR]