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Feima Wu, Guangchao Li, Huijuan Shen, Jing Huang, Zhi Liu, Yangmin Zhu, Qi Zhong, Ruiming Ou, Qing Zhang, Shuang Liu Department of Hematology, Guangdong Second Provincial General Hospital, Guangzhou, Guangdong, People’s Republic of ChinaCorrespondence: Shuang Liu, Department of Hematology, Guangdong Second Provincial General Hospital, XinGangZhong Road 466#, Haizhu Distict, Guangzhou, Guangdong Province, 510317, People’s Republic of China, Tel +86-20-89169214, Email liush@gd2h.org.cnBackground: Centromere protein I (CENPI) has been shown to affect the tumorigenesis of breast and colorectal cancers. However, its biological role and prognostic value in other kinds of cancer, especially adrenocortical carcinoma (ACC), remained to be further investigated.Methods: Various bioinformatics tools were adopted for exploring the significance of differential expression of CENPI in several malignant tumors from databases such as Depmap portal, GTEx, and TCGA. ACC was selected for further analyzed, and information such as clinicopathological features, the prognostic outcome of diverse subgroups, differentially expressed genes (DEGs), co-expression genes, as well as levels of tumor-infiltrating immune cells (TIIC), was extracted from multiple databases. To verify the possibility of CENPI as a therapeutic target in ACC, drug sensitivity assay and si-RNA mediate knockdown of CENPI were carried out.Results: The pan-cancer analyses showed that the CENPI mRNA expression levels differed significantly among most cancer types. Additionally, a high precision in cancer prediction and close relation with cancer survival indicated that CENPI could be a potential candidate biomarker to diagnose and predict cancer prognosis. In ACC, CENPI was closely related to multiple clinical characteristics, such as pathological stage and primary therapy outcome. High CENPI levels predicted poor overall survival (OS), progression-free interval (PFI), and disease-specific survival (DSS) of ACC patients, particularly for different clinical subgroups. Moreover, the expression of CENPI showed positive relationship to Th2 cells but negatively related to most of the TIICs. Furthermore, drug sensitivity assay showed that vorinostat inhibit CENPI expression and ACC cell growth. Additionally, si-RNA mediated knockdown of CENPI inhibited ACC cell growth and invasion and showed synergistic anti-proliferation effect with AURKB inhibitor barasertib.Conclusion: Pan-cancer analysis demonstrated that CENPI is a potential diagnostic and prognostic biomarker in various cancers as well as an anti-ACC therapeutic target.Keywords: CENPI, pan-cancer analysis, diagnosis, prognostic biomarker, adrenocortical carcinoma

Targeted therapy for acute myeloid leukemia (AML) is an effective strategy, but currently, there are very limited therapeutic targets for AML treatment. Ferroptosis is strongly related to drug resistance and carcinogenesis. However, there are few reports about ferroptosis in AML. This article explores the relationship between ferroptosis-related gene (FRG) expression and prognosis in AML patients from the FerrDb and the Cancer Genome Atlas (TCGA) databases. The ferroptosis-related gene ARNTL was observed to have high expression and poor prognosis in AML. Receiver operating characteristic curve (ROC) analysis revealed the predictive accuracy of the signature. The area under the time-dependent ROC curve (AUC) was 0.533 at one year, 0.619 at two years, and 0.622 at three years within the training cohort. Moreover, we found that the ARNTL expression is closely associated with tumor-infiltrating immune cells like the macrophages and NK cells. Inhibiting the ARNTL expression suppressed colony formation and induced ferroptosis in AML cells. Overall, the survival prediction model constructed based on ARNTL accurately predicted the survival in AML patients, which could be a potential candidate for diagnosing and treating AML.

To explore impaired cognition characteristics and abnormal behavior in children with Sleep-Disordered Breathing (SDB) via Event-Related Potentials (ERPs), continuous performance testing (CPT), and the Child Behavior Checklist (CBCL).A total of 108 children aged 6-8 years old were recruited, including fifty-four children (28 boys) with SDB and fifty-four normal children (28 boys). CBCL and Chinese version of the OSA-18 questionnaire were administered. Nineteen children with SDB (OSA-18 questionnaire value60) and Nineteen normal children completed a CPT task. ERP was extracted using the BESA software.No significant differences in the correct number, reaction time, or the number of commission error were noted between the CPT of the two groups (P 0.05). The ERP Go-P3 amplitudes at F3, Fz and F4 of the SDB group were significantly higher than those of the control group (P 0.05). The NoGo-N2 amplitudes at F3 and Fz of the SDB group were significantly lower than those of the control group (P 0.05). The Fz and F4 Go-P3 and FZ NoGo-P3 latency of the SDB group were significantly longer than those of the control group (P 0.05). However, among boys, the CBCL scores of the SDB group including the subscores, schizo, somatic complaints, compulsion, aggression, and hyperactivity, as well as the total score, were significantly higher than the control group (all P 0.05).Children with SDB demonstrate significant functional deficits in regard to conflict monitoring, attention, and inhibition. The frontal region is the primary area of dysfunction, especially in the left brain region, and inhibition function dysfunction may be a common pathogenesis of SDB and ADHD. Moreover, boys with SDB may exhibit more behavior problems when compared to girls.

In order to solve the storage difficulty of power failure signals under big data fusion, which leads to the waste of hardware resources, this paper proposed a Dice-gradient projection for sparse recovery (Dice-GPSR) algorithm based on the compressed sensing theory to reconstruct the fusion signals. Firstly, the algorithm optimizes the support set based on the Dice coefficient measure matching criterion, changes the search direction and iterative search path of the gradient projection sparse reconstruction algorithm, and improves the convergence speed. Secondly, the sparsity of the signal is estimated and the flow of Dice-GPSR algorithm is given. Finally, Dice-GPSR algorithm is used to reconstruct the original signal and compare the reconstruction performance with other reconstruction algorithms. The simulation results show that Dice-GPSR algorithm has higher reconstruction accuracy and reconstruction signal to noise ratio than other reconstruction algorithms.