Study of the Tail Dependence Structure in Global Financial Markets Using Extreme Value Theory

Abstract: The presence of tail dependencies invalidates the multivariate normality assumptions in portfolio risk management. The identification of tail (in)dependencies has drawn major attention in empirical financial studies. Yet it is still a challenging issue both theoretically and practically. Previous studies based on either a restrictive model or the null hypothesis of tail (perfect) dependence does not well describe or interpret extreme co-movements in financial markets. This paper examines tail dependence structures underlying a broad range of financial asset classes employing the newly developed tail quotient correlation coefficients. In theory, the original tail quotient correlation coefficient proposed in (Zhang 2008) is adapted to incorporate cases with varying data driven random thresholds. Our empirical results demonstrate different tail dependence structures underlying various global financial markets. Either omission or unanimous treatment of the tail dependence structures for different financial markets will lead to erroneous conclusions or suboptimal investment choices. The multivariate extreme value theory framework in this study has the potential to serve as an useful tool in exploiting arbitrage opportunities, optimizing asset allocations, and building robust risk management strategies

Recent Achievement in Gene Cloning and Functional Genomics in Soybean

Soybean is a model plant for photoperiodism as well as for symbiotic nitrogen fixation. However, a rather low efficiency in soybean transformation hampers functional analysis of genes isolated from soybean. In comparison, rapid development and progress in flowering time and photoperiodic response have been achieved in Arabidopsis and rice. As the soybean genomic information has been released since 2008, gene cloning and functional genomic studies have been revived as indicated by successfully characterizing genes involved in maturity and nematode resistance. Here, we review some major achievements in the cloning of some important genes and some specific features at genetic or genomic levels revealed by the analysis of functional genomics of soybean

Pulmonary infection associated with immune dysfunction is associated with poor prognosis in patients with myelodysplastic syndrome accompanied by TP53 abnormalities

The aim of this study was to examine the characteristics and prognosis of patients with myelodysplastic syndrome (MDS) accompanied by TP53 abnormalities and explore potential prognostic factors and treatment responses. This retrospective analysis included 95 patients with MDS and TP53 abnormalities and 173 patients with MDS without TP53 abnormalities at the Fujian Medical University Union Hospital between January 2016 and June 2023. Among patients with TP53 abnormalities, 26 (27.4%) developed AML during the disease course, with a median transformation time of 5.7 months. Complex karyotypes were observed in 73.1% of patients, and the proportions of -5 or del(5q), -7 or del(7q), +8, and -20 or del(20q) were 81.8%, 54.5%, 30.7%, and 25.0%, respectively. These patients exhibited poor survival, with a median overall survival (OS) of 7.3 months, and had 1- and 2-year OS rates of 42.2% and 21.5%, respectively. The complete response rates for azacitidine monotherapy, venetoclax combined with azacitidine, decitabine monotherapy, and decitabine combined with low-dose chemotherapy were 9.1%, 41.7%, 37.5%, and 33.3%, respectively. Long-term survival was similar among the four treatment groups. Patients who underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) had a median OS of 21.3 months, which trended to be longer than that of patients who did not undergo allo-HSCT (5.6 months; P = 0.1449). Patients with pulmonary infection at diagnosis experienced worse OS than those without pulmonary infection (2.3 months vs. 15.4 months; P < 0.0001). Moreover, 61.9% of patients with pulmonary infection had immune dysfunction, with a ratio of CD4+ to CD8+ T lymphocytes below two. Pulmonary infections and complex karyotypes were independent adverse prognostic factors for OS. In conclusion, TP53 abnormalities in patients with MDS were frequently accompanied by complex karyotypes, and treatments based on hypomethylating agents or venetoclax have limited efficacy. Pulmonary infections associated with immune dysfunction is associated with poor prognosis

Identification and validation of novel biomarkers associated with immune infiltration for the diagnosis of osteosarcoma based on machine learning

Objectives: Osteosarcoma is the most common primary malignant tumor in children and adolescents, and the 5-year survival of osteosarcoma patients gained no substantial improvement over the past decades. Effective biomarkers in diagnosing osteosarcoma are warranted to be developed. This study aims to explore novel biomarkers correlated with immune cell infiltration in the development and diagnosis of osteosarcoma.Methods: Three datasets (GSE19276, GSE36001, GSE126209) comprising osteosarcoma samples were extracted from Gene Expression Omnibus (GEO) database and merged to obtain the gene expression. Then, differentially expressed genes (DEGs) were identified by limma and potential biological functions and downstream pathways enrichment analysis of DEGs was performed. The machine learning algorithms LASSO regression model and SVM-RFE (support vector machine-recursive feature elimination) analysis were employed to identify candidate hub genes for diagnosing patients with osteosarcoma. Receiver operating characteristic (ROC) curves were developed to evaluate the discriminatory abilities of these candidates in both training and test sets. Furthermore, the characteristics of immune cell infiltration in osteosarcoma, and the correlations between these potential genes and immune cell abundance were illustrated using CIBERSORT. qRT-PCR and western blots were conducted to validate the expression of diagnostic candidates.Results: GEO datasets were divided into the training (merged GSE19276, GSE36001) and test (GSE126209) groups. A total of 71 DEGs were screened out in the training set, including 10 upregulated genes and 61 downregulated genes. These DEGs were primarily enriched in immune-related biological functions and signaling pathways. After machine learning by SVM-RFE and LASSO regression model, four biomarkers were chosen for the diagnostic nomogram for osteosarcoma, including ASNS, CD70, SRGN, and TRIB3. These diagnostic biomarkers all possessed high diagnostic values (AUC ranging from 0.900 to 0.955). Furthermore, these genes were significantly correlated with the infiltration of several immune cells, such as monocytes, macrophages M0, and neutrophils.Conclusion: Four immune-related candidate hub genes (ASNS, CD70, SRGN, TRIB3) with high diagnostic value were confirmed for osteosarcoma patients. These diagnostic genes were significantly connected with the immune cell abundance, suggesting their critical roles in the osteosarcoma tumor immune microenvironment. Our study provides highlights on novel diagnostic candidate genes with high accuracy for diagnosing osteosarcoma patients

Clinical significance of S100B protein in pregnant woman with early- onset severe preeclampsia

Objectives: Preeclampsia is one of the most feared complications of pregnancy, which can progress rapidly to serious complications such as death of both mother and fetus. To present, the leading cause of preeclampsia is still debated. The purpose of this article was to explore the clinical significance of S100B protein, a kind of Ca2+ -sensor protein, in the early-onset severe preeclampsia. Material and methods: Nine pregnant women with early-onset severe preeclampsia (the study group) and 13 healthy pregnant women (the control group) were included in this study. The level of S100B in the amniotic fluid, maternal blood, and umbilical cord blood were detected by enzyme-linked immunosorbent assay (ELISA) and surface plasmon resonance imaging (SPRi) methods. Diagnostic values of S100B for early-onset severe preeclampsia were assessed by Receiver Operating Characteristic (ROC) curve analysis. Results: The levels of S100B in maternal blood and amniotic fluid in the study group were higher than those in the control group (p < 0.05). ROC curve analysis showed that S100B detected by SPRi method (SPRi-S100B) showed a cut-off level of 181 ng/mL with sensitivity of 100%, a specificity of 84.6%, and a Youden index of 0.846 in the maternal blood, which had better clinical significance and diagnostic value (at than that detected by ELISA (ELISA-S100B).   Conclusions: The levels of S100B detected by SPRi in maternal blood can indicate early-onset severe preeclampsia and perinatal brain injury

Comparative genomics and phylogenomics of the genus Glycyrrhiza (Fabaceae) based on chloroplast genomes

Glycyrrhiza (Fabaceae) species are rich in metabolites and widely used in medicine. Research on the chloroplast genome of Glycyrrhiza is important for understanding its phylogenetics, biogeography, genetic diversity, species identification, and medicinal properties. In this study, comparative genomics and phylogenomics of Glycyrrhiza were analyzed based on the chloroplast genome. The chloroplast genomes of six Glycyrrhiza species were obtained using various assembly and annotation tools. The final assembled chloroplast genome sizes for the six Glycyrrhiza species ranged from 126,380 bp to 129,115 bp, with a total of 109–110 genes annotated. Comparative genomics results showed that the chloroplast genomes of Glycyrrhiza showed typically lacking inverted repeat regions, and the genome length, structure, GC content, codon usage, and gene distribution were highly similar. Bioinformatics analysis revealed the presence of 69–96 simple sequence repeats and 61–138 long repeats in the chloroplast genomes. Combining the results of mVISTA and nucleotide diversity, four highly variable regions were screened for species identification and relationship studies. Selection pressure analysis indicated overall purifying selection in the chloroplast genomes of Glycyrrhiza, with a few positively selected genes potentially linked to environmental adaptation. Phylogenetic analyses involving all tribes of Fabaceae with published chloroplast genomes elucidated the evolutionary relationships, and divergence time estimation estimated the chronological order of species differentiations within the Fabaceae family. The results of phylogenetic analysis indicated that species from the six subfamilies formed distinct clusters, consistent with the classification scheme of the six subfamilies. In addition, the inverted repeat-lacking clade in the subfamily Papilionoideae clustered together, and it was the last to differentiate. Co-linear analysis confirmed the conserved nature of Glycyrrhiza chloroplast genomes, and instances of gene rearrangements and inversions were observed in the subfamily Papilionoideae

Avian Influenza (H5N1) Virus in Waterfowl and Chickens, Central China

In 2004, 3 and 4 strains of avian influenza virus (subtype H5N1) were isolated from waterfowl and chickens, respectively, in central People’s Republic of China. Viral replication and pathogenicity were evaluated in chickens, quails, pigeons, and mice. We analyzed the sequences of the hemagglutinin and neuraminidase genes of the isolates and found broad diversity among them

Ferroptosis-related gene HIC1 in the prediction of the prognosis and immunotherapeutic efficacy with immunological activity

BackgroundHypermethylated in Cancer 1 (HIC1) was originally confirmed as a tumor suppressor and has been found to be hypermethylated in human cancers. Although growing evidence has supported the critical roles of HIC1 in cancer initiation and development, its roles in tumor immune microenvironment and immunotherapy are still unclear, and no comprehensive pan-cancer analysis of HIC1 has been conducted.MethodsHIC1 expression in pan-cancer, and differential HIC1 expression between tumor and normal samples were investigated. Immunohistochemistry (IHC) was employed to validate HIC1 expression in different cancers by our clinical cohorts, including lung cancer, sarcoma (SARC), breast cancer, and kidney renal clear cell carcinoma (KIRC). The prognostic value of HIC1 was illustrated by Kaplan-Meier curves and univariate Cox analysis, followed by the genetic alteration analysis of HIC1 in pan-cancer. Gene Set Enrichment Analysis (GSEA) was conducted to illustrate the signaling pathways and biological functions of HIC1. The correlations between HIC1 and tumor mutation burden (TMB), microsatellite instability (MSI), and the immunotherapy efficacy of PD-1/PD-L1 inhibitors were analyzed by Spearman correlation analysis. Drug sensitivity analysis of HIC1 was performed by extracting data from the CellMiner™ database.ResultsHIC1 expression was abnormally expressed in most cancers, and remarkable associations between HIC1 expression and prognostic outcomes of patients in pan-cancer were detected. HIC1 was significantly correlated with T cells, macrophages, and mast cell infiltration in different cancers. Moreover, GSEA revealed that HIC1 was significantly involved in immune-related biological functions and signaling pathways. There was a close relationship of HIC1 with TMB and MSI in different cancers. Furthermore, the most exciting finding was that HIC1 expression was significantly correlated with the response to PD-1/PD-L1 inhibitors in cancer treatment. We also found that HIC1 was significantly correlated with the sensitivity of several anti-cancer drugs, such as axitinib, batracylin, and nelarabine. Finally, our clinical cohorts further validated the expression pattern of HIC1 in cancers.ConclusionsOur investigation provided an integrative understanding of the clinicopathological significance and functional roles of HIC1 in pan-cancer. Our findings suggested that HIC1 can function as a potential biomarker for predicting the prognosis, immunotherapy efficacy, and drug sensitivity with immunological activity in cancers