The impact of bank merger growth on CEO compensation

We examine the impact of bank mergers on chief executive officer (CEO) compensation during the period 1992–2014, a period characterised by significant banking consolidation. We show that CEO compensation is positively related to both merger growth and non-merger internal growth, with the former relationship being higher in magnitude. While CEO pay–risk sensitivity is not significantly related to merger growth, CEO pay–performance sensitivity is negatively and significantly related to merger growth. Collectively, our results suggest that, through bank mergers, CEOs can earn higher compensation and decouple personal wealth from bank performance. Furthermore, we document a more severe agency problem in CEO compensation as a consequence of bank mergers relative to mergers in industrial firms. Finally, we find that the post-financial crisis regulatory reform of executive compensation in banks has limited effectiveness in curbing the merger–pay links

A combined method for gas-bearing layer identification in a complex sandstone reservoir

Langgu Depression is a mature oil and gas exploration area with complicated lithological and physical properties. The varying formation fluid, low-resistivity hydrocarbon-bearing reservoirs, and non-uniform logging series greatly increase the difficulty of gas reservoir identification. The Monte Carlo method is employed to simulate the neutron–gamma logging responses to gas saturation and the influential factors. According to the result, a new gas identification chart eliminating the influence of porosity and formation water salinity is proposed to identify gas reservoirs in the old wells. At the same time, a fluid factor extracted from array acoustic logging and core measurement data is sensitive to the development of gas-bearing layers and useful for the identification of gas reservoirs in the new wells with array acoustic logging. The field examples show that the new combined method greatly improves the ability to identify gas-bearing layers and works well in old well reexamination and new well interpretation

miR-27b Suppresses Endothelial Cell Proliferation and Migration by Targeting Smad7 in Kawasaki Disease

Background/Aims: Increasing evidence indicates that microRNAs (miRNAs) play important roles in Kawasaki disease (KD). Our previous study demonstrated that hsa-miR-27b-3p (miR-27b) was up-regulated in KD serum. However, the specific role of miR-27b in KD remains unclear. We aimed to investigate that miR-27b could be a biomarker and therapeutic target for KD treatment. As well, the specific mechanism of miR-27b effecting endothelial cell functions was studied. Methods: The expression of miR-27b and Smad7 was measured by qRT-PCR. Gain-of-function strategy was used to observe the effect of miR-27b on human umbilical vein endothelial cells (HUVECs) proliferation and migration. Bioinformatics analyses were applied to predict miR-27b targets and then we verified Smad7 by a luciferase reporter assay. Western blot was performed to detect the protein expression of Smad7, PCNA, MMP9, MMP12 and TGF-β-related genes. Results: We confirmed that miR-27b was shown to be dramatically up-regulated in KD serum and KD serum-treated HUVECs and that elevated expression of miR-27b suppressed the proliferation and migration of HUVECs. Furthermore, our results verified that miR-27b mediated cell functions by affecting the TGF-β via targeting Smad7 in HUVECs. Conclusion: These results suggested that up-regulated miR-27b had a protective role in HUVECs proliferation and migration via targeting Smad7 and affecting TGF-β pathway. Therefore, miR-27b represented a potential biomarker for KD and may serve as a promising therapeutic target for KD treatment

Efficacy of chimeric antigen receptor T cell therapy and autologous stem cell transplant in relapsed or refractory diffuse large B-cell lymphoma: A systematic review

BackgroundWe aimed to compare the efficacy of chimeric antigen receptor T (CAR-T) cell therapy with that of autologous stem cell transplantation (auto-HSCT) in relapsed/refractory diffuse large B cell lymphoma (R/R DLBCL).Research design and methodsWe searched eligible publications up to January 31st, 2022, in PubMed, Cochrane Library, Springer, and Scopus. A total of 16 publications with 3484 patients were independently evaluated and analyzed using STATA SE software.ResultsPatients who underwent CAR-T cell therapy showed a better overall response rate (ORR) and partial response (PR) than those treated with auto-HSCT (CAR-T vs. auto-HSCT, ORR: 80% vs. 73%, HR:0.90,95%CI:0.76-1.07,P = 0.001; PR: 20% vs. 14%, HR:0.65,95%CI:0.62-0.68,P = 0.034). No significant difference was observed in 6-month overall survival (OS) (CAR-T vs. auto-HSCT, six-month OS: 81% vs. 84%, HR:1.23,95%CI:0.63-2.38, P = 0.299), while auto-HSCT showed a favorable 1 and 2-year OS (CAR-T vs. auto-HSCT, one-year OS: 64% vs. 73%, HR:2.42,95%CI:2.27-2.79, P < 0.001; two-year OS: 54% vs. 68%, HR:1.81,95%CI:1.78-1.97, P < 0.001). Auto-HSCT also had advantages in progression-free survival (PFS) (CAR-T vs. auto-HSCT, six-month PFS: 53% vs. 76%, HR:2.81,95%CI:2.53-3.11,P < 0.001; one-year PFS: 46% vs. 61%, HR:1.84,95%CI:1.72-1.97,P < 0.001; two-year PFS: 42% vs. 54%, HR:1.62,95%CI:1.53-1.71, P < 0.001). Subgroup analysis by age, prior lines of therapy, and ECOG scores was performed to compare the efficacy of both treatment modalities.ConclusionAlthough CAR-T cell therapy showed a beneficial ORR, auto-HSCT exhibited a better long-term treatment superiority in R/R DLBCL patients. Survival outcomes were consistent across different subgroups

Identification of microtubule-associated biomarkers in diffuse large B-cell lymphoma and prognosis prediction

Background: Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous disease with a complicated prognosis. Even though various prognostic evaluations have been applied currently, they usually only use the clinical factors that overlook the molecular underlying DLBCL progression. Therefore, more accurate prognostic assessment needs further exploration. In the present study, we constructed a novel prognostic model based on microtubule associated genes (MAGs).Methods: A total of 33 normal controls and 1360 DLBCL samples containing gene-expression from the Gene Expression Omnibus (GEO) database were included. Subsequently, the univariate Cox, the least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were used to select the best prognosis related genes into the MAGs model. To validate the model, Kaplan-Meier curve, and nomogram were analyzed.Results: A risk score model based on fourteen candidate MAGs (CCDC78, CD300LG, CTAG2, DYNLL2, MAPKAPK2, MREG, NME8, PGK2, RALBP1, SIGLEC1, SLC1A1, SLC39A12, TMEM63A, and WRAP73) was established. The K-M curve presented that the high-risk patients had a significantly inferior overall survival (OS) time compared to low-risk patients in training and validation datasets. Furthermore, knocking-out TMEM63A, a key gene belonging to the MAGs model, inhibited cell proliferation noticeably.Conclusion: The novel MAGs prognostic model has a well predictive capability, which may as a supplement for the current assessments. Furthermore, candidate TMEM63A gene has therapeutic target potentially in DLBCL

Individualism and stock price crash risk

Employing a sample of 26,473 firms across 42 countries from 1990 to 2013, we find that firms located in countries with higher individualism have higher stock price crash risk. Furthermore, individualism can be transmitted by foreign investors from overseas markets to influence local firms’ crash risk, and can exacerbate the impact of firm risk taking and earnings management on crash risk. Moreover, the positive relation between individualism and crash risk is amplified during the global financial crisis and attenuated by enhanced country-level financial information transparency and the adoption of International Financial Reporting Standards

Winner's Curse Correction and Variable Thresholding Improve Performance of Polygenic Risk Modeling Based on Genome-Wide Association Study Summary-Level Data

Recent heritability analyses have indicated that genome-wide association studies (GWAS) have the potential to improve genetic risk prediction for complex diseases based on polygenic risk score (PRS), a simple modelling technique that can be implemented using summary-level data from the discovery samples. We herein propose modifications to improve the performance of PRS. We introduce threshold-dependent winner's-curse adjustments for marginal association coefficients that are used to weight the single-nucleotide polymorphisms (SNPs) in PRS. Further, as a way to incorporate external functional/annotation knowledge that could identify subsets of SNPs highly enriched for associations, we propose variable thresholds for SNPs selection. We applied our methods to GWAS summary-level data of 14 complex diseases. Across all diseases, a simple winner's curse correction uniformly led to enhancement of performance of the models, whereas incorporation of functional SNPs was beneficial only for selected diseases. Compared to the standard PRS algorithm, the proposed methods in combination led to notable gain in efficiency (25-50% increase in the prediction R2) for 5 of 14 diseases. As an example, for GWAS of type 2 diabetes, winner's curse correction improved prediction R2 from 2.29% based on the standard PRS to 3.10% (P = 0.0017) and incorporating functional annotation data further improved R2 to 3.53% (P = 2×10-5). Our simulation studies illustrate why differential treatment of certain categories of functional SNPs, even when shown to be highly enriched for GWAS-heritability, does not lead to proportionate improvement in genetic risk-prediction because of non-uniform linkage disequilibrium structure