Non-interest Income and Bank Profitability

In the U.S. commercial banking systems, non-interest income contributes to as much as over 40% of net operating income, compared to only 20% in 1980, which demonstrates non-interest income is playing a very important role. To test how non-interest income affects U.S. commercial banks’ profitability for recent decade, we accepted accounting ratios to measure the links between non-interest income and other factors contributing to the bank profitability from 2000 to 2010. The results show that banks with higher non-interest income normally have stronger power of profitability. It also indicates that the impact of non-interest income on bank performance can be different, depending on how performance is measured. Thus it can be a helpful complimentary for nowadays non-interest income research

A multi-parameter cinematic curvature

We state a multi-parameter cinematic curvature condition, and prove $L^p$ bounds for related maximal operators

OccuQuest: Mitigating Occupational Bias for Inclusive Large Language Models

The emergence of large language models (LLMs) has revolutionized natural language processing tasks. However, existing instruction-tuning datasets suffer from occupational bias: the majority of data relates to only a few occupations, which hampers the instruction-tuned LLMs to generate helpful responses to professional queries from practitioners in specific fields. To mitigate this issue and promote occupation-inclusive LLMs, we create an instruction-tuning dataset named \emph{OccuQuest}, which contains 110,000+ prompt-completion pairs and 30,000+ dialogues covering over 1,000 occupations in 26 occupational categories. We systematically request ChatGPT, organizing queries hierarchically based on Occupation, Responsibility, Topic, and Question, to ensure a comprehensive coverage of occupational specialty inquiries. By comparing with three commonly used datasets (Dolly, ShareGPT, and WizardLM), we observe that OccuQuest exhibits a more balanced distribution across occupations. Furthermore, we assemble three test sets for comprehensive evaluation, an occu-test set covering 25 occupational categories, an estate set focusing on real estate, and an occu-quora set containing real-world questions from Quora. We then fine-tune LLaMA on OccuQuest to obtain OccuLLaMA, which significantly outperforms state-of-the-art LLaMA variants (Vicuna, Tulu, and WizardLM) on professional questions in GPT-4 and human evaluations. Notably, on the occu-quora set, OccuLLaMA reaches a high win rate of 86.4\% against WizardLM

Effect of Berberine on PPAR α

Rhizoma coptidis, the root of Coptis chinensis Franch, has been used in China as a folk medicine in the treatment of diabetes for thousands of years. Berberine, one of the active ingredients of Rhizoma coptidis, has been reported to improve symptoms of diabetes and to treat experimental cardiac hypertrophy, respectively. The objective of this study was to evaluate the potential effect of berberine on cardiomyocyte hypertrophy in diabetes and its possible influence on peroxisome proliferator-activated receptor-α (PPARα)/nitric oxide (NO) signaling pathway. The cardiomyocyte hypertrophy induced by high glucose (25.5 mmol/L) and insulin (0.1 μmol/L) (HGI) was characterized in rat primary cardiomyocyte by measuring the cell surface area, protein content, and atrial natriuretic factor mRNA expression level. Protein and mRNA expression were measured by western blot and real-time RT-PCR, respectively. The enzymatic activity of NO synthase (NOS) was measured using a spectrophotometric assay, and NO concentration was measured using the Griess assay. HGI significantly induced cardiomyocyte hypertrophy and decreased the expression of PPARα and endothelial NOS at the mRNA and protein levels, which occurred in parallel with declining NOS activity and NO concentration. The effect of HGI was inhibited by berberine (0.1 to 100 μmol/L), fenofibrate (0.3 μmol/L), or L-arginine (100 μmol/L). MK886 (0.3 μmol/L), a selective PPARα antagonist, could abolish the effects of berberine and fenofibrate. NG-nitro-L-arginine-methyl ester (100 μmol/L), a NOS inhibitor, could block the effects of L-arginine, but only partially blocked the effects of berberine. These results suggest that berberine can blunt HGI-induced cardiomyocyte hypertrophy in vitro, through the activation of the PPARα/NO signaling pathway

Transcriptome profiling in rumen, reticulum, omasum, and abomasum tissues during the developmental transition of pre-ruminant to the ruminant in yaks

The development of the four stomachs of yak is closely related to its health and performance, however the underlying molecular mechanisms are largely unknown. Here, we systematically analyzed mRNAs of four stomachs in five growth time points [0 day, 20 days, 60 days, 15 months and 3 years (adult)] of yaks. Overall, the expression patterns of DEmRNAs were unique at 0 d, similar at 20 d and 60 d, and similar at 15 m and adult in four stomachs. The expression pattern in abomasum was markedly different from that in rumen, reticulum and omasum. Short Time-series Expression Miner (STEM) analysis demonstrated that multi-model spectra are drastically enriched over time in four stomachs. All the identified mRNAs in rumen, reticulum, omasum and abomasum were classified into 6, 4, 7, and 5 cluster profiles, respectively. Modules 9, 38, and 41 were the most significant three colored modules. By weighted gene co-expression network analysis (WGCNA), a total of 5,486 genes were categorized into 10 modules. CCKBR, KCNQ1, FER1L6, and A4GNT were the hub genes of the turquoise module, and PAK6, TRIM29, ADGRF4, TGM1, and TMEM79 were the hub genes of the blue module. Furthermore, functional KEGG enrichment analysis suggested that the turquoise module was involved in gastric acid secretion, sphingolipid metabolism, ether lipid metabolism, etc., and the blue module was enriched in pancreatic secretion, pantothenate and CoA biosynthesis, and starch and sucrose metabolism, etc. Our study aims to lay a molecular basis for the study of the physiological functions of rumen, reticulum, omasum and abomasum in yaks. It can further elucidate the important roles of these mRNAs in regulation of growth, development and metabolism in yaks, and to provide a theoretical basis for age-appropriate weaning and supplementary feeding in yaks

Differential Reponses of Hematopoietic Stem and Progenitor Cells to mTOR Inhibition

Abnormal activation of the mammalian target of rapamycin (mTOR) signaling pathway has been observed in a variety of human cancers. Therefore, targeting of the mTOR pathway is an attractive strategy for cancer treatment and several mTOR inhibitors, including AZD8055 (AZD), a novel dual mTORC1/2 inhibitor, are currently in clinical trials. Although bone marrow (BM) suppression is one of the primary side effects of anticancer drugs, it is not known if pharmacological inhibition of dual mTORC1/2 affects BM hematopoietic stem and progenitor cells (HSPCs) function and plasticity. Here we report that dual inhibition of mTORC1/2 by AZD or its analogue (KU-63794) depletes mouse BM Lin − Sca-1 + c-Kit + cells in cultures via the induction of apoptotic cell death. Subsequent colony-forming unit (CFU) assays revealed that inhibition of mTORC1/2 suppresses the clonogenic function of hematopoietic progenitor cells (HPCs) in a dose-dependent manner. Surprisingly, we found that dual inhibition of mTORC1/2 markedly inhibits the growth of day-14 cobblestone area-forming cells (CAFCs) but enhances the generation of day-35 CAFCs. Given the fact that day-14 and day-35 CAFCs are functional surrogates of HPCs and hematopoietic stem cells (HSCs), respectively, these results suggest that dual inhibition of mTORC1/2 may have distinct effects on HPCs versus HSCs

Nomenclatural and taxonomic notes on Rubus davidianus Kuntze and R. viburnifolius Franch

Critical examinations of specimens, with literature reviews, have shown that Rubus davidianus is conspecific with R. lambertianus. Therefore, we treat R. davidianus as a new synonym within Rubus. We propose a new name, Rubus loirensis Ti R. Huang nom. nov. to replace the later homonym of R. pycnanthus Genev. Additionally, lectotypification of three names, R. davidianus Kuntze, R. malifolius Focke and R. viburnifolius Franch., are designated here after examination of previous works

Allele-specific induction of IL-1beta expression by C/EBPbeta and PU.1 contributes to increased tuberculosis susceptibility

Mycobacterium tuberculosis infection is associated with a spectrum of clinical outcomes, from long-term latent infection to different manifestations of progressive disease. Pro-inflammatory pathways, such as those controlled by IL-1beta, have the contrasting potential both to prevent disease by restricting bacterial replication, and to promote disease by inflicting tissue damage. Thus, the ultimate contribution of individual inflammatory pathways to the outcome of M. tuberculosis infection remains ambiguous. In this study, we identified a naturally-occurring polymorphism in the human IL1B promoter region, which alters the association of the C/EBPbeta and PU.1 transcription factors and controls Mtb-induced IL-1beta production. The high-IL-1beta expressing genotype was associated with the development of active tuberculosis, the severity of pulmonary disease and poor treatment outcome in TB patients. Higher IL-1beta expression did not suppress the activity of IFN-gamma-producing T cells, but instead correlated with neutrophil accumulation in the lung. These observations support a specific role for IL-1beta and granulocytic inflammation as a driver of TB disease progression in humans, and suggest novel strategies for the prevention and treatment of tuberculosis

An efficient ECG denoising method by fusing ECA-Net and CycleGAN

For wearable electrocardiogram (ECG) acquisition, it was easy to infer motion artifices and other noises. In this paper, a novel end-to-end ECG denoising method was proposed, which was implemented by fusing the Efficient Channel Attention (ECA-Net) and the cycle consistent generative adversarial network (CycleGAN) method. The proposed denoising model was optimized by using the ECA-Net method to highlight the key features and introducing a new loss function to further extract the global and local ECG features. The original ECG signal came from the MIT-BIH Arrhythmia Database. Additionally, the noise signals used in this method consist of a combination of Gaussian white noise and noises sourced from the MIT-BIH Noise Stress Test Database, including EM (Electrode Motion Artifact), BW (Baseline Wander) and MA (Muscle Artifact), as well as mixed noises composed of EM+BW, EM+MA, BW+MA and EM+BW+MA. Moreover, corrupted ECG signals were generated by adding different levels of single and mixed noises to clean ECG signals. The experimental results show that the proposed method has better denoising performance and generalization ability with higher signal-to-noise ratio improvement (SNRimp), as well as lower root-mean-square error (RMSE) and percentage-root-mean-square difference (PRD)