The impact of cross border M&As on company performance from emerging market: empirical evidence from China

This study is arranged according to three main research tasks: (i) To test short-run announcement wealth effects of Chinese OMAs in stock markets by event study. (ii) To investigate the determinants of OMA announcement effects by cross-sectional regression. (iii) To evaluate the three years company performance after OMA by financial ratio analysis. Findings report highly significant negative abnormal returns around six selected event windows around announcement date in terms of shareholder value and declining trend in financial ratios in three years after OMA activity. No significant result is discovered from hypothesis testing for determinants of negative abnormal returns

Molecular analysis of phosphomannomutase (PMM) genes reveals a unique PMM duplication event in diverse Triticeae species and the main PMM isozymes in bread wheat tissues

BACKGROUND: Phosphomannomutase (PMM) is an essential enzyme in eukaryotes. However, little is known about PMM gene and function in crop plants. Here, we report molecular evolutionary and biochemical analysis of PMM genes in bread wheat and related Triticeae species. RESULTS: Two sets of homoeologous PMM genes (TaPMM-1 and 2) were found in bread wheat, and two corresponding PMM genes were identified in the diploid progenitors of bread wheat and many other diploid Triticeae species. The duplication event yielding PMM-1 and 2 occurred before the radiation of diploid Triticeae genomes. The PMM gene family in wheat and relatives may evolve largely under purifying selection. Among the six TaPMM genes, the transcript levels of PMM-1 members were comparatively high and their recombinant proteins were all enzymatically active. However, PMM-2 homoeologs exhibited lower transcript levels, two of which were also inactive. TaPMM-A1, B1 and D1 were probably the main active isozymes in bread wheat tissues. The three isozymes differed from their counterparts in barley and Brachypodium distachyon in being more tolerant to elevated test temperatures. CONCLUSION: Our work identified the genes encoding PMM isozymes in bread wheat and relatives, uncovered a unique PMM duplication event in diverse Triticeae species, and revealed the main active PMM isozymes in bread wheat tissues. The knowledge obtained here improves the understanding of PMM evolution in eukaryotic organisms, and may facilitate further investigations of PMM function in the temperature adaptability of bread wheat

Prognostic value of fatty acid metabolism-related genes in colorectal cancer and their potential implications for immunotherapy

IntroductionColorectal cancer is one of the most common gastrointestinal cancers and the second leading cause of cancer-related death. Although colonoscopy screening has greatly improved the early diagnosis of colorectal cancer, its recurrence and metastasis are still significant problems. Tumour cells usually have the hallmark of metabolic reprogramming, while fatty acids play important roles in energy storage, cell membrane synthesis, and signal transduction. Many pathways of fatty acid metabolism (FAM) are involved in the occurrence and development of colon cancer, and the complex molecular interaction network contains a variety of genes encoding key enzymes and related products.MethodsClinical information and RNA sequencing data were collected from TCGA and GEO databases. The prognosis model of colon cancer was constructed by LASSO-Cox regression analysis among the selected fatty acid metabolism genes with differential expression. Nomogram for the prognosis model was also constructed in order to analyze its value in evaluating the survival and clinical stage of the colon cancer patients. The differential expression of the selected genes was verified by qPCR and immunohistochemistry. GSEA and GSVA were used to analyze the enrichment pathways for high- and low-risk groups. CIBERSORT was used to analyze the immune microenvironment of colon cancer and to compare the infiltration of immune cells in the high- and low-risk groups. The “circlize” package was used to explore the correlation between the risk score signature and immunotherapy for colon cancer.ResultsWe analysed the differential expression of 704 FAM-related genes between colon tumour and normal tissue and screened 10 genes with prognostic value. Subsequently, we constructed a prognostic model for colon cancer based on eight optimal FAM genes through LASSO Cox regression analysis in the TCGA-COAD dataset, and its practicality was validated in the GSE39582 dataset. Moreover, the risk score calculated based on the prognostic model was validated as an independent prognostic factor for colon cancer patients. We further constructed a nomogram composed of the risk score signature, age and American Joint Committee on Cancer (AJCC) stage for clinical application. The colon cancer cohort was divided into high- and low-risk groups according to the optimal cut-off value, and different enrichment pathways and immune microenvironments were depicted in the groups.DiscussionSince the risk score signature was significantly correlated with the expression of immune checkpoint molecules, the prognostic model might be able to predict the immunotherapy response of colon cancer patients. In summary, our findings expand the prognostic value of FAM-related genes in colon cancer and provide evidence for their application in guiding immunotherapy

Imaging 3D Chemistry at 1 nm Resolution with Fused Multi-Modal Electron Tomography

Measuring the three-dimensional (3D) distribution of chemistry in nanoscale matter is a longstanding challenge for metrological science. The inelastic scattering events required for 3D chemical imaging are too rare, requiring high beam exposure that destroys the specimen before an experiment completes. Even larger doses are required to achieve high resolution. Thus, chemical mapping in 3D has been unachievable except at lower resolution with the most radiation-hard materials. Here, high-resolution 3D chemical imaging is achieved near or below one nanometer resolution in a Au-Fe$_3$O$_4$ metamaterial, Co$_3$O$_4$ - Mn$_3$O$_4$ core-shell nanocrystals, and ZnS-Cu$_{0.64}$S$_{0.36}$ nanomaterial using fused multi-modal electron tomography. Multi-modal data fusion enables high-resolution chemical tomography often with 99\% less dose by linking information encoded within both elastic (HAADF) and inelastic (EDX / EELS) signals. Now sub-nanometer 3D resolution of chemistry is measurable for a broad class of geometrically and compositionally complex materials

CD44s-activated tPA/LRP1-NFκB pathway drives lamellipodia outgrowth in luminal-type breast cancer cells

Some cancer cells migration and metastasis are characterized by the outgrowth of lamellipodia protrusions in which the underlying mechanism remains unclear. Evidence has confirmed that lamellipodia formation could be regulated by various adhesion molecules, such as CD44, and we previously reported that lamellipodia at the leading edge of luminal type breast cancer (BrCa) were enriched with high expression of CD44. In this study, we found that the overexpression of CD44s could promote lamellipodia formation in BrCa cells through inducing tissue type plasminogen activator (tPA) upregulation, which was achieved by PI3K/Akt signaling pathway activation. Moreover, we revealed that tPA could interact with LDL receptor related protein 1 (LRP1) to activate the downstream NFκB signaling pathway, which in turn facilitate lamellipodia formation. Notably, inhibition of the tPA/LRP1-NFkB signaling cascade could attenuate the CD44s-induced lamellipodia formation. Thus, our findings uncover a novel role of CD44s in driving lamellipodia outgrowth through tPA/LRP1-NFkB axis in luminal BrCa cells that may be helpful for seeking potential therapeutic targets

Exploring genetic associations with ceRNA regulation in the human genome

Abstract Competing endogenous RNAs (ceRNAs) are RNA molecules that sequester shared microRNAs (miRNAs) thereby affecting the expression of other targets of the miRNAs. Whether genetic variants in ceRNA can affect its biological function and disease development is still an open question. Here we identified a large number of genetic variants that are associated with ceRNA's function using Geuvaids RNA-seq data for 462 individuals from the 1000 Genomes Project. We call these loci competing endogenous RNA expression quantitative trait loci or ‘cerQTL’, and found that a large number of them were unexplored in conventional eQTL mapping. We identified many cerQTLs that have undergone recent positive selection in different human populations, and showed that single nucleotide polymorphisms in gene 3΄UTRs at the miRNA seed binding regions can simultaneously regulate gene expression changes in both cis and trans by the ceRNA mechanism. We also discovered that cerQTLs are significantly enriched in traits/diseases associated variants reported from genome-wide association studies in the miRNA binding sites, suggesting that disease susceptibilities could be attributed to ceRNA regulation. Further in vitro functional experiments demonstrated that a cerQTL rs11540855 can regulate ceRNA function. These results provide a comprehensive catalog of functional non-coding regulatory variants that may be responsible for ceRNA crosstalk at the post-transcriptional level

Evaluation of a computer-aided diagnostic model for corneal diseases by analyzing in vivo confocal microscopy images

ObjectiveIn order to automatically and rapidly recognize the layers of corneal images using in vivo confocal microscopy (IVCM) and classify them into normal and abnormal images, a computer-aided diagnostic model was developed and tested based on deep learning to reduce physicians’ workload.MethodsA total of 19,612 corneal images were retrospectively collected from 423 patients who underwent IVCM between January 2021 and August 2022 from Renmin Hospital of Wuhan University (Wuhan, China) and Zhongnan Hospital of Wuhan University (Wuhan, China). Images were then reviewed and categorized by three corneal specialists before training and testing the models, including the layer recognition model (epithelium, bowman’s membrane, stroma, and endothelium) and diagnostic model, to identify the layers of corneal images and distinguish normal images from abnormal images. Totally, 580 database-independent IVCM images were used in a human-machine competition to assess the speed and accuracy of image recognition by 4 ophthalmologists and artificial intelligence (AI). To evaluate the efficacy of the model, 8 trainees were employed to recognize these 580 images both with and without model assistance, and the results of the two evaluations were analyzed to explore the effects of model assistance.ResultsThe accuracy of the model reached 0.914, 0.957, 0.967, and 0.950 for the recognition of 4 layers of epithelium, bowman’s membrane, stroma, and endothelium in the internal test dataset, respectively, and it was 0.961, 0.932, 0.945, and 0.959 for the recognition of normal/abnormal images at each layer, respectively. In the external test dataset, the accuracy of the recognition of corneal layers was 0.960, 0.965, 0.966, and 0.964, respectively, and the accuracy of normal/abnormal image recognition was 0.983, 0.972, 0.940, and 0.982, respectively. In the human-machine competition, the model achieved an accuracy of 0.929, which was similar to that of specialists and higher than that of senior physicians, and the recognition speed was 237 times faster than that of specialists. With model assistance, the accuracy of trainees increased from 0.712 to 0.886.ConclusionA computer-aided diagnostic model was developed for IVCM images based on deep learning, which rapidly recognized the layers of corneal images and classified them as normal and abnormal. This model can increase the efficacy of clinical diagnosis and assist physicians in training and learning for clinical purposes

Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions

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