Prognostic value of elevated lipoprotein (a) in patients with acute coronary syndromes: a systematic review and meta-analysis

Background

Elevated lipoprotein (a) level was recognized as an independent risk factor for significant adverse cardiovascular events in acute coronary syndrome (ACS) patients. Despite this recognition, the consensus in the literature regarding the prognostic significance of elevated lipoprotein (a) in ACS was also limited. Consequently, we conducted a thorough systematic review and meta-analysis to evaluate the prognostic relevance of elevated lipoprotein (a) level in individuals diagnosed with ACS.

Methods and results

A thorough literature review was conducted by systematically searching PubMed, Embase, and Cochrane databases until September 2023. This review specifically examined cohort studies exploring the prognostic implications of elevated lipoprotein (a) level in relation to major adverse cardiovascular events (MACE), including death, stroke, non-fatal myocardial infarction (MI), and coronary revascularization, in patients with ACS. The meta-analysis utilized aggregated multivariable hazard ratios (HR) and their respective 95% confidence intervals (CI) to evaluate prognostic implications between high and low lipoprotein (a) levels [the cut-off of high lipoprotein (a) level varies from 12.5 to 60 mg/dl]. Among 18,168 patients in the identified studies, elevated lipoprotein (a) was independently associated with increased MACE risk (HR 1.26; 95% CI: 1.17-1.35, P < 0.00001) and all-cause mortality (HR 1.36; 95% CI: 1.05-1.76, P = 0.02) in ACS patients. In summary, elevated lipoprotein (a) levels independently forecast MACE and all-cause mortality in ACS patients. Assessing lipoprotein (a) levels appears promising for risk stratification in ACS, offering valuable insights for tailoring secondary prevention strategies.

Systematic Review Registration

PROSPERO (CRD42023476543).

Pseudogene AK4P1 promotes pancreatic ductal adenocarcinoma progression through relieving miR-375-mediated YAP1 degradation

Pseudogenes have been reported to play oncogenic or tumor-suppressive roles in cancer progression. However, the molecular mechanism of most pseudogenes in pancreatic ductal adenocarcinoma (PDAC) remains unknown. Herein, we characterized a novel pseudogene-miRNA-mRNA network associated with PDAC progression using bioinformatics analysis. After screening by dreamBase and GEPIA, 12 up-regulated and 7 down-regulated differentially expressed pseudogenes (DEPs) were identified. According to survival analysis, only elevated AK4P1 indicated a poor prognosis for PDAC patients. Moreover, we found that AK4 acts as a cognate gene of AK4P1 and also predicts worse survival for PDAC patients. Furthermore, 32 miRNAs were predicted to bind to AK4P1 by starBase, among which miR-375 was identified as the most potential binding miRNA of AK4P1. A total of 477 potential target genes of miR-375 were obtained by miRNet, in which 49 hub genes with node degree ≥ 20 were identified by STRING. Subsequent analysis for hub genes demonstrated that YAP1 may be a functional downstream target of AK4P1. To confirmed the above findings, microarray, and qRT-PCR assay revealed that YAP1 was dramatically upregulated in both PDAC cells and tissues. Functional experiments showed that knockdown of YAP1 significantly suppressed PDAC cells growth, increased apoptosis, and decreased the ability of invasion. In conclusion, amplification of AK4P1 may fuel the onset and development of PDAC by targeting YAP1 through competitively binding to miR-375, and serve as a promising biomarker and therapeutic target for PDAC.

Transcriptome analysis of oviduct in laying ducks under different stocking densities

1. High stocking densities can lead to animal stress responses and lead to changes in bird behaviour, egg production and the fertility of laying birds. The oviduct plays a crucial role during the process of laying eggs. Therefore, it is essential to know how high stocking density affects oviduct function.2. In this study, a total of 2,115 differentially expressed genes (DEGs) were identified in duck oviduct tissues between different stocking density groups. These genes are mainly enriched in membrane components, calcium ion binding, cytokine-cytokine receptor interaction and focal adhesion. These pathways were closely related to the formation of eggs. This indicated that secretion and material transport functions of the oviduct are affected under high-density stocking. Further analysis showed that a total of 408 genes related to the transportation process were expressed in the oviduct, of which 96 genes were differentially expressed (LogFC≥1, P < 0.05). Forty-two of these DEGs belonged to the solute carrier family. The data showed that the expression of 31 transcripts was different between the two density groups. Expression of KCNJ15, SLC26A8, and TRPM5 was only seen in the high-density group (8/m²), while ATP13A3 and KCNIP2 were only expressed in the low-density group (4/m²).3. Consequently, high stocking density may affect the expression and splicing of genes related to molecular transport in the oviduct.

Machine Learning Methods in Prediction of Protein Palmitoylation Sites: A Brief Review

Protein palmitoylation is a fundamental and reversible post-translational lipid modification that involves a series of biological processes. Although a large number of experimental studies have explored the molecular mechanism behind the palmitoylation process, the computational methods has attracted much attention for its good performance in predicting palmitoylation sites compared with expensive and time-consuming biochemical experiments. The prediction of protein palmitoylation sites is helpful to reveal its biological mechanism. Therefore, the research on the application of machine learning methods to predict palmitoylation sites has become a hot topic in bioinformatics and promoted the development in the related fields. In this review, we briefly introduced the recent development in predicting protein palmitoylation sites by using machine learningbased methods and discussed their benefits and drawbacks. The perspective of machine learning-based methods in predicting palmitoylation sites was also provided. We hope the review could provide a guide in related fields.

Understanding Membrane Protein Drug Targets in Computational Perspective

Membrane proteins play crucial physiological roles in vivo and are the major category of drug targets for pharmaceuticals. The research on membrane protein is a significant part in the drug discovery. The biological process is a cycled network, and the membrane protein is a vital hub in the network since most drugs achieve the therapeutic effect via interacting with the membrane protein. In this review, typical membrane protein targets are described, including GPCRs, transporters and ion channels. Also, we conclude network servers and databases that are referring to the drug, drug-target information and their relevant data. Furthermore, we chiefly introduce the development and practice of modern medicines, particularly demonstrating a series of state-of-the-art computational models for the prediction of drug-target interaction containing network-based approach and machine-learningbased approach as well as showing current achievements. Finally, we discuss the prospective orientation of drug repurposing and drug discovery as well as propose some improved framework in bioactivity data, created or improved predicted approaches, alternative understanding approaches of drugs bioactivity and their biological processes.

Hippocampal shape analysis of Alzheimer disease based on machine learning methods

BACKGROUND AND PURPOSE

Alzheimer disease (AD) is a neurodegenerative disease characterized by progressive dementia. The hippocampus is particularly vulnerable to damage at the very earliest stages of AD. This article seeks to evaluate critical AD-associated regional changes in the hippocampus using machine learning methods.

MATERIALS AND METHODS

High-resolution MR images were acquired from 19 patients with AD and 20 age- and sex-matched healthy control subjects. Regional changes of bilateral hippocampi were characterized using computational anatomic mapping methods. A feature selection method for support vector machine and leave-1-out cross-validation was introduced to determine regional shape differences that minimized the error rate in the datasets.

RESULTS

Patients with AD showed significant deformations in the CA1 region of bilateral hippocampi, as well as the subiculum of the left hippocampus. There were also some changes in the CA2-4 subregions of the left hippocampus among patients with AD. Moreover, the left hippocampal surface showed greater variations than the right compared with those in healthy control subjects. The accuracies of leave-1-out cross-validation and 3-fold cross-validation experiments for assessing the reliability of these subregions were more than 80% in bilateral hippocampi.

CONCLUSION

Subtle and spatially complex deformation patterns of hippocampus between patients with AD and healthy control subjects can be detected by machine learning methods.

Post-ischemic administration [correction of administeration] but not pre-ischemic administration [correction of administeration] of NG-nitro-L-arginine prevents spatial memory impairments and apoptosis by an inhibition of a delayed increase in NOx- in the hippocampus following repeated cerebral ischemia

In the present study, we investigated the effects of N(G)-nitro-L-arginine (L-NAME), an inhibitor of nitric oxide synthase, on repeated cerebral ischemia-induced impairment of spatial memory of the 8-arm radial maze in rats. Repeated ischemia (10 min ischemia x 2 times with 1 h interval) impaired the spatial memory in the 8-arm radial maze test and produced apoptosis in the hippocampus 7 days after final occlusion, and gradually increased the NO(x)(-) levels approximately 30-180 min after the second reperfusion. Post-ischemic administration of L-NAME at a dose of 50 mg/kg, i.p. 30 min following the second occlusion, significantly attenuated the repeated ischemia-induced impairment of spatial memory in the 8-arm radial maze test and suppressed apoptosis in the hippocampus, and also significantly suppressed a delayed increase in the NO(x)(-) levels induced by repeated ischemia. However, pre-ischemic administration of L-NAME at a dose of 50 mg/kg, i.p. 30 min before the first occlusion, caused about 90% mortality (the mortality rate of vehicle-treated group was 10%). These results suggest that the delayed generation of NO(x)(-) may cause spatial memory impairment and induction of apoptosis in the hippocampus in rats subjected to repeated ischemia.

[3D visualization and information interaction in biomedical applications]

3D visualization and virtual reality are important trend in the development of modern science and technology, and as well in the studies on biomedical engineering. This paper presents a computer procedure developed for 3D visualization in biomedical applications. The biomedical models are constructed in slice sequences based on polygon cells and information interaction is realized on the basis of OpenGL selection mode in particular consideration of the specialties in this field such as irregularity in geometry and complexity in material etc. The software developed has functions of 3D model construction and visualization, real-time modeling transformation, information interaction and so on. It could serve as useful platform for 3D visualization in biomedical engineering research.

[Computer-aided legal medical examination of body surface]

This paper provides a package of automatic and semi-automatic methods for computing the area of different kinds of body surface injuries. Compared with traditional methods, these processes of examination are faster and the conclusions are more precise and objective. Also presented are the authors classify the items into many types by standards which are necessary to let computer draw conclusions automatically. This software is conducive to improvement in work efficiency and convenience for judicial supervision.

Effect of berbamine on T-cell mediated immunity and the prevention of rejection on skin transplants in mice

Berbamine, an ingredient of Berberis, which itself is widely utilized in Chinese folk-medicine has been used as a source of leukogenics, anti-arrhythmics and anti-hypertensives. In recent years, the immunosuppressive effects of berbamine has been demonstrated. In order to further investigate the value of berbamine as an immunosuppressive agent, the delayed type hypersensitivity reaction (DTH) response with sheep red blood cells (SRBC), the mixed lymphocyte reaction (MLR) and a skin model of allograft rejection on mice were studied. Berbamine showed suppressive effects on DTH and MLR and significantly prolonged allograft survival compared with untreated transplanted mice. The results indicate that berbamine may be a potential agent in clinical transplantation.

Isolation of the Anabaena sp. strain PCC 7120 sigA gene in a transcriptional-interference selection

A transcriptional-interference selection was performed to identify genes of Anabaena sp. strain PCC 7120 that encode DNA-binding proteins able to bind to the rbcL promoter. Unexpectedly, the selection yielded the previously identified sigA gene, which encodes the principal sigma factor. Protein extracts from Escherichia coli containing the sigA gene bound the rbcL promoter fragment in mobility shift assays, and competition experiments indicated binding to rbcL and glnA but not xisA or nifH upstream regions.

Anabaena sp. strain PCC 7120 bifA gene encoding a sequence-specific DNA-binding protein cloned by in vivo transcriptional interference selection

VF1 is a DNA-binding protein from the cyanobacterium Anabaena sp. strain PCC 7120. VF1 was originally identified on the basis of its binding affinity to the upstream region of xisA, which encodes a heterocyst-specific site-specific recombinase. VF1 also binds to the glnA, rbcL, and nifH promoters in vitro, suggesting that VF1 interacts with genes expressed in both vegetative cells and heterocysts. The role of VF1 in regulating gene expression in PCC 7120 is unknown. As a step towards the goal of understanding the role of VF1 in regulating gene expression, we have cloned the bifA gene by using a genetic selection strategy. bifA encodes a protein, BifA, that has chromatographic and DNA-binding properties indistinguishable from those of VF1. The cloning strategy was based on a transcriptional interference assay in which a strong synthetic promoter, conII, interferes with the expression of an aadA gene, which provides resistance to spectinomycin and streptomycin (S. J. Elledge, P. Sugiono, L. Guarente, and R. W. Davis, Proc. Natl. Acad. Sci. USA 86:3689-3693, 1989). A selection plasmid, pAM994, which has the conII promoter negatively regulated by a VF1-binding site, was used to enrich for VF1-producing clones from an expression library containing PCC 7120 DNA fragments. Mobility shift assays were used to identify a 672-bp open reading frame that encoded VF1-like binding activity. The deduced BifA amino acid sequence shows 77% identity to NtcA, which is a global regulator involved in nitrogen control in Synechococcus sp. strain PCC 7942. Both BifA and NtcA belong to the cyclic AMP receptor protein (CRP) family of prokaryotic regulatory proteins. Genes similar to envM, hisB, and ORF60-5 were found near the bifA gene.

[Chemical components of the essential oil from Ligusticum brachylobum Franch]

45 chemical components of the essential oil from Ligusticum brachylobum were identified, the main ones being alpha-pinene (45.46%), beta-pinene (18.01%) and limonene (8.19%), etc. In the essential oil, however, no ligustilide was found that makes an effective component of the essential oils from L. sinense cv. chuanxiong and from L. sinense. This result provides a basis for the quality evaluation of the drug.