Effects of Chronic Restraint Stress on Apoptosis of Amygdala Cells in Rats / 法医学杂志

OBJECTIVES@#To explore the damage effects of chronic restraint stress (CRS) on amygdala cells through the rat CRS model.@*METHODS@#The rat CRS model was established, and the changes in body weight and adrenal mass in control group and CRS group were monitored at 1 d, 7 d, 14 d and 21 d. The behavior changes were evaluated by the percentage of retention time of open arms and open arm entries using the elevated plus maze (EPM). ELISA was used to detect the concentrations of rat's corticotropin releasing hormone (CRH), adrenocorticotropic hormone (ACTH) and cortisol. The changes of expression of glucocorticoid receptor (GR) and glial fibrillary acidic protein (GFAP) in amygdala were determined by immunohistochemistry and Western blotting. Ultrastructure changes of glial cell were observed by transmission electron microscopy. The apoptosis rate of amygdala was measured by flow cytometry.@*RESULTS@#Compared with the control group at the same time points, body weight of CRS 1 d, 7 d, 14 d and 21 d groups increased slowly, but adrenal mass increased significantly; the serum level of CRH, cortisol and ACTH increased significantly at 7 d, 14 d and 21 d respectively; the expression of GR in amygdala was increased while that of GFAP was decreased; EPM test suggested that the percentage of retention time of open arms and open arm entries decreased significantly after 14 d. The CRS group showed different degrees of glial cell damage in amygdala, and the apoptosis rate of glial cell was significantly increased in 21 d group.@*CONCLUSIONS@#This study successfully established a CRS model in rats, and anxiety-like behavioral changes in model rats may be caused by apoptosis of amygdala astrocytes.

The Role of circRNAs in the Diagnosis of Colorectal Cancer: A Meta-Analysis.

Background: A novel category of non-coding circular RNAs (circRNAs) has been found to be dysregulated in colorectal cancer (CRC) and significantly contribute to its progression. However, the feasibility of using circRNA as a diagnostic biomarker for CRC remains to be elucidated. Herein, we aimed to comprehensively collect and analyze evidence regarding the potential application of circRNAs as diagnostic indicators for CRC. Methods: A comprehensive retrieval of relevant studies dating from January, 2015 to December 2020, was carried out in PubMed, Cochrane Library, and Web of Science. Data regarding the diagnostic accuracy of circRNA for CRC, including sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC), were obtained from the included studies. Quality assessment of diagnostic accuracy studies (QUADAS-2) was used to assess the methodological quality of each study. Statistical analysis was performed using STAT and RevMan software. Results: Eighteen studies, involving a total of 2021 individuals, were included in the present meta-analysis. The specimens examined included tissue, serum, and plasma. The pooled sensitivity, specificity, DOR, PLR, NLR, and AUC, with a 95% confidence interval (CI), of circRNAs in the diagnosis of CRC were 0.78 (0.71-0.83), 0.73 (0.68-0.78), 9.68 (6.76-13.85), 2.92 (2.45-3.50), 0.30 (0.23-0.39), and 0.81 (0.78-0.85), respectively. Subgroup analysis showed that the upregulated circRNAs in the tissue or plasma possessed relatively higher diagnostic values for CRC than the downregulated circRNAs. There was no significant difference between the tissue-derived and non-tissue-derived circRNA subgroups. Conclusion: circRNA may be used as a diagnostic biomarker for CRC because of its relatively high diagnostic accuracy in distinguishing CRC patients from normal controls. Further prospective studies are needed to identify more representative circRNAs as diagnostic markers for CRC.

Ultrasensitive, colorimetric detection of microRNAs based on isothermal exponential amplification reaction-assisted gold nanoparticle amplification.

MicroRNAs (miRNAs) play important roles in a wide range of biological processes, and their aberrant expressions are linked to a large number of human diseases and disorders. In this work, we developed a colorimetric method for rapid, ultrasensitive miRNA detection via isothermal exponential amplification reaction (EXPAR)-assisted gold nanoparticle (AuNP) amplification. The sensing probe designed with a tandem phosphorothioate modification in the backbone of the polyadenines at the 5' terminus was employed to directly assemble onto the surface of AuNP with high adsorption affinity. The recognition domain at the 3' terminus of the sensing probe hybridizes with target miRNAs to trigger EXPAR with exponential signal amplification. With the amplification reaction with the action of DNA polymerase, the sensing probe gradually detaches from the AuNP, resulting in the aggregation of bare AuNPs in the high-salt reaction environment due to lack of DNA protection. The presence of AuNP aggregation is conveniently measured by UV-vis spectroscopy. Our proposed method could provide a linear detection range from 50fM to 10nM with a detection limit of ∼46fM within 60min, and also discriminate a single-nucleotide difference between homologous miRNAs.

Enzyme-free detection of sequence-specific microRNAs based on nanoparticle-assisted signal amplification strategy.

Developing direct and convenient methods for microRNAs (miRNAs) analysis is of great significance in understanding biological functions of miRNAs, and early diagnosis of cancers. We have developed a rapid, enzyme-free method for miRNA detection based on nanoparticle-assisted signal amplification coupling fluorescent metal nanoclusters as signal output. The proposed method involves two processes: target miRNA-mediated nanoparticle capture, which consists of magnetic microparticle (MMP) probe and CuO nanoparticle (NP) probe, and nanoparticle-mediated amplification for signal generation, which consists of fluorescent DNA-Cu/Ag nanocluster (NC) and 3-mercaptopropionic acid (MPA). In the presence of target miRNA, MMP probe and NP probe sandwich-capture the target miRNA via their respective complementary sequence. The resultant sandwich complex (MMP probe-miRNA-CuO NP probe) is separated using a magnetic field and further dissolved by acidolysis to turn CuO NP into a great amount of copper (II) ions (Cu(2+)). Cu(2+) could disrupt the interactions between thiol moiety of MPA and the fluorescent Cu/Ag NCs by preferentially reacting with MPA to form a disulfide compound as intermediate. By this way, the fluorescence emission of the DNA-Cu/Ag NCs in the presence of MPA increases upon the increasing concentration of Cu(2+), which is directly proportional to the amount of target miRNA. The proposed method allows quantitative detection of a liver-specific miR-221-5p in the range of 5 pM to 1000 pM with a detection limit of ~0.73 pM, and shows a good ability to discriminate single-base difference. Moreover, the detection assay can be applied to detect miRNA in cancerous cell lysates in excellent agreement with that from a commercial miRNA detection kit.

Colorimetric detection of sequence-specific microRNA based on duplex-specific nuclease-assisted nanoparticle amplification.

Developing simple and rapid methods for sequence-specific microRNA (miRNA) analysis is imperative to the miRNA study and use in clinical diagnosis. We have developed a colorimetric method for miRNA detection based on duplex-specific nuclease (DSN)-assisted signal amplification coupled to the aggregation of gold nanoparticles (AuNPs). The proposed method involves two processes: target-mediated probe digestion by a DSN enzyme and probe-triggered AuNP aggregation as a switch for signal output. The reaction system consists of a rationally designed probe complex formed by two partly complementary DNA probes, and two sets of different oligonucleotide-modified AuNPs with sequences complementary to a DNA probe in the probe complex. In the presence of target miRNA, the probe complex is invaded, resulting in the formation of a miRNA-probe heteroduplex as the substrate of the DSN enzyme, and releasing the other probe to link to the AuNPs. The proposed method allows quantitative detection of miR-122 in the range of 20 pM to 1 nM with a detection limit of ∼16 pM, and shows an excellent ability to discriminate single-base differences. Moreover, the detection assay can be applied to accurately quantify miR-122 in cancerous cell lysates which is in excellent agreement with the results from a commercial miRNA detection kit. This method is simple, cost-effective, highly selective, and free of dye label and separation procedures.

Characterizing criticality of proteins by systems dynamics: Escherichia coli central carbon metabolism as a working example.

BACKGROUND: Systems biology calls for studying system-level properties of genes and proteins rather than their individual chemical/biological properties, regarding the bio-molecules as system components. By characterizing how critical the components are to the system and classifying them accordingly, we can study the underlying complex mechanisms, facilitating researches in drug target selection, metabolic engineering, complex disease, etc. Up to date, most studies aiming at this goal are confined to the topology-based or flux-analysis approaches. However, proteins have tertiary structures and specific functions, especially in metabolic systems. Thus topological properties such as connectivity, path length, etc., are not good surrogates for protein properties. Also, the manner of individual sensitivity analysis in most flux-analysis approaches cannot reveal the simultaneous impacts on collateral components as well as the overall impact on the system, thus lacking in system-level perspective. RESULTS: In the present work, we developed a method to directly assess protein system-level properties based on system dynamics and in silico knockouts, regarding to the conceptual term "criticality". Applying the method to E. coli central carbon metabolic system, we found that multiple enzymes including phosphoglycerate kinase, enolase, transketolase-b, etc., had critical roles in the system in terms of both system states and dynamical stability. In contrast, another set of enzymes including glucose-6-phosphate isomerise, pyruvate kinase, phosphoglucomutase, etc., exerted very little influences when deleted. The finding is consistent with experimental characterization of metabolic essentiality and other studies on E. coli gene essentiality and functions. We also found that enzymes could affect distant metabolites or enzymes even greater than a close neighbour and asymmetry in system-level properties of enzymes catalyzing alternative pathways could give rise to local flux compensation. CONCLUSIONS: Our method creates a different angle for evaluating protein criticality to a biological system from the conventional methodologies. Moreover, the method leads to consistent results with experimental references, showing its efficiency in studying protein system-level properties. Besides working on metabolic systems, the application of the method can be extended to other kinds of bio-systems to reveal the constitutive/functional properties of system building blocks.

An improved kinetic model for the acetone-butanol-ethanol pathway of Clostridium acetobutylicum and model-based perturbation analysis.

BACKGROUND: Comprehensive kinetic models of microbial metabolism can enhance the understanding of system dynamics and regulatory mechanisms, which is helpful in optimizing microbial production of industrial chemicals. Clostridium acetobutylicum produces solvents (acetone-butanol-ethanol, ABE) through the ABE pathway. To systematically assess the potential of increased production of solvents, kinetic modeling has been applied to analyze the dynamics of this pathway and make predictive simulations. Up to date, only one kinetic model for C. acetobutylicum supported by experiment has been reported as far as we know. But this model did not integrate the metabolic regulatory effects of transcriptional control and other complex factors. It also left out the information of some key intermediates (e.g. butyryl-phosphate). RESULTS: We have developed an improved kinetic model featured with the incorporation of butyryl-phosphate, inclusion of net effects of complex metabolic regulations, and quantification of endogenous enzyme activity variations caused by these regulations. The simulation results of our model are more consistent with published experimental data than the previous model, especially in terms of reflecting the kinetics of butyryl-phosphate and butyrate. Through parameter perturbation analysis, it was found that butyrate kinase has large and positive influence on butanol production while CoA transferase has negative effect on butanol production, suggesting that butyrate kinase has more efficiency in converting butyrate to butanol than CoA transferase. CONCLUSIONS: Our improved kinetic model of the ABE process has more capacity in approaching real circumstances, providing much more insight in the regulatory mechanisms and potential key points for optimization of solvent productions. Moreover, the modeling strategy can be extended to other biological processes.