Epileptic Seizure Detection Based on Path Signature and Bi-LSTM Network With Attention Mechanism.

Automatic seizure detection using electroen-cephalogram (EEG) can significantly expedite the diagnosis of epilepsy, thereby facilitating prompt treatment and reducing the risk of future seizures and associated complications. While most existing EEG-based epilepsy detection studies employ deep learning models, they often ignore the chronological relationships between different EEG channels. To tackle this limitation, a novel automatic epilepsy detection method is proposed, which leverages path signature and Bidirectional Long Short-Term Memory (Bi-LSTM) neural network with an attention mechanism. The path signature algorithm is used to extract discriminative features for capturing the dynamic dependencies between different channels of EEG, while Bi-LSTM with attention further analyzes the inherent temporal dependencies hidden in EEG signal features. Our method is evaluated on two public EEG databases with different sizes (CHB-MIT and TUEP) and a private database from a local hospital. Two experimental settings are used, i.e., five-fold cross-validation and leave-one-out cross-validation. Experimental results show that our method achieves 99.09%, 95.60%, and 99.87% average accuracies on CHB-MIT, TUEP with 250Hz, and TUEP with 256Hz, respectively. On the private dataset, our method also achieves 99.40% average accuracy, which outperforms other methods. Furthermore, our method exhibits robustness in patients, as demonstrated by the evaluation results of cross-patient experiments.

[Construction of integrated platform for emergency clinical scientific research based on big data].

OBJECTIVE: To explore clinical rules based on the big data of the emergency department of the Second Affiliated Hospital of Guangzhou Medical University, and to establish an integrated platform for clinical research in emergency, which was finally applied to clinical practice. METHODS: Based on the hospital information system (HIS), laboratory information system (LIS), emergency specialty system, picture archiving and communication systems (PACS) and electronic medical record system of the Second Affiliated Hospital of Guangzhou Medical University, the structural and unstructured information of patients in the emergency department from March 2019 to April 2022 was extracted. By means of extraction and fusion, normalization and desensitization quality control, the database was established. In addition, data were extracted from the database for adult patients with pre screening triage level III and below who underwent emergency visits from March 2019 to April 2022, such as demographic characteristics, vital signs during pre screening triage, diagnosis and treatment characteristics, diagnosis and grading, time indicators, and outcome indicators, independent risk factors for poor prognosis in patients were analyzed. RESULTS: (1) The data of 338 681 patients in the emergency department of the Second Affiliated Hospital of Guangzhou Medical University from March 2019 to April 2022 were extracted, including 15 modules, such as demographic information, triage information, visit information, green pass and rescue information, diagnosis information, medical record information, laboratory examination overview, laboratory information, examination information, microbiological information, medication information, treatment information, hospitalization information, chest pain management and stroke management. The database ensured data visualization and operability. (2) Total 140 868 patients with pre-examination and triage level III and below were recruited from the emergency department database. The gender, age, type of admission to the hospital, pulse, blood pressure, Glasgow coma scale (GCS) and other indicators of the patients were included. Taking emergency admission to operating room, emergency admission to intervention room, emergency admission to intensive care unit (ICU) or emergency death as poor prognosis, the poor prognosis prediction model for patients with pre-examination and triage level III and below was constructed. The receiver operator characteristic curve and forest map results showed that the model had good predictive efficiency and could be used in clinical practice to reduce the risk of insufficient emergency pre-examination and triage. CONCLUSIONS: The establishment of high-quality clinical database based on big data in emergency department is conducive to mining the clinical value of big data, assisting clinical decision-making, and improving the quality of clinical diagnosis and treatment.

Effects of aerobic exercise on depression-like behavior and TLR4/NLRP3 pathway in hippocampus CA1 region of CUMS-depressed mice.

BACKGROUND AND PURPOSE: The paper observes regulation of the expression levels of NLRP3 and TLR4 in hippocampal CA1 neurons in CUMS mice by aerobic exercise with constructing CUMS depression mouse model, in order to explore the neuroprotective mechanism of aerobic exercise on the hippocampus of depressed mice. STUDY DESIGN AND METHOD: 24 healthy male 8-week-old C57BL/6 mice were randomly divided into CG, MG and ME. Thirteen stress-stimulating factors were randomly formulated into a CUMS stress-stimulating program. The mice were underwent 28 days of CUMS depression model, referenced clinical means for experimental research. The study was approved by the Ethics Committee of Yichun University (YCUEC IRB number LSK NO.2022.18). After model preparation, ME mice were subjected to moderate-intensity treadmill exercise training for 8 weeks. TST, FST and SPT were used to detect the depression-like behaviors of the mice in each group. Nissl staining was used to compare the cell morphology in the CA1 region of the mouse hippocampus. Immunohistochemical staining and western blot were used to detect the changes in the expression levels of NLRP3, TLR4 and other proteins in the CA1 region of the mouse hippocampus. RESULTS: The results of neurobehavioral assessment showed that, the immobility time of TST and FST were significantly increased, and SPT index was significantly decreased of MG mice. Compared with MG, ME mice significantly improved depression-like behaviors such as TST, FST and SPT index. Nissl staining showed that the morphology of neurons in CA1 region of hippocampus of MG mice were mostly vacuolar-like, with severe nuclear pyknosis. Abnormal morphological changes such as vacuolar-like and pyknotic pyknosis of neurons in the hippocampal CA1 region of ME mice were significantly reduced. Protein expression test showed that the number of NLRP3, TLR4, IL-1ß and IL-10 positive neurons in hippocampal CA1 region of MG mice increased significantly compared with CG, and the proportion of positive cells increased significantly, while NLRP3 and TLR4 positive neurons in the hippocampal CA1 region of ME mice were significantly reduced, the proportion of TLR4 positive cells was significantly reduced. CONCLUSION: Systematic moderate-intensity exercise can effectively improve the depression-like behavior of CUMS depressed mice through the expression of TLR4/NLRP3 inflammatory signaling pathway, and provide an effective experimental basis for the clinical rehabilitation treatment of depression.

Cryogenic mid-wave infrared hyperspectral Fabry-Perot filter based on a tensile-strained single-layer subwavelength grating mirror.

We report here the first demonstration of a cryogenic mid-wave infrared (MWIR) hyperspectral fixed-cavity Fabry-Perot filter based on a suspended tensile-strained single-layer 2-D subwavelength grating (SWG) mirror. Optical design optimization of the 2-D SWG mirror and parameter tolerance study are performed. For the first time, process control of grating air-hole sidewall angle and the grating air-hole fill-factor fabrication error caused by e-beam lithography electron-scattering effect is reported. At 80 K, namely the operating temperature of MWIR photodetectors, the as-fabricated suspended 2-D SWG mirror has achieved excellent surface flatness with a slight center-to-edge bowing of 15 nm over a 1-mm2 large mirror area and a high average reflectivity of 0.97 across a wavelength range of 3.72-5 µm, which represents an unprecedentedly wide fractional bandwidth Δλ/λc of 30%. The cryogenically cooled Fabry-Perot filter exhibits an unrivaled high spectral resolution of 10 nm that far exceeds the optical requirement for MWIR hyperspectral imaging applications.

Meta-analysis of the diagnostic value of exosomal miR-21 as a biomarker for the prediction of cancer.

BACKGROUND: Early diagnosis of cancer is still the most effective method to increase survival and therapeutically effective patient management. Accumulating studies had exploited exosomes as an indicator for the diagnosis and prognosis of cancer. In addition to exosomes, exosome-derived miRs are widely investigated as a novel biomarker for diagnosis in cancer patients. The aim of this study was to clarify the diagnostic value of ex-miR-21 in cancer. METHODS: Databases were searched for eligible studies up to June, 2021. Studies included in this meta-analysis were reviewed and selected independently by two authors. The data of sensitivity, specificity, diagnostic odds ratio (DOR), and summary receiver operating characteristic curves (SROC) of exosomal miR-21 as a diagnostic biomarker were extracted and calculated. Quality assessment was conducted by using the QUADAS-2 tool. RESULTS: A total of 26 studies were included in the systematic analysis and meta-analysis. The pooled results of sensitivity, specificity, PLR/NLR, DOR, and area under the curve were 76% (95%CI, 0.70-0.81), 82% (0.77-0.87), 4.3 (3.1-6.0), 0.29 (0.22-0.38), 15 (8-26), and 0.86 (0.83-0.89), respectively. Sensitivity analysis and Deeks' funnel plot indicated that results remained unchanged and had no publication bias. For the subgroup analysis, it was showed that ex-miR-21 had a superior diagnostic accuracy on identifying PC. CONCLUSION: Exosomal microRNA-21 can serve as an effective and widely used diagnostic biomarker for cancer, especially in PC. The using field of exosomes and exosome-derived miR can further extend the prognosis and therapeutic management. Standardized isolation of exosomes and miRNA-21 should be developed.

[Construction of sepsis-associated competing endogenous RNA network based on Gene Expression Omnibus datasets and bioinformatic analysis].

OBJECTIVE: To analyze the sepsis related long non-coding RNA (lncRNA) and mRNA expression profiles based on Gene Expression Omnibus (GEO) datasets and bioinformatic analysis, and to analyze the sepsis-associated competing endogenous RNA (ceRNA) network based on microRNA (miRNA) database. METHODS: The sepsis-related lncRNA dataset was downloaded from the GEO database, and the differential expression analysis was conducted by Bioconductor on the sepsis dataset to obtain differentially expressed lncRNA (DElncRNA) and differentially expressed mRNA (DEmRNA), and cluster heat map was drawn. miRNA combined with DElncRNA were predicted by miRcode. mRNA targeted by miRNA was simultaneously met by three databases: TargetScan, miRDB, and mirTarBase. The interaction relationship of lncRNA-miRNA-mRNA was obtained. The regulatory network visualization software CytoScape was used to draw ceRNA networks. DEmRNA in the ceRNA networks were imported into the Search Tool for the Retrieval of Interacting Genes Database (STRING) online database to draw the protein-protein interaction (PPI) map. The gene ontology (GO) function annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEmRNA were performed. RESULTS: Dataset GSE89376 and GSE145227 were found from GEO database. Difference analysis showed there were 14 DElncRNA and 359 DEmRNA in the elderly group of GSE89376; 8 DElncRNA and 153 DEmRNA in the adult group of GSE89376; 1 232 DElncRNA and 1 224 DEmRNA in the children group of GSE145227. Clustering heatmap showed that there were significant differences in the expression of lncRNA and mRNA between the sepsis group and the control group. The ceRNA networks were constructed with miRNA. Several DElncRNA and multiple DEmRNA participated in the ceRNA network of sepsis. The PPI diagram demonstrated that several genes encoding proteins interacted with each other and form a multi-node interaction network with multiple genes encoding proteins. Functional annotation and enrichment analysis demonstrated that there might be a crosstalk mechanism on functionally related genes such as nuclear receptor activity, ligand-activated transcription factor activity, and steroid hormone receptor activity, and played a role in the occurrence and development of diseases through forkhead box transcription factor O (FoxO) signaling pathway, Janus kinase/signal transducers and activators of transcription (JAK/STAT) signaling pathway, p53 signaling pathway, and phosphateidylinositol 3-kinase (PI3K)/Akt signaling pathway. CONCLUSIONS: Through sepsis-related lncRNA-miRNA-mRNA ceRNA network and combining with KEGG pathway analysis, there were several lncRNA and mRNA participating in the ceRNA network related sepsis, which played an important role in several signal pathways.

Machine learning-based models to support decision-making in emergency department triage for patients with suspected cardiovascular disease.

BACKGROUND: Accurate differentiation and prioritization in emergency department (ED) triage is important to identify high-risk patients and to efficiently allocate of finite resources. Using data available from patients with suspected cardiovascular disease presenting at ED triage, this study aimed to train and compare the performance of four common machine learning models to assist in decision making of triage levels. METHODS: This cross-sectional study in the second Affiliated Hospital of Guangzhou Medical University was conducted from August 2015 to December 2018 inclusive. Demographic information, vital signs, blood glucose, and other available triage scores were collected. Four machine learning models - multinomial logistic regression (multinomial LR), eXtreme gradient boosting (XGBoost), random forest (RF) and gradient-boosted decision tree (GBDT) - were compared. For each model, 80 % of the data set was used for training and 20 % was used to test the models. The area under the receiver operating characteristic curve (AUC), accuracy and macro- F1 were calculated for each model. RESULTS: In 17,661 patients presenting with suspected cardiovascular disease, the distribution of triage of level 1, level 2, level 3 and level 4 were 1.3 %, 18.6 %, 76.5 %, and 3.6 % respectively. The AUCs were: XGBoost (0.937), GBDT (0.921), RF (0.919) and multinomial LR (0.908). Based on feature importance generated by XGBoost, blood pressure, pulse rate, oxygen saturation, and age were the most significant variables for making decisions at triage. CONCLUSION: Four machine learning models had good discriminative ability of triage. XGBoost demonstrated a slight advantage over other models. These models could be used for differential triage of low-risk patients and high-risk patients as a strategy to improve efficiency and allocation of finite resources.

An efficient Fourier ptychographic microscopy method based on optimized pattern of LED angle illumination.

Considering angle diversity and synthetic aperture, Fourier ptychographic microscopy (FPM) could address contradiction of high resolution and wide field of view. However, in the conventional FPM method, large capture quantity leads to poor efficiency. So, an efficient FPM method based on optimized pattern of LED angle illumination is proposed. Firstly, from position relationship between the LED, aperture and sample, we obtain the theoretical expandable spectrum range and the spectrum distribution in Fourier space of all LEDs. Secondly, we u se image quality assessment methods to extract differential expressions between an arbitrary LED illumination and full LEDs illumination. Thirdly, the optimized angle illumination strategy is achieved according to the analysis of different expressions. Based on this method, we design a rhombus-based illumination method for the LED array to accelerate the FPM efficiency. Finally, we validate the effectiveness and efficiency of our method with both simulated and real experiments. The results indicate that our method can effectively improve the efficiency for FPM without sacrificing image reconstruction quality.

Derivation of a Prediction Rule for Unfavorable Outcome after Ischemic Stroke in the Chinese Population.

BACKGROUND: Efficient assessment of patients after ischemic stroke has important reference value for doctors to choose appropriate treatment for patients. Our study aimed to develop a new prognostic model for predicting outcomes 3 months after ischemic stroke among Chinese Population. METHODS: A prospective observational cohort study among ischemic stroke patients presenting to Emergency Department in the Second Affiliated Hospital of Guangzhou Medical University was conducted from May 2012 to June 2013. Demographic data of ischemic stroke patients, assessment of NIHSS and laboratory results were collected. Based on 3-month modified Rankin Scale (mRS) ischemic stroke patients were divided into either favorable outcome (mRS: 0-2) or unfavorable outcome groups (mRS: 3-6). The variables closely associated with prognosis of ischemic stroke were selected to develop the new prognostic model (NAAP) consisted of 4 parameters: NIHSS, age, atrial fibrillation, and prealbumin. The prognostic value of the modified prognostic model was then compared with NIHSS alone. RESULTS: A total of 454 patients with suspected stroke were recruited. One hundred eighty-six patients with ischemic stroke were included in the final analysis. A new prognostic model, NAAP was developed. The area under curve (AUC) of NAAP was .861 (95%confidence interval: .803-.907), whilst the AUC of NIHSS was .783 (95%CI: .717-.840), (P = .0048). Decision curve analysis showed that NAAP had a higher net benefit for threshold probabilities of 65% for predictive risk of poor outcomes. CONCLUSIONS: The modified prognostic model, NAAP may be a better prognostic tool for predicting 3-month unfavorable outcomes for ischemic stroke than NIHSS alone.

Comparative analysis of bla KPC-2- and rmtB-carrying IncFII-family pKPC-LK30/pHN7A8 hybrid plasmids from Klebsiella pneumoniae CG258 strains disseminated among multiple Chinese hospitals.

BACKGROUND: We recently reported the complete sequence of a blaKPC-2- and rmtB-carrying IncFII-family plasmid p675920-1 with the pKPC-LK30/pHN7A8 hybrid structure. Comparative genomics of additional sequenced plasmids with similar hybrid structures and their prevalence in bla KPC-carrying Klebsiella pneumoniae strains from China were investigated in this follow-up study. METHODS: A total of 51 bla KPC-carrying K. pneumoniae strains were isolated from 2012 to 2016 from five Chinese hospitals and genotyped by multilocus sequence typing. The bla KPC-carrying plasmids from four representative strains were sequenced and compared with p675920-1 and pCT-KPC. Plasmid transfer, carbapenemase activity determination, and bacterial antimicrobial susceptibility test were performed to characterize resistance phenotypes mediated by these plasmids. The prevalence of pCT-KPC-like plasmids in these bla KPC-carrying K. pneumoniae strains was screened by PCR. RESULT: The six KPC-encoding plasmids p1068-KPC, p20049-KPC, p12139-KPC and p64917-KPC (sequenced in this study) and p675920-1 and pCT-KPC slightly differed from one another due to deletion and acquisition of various backbone and accessory regions. Two major accessory resistance regions, which included the blaKPC-2 region harboring blaKPC-2 (carbapenem resistance) and blaSHV-12 (ß-lactam resistance), and the MDR region carrying rmtB (aminoglycoside resistance), fosA3 (fosfomycin resistance), bla TEM-1B (ß-lactam resistance) and bla CTX-M-65 (ß-lactam resistance), were found in each of these six plasmids and exhibited several parallel evolution routes. The pCT-KPC-like plasmids were present in all the 51 K. pneumoniae isolates, all of which belonged to CG258. CONCLUSION: There was clonal dissemination of K. pneumoniae CG258 strains, harboring bla KPC-2- and rmtB-carrying IncFII-family pKPC-LK30/pHN7A8 hybrid plasmids, among multiple Chinese hospitals.

Development of the Biomaterials Technology for the Infection Resistance.

Infections caused by microbial proliferation are one of the common issues and serious threats to the medical care, and they usually result in disease spread. Therefore, it is a significant issue for developing the antiinfective biomaterials to control this problem, according to the specific clinical application. Meanwhile, all their properties, the best anti-infective performance, the safe biocompatibility and the appropriate tissue interactions must be conformed to each other. At present, technologies are developing novel biomaterials and surfaces endowed with anti-infective properties, relying either on bactericidal or anti-biofilm activities. This review focuses on thoroughly summarizing numerous kinds of antibacterial biomaterials, including the antibacterial matrix biomaterials, antibacterial coatings and films, nanostructured materials and antibacterial fibers. Among these strategies, the utilization of bio-glass base and graphene base antibacterial matrix, and their effects on the antibiosis mechanism were emphatically discussed. Simultaneously, the effects and mechanisms of nano-coated metallic ions are also mentioned. Overall, there is a wealth of technical solutions to contrast the establishment of an implant infection. The lack of well-structured prospective multicenter clinical trials hinders the achievement of conclusive data on the efficacy and comparative performance of antibacterial biomaterials.

Effects of Macrothele raven venom on intrarenal invasion and metastasis of H22 liver cancer cells in mice.

BACKGROUND: Extrahepatic metastatic hepatocellular carcinoma (HCC) and its insensitivity to chemotherapy are the main causes of poor prognosis in patients with HCC. This study investigated the anti-cancer effect of Macrothele raveni venom on intrarenal metastatic HCC. MATERIALS AND METHODS: Subrenal capsule xenograft model of HCC was established by inoculation of H22 liver cancer cells. RESULTS: The general health, histology, and molecular changes were observed after administering 10 times of different dose of Macrothele raven venom injections. A volume of 0.8 µg/ml and 1.0 µg/ml of Macrothele raven venom significantly improved general health status in mice with subrenal capsule HCC tumors. Hematoxylin and eosin staining showed that Macrothele raven venom dose-dependently reduced invasion and metastasis of liver cancer cells in the kidney. Immunohistochemistry and real-time polymerase chain reaction showed that Macrothele raven venom injection dose-dependently decreased PI3K mRNA and protein, Akt protein, and mTOR mRNA expression, but increased Bad mRNA and protein expression in the kidney with H22 tumor cell invasion. 0.8 µg/ml is the most effective dose for the treatment of intrarenal metastatic HCC. CONCLUSIONS: Macrothele raven venom dose-dependently inhibits invasion and metastasis of intrarenal metastatic HCC through inhibition of PI3K-Akt-mTOR signaling and increase of Bad expression.

Aerobic exercise combined with huwentoxin-I mitigates chronic cerebral ischemia injury.

Ca2+ channel blockers have been shown to protect neurons from ischemia, and aerobic exercise has significant protective effects on a variety of chronic diseases. The present study injected huwentoxin-I (HWTX-I), a spider peptide toxin that blocks Ca2+ channels, into the caudal vein of a chronic cerebral ischemia mouse model, once every 2 days, for a total of 15 injections. During this time, a subgroup of mice was subjected to treadmill exercise for 5 weeks. Results showed amelioration of cortical injury and improved neurological function in mice with chronic cerebral ischemia in the HWTX-I + aerobic exercise group. The combined effects of HWTX-I and exercise were superior to HWTX-I or aerobic exercise alone. HWTX-I effectively activated the Notch signal transduction pathway in brain tissue. Aerobic exercise up-regulated synaptophysin mRNA expression. These results demonstrated that aerobic exercise, in combination with HWTX-I, effectively relieved neuronal injury induced by chronic cerebral ischemia via the Notch signaling pathway and promoting synaptic regeneration.

Development of a new stroke scale in an emergency setting.

BACKGROUND: Early identification of stroke is crucial to maximize early management benefits in emergency departments. This study aimed to develop and validate a new stroke recognition instrument for differentiating acute stroke from stroke mimics in an emergency setting. METHODS: A prospective observational cohort study among suspected stroke patients presenting to Emergency Department in the Second Affiliated Hospital of Guangzhou Medical University was conducted from May 2012 to March 2013. The symptoms and signs of suspected stroke patients were collected. Logistic regression analysis was used to identify the factors associated with acute stroke. The symptoms and signs closely associated with acute stroke were selected to develop the new stroke scale, Guangzhou Stroke Scale (GZSS). The diagnostic value of GZSS was then compared with ROSIER, FAST and LAPSS. The primary outcome was confirmed stroke by CT within 24 h. RESULTS: Four hundred and sixteen suspected stroke patients (247 ischemia, 107 hemorrhage, 4 transient ischemic attack, 58 non-stroke) were assessed. A new stroke scale, GZSS (total score from -1 to 8.5), was developed and consisted of nine parameters: vertigo (-1), GCS ≤ 8 (+2), facial paralysis (+1), asymmetric arm weakness (+1), asymmetric leg weakness (+1), speech disturbance (+0.5), visual field defect (+1), systolic blood pressure ≥145 mmHg (+1) and diastolic blood pressure ≥95 mmHg (+1). Among the four scales, the discriminatory value (C-statistic) of GZSS was the best (AUC: 0.871 (p < 0.001) when compared to ROSIER (0.772), LAPSS (0.722) and FAST (0.699). At an optimal cut-off score of >1.5 on a scale from -1 to 8.5, the sensitivity and specificity of GZSS were 83.2 and 74.1 %, whilst the sensitivities and specificities of ROSIER were 77.7 and 70.7 %, FAST were 76.0 and 63.8 %, LAPSS were 56.4 and 87.9 %. CONCLUSION: GZSS had better sensitivity than existing stroke scales in Chinese patients with suspected stroke. Further studies should be conducted to confirm its effectiveness in the initial differentiation of acute stroke from stroke mimics.

Increased expression of microRNA-21 in peripheral blood mediates the down-regulation of IFN-γ and increases the prevalence of stroke-associated infection.

BACKGROUND: Increasing levels of microRNA (miRNA)-21 can lead to IFN-γ deficiency, thereby suppressing immune function. Whether changes in the peripheral blood expression of miRNA-21 in patients with acute stroke are related to stroke-associated infection (SAI) remains unsettled. METHODS: MiRNA-21 and IFN-γ expression levels in peripheral blood plasma were measured in stroke patients presenting within 24h of symptom onset to assess whether these expression levels are associated with the prevalence of SAI. RESULTS: The stroke with SAI group had significantly higher miRNA-21 expression and lower IFN-γ levels than the stroke without SAI group (p<0.05). A significant negative correlation was observed between miRNA-21 expression and IFN-γ levels (r=-0.303, p=0.026). ROC curves were constructed to measure the performance of the miRNA-21 and IFN-γ to judge SAI. The areas under the ROC curve (AUC) for miRNA-21 and IFN-γ were 0.667 (95% CI, 0.525 to 0.798, p=0.028) and 0.698 (95% CI, 0.558 to 0.816, p=0.005), respectively. The optimal cutoff value was miRNA-21>0.53 and IFN-γ≤72.57pg/ml. There was a significantly different prevalence of SAI between the high miRNA-21 group and the low miRNA-21 group (p=0.008, log rank test). There was also a significant difference between the high IFN-γ group and the low IFN-γ group (p=0.003, log rank test). CONCLUSIONS: Plasma up-regulated miRNA-21 and decreased IFN-γ in acute stroke can be considered new biological predictors for SAI and thus, new therapeutic targets.

Circular RNA expression alterations are involved in OGD/R-induced neuron injury.

Cerebral ischemia-reperfusion injury (IRI) is a common clinical pathological process, and it is a key step in causing further ischemic organ damage. The mechanism of cerebral IRI is still not fully understood, leading to a lack of effective treatment. It has been demonstrated that circular RNAs (circRNAs) can act as miRNA sponges and play an important role in regulating gene expression through a circRNA-miRNA-gene pathway. The specific role of circRNAs in the pathogenesis of cerebral IRI, however, is still unclear. Thus, in the present study, we investigated circRNA expression differences in HT22 cells with oxygen-glucose deprivation/reoxygenation (OGD/R) versus normal controls. The results from circRNA microarrays revealed that 15 circRNAs were significantly altered in the OGD/R model (p < 0.05) compared with the control group. Among them, 3 were significantly up-regulated, and the other 12 were down-regulated. Furthermore, the up-regulated expression of mmu-circRNA-015947 was verified using quantitative real-time polymerase chain reaction (qRT-PCR). Bioinformatics analysis revealed that up-regulated expression of mmu-circRNA-015947 could interact with miRNAs (mmu-miR-188-3p, mmu-miR-329-5p, mmu-miR-3057-3p, mmu-miR-5098 and mmu-miR-683) and thereby enhance target gene expression. KEGG pathway analysis predicted that mmu-circRNA-015947 may participate in apoptosis-related, metabolism-related and immune-related pathways, which are known to be involved in the pathogenesis of IRI. This research suggests that the overlapping expression of mmu-circRNA-015947 might be involved in the process of cerebral IRI and presents a novel molecular target for clinical therapy.

Lithium perchlorate-nitromethane-promoted alkylation of anilines with arylmethanols.

A new application of lithium perchlorate-nitromethane (LPNM) for the formation of aromatic C-N and C-C bonds is introduced. LPNM-promoted reactions of anilines with diarylmethanols selectively generate N-alkylated anilines or mono and double Friedel-Crafts alkylation products under different conditions by changing the reaction time, reaction temperature, and the ratio of the reactants. This method does not require the use of transition metal catalysts to prepare alkylated aniline derivatives.

Effect of Huwentoxin-I on the Fas and TNF apoptosis pathway in the hippocampus of rat with global cerebral ischemia.

Neuronal injury is the most important reason for various brain injuries. Cytosolic Ca(2+) overloading has been proposed as one of the main cellular processes leading to neuronal death during cerebral ischemia. It is well accepted that Ca(2+) channel blockers can protect cerebral neurons from ischemic injury. In the present studies, we investigated the molecular mechanism for the neuro-protective effect of Huwentoxin-I (HWTX-I), a spider toxin selectively blocking N-type voltage-dependent Ca((2+)) channel, on rat models with global cerebral ischemia-reperfusion injury. Our studies demonstrated that HWTX-I could maintain the morphological stability of pyramidal cells in this model. Furthermore, HWTX-I could decrease the concentration of malon-dialdehyde, but increase the activity of superoxide dismutase and glutathione peroxidase. It also reduced the expression level of related factors of Fas and tumor necrosis factor death receptor apoptosis pathways in the hippocampus. In summary, HWTX-I has an obvious neuroprotective effect, which may act through its inhibition on a certain apoptosis pathway.