ATF3 is a neuron-specific biomarker for spinal cord injury and ischaemic stroke.

BACKGROUND: Although many molecules have been investigated as biomarkers for spinal cord injury (SCI) or ischemic stroke, none of them are specifically induced in central nervous system (CNS) neurons following injuries with low baseline expression. However, neuronal injury constitutes a major pathology associated with SCI or stroke and strongly correlates with neurological outcomes. Biomarkers characterized by low baseline expression and specific induction in neurons post-injury are likely to better correlate with injury severity and recovery, demonstrating higher sensitivity and specificity for CNS injuries compared to non-neuronal markers or pan-neuronal markers with constitutive expressions. METHODS: In animal studies, young adult wildtype and global Atf3 knockout mice underwent unilateral cervical 5 (C5) SCI or permanent distal middle cerebral artery occlusion (pMCAO). Gene expression was assessed using RNA-sequencing and qRT-PCR, while protein expression was detected through immunostaining. Serum ATF3 levels in animal models and clinical human samples were measured using commercially available enzyme-linked immune-sorbent assay (ELISA) kits. RESULTS: Activating transcription factor 3 (ATF3), a molecular marker for injured dorsal root ganglion sensory neurons in the peripheral nervous system, was not expressed in spinal cord or cortex of naïve mice but was induced specifically in neurons of the spinal cord or cortex within 1 day after SCI or ischemic stroke, respectively. Additionally, ATF3 protein levels in mouse blood significantly increased 1 day after SCI or ischemic stroke. Importantly, ATF3 protein levels in human serum were elevated in clinical patients within 24 hours after SCI or ischemic stroke. Moreover, Atf3 knockout mice, compared to the wildtype mice, exhibited worse neurological outcomes and larger damage regions after SCI or ischemic stroke, indicating that ATF3 has a neuroprotective function. CONCLUSIONS: ATF3 is an easily measurable, neuron-specific biomarker for clinical SCI and ischemic stroke, with neuroprotective properties. HIGHLIGHTS: ATF3 was induced specifically in neurons of the spinal cord or cortex within 1 day after SCI or ischemic stroke, respectively. Serum ATF3 protein levels are elevated in clinical patients within 24 hours after SCI or ischemic stroke. ATF3 exhibits neuroprotective properties, as evidenced by the worse neurological outcomes and larger damage regions observed in Atf3 knockout mice compared to wildtype mice following SCI or ischemic stroke.

Activation of glutamatergic neurones in the pedunculopontine tegmental nucleus promotes cortical activation and behavioural emergence from sevoflurane-induced unconsciousness in mice.

BACKGROUND: The neural mechanisms underlying sevoflurane-induced loss of consciousness and recovery of consciousness after anaesthesia remain unknown. We investigated whether glutamatergic pedunculopontine tegmental nucleus (PPT) neurones are involved in the regulation of states of consciousness under sevoflurane anaesthesia. METHODS: In vivo fibre photometry combined with electroencephalography (EEG)/electromyography recording was used to record changes in the activity of glutamatergic PPT neurones under sevoflurane anaesthesia. Chemogenetic and cortical EEG recordings were used to explore their roles in the induction of and emergence from sevoflurane anaesthesia. Optogenetic methods combined with EEG recordings were used to explore the roles of glutamatergic PPT neurones and of the PPT-ventral tegmental area pathway in maintenance of anaesthesia. RESULTS: The population activity of glutamatergic PPT neurones was reduced before sevoflurane-induced loss of righting reflex and gradually recovered after return of righting reflex. Chemogenetic inhibition of glutamatergic PPT neurones accelerated induction of anaesthesia (hM4Di-CNO vs mCherry-CNO, 76 [17] vs 121 [27] s, P<0.0001) and delayed emergence from sevoflurane anaesthesia (278 [98] vs 145 [53] s, P<0.0001) but increased sevoflurane sensitivity. Optogenetic stimulation of glutamatergic PPT neurons or of the PPT-ventral tegmental area pathway promoted cortical activation and behavioural emergence during steady-state sevoflurane anaesthesia, reduced the depth of anaesthesia, and caused cortical arousal during sevoflurane-induced EEG burst suppression. CONCLUSIONS: Glutamatergic PPT neurones regulate induction and emergence of sevoflurane anaesthesia.

Distinct phases of adult microglia proliferation: a Myc-mediated early phase and a Tnfaip3-mediated late phase.

Microgliosis is a hallmark of many neurological diseases, including Alzheimer's disease, stroke, seizure, traumatic brain and spinal cord injuries, and peripheral and optic nerve injuries. Recent studies have shown that the newly self-renewed microglia have specific neurological functions. However, the mechanism of adult microglia proliferation remains largely unclear. Here, with single-cell RNA sequencing, flow cytometry, and immunohistochemistry, we demonstrate that the sciatic nerve injury induced two distinct phases of microglia proliferation in mouse spinal cord, each with different gene expression profiles. We demonstrate that the transcription factor Myc was transiently upregulated in spinal cord microglia after nerve injury to mediate an early phase microglia proliferation. On the other hand, we reveal that the tumor-necrosis factor alpha-induced protein 3 (Tnfaip3) was downregulated to mediate the Myc-independent late-phase microglia proliferation. We show that cyclin dependent kinase 1, a kinase with important function in the M phase of the cell cycle, was involved only in the early phase. We reveal that although the early phase was neither necessary nor sufficient for the late phase proliferation, the late-phase suppressed the early phase microglia proliferation in the spinal cord. Finally, we demonstrate that the termination of spinal cord microglia proliferation required both Myc and Tnfaip3 to resume their baseline expression. Thus, we have delineated an interactive signaling network in the proliferation of differentiated microglia.

Inflammation as a risk factor for stroke in atrial fibrillation: data from a microarray data analysis.

OBJECTIVE: Stroke is a severe complication of atrial fibrillation (AF). We aimed to discover key genes and microRNAs related to stroke risk in patients with AF using bioinformatics analysis. METHODS: GSE66724 microarray data, including peripheral blood samples from eight patients with AF and stroke and eight patients with AF without stroke, were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between AF patients with and without stroke were identified using the GEO2R online tool. Functional enrichment analysis was performed using the DAVID database. A protein-protein interaction (PPI) network was obtained using the STRING database. MicroRNAs (miRs) targeting these DEGs were obtained from the miRNet database. A miR-DEG network was constructed using Cytoscape software. RESULTS: We identified 165 DEGs (141 upregulated and 24 downregulated). Enrichment analysis showed enrichment of certain inflammatory processes. The miR-DEG network revealed key genes, including MEF2A, CAND1, PELI1, and PDCD4, and microRNAs, including miR-1, miR-1-3p, miR-21, miR-21-5p, miR-192, miR-192-5p, miR-155, and miR-155-5p. CONCLUSION: Dysregulation of certain genes and microRNAs involved in inflammation may be associated with a higher risk of stroke in patients with AF. Evaluating these biomarkers could improve prediction, prevention, and treatment of stroke in patients with AF.

Applying deep learning in recognizing the femoral nerve block region on ultrasound images.

BACKGROUND: Identifying the nerve block region is important for the less experienced operators who are not skilled in ultrasound technology. Therefore, we constructed and shared a dataset of ultrasonic images to explore a method to identify the femoral nerve block region. METHODS: Ultrasound images of femoral nerve block were retrospectively collected and marked to establish the dataset. The U-net framework was used for training data and output segmentation of region of interest. The performance of the model was evaluated by Intersection over Union and accuracy. Then the predicted masks were highlighted on the original image to give an intuitive evaluation. Finally, cross validation was used for the whole data to test the robust of the results. RESULTS: We selected 562 ultrasound images as the whole dataset. The training set intersection over union (IoU) was 0.713, the development set IoU is 0.633 and the test set IoU is 0.638. For the single image, the median and upper/lower quartiles of IoU were 0.722 (0.647-0.789), 0.653 (0.586-0.703), 0.644 (0.555-0.735) for the training set, development set and test set respectively. The segmentation accuracy of the test set was 83.9%. For 10-fold cross validation, the median and quartiles of the 10-iteration sum IoUs was 0.656 (0.628-0.672); for accuracy, they were 88.4% (82.1-90.7%). CONCLUSIONS: We provided a dataset and trained a model for femoral-nerve region segmentation with U-net, obtaining a satisfactory performance. This technique may have potential clinical application.

Dexmedetomidine versus midazolam and propofol for sedation in critically ill patients: Mining the Medical Information Mart for Intensive Care data.

BACKGROUND: The benefits of dexmedetomidine on reducing mortality and length of intensive care unit (ICU) stay are still controversial. We aimed to evaluate the superiority of dexmedetomidine by comparing it with midazolam and propofol. METHODS: Subjects who were given dexmedetomidine, midazolam and propofol exclusively as sedatives in the Beth Israel Deaconess Medical Center between 2001 and 2012 were identified from the Medical Information Mart for Intensive Care (MIMIC) III database. Univariate, multivariate and stratified analysis was performed to compare the mortality and length of ICU stay between the dexmedetomidine, midazolam and propofol groups. To compare the depth of sedation between the midazolam and propofol group, we used propensity score matching (PSM) to create comparable units and their Richmond Agitation Sedation Score (RASS) were analyzed. RESULTS: A total of 1,542 unique ICU records were identified in the MIMIC-III database, among which 163 belonged to the dexmedetomidine group and 531 belonged to the midazolam group and 848 belonged to the propofol group. Mortality was decreased in dexmedetomidine group compared with midazolam group (OR 15.25; 95% CI, 5.29-64.80, P<0.001) and propofol group (OR 5.51; 95% CI, 1.91-23.45, P=0.006). In patients with high Simplified Acute Physiologic Score (SAPS) II (>52), midazolam was related to a higher mortality (~50%). But competing risk analysis revealed that dexmedetomidine was associated with longer ICU stay (P<0.001). There was no significant difference in the RASS between propofol and midazolam group (P=0.300). CONCLUSIONS: Dexmedetomidine was significantly related to lower mortality when compared with midazolam and propofol. Midazolam had a comparably higher mortality than propofol and dexmedetomidine in patients with high SAPS II. Propofol and midazolam were equivalent in sedative efficacy. Further evaluation is needed.

Multiple Machine Learnings Revealed Similar Predictive Accuracy for Prognosis of PNETs from the Surveillance, Epidemiology, and End Result Database.

Background: Prognosis prediction is indispensable in clinical practice and machine learning has been proved to be helpful. We expected to predict survival of pancreatic neuroendocrine tumors (PNETs) with machine learning, and compared it with the American Joint Committee on Cancer (AJCC) staging system. Methods: Data of PNETs cases were extracted from The Surveillance, Epidemiology, and End Result (SEER) database. Statistic description, multivariate survival analysis and preprocessing were done before machine learning. Four different algorithms (logistic regression (LR), support vector machines (SVM), random forest (RF) and deep learning (DL)) were used to train the model. We used proper imputations to manage missing data in the database and sensitive analysis was performed to evaluate the imputation. The model with the best predictive accuracy was compared with the AJCC staging system using the SEER cases. Results: The four models had similar predictive accuracy with no significant difference existed (p = 0.664). The DL model showed a slightly better predictive accuracy than others (81.6% (± 1.9%)), thus it was used for further comparison with the AJCC staging system and revealed a better performance for PNETs cases in SEER database (Area under receiver operating characteristic curve: 0.87 vs 0.76). The validity of missing data imputation was supported by sensitivity analysis. Conclusions: The models developed with machine learning performed well in survival prediction of PNETs, and the DL model have a better accuracy and specificity than the AJCC staging system in SEER data. The DL model has potential for clinical application but external validation is needed.

Prolonged dexmedetomidine infusion in critically ill adult patients: a retrospective analysis of a large clinical database Multiparameter Intelligent Monitoring in Intensive Care III.

BACKGROUND: There is no conclusive evidence for the effects of prolonged infusion of dexmedetomidine in critically ill patients. We aimed to investigate the safety of long-term dexmedetomidine infusion in a large critically ill patients cohort from the Multiparameter Intelligent Monitoring in Intensive Care III (MIMIC-III) database. METHODS: We retrospectively extracted records from MIMIC-III database. Dexmedetomidine administration time was the basis for group. Variables were compared by chi-square tests, and Mann-Whitney U test as appropriate. We used logistic regression model for multivariate analysis. Contour maps were drawn to measure rebound of heart rate (HR) and blood pressure (BP). RESULTS: We finally got 1,946 records including 1,368 distinct individuals. Age, body mass index (BMI), length of stay in hospital, accumulated doses of dexmedetomidine and Sequential Organ Failure Assessment (SOFA) score were independent risk factors of in-hospital mortality (P<0.05). But prolonged dexmedetomidine infusion (≥24 h) and abrupt cessation did not increase in-hospital mortality. Furthermore, the rebound of HR and BP was more likely to occur in patients with prolonged infusion of dexmedetomidine. CONCLUSIONS: Prolonged dexmedetomidine infusion is not related to an increased in-hospital mortality, but it is associated with the rebound effect of HR and BP. Further prospective studies are needed.

Prophylactic Intravenous Lidocaine at Different Doses for Fentanyl-Induced Cough (FIC): A Meta-Analysis.

To evaluate whether different doses of intravenous lidocaine are effective at preventing fentanyl-induced cough (FIC), we searched PubMed, Scopus, Cochrane Library, EMBASE and Web of Science, according to predefined criteria, for all articles published until June 2017. A meta-analysis and subgroup analysis were performed by combining the reported incidence of FIC. The odds ratio (OR) was used as a summary statistic. Eleven articles were included, with 965 patients in the lidocaine group and 745 patients in the control group. A pooled analysis indicated that the overall incidence of FIC was significantly different between the lidocaine group and the control group (OR, 0.27; 95% confidence interval (CI), 0.21-0.35; P < 0.05), as well as between the adult and paediatric subgroups. Sensitivity analysis showed that the results were stable. Subgroup analyses showed that compared to a placebo, both low (0.5-1.0 mg/kg) and high doses of lidocaine (1.5-2.0 mg/kg) were effective at reducing FIC incidence. There was no significant difference between low or high doses of lidocaine. Fentanyl doses added no significant heterogeneity as shown by meta-regression. The findings of this meta-analysis indicate that prophylactic intravenous lidocaine is effective at preventing FIC in both adults and children.

Bioinformatic Analysis of Potential Biomarkers for Spinal Cord-injured Patients with Intractable Neuropathic Pain.

BACKGROUND: Neuropathic pain is one of the common complications after spinal cord injury (SCI), affecting individuals' quality of life. The molecular mechanism for neuropathic pain after SCI is still unclear. We aimed to discover potential genes and microRNAs (miRNAs) related to neuropathic pain by the bioinformatics method. METHODS: Microarray data of GSE69901 were obtained from Gene Expression Omnibus (GEO) database. Peripheral blood samples from individuals with or without neuropathic pain after SCI were collected. Twelve samples from individuals with neuropathic pain and 13 samples from individuals without pain as controls were included in the downloaded microarray. Differentially expressed genes (DEGs) between the neuropathic pain group and the control group were detected using the GEO2R online tool. Functional enrichment analysis of DEGs was performed using the DAVID database. Protein-protein interaction network was constructed from the STRING database. MiRNAs targeting these DEGs were obtained from the miRNet database. A merged miRNA-DEG network was constructed and analyzed with Cytoscape software. RESULTS: In total, 1134 DEGs were identified between individuals with or without neuropathic pain (case and control), and 454 biological processes were enriched. We identified 4 targeted miRNAs, including mir-204-5p, mir-519d-3p, mir-20b-5p, mir-6838-5p, which may be potential biomarkers for SCI patients. CONCLUSION: Protein modification and regulation of the biological process of the central nervous system may be a risk factor in SCI. Certain genes and miRNAs may be potential biomarkers for the prediction of and potential targets for the prevention and treatment of neuropathic pain after SCI.

A bibliometric analysis in gene research of myocardial infarction from 2001 to 2015.

OBJECTIVES: We aimed to evaluate the global scientific output of gene research of myocardial infarction and explore their hotspots and frontiers from 2001 to 2015, using bibliometric methods. METHODS: Articles about the gene research of myocardial infarction between 2001 and 2015 were retrieved from the Web of Science Core Collection (WoSCC). We used the bibliometric method and Citespace V to analyze publication years, journals, countries, institutions, research areas, authors, research hotspots, and trends. We plotted the reference co-citation network, and we used key words to analyze the research hotspots and trends. RESULTS: We identified 1,853 publications on gene research of myocardial research from 2001 to 2015, and the annual publication number increased with time. Circulation published the highest number of articles. United States ranked highest in the countries with most publications, and the leading institute was Harvard University. Relevant publications were mainly in the field of Cardiovascular system cardiology. Keywords and references analysis indicated that gene expression, microRNA and young women were the research hotspots, whereas stem cell, chemokine, inflammation and cardiac repair were the frontiers. CONCLUSIONS: We depicted gene research of myocardial infarction overall by bibliometric analysis. Mesenchymal stem cells Therapy, MSCs-derived microRNA and genetic modified MSCs are the latest research frontiers. Related studies may pioneer the future direction of this filed in next few years. Further studies are needed.

The influence of marital status on survival in patients with oral tongue squamous cell carcinoma.

Marital status was found to be an independent prognostic factor for survival in several cancers. However related researches of oral tongue squamous cell carcinoma (OTSCC) are still rare. We explored the Surveillance, Epidemiology, and End Results (SEER) program and finally identified 14,194 patients with OTSCC. Kaplan-Meier analysis and multivariate Cox regression models were used to distinguish risk factors for overall survival (OS) and tumor cause-specific survival (TCSS). Widowed patients had the highest percentage of female, highest average ages and more prevalence with localized SEER Stage significantly, while patients in the single group were younger than other groups. After univariate analysis and multivariate analysis, marital status was demonstrated to be an independent prognostic factor of OS and TCSS. Married patients showed better 5-year OS (65.6%) and 5-year TCSS (89.9%) than other patients. Subgroup survival analysis according to AJCC TNM stage and SEER stage showed that the widowed patients demonstrated worst OS and TCSS compared to other groups. Marital status was an important prognostic factor for survival in patients with OTSCC. Widowed patients exhibited with the highest risk of death compared with other groups.

A 16-gene signature predicting prognosis of patients with oral tongue squamous cell carcinoma.

BACKGROUND: Oral tongue squamous cell carcinoma (OTSCC) is the most common subtype of oral cancer. A predictive gene signature is necessary for prognosis of OTSCC. METHODS: Five microarray data sets of OTSCC from the Gene Expression Omnibus (GEO) and one data set from The Cancer Genome Atlas (TCGA) were obtained. Differentially expressed genes (DEGs) of GEO data sets were identified by integrated analysis. The DEGs associated with prognosis were screened in the TCGA data set by univariate survival analysis to obtain a gene signature. A risk score was calculated as the summation of weighted expression levels with coefficients by Cox analysis. The signature was used to distinguish carcinoma, estimated by receiver operator characteristic curves and the area under the curve (AUC). All were validated in the GEO and TCGA data sets. RESULTS: Integrated analysis of GEO data sets revealed 300 DEGs. A 16-gene signature and a risk score were developed after survival analysis. The risk score was effective to stratify patients into high-risk and low-risk groups in the TCGA data set (P < 0.001). The 16-gene signature was valid to distinguish the carcinoma from normal samples (AUC 0.872, P < 0.001). DISCUSSION: We identified a useful 16-gene signature for prognosis of OTSCC patients, which could be applied to clinical practice. Further studies were needed to prove the findings.

Racial disparities in pancreatic neuroendocrine tumors survival: a SEER study.

Pancreatic neuroendocrine tumor (pancreatic NETs), is an important cause of cancer-related death worldwide. No study has rigorously explored the impact of ethnicity on pancreatic NETs. We aimed to demonstrate the relationship between ethnicity and the survival of patients with pancreatic NETs. We used the SEER database to identify patients with pancreatic NETs from 2004 to 2013. Kaplan-Meier methods and Cox proportional hazard models were used to evaluate the impact of race on survival in pancreatic NETs patients. A total of 3850 patients were included: 3357 Non-Blacks, 493 Blacks. We stratified races as "Black" and "White/Other." Blacks were more likely to be diagnosed with later stages of tumors (P = 0.021). As for the treatment, the access to surgery seemed to be more limited in Blacks than non-Black patients (P = 0.012). Compared with non-Black patients, Black patients have worse overall survival (OS) (HR = 1.17, 95% CI: 1.00-1.37, P = 0.046) and pancreatic neuroendocrine tumors specific survival (PNSS) (HR = 1.22, 95% CI: 1.01-1.48, P = 0.044). Multivariate Cox analysis identified that disease extension at the time of diagnosis and surgical status contributed to the ethnical survival disparity. Black patients whose stages at diagnosis were localized had significantly worse OS (HR = 2.09, 95% CI: 1.18-3.71, P = 0.011) and PNSS (HR = 3.79, 95% CI: 1.62-8.82, P = 0.002). As for the patients who did not receive surgery, Blacks also have a worse OS (HR = 1.18, 95% CI: 1.00-1.41, P = 0.045). The Black patients had both worse OS and PNSS compared to non-Black patients. The restricted utilization of surgery, and the advanced disease extension at the time of diagnosis are the possible contributors to poorer survival of Blacks with pancreatic NETs.

Analysis of gene expression profile microarray data in complex regional pain syndrome.

The aim of the present study was to predict key genes and proteins associated with complex regional pain syndrome (CRPS) using bioinformatics analysis. The gene expression profiling microarray data, GSE47603, which included peripheral blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in CRPS patients compared with healthy controls were identified using the GEO2R online tool. Functional enrichment analysis was then performed using The Database for Annotation Visualization and Integrated Discovery online tool. Protein­protein interaction (PPI) network analysis was subsequently performed using Search Tool for the Retrieval of Interaction Genes database and analyzed with Cytoscape software. A total of 257 DEGs were identified, including 243 upregulated genes and 14 downregulated ones. Genes in the human leukocyte antigen (HLA) family were most significantly differentially expressed. Enrichment analysis demonstrated that signaling pathways, including immune response, cell motion, adhesion and angiogenesis were associated with CRPS. PPI network analysis revealed that key genes, including early region 1A binding protein p300 (EP300), CREB­binding protein (CREBBP), signal transducer and activator of transcription (STAT)3, STAT5A and integrin α M were associated with CRPS. The results suggest that the immune response may therefore serve an important role in CRPS development. In addition, genes in the HLA family, such as HLA­DQB1 and HLA­DRB1, may present potential biomarkers for the diagnosis of CRPS. Furthermore, EP300, its paralog CREBBP, and the STAT family genes, STAT3 and STAT5 may be important in the development of CRPS.

Integrated clinicopathological features and gene microarray analysis of pancreatic neuroendocrine tumors.

Pancreatic neuroendocrine tumors are relatively rare pancreatic neoplasms over the world. Investigations about molecular biology of PNETs are insufficient for nowadays. We aimed to explore the expression of messenger RNA and regulatory processes underlying pancreatic neuroendocrine tumors from different views. The expression profile of GSE73338 were downloaded, including samples with pancreatic neuroendocrine tumors. First, the Limma package was utilized to distinguish the differentially expressed messenger RNA. Gene Ontology classification and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed to explore the functions and pathways of target genes. In addition, we constructed a protein-protein interaction network. NEK2, UBE2C, TOP2A and PPP1R1A were revealed with continuous genomic alterations in higher tumor stage. 91 up-regulated and 36 down-regulated genes were identified to be differentially expressed in malignant PNETs. Locomotory behavior was significantly enriched for biological processes of metastasis PNETs. GCGR and GNAS were identified as the hub of proteins in the protein-protein interaction sub-network of malignant PNETs. We showed the gene expression differences in PNETs according to different clinicopathological aspects. NEK2, UBE2C, TOP2A are positively associated with high tumor grade, and PPP1R1A negatively. GCGR and GNAS are regarded as the hub of the PPI sub-network. CXCR4 may affect the progression of PNETs via the CXCR4-CXCL12-CXCR7 chemokine receptor axis. However, more studies are required.

Marital status is an independent prognostic factor for pancreatic neuroendocrine tumors patients: An analysis of the Surveillance, Epidemiology, and End Results (SEER) database.

BACKGROUND AND OBJECTIVES: Marital status's prognostic impact on pancreatic neuroendocrine tumors (PNET) has not been rigorously studied. We aimed to explore the relationship between marital status and outcomes of PNET. METHODS: We retrospectively investigated 2060 PNET cases between 2004 and 2010 from Surveillance, Epidemiology, and End Results (SEER) database. Variables were compared by Chi2 test, t-test as appropriate. Kaplan-Meier methods and COX proportional hazard models were used to ascertain independent prognostic factors. RESULTS: Married patients had better 5-year overall survival (OS) (53.37% vs. 42.27%, P<0.001) and 5-year pancreatic neuroendocrine tumor specific survival (PNSS) (67.76% vs. 59.82%, P=0.001) comparing with unmarried patients. Multivariate analysis revealed marital status is an independent prognostic factor, with married patients showing better OS (HR=0.74; 95% CI: 0.65-0.84; P<0.001) and PNSS (HR=0.78; 95% CI: 0.66-0.92; P=0.004). Subgroup analysis suggested marital status plays a more important role in the PNET patients with distant stage rather than regional or localized disease. CONCLUSIONS: Marital status is an independent prognostic factor for survival in PNET patients. Poor prognosis in unmarried patients may be associated with a delayed diagnosis with advanced tumor stage, psychosocial and socioeconomic factors. Further studies are needed.

The Efficacy of Lidocaine in Laryngospasm Prevention in Pediatric Surgery: a Network Meta-analysis.

Higher incidence and worse outcomes of laryngospasm during general anesthesia in children than adults have been reported for many years, but few prevention measures are put forward. Efficacy of lidocaine in laryngospasm prevention has been argued for many years and we decided to design this network meta-analysis to assess the efficacy of lidocaine. We conducted an electronic search of six sources and finally included 12 Randomized Controlled Trials including 1416 patients. A direct comparison between lidocaine and placebo revealed lidocaine had the effect on preventing laryngospasm in pediatric surgery (RR = 0.46, 95% CI = [0.30, 0.70], P = 0.0002, I(2) = 0%). Both subgroup analysis and network analysis demonstrated that both intravenous lidocaine (subgroup: RR = 0.39, 95% CI = [0.18, 0.86], P = 0.02, I(2) = 38%; network: RR = 0.25, 95% CI = [0.04, 0.86]) and topical lidocaine (subgroup: RR = 0.37, 95% CI = [0.19, 0.72], P = 0.003, I(2) = 0%; network: RR = 0.14, 95% CI = [0.02, 0.55]) was effective in laryngospasm prevention, while no statistical difference was found in a comparison between intravenous and topical lidocaine. In conclusion, both intravenous and topical lidocaine are effective in laryngospasm prevention in pediatric surgery, while a comparison between them needs more evidences.

Integrated Analysis of Expression Profile Based on Differentially Expressed Genes in Middle Cerebral Artery Occlusion Animal Models.

Stroke is one of the most common causes of death, only second to heart disease. Molecular investigations about stroke are in acute shortage nowadays. This study is intended to explore a gene expression profile after brain ischemia reperfusion. Meta-analysis, differential expression analysis, and integrated analysis were employed on an eight microarray series. We explored the functions and pathways of target genes in gene ontology (GO) enrichment analysis and constructed a protein-protein interaction network. Meta-analysis identified 360 differentially expressed genes (DEGs) for Mus musculus and 255 for Rattus norvegicus. Differential expression analysis identified 44 DEGs for Mus musculus and 21 for Rattus norvegicus. Timp1 and Lcn2 were overexpressed in both species. The cytokine-cytokine receptor interaction and chemokine signaling pathway were highly enriched for the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. We have exhibited a global view of the potential molecular differences between middle cerebral artery occlusion (MCAO) animal model and sham for Mus musculus or Rattus norvegicus, including the biological process and enriched pathways in DEGs. This research helps contribute to a clearer understanding of the inflammation process and accurate identification of ischemic infarction stages, which might be transformed into a therapeutic approach.