Poly (ADP-ribose) polymerase plays an important role in intermittent hypoxia-induced cell death in rat cerebellar granule cells

<p>Abstract</p> <p>Background</p> <p>Episodic cessation of airflow during sleep in patients with sleep apnea syndrome results in intermittent hypoxia (IH). Our aim was to investigate the effects of IH on cerebellar granule cells and to identify the mechanism of IH-induced cell death.</p> <p>Methods</p> <p>Cerebellar granule cells were freshly prepared from neonatal Sprague-Dawley rats. IH was created by culturing the cerebellar granule cells in the incubators with oscillating O₂concentration at 20% and 5% every 30 min for 1-4 days. The results of this study are based on image analysis using a confocal microscope and associated software. Cellular oxidative stress increased with increase in IH. In addition, the occurrence of cell death (apoptosis and necrosis) increased as the duration of IH increased, but decreased in the presence of an iron chelator (phenanthroline) or poly (ADP-ribose) polymerase (PARP) inhibitors [3-aminobenzamide (3-AB) and DPQ]. The fluorescence of caspase-3 remained the same regardless of the duration of IH, and Western blots did not detect activation of caspase-3. However, IH increased the ratio of apoptosis-inducing factor (AIF) translocation to the nucleus, while PARP inhibitors (3-AB) reduced this ratio.</p> <p>Results</p> <p>According to our findings, IH increased oxidative stress and subsequently leading to cell death. This effect was at least partially mediated by PARP activation, resulting in ATP depletion, calpain activation leading to AIF translocation to the nucleus.</p> <p>Conclusions</p> <p>We suggest that IH induces cell death in rat primary cerebellar granule cells by stimulating oxidative stress PARP-mediated calpain and AIF activation.</p

Evodiamine Induces Transient Receptor Potential Vanilloid-1-Mediated Protective Autophagy in U87-MG Astrocytes

Cerebral ischemia is a leading cause of mortality and morbidity worldwide, which results in cognitive and motor dysfunction, neurodegenerative diseases, and death. Evodiamine (Evo) is extracted from Evodia rutaecarpa Bentham, a plant widely used in Chinese herbal medicine, which possesses variable biological abilities, such as anticancer, anti-inflammation, antiobesity, anti-Alzheimer’s disease, antimetastatic, antianoxic, and antinociceptive functions. But the effect of Evo on ischemic stroke is unclear. Increasing data suggest that activation of autophagy, an adaptive response to environmental stresses, could protect neurons from ischemia-induced cell death. In this study, we found that Evo induced autophagy in U87-MG astrocytes. A scavenger of extracellular calcium and an antagonist of transient receptor potential vanilloid-1 (TRPV-1) decreased the percentage of autophagy accompanied by an increase in apoptosis, suggesting that Evo may induce calcium-mediated protective autophagy resulting from an influx of extracellular calcium. The same phenomena were also confirmed by a small interfering RNA technique to knock down the expression of TRPV1. Finally, Evo-induced c-Jun N-terminal kinases (JNK) activation was reduced by a TRPV1 antagonist, indicating that Evo-induced autophagy may occur through a calcium/c-Jun N-terminal kinase (JNK) pathway. Collectively, Evo induced an influx of extracellular calcium, which led to JNK-mediated protective autophagy, and this provides a new option for ischemic stroke treatment

Continuous epidermal growth factor receptor-tyrosine kinase inhibitor administration in primary lung adenocarcinoma patients harboring favorable mutations with controlled target lung tumors dose not hinder survival benefit despite small new lesions

AbstractBackgroundIn this study, we investigated the efficacy of continuous epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) administration in lung adenocarcinoma patients harboring favorable mutations regarding the progressive disease (PD) status with appearance of indolent new lesions.MethodsFrom June 2010 to October 2012, 102 patients with lung adenocarcinoma, harboring favorable EGFR mutations and treated with EGFR-TKI were analyzed. Definite new lesions were detected during EGFR-TKI therapy, even though the primary target tumors were controlled.ResultsOf the 102 patients, 57 continued and 45 discontinued EGFR-TKI therapy. The median overall survival was 529 days for the discontinuation group and 791 days for the continuation group (p = 0.0197). Median survival time after the discontinuation of EGFR-TKI was 181 days and 115 days in the discontinuation and continuation groups, respectively (p = 0.1776), whereas median survival time after the appearance of indolent new lesions was 204 days and 262 days, respectively (p = 0.0237).ConclusionContinuous EGFR-TKI administration in favorable EGFR-mutative lung adenocarcinoma patients with controlled primary tumors did not hinder the survival benefit, despite the appearance of new lesions

The fate of steroid estrogens: Partitioning during wastewater treatment and onto river sediments

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2010 Springer Science+Business Media B.V.The partitioning of steroid estrogens in wastewater treatment and receiving waters is likely to influence their discharge to, and persistence in, the environment. This study investigated the partitioning behaviour of steroid estrogens in both laboratory and field studies. Partitioning onto activated sludge from laboratory-scale Husmann units was rapid with equilibrium achieved after 1 h. Sorption isotherms and Kd values decreased in the order 17α-ethinyl estradiol > 17α-estradiol > estrone > estriol without a sorption limit being achieved (1/n >1). Samples from a wastewater treatment works indicated no accumulation of steroid estrogens in solids from primary or secondary biological treatment, however, a range of steroid estrogens were identified in sediment samples from the River Thames. This would indicate that partitioning in the environment may play a role in the long-term fate of estrogens, with an indication that they will be recalcitrant in anaerobic conditions.EPSR

More than a piece of cake:Noun classifier processing in primary progressive aphasia

INTRODUCTION: Clinical understanding of primary progressive aphasia (PPA) has been primarily derived from Indo-European languages. Generalizing certain linguistic findings across languages is unfitting due to contrasting linguistic structures. While PPA patients showed noun classes impairments, Chinese languages lack noun classes. Instead, Chinese languages are classifier language, and how PPA patients manipulate classifiers is unknown. METHODS: We included 74 native Chinese speakers (22 controls, 52 PPA). For classifier production task, participants were asked to produce the classifiers of high-frequency items. In a classifier recognition task, participants were asked to choose the correct classifier. RESULTS: Both semantic variant (sv) PPA and logopenic variant (lv) PPA scored significantly lower in classifier production task. In classifier recognition task, lvPPA patients outperformed svPPA patients. The classifier production scores were correlated to cortical volume over left temporal and visual association cortices. DISCUSSION: This study highlights noun classifiers as linguistic markers to discriminate PPA syndromes in Chinese speakers. Highlights: Noun classifier processing varies in the different primary progressive aphasia (PPA) variants. Specifically, semantic variant PPA (svPPA) and logopenic variant PPA (lvPPA) patients showed significantly lower ability in producing specific classifiers. Compared to lvPPA, svPPA patients were less able to choose the accurate classifiers when presented with choices. In svPPA, classifier production score was positively correlated with gray matter volume over bilateral temporal and left visual association cortices in svPPA. Conversely, classifier production performance was correlated with volumetric changes over left ventral temporal and bilateral frontal regions in lvPPA. Comparable performance of mass and count classifier were noted in Chinese PPA patients, suggesting a common cognitive process between mass and count classifiers in Chinese languages.</p

A multilevel analysis of neighborhood and individual effects on individual smoking and drinking in Taiwan

<p>Abstract</p> <p>Background</p> <p>We assessed direct effects of neighborhood-level characteristics and interactive effects of neighborhood-level characteristics and individual socioeconomic position on adult smoking and drinking, after consideration of individual-level characteristics in Taiwan.</p> <p>Methods</p> <p>Data on individual sociodemographic characteristics, smoking, and drinking were obtained from Taiwan Social Change Survey conducted in 1990, 1995, and 2000. The overall response rate was 67%. A total of 5883 women and men aged over 20 living in 434 neighborhoods were interviewed. Participants' addresses were geocoded and linked with Taiwan census data for measuring neighborhood-level characteristics including neighborhood education, neighborhood concentration of elderly people, and neighborhood social disorganization. The data were analyzed with multilevel binomial regression models.</p> <p>Results</p> <p>Several interaction effects between neighborhood characteristics and individual socioeconomic status (SES) were found in multilevel analyses. Our results indicated that different neighborhood characteristics led to different interaction patterns. For example, neighborhood education had a positive effect on smoking for low SES women, in contrast to a negative effect on smoking for high SES women. This result supports the hypothesis of "relative deprivation," suggesting that poor people living in affluent neighborhoods suffer from relative deprivation and relative standing. On the other hand, neighborhood social disorganization has positive effects on drinking for low SES individuals, but not for high SES individuals. These interactive effects support the hypothesis of the double jeopardy theory, suggesting that living in neighborhoods with high social disorganization will intensify the effects of individual low SES.</p> <p>Conclusion</p> <p>The findings of this study show new evidence for the effects of neighborhood characteristics on individual smoking and drinking in Taiwan, suggesting that more studies are needed to understand neighborhood effects in Asian societies.</p

Predicting Hospital-Acquired Infections by Scoring System with Simple Parameters

BACKGROUND: Hospital-acquired infections (HAI) are associated with increased attributable morbidity, mortality, prolonged hospitalization, and economic costs. A simple, reliable prediction model for HAI has great clinical relevance. The objective of this study is to develop a scoring system to predict HAI that was derived from Logistic Regression (LR) and validated by Artificial Neural Networks (ANN) simultaneously. METHODOLOGY/PRINCIPAL FINDINGS: A total of 476 patients from all the 806 HAI inpatients were included for the study between 2004 and 2005. A sample of 1,376 non-HAI inpatients was randomly drawn from all the admitted patients in the same period of time as the control group. External validation of 2,500 patients was abstracted from another academic teaching center. Sixteen variables were extracted from the Electronic Health Records (EHR) and fed into ANN and LR models. With stepwise selection, the following seven variables were identified by LR models as statistically significant: Foley catheterization, central venous catheterization, arterial line, nasogastric tube, hemodialysis, stress ulcer prophylaxes and systemic glucocorticosteroids. Both ANN and LR models displayed excellent discrimination (area under the receiver operating characteristic curve [AUC]: 0.964 versus 0.969, p = 0.507) to identify infection in internal validation. During external validation, high AUC was obtained from both models (AUC: 0.850 versus 0.870, p = 0.447). The scoring system also performed extremely well in the internal (AUC: 0.965) and external (AUC: 0.871) validations. CONCLUSIONS: We developed a scoring system to predict HAI with simple parameters validated with ANN and LR models. Armed with this scoring system, infectious disease specialists can more efficiently identify patients at high risk for HAI during hospitalization. Further, using parameters either by observation of medical devices used or data obtained from EHR also provided good prediction outcome that can be utilized in different clinical settings

Improving model predictions for RNA interference activities that use support vector machine regression by combining and filtering features

<p>Abstract</p> <p>Background</p> <p>RNA interference (RNAi) is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathways. To dissect the factors that result in effective siRNA sequences a regression kernel Support Vector Machine (SVM) approach was used to quantitatively model RNA interference activities.</p> <p>Results</p> <p>Eight overall feature mapping methods were compared in their abilities to build SVM regression models that predict published siRNA activities. The primary factors in predictive SVM models are position specific nucleotide compositions. The secondary factors are position independent sequence motifs (<it>N</it>-grams) and guide strand to passenger strand sequence thermodynamics. Finally, the factors that are least contributory but are still predictive of efficacy are measures of intramolecular guide strand secondary structure and target strand secondary structure. Of these, the site of the 5' most base of the guide strand is the most informative.</p> <p>Conclusion</p> <p>The capacity of specific feature mapping methods and their ability to build predictive models of RNAi activity suggests a relative biological importance of these features. Some feature mapping methods are more informative in building predictive models and overall <it>t</it>-test filtering provides a method to remove some noisy features or make comparisons among datasets. Together, these features can yield predictive SVM regression models with increased predictive accuracy between predicted and observed activities both within datasets by cross validation, and between independently collected RNAi activity datasets. Feature filtering to remove features should be approached carefully in that it is possible to reduce feature set size without substantially reducing predictive models, but the features retained in the candidate models become increasingly distinct. Software to perform feature prediction and SVM training and testing on nucleic acid sequences can be found at the following site: <url>ftp://scitoolsftp.idtdna.com/SEQ2SVM/</url>.</p

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements