Failed Neuroprotection of Combined Inhibition of L-Type and ASIC1a Calcium Channels with Nimodipine and Amiloride

Effective pharmacological neuroprotection is one of the most desired aims in modern medicine. We postulated that a combination of two clinically used drugs—nimodipine (L-Type voltage-gated calcium channel blocker) and amiloride (acid-sensing ion channel inhibitor)—might act synergistically in an experimental model of ischaemia, targeting the intracellular rise in calcium as a pathway in neuronal cell death. We used organotypic hippocampal slices of mice pups and a well-established regimen of oxygen-glucose deprivation (OGD) to assess a possible neuroprotective effect. Neither nimodipine (at 10 or 20 µM) alone or in combination with amiloride (at 100 µM) showed any amelioration. Dissolved at 2.0 Vol.% dimethyl-sulfoxide (DMSO), the combination of both components even increased cell damage (p = 0.0001), an effect not observed with amiloride alone. We conclude that neither amiloride nor nimodipine do offer neuroprotection in an in vitro ischaemia model. On a technical note, the use of DMSO should be carefully evaluated in neuroprotective experiments, since it possibly alters cell damage.     

亲爱的景观,你非得是绿色的么

景观作为新地区开发的一种视觉和审美的品质,受到人们尤其是设计师专业人士的青睐,指出把景观等同于植物"绿色"是一种肤浅的观念。通过对智利圣地亚哥等地城市与建筑景观建设经验的追述,提出人类活动、自然元素、文化生态系统共同创造的空间动态平衡,才是"景观"的真谛。     

Comprehensive analysis of the substituent distribution in the glucosyl units and along the polymer chain of hydroxyethylmethyl celluloses and statistical evaluation

Hydroxyethylmethyl celluloses (HEMC, DS(Me) 1.46-1.66, DS(HE) = 0.14-0.17) have been analyzed with respect to their methyl and hydroxyethyl pattern in the glucosyl units and along the polymer chain. Methyl groups were located by GLC/MS after direct hydrolysis, reduction, and acetylation, and the distribution of hydroxyethyl residues in the glucosyl units could be determined with enhanced sensitivity after permethylation to unify a certain HE pattern occurring in combination with various methyl patterns in a single peak. To get insight into the distribution of Me and HE along the cellulose chain, a method was developed which overcomes the strong discrimination of relative ion intensities caused by hydroxyalkyl groups and enables quantitative determination of the oligomer composition after random degradation for the first time. This comprises perdeuteriomethylation; partial acid hydrolysis; reductive amination with propylamine; and, finally, permethylation to yield completely O- and N-alkylated, permanently charged oligosaccharides. Although the methyl pattern can be determined by electrospray ionization ion-trap mass spectrometry (ESI-IT-MS) and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), as well, only MALDI-TOF-MS produced representative data for a quantitative evaluation of the HE pattern. Distribution of HE groups matches with a random distribution calculated from the monomer composition, whereas the methyl pattern was heterogeneous to a different extent.     

Case‐based decision support for fault diagnosis: Do salient ratings discourage situation analysis?

In the processing industry, frequent faults call for assistance in diagnosis, and case‐based reasoning (CBR) can provide solutions applied by other operators in the past. This study investigated whether salient case ratings promote an uncritical acceptance of solutions. In 2 experiments, subjects diagnosed faults with a simulated CBR system, and ratings were presented in graphical or verbal format. In most trials, the case with the highest rating provided the correct solution, while in catch‐trials, it did not. Graphical ratings were hypothesized to speed up solutions but discourage cross‐checking and lead to errors in catch‐trials. These hypotheses were not confirmed, even though Experiment 2 maximized the incentive of relying on case ratings. While graphical ratings led subjects to start with the most highly rated case, they did not impair situation analysis and accuracy. The results suggest that during fault diagnosis people are not easily misled into overtrusting a CBR system.     

Process industries versus discrete processing: how system characteristics affect operator tasks

Cognition, Technology & Work - Despite an increasing level of automation, human operators still play a central role in industrial production. They need to monitor and adjust plant operations,...     

Data or interpretations: Impacts of information presentation strategies on diagnostic processes

Industrial fault diagnosis can be supported by assistance systems that infer fault causes from sensor data. The present study asked what information these algorithms should make available to operators. In a computer‐based experiment about fault diagnosis in a packaging machine, three information presentation strategies were compared regarding their impacts on information sampling, performance, and knowledge acquisition: Providing only sensor data, sensor data along with three possible interpretations, or only the most likely interpretation. Before submitting a diagnosis, participants could sample process parameters, one of which indicated the fault cause. We hypothesized that providing only sensor data would lead to more parameter checking and slower solutions than interpretations. While providing only one interpretation was expected to enable efficient performance for correct interpretations, it should lead to either of two types of performance costs for incorrect interpretations: Errors if participants refrain from checking parameters, or slowdowns in performance if they keep on checking. The results confirmed that participants with only sensor data performed inefficiently. Participants with only one interpretation thoroughly checked parameters but still were fastest when the interpretation was correct, while when it was incorrect they were three times slower than participants with only sensor data. Participants with three interpretations (one of which was always correct) performed almost as efficiently as those with only one correct interpretation. The results indicate that highly preprocessed information leads to efficient performance when it is correct but prevents learning about fault causes. Overall, providing several possible interpretations seemed to be the best strategy.     

Improved automatic English proficiency rating of unconstrained speech with multiple corpora

The performance of machine learning classifiers in automatically scoring the English proficiency of unconstrained speech has been explored. Suprasegmental measures were computed by software, which identifies the basic elements of Brazil’s model in human discourse. This paper explores machine learning training with multiple corpora to improve two of those algorithms: prominent syllable detection and tone choice classification. The results show that machine learning training with the Boston University Radio News Corpus can improve automatic English proficiency scoring of unconstrained speech from a Pearson’s correlation of 0.677–0.718. This correlation is higher than any other existing computer programs for automatically scoring the proficiency of unconstrained speech and is approaching that of human raters in terms of inter-rater reliability.