Hippocampal Theta Activity During Stimulus Discrimination Task

The configural association theory and conflict resolution model both propose that hippocampal function plays role in the solving a negative patterning task but not simple discrimination task. Some hippocampal lesion study showed that inactivity of rats’ hippocampal CA1 area induced impairment of performance of a negative patterning task. Other previous studies, however, showed that the lesion did not affect the performance of the task. Thus, it did not reveal whether hippocampal function was important for solving the negative patterning task. Our recent research using an electrophysiological approach showed that the hippocampal theta power decreased with a compound stimulus of a negative patterning task, and that the hippocampal theta power was decreased by a compound stimulus of a feature negative task. These results indicate that a decrease in hippocampal theta activity is elicited by behavioral inhibition for conflict stimuli with overlapping elements. This finding strongly supports the conflict resolution model and suggests a hippocampal role in learning behavioral inhibition for conflict stimuli during nonspatial stimulus discrimination tasks

Water transport across the membrane of a direct toluene electro-hydrogenation electrolyzer: Experiments and modelling

Toluene/methylcyclohexane is a promising liquid organic hydride for hydrogen storage and transport under ambient conditions. Direct toluene electro-hydrogenation electrolyzers, utilizing proton exchange membrane technology, offer benefits in reducing the reversible decomposition voltage and eliminating theoretical heat losses associated with conventional hydrogenation methods. Nevertheless, water transport across the membrane can inhibit the supply of toluene to reaction sites at the cathode. This study investigates water transport across the Nafion™ 117 membrane of an in-house electrolyzer cell, employing sulfuric acid and toluene solutions as the anode and cathode reactant, respectively, and operating at current densities from 0.1 to 0.8 A/cm2. The experiments show that the cathode toluene concentration has a negligible effect on drag water, while water flux increases with electric current and decreases with higher anode sulfuric acid concentrations. The modelling approach assumes electro-osmosis and diffusion mechanisms govern water transport. Simulations predict a linear decrease in the electro-osmotic drag coefficient from 2.3 to 1.6 as the sulfuric acid concentration rises from 0.1 to 1.5 mol/L, while the back diffusion flux increases linearly up to 2 mg/(min·cm2). These findings closely align with experimental data and previous literature, despite the high complexity of water transport in polymer electrolyte membranes.Funding for open access charge: Universidad de Málaga / CBU

Drug effectiveness for COVID-19 inpatients inferred from Japanese medical claim data using propensity score matching [version 2; peer review: 2 approved]

Background Earlier studies and clinical trials of Coronavirus 2019 (COVID-19) showed that drugs such as antiviral drugs, antibody cocktails, and steroids and anti-inflammatory drugs can prevent severe outcomes and death. Methods Observational data in Japan assess drug effectiveness against COVID-19. We applied the average treatment effect model, particularly propensity scoring, which can treat the choice of administered drug as if administration were randomly assigned to inpatients. Data of the Medical Information Analysis Databank, operated by National Hospital Organization in Japan, were used. The outcome was defined as mortality. Subjects were all inpatients, inpatients with oxygen administration, and inpatients using respiratory ventilation, classified by three age classes: all ages, 65 years old or older, and younger than 65 years old. Information about demographic characteristics, underlying disease, administered drug, the proportions of Alpha, Beta and Omicron variant strains, and vaccine coverage were used as explanatory variables for logistic regression. Results Estimated results indicated that only one antibody cocktail (sotrovimab, casirivimab and imdevimab) was associated with raising the probability of survival consistently and significantly. By contrast, other drugs, an antiviral drug (remdesivir), a steroid (dexamethasone), and an anti-inflammatory drug (baricitinib and tocilizumab) were related to reduce the probability of survival. However, propensity score matching method might engender biased results because of a lack of data such as detailed information related to intervention and potential confounders. Therefore, the effectiveness of some drugs might not be evaluated properly in this study. Conclusions Results indicate high likelihood that antibody cocktails were consistently associated with high probability of survival, although low likelihood was found for other drugs for older patients with mild to severe severity and all age patients with moderate severity. Further study is necessary in light of the lack of available data

Recognition of Brain Wave Related to the Episode Memory by Deep Learning Methods

Hippocampus makes an important role of memory in the brain. In this chapter, a study of brain wave recognition using deep learning methods is introduced. The purpose of the study is to match the ripple-firings of the hippocampal activity to the episodic memories. In fact, brain spike signals of rats (300–10 kHz) were recorded and machine learning methods such as Convolutional Neural Networks (CNN), Support Vector Machine (SVM), a deep learning model VGG16, and combination models composed by CNN with SVM and VGG16 with SVM were adopted to be classifiers of the brain wave signals. Four kinds of episodic memories, that is, a male rat contacted with a female/male rat, contacted with a novel object, and an experience of restrain stress, were detected corresponding to the ripple waves of Multiple-Unit Activities (MUAs) of hippocampal CA1 neurons in male rats in the experiments. The experiment results showed the possibility of matching of ripple-like firing patterns of hippocampus to episodic memory activities of rats, and it suggests disorders of memory function may be found by the analysis of brain waves

Study on Morphological Properties and Mass Transport Parameters of ORR in Recast Ion- exchange Polymer Electrolyte Membranes

ABSTRACT We have investigated the effect of the recast temperature, i.e., heat treatment of a polymer electrolyte, on the diffusion coefficient and solubility of oxygen in the electrolyte and also on the morphological properties of recast ion-exchange membranes for improving the cathode activity in PEFCs. The recast membranes were prepared at different recast temperatures from Nafion ® and Aciplex ® solutions. Based on the chronoamperometric measurements, it was found that the diffusion coefficient and solubility of oxygen were deeply affected by the recast temperature. The diffusion coefficient increased with the decreasing recast temperature while the solubility had the opposite tendency. The water uptakes and ionic cluster size also varied with the recast temperature. Based on the X-ray measurements, it is considered that the differences in the mass transport parameters, the cluster sizes and water uptakes are due to the growth of clusters and crystallinity in the electrolyte

Plasma Free Amino Acid Profiling of Five Types of Cancer Patients and Its Application for Early Detection

BACKGROUND: Recently, rapid advances have been made in metabolomics-based, easy-to-use early cancer detection methods using blood samples. Among metabolites, profiling of plasma free amino acids (PFAAs) is a promising approach because PFAAs link all organ systems and have important roles in metabolism. Furthermore, PFAA profiles are known to be influenced by specific diseases, including cancers. Therefore, the purpose of the present study was to determine the characteristics of the PFAA profiles in cancer patients and the possibility of using this information for early detection. METHODS AND FINDINGS: Plasma samples were collected from approximately 200 patients from multiple institutes, each diagnosed with one of the following five types of cancer: lung, gastric, colorectal, breast, or prostate cancer. Patients were compared to gender- and age- matched controls also used in this study. The PFAA levels were measured using high-performance liquid chromatography (HPLC)-electrospray ionization (ESI)-mass spectrometry (MS). Univariate analysis revealed significant differences in the PFAA profiles between the controls and the patients with any of the five types of cancer listed above, even those with asymptomatic early-stage disease. Furthermore, multivariate analysis clearly discriminated the cancer patients from the controls in terms of the area under the receiver-operator characteristics curve (AUC of ROC >0.75 for each cancer), regardless of cancer stage. Because this study was designed as case-control study, further investigations, including model construction and validation using cohorts with larger sample sizes, are necessary to determine the usefulness of PFAA profiling. CONCLUSIONS: These findings suggest that PFAA profiling has great potential for improving cancer screening and diagnosis and understanding disease pathogenesis. PFAA profiles can also be used to determine various disease diagnoses from a single blood sample, which involves a relatively simple plasma assay and imposes a lower physical burden on subjects when compared to existing screening methods