Intra- and Intersubunit Cooperativity in Activation of BK Channels by Ca2+

The activation of BK channels by Ca2+ is highly cooperative, with small changes in intracellular Ca2+ concentration having large effects on open probability (Po). Here we examine the mechanism of cooperative activation of BK channels by Ca2+. Each of the four subunits of BK channels has a large intracellular COOH terminus with two different high-affinity Ca2+ sensors: an RCK1 sensor (D362/D367) located on the RCK1 (regulator of conductance of K+) domain and a Ca-bowl sensor located on or after the RCK2 domain. To determine interactions among these Ca2+ sensors, we examine channels with eight different configurations of functional high-affinity Ca2+ sensors on the four subunits. We find that the RCK1 sensor and Ca bowl contribute about equally to Ca2+ activation of the channel when there is only one high-affinity Ca2+ sensor per subunit. We also find that an RCK1 sensor and a Ca bowl on the same subunit are much more effective in increasing Po than when they are on different subunits, indicating positive intrasubunit cooperativity. If it is assumed that BK channels have a gating ring similar to MthK channels with alternating RCK1 and RCK2 domains and that the Ca2+ sensors act at the flexible (rather than fixed) interfaces between RCK domains, then a comparison of the distribution of Ca2+ sensors with the observed responses suggest that the interface between RCK1 and RCK2 domains on the same subunit is flexible. On this basis, intrasubunit cooperativity arises because two high-affinity Ca2+ sensors acting across a flexible interface are more effective in opening the channel than when acting at separate interfaces. An allosteric model incorporating intrasubunit cooperativity nested within intersubunit cooperativity could approximate the Po vs. Ca2+ response for eight possible subunit configurations of the high-affinity Ca2+ sensors as well as for three additional configurations from a previous study

CasGCN: Predicting future cascade growth based on information diffusion graph

Sudden bursts of information cascades can lead to unexpected consequences such as extreme opinions, changes in fashion trends, and uncontrollable spread of rumors. It has become an important problem on how to effectively predict a cascade' size in the future, especially for large-scale cascades on social media platforms such as Twitter and Weibo. However, existing methods are insufficient in dealing with this challenging prediction problem. Conventional methods heavily rely on either hand crafted features or unrealistic assumptions. End-to-end deep learning models, such as recurrent neural networks, are not suitable to work with graphical inputs directly and cannot handle structural information that is embedded in the cascade graphs. In this paper, we propose a novel deep learning architecture for cascade growth prediction, called CasGCN, which employs the graph convolutional network to extract structural features from a graphical input, followed by the application of the attention mechanism on both the extracted features and the temporal information before conducting cascade size prediction. We conduct experiments on two real-world cascade growth prediction scenarios (i.e., retweet popularity on Sina Weibo and academic paper citations on DBLP), with the experimental results showing that CasGCN enjoys a superior performance over several baseline methods, particularly when the cascades are of large scale

Similarities and differences of functional connectivity in drug-naïve, first-episode adolescent and young adult with major depressive disorder and schizophrenia

Major depressive disorder (MDD) and schizophrenia (SZ) are considered two distinct psychiatric disorders. Yet, they have considerable overlap in symptomatology and clinical features, particularly in the initial phases of illness. The amygdala and prefrontal cortex (PFC) appear to have critical roles in these disorders; however, abnormalities appear to manifest differently. In our study forty-nine drug-naïve, first-episode MDD, 45 drug-naïve, first-episode SZ, and 50 healthy control (HC) participants from 13 to 30 years old underwent resting-state functional magnetic resonance imaging. Functional connectivity (FC) between the amygdala and PFC was compared among the three groups. Significant differences in FC were observed between the amygdala and ventral PFC (VPFC), dorsolateral PFC (DLPFC), and dorsal anterior cingulated cortex (dACC) among the three groups. Further analyses demonstrated that MDD showed decreased amygdala-VPFC FC and SZ had reductions in amygdala-dACC FC. Both the diagnostic groups had significantly decreased amygdala-DLPFC FC. These indicate abnormalities in amygdala-PFC FC and further support the importance of the interaction between the amygdala and PFC in adolescents and young adults with these disorders. Additionally, the alterations in amygdala-PFC FC may underlie the initial similarities observed between MDD and SZ and suggest potential markers of differentiation between the disorders at first onset

Cultivation of microalgae in food processing effluent for pollution attenuation and astaxanthin production: a review of technological innovation and downstream application

Valorization of food processing effluent (FPE) by microalgae cultivation for astaxanthin production is regarded as a potential strategy to solve the environmental pollution of food processing industry and promote the development of eco-friendly agriculture. In this review paper, microalgal species which have the potential to be employed for astaxanthin in FPE were identified. Additionally, in terms of CO2 emission, the performances of microalgae cultivation and traditional methods for FPE remediation were compared. Thirdly, an in-depth discussion of some innovative technologies, which may be employed to lower the total cost, improve the nutrient profile of FPE, and enhance the astaxanthin synthesis, was provided. Finally, specific effects of dietary supplementation of algal astaxanthin on the growth rate, immune response, and pigmentation of animals were discussed. Based on the discussion of this work, the cultivation of microalgae in FPE for astaxanthin production is a value-adding process which can bring environmental benefits and ecological benefits to the food processing industry and agriculture. Particularly, technological innovations in recent years are promoting the shift of this new idea from academic research to practical application. In the coming future, with the reduction of the total cost of algal astaxanthin, policy support from the governments, and further improvement of the innovative technologies, the concept of growing microalgae in FPE for astaxanthin will be more applicable in the industry

Unified Classification of Nominal Classifiers and Formalization of Classifier-noun Phrases

One of the main problems that affect the quality of machine translation is how to express the knowledge of language in precision. Based on the theory of Semantic Element (SE) in Unified Linguistics, a new unified classification of English and Chinese nominal classifiers is proposed from the perspective of C-E and E-C translation. Different Semantic Element Representations (SER) of classifiers in English and Chinese have the same semantic type of classifiers. The English and Chinese noun-classifier phrases are formalized into English and Chinese SER respectively. Key words: Chinese Classifier-Noun Phrase; Classification of Nominal Classifiers; Formalization; SE; SE

System Reliability Allocation Based on Bayesian Network

Abstract: In this paper, system reliability allocation using BN(Bayesian Network) was researched. The relationship between system failure and component failure can be expressed by probability importance degree, structure importance degree and key importance degree in FTA (Fault Tree Analysis). BN supplies a new method to reflect the importance of components in system. That is the conditional failure probability which points out the most possible reason of system failure and is more reasonable and reliable. Some examples are given to allocate the reliability of systems by BN and the results show that BN is useful and effective

Reliability Modeling and Assessment of Component with Multiple Weak Sites under Complex Loading

A component with multiple weak sites is widely used in practical engineering and the existence of multiple weak sites can significantly decrease the component reliability. On the other hand, only a few components bear static loading and most components bear dynamic loading. In this paper, a reliability model of isomorphic component with multiple weak sites is built based on an order statistics model and the influences of strength decentrality and loading decentrality on isomorphic component with multiple weak sites are discussed. Furthermore the influence of loading times is studied in detail. The results show that unlike a component with only one weak site, not only does the failure of a component with multiple weak sites have a relationship with the safety margin, but there also exist relationships with the number of weak sites, the loading roughness, and loading times. The work in this paper is of some guiding significance in reliability design and assessment of a component with multiple weak sites under complex loading

Slo1 Tail Domains, but Not the Ca2+ Bowl, Are Required for the β1 Subunit to Increase the Apparent Ca2+ Sensitivity of BK Channels

Functional large-conductance Ca2+- and voltage-activated K+ (BK) channels can be assembled from four α subunits (Slo1) alone, or together with four auxiliary β1 subunits to greatly increase the apparent Ca2+ sensitivity of the channel. We examined the structural features involved in this modulation with two types of experiments. In the first, the tail domain of the α subunit, which includes the RCK2 (regulator of K+ conductance) domain and Ca2+ bowl, was replaced with the tail domain of Slo3, a BK-related channel that lacks both a Ca2+ bowl and high affinity Ca2+ sensitivity. In the second, the Ca2+ bowl was disrupted by mutations that greatly reduce the apparent Ca2+ sensitivity. We found that the β1 subunit increased the apparent Ca2+ sensitivity of Slo1 channels, independently of whether the α subunits were expressed as separate cores (S0-S8) and tails (S9-S10) or full length, and this increase was still observed after the Ca2+ bowl was mutated. In contrast, β1 subunits no longer increased Ca2+ sensitivity when Slo1 tails were replaced by Slo3 tails. The β1 subunits were still functionally coupled to channels with Slo3 tails, as DHS-I and 17 β-estradiol activated these channels in the presence of β1 subunits, but not in their absence. These findings indicate that the increase in apparent Ca2+ sensitivity induced by the β1 subunit does not require either the Ca2+ bowl or the linker between the RCK1 and RCK2 domains, and that Slo3 tails cannot substitute for Slo1 tails. The β1 subunit also induced a decrease in voltage sensitivity that occurred with either Slo1 or Slo3 tails. In contrast, the β1 subunit–induced increase in apparent Ca2+ sensitivity required Slo1 tails. This suggests that the allosteric activation pathways for these two types of actions of the β1 subunit may be different