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The selective oxidation of methacrolein (MAL) to high value-added methacrylic acid (MAA) using green chemical technology is of high research value.

Background & Objective: To explore the influencing factors for cognitive impairment in patients with dorsolateral frontal lobe epilepsy (FLE) and the correlation between cognitive function and abnormal electroencephalograms. Methods: Eighty-two patients with dorsolateral FLE treated from April 2018 to April 2020 were selected. According to cognitive function test results, they were divided into a normal group (n=47) and an impairment group (n=35). Their general data were compared. The factors affecting cognitive function were assessed by univariate and multivariate logistic regression analyses. A nomogram prediction model was constructed for predicting cognitive impairment, and the predictive accuracy was assessed. The cognitive function and electroencephalogram results were compared. The correlation between abnormal electroencephalograms and cognitive function was analyzed. Results: Onset age ≥20 years old, educational years ≤12 years, course of disease ≥8 years, seizure frequency ≥once every 4 months, seizure duration ≥1.5 min and medication type were independent risk factors influencing the cognitive function of patients with dorsolateral FLE. The nomogram prediction model was highly accurate for predicting cognitive impairment. The levels of directional memory, associative learning memory, free recall of images, re-recognition of meaningless images, recall of character features, digital symbol substitution test, verbal fluency test, and backward digital span test of the impairment group were significantly lower than those of the normal group, and the number of patients with abnormal electroencephalograms was remarkably larger in the former group. Abnormal electroencephalogram had a significant negative correlation with cognitive impairment. Conclusion: Onset age, educational years, course of the disease, seizure frequency, seizure duration and medication type influence the cognitive function of patients with dorsolateral FLE. Abnormal electroencephalograms are closely correlated with cognitive function.

CircRNAs are an important class of noncoding RNAs characterized by a covalently closed circular structure. CircRNAs have been proven to impact numerous cellular processes, where they conduct specialized biological activities.

Background: Previous studies have shown that Donepezil has therapeutic effects on vascular dementia (VD). PI3K/AKT involves in oxidative stress injury and cell apoptosis. This study investigated whether Donepezil affects the neurological function and apoptosis of VD mice via PI3K/AKT signaling. Methods: Mice were assigned into Sham group, VD group, VD+Donepezil groupfollowed by analysis of mice learning and memory ability by Water maze test, p-AKT expression by Western blot, Caspase-3 activity, MDA content, SOD activity and GSH-Px in hippocampus. HT22 cells were cultured and separated into control group, I-R group and I-R+Donepezil group followed by measuring p-AKT level, ROS content and apoptosis. Results: Learning and memory abilities of VD group mice were significantly decreased, Caspase-3 activity and MDA in brain tissue were significantly increased, along with decreased SOD activity, GSH-Px and p-AKT level. Donepezil treatment can significantly improve VD mice learning and memory ability, reduce Caspase-3 activity and MDA in brain tissue, increase SOD activity, GSH-Px and p-AKT level. In vitro, I-R treatment significantly induced apoptosis of HT22 cells, increased ROS production and decreased p-AKT level. Donepezil treatment could up-regulate p-AKT in HT22 cells and reduce apoptosis and ROS production in HT22 cells. Conclusion: Donepezil improves the function of brain nerve in VD mice through regulating PI3K/AKT pathway, thus reducing oxidative stress injury and apoptosis of brain nerve cells.

Eukaryotic translation initiation factor 4B (eIF4B) plays an important role in mRNA translation initiation, cell survival and proliferation

Hebbian plasticity is a key mechanism for higher brain functions, such as learning and memory. This form of synaptic plasticity primarily involves the regulation of synaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) abundance and properties, whereby AMPARs are inserted into synapses during long-term potentiation (LTP) or removed during long-term depression (LTD). The molecular mechanisms underlying AMPAR trafficking remain elusive, however. Here we show that glutamate receptor interacting protein 1 (GRIP1), an AMPAR-binding protein shown to regulate the trafficking and synaptic targeting of AMPARs, is required for LTP and learning and memory. GRIP1 is recruited into synapses during LTP, and deletion of Grip1 in neurons blocks synaptic AMPAR accumulation induced by glycine-mediated depolarization. In addition, Grip1 knockout mice exhibit impaired hippocampal LTP, as well as deficits in learning and memory. Mechanistically, we find that phosphorylation of serine-880 of the GluA2 AMPAR subunit (GluA2-S880) is decreased while phosphorylation of tyrosine-876 on GluA2 (GluA2-Y876) is elevated during chemically induced LTP. This enhances the strength of the GRIP1–AMPAR association and, subsequently, the insertion of AMPARs into the postsynaptic membrane. Together, these results demonstrate an essential role of GRIP1 in regulating AMPAR trafficking during synaptic plasticity and learning and memory.

Hebbian plasticity, comprised of long-term potentiation (LTP) and depression (LTD), allows neurons to encode and respond to specific stimuli; while homeostatic synaptic scaling is a counterbalancing mechanism that enables the maintenance of stable neural circuits. Both types of synaptic plasticity involve the control of postsynaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor (AMPAR) abundance, which is modulated by AMPAR phosphorylation. To address the necessity of GluA2 phospho-Y876 in synaptic plasticity, we generated phospho-deficient GluA2 Y876F knock-in mice. We show that, while GluA2 phospho-Y876 is not necessary for Hebbian plasticity, it is essential for both in vivo and in vitro homeostatic upscaling. Bidirectional changes in GluA2 phospho-Y876 were observed during homeostatic scaling, with a decrease during downscaling and an increase during upscaling. GluA2 phospho-Y876 is necessary for synaptic accumulation of glutamate receptor interacting protein 1 (GRIP1), a crucial scaffold protein that delivers AMPARs to synapses, during upscaling. Furthermore, increased phosphorylation at GluA2 Y876 increases GluA2 binding to GRIP1. These results demonstrate that AMPAR trafficking during homeostatic upscaling can be gated by a single phosphorylation site on the GluA2 subunit.

Using Tapio elastic analysis, the differences and similarities of the energy consumption in the transportation sectors in China and the United States were compared. The results showed that the energy consumption of the transportation sectors in the two countries in 2000–2015 had a weak decoupling overall from economic growth in the long term. The decoupling indicator (0.61) in China was about ten times that (0.069) of the United States. Namely, the dependence of China’s transportation sector on energy consumption was far larger than that of the United States. Furthermore, using a logarithmic mean Divisia index (LMDI) model, the factors influencing the energy consumption in transportation sectors in China and the United States were analyzed from five perspectives. Based on this model, the reason why the two countries show decoupling difference was explained. Relevant policies implications for energy conservation and emission reduction in the transportation sector were discussed.

The 3-dimensional bin packing problem (3D-BPP) is not only fundamental in combinatorial optimization but also widely applied in real world logistics. In the modern logistics industry, the complexity of constraints, heterogeneity of cargoes and scale of orders are dramatically increased, leading to great challenges to devise packing plans up to standard. While the tree search algorithm is proved to be a successful paradigm to solve the 3D-BPP, it is too time-consuming to be applied in the aforementioned large-scale scenarios. To overcome the limitation, we propose a data-driven tree search algorithm (DDTS) to tackle the 3D-BPP. The solution space with complicated constraints is explored by a tree search algorithm, and a convolutional neural network trained with historical data guides pruning the tree so as to accelerate the search process. Computational experiments on real-world datasets show that our algorithm outperforms the state-of-the-art approach with a loading rate improvement of 2.47%. Moreover, the deep learning technique increases searching efficiency by 37.14% with only 0.04% performance loss. The algorithm has been deployed in Huawei Logistics System, which increases the loading rate by 3% and could reduce the logistics cost by millions of dollars per year. To the best of our knowledge, we are the first to embed pruning networks into tree search for the large-scale 3D-BPP.

In a multi-energy building energy system, the key to improve the energy efficiency and economy is coordinating the capacity configuration and operation scheduling of both electrical and thermal energy storage. Considering the electricity storage characteristics of electricity feedback arbitrage and degradation, as well as part load rate and ON/OFF time constraints for the combined operation of thermal energy storage and ground source heat pump, this paper presents a bi-level optimization method, including upper capacity optimization and lower operation optimization. The simulation results show that, compared to the system without energy storage, the proposed method significantly reduces total annualized cost, shifts large amounts of peak load and increases renewable energy self-consumption rate.

Elucidating how synaptic molecules such as AMPA receptors mediate neuronal communication and tracking their dynamic expression during behavior is crucial to understand cognition and disease, but current technological barriers preclude large-scale exploration of molecular dynamics in vivo. We have developed a suite of innovative methodologies that break through these barriers: a new knockin mouse line with fluorescently tagged endogenous AMPA receptors, two-photon imaging of hundreds of thousands of labeled synapses in behaving mice, and computer-vision-based automatic synapse detection. Using these tools, we can longitudinally track how the strength of synapses changes during behavior. We used this approach to generate an unprecedentedly detailed spatiotemporal map of synaptic plasticity underlying sensory experience. More generally, these tools can be used as an optical probe capable of measuring functional synapse strength across entire brain areas during any behavioral paradigm, describing complex system-wide changes with molecular precision.

Unlike conventional aluminosilicate zeolites synthesized in alkaline media, aluminophosphate molecular sieves (AlPOs) have always been prepared under acidic conditions in the past three decades; this has been regarded as one of essential factors for synthesis, except for the case of silica-substituted analogues (SAPOs). For the first time, we demonstrate herein a simple and generalized route for synthesizing various types of aluminophosphate molecular sieves in alkaline media. A series of aluminophosphate sieves and their analogues have been prepared with different quaternary ammonium cations as structure-directing agents in this manner. The above successes have extended the systematic media from acidic or neutral to alkaline for the preparation of a series of aluminophosphate molecular sieves, which possibly open an alternative route for the synthesis of aluminophosphate molecular sieves.

In human resource management, employee turnover problem is heavily concerned by managers since the leave of key employees can bring great loss to the company. However, most existing researches are employee-centered, which ignored the historical events of turnover behaviors or the longitudinal data of job records. In this paper, from an event-centered perspective, we design a hybrid model based on survival analysis and machine learning, and propose a turnover prediction algorithm named RFRSF, which combines survival analysis for censored data processing and ensemble learning for turnover behavior prediction. In addition, we take strategies to handle employees with multiple turnover records so as to construct survival data with censored records. We compare RFRSF with several baseline methods on a real dataset crawled from one of the biggest online professional social platforms of China. The results show that the survival analysis model can significantly benefit the employee turnover prediction performance.

This study discusses decoupling trends in world economic growth and CO2 emissions based on decoupling theories. The decoupling trends of economic growth and CO2 emissions in typical developed and developing countries in 1965–2015 are compared by using an OECD decoupling factor model, and Tapio elastic analysis (TEA) method, and the IGTX decoupling model. On this basis, this study evaluates correlations of these three decoupling models by employing the Spearman's rank correlation coefficient. The research indicates that, owing to the IGTX decoupling model being easily affected by other non-environmental factors, the shorter the research period of interest, the more easily the decoupling indices distort, while the accuracy of the TEA method is not limited by the length of the research period of interest. With respect to the overall decoupling trend, the research shows that: (1) strong decoupling is found in developed countries and slightly increases in the stabilisation thereof. The decoupling state in the United Kingdom and Germany is more stable than that of the United States and France. (2) Developing countries demonstrate weak decoupling that fluctuates significantly and lacks regularity. The stabilisation and optimisation of China in decoupling process are better than those of Brazil and India. Finally, according to research conclusions, relevant policies and suggestions are proposed in view of energy savings and emissions reduction in developing countries.

The development of economy in developing countries is expected to contribute mostly to the growth of world energy consumption. Using environment Impact-GDP-Technology (IGT) decoupling model, we carry out a comparative study on the decoupling trends of economic growth and energy consumption for both developed and developing countries in past five decades (1965–2015). The results indicate that the decoupling indices of developed countries are superior to that of developing countries. The specific performances are: (1) The decoupling indices of developed countries are shown to be stable and tend to approximate absolute decoupling; (2) The decoupling indices of developing countries fluctuate in the relative decoupling interval. On this basis, this research employs grey relational analysis (GRA) to explore the reasons resulting in the difference of decoupling indices from the perspective of technical progress, industrial structure and economic growth pattern. The findings show that: in developed countries, technical progress factor exerts greatest influence on decoupling indices, followed by industrial structure and economic growth pattern; in developing countries, industrial structure and economic growth pattern have greater impact on decoupling indices than technical progress. Based on research conclusion, this research offers developing countries relevant policy suggestions for energy saving and emission reduction in the future.

Neuronal information is majorly encoded chemically at synapses and the elementary unit of synaptic transmission is the contents of neurotransmitter released from single vesicle. However, the contents of quantal neurotransmitter have never been precisely estimated at synapses, which largely prevent our understanding the nature of quantal neurotransmitter release and its impact on neuronal information processing. In order to break through the technical bottleneck of precisely counting quantal neurotransmitter molecules, we developed a new approach in combination of electrophysiology and electrochemistry to measure intact quantal content of single vesicles. An etched submicro-carbon fiber electrode for electrochemical detection was designed to be enclosed in an electrophysiologically used glass pipette. The glass pipette allowed the electrochemical electrode to access the release site, and amperometric recordings were made within the enclosed space at the electrophysiological loose-patch mode. Our study showed that the intact quantal release could be successfully detected at the dopaminergic varicosities by this loose-patch amperometric measurement in real time with negligible leakage.

Vesicle recycling is pivotal for maintaining reliable synaptic signaling, but its basic properties remain poorly understood. Here, we developed an approach to quantitatively analyze the kinetics of vesicle recycling with exquisite signal and temporal resolution at the calyx of Held synapse. The combination of this electrophysiological approach with electron microscopy revealed that ∼80% of vesicles (∼270,000 out of ∼330,000) in the nerve terminal are involved in recycling. Under sustained stimulation, recycled vesicles start to be reused in tens of seconds when ∼47% of the preserved vesicles in the recycling pool (RP) are depleted. The heterogeneity of vesicle recycling as well as two kinetic components of RP depletion revealed the existence of a replenishable pool of vesicles before the priming stage and led to a realistic kinetic model that assesses the size of the subpools of the RP. Thus, our study quantified the kinetics of vesicle recycling and kinetically dissected the whole vesicle pool in the calyceal terminal into the readily releasable pool (∼0.6%), the readily priming pool (∼46%), the premature pool (∼33%), and the resting pool (∼20%).

Abnormalities in parvalbumin (PV)-expressing interneurons cause neurodevelopmental disorders such as epilepsy, autism, and schizophrenia. Unlike other types of neurons that can be efficiently differentiated from pluripotent stem cells, PV neurons were minimally generated using a conventional differentiation strategy. In this study we developed an adenovirus-based transdifferentiation strategy that incorporates an additional chemical compound for the efficient generation of induced PV (iPV) neurons. The chemical compound forskolin combined with Ascl1 induced ∼80% of mouse fibroblasts to iPV neurons. The iPV neurons generated by this procedure matured 5–7 days post infection and were characterized by electrophysiological properties and known neuronal markers, such as PV and GABA. Our studies, therefore, identified an efficient approach for generating PV neurons.

A performance study of a water ramjet engine is described. The engine is powered by the reaction of a magnesium-based propellant and ingested water. In this study, a solid propellant, which consisted of a large percentage of magnesium, a binder and a small amount of oxidant, was used as a hydro reactive fuel. Cold water was injected into the combustion chamber as a main oxidant. A scaled-down experimental engine was tested in a direct-connect ground testing system to characterize the factors influencing the engine performance. The results show that the increasing of total water/fuel ratio, an addition of secondary water intake along the combustion chamber, a larger magnesium content in the solid propellant, a smaller primary water injection angle towards the coming main flow, and a higher primary injection pressure were all able to promote the engine performance. The maximum engine performance was obtained in test 08, and with all tests, an appropriate set of parameters and conditions for the optimum engine performance were determined

Regulation of AMPA-type glutamate receptor (AMPAR) number at synapses is a major mechanism for controlling synaptic strength during homeostatic scaling in response to global changes in neural activity. We show that the secreted guidance cue semaphorin 3F (Sema3F) and its neuropilin-2 (Npn-2)/plexinA3 (PlexA3) holoreceptor mediate homeostatic plasticity in cortical neurons. Sema3F-Npn-2/PlexA3 signaling is essential for cell surface AMPAR homeostatic downscaling in response to an increase in neuronal activity, Npn-2 associates with AMPARs, and Sema3F regulates this interaction. Therefore, Sema3F-Npn-2/PlexA3 signaling controls both synapse development and synaptic plasticity.

The aim of the present study was to investigate the expression of estrogen receptor β (ERβ) in triple-negative and triple-positive breast cancer patients, and evaluate its utility as a prognostic factor. Between January 2000 and December 2010, primary tumor tissue samples were collected from 234 subjects, including 107 triple-negative and 127 triple-positive breast cancer patients. The samples were embedded in paraffin and immunohistochemical staining was conducted to determine the expression levels of ERβ. The Kaplan-Meier method was used to analyze patient survival rates. ERβ expression was observed in 38/107 patients (35.5%) with triple-negative breast cancer and 63/127 patients (49.6%) with triple-positive breast cancer. The ERβ expression rate was significantly decreased in the patients with triple-negative breast cancer, as compared with those with triple-positive breast cancer (P=0.03). Analysis of the survival rates indicated that patients with triple-negative breast cancer and positive ERβ expression exhibited poor disease progression-free survival (DFS) compared with those with negative ERβ expression (P=0.021). However, no statistically significant difference was observed in the DFS between the triple-positive breast cancer patients with positive and negative ERβ expression. Therefore, the expression of ERβ varies between triple-negative and triple-positive breast cancer patients. In addition, positive expression of ERβ indicates a poor prognosis in triple-negative breast cancer patients; however, this is not the case for triple-positive breast cancer patients.