Therapeutic potential of N-methyl-D-aspartate receptor modulators in psychiatry.

N-methyl-D-aspartate (NMDA) receptors mediate a slow component of excitatory synaptic transmission, are widely distributed throughout the central nervous system, and regulate synaptic plasticity. NMDA receptor modulators have long been considered as potential treatments for psychiatric disorders including depression and schizophrenia, neurodevelopmental disorders such as Rett Syndrome, and neurodegenerative conditions such as Alzheimer's disease. New interest in NMDA receptors as therapeutic targets has been spurred by the findings that certain inhibitors of NMDA receptors produce surprisingly rapid and robust antidepressant activity by a novel mechanism, the induction of changes in the brain that well outlast the presence of drug in the body. These findings are driving research into an entirely new paradigm for using NMDA receptor antagonists in a host of related conditions. At the same time positive allosteric modulators of NMDA receptors are being pursued for enhancing synaptic function in diseases that feature NMDA receptor hypofunction. While there is great promise, developing the therapeutic potential of NMDA receptor modulators must also navigate the potential significant risks posed by the use of such agents. We review here the emerging pharmacology of agents that target different NMDA receptor subtypes, offering new avenues for capturing the therapeutic potential of targeting this important receptor class.

The relationship between hotel star rating and website information quality based on visual presentation.

The hotel industry is essential for tourism. With the rapid expansion of the internet, consumers only search for their desired keywords on the website when they trying to find a hotel to stay, causing the relevant hotel information would appear. To quickly respond to the changing market and consumer habits, each hotel must focus on its website information and information quality. This study proposes a novel methodology that uses rough set theory (RST), principal component analysis, t-Distributed Stochastic Neighbor Embedding (t-SNE), and attribute performance visualization to explore the relationship between hotel star ratings and hotel website information quality. The collected data are based on the star-rated hotels of the Taiwanstay website, and the checklists of hotel website services are used to obtain the relevant attributes data. The results show that there are significant differences in information quality between hotels below two stars and those above four stars. The information quality provided by the higher star hotels was more detailed than that offered by low-star hotels. Based on the attribute performance matrix, the one-star and two-star hotels have advantage attributes in their landscape, reply time, restaurant information, social media, and compensation. Furthermore, the three-five star hotels have advantage attributes in their operational support, compensation, restaurant information, traffic information, and room information. These results could be provided to the stakeholders as a reference.

Polarized microtubule remodeling transforms the morphology of reactive microglia and drives cytokine release.

Microglial reactivity is a pathological hallmark in many neurodegenerative diseases. During stimulation, microglia undergo complex morphological changes, including loss of their characteristic ramified morphology, which is routinely used to detect and quantify inflammation in the brain. However, the underlying molecular mechanisms and the relation between microglial morphology and their pathophysiological function are unknown. Here, proteomic profiling of lipopolysaccharide (LPS)-reactive microglia identifies microtubule remodeling pathways as an early factor that drives the morphological change and subsequently controls cytokine responses. We find that LPS-reactive microglia reorganize their microtubules to form a stable and centrosomally-anchored array to facilitate efficient cytokine trafficking and release. We identify cyclin-dependent kinase 1 (Cdk-1) as a critical upstream regulator of microtubule remodeling and morphological change in-vitro and in-situ. Cdk-1 inhibition also rescues tau and amyloid fibril-induced morphology changes. These results demonstrate a critical role for microtubule dynamics and reorganization in microglial reactivity and modulating cytokine-mediated inflammatory responses.

TPL2 kinase activity regulates microglial inflammatory responses and promotes neurodegeneration in tauopathy mice.

Tumor progression locus 2 (TPL2) (MAP3K8) is a central signaling node in the inflammatory response of peripheral immune cells. We find that TPL2 kinase activity modulates microglial cytokine release and is required for microglia-mediated neuron death in vitro. In acute in vivo neuroinflammation settings, TPL2 kinase activity regulates microglia activation states and brain cytokine levels. In a tauopathy model of chronic neurodegeneration, loss of TPL2 kinase activity reduces neuroinflammation and rescues synapse loss, brain volume loss, and behavioral deficits. Single-cell RNA sequencing analysis indicates that protection in the tauopathy model was associated with reductions in activated microglia subpopulations as well as infiltrating peripheral immune cells. Overall, using various models, we find that TPL2 kinase activity can promote multiple harmful consequences of microglial activation in the brain including cytokine release, iNOS (inducible nitric oxide synthase) induction, astrocyte activation, and immune cell infiltration. Consequently, inhibiting TPL2 kinase activity could represent a potential therapeutic strategy in neurodegenerative conditions.

A Near-Optimal Energy Management Mechanism Considering QoS and Fairness Requirements in Tree Structure Wireless Sensor Networks.

The rapid development of AIOT-related technologies has revolutionized various industries. The advantage of such real-time sensing, low costs, small sizes, and easy deployment makes extensive use of wireless sensor networks in various fields. However, due to the wireless transmission of data, and limited built-in power supply, controlling energy consumption and making the application of the sensor network more efficient is still an urgent problem to be solved in practice. In this study, we construct this problem as a tree structure wireless sensor network mathematical model, which mainly considers the QoS and fairness requirements. This study determines the probability of sensor activity, transmission distance, and transmission of the packet size, and thereby minimizes energy consumption. The Lagrangian Relaxation method is used to find the optimal solution with the lowest energy consumption while maintaining the network's transmission efficiency. The experimental results confirm that the decision-making speed and energy consumption can be effectively improved.

Machine Learning-Based Text Analysis to Predict Severely Injured Patients in Emergency Medical Dispatch: Model Development and Validation.

BACKGROUND: Early recognition of severely injured patients in prehospital settings is of paramount importance for timely treatment and transportation of patients to further treatment facilities. The dispatching accuracy has seldom been addressed in previous studies. OBJECTIVE: In this study, we aimed to build a machine learning-based model through text mining of emergency calls for the automated identification of severely injured patients after a road accident. METHODS: Audio recordings of road accidents in Taipei City, Taiwan, in 2018 were obtained and randomly sampled. Data on call transfers or non-Mandarin speeches were excluded. To predict cases of severe trauma identified on-site by emergency medical technicians, all included cases were evaluated by both humans (6 dispatchers) and a machine learning model, that is, a prehospital-activated major trauma (PAMT) model. The PAMT model was developed using term frequency-inverse document frequency, rule-based classification, and a Bernoulli naïve Bayes classifier. Repeated random subsampling cross-validation was applied to evaluate the robustness of the model. The prediction performance of dispatchers and the PAMT model, in severe cases, was compared. Performance was indicated by sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. RESULTS: Although the mean sensitivity and negative predictive value obtained by the PAMT model were higher than those of dispatchers, they obtained higher mean specificity, positive predictive value, and accuracy. The mean accuracy of the PAMT model, from certainty level 0 (lowest certainty) to level 6 (highest certainty), was higher except for levels 5 and 6. The overall performances of the dispatchers and the PAMT model were similar; however, the PAMT model had higher accuracy in cases where the dispatchers were less certain of their judgments. CONCLUSIONS: A machine learning-based model, called the PAMT model, was developed to predict severe road accident trauma. The results of our study suggest that the accuracy of the PAMT model is not superior to that of the participating dispatchers; however, it may assist dispatchers when they lack confidence while making a judgment.

Complement C1q-dependent excitatory and inhibitory synapse elimination by astrocytes and microglia in Alzheimer's disease mouse models.

Microglia and complement can mediate neurodegeneration in Alzheimer's disease (AD). By integrative multi-omics analysis, here we show that astrocytic and microglial proteins are increased in TauP301S synapse fractions with age and in a C1q-dependent manner. In addition to microglia, we identified that astrocytes contribute substantially to synapse elimination in TauP301S hippocampi. Notably, we found relatively more excitatory synapse marker proteins in astrocytic lysosomes, whereas microglial lysosomes contained more inhibitory synapse material. C1q deletion reduced astrocyte-synapse association and decreased astrocytic and microglial synapses engulfment in TauP301S mice and rescued synapse density. Finally, in an AD mouse model that combines ß-amyloid and Tau pathologies, deletion of the AD risk gene Trem2 impaired microglial phagocytosis of synapses, whereas astrocytes engulfed more inhibitory synapses around plaques. Together, our data reveal that astrocytes contact and eliminate synapses in a C1q-dependent manner and thereby contribute to pathological synapse loss and that astrocytic phagocytosis can compensate for microglial dysfunction.

One-Step Microwave-Assisted Synthesis of PtNiCo/rGO Electrocatalysts with High Electrochemical Performance for Direct Methanol Fuel Cells.

Platinum (Pt) is widely used as an activator in direct methanol fuel cells (DMFCs). However, the development of Pt catalyst is hindered due to its high cost and CO poisoning. A multi-metallic catalyst is a promising catalyst for fuel cells. We develop a simple and rapid method to synthesize PtNiCo/rGO nanocomposites (NCs). The PtNiCo/rGO NCs catalyst was obtained by microwave-assisted synthesis of graphene oxide (GO) with Pt, Ni, and Co precursors in ethylene glycol (EG) solution after heating for 20 min. The Pt-Ni-Co nanoparticles showed a narrow particle size distribution and were uniformly dispersed on the reduced graphene oxide without agglomeration. Compared with PtNiCo catalyst, PtNiCo/rGO NCs have superior electrocatalytic properties, including a large electrochemical active surface area (ECSA), the high catalytic activity of methanol, excellent anti-toxic properties, and high electrochemical stability. The ECSA can be up to 87.41 m2/g at a scan rate of 50 mV/s. They also have the lowest oxidation potential of CO. These excellent electrochemical performances are attributed to the uniform dispersion of PtNiCo nanoparticles, good conductivity, stability, and large specific surface area of the rGO carrier. The synthesized PtNiCo/rGO nanoparticles have an average size of 17.03 ± 1.93 nm. We also investigated the effect of catalyst material size on electrocatalytic performance, and the results indicate that PtNiCo/rGO NC catalysts can replace anode catalyst materials in fuel cell applications in the future.

Developing a sustainability strategy for Taiwan's tourism industry after the COVID-19 pandemic.

The outbreak of COVID-19 around the world has caused great damage to the global economy. The tourism industry is among the worst-hit industries. How to focus on visitors who are most helpful to the tourism industry and develop sustainable strategy of operation is a very important question for after the epidemic is over. This study applied two-stage data envelopment analysis (DEA) and principal component analysis (PCA) to investigate past statistics from the Tourism Bureau and explore the shopping patterns of tourists who travel to Taiwan. The focus will be on tourists from major countries such as China, Japan, and Southeast Asian countries. According to the analysis of tourists from different countries, the money spent by tourists from different countries is concentrated on different items, and there are subitems that they particularly like to purchase. For the analysis of the purpose of coming to Taiwan, some tourism areas worth developing (such as medical treatment and leisure) are also presented in the research results. Based on these results, and according to the sustainable development goals, specific recommendations for the sustainability strategy of operation are made as a reference for the government and relevant industries. This research also broadens the scope of application of DEA and points out a different direction for future research.

Isomeric Pyrene-Porphyrins for Efficient Dye-Sensitized Solar Cells: An Unexpected Enhancement of the Photovoltaic Performance upon Structural Modification.

Four pyrene-porphyrins were synthesized to study the isomer effect on the photovoltaic performance of dye-sensitized solar cells. One of these porphyrins is conjugated with a terminal pyrene, whereas the other three are each attached with a pyrene bearing an extra donor group. According to the positions of the extra donor and porphyrin core on pyrene, the 1,6-, 1,8-, and 2,7-isomers were compared for their fundamental and photovoltaic properties. For fundamental properties, UV-visible absorption, fluorescence emission, electrochemistry, and DFT calculations were carried out. For photovoltaic measurements, the seemingly inferior 1,8-isomer outperforms others with an overall efficiency of 10.30% under one-sun irradiation. Superior photovoltaic performance of the 1,8-isomeric dye may be related to the so-called umbrella effect. The findings of this work may provide insight into isomeric dye design for future applications.

Relocation of an Extrasynaptic GABAA Receptor to Inhibitory Synapses Freezes Excitatory Synaptic Strength and Preserves Memory.

The excitatory synapse between hippocampal CA3 and CA1 pyramidal neurons exhibits long-term potentiation (LTP), a positive feedback process implicated in learning and memory in which postsynaptic depolarization strengthens synapses, promoting further depolarization. Without mechanisms for interrupting positive feedback, excitatory synapses could strengthen inexorably, corrupting memory storage. Here, we reveal a hidden form of inhibitory synaptic plasticity that prevents accumulation of excitatory LTP. We developed a knockin mouse that allows optical control of endogenous α5-subunit-containing γ-aminobutyric acid (GABA)A receptors (α5-GABARs). Induction of excitatory LTP relocates α5-GABARs, which are ordinarily extrasynaptic, to inhibitory synapses, quashing further NMDA receptor activation necessary for inducing more excitatory LTP. Blockade of α5-GABARs accelerates reversal learning, a behavioral test for cognitive flexibility dependent on repeated LTP. Hence, inhibitory synaptic plasticity occurs in parallel with excitatory synaptic plasticity, with the ensuing interruption of the positive feedback cycle of LTP serving as a possible critical early step in preserving memory.

Parvalbumin interneurons provide spillover to newborn and mature dentate granule cells.

Parvalbumin-expressing interneurons (PVs) in the dentate gyrus provide activity-dependent regulation of adult neurogenesis as well as maintain inhibitory control of mature neurons. In mature neurons, PVs evoke GABAA postsynaptic currents (GPSCs) with fast rise and decay phases that allow precise control of spike timing, yet synaptic currents with fast kinetics do not appear in adult-born neurons until several weeks after cell birth. Here we used mouse hippocampal slices to address how PVs signal to newborn neurons prior to the appearance of fast GPSCs. Whereas PV-evoked currents in mature neurons exhibit hallmark fast rise and decay phases, newborn neurons display slow GPSCs with characteristics of spillover signaling. We also unmasked slow spillover currents in mature neurons in the absence of fast GPSCs. Our results suggest that PVs mediate slow spillover signaling in addition to conventional fast synaptic signaling, and that spillover transmission mediates activity-dependent regulation of early events in adult neurogenesis.

Synthesis, properties and photovoltaic performance in dye-sensitized solar cells of three meso-diphenylbacteriochlorins bearing a dual-function electron-donor.

Bacteriochlorins are crucial to photosynthesis in bacteria. Studies of air-stable, meso-substituted bacteriochlorins are rare. We herein report the synthesis, properties, and photovoltaic performance of three new air-stable, meso-substituted bacteriochlorins bearing a dioctylfluorenylethyne (denoted as LS-17), a dioctylaminophenylethynylanthrylethyne (LS-43), and a diarylaminoanthrylethyne (LS-45) as the electron-donating groups. Among these LS-bacteriochlorins, LS-17 displays sharp UV-visible absorption bands whereas LS-43 and LS-45 give rise to broadened and red-shifted absorptions. Electrochemical and DFT results suggest that the first oxidation and reduction reactions of these bacteriochlorins are consistent with the formation of the cation and anion radicals, respectively. For dye-sensitized solar cell applications, photovoltaic performance of the LS-45 cell achieves an overall efficiency of 6.04% under one-sun irradiation.

Design of New n-Type Porphyrin Acceptors with Subtle Side-Chain Engineering for Efficient Nonfullerene Solar Cells with Low Energy Loss and Optoelectronic Response Covering the Near-Infrared Region.

A series of tailor-made highly efficient and near-infrared (NIR) porphyrin-based acceptors is designed and synthesized for fullerene-free bulk-heterojunction (BHJ) organic solar cells. Constructing BHJ active layers using a PTB7-Th donor and porphyrin acceptors (P-x), which have complementary absorption, accomplishes panchromatic photon-to-current conversion from 300 to 950 nm. Our study shows that side chains of the porphyrin acceptors fairly influence the molecular ordering and nanomorphology of the BHJ active layers. Significantly, the porphyrin acceptor with four dodecoxyl side chains (P-2) achieves an open-circuit voltage (VOC) of 0.80 V, short-circuit current density (JSC) of 13.94 mA cm-2, fill factor of 64.8%, and overall power conversion efficiency of 7.23%. This great performance is attributable to the ascendant light-harvesting capability in the visible and near-infrared region, a high-lying LUMO energy level, a relatively high and more balanced carrier mobilities, and more ordered face-on molecular packing, which is beneficial for obtaining high VOC and JSC.

Porphyrin-Containing Polymer as a Superior Blue Light-Absorbing Additive To Afford High- Jsc Ternary Solar Cells.

Integrating an additional component featuring complementary light absorption into binary polymer solar cells is a superior tactic to ameliorate solar cell efficiency and stability. An appropriate additive not only extends the absorption range but may also facilitate charge separation and transport processes. In this work, we elucidate the effects of incorporating a porphyrin-containing conjugated polymer (PPor-1), which displays absorption in 350-500 nm, into binary PTB7-Th:4TIC and PTB7-Th:ITIC blends, affording devices with an average power conversion efficiency approaching 9%. We successfully demonstrate that PPor-1 can be incorporated as an additive to impart improved Jsc (up to 19.1 mA cm-2).

Design of a Highly Bistable Photoswitchable Tethered Ligand for Rapid and Sustained Manipulation of Neurotransmission.

Photoswitchable neurotransmitter receptors are powerful tools for precise manipulation of neural signaling. However, their applications for slow or long-lasting biological events are constrained by fast thermal relaxation of cis-azobenzene. We address this issue by modifying the ortho positions of azobenzene used in the tethered ligand. In cultured cells and intact brain tissue, conjugating inhibitory neurotransmitter receptors with one of the derivatives, dMPC1, allows bidirectional receptor control with 380 and 500 nm light. Moreover, the receptors can be locked in either an active or an inactive state in darkness after a brief pulse of light. This strategy thus enables both rapid and sustained manipulation of neurotransmission, allowing optogenetic interrogation of neural functions over a broad range of time scales.

Forecasting leading industry stock prices based on a hybrid time-series forecast model.

Many different time-series methods have been widely used in forecast stock prices for earning a profit. However, there are still some problems in the previous time series models. To overcome the problems, this paper proposes a hybrid time-series model based on a feature selection method for forecasting the leading industry stock prices. In the proposed model, stepwise regression is first adopted, and multivariate adaptive regression splines and kernel ridge regression are then used to select the key features. Second, this study constructs the forecasting model by a genetic algorithm to optimize the parameters of support vector regression. To evaluate the forecasting performance of the proposed models, this study collects five leading enterprise datasets in different industries from 2003 to 2012. The collected stock prices are employed to verify the proposed model under accuracy. The results show that proposed model is better accuracy than the other listed models, and provide persuasive investment guidance to investors.

Enhanced Electrochemical Catalytic Efficiencies of Electrochemically Deposited Platinum Nanocubes as a Counter Electrode for Dye-Sensitized Solar Cells.

Platinum nanocubes (PtNCs) were deposited onto a fluorine-doped tin oxide glass by electrochemical deposition (ECD) method and utilized as a counter electrode (CE) for dye-sensitized solar cells (DSSCs). In this study, we controlled the growth of the crystalline plane to synthesize the single-crystal PtNCs at room temperature. The morphologies and crystalline nanostructure of the ECD PtNCs were examined by field emission scanning electron microscopy and high-resolution transmission electron microscopy. The surface roughness of the ECD PtNCs was examined by atomic force microscopy. The electrochemical properties of the ECD PtNCs were analyzed by cyclic voltammetry, Tafel polarization, and electrochemical impedance spectra. The Pt loading was examined by inductively coupled plasma mass spectrometry. The DSSCs were assembled via an N719 dye-sensitized titanium dioxide working electrode, an iodine-based electrolyte, and a CE. The photoelectric conversion efficiency (PCE) of the DSSCs with the ECD PtNC CE was examined under the illumination of AM 1.5 (100 mWcm(-2)). The PtNCs in this study presented a single-crystal nanostructure that can raise the electron mobility to let up the charge-transfer impedance and promote the charge-transfer rate. In this work, the electrocatalytic mass activity (MA) of the Pt film and PtNCs was 1.508 and 4.088 mAmg(-1), respectively, and the MA of PtNCs was 2.71 times than that of the Pt film. The DSSCs with the pulse-ECD PtNC CE showed a PCE of 6.48 %, which is higher than the cell using the conventional Pt film CE (a PCE of 6.18 %). In contrast to the conventional Pt film CE which is fabricated by electron beam evaporation method, our pulse-ECD PtNCs maximized the Pt catalytic properties as a CE in DSSCs. The results demonstrated that the PtNCs played a good catalyst for iodide/triiodide redox couple reactions in the DSSCs and provided a potential strategy for electrochemical catalytic applications.

A Comprehensive Optogenetic Pharmacology Toolkit for In Vivo Control of GABA(A) Receptors and Synaptic Inhibition.

Exogenously expressed opsins are valuable tools for optogenetic control of neurons in circuits. A deeper understanding of neural function can be gained by bringing control to endogenous neurotransmitter receptors that mediate synaptic transmission. Here we introduce a comprehensive optogenetic toolkit for controlling GABA(A) receptor-mediated inhibition in the brain. We developed a series of photoswitch ligands and the complementary genetically modified GABA(A) receptor subunits. By conjugating the two components, we generated light-sensitive versions of the entire GABA(A) receptor family. We validated these light-sensitive receptors for applications across a broad range of spatial scales, from subcellular receptor mapping to in vivo photo-control of visual responses in the cerebral cortex. Finally, we generated a knockin mouse in which the "photoswitch-ready" version of a GABA(A) receptor subunit genomically replaces its wild-type counterpart, ensuring normal receptor expression. This optogenetic pharmacology toolkit allows scalable interrogation of endogenous GABA(A) receptor function with high spatial, temporal, and biochemical precision.

The ubiquitous nature of multivesicular release.

'Simplicity is prerequisite for reliability' (E.W. Dijkstra [1]) Presynaptic action potentials trigger the fusion of vesicles to release neurotransmitter onto postsynaptic neurons. Each release site was originally thought to liberate at most one vesicle per action potential in a probabilistic fashion, rendering synaptic transmission unreliable. However, the simultaneous release of several vesicles, or multivesicular release (MVR), represents a simple mechanism to overcome the intrinsic unreliability of synaptic transmission. MVR was initially identified at specialized synapses but is now known to be common throughout the brain. MVR determines the temporal and spatial dispersion of transmitter, controls the extent of receptor activation, and contributes to adapting synaptic strength during plasticity and neuromodulation. MVR consequently represents a widespread mechanism that extends the dynamic range of synaptic processing.