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The cholinergic system in the brain plays crucial roles in regulating sensory and motor functions as well as cognitive behaviors by modulating neuronal activity. Understanding the organization of the cholinergic system requires a complete map of cholinergic neurons and their axon arborizations throughout the entire brain at the level of single neurons. Here, we report a comprehensive whole-brain atlas of the cholinergic system originating from various cortical and subcortical regions of the mouse brain. Using genetically labeled cholinergic neurons together with whole-brain reconstruction of optical images at 2-µm resolution, we obtained quantification of the number and soma volume of cholinergic neurons in 22 brain areas. Furthermore, by reconstructing the complete axonal arbors of fluorescently labeled single neurons from a subregion of the basal forebrain at 1-µm resolution, we found that their projections to the forebrain and midbrain showed neuronal subgroups with distinct projection specificity and diverse arbor distribution within the same projection area. These results suggest the existence of distinct subtypes of cholinergic neurons that serve different regulatory functions in the brain and illustrate the usefulness of complete reconstruction of neuronal distribution and axon projections at the mesoscopic level. [ABSTRACT FROM AUTHOR]

The firing rate of the mitral/tufted cells in the olfactory bulb is known to undergo significant trial-to-trial variability and is affected by anesthesia. Here we ask whether odorant-elicited changes in firing rate depend on the rate before application of the stimulus in the awake and anesthetized mouse. We find that prestimulus firing rate varies widely on a trial-to-trial basis and that the stimulus-induced change in firing rate decreases with increasing prestimulus firing rate. Interestingly, this prestimulus firing rate dependence was different when the behavioral task did not involve detecting the valence of the stimulus. Finally, when the animal was learning to associate the odor with reward, the prestimulus firing rate was smaller for false alarms compared with correct rejections, suggesting that intrinsic activity reflects the anticipatory status of the animal. Thus, in this sensory modality, changes in behavioral status alter the intrinsic prestimulus activity, leading to a change in the responsiveness of the second-order neurons. We speculate that this trial-to-trial variability in odorant responses reflects sampling of the massive parallel input by subsets of mitral cells. [ABSTRACT FROM AUTHOR]

Recently, extensive researches focus on the joint estimation of carrier frequency and direction-of-arrival, whereas the heavy computation burden and affordable hardware cost are always required therein. To alleviate the problem, we propose a relaxed coprime array based two-stage estimator, which can sequentially detect the frequencies and direction-of-arrival for multiple targets. Guided by the closed-form robust algorithm, this relaxation yields a higher array sparsity compared with existing sparse arrays. Specifically, the first stage aims to achieve the classification of the frequency and angle remainders arising from temporal-spatial undersampling, which is realized by combining spectrum correction with pattern clustering. By incorporating the closed-form robust Chinese Remainder Theorem into the remainder classification result, we obtain all the frequencies and direction-of-arrival in the second stage. Both performance analysis and numerical results were conducted to verify the effectiveness of the proposed estimator in the multi-target case.

Accurate measurement and estimation on the trends and spatial distributions of VOCs emissions in China are critical to establishing efficient local or regional pollution control measures, while less is known about the discrepancies on VOCs emissions estimated by previous studies. In this study, two of the estimation approaches including the bottom-up and top-down methods have been reviewed with the data collected from many studies. The approaches demonstrated that the total anthropogenic VOCs emissions in China have been increasing since 1949. The contributions of industrial and solvent use to total VOCs emissions have been increasing since 2000, whereas the contributions of transportation sector have shown a decreasing trend since 2000. The contributions of fuel combustion have also been decreasing since 1950. The gaps of emission estimates for the industry and solvent use were 99.3 ± 22.7% and 81.5 ± 41.8%, respectively, which distributed in much wider ranges than other sources (e.g. 28.9 ± 16.7% for fuel combustion). In comparison to the top-down method, larger variations on the annual VOCs emission estimates were seen using the bottom-up method that comprised different data sources. For the view of spatial pattern, most hot emission estimate spots were concentrated in the eastern China, consistent to their relatively stronger strengths in the industrialization and urbanization. Although the total VOCs emission in China has been continuously increasing during 2008–2016, the VOCs emissions per gross domestic production (GDP) showed a decreasing trend. As for individual compounds, large discrepancy was seen on formaldehyde, with the coefficient of variation (CV) ranged from 37% to 128% over the years. In overall of view, the importance of industrial process and solvent use is increasing. More focuses must be made to these two sources. Emissions of individual compound, particularly those of oxygenated VOCs, were not completely determined and should be better quantified.

The El Niño-Southern Oscillation (ENSO) is one of the main drivers of the interannual climate variability of Earth and can cause a wide range of climate anomalies, so multi year ENSO forecasts are a paramount scientific issue. However, most existing works rely on the conventional iterative mechanism and, thus, fail to provide reliable long-term predictions due to error accumulation. Although methods based on deep learning (DL) apply the parallel modeling scheme for different lead times instead of a single iteration model, they leverage the same DL model for prediction, which can not fully mine the variability of different lead times, resulting in a decrease of prediction accuracy. To solve this problem, we propose a novel parallel deep convolutional neural network (CNN) with a heterogeneous architecture. In this study, by adaptively selecting network architectures for different lead times, we realize variability modeling of different tasks (lead times) and thereby improve the reliability of long-term predictions. Furthermore, we propose a relationship between different prediction lead times and neural network architecture from a unique perspective, namely, the receptive field originally proposed in computer vision. According to the spatio-temporal correlated area and sampling scale of lead times, the size of the convolution kernel and the mesh size of sampling are adjusted as the lead time increases. The Coupled Model Intercomparison Project phase 5 (CMIP5) from 1861 to 2004 and the Simple Ocean Data Assimilation (SODA) from 1871 to 1973 were used for model training, and the GODAS from 1982 to 2017 were used for testing the forecast skill of the model. Experimental results demonstrate that the proposed method outperforms the other well-known methods, especially for long-term predictions.

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab® and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level. [ABSTRACT FROM AUTHOR]

Pancreatic cancer (PCa) is one of the most aggressive lethal malignancies, and cancer metastasis is the major cause of PCa-associated death. F-box/LRR-repeat protein 7 (FBXL7) regulates cancer metastasis and the chemosensitivity of human pancreatic cancer. However, the clinical significance and biological role of FBXL7 in PCa have been rarely studied. In this study, we found that the expression of FBXL7 was down-regulated in PCa tissues compared with tumor-adjacent tissues, and the low expression of FBXL7 was positively associated with cancer metastasis. Functionally, overexpression of FBXL7 attenuated PANC1 cell invasion, whereas FBXL7 silencing promoted BxPC-3 cell invasion. Forced expression of FBXL7 upregulated the expression of epithelial markers (e.g., E-cadherin) and repressed the expression of mesenchymal markers (e.g., N-cadherin and Vimentin), indicating that FBXL7 negatively regulated the epithelial-mesenchymal transition (EMT) of PCa cells. Furthermore, we identified that FBXL7 repressed the expression of Snail1, a crucial transcription factor of EMT. Mechanistically, FBXL7 bound to Snail1 and promoted its ubiquitination and proteasomal degradation. In vivo studies demonstrated that FBXL7 inhibition promotes PCa metastasis. Taken together, our findings demonstrate that FBXL7 knockdown could efficiently enhance PCa metastasis by regulating Snail1-dependent EMT.

With the growing demand of automatic emotion recognition system, emotion recognition is becoming more and more crucial for human–computer interaction (HCI) research. Recently, there is a continuous improvement in the performance of automatic emotion recognition due to the development of both hardware and deep learning methods. However, because of the abstract concept and multiple expressions of emotion, automatic emotion recognition is still a challenging task. In this paper, we propose a novel Multi-modal Correlated Network for emotion recognition aiming at exploiting the information from both audio and visual channels to achieve more robust and accurate detection. In the proposed method, the audio signals and visual signals are first preprocessed for the feature extraction. After preprocessing, we obtain the Mel-spectrograms, which can be treated as images, and the representative frames from visual segments. Then the Mel-spectrograms are fed to the convolutional neural network (CNN) to get the audio features and the representative frames are fed to the CNN and LSTM to get features. Specially, we employ the triplet loss to increase the differentiation of inter-class. Meanwhile, we propose a novel correlated loss to reduce the differentiation of intra-class. Finally, we apply the feature fusion method to fuse the audio and visual feature for emotion recognition classification. The experimental result on AEFW dataset demonstrates the correlation information of multiple modals is crucial for automatic emotion recognition and the proposed method can achieve the state-of-the-art performance on the classification task. Keywords: Multi-modal, Emotion recognition, Neural networks

There are some unsolvable fundamental questions, such as cell type classification, neural circuit tracing and neurovascular coupling, though great progresses are being made in neuroscience. Because of the structural features of neurons and neural circuits, the solution of these questions needs us to break through the current technology of neuroanatomy for acquiring the exactly fine morphology of neuron and vessels and tracing long-distant circuit at axonal resolution in the whole brain of mammals. Combined with fast-developing labeling techniques, efficient whole-brain optical imaging technology emerging at the right moment presents a huge potential in the structure and function research of specific-function neuron and neural circuit. In this review, we summarize brain-wide optical tomography techniques, review the progress on visible brain neuronal/vascular networks benefit from these novel techniques, and prospect the future technical development. [ABSTRACT FROM AUTHOR]

Studies in different sensory systems indicate that short spike patterns within a spike train that carry items of sensory information can be extracted from the overall train by using field potential oscillations as a reference (Kayser et al., 2012; Panzeri et al., 2014). Here we test the hypothesis that the local field potential (LFP) provides the temporal reference frame needed to differentiate between odors regardless of associated outcome. Experiments were performed in the olfactory system of the mouse (Mus musculus) where the mitral/tufted (M/T) cell spike rate develops differential responses to rewarded and unrewarded odors as the animal learns to associate one of the odors with a reward in a go-no go behavioral task. We found that coherence of spiking in M/T cells with the Y LFP (65 to 95 Hz) differentiates between odors regardless of the associated behavioral outcome of odor presentation. [ABSTRACT FROM AUTHOR]

Sensory neuron input to the olfactory bulb (OB) was activated precisely for different durations with blue light in mice expressing channelrhodopsin-2 in olfactory sensory neurons. Behaviorally the mice discriminated differences of 10 ms in duration of direct glomer-ular activation. In addition, a subset of mitral/tufted cells in the OB of awake mice responded tonically therefore conveying information on stimulus duration. Our study provides evidence that duration of the input to glomeruli not synchronized to sniffing is detected. This potent cue may be used to obtain information on puffs in odor plumes. [ABSTRACT FROM AUTHOR]

It is critical for normal brains to perceive the external world precisely and accurately under ever-changing operational conditions, yet the mechanisms underlying this fundamental brain function in the sensory systems are poorly understood. To address this issue in the olfactory system, we investigated the responses of olfactory bulbs to odor stimulations under different brain states manipulated by anesthesia levels. Our results revealed that in two brain states, where the spontaneous baseline activities differed about twofold based on the local field potential (LFP) signals, the levels of neural activities reached after the same odor stimulation had no significant difference. This phenomenon was independent of anesthetics (pentobarbital or chloral hydrate), stimulating odorants (ethyl propionate, ethyl butyrate, ethyl valerate, amyl acetate, n-heptanal, or 2-heptanone), odor concentrations, and recording sites (the mitral or granular cell layers) for LFPs in three frequency bands (12-32 Hz, 33-64 Hz, and 65-90 Hz) and for multiunit activities. Furthermore, the activity patterns of the same stimulation under these two brain states were highly similar at both LFP and multiunit levels. These converging results argue the existence of mechanisms in the olfactory bulbs that ensure the delivery of peripheral olfactory information to higher olfactory centers with high fidelity under different brain states. [ABSTRACT FROM AUTHOR]

The neuroanatomical architecture is considered to be the basis for understanding brain function and dysfunction. However, existing imaging tools have limitations for brainwide mapping of neural circuits at a mesoscale level. We developed a micro-optical sectioning tomography (MOST) system that can provide micrometer-scale tomography of a centimeter-sized whole mouse brain. Using MOST, we obtained a three-dimensional structural data set of a Golgi-stained whole mouse brain at the neurite level. The morphology and spatial locations of neurons and traces of neurites could be clearly distinguished. We found that neighboring Purkinje cells stick to each other. [ABSTRACT FROM AUTHOR]

Scavenger receptor class B, type I (SR-BI)/ApoE double null mice develop severe atherosclerosis within 4 weeks, whereas ApoE null mice take several months to develop the disease, indicating that SR-BI plays a pivotal role in atherosclerosis. Importantly, SR-BI/ApoE double null mice have lower plasma cholesterol levels than ApoE null mice, suggesting involvement of a non-lipids mechanism. In the present study, we revealed a novel ligand-independent apoptotic pathway induced by SR-BI, and regulated by endothelial nitric-oxide synthase (eNOS) and high density lipoprotein (HDL). SR-BI significantly induces apoptosis in three independent cell systems. In contrast to known ligand-dependent apoptotic pathways, SR-BI-induced apoptosis is ligand-independent. We further showed that SR-BI-induced apoptosis is suppressed by eNOS and HDL. By using a single site mutation, we demonstrated that SR-BI induces apoptosis through a highly conserved CXXS redox motif. We finally demonstrated that SR-BI-induced apoptosis is via the caspase-8 pathway. We hypothesize that in healthy cells, the SR-BI apoptotic pathway is turned off by eNOS and HDL which prevents inappropriate apoptotic damage to the vascular wall. When HDL levels are low, oxidative stress causes the relocation of eNOS away from caveolae, which turns on SR-BI-induced apoptosis and rapidly clears damaged cells to prevent further inflammatory damage to neighboring cells. The current studies offer a new paradigm in which to study the non-cholesterol effects of SR-BI, HDL, and eNOS on the development of atheroselerosis and potentially other cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Nitrogen-containing organic compounds possess the most important status in drug molecules and agricultural chemicals. More than 80% currently used drugs have at least a C-N bond. The green and mild methodology to prepare diverse C-N bonds to replace traditional harsh preparation protocols is always a hotspot in modern synthetic chemistry. TiO2-based nanomaterials, considered as environmentally benign, stable, and powerful photocatalysts, have recently been applied in some certain challenging organic synthesis including construction of useful C-N compounds under mild conditions that are impossible to complete by conventional catalysis. This mini review would present state-of-the-art paragon examples of TiO2 photocatalyzed C-N bond formations. The discussion would be divided into two main sections: (1) N-alkylation of amines and (2) C-N formation in heterocycle synthesis. Especially, the mechanism of TiO2 photocatalytic C-N bond formation through activating alcohol into C=O by photo-induced hole followed by C=NH-R formation and finally hydrogenating C=NH-R into C-N bonds by combination of photo-induced electron/H+ assisted with loaded-Pt would be covered in detail. We believe that the mini-review will bring new insights into TiO2 photocatalysis applied to construct challenging organic compounds through enabling photo-induced hole and electron in a concerted way on coupling two substrate molecules together with respect to their conventionally independent catalysis behavior.

Efficient storage and sharing of massive biomedical data would open up their wide accessibility to different institutions and disciplines. However, compressors tailored for natural photos/videos are rapidly limited for biomedical data, while emerging deep learning-based methods demand huge training data and are difficult to generalize. Here, we propose to conduct Biomedical data compRession with Implicit nEural Function (BRIEF) by representing the target data with compact neural networks, which are data specific and thus have no generalization issues. Benefiting from the strong representation capability of implicit neural function, BRIEF achieves 2-3 orders of magnitude compression on diverse biomedical data at significantly higher fidelity than existing techniques. Besides, BRIEF is of consistent performance across the whole data volume, and supports customized spatially varying fidelity. BRIEF's multifold advantageous features also serve reliable downstream tasks at low bandwidth. Our approach will facilitate low-bandwidth data sharing and promote collaboration and progress in the biomedical field. [ABSTRACT FROM AUTHOR]

Covalent organic frameworks (COFs) are a kind of porous crystalline polymeric material. They are constructed by organic module units connected with strong covalent bonds extending in two or three dimensions. COFs possess the advantages of low-density, large specific surface area, high thermal stability, developed pore-structure, long-range order, good crystallinity, and the excellent tunability of the monomer units and the linking reticular chemistry. These features endowed COFs with the ability to be applied in a plethora of applications, ranging from adsorption and separation, sensing, catalysis, optoelectronics, energy storage, mass transport, etc. In this paper, we will review the recent progress of COFs materials applied in photocatalytic CO2 reduction. The state-of-the-art paragon examples and the current challenges will be discussed in detail. The future direction in this research field will be finally outlooked.

Carbon gels are a kind of porous organic polymer, which play pivotal roles in electrode, supercapacitor, hydrogen storage, and catalysis. Carbon gels are commonly prepared by the condensation of resorcinol and formaldehyde. The as-prepared polymers are further aged and sintered at a high temperature in an inert atmosphere to form cross-linked and intertwined porous structures. Owing to its large specific area and narrow pore size distribution, this kind of material is very appropriate for mass transfer, substrate absorption, and product desorption from the pores. In recent years, carbon gels have been discovered to function as effective hybrid materials with TiO2 for photocatalytic applications. They could act as efficient deep-traps for photo-induced holes, which decreases the recombination probability of photo-induced carriers and lengthens their lifetime. In this mini-review, we will discuss the state-of-the-art paragon examples of carbon gels/TiO2 composite materials applied in photo(electro)catalysis. The major challenges and gaps of its application in this field will also be emphasized.

Background: Pancreatic ductal adenocarcinoma (PDAC) ranks fourth on the list of cancer-related causes of death and its prognosis has not improved significantly over the past decades. Deregulation or dysfunction of miRNAs contribute to cancer development. Previous data indicates that miR-429 is involved in the pathogenesis of PDAC. However, the role of miR-429 in PDAC remained unknown. Methods: MiR-429 levels in sample tissues of 78 patients and in PANC1 and SW1990 cell lines were quantified by real-time PCR. MiR-429 expression was modulated using specific pre- and anti-miRNAs and cell growth was assayed by MTT analysis. Bioinformatics prediction of the miR-429 putative target genes was performed and luciferase assays confirmed TBK1 as a direct target gene. TBK1 levels in PDAC tissues were analyzed by immunohistochemistry. Results: MiR-429 was remarkably decreased in PDAC tissues and cell lines. Lower miR-429 expression in PDAC tissues significantly correlated with shorter survival of PDAC patients. Overexpression of miR-429 inhibited PDAC cell lines growth in vitro and vice versa. TBK1 was found to be the direct target gene of miR-429. Higher TBK1 protein level in PDAC tissues correlated with shorter survival of PDAC patients. Overexpression of TBK1 partly restored cell proliferation. Conclusions: Low level of miR-429 and high level of TBK1 in PDAC promoted PDAC cells growth which might be related to the low survival rate of PDAC patients. MiR-429 play its role in PDAC by targeting TBK1.

High-throughput optical imaging is critical to obtain large-scale neural connectivity information of brain in neuroscience. Using a digital mirror device and a scientific complementary metal-oxide semiconductor camera, we report a significant speed improvement of structured illumination microscopy (SIM), which produces a maximum SIM net frame rate of 133 Hz. We perform three-dimensional (3-D) imaging of mouse brain slices at diffraction-limited resolution and demonstrate the fast 3-D imaging capability to a large sample with an imaging rate of 6.9 x 107 pixel/s of our system, an order of magnitude faster than previously reported. [ABSTRACT FROM AUTHOR]

Catalytic transfer hydrogenation reactions, based on hydrogen sources other than gaseous H2, are important processes that are preferential in both laboratories and factories. However, harsh conditions, such as high temperature, are usually required for most transition-metal catalytic and organocatalytic systems. Moreover, non-volatile hydrogen donors such as dihydropyridinedicarboxylate and formic acid are often required in these processes which increase the difficulty in separating products and lowered the whole atom economy. Recently, TiO2 photocatalysis provides mild and facile access for transfer hydrogenation of C=C, C=O, N=O and C-X bonds by using volatile alcohols and amines as hydrogen sources. Upon light excitation, TiO2 photo-induced holes have the ability to oxidatively take two hydrogen atoms off alcohols and amines under room temperature. Simultaneously, photo-induced conduction band electrons would combine with these two hydrogen atoms and smoothly hydrogenate multiple bonds and/or C-X bonds. It is heartening that practices and principles in the transfer hydrogenations of substrates containing C=C, C=O, N=O and C-X bond based on TiO2 photocatalysis have overcome a lot of the traditional thermocatalysis’ limitations and flaws which usually originate from high temperature operations. In this review, we will introduce the recent paragon examples of TiO2 photocatalytic transfer hydrogenations used in (1) C=C and C≡C (2) C=O and C=N (3) N=O substrates and in-depth discuss basic principle, status, challenges and future directions of transfer hydrogenation mediated by TiO2 photocatalysis.

Covalent organic frameworks (COFs) are defined as highly porous and crystalline polymers, constructed and connected via covalent bonds, extending in two- or three-dimension. Compared with other porous materials such as zeolite and active carbon, the versatile and alternative constituent elements, chemical bonding types and characteristics of ordered skeleton and pore, enable the rising large family of COFs more available to diverse applications including gas separation and storage, optoelectronics, proton conduction, energy storage and in particular, catalysis. As the representative candidate of next-generation catalysis materials, because of their large surface area, accessible and size-tunable open nano-pores, COFs materials are suitable for incorporating external useful active ingredients such as ligands, complexes, even metal nanoparticles deposition and substrate diffusion. These advantages make it capable to catalyze a variety of useful organic reactions such as important C-C bond formations. By appropriate pore-engineering in COFs materials, even enantioselective asymmetric C-C bond formations could be realized with excellent yield and ee value in much shorter reaction time compared with their monomer and oligomer analogues. This review will mainly introduce and discuss the paragon examples of COFs materials for application in C-C bond formation reactions for the organic synthetic purpose.

Fulfilling the direct inert C–H bond functionalization of raw materials that are earth-abundant and commercially available for the synthesis of diverse targeted organic compounds is very desirable and its implementation would mean a great reduction of the synthetic steps required for substrate prefunctionalization such as halogenation, borylation, and metalation. Successful C–H bond functionalization mainly resorts to homogeneous transition-metal catalysis, albeit sometimes suffering from poor catalyst reusability, nontrivial separation, and severe biotoxicity. TiO2 photocatalysis displays multifaceted advantages, such as strong oxidizing ability, high chemical stability and photostability, excellent reusability, and low biotoxicity. The chemical reactions started and delivered by TiO2 photocatalysts are well known to be widely used in photocatalytic water-splitting, organic pollutant degradation, and dye-sensitized solar cells. Recently, TiO2 photocatalysis has been demonstrated to possess the unanticipated ability to trigger the transformation of inert C–H bonds for C–C, C–N, C–O, and C–X bond formation under ultraviolet light, sunlight, and even visible-light irradiation at room temperature. A few important organic products, traditionally synthesized in harsh reaction conditions and with specially functionalized group substrates, are continuously reported to be realized by TiO2 photocatalysis with simple starting materials under very mild conditions. This prominent advantage—the capability of utilizing cheap and readily available compounds for highly selective synthesis without prefunctionalized reactants such as organic halides, boronates, silanes, etc.—is attributed to the overwhelmingly powerful photo-induced hole reactivity of TiO2 photocatalysis, which does not require an elevated reaction temperature as in conventional transition-metal catalysis. Such a reaction mechanism, under typically mild conditions, is apparently different from traditional transition-metal catalysis and beyond our insights into the driving forces that transform the C–H bond for C–C bond coupling reactions. This review gives a summary of the recent progress of TiO2 photocatalytic C–H bond activation for C–C coupling reactions and discusses some model examples, especially under visible-light irradiation.

Titanium dioxide nanoparticles (TiO2 NPs) have been used in various medical and industrial areas. However, the impacts of these nanoparticles on neuroinflammation in the brain are poorly understood. In this study, mice were exposed to 2.5, 5, or 10 mg/kg body weight TiO2 NPs for 90 consecutive days, and the TLRs/TNF-α/NF-κB signaling pathway associated with the hippocampal neuroinflammation was investigated. Our findings showed titanium accumulation in the hippocampus, neuroinflammation and impairment of spatial memory in mice following exposure to TiO2 NPs. Furthermore, TiO2 NPs significantly activated the expression of Toll-like receptors (TLR2, TLR4), tumor necrosis factor-α, nucleic IκB kinase, NF-κB-inducible kinase, nucleic factor-κB, NF-κB2(p52), RelA(p65), and significantly suppressed the expression of IκB and interleukin-2. These findings suggest that neuroinflammation may be involved in TiO2 NP-induced alterations of cytokine expression in mouse hippocampus. Therefore, more attention should be focused on the application of TiO2 NPs in the food industry and their long-term exposure effects, especially in the human central nervous system.

Histamine is a conserved neuromodulator in mammalian brains and critically involved in many physiological functions. Understanding the precise structure of the histaminergic network is the cornerstone in elucidating its function. Herein, using histidine decarboxylase (HDC)-CreERT2 mice and genetic labeling strategies, we reconstructed a whole-brain three dimensional (3D) structure of histaminergic neurons and their outputs at 0.32 × 0.32 × 2 μm3 pixel resolution with a cutting-edge fluorescence microoptical sectioning tomography system. We quantified the fluorescence density of all brain areas and found that histaminergic fiber density varied significantly among brain regions. The density of histaminergic fiber was positively correlated with the amount of histamine release induced by optogenetic stimulation or physiological aversive stimulation. Lastly, we reconstructed a fine morphological structure of 60 histaminergic neurons via sparse labeling and uncovered the largely heterogeneous projection pattern of individual histaminergic neurons. Collectively, this study reveals an unprecedented whole-brain quantitative analysis of histaminergic projections at the mesoscopic level, providing a foundation for future functional histaminergic study [ABSTRACT FROM AUTHOR]

Background: A growing body of research shows that drug monomers from traditional Chinese herbal medicines have antineuroinflammatory and neuroprotective effects that can significantly improve the recovery of motor function after spinal cord injury (SCI). Here, we explore the role and molecular mechanisms of Alpinetin on activating microglia-mediated neuroinflammation and neuronal apoptosis after SCI. Methods: Stimulation of microglia with lipopolysaccharide (LPS) to simulate neuroinflammation models in vitro, the effect of Alpinetin on the release of pro-inflammatory mediators in LPS-induced microglia and its mechanism were detected. In addition, a co-culture system of microglia and neuronal cells was constructed to assess the effect of Alpinetin on activating microglia-mediated neuronal apoptosis. Finally, rat spinal cord injury models were used to study the effects on inflammation, neuronal apoptosis, axonal regeneration, and motor function recovery in Alpinetin. Results: Alpinetin inhibits microglia-mediated neuroinflammation and activity of the JAK2/STAT3 pathway. Alpinetin can also reverse activated microglia-mediated reactive oxygen species (ROS) production and decrease of mitochondrial membrane potential (MMP) in PC12 neuronal cells. In addition, in vivo Alpinetin significantly inhibits the inflammatory response and neuronal apoptosis, improves axonal regeneration, and recovery of motor function. Conclusion: Alpinetin can be used to treat neurodegenerative diseases and is a novel drug candidate for the treatment of microglia-mediated neuroinflammation. [ABSTRACT FROM AUTHOR]

Through synaptic connections, long-range circuits transmit information among neurons and connect different brain regions to form functional motifs and execute specific functions. Tracing the synaptic distribution of specific neurons requires submicron-level resolution information. However, it is a great challenge to map the synaptic terminals completely because these fine structures span multiple regions, even in the whole brain. Here, we develop a pipeline including viral tracing, sample embedding, fluorescent micro-optical sectional tomography, and big data processing. We mapped the whole-brain distribution and architecture of long projections of the parvalbumin neurons in the basal forebrain at the synaptic level. These neurons send massive projections to multiple downstream regions with subregional preference. With three-dimensional reconstruction in the targeted areas, we found that synaptic degeneration was inconsistent with the accumulation of amyloid-β plaques but was preferred in memory-related circuits, such as hippocampal formation and thalamus, but not in most hypothalamic nuclei in 8-month-old mice with five familial Alzheimer’s disease mutations. Our pipeline provides a platform for generating a whole-brain atlas of cell-type-specific synaptic terminals in the physiological and pathological brain, which can provide an important resource for the study of the organizational logic of specific neural circuits and the circuitry changes in pathological conditions. [ABSTRACT FROM AUTHOR]

Background: Images of anatomical regions and neuron type distribution, as well as their related literature are valuable assets for neuroscience research. They are vital evidence and vehicles in discovering new phenomena and knowledge refinement through image and text big data. The knowledge acquired from image data generally echoes with the literature accumulated over the years. The knowledge within the literature can provide a comprehensive context for a deeper understanding of the image data. However, it is quite a challenge to manually identify the related literature and summarize the neuroscience knowledge in the large-scale corpus. Thus, neuroscientists are in dire need of an automated method to extract neuroscience knowledge from large-scale literature. Methods: A proposed deep learning model named BioBERT-CRF extracts brain region entities from the WhiteText dataset. This model takes advantage of BioBERT and CRF to predict entity labels while training. Results: The proposed deep learning model demonstrated comparable performance against or even outperforms the previous models on the WhiteText dataset. The BioBERT-CRF model has achieved the best average precision, recall, and F1 score of 81.3%, 84.0%, and 82.6%, respectively. We used the BioBERT-CRF model to predict brain region entities in a large-scale PubMed abstract dataset and used a rule-based method to normalize all brain region entities to three neuroscience dictionaries. Conclusions: Our work shows that the BioBERT-CRF model can be well-suited for brain region entity extraction. The rankings of different brain region entities by their appearance in the large-scale corpus indicate the anatomical regions that researchers are most concerned about. [ABSTRACT FROM AUTHOR]

Pain and itch are distinct sensations arousing evasion and compulsive desire for scratching, respectively. It's unclear whether they could invoke different neural networks in the brain. Here, we use the type 1 herpes simplex virus H129 strain to trace the neural networks derived from two types of dorsal root ganglia (DRG) neurons: one kind of polymodal nociceptors containing galanin (Gal) and one type of pruriceptors expressing neurotensin (Nts). The DRG microinjection and immunosuppression were performed in transgenic mice to achieve a successful tracing from specific types of DRG neurons to the primary sensory cortex. About one-third of nuclei in the brain were labeled. More than half of them were differentially labeled in two networks. For the ascending pathways, the spinothalamic tract was absent in the network derived from Nts-expressing pruriceptors, and the two networks shared the spinobulbar projections but occupied different subnuclei. As to the motor systems, more neurons in the primary motor cortex and red nucleus of the somatic motor system participated in the Gal-containing nociceptor-derived network, while more neurons in the nucleus of the solitary tract (NST) and the dorsal motor nucleus of vagus nerve (DMX) of the emotional motor system was found in the Nts-expressing pruriceptor-derived network. Functional validation of differentially labeled nuclei by c-Fos test and chemogenetic inhibition suggested the red nucleus in facilitating the response to noxious heat and the NST/DMX in regulating the histamine-induced scratching. Thus, we reveal the organization of neural networks in a DRG neuron type-dependent manner for processing pain and itch. [ABSTRACT FROM AUTHOR]

Olfaction and satiety status influence each other: cues from the olfactory system modulate eating behavior, and satiety affects olfactory abilities. However, the neural mechanisms governing the interactions between olfaction and satiety are unknown. Here, we investigate how an animal’s nutritional state modulates neural activity and odor representation in the mitral/tufted cells of the olfactory bulb, a key olfactory center that plays important roles in odor processing and representation. At the single-cell level, we found that the spontaneous firing rate of mitral/tufted cells and the number of cells showing an excitatory response both increased when mice were in a fasted state. However, the neural discrimination of odors slightly decreased. Although ongoing baseline and odor-evoked beta oscillations in the local field potential in the olfactory bulb were unchanged with fasting, the amplitude of odor-evoked gamma oscillations significantly decreased in a fasted state. These neural changes in the olfactory bulb were independent of the sniffing pattern, since both sniffing frequency and mean inhalation duration did not change with fasting. These results provide new information toward understanding the neural circuit mechanisms by which olfaction is modulated by nutritional status. [ABSTRACT FROM AUTHOR]

Abstract: During compressive creep, the cubical γ′ phase in [001] orientation single crystal nickel-based superalloy is transformed into the rafted structure along the direction parallel to the applied stress axis. By means of the elastic stress–strain finite element method (FEM), the von Mises stress distributions of the cubical γ′/γ phases are calculated for investigating the influence of the applied stress on the stress distribution and the directional coarsening regularity of γ′ phase. Results show that the stress distribution of the cubical γ/γ′ phases may be changed by the applied compressive stress, and the coarsening orientation of γ′ phase is related to the von Mises stress distribution of the γ matrix channel. Thereinto, under the action of applied compressive stress, the bigger von Mises stress produced on (001) plane of the cubical γ′ phase is thought to be a main reason of the microstructure evolution. The expression of the driving force for the elements diffusion and the directional growing of γ′ phase during compressive creep are also proposed. [Copyright &y& Elsevier]