cAMP is a key second messenger that regulates diverse cellular functions including neural plasticity. However, the spatiotemporal dynamics of intracellular cAMP in intact organisms are largely ...unknown due to low sensitivity and/or brightness of current genetically encoded fluorescent cAMP indicators. Here, we report the development of the new circularly permuted GFP (cpGFP)-based cAMP indicator G-Flamp1, which exhibits a large fluorescence increase (a maximum ΔF/F
of 1100% in HEK293T cells), decent brightness, appropriate affinity (a K
of 2.17 μM) and fast response kinetics (an association and dissociation half-time of 0.20 and 0.087 s, respectively). Furthermore, the crystal structure of the cAMP-bound G-Flamp1 reveals one linker connecting the cAMP-binding domain to cpGFP adopts a distorted β-strand conformation that may serve as a fluorescence modulation switch. We demonstrate that G-Flamp1 enables sensitive monitoring of endogenous cAMP signals in brain regions that are implicated in learning and motor control in living organisms such as fruit flies and mice.
Electromagnetic wave simulation is of pivotal importance in the design and implementation of photonic nano-structures. In this study, we developed a lattice Boltzmann model with a single extended ...force term (LBM-SEF) to simulate the propagation of electromagnetic waves in dispersive media. By reconstructing the solution of the macroscopic Maxwell equations using the lattice Boltzmann equation, the final form only involves an equilibrium term and a non-equilibrium force term. The two terms are evaluated using the macroscopic electromagnetic variables and the dispersive effect, respectively. The LBM-SEF scheme is capable of directly tracking the evolution of macroscopic electromagnetic variables, leading to lower virtual memory requirement and facilitating the implementation of physical boundary conditions. The mathematical consistency of the LBM-SEF with the Maxwell equations was validated by using the Champman-Enskog expansion; while three practical models were used to benchmark the numerical accuracy, stability, and flexibility of the proposed method.
Programmed cell death ligand 1 (PD‐L1) is a major immunosuppressive checkpoint protein expressed by tumor cells to subvert anticancer immunity. Recent studies have shown that ionizing radiation (IR) ...upregulates the expression of PD‐L1 in tumor cells. However, whether an IR‐induced DNA damage response (DDR) directly regulates PD‐L1 expression and the functional significance of its upregulation are not fully understood. Here, we show that IR‐induced upregulation of PD‐L1 expression proceeds through both transcriptional and post‐translational mechanisms. Upregulated PD‐L1 was predominantly present on the cell membrane, resulting in T‐cell apoptosis in a co‐culture system. Using mass spectrometry, we identified PD‐L1 interacting proteins and found that BCLAF1 (Bcl2 associated transcription factor 1) is an important regulator of PD‐L1 in response to IR. BCLAF1 depletion decreased PD‐L1 expression by promoting the ubiquitination of PD‐L1. In addition, we show that CMTM6 is upregulated in response to IR and participates in BCLAF1‐dependent PD‐L1 upregulation. Finally, we demonstrated that the ATM/BCLAF1/PD‐L1 axis regulated PD‐L1 stabilization in response to IR. Together, our findings reveal a novel regulatory mechanism of PD‐L1 expression in the DDR.
IR‐induced PD‐L1 upregulation expression proceeded through post‐translational mechanisms. We identified BCLAF1 as a new PD‐L1 stabilization regulator in response to IR.
Aging induced chronic systemic inflammatory response is an important risk factor for atherosclerosis (AS) development; however, the detailed mechanism is yet to be elucidated.
To explore the ...underlying mechanism of how aging aggravates AS advancement.
A young (five-week-old, YM) and aged group (32-week-old, OM) male apoE
mice with a high fat diet were used as models, and age-matched male wild-type C57BL/6J (WT) mice were used as controls. AS lesion size, serum lipid profile, cytokines, and gut microbiota-derived LPS were analyzed after 32 weeks of diet intervention. A correlation analysis between the 16S rRNA sequencing of the feces and serum metabolomics profiles was applied to examine the effect of their interactions on AS.
ApoE
mice developed severe atherosclerosis and inflammation in the aorta compared to the WT groups, and aged apoE
mice suffered from a more severe AS lesion than their younger counterparts and had low-grade systemic inflammation. Furthermore, increased levels of serum LPS, decreased levels of SCFAs production, as well as dysfunction of the ileal mucosal barrier were detected in aged mice compared with their younger counterparts. There were significant differences in the intestinal flora composition among the four groups, and harmful bacteria such as
,
,
,
and
were significantly increased in the aged apoE
mice compared with the other groups. Concurrently, metabolomics profiling revealed that components involved in the arachidonic acid (AA) metabolic pathway such as 20-HETE, PGF2α, arachidonic acid, and LTB4 were significantly higher in the aged AS group than in the other groups. This suggested that metabolic abnormalities and disorders of intestinal flora occurred in AS mice.
Aging not only altered the gut microbiome community but also substantially disturbed metabolic conditions. Our results confirm that AA metabolism is associated with the imbalance of the intestinal flora in the AS lesions of aged mice. These findings may offer new insights regarding the role of gut flora disorders and its consequent metabolite changed in inflammaging during AS development.
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As a chronic inflammatory disease, atherosclerosis is characterized by accumulation of lipid-rich macrophages on the inner walls of arteries. Deposited macrophages promote ...atherosclerotic lesion progression; therefore they are viewed as the main targets in order to alleviate atherosclerosis. Danlou tablet, a patented Chinese Medicine, has long been used to treat cardiovascular diseases. In the present study, we used Apolipoprotein E-deficient (ApoE−/−) mice model and in vitro cell line of RAW264.7 to explore the mechanisms of ethanol extracts of Danlou tablet (EEDT) in treating atherosclerosis. The potential targets that EEDT works to treat atherosclerosis were predicted by “Network pharmacology analysis”, based on which we designed mRNA array of 93 genes. Then mRNA array and oil red O staining were performed in aortic extracted from the cohorts of Control (C57BL/6 mice, chow fed), Model (ApoE-/- C57BL/6 mice, 20 weeks of high-fat diet) and EEDT intervening (ApoE-/- mice, 20 weeks of high-fat diet with 12 weeks of EEDT treatment) group. Furthermore, mRNA array, inflammation cytokines and lipid content were examined in RAW264.7 cell line. It was showed that EEDT decreased the expressions of inflammation cytokines by down regulating NF-κB singling pathway and accelerated cholesterol effluent through activating PPARα/ABCA1 signaling pathway. On the other hand, activation of NF-κB pathway or suppression of PPARα/ABCA1 signaling pathway both abolished the therapeutic effect of EEDT. In conclusion, EEDT played a key role in anti-inflammation and preventing lipid deposition in macrophages of atherosclerosis via suppressing NF-κB signaling and triggering PPARα/ABCA1 signaling pathway.
Condensate gas reservoirs are a special kind of reservoir because of the presence of multiphase flow in their production. The accurate calculation of the multiphase flow productivity in horizontal ...wells is of great significance for reservoir development. In this study, the total pseudopressure and the equivalent total flow are defined to solve the multiphase nonlinear problem in the oil–gas–water three-phase control flow equation, and to establish a three-phase productivity equation considering the non-Darcy effect. It provides a solution for the three-phase productivity calculation of horizontal wells in water-bearing condensate gas reservoirs. The example verification and error analysis of three horizontal wells, except for the gas production error of Well Y3 and the average error of the production data of other gas wells, is below 4%. The fitting effect of Well Y2 is better than that of the other two horizontal wells, and the average error of the oil, gas, and water phases is below 3%. This method provides a practical and simple engineering tool for the analysis of the productivity of condensate gas reservoirs considering multiphase flow.
Promoters are essential tools for basic and translational neuroscience research. An ideal promoter should possess the shortest possible DNA sequence with cell-type selectivity. However, whether ...ultra-compact promoters can offer neuron-specific expression is unclear. Here, we report the development of an extremely short promoter that enables selective gene expression in neurons, but not glial cells, in the brain. The promoter sequence originates from the human CALM1 gene and is only 120 bp in size. The CALM1 promoter (pCALM1) embedded in an adeno-associated virus (AAV) genome directed broad reporter expression in excitatory and inhibitory neurons in mouse and monkey brains. Moreover, pCALM1, when inserted into an all-in-one AAV vector expressing SpCas9 and sgRNA, drives constitutive and conditional in vivo gene editing in neurons and elicits functional alterations. These data demonstrate the ability of pCALM1 to conduct restricted neuronal gene expression, illustrating the feasibility of ultra-miniature promoters for targeting brain-cell subtypes.
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•A 120-bp promoter, pCALM1, drives selective neuronal expression in mouse and macaque brains•pCALM1 efficiently and durably mediates reporter expression after i.c.v./i.v./local delivery•pCALM1 induces strong opsin expression in the mouse motor cortex for behavioral modulations•pCALM1 constitutes an all-in-one SpCas9-expressing AAV for in vivo neuronal genome editing
Wang et al. designed an ultra-compact promoter, pCALM1, which can induce robust and specific gene expression in neurons, but not glia, in rodent and primate brains. pCALM1 efficiently mediates anatomical, functional, and genetic interrogations specifically targeted to neurons.
The carboniferous carbonate reservoirs in the North Truva Oilfield have undergone complex sedimentation, diagenesis and tectonic transformation. Various reservoir spaces of pores, caves and ...fractures, with strong reservoir heterogeneity and diverse pore structures, have been developed. As a result, a quantitative description of the pore structure is difficult, and the accuracy of logging identification and prediction is low. These pose a lot of challenges to reservoir classification and evaluation as well as efficient development of the reservoirs. This study is based on the analysis of core, thin section, scanning electron microscope, high-pressure mercury injection and other data. Six types of petrophysical facies, PG1, PG2, PG3, PG4, PG5, and PG6, were divided according to the displacement pressure, mercury removal efficiency, and median pore-throat radius isobaric mercury parameters, combined with the shape of the capillary pressure curve. The petrophysical facies of the wells with mercury injection data were divided accordingly, and then the machine learning method was applied. The petrophysical facies division results of two mercury injection wells were used as training samples. The artificial neural network (ANN) method was applied to establish a training model of petrophysical facies recognition. Subsequently, the prediction for the petrophysical facies of each well in the oilfield was carried out, and the petrophysical facies division results of other mercury injection wells were applied to verify the prediction. The results show that the overall coincidence rate for identifying petrophysical facies is as high as 89.3%, which can be used for high-precision identification and prediction of petrophysical facies in non-coring wells.
Jurassic strata in the ST gas field of the northern West Siberia Basin have been regarded as a potential exploration target with undiscovered hydrocarbon resources. However limited research has been ...performed on the sequence stratigraphy of the Jurassic strata, as well as its sandstone distribution controlled by variable sea level change and sediment input. In this paper, four third-order sequences (SQ1, SQ2, SQ3, and SQ4) and nine fourth-order sequences for the Jurassic strata are interpreted based on seismic facies analysis and the lithology stacking patterns of seven wells. SQ1 is characterized by the special Bazhenov Formation which is featured by regionally distributed deep marine shales. SQ2 (J1) is composed of a coarsening upward sequence, the base of which is an unconformable surface that can be recognizable in both seismic profiles and well logging data. SQ3 (J2-J8) is composed of a complete fining-upward and coarsening-upward sequence, showing a series of transgressive and regressive successions. A complete SQ4 has not been drilled through by all the seven wells, only showing a coarsening upward succession on its top (J9) which evolves into a fining upward succession at the base of SQ3. Combined with the seismic inversion result, which predicts sandstone distribution, a sequence evolution model was built for SQ3 showing a full unit of transgressive system tract and highstand system tract (TST-HST) which often occurs in shallow marine shelves. During sequence development, most reservoir sandstones are deposited in the shelf and tidal delta environment at the bottom of the TST and the top of HST, and mudstones are deposited as shelf mudstones, especially at maximum flooding surface. That is controlled by both accommodation and sediment input. Generally, under this sequence framework, the depositional architecture can be further analyzed with implications for source rock, reservoir sandstones, and sealing rock, which may guide future gas exploration and exploitation in this area.
In sparse dictionary learning based face recognition (FR), a discriminative dictionary is learned from the training set so that good classification performance can be achieved on probe set. In order ...to achieve better performance and less computation, dimensionality reduction is applied on source data before training. Most of the proposed dictionary learning methods learn features and dictionary separatively, which may decrease the power of dictionary learning because the classification ability of dictionary learning method is based on data structure of source domain. Therefore, a sparse embedded dictionary learning method (SEDL) is proposed, of which dictionary learning and dimensionality reduction are jointly realized and the margin of coefficients distance between between-class and within-class is encourage to be large in order to enhance the classification ability and gain discriminative information. Moreover, orthogonality of the projection matrix is preserved which is critical to data reconstruction. And data reconstruction is considered to be important for sparse representation. In this paper, an extension of discriminant dictionary learning and sparse embedding is proposed and realized with novel strategies. Experiments show that our method achieves better performance than other state-of-art methods on face recognition.
•A sparse embedded dictionary learning method is proposed.•Dictionary learning and dimensionality reduction are jointly realized.•Orthogonality of the projection matrix is preserved during the training stage.
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