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Abstract Open banking is an emerging business model that is representative of FinTech. To explore whether inclusive FinTech can improve bank performance and identify the underlying mechanisms by which this occurs, we investigate a sample of Chinese commercial banks involved in open banking during 2011–2020. The results show that inclusive FinTech can improve bank performance by improving the bank’s lending rate and liability structure, and that this positive effect is more pronounced in national and rural banks. The results indicate that inclusive FinTech has the greatest impact among banks serving the largest population and those who are excluded from the traditional financial system, and that financial inclusion does not detract from bank performance. However, the results do not provide evidence that inclusive FinTech improves bank performance by reducing risk-taking, suggesting a greater need for inclusive FinTech to focus on risk management. This study adds empirical evidence regarding the role of inclusive FinTech in banks. To promote inclusive FinTech and bank performance, developing economies like China should strengthen digital financial innovations, focus on risk management, and promote cooperation under the open finance framework.

The influence of TiN addition on the new precipitation sequence and hardening effects of TiN modified Al-Mn-Sc alloy processed by LPBF was systematically studied in this work. The diffusion behavior of TiN particles results in obvious difference in the main alloying elements concentrations, altering the lattice constants of both primary and secondary L12-Al3(Ti,Sc,Zr) precipitates in the alloy matrix composite. After being subjected to peak-aging treatment, a novel precipitation sequence was observed in the sample containing 1.5 wt% TiN via generating a higher volume fraction of coherent L12-Al3Sc and semi-coherent rod-like Al6(Mn,Fe) precursors, corresponding to an alleviated internal strain as well. This new phenomenon has been demonstrated as a novel hardening mechanisms contributing to both microstructure refinement and mechanical property enhancement. As the results, the sample containing 1.5 wt% TiN exhibits an ultra-high yield strength of 651 ± 7 MPa and a compensate fracture elongation rate of 3.9 ± 0.3 %.

ABSTRACT The interaction between Z-DNA binding protein 1 (ZBP1) and the NLR family pyrin domain-containing 3 (NLRP3) inflammasome has been uncovered in several viral infections. However, the role of this molecular pathway during infection with the alpha-herpesvirus pseudorabies virus (PRV) remains largely elusive. Here, we report that during PRV infection, ZBP1-mediated NLRP3 inflammasome activation is inhibited by the viral tegument protein VP22, thereby facilitating viral infection. Through a combination of RNA sequencing and genetic studies, we demonstrate that PRV VP22 functions as a virus-encoded virulence factor by evading the inhibitory effects of ZBP1 on virus infection. Importantly, the replication and pathogenicity of a recombinant PRV lacking VP22 are significantly increased in ZBP1-deficient cells and mice. Mechanistically, PRV VP22 interacts with ZBP1, impeding the recruitment of receptor-interacting protein kinase 3 and Caspase-8, thereby inhibiting NLRP3 activation. Furthermore, we show that the N-terminal 1–50 amino acid domain of VP22 dominantly destabilizes ZBP1-mediated function. Taken together, these findings identify a functional link between PRV infection and ZBP1-mediated NLRP3 inflammatory response, providing novel insights into the pathogenesis of PRV and other herpesviruses.IMPORTANCEZ-DNA binding protein 1 (ZBP1) functions as a pivotal innate immune sensor that regulates inflammatory cell death during viral infections. However, its role in pseudorabies virus (PRV) infection remains unknown. Here, we demonstrate that ZBP1 serves as a restrictive factor by triggering the activation of the NLR family pyrin domain-containing 3 inflammasome, a process counteracted by PRV-encoded protein VP22. Furthermore, VP22 interferes with the interaction between ZBP1 and receptor-interacting protein kinase 3/Caspase-8, particularly through its N-terminal 1–50 amino acids. Importantly, deficiency in ZBP1 enhances the replication and virulence of recombinant viruses lacking VP22 or its N-terminal 1–50 amino acids. These findings reveal how PRV escapes ZBP1-mediated inflammatory responses during infection, potentially informing the rational design of therapeutic interventions.

Abstract Background Aging is associated with significant structural and functional changes in the spleen, leading to immunosenescence, yet the detailed effects on splenic vascular endothelial cells (ECs) and their immunomodulatory roles are not fully understood. In this study, a single-cell RNA (scRNA) atlas of EC transcriptomes from young and aged mouse spleens was constructed to reveal age-related molecular changes, including increased inflammation and reduced vascular development and also the potential interaction between splenic endothelial cells and immune cells. Results Ten clusters of splenic endothelial cells were identified. DEGs analysis across different EC clusters revealed the molecular changes with aging, showing the increase in the overall inflammatory microenvironment and the loss in vascular development function of aged ECs. Notably, four EC clusters with immunological functions were identified, suggesting an Endothelial-to-Immune-like Cell Transition (EndICLT) potentially driven by aging. Pseudotime analysis of the Immunology4 cluster further indicated a possible aging-induced transitional state, potentially initiated by Ctss gene activation. Finally, the effects of aging on cell signaling communication between different EC clusters and immune cells were analyzed. Conclusions This comprehensive atlas elucidates the complex interplay between ECs and immune cells in the aging spleen, offering new insights into endothelial heterogeneity, reprogramming, and the mechanisms of immunosenescence.

In this work, the various amount of Nb powder was mechanically mixed into the Cu–Al–Mn shape memory alloys (SMAs) to prepare quaternary SMAs by laser powder bed fusion (LPBF). Altered microstructure, transformation behaviour of alloys and its underlying mechanisms were analyzed. Corresponding shape memory effect (SME) was also studied. Result shows that Nb content has significant effect on the microstructure, phase transition temperatures (TTs) and SME. The microstructure of the alloy was refined by addition of appropriate Nb content. The formation of precipitates and massive grain boundaries after the addition of Nb caused a reduction of TTs and wide thermal hysteresis. Sample with 1 at%Nb containing fine and small volume fraction precipitate shows the best available strain.

The current work aims to explore the suitable drying technique for peanut pods which can be used for seeds or edible peanuts. Four drying methods, namely naturally-open sun drying as the control check (CK), hot air drying (HAD), pulsed vacuum drying (PVD), and radio frequency combined hot air drying (RF-HAD), were employed to dry peanut pods, and their effects on the nutritional quality attributes in terms of protein, fat, fatty acid contents, etc., germination characteristics, microstructure, color, texture, acid value and peroxide value of peanuts were explored. Mathematical models of peanuts drying with four drying methods were also established. According to the statistical parameters including the determination coefficient (R2)、root mean square error (RMSE) and chi-square value (χ2), the Weibull model was best for predicting the moisture ratio change kinetics of peanuts during its four drying processes. There were significant differences in physicochemical indexes of peanut by different drying methods (p

[Introduction] Since the power line has the characteristics of long transmission distance and a complex spatial environment, the UAV LiDAR point cloud technology can completely and efficiently obtain the geometric information of the power line and its surrounding spatial objects, and the existing supervised extraction and unsupervised extraction methods are deficient in point cloud data extraction in a large range of complex environments, according to the spatial environment characteristics of the main network and distribution network line point cloud data, a rapid extraction method of point cloud power line is proposed based on projection line characteristics and region growing algorithm. [Method] Firstly, in view of the characteristics that the overhead lines of the main network were usually higher than the surrounding spatial objects, the power lines were roughly extracted by the elevation histogram threshold method. Then, considering the characteristics that the vegetation canopy was higher than the distribution network line in the distribution network area, the KNN data points of the roughly extracted power line point cloud were obtained, and the point cloud was projected on the horizontal plane, and whether the point cloud was a power line point cloud was judged by the linear measurement of the point cloud. [Result] According to the existence of missing power line point clouds, all the power line point cloud clusters are obtained through a region growing mode, and on this basis, the catenary formula of each power line point cloud cluster is calculated through the catenary formula, and the point cloud with a fitting distance less than the threshold is merged as the same power line point cloud. [Conclusion] The proposed method aims at the problem of rapid power line extraction in inspection applications and overcomes the problem of power line point cloud missing and vegetation impact in the process of power line extraction, so this method can achieve power line point cloud extraction with high efficiency and accuracy.

Stable pressure control can improve the lifespan, efficiency, and stability of proton exchange membrane fuel cell system (PEMFCs). We successfully implemented a feedforward-based proportion-integral controller (FPIC) to control the anode pressure of a 100 kW fuel cell system. The bench experimental results demonstrate that the fuel cell stack achieves a maximum efficiency of 62.3 %, while the fuel cell power generation system achieve a maximum efficiency of 53.5 %. Under the steady-state and dynamic conditions, the strategy achieves a pressure tracking control accuracy of 98.93 % and 94.47 %, respectively. To address the large overshoot phenomenon and slow response speed of the FPIC when controlling the anode pressure, we further design a second order active disturbance rejection controller (SOADRC). The simulation results show that the SOADRC exhibits higher control stability and lower overshoot than FPIC. Moreover, it demonstrates a 51.3 % increase in response speed and an 80.7 % improvement in control stability under steady-state conditions compared to FPIC. The evaluation metrics for the error integral criterion (eISE = 0.023, eITSE = 2.58, eIAE = 0.35, and eIEAE = 36.76) are lower than FPIC, which demonstrates that the SOADRC provides more precise control of anode pressure, and enhances the stability of PEMFCs.

Ptosis is a common ophthalmologic condition, and the diagnosis is primarily based on ocular appearance. The diagnosis of such conditions can be improved using emerging technology such as artificial intelligence-based methods. However, unified data collection and labeling standards have not yet been established. This directly impacts the accuracy of ptosis diagnosis based on appearance alone. Therefore, in the present study, we aimed to establish a procedure to obtain and label images to devise a recommendation system for optimal recognition of ptosis based on ocular appearances. This would help to standardize and facilitate data sharing and serve as a guideline for the development and improvisation of algorithms in artificial intelligence for ptosis.

Mechanical and corrosion behaviors perpendicular to build direction (XOY) and along build direction (XOZ) of UNS S31803 duplex stainless steel (DSS) fabricated by laser powder bed fusion (LPBF) were investigated. With the post-annealing, the steel exhibited a ferrite-austenite microstructure. For XOY plane, austenite displayed a primarily texture while ferrite kept preferred orientation, and mainly held a Nishiyama-Wassermann orientation relationship. However, for XOZ plane, austenite showed a mixed texture. The average size of ferrite grains was larger for XOZ plane than XOY. The austenite in XOY plane was mostly island morphology grains, while in XOZ plane, there were a large number of coarse columnar grains. A higher geometrically necessary dislocation density and proportion of low-angle grain boundaries on XOY plane were observed. The yield strength and ultimate tensile strength values perpendicular to build direction were higher than those along build direction. While the total elongation perpendicular to build direction was lower. Moreover, the XOY plane shows slightly better corrosion resistance than the XOZ.

In this paper, a novel design strategy for l-PBFed AlMnMgScZr/TiN composites with ultrahigh strength was proposed. TiN particles can not only function as ceramic reinforcement, but also decompose and reprecipitate to form a large density of L12-precipitates at a high melting temperature during l-PBF. Meanwhile, the primary L12-Al3X (X=Ti/Sc/Zr) phase promotes the columnar-to-equiaxed grain transition effect, creating a fine bi-modal grain structure in the as-built sample. A high volume fraction of L12 nanoparticles are additionally precipitated from Al matrix during post heat treatment. In this regard, effective grain refinement and precipitation hardening mechanism contribute to an excellent tensile performance with a combination of an ultimate tensile strength of 681±4 MPa, a yield strength of 677±4 MPa, and an elongation rate of 5.4 ± 1.2%. The yield strength of 677 MPa is particularly the highest among all previously reported l-PBFed Al matrix composites and Al alloys.

Summary: Patients with Graves’ disease (GD) can develop Graves’ ophthalmopathy (GO), but the underlying pathological mechanisms driving this development remain unclear. In our study, which included patients with GD and GO, we utilized single-cell RNA sequencing (scRNA-seq) and multiplatform analyses to investigate CD169+ classical monocytes, which secrete proinflammatory cytokines and are expanded through activated interferon signaling. We found that CD169+ clas_mono was clinically significant in predicting GO progression and prognosis, and differentiated into CD169+ macrophages that promote inflammation, adipogenesis, and fibrosis. Our murine model of early-stage GO showed that CD169+ classical monocytes accumulated in orbital tissue via the Cxcl12-Cxcr4 axis. Further studies are needed to investigate whether targeting circulating monocytes and the Cxcl12-Cxcr4 axis could alleviate GO progression.

Abstract Background To investigate the anti-inflammatory and antioxidative effects of gallic acid (GA) on human corneal epithelial cells (HCECs) and RAW264.7 macrophages as well as its therapeutic effects in an experimental dry eye (EDE) mouse model. Methods A cell counting kit-8 (CCK-8) assay was used to test the cytotoxicity of GA. The effect of GA on cell migration was evaluated using a scratch wound healing assay. The anti-inflammatory and antioxidative effects of GA in vitro were tested using a hypertonic model (HCECs) and an inflammatory model (RAW264.7 cells). The in vivo biocompatibility of GA was detected by irritation tests in rabbits, whereas the preventive and therapeutic effect of GA in vivo was evaluated using a mouse model of EDE. Results In the range of 0–100 μM, GA showed no cytotoxicity in RAW264.7 cells or HCECs and did not delay the HCECs monolayer wound healing within 24 h. Ocular tolerance to GA in the in vivo irritation test was good after seven days. In terms of antioxidative activity, GA significantly reduced the intracellular reactive oxygen species (ROS) in lipopolysaccharide (LPS) activated RAW264.7 macrophages and HCECs exposed to hyperosmotic stress. Furthermore, after pre-treatment with GA, the expression levels of nuclear factor E2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), and NADPH quinone oxidoreductase-1 (NQO-1) were significantly upregulated in RAW264.7 macrophages. GA also exhibits excellent anti-inflammatory properties. This is mainly demonstrated by the ability of GA to effectively downregulate the nuclear transcription factor-κB (NF-κB) pathway in LPS-activated RAW264.7 macrophages and to reduce inflammatory factors, such as nitric oxide (NO), interleukin 6 (IL-6), and tumor necrosis factor alpha (TNF-α). In vivo efficacy testing results in a mouse model of EDE showed that GA can effectively prevent and inhibit the apoptosis of corneal epithelial cells (CECs), reduce inflammatory factors in the cornea and conjunctiva as well as protect goblet cells. Conclusion In vitro and in vivo results indicate that GA possesses potent anti-inflammatory and antioxidative properties with no apparent cytotoxicity within the range of 0–100 μM. It is a promising eye drop formulation for the effective prevention and treatment of dry eye disease (DED).

IntroductionSeasonal influenza A H3N2 viruses are constantly changing, reducing the effectiveness of existing vaccines. As a result, the World Health Organization (WHO) needs to frequently update the vaccine strains to match the antigenicity of emerged H3N2 variants. Traditional assessments of antigenicity rely on serological methods, which are both labor-intensive and time-consuming. Although numerous computational models aim to simplify antigenicity determination, they either lack a robust quantitative linkage between antigenicity and viral sequences or focus restrictively on selected features.MethodsHere, we propose a novel computational method to predict antigenic distances using multiple features, including not only viral sequence attributes but also integrating four distinct categories of features that significantly affect viral antigenicity in sequences.ResultsThis method exhibits low error in virus antigenicity prediction and achieves superior accuracy in discerning antigenic drift. Utilizing this method, we investigated the evolution process of the H3N2 influenza viruses and identified a total of 21 major antigenic clusters from 1968 to 2022.DiscussionInterestingly, our predicted antigenic map aligns closely with the antigenic map generated with serological data. Thus, our method is a promising tool for detecting antigenic variants and guiding the selection of vaccine candidates.

Esophageal squamous cell carcinoma (ESCC) consistently ranks as one of the most challenging variants of squamous cell carcinomas, primarily due to the lack of effective early detection strategies. We herein aimed to elucidate the underlying mechanisms and biological role associated with A-kinase anchoring protein 12 (AKAP12) in the context of ESCC. Bioinformatic analysis had revealed significantly lower expression level of AKAP12 in ESCC tissue samples than in their non-cancerous counterparts. To gain deeper insights into the potential role of AKAP12 in the progression of ESCC, we conducted a single-gene set enrichment analysis of AKAP12 on ESCC datasets. Our findings suggested that AKAP12 exhibits functions inhibiting cell cycle progression, tumor proliferation, and epithelial-mesenchymal transition. To further validate our findings, we subjected ESCC cell lines to AKAP12 overexpression using CRISPR/Cas9-SAM. In vitro analyses demonstrated that increased expression of AKAP12 significantly reduced cell proliferation, migration, and cell cycle progression. Simultaneously, genes associated with this biological role undergo corresponding regulatory shifts. These observations provided valuable insights into the biological role played by AKAP12 in ESCC progression. In summary, AKAP12 shows promise as a new potential biomarker for early ESCC diagnosis, offering potential advantages for subsequent therapeutic intervention and disease management.

BackgroundCoronary artery disease (CAD) is a main cause leading to increasing mortality of cardiovascular disease (CVD) worldwide. We aimed to discover marker genes and develop a diagnostic model for CAD.MethodsCAD-related target genes were searched from DisGeNET. Count expression data and clinical information were screened from the GSE202626 dataset. edgeR package identified differentially expressed genes (DEGs). Using online STRING tool and Cytoscape, protein-protein reactions (PPI) were predicted. WebGestaltR package was employed to functional enrichment analysis. We used Metascape to conduct module-based network analysis. VarElect algorithm provided genes-phenotype correlation analysis. Immune infiltration was assessed by ESTIMATE package and ssGSEA analysis. mRNAsi was determined by one class logistic regression (OCLR). A diagnostic model was constructed by SVM algorithm.Results162 target genes were screened by intersection 1,714 DEGs and 1,708 CAD related target genes. 137 target genes of the 162 target genes were obtained using PPI analysis, in which those targets were enriched in inflammatory cytokine pathways, such as chemokine signaling pathway, and IL-17 signaling pathway. From the above 137 target genes, four functional modules (MCODE1-4) were extracted. From the 162 potential targets, CAD phenotype were directly and indirectly associated with 161 genes and 22 genes, respectively. Finally, 5 hub genes (CCL2, PTGS2, NLRP3, VEGFA, LTA) were screened by intersections with the top 20, directly and indirectly, and genes in MCODE1. PTGS2, NLRP3 and VEGFA were positively, while LTA was negatively correlated with immune cells scores. PTGS2, NLRP3 and VEGFA were negatively, while LTA was positively correlated with mRNAsi. A diagnostic model was successfully established, evidenced by 92.59% sensitivity and AUC was 0.9230 in the GSE202625 dataset and 94.11% sensitivity and AUC was 0.9706 in GSE120774 dataset.ConclusionIn this work, we identified 5 hub genes, which may be associated with CAD development.

With the rapid development of networks, the traffic in the networks has increased sharply, resulting in frequent congestion, especially in spatial networks, such as the railway network, aviation network, and sensor network, and congestion not only affects the user’s experience but also causes serious economic losses. Therefore, in this paper, we effectively identify the high-load nodes in spatial networks by considering harmony centrality and degree. On this basis, we design the HD routing strategy by avoiding these key nodes, which can enhance the traffic throughput of spatial networks efficiently. The results provide new ideas and directions for the design of routing strategies for spatial networks.

Boosting transcorneal permeability and pharmacological activity of drug poses a great challenge in the field of ocular drug delivery. In the present study, we propose a drug-peptide supramolecular hydrogel based on anti-inflammatory drug, dexamethasone (Dex), and Arg-Gly-Asp (RGD) motif for boosting transcorneal permeability and pharmacological activity via the ligand-receptor interaction. The drug-peptide (Dex-SA-RGD/RGE) supramolecular hydrogel comprised of uniform nanotube architecture formed spontaneously in phosphate buffered saline (PBS, pH = 7.4) without external stimuli. Upon storage at 4 °C, 25 °C, and 37 °C for 70 days, Dex-SA-RGD in hydrogel did not undergo significant hydrolysis, suggesting great long-term stability. In comparison to Dex-SA-RGE, Dex-SA-RGD exhibited a more potent in vitro anti-inflammatory efficacy in lipopolysaccharide (LPS)-activated RAW 264.7 macrophages via the inhibition of nuclear factor кB (NF-κB) signal pathway. More importantly, using drug-peptide supramolecular hydrogel labeled with 7-nitro-2,1,3-benzoxadiazole (NBD), the Dex-SA-K(NBD)RGD showed increased performance in terms of integrin targeting and cellular uptake compared to Dex-SA-K(NBD)RGE, as revealed by cellular uptake assay. On topical instillation in rabbit's eye, the proposed Dex-SA-K(NBD)RGD could effectively enhance the transcorneal distribution and permeability with respect to the Dex-SA-K(NBD)RGE. Overall, our findings demonstrate the performance of the ligand-receptor interaction for boosting transcorneal permeability and pharmacological activity of drug.

Quantitative and mechanistic understanding of learning and long-term memory at the level of single neurons in living brains require highly demanding techniques. A specific need is to precisely label one cell whose firing output property is pinpointed amidst a functionally characterized large population of neurons through the learning process and then investigate the distribution and properties of dendritic inputs. Here, we disseminate an integrated method of daily two-photon neuronal population Ca2+ imaging through an auditory associative learning course, followed by targeted single-cell loose-patch recording and electroporation of plasmid for enhanced chronic Ca2+ imaging of dendritic spines in the targeted cell. Our method provides a unique solution to the demand, opening a solid path toward the hard-cores of how learning and long-term memory are physiologically carried out at the level of single neurons and synapses.

BackgroundConversational agents (CAs) have been developed in outpatient departments to improve physician-patient communication efficiency. As end users, patients’ continuance intention is essential for the sustainable development of CAs. ObjectiveThe aim of this study was to facilitate the successful usage of CAs by identifying key factors influencing patients’ continuance intention and proposing corresponding managerial implications. MethodsThis study proposed an extended expectation-confirmation model and empirically tested the model via a cross-sectional field survey. The questionnaire included demographic characteristics, multiple-item scales, and an optional open-ended question on patients’ specific expectations for CAs. Partial least squares structural equation modeling was applied to assess the model and hypotheses. The qualitative data were analyzed via thematic analysis. ResultsA total of 172 completed questionaries were received, with a 100% (172/172) response rate. The proposed model explained 75.5% of the variance in continuance intention. Both satisfaction (β=.68; P

Green technology innovation is an important means to help reduce carbon emissions. Most of the current researches focus on the evaluation of green technology innovation and its relationship with economic factors, while ignoring its relationship with financial factors. In fact, financial development is an important driving force for further improving the efficiency of technological innovation, especially in developing countries. China, which has put forward the “double carbon” strategy (achieve peak carbon dioxide emission and carbon neutrality) in recent years, has a lot of interaction between green technology innovation and financial development, which is a good research sample. Based on the provincial panel data of 30 provinces in China from 2003 to 2020, this paper follows the research steps: 1) From the perspective of carbon emissions, we use the non-radial super-efficiency SBM-ML model to measure the total factor productivity of green technology innovation. 2) We analyze the temporal and spatial changes of green technology innovation and financial agglomeration in each province. 3) We establish a spatial simultaneous model of generalized three-stage least squares to study the intrinsic relationship between green technology innovation and financial agglomeration. The results show that: 1) The financial agglomeration level of each province is basically stable due to the fixedness of the financial core area, but the development speed of green technology innovation in the southeast coastal area is significantly higher than that in the inland area. 2) The interaction between green technology innovation and financial agglomeration has a nonlinear mechanism of “low-level inhibition and high-level promotion,” that is, low-level financial agglomeration has an inhibitory effect on green technology innovation, and as the level of financial agglomeration increases, its impact on green technology innovation gradually develops positively, and vice versa. 3) The green technology innovation and financial agglomeration in the surrounding provinces have positive and significant promoting effects on the green technology innovation and financial agglomeration in the province, but the impact of green technology innovation is significantly stronger than that of financial agglomeration. Finally, suggestions are put forward for further reducing carbon emissions, realizing the sustainable economic growth and approaching goals of “carbon peaking and carbon neutrality.”

Purpose: Obtaining a better understanding of the pathogenesis of primary angle-closure disease (PACD) still requires studies that provide measurements of anterior and posterior biometric characteristics together and that assess the relationship between them. Methods: In total, 201 eyes were enrolled in this cross-sectional study: 50 normal controls, 49 primary angle-closure suspect (PACS), 38 primary angle closure (PAC), and 64 primary angle-closure glaucoma (PACG) eyes. The anterior and posterior structural features were measured by anterior segment optical coherence tomography and swept-source optical coherence tomography. Results: All PACD groups had smaller anterior chamber depth (ACD), anterior chamber area (ACA), anterior chamber volume (ACV), angle opening distance at 750 μm from the scleral spur (AOD750), trabecular–iris space area at 750 μm from the scleral spur (TISA750), and angle recess area (ARA), as well as a larger lens vault (LV), than controls (all P < 0.001). The PACS and PAC groups had thicker iris thickness at 750 μm from the scleral spur (IT750) than controls (P = 0.017 and P = 0.002, respectively). Choroidal thickness (CT) was not statistically different among normal, PACS, PAC, and PACG eyes. Univariate and multivariate linear regression analysis revealed a significant association between thinner IT750 and increased CT in PACD eyes (P = 0.031, univariate analysis; P = 0.008, multivariate analysis). Conclusion: Thinner iris thickness was associated with increased CT in PACD eyes; however, the underlying mechanism needs further investigation.

Abstract By 2040, ~100 million people will have glaucoma. To date, there are a lack of high-efficiency glaucoma diagnostic tools based on visual fields (VFs). Herein, we develop and evaluate the performance of ‘iGlaucoma’, a smartphone application-based deep learning system (DLS) in detecting glaucomatous VF changes. A total of 1,614,808 data points of 10,784 VFs (5542 patients) from seven centers in China were included in this study, divided over two phases. In Phase I, 1,581,060 data points from 10,135 VFs of 5105 patients were included to train (8424 VFs), validate (598 VFs) and test (3 independent test sets—200, 406, 507 samples) the diagnostic performance of the DLS. In Phase II, using the same DLS, iGlaucoma cloud-based application further tested on 33,748 data points from 649 VFs of 437 patients from three glaucoma clinics. With reference to three experienced expert glaucomatologists, the diagnostic performance (area under curve [AUC], sensitivity and specificity) of the DLS and six ophthalmologists were evaluated in detecting glaucoma. In Phase I, the DLS outperformed all six ophthalmologists in the three test sets (AUC of 0.834–0.877, with a sensitivity of 0.831–0.922 and a specificity of 0.676–0.709). In Phase II, iGlaucoma had 0.99 accuracy in recognizing different patterns in pattern deviation probability plots region, with corresponding AUC, sensitivity and specificity of 0.966 (0.953–0.979), 0.954 (0.930–0.977), and 0.873 (0.838–0.908), respectively. The ‘iGlaucoma’ is a clinically effective glaucoma diagnostic tool to detect glaucoma from humphrey VFs, although the target population will need to be carefully identified with glaucoma expertise input.

Using a combination of two-photon imaging and single-cell electrophysiology, the authors discover that associative learning induces the emergence of a unique subset of neurons in the auditory cortex, exhibiting high-rate bursting responses to the learned complex sounds but not to any of the constituents.

Two-photon Ca2+ imaging is a widely used technique for investigating brain functions across multiple spatial scales. However, the recording of neuronal activities is affected by movement of the brain during tasks in which the animal is behaving normally. Although post-hoc image registration is the commonly used approach, the recent developments of online neuroscience experiments require real-time image processing with efficient motion correction performance, posing new challenges in neuroinformatics. We propose a fast and accurate image density feature-based motion correction method to address the problem of imaging animal during behaviors. This method is implemented by first robustly estimating and clustering the density features from two-photon images. Then, it takes advantage of the temporal correlation in imaging data to update features of consecutive imaging frames with efficient calculations. Thus, motion artifacts can be quickly and accurately corrected by matching the features and obtaining the transformation parameters for the raw images. Based on this efficient motion correction strategy, our algorithm yields promising computational efficiency on imaging datasets with scales ranging from dendritic spines to neuronal populations. Furthermore, we show that the proposed motion correction method outperforms other methods by evaluating not only computational speed but also the quality of the correction performance. Specifically, we provide a powerful tool to perform motion correction for two-photon Ca2+ imaging data, which may facilitate online imaging experiments in the future.

This research studies the optimal consumption, investment, and life insurance choices for a wage earner with habit formation, inflation risk, and mortality risk. The wage earner has access to a risk-free asset, an index bond, and a stock in a financial market. The index bond hedges inflation risk, while life insurance hedges mortality risk. The aim of the wage earner is to maximize the expected utility of consumption, bequest, and terminal wealth, where the utility of consumption comes from the part of the consumption that exceeds a minimum consumption requirement given by the habit level. By using the dynamic programming method, we provide and prove a verification theorem and obtain closed-form expressions for the value function, the optimal life insurance premium rate, and the optimal investment and consumption strategies. Numerical results reveal that habit formation and mortality force change play important roles in the financial behaviors of the wage earner. Especially, the impacts of the expected inflation rate and consumption habit on the optimal strategies are mutual restraint; increasing mortality force raises the demand for life insurance; and the effects of other parameters are also affected by consumption habit and mortality force change.

Cistanche deserticola is one of the most precious plants, traditionally as Chinese medicine, and has recently been used in pharmaceutical and healthy food industries. Steaming and drying are two important steps in the processing of Cistanche deserticola. Unfortunately, a comprehensive understanding of the chemical composition changes of Cistanche deserticola during thermal processing is limited. In this study, ultra-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS)-based widely targeted metabolomics analysis was used to investigate the transformation mechanism of Cistanche deserticola active compounds during steaming and drying processes. A total of 776 metabolites were identified in Cistanche deserticola during thermal processing, among which, 77 metabolites were differentially regulated (p < 0.05) wherein 39 were upregulated (UR) and 38 were downregulated (DR). Forty-seven (17 UR, 30 DR) and 30 (22 UR, 8 DR) differential metabolites were identified during steaming and drying, respectively. The most variation of the chemicals was observed during the process of steaming. Metabolic pathway analysis indicated that phenylpropanoid, flavonoid biosynthesis, and alanine metabolism were observed during steaming, while glycine, serine, and threonine metabolism, thiamine metabolism, and unsaturated fatty acid biosynthesis were observed during drying. The possible mechanisms of the chemical alterations during thermal processing were also provided by the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Furthermore, the blackening of the appearance of Cistanche deserticola mainly occurred in the steaming stage rather than the drying stage, which is associated with the metabolism of the amino acids. All results indicated that the formation of active compounds during the processing of Cistanche deserticola mainly occurred in the steaming stage.

Two-photon Ca2+ imaging is a leading technique for recording neuronal activities in vivo with cellular or subcellular resolution. However, during experiments, the images often suffer from corruption due to complex noises. Therefore, the analysis of Ca2+ imaging data requires preprocessing steps, such as denoising, to extract biologically relevant information. We present an approach that facilitates imaging data restoration through image denoising performed by a neural network combining spatiotemporal filtering and model blind learning. Tests with synthetic and real two-photon Ca2+ imaging datasets demonstrate that the proposed approach enables efficient restoration of imaging data. In addition, we demonstrate that the proposed approach outperforms the current state-of-the-art methods by evaluating the qualities of the denoising performance of the models quantitatively. Therefore, our method provides an invaluable tool for denoising two-photon Ca2+ imaging data by model blind spatiotemporal processing.

The olivocerebellar circuitry is important to convey both motor and non-motor information from the inferior olive (IO) to the cerebellar cortex. Several methods are currently established to observe the dynamics of the olivocerebellar circuitry, largely by recording the complex spike activity of cerebellar Purkinje cells; however, these techniques can be technically challenging to apply in vivo and are not always possible in freely behaving animals. Here, we developed a method for the direct, accessible, and robust recording of climbing fiber (CF) Ca2+ signals based on optical fiber photometry. We first verified the IO stereotactic coordinates and the organization of contralateral CF projections using tracing techniques and then injected Ca2+ indicators optimized for axonal labeling, followed by optical fiber-based recordings. We demonstrated this method by recording CF Ca2+ signals in lobule IV/V of the cerebellar vermis, comparing the resulting signals in freely moving mice. We found various movement-evoked CF Ca2+ signals, but the onset of exploratory-like behaviors, including rearing and tiptoe standing, was highly synchronous with recorded CF activity. Thus, we have successfully established a robust and accessible method to record the CF Ca2+ signals in freely behaving mice, which will extend the toolbox for studying cerebellar function and related disorders.

Since similar complex diseases are much alike in clinical symptoms, patients are easily misdiagnosed and mistreated. It is crucial to accurately predict the disease status and identify markers with high sensitivity and specificity for classifying similar complex diseases. Many approaches incorporating network information have been put forward to predict outcomes, but they are not robust because of their low reproducibility. Several pathway-based methods are robust and functionally interpretable. However, few methods characterize the disease-specific states of single samples from the perspective of pathways. In this study, we propose a novel framework, Pathway Activation for Single Sample (PASS), which utilizes the pathway information in a single sample way to better recognize the differences between two similar complex diseases. PASS can mainly be divided into two parts: for each pathway, the extent of perturbation of edges and the statistic difference of genes caused by a single disease sample are quantified; then, a novel method, named as an AUCpath, is applied to evaluate the pathway activation for single samples from the perspective of genes and their interactions. We have applied PASS to two main types of inflammatory bowel disease (IBD) and widely verified the characteristics of PASS. For a new patient, PASS features can be used as the indicators or potential pathway biomarkers to precisely diagnose complex diseases, discover significant features with interpretability and explore changes in the biological mechanisms of diseases.

Tailoring the terminal motif of molecules including drugs might significantly affect their self-assembly tendency in aqueous solution, thus providing a rational strategy to modulate its macroscopic characteristics of supramolecular assembly. A model drug of dexamethasone (Dex) was esterified by different fatty acids [succinic acid (SA), glutaric acid (GA), and adipic acid (AA)] and aromatic acid [phthalic acid (PA)] to generate a series of Dex derivatives. Aqueous solution of Dex-SA, Dex-GA, and Dex-AA turned into hydrogel spontaneously after a period time of incubation (24, 48, and 72 h, respectively) via the auto-hydrolytic strategy, while aqueous solution of Dex-PA did not result in hydrogelation during 3 days of incubation. Aqueous solutions of Dex-SA, Dex-GA, and Dex-AA underwent apparent hydrolysis (10.73 ± 0.64%, 15.17 ± 2.24%, and 17.29 ± 1.39%, respectively), while Dex-PA exhibited a minimal hydrolysis (

Abstract Background To analyse the associated factors, diagnosis, clinical manifestations and therapeutic effects of Acanthamoeba keratitis at a tertiary ophthalmic centre in Southern China. Methods A retrospective clinical study was performed in fifteen patients who were admitted to Zhongshan Ophthalmic Centre (ZOC) from January 2004 to December 2014. The patients’ pathogenesis-associated factors were analysed, and preoperative diagnoses were determined using corneal scraping cultures and/or confocal microscopy followed. All diagnoses were confirmed by postoperative pathological examinations. At follow-up, best-corrected visual acuity (BCVA), the recurrence rate and graft transparency were evaluated to assess therapeutic effects. Results The main pathogenic factors observed in the fifteen patients were a history of injury or a foreign body entering the eyes (12 cases). In all, Acanthamoeba keratitis was preoperatively diagnosed in 5 cases using corneal scraping cultures or confocal microscopy. Ocular symptoms included redness, photophobia, tearing, and blurred vision. Penetrating keratoplasty was performed in thirteen patients, and postoperative pathological examinations were performed to confirm these diagnoses. The logarithm of the minimum angle of resolution (logMAR) of visual acuity was significantly improved after keratoplasty (p

Abstract Nonhuman primates provide an important model not only for understanding human brain but also for translational research in neurological and psychiatric disorders. However, many high-resolution techniques for recording neural activity in vivo that were initially established for rodents have not been yet applied to the nonhuman primate brain. Here, we introduce a combination of two-photon targeted patching and dendritic Ca2+ imaging to the neocortex of adult common marmoset, an invaluable primate model for neuroscience research. Using targeted patching, we show both spontaneous and sensory-evoked intracellular dynamics of visually identified neurons in the marmoset cortex. Using two-photon Ca2+ imaging and intracellular pharmacological manipulation, we report both action-potential-associated global and synaptically-evoked NMDA (N-methyl-D-aspartate) receptor-mediated local Ca2+ signals in dendrites and spines of the superficial-layer cortical neurons. Therefore, we demonstrate the presence of synaptic Ca2+ signals in neuronal dendrites in living nonhuman primates. This work represents a proof-of-principle for exploring the primate brain functions in vivo by monitoring neural activity and morphology at a subcellular resolution.

Recent research shows that majority of the druggable human proteome is yet to be annotated and explored. Accurate identification of these unexplored druggable proteins would facilitate development, screening, repurposing, and repositioning of drugs, as well as prediction of new drug–protein interactions. We contrast the current drug targets against the datasets of non-druggable and possibly druggable proteins to formulate markers that could be used to identify druggable proteins. We focus on the markers that can be extracted from protein sequences or names/identifiers to ensure that they can be applied across the entire human proteome. These markers quantify key features covered in the past works (topological features of PPIs, cellular functions, and subcellular locations) and several novel factors (intrinsic disorder, residue-level conservation, alternative splicing isoforms, domains, and sequence-derived solvent accessibility). We find that the possibly druggable proteins have significantly higher abundance of alternative splicing isoforms, relatively large number of domains, higher degree of centrality in the protein-protein interaction networks, and lower numbers of conserved and surface residues, when compared with the non-druggable proteins. We show that the current drug targets and possibly druggable proteins share involvement in the catalytic and signaling functions. However, unlike the drug targets, the possibly druggable proteins participate in the metabolic and biosynthesis processes, are enriched in the intrinsic disorder, interact with proteins and nucleic acids, and are localized across the cell. To sum up, we formulate several markers that can help with finding novel druggable human proteins and provide interesting insights into the cellular functions and subcellular locations of the current drug targets and potentially druggable proteins.

The selective formation of nanomaterials in cancer cells and tumors holds great promise for cancer diagnostics and therapy. Until now, most strategies rely on a single trigger to control the formation of nanomaterials in situ. The combination of two or more triggers may provide for more sophisticated means of manipulation. In this study, we rationally designed a molecule (Comp. 1) capable of responding to two enzymes, alkaline phosphatase (ALP), and reductase. Since the A549 lung cancer cell line showed elevated levels of extracellular ALP and intracellular reductase, we demonstrated that Comp. 1 responded in a stepwise fashion to those two enzymes and displayed a tandem molecular self-assembly behavior. The selective formation of nanofibers in the mitochondria of the lung cancer cells led to the disruption of the mitochondrial membrane, resulting in an increased level of reactive oxygen species (ROS) and the release of cytochrome C (Cyt C). ROS can react with proteins, resulting in endoplasmic reticulum (ER) stress and the unfolded protein response (UPR). This severe ER stress led to disruption of the ER, formation of vacuoles, and ultimately, apoptosis of the A549 cells. Therefore, Comp. 1 could selectively inhibit lung cancer cells in vitro and A549 xenograft tumors in vivo. Our study provides a novel strategy for the selective formation of nanomaterials in lung cancer cells, which is powerful and promising for the diagnosis and treatment of lung cancer.

In vivo two-photon Ca2+ imaging is a powerful tool for recording neuronal activities during perceptual tasks and has been increasingly applied to behaving animals for acute or chronic experiments. However, the auditory cortex is not easily accessible to imaging because of the abundant temporal muscles, arteries around the ears and their lateral locations. Here, we report a protocol for two-photon Ca2+ imaging in the auditory cortex of head-fixed behaving mice. By using a custom-made head fixation apparatus and a head-rotated fixation procedure, we achieved two-photon imaging and in combination with targeted cell-attached recordings of auditory cortical neurons in behaving mice. Using synthetic Ca2+ indicators, we recorded the Ca2+ transients at multiple scales, including neuronal populations, single neurons, dendrites and single spines, in auditory cortex during behavior. Furthermore, using genetically encoded Ca2+ indicators (GECIs), we monitored the neuronal dynamics over days throughout the process of associative learning. Therefore, we achieved two-photon functional imaging at multiple scales in auditory cortex of behaving mice, which extends the tool box for investigating the neural basis of audition-related behaviors.

To measure the anterior and posterior ocular biometric characteristics concurrently and to determine the relationship between the iris and choroid in healthy Chinese subjects.A total of 148 subjects (270 eyes) were enrolled in this cross-section study. The anterior and posterior ocular biometric characteristics were measured simultaneously by anterior segment optical coherence tomography (AS-OCT) and swept-source optical coherence tomography (SS-OCT).Compared with male eyes, female eyes had narrower anterior biometric parameters that presented with smaller anterior segment parameters [including anterior chamber depth (ACD), width (ACW), area (ACA), and volume (ACV); (all p