Forebrain excitatory neuron-specific loss of Brpf1 attenuates excitatory synaptic transmission and impairs spatial and fear memory

Bromodomain and plant homeodomain(PHD)finger containing protein 1(Brpf1)is an activator and scaffold protein of a multiunit complex that includes other components involving lysine acetyltransferase(KAT)6A/6B/7.Brpf1,KAT6A,and KAT6B mutations were identified as the causal genes of neurodevelopmental disorders leading to intellectual disability.Our previous work revealed strong and specific expression of Brpf1 in both the postnatal and adult forebrain,especially the hippocampus,which has essential roles in learning and memory.Here,we hypothesized that Brpf1 plays critical roles in the function of forebrain excitatory neurons,and that its deficiency leads to learning and memory deficits.To test this,we knocked out Brpf1 in forebrain excitatory neurons using CaMKIIa-Cre.We found that Brpf1 deficiency reduced the frequency of miniature excitatory postsynaptic currents and downregulated the expression of genes Pcdhgb1,Slc16a7,Robo3,and Rho,which are related to neural development,synapse function,and memory,thereby damaging spatial and fear memory in mice.These findings help explain the mechanisms of intellectual impairment in patients with BRPF1 mutation.

Designs of 3D Mesh and Torus Optical Network-on-Chips:Topology,Optical Router and Routing Module

As a nanometer-level interconnection,the Optical Network-on-Chip(ONoC)was proposed since it was typically characterized by low latency,high bandwidth and power efficiency. Compared with a 2-Dimensional(2D)design,the 3D integration has the higher packing density and the shorter wire length. Therefore,the 3D ONoC will have the great potential in the future. In this paper,we first discuss the existing ONoC researches,and then design mesh and torus ONoCs from the perspectives of topology,router,and routing module,with the help of 3D integration. A simulation platform is established by using OPNET to compare the performance of 2D and 3D ONoCs in terms of average delay and packet loss rate. The performance comparison between 3D mesh and 3D torus ONoCs is also conducted. The simulation results demonstrate that 3D integration has the advantage of reducing average delay and packet loss rate,and 3D torus ONoC has the better performance compared with 3D mesh solution. Finally,we summarize some future challenges with possible solutions,including microcosmic routing inside optical routers and highly-efficient traffic grooming.

Interoperative fundus image and report sharing in compliance with integrating the healthcare enterprise conformance and web access to digital imaging and communication in medicine persistent object protocol

AIM:To address issues in interoperability between different fundus image systems,we proposed a web eyepicture archiving and communication system(PACS)framework in conformance with digital imaging and communication in medicine(DICOM)and health level 7(HL7)protocol to realize fundus images and reports sharing and communication through internet.METHODS:Firstly,a telemedicine-based eye care work flow was established based on integrating the healthcare enterprise(IHE)Eye Care technical framework.Then,a browser/server architecture eye-PACS system was established in conformance with the web access to DICOM persistent object(WADO)protocol,which contains three tiers.RESULTS:In any client system installed with web browser,clinicians could log in the eye-PACS to observe fundus images and reports.Multipurpose internet mail extensions(MIME)type of a structured report is saved as pdf/html with reference link to relevant fundus image using the WADO syntax could provide enough information for clinicians.Some functions provided by open-source Oviyam could be used to query,zoom,move,measure,view OICOM fundus images.CONCLUSION:Such web eye-PACS in compliance to WADO protocol could be used to store and communicate fundus images and reports,therefore is of great significance for teleophthalmology.

Clomipramine inhibits microglial NLRP3 inflammasome in the hippocampus of depressive rats

Neuroinflammation is implicated in the pathophysiology of depression.The reduction of hippocampal volume in depression remains controversial because of interindividual variability in clinical studies.Herein,we studied the effects of clomipramine,a tricyclic antidepressant(TCA)that modulates serotonin and norepinephrine uptake,on chronic mild unpredictable stress(CMS)-induced depressive-like behaviors,hippocampal neuroinflammation,and hippocampal volume.

iHDFS: A Distributed File System Supporting Incremental Computing

Big data are always processed repeatedly with small changes, which is a major form of big data processing. The feature of incremental change of big data shows that incremental computing mode can improve the performance greatly. HDFS is a distributed file system on Hadoop which is the most popular platform for big data analytics. And HDFS adopts fixed-size chunking policy, which is inefficient facing incremental computing. Therefore, in this paper, we proposed iHDFS (incremental HDFS), a distributed file system, which can provide basic guarantee for big data parallel processing. The iHDFS is implemented as an extension to HDFS. In iHDFS, Rabin fingerprint algorithm is applied to achieve content defined chunking. This policy make data chunking has much higher stability, and the intermediate processing results can be reused efficiently, so the performance of incremental data processing can be improved significantly. The effectiveness and efficiency of iHDFS have been demonstrated by the experimental results.

An Ultrasonic Backscatter Instrument for Cancellous Bone Evaluation in Neonates

Ultrasonic backscatter technique has shown promise as a noninvasive cancellous bone assessment tool. A novel ultrasonic backscatter bone diagnostic(UBBD) instrument and an in vivo application for neonatal bone evaluation are introduced in this study. The UBBD provides several advantages, including noninvasiveness, nonionizing radiation, portability, and simplicity. In this study, the backscatter signal could be measured within 5 s using the UBBD. Ultrasonic backscatter measurements were performed on 467 neonates(268 males and 199 females) at the left calcaneus. The backscatter signal was measured at a central frequency of 3.5 MHz. The delay(T_1) and duration(T_2) of the backscatter signal of interest(SOI) were varied, and the apparent integrated backscatter(AIB), frequency slope of apparent backscatter(FSAB), zero frequency intercept of apparent backscatter(FIAB), and spectral centroid shift(SCS) were calculated. The results showed that the SOI selection had a direct influence on cancellous bone evaluation. The AIB and FIAB were positively correlated with the gestational age(|R| up to 0.45, P < 0.001) when T_1 was short(< 8 μs), while negative correlations(|R| up to 0.56, P < 0.001) were commonly observed for T_1 > 10 μs. Moderate positive correlations(|R| up to 0.45, P < 0.001) were observed for FSAB and SCS with gestational age when T_1 was long(> 10 μs). The T_2 mainly introduced fluctuations in the observed correlation coefflcients. The moderate correlations observed with UBBD demonstrate the feasibility of using the backscatter signal to evaluate neonatal bone status. This study also proposes an explicit standard for in vivo SOI selection and neonatal cancellous bone assessment.

Catalpol ameliorates depressive-like behaviors in CUMS mice via oxidative stress-mediated NLRP3 inflammasome and neuroinflammation

The purpose of the present study was to investigate whether catalpol exhibited neuro-protective effects in chronic unpredictable mild stress(CUMS)mice through oxidative stress-mediated nucleotide-binding oligomerization domain,leucine-rich repeat,and pyrin-domain-containing 3(NLRP3)inflammasome and neuroinflammation.

Directional Routing Algorithm for Deep Space Optical Network

With the development of science, economy and society, the needs for research and exploration of deep space have entered a rapid and stable development stage. Deep Space Optical Network(DSON) is expected to become an important foundation and inevitable development trend of future deepspace communication. In this paper, we design a deep space node model which is capable of combining the space division multiplexing with frequency division multiplexing. Furthermore, we propose the directional flooding routing algorithm(DFRA) for DSON based on our node model. This scheme selectively forwards the data packets in the routing, so that the energy consumption can be reduced effectively because only a portion of nodes will participate the flooding routing. Simulation results show that, compared with traditional flooding routing algorithm(TFRA), the DFRA can avoid the non-directional and blind transmission. Therefore, the energy consumption in message routing will be reduced and the lifespan of DSON can also be prolonged effectively. Although the complexity of routing implementation is slightly increased compared with TFRA, the energy of nodes can be saved and the transmission rate is obviously improved in DFRA. Thus the overall performance of DSON can be significantly improved.

Morphological Evidence of Telocytes in Mice Aorta

Background： Telocytes （TCs） are a novel type of interstitial cells, which have been recently described in a large variety of cavitary and noncavitary organs. TCs have small cell bodies, and remarkably thin, long, and moniliform prolongations called telopodes （Tps）. Until now, TCs have been found in various loose connective tissues surrounding the arterioles, venules, and capillaries, but as a histological cellular component, whether TCs exist in large arteries remains unexplored. Methods： TCs were identified by transmission electron microscope in the aortic arch of male C57BL/6 mice. Results： TCs in aortic arch had small cell bodies （length： 6.06-13.02 μm： width： 1.05-4.25 μm） with characteristics of specific long （7.74-39.05 μm）, thin, and moniliform Tps; TCs distributed in the whole connective tissue layer of tunica adventitia： TCs in the innermost layer of tunica adventitia, located at the juncture between media and adventitia, with their long axes oriented parallel to the outer elastic membrane： and TCs in outer layers oftunica adventitia, were embedded among transverse and longitudinal oriented collagen fibers,forming a highly complex three-dimensional meshwork. Moreover, desmosomes were observed, serving as pathways connecting neighboring Tps. In addition, vesicles shed from the surface of TCs into the extracellular matrix, participating in some biological processes. Conclusions： TCs in aorta arch are a newly recognized complement distinct from other interstitial cells in large arteries, such as fibroblasts. And further biologically functional correlations need to be elucidated.

Semantic movie summarization based on string of IE-Role Nets

Roles, their emotion, and interactions between them are three key elements for semantic content understanding of movies. In this paper, we proposed a novel movie summarization method to capture the semantic content in movies based on a string of IE-Role Nets. An IE-Role Net(interaction and emotion rolenet) models the emotion and interactions of roles in a shot of the movie. The whole movie is represented as a string of IE-Role Nets. Summarization of a movie is transformed into finding an optimal substring with user-specified summarization ratio.Hierarchical substring mining is conducted to find an optimal substring of the whole movie. We have conducted objective and subjective experiments on our method. Experimental results show the ability of our method to capture the semantic content of movies.

Estimating mean trabecular bone spacing based on the combination of Hilbert transform and fundamental frequency estimation

Ultrasonic backscatter signals from cancellous bone are sensitive to the microstructure of trabecular bone,and thus enable the feasibility to extract microstructural information of trabecular bone.The mean trabecular bone spacing(MTBS)is an important parameter for characterizing bone microstructure.This paper proposes an MTBS estimation method based on the combination of Hilbert transform and fundamental frequency estimation(CHF). The CHF was verified with ultrasonic backscatter signals from simulations and in vitro measurements at a central frequency of 5MHz.The CHF method was compared with the simplified inverse filter tracking(SIFT)method,Simons' Quadratic Transformation(QT)method,Singular Spectrum Analysis(SSA)method,and Spectral Autocorrelation(SAC)method.Monte-Carlo simulations were performed by varying the MTBS,signal-to-noise ratio(SNR),standard deviation of regular spacing(SDRS),amplitude ratio of diffuse scattering to regular scattering(Ad)and frequency dependent attenuation(nBUA).The simulation results showed that the CHF method had a better performance in MTBS estimation under almost all the examination conditions except for SNR.The estimation percentage correct(EPC)was greater than 90% when the MTBS was in the range of 0.4to 1.4mm.In the in vitro measurements,the estimated EPC by the CHF method was91.25±7.81%(mean±standard deviation).A significant correlation was observed for the CHF-estimated MTBS and micro-computed tomography(μ-CT)-measured values(R^2=0.75,p<0.01).These results demonstrate that the CHF method is anti-interference for MTBS estimation and can be used to estimate trabecular bone spacing.

A learnable self-supervised task for unsupervised domain adaptation on point cloud classification and segmentation

1 Introduction Deep neural networks have exhibited excellent performance in supervised tasks on point clouds,such as classification,segmentation[1]and registration[2].In supervised learning schemes,manual labeling of massive point clouds is needed for model training.However,point clouds captured from different scenarios exist inevitable distribution discrepancy,and model trained from one domain always generalize badly in another domain.To reduce the doamin distribution discrepancy,many studies[3–6]have emerged for point cloud unsupervised domain adaptation(UDA)by learning domain-invariant features,where[5]proposed using adaptive nodes to align the local features between the source and the target domains[3,4],and[6]proposed utilizing self-supervised tasks to help capture highly transferable feature representations.

RNA splicing alterations in lung cancer pathogenesis and therapy

RNA splicing alterations are widespread and play critical roles in cancer pathogenesis and therapy.Lung cancer is highly heterogeneous and causes the most cancer-related deaths worldwide.Large-scale multi-omics studies have not only characterized the mutational landscapes but also discovered a plethora of transcriptional and post-transcriptional changes in lung cancer.Such resources have greatly facilitated the development of new diagnostic markers and therapeutic options over the past two decades.Intriguingly,altered RNA splicing has emerged as an important molecular feature and therapeutic target of lung cancer.In this review,we provide a brief overview of splicing dysregulation in lung cancer and summarize the recent progress on key splicing events and splicing factors that contribute to lung cancer pathogenesis.Moreover,we describe the general strategies targeting splicing alterations in lung cancer and highlight the potential of combining splicing modulation with currently approved therapies to combat this deadly disease.This review provides new mechanistic and therapeutic insights into splicing dysregulation in cancer.

Outlier Detection over Sliding Windows for Probabilistic Data Streams

Outlier detection is a very useful technique in many applications, where data is generally uncertain and could be described using probability. While having been studied intensively in the field of deterministic data, outlier detection is still novel in the emerging uncertain data field. In this paper, we study the semantic of outlier detection on probabilistic data stream and present a new definition of distance-based outlier over sliding window. We then show the problem of detecting an outlier over a set of possible world instances is equivalent to the problem of finding the k-th element in its neighborhood. Based on this observation, a dynamic programming algorithm （DPA） is proposed to reduce the detection cost from 0（2IR（~＇d）l） to O（Ik.R（e, d）l）, where R（e, d） is the d-neighborhood of e. Furthermore, we propose a pruning-based approach （PBA） to effectively and efficiently filter non-outliers on single window, and dynamically detect recent m elements incrementally. Finally, detailed analysis and thorough experimental results demonstrate the efficiency and scalability of our approach.

Prohibitin(PHB)interacts with AKT in mitochondria to coordinately modulate sperm motility

Prohibitin(PHB),an evoluti on arily con served mitochondrial inner membra ne protein,is highly expressed in cells that require strong mitoch on drial function.Recently,we dem on strated that the deleti on of Phb in spermatocytes results in impaired mitochondrial function.In addition,PHB expression in the mitochondrial sheath of human sperm has a significantly negative correlation with mitochondrial reactive oxygen species levels,but a positive one with mitochondrial membrane potential and sperm motility.These results suggest that mitochondrial PHB expression plays a role in sperm motility.However,the mechanism of PHB-mediated regulation of sperm motility remai ns unk nown.Here,we dem on strate for the first time that PHB interacts with protei n kinase B(AKT)and exists in a complex with phospho-PHB(pT258)and phospho-AKT in the mitochondrial sheath of murine sperm,as determined using colocalization and coimmunoprecipitation assays.After blocking AKT activity using wortmannin(a phosphatidylinositol 3-kinase[PI3K]inhibitor),murine sperm have significantly(P<0.05)decreased levels of phospho-PHB(pT258)and the total and progressive motility.Furthermore,significantly(P<0.05)lower levels of phospho-PI3K P85 subunit a+γ(pY199 and pY46)and phospho-AKT(pS473;pT308)are found in sperm from infertile asthenospermic and oligoasthenospermic men compared with no rmospermic subjects,which suggest a reduced activity of the PI3K/AKT pathway in these in fertile subjects.Importantly,these sperm from infertile subjects also have a significantly(P<0.05)lower level of phospho-PHB(pT258).Collectively,our findings suggest that the interaction of PHB with AKT in the mitochondrial sheath is critical for sperm motility,where PHB phosphorylation(pT258)level and PI3K/AKT activity are key regulatory factors.

High total variation-based method for sparse-view photoacoustic reconstruction

We propose a novel method by combining the total variation（TV） with the high-degree TV（HDTV） to improve the reconstruction quality of sparse-view sampling photoacoustic imaging（PAI）. A weighing function is adaptively updated in an iterative way to combine the solutions of the TV and HDTV minimizations. The fast iterative shrinkage/thresholding algorithm is implemented to solve both the TV and the HDTV minimizations with better convergence rate. Numerical results demonstrate the superiority and efficiency of the proposed method on sparse-view PAI. In vitro experiments also illustrate that the method can be used in practical sparse-view PAI.

Efficient secure data publishing algorithms for supporting information sharing

Many data sharing applications require that publishing data should protect sensitive information pertaining to individuals, such as diseases of patients, the credit rating of a customer, and the salary of an employee. Meanwhile, certain information is required to be published. In this paper, we consider data-publishing applications where the publisher specifies both sensitive information and shared information. An adversary can infer the real value of a sensitive entry with a high confidence by using publishing data. The goal is to protect sensitive information in the presence of data inference using derived association rules on publishing data. We formulate the inference attack framework, and develop complexity results. We show that computing a safe partial table is an NP-hard problem. We classify the general problem into subcases based on the requirements of publishing information, and propose algorithms for finding a safe partial table to publish. We have conducted an empirical study to evaluate these algorithms on real data. The test results show that the proposed algorithms can produce approximate maximal published data and improve the performance of existing algorithms.

Classifying Uncertain and Evolving Data Streams with Distributed Extreme Learning Machine

Conventional classification algorithms are not well suited for the inherent uncertainty, potential concept drift, volume, and velocity of streaming data. Specialized algorithms are needed to obtain efficient and accurate classifiers for uncertain data streams. In this paper, we first introduce Distributed Extreme Learning Machine （DELM）, an optimization of ELM for large matrix operations over large datasets. We then present Weighted Ensemble Classifier Based on Distributed ELM （WE-DELM）, an online and one-pass algorithm for efficiently classifying uncertain streaming data with concept drift. A probability world model is built to transform uncertain streaming data into certain streaming data. Base classifiers are learned using DELM. The weights of the base classifiers are updated dynamically according to classification results. WE-DELM improves both the efficiency in learning the model and the accuracy in performing classification. Experimental results show that WE-DELM achieves better performance on different evaluation criteria, including efficiency, accuracy, and speedup.

Improving SPARQL query performance with algebraic expression tree based caching and entity caching

To obtain comparable high query performance with relational databases,diverse database technologies have to be adapted to confront the complexity posed by both Resource Description Framework(RDF) data and SPARQL query.Database caching is one of such technologies that improves the performance of database with reasonable space expense based on the spatial/temporal/semantic locality principle.However,existing caching schemes exploited in RDF stores are found to be dysfunctional for complex query semantics.Although semantic caching approaches work effectively in this case,little work has been done in this area.In this paper,we try to improve SPARQL query performance with semantic caching approaches,i.e.,SPARQL algebraic expression tree(AET) based caching and entity caching.Successive queries with multiple identical sub-queries and star-shaped joins can be efficiently evaluated with these two approaches.The approaches are implemented on a two-level-storage structure.The main memory stores the most frequently accessed cache items,and items swapped out are stored on the disk for future possible reuse.Evaluation results on three mainstream RDF benchmarks illustrate the effectiveness and efficiency of our approaches.Comparisons with previous research are also provided.

Automated brain tumor segmentation in magnetic resonance imaging based on sliding-window technique and symmetry analysis

Background Brain tumor segmentation from magnetic resonance imaging （MRI） is an important step toward surgical planning,treatment planning,monitoring of therapy.However,manual tumor segmentation commonly used in clinic is time-consuming and challenging,and none of the existed automated methods are highly robust,reliable and efficient in clinic application.An accurate and automated tumor segmentation method has been developed for brain tumor segmentation that will provide reproducible and objective results close to manual segmentation results.Methods Based on the symmetry of human brain,we employed sliding-window technique and correlation coefficient to locate the tumor position.At first,the image to be segmented was normalized,rotated,denoised,and bisected.Subsequently,through vertical and horizontal sliding-windows technique in turn,that is,two windows in the left and the right part of brain image moving simultaneously pixel by pixel in two parts of brain image,along with calculating of correlation coefficient of two windows,two windows with minimal correlation coefficient were obtained,and the window with bigger average gray value is the location of tumor and the pixel with biggest gray value is the locating point of tumor.At last,the segmentation threshold was decided by the average gray value of the pixels in the square with center at the locating point and 10 pixels of side length,and threshold segmentation and morphological operations were used to acquire the final tumor region.Results The method was evaluated on 3D FSPGR brain MR images of 10 patients.As a result,the average ratio of correct location was 93.4％ for 575 slices containing tumor,the average Dice similarity coefficient was 0.77 for one scan,and the average time spent on one scan was 40 seconds.Conclusions An fully automated,simple and efficient segmentation method for brain tumor is proposed and promising for future clinic use.Correlation coefficient is a new and effective feature for tumor location.