A non-image-forming visual circuit mediates the innate fear of heights in male mice.

The neural basis of fear of heights remains largely unknown. In this study, we investigated the fear response to heights in male mice and observed characteristic aversive behaviors resembling human height vertigo. We identified visual input as a critical factor in mouse reactions to heights, while peripheral vestibular input was found to be nonessential for fear of heights. Unexpectedly, we found that fear of heights in naïve mice does not rely on image-forming visual processing by the primary visual cortex. Instead, a subset of neurons in the ventral lateral geniculate nucleus (vLGN), which connects to the lateral/ventrolateral periaqueductal gray (l/vlPAG), drives the expression of fear associated with heights. Additionally, we observed that a subcortical visual pathway linking the superior colliculus to the lateral posterior thalamic nucleus inhibits the defensive response to height threats. These findings highlight a rapid fear response to height threats through a subcortical visual and defensive pathway from the vLGN to the l/vlPAG.

Effects and Mechanism of Luteolin on Proliferation and Apoptosis of Glioma.

Objective: To explore and analyze the efficacy of luteolin on the proliferation and apoptosis of cerebral glioma and its possible mechanism, providing a theoretical basis for luteolin in glioma treatment. Methods: The cell line of Human cerebral glioma U87 was utilized for our current research. The study group were added with 0, 20, 40, and 80 µmol/L luteolin, respectively. Luteolin's Inhibitory function in the proliferation of U87 cells was detected by CCK-8, the Transwell chamber test was used to measure cell migration and invasion, while flow cytometry was used to assess apoptosis and Western Blot to gauge the expression of JNK/STAT3 pathway proteins. Results: In comparison with the control group, the intervention of various doses of luteolin could effectively inhibit glioma cell proliferation, the inhibitory rate uplifted remarkably with an increase of dose as well as intervention time (95% CI. 92.160-107.494, P < .05), which presented a significant time and dose dependence. The apoptosis rate of the low-dose, medium-dose, and high-dose categories was higher than that of the comparison group after 2 days of luteolin intervention (P < .05), and the apoptosis rate appeared to increase with the increase in intervention dose (P < .05). After 2 days of luteolin intervention, there were significantly more migratory and invasive cells in 3 categories than that in the control group (P < .05), and the number increased as the luteolin intervention dose was raised (P < .05). Bax and Cyt-c expressions dropped after 2 days of luteolin treatment when compared with the control set (P < .05), and the expression of Bax and Cyt-c fell considerably with increasing luteolin dose. Bcl-2, Caspase-3 and PARP expressions were significantly elevated in comparison to the control group (P < .05), and the increase was more obvious with the rise of the luteolin dose. Conclusion: Luteolin has a good inhibiting function on the proliferation of glioma cells, inhibiting cellular invasion and migration and promoting the apoptosis of glioma cells and the expression of apoptosis-related proteins, which has laid a good foundation for the application of luteolin to treat glioma cells.

Cross-Layer Design for Energy-Efficient Reliable Multi-Path Transmission in Event-Driven Wireless Sensor Networks.

In event-driven wireless sensor networks (WSNs), a reliable, efficient, and scalable routing solution is required for the reliable delivery of sensory data to the base station (BS). However, existing routing algorithms rarely address the issue of energy efficiency under multi-path conflicts for multi-event-driven scenarios. In order to maximize energy efficiency while maintaining a manageable conflict probability, this paper investigates a cross-layer design of routing and power control for multi-event-driven WSNs. We first develop a mathematical characterization of the conflict probability in multi-path routing, and we then formulate the energy efficiency maximization problem as a non-convex combinatorial fractional optimization problem subject to a maximum conflict probability constraint. By utilizing non-linear fractional programming and dual decomposition, an iterative search algorithm was used to obtain near-optimal power allocation and routing solutions. Extensive results demonstrate that our proposed algorithm achieved a gain of 9.09% to 35.05% in energy efficiency compared to other routing algorithms, thus indicating that our proposed algorithm can avoid unnecessary control overhead from multi-path conflicts with a lower conflict probability and can ensure maximum energy efficiency through routing and power control design.

Social deficits via dysregulated Rac1-dependent excitability control of prefrontal cortical neurons and increased GABA/glutamate ratios.

Identifying symptom-specific convergent mechanisms for neurodevelopmental disorders is a promising strategy in advancing therapies. Here, we show that bidirectional dysregulation of Rac1 activity in the medial prefrontal cortex (mPFC) dictates shared social deficits in mice. Selective upregulation or downregulation of Rac1 activity in glutamatergic or fast-spiking GABAergic neurons results in excessive or inadequate control of excitability combined with a decrease in glutamate or an increase in GABA concentrations and an increase in the GABA/glutamate ratio, which is responsible for social deficits. Notably, the autism model of Shank3B knockout mice exhibits aberrantly enhanced Rac1 activity, reduced glutamate concentrations, and pyramidal neuron excitability in mPFC accompanied with social deficits, which were corrected by either excitatory-neuron-specific downregulation of Rac1 activity or upregulation of neuronal excitability. Thus, this work shows a convergence between genetic autism risk factors, dysregulation of Rac1 signaling, and excitation-inhibition imbalance, enabling mechanism-based stratification of patients with social deficits.

Fate of dissolved inorganic nitrogen in turbulent rivers: The critical role of dissolved oxygen levels.

Dissolved inorganic nitrogen (DIN) is considered the main factor that induces eutrophication in water, and is readily influenced by hydrodynamic activities. In this study, a 4-year field investigation of nitrogen dynamics in a turbulent river was conducted, and a laboratory study was performed in the approximately homogeneous turbulence simulation system to investigate potential mechanisms involved in DIN transformation under turbulence. The field investigation revealed that, contrary to NO-3 dynamics, the NH+4 concentrations in water were lower in flood seasons than in drought seasons. Further laboratory results demonstrated that limitation of dissolved oxygen (DO) caused inactive nitrification and active denitrification in static river sediment. In contrast, the increased DO levels in turbulent river intensified the mineralization of organic nitrogen in sediment; moreover, ammonification and nitrification were activated, while denitrification was first activated and then depressed. Turbulence therefore decreased NH+4 and NO-2 concentrations, but increased NO-3 and total DIN concentrations in the overlying water, causing the total DIN to increase from 0.4 mg/L to maximum of 1.0 and 1.7 mg/L at low and high turbulence, respectively. The DIN was maintained at 0.7 and 1.0 mg/L after the 30-day incubation under low and high turbulence intensities (ε) of 3.4 × 10-4 and 7.4 × 10-2 m2/s3, respectively. These results highlight the critical role of DO in DIN budgets under hydrodynamic turbulence, and provide new insights into the DIN transport and transformation mechanisms in turbulent rivers.

Association of CDH11 with Autism Spectrum Disorder Revealed by Matched-gene Co-expression Analysis and Mouse Behavioral Studies.

A large number of putative risk genes for autism spectrum disorder (ASD) have been reported. The functions of most of these susceptibility genes in developing brains remain unknown, and causal relationships between their variation and autism traits have not been established. The aim of this study was to predict putative risk genes at the whole-genome level based on the analysis of gene co-expression with a group of high-confidence ASD risk genes (hcASDs). The results showed that three gene features - gene size, mRNA abundance, and guanine-cytosine content - affect the genome-wide co-expression profiles of hcASDs. To circumvent the interference of these features in gene co-expression analysis, we developed a method to determine whether a gene is significantly co-expressed with hcASDs by statistically comparing the co-expression profile of this gene with hcASDs to that of this gene with permuted gene sets of feature-matched genes. This method is referred to as "matched-gene co-expression analysis" (MGCA). With MGCA, we demonstrated the convergence in developmental expression profiles of hcASDs and improved the efficacy of risk gene prediction. The results of analysis of two recently-reported ASD candidate genes, CDH11 and CDH9, suggested the involvement of CDH11, but not CDH9, in ASD. Consistent with this prediction, behavioral studies showed that Cdh11-null mice, but not Cdh9-null mice, have multiple autism-like behavioral alterations. This study highlights the power of MGCA in revealing ASD-associated genes and the potential role of CDH11 in ASD.

Potassium supplement enhanced cadmium removal in a Microcystis aeruginosa photobioreactor: Evidence from actual and simulated wastewater.

In this study, a Microcystis aeruginosa-based photobioreactor (M. aeruginosa-based PBR) was developed for the removal of cadmium (Cd2+) from diluted actual mine wastewater (DW) and Cd2+-contained simulated wastewater (SW), with a uniform Cd2+ concentration of 0.5 mg/L. For the DW and SW, both K+ -abundant (DWA & SWA) and K+-insufficient (DWB & SWB) treatments were conducted. It was found that continuous supplementation of K+ benefited Cd2+ removal. The Cd2+ removal efficiency in SWA reached 70% during the 41 days of operation, which was 20% higher than that in the SWB. The K+ addition triggered great higher Cd2+ removal efficiency (90%) in the DWA in comparison to the SWA. The Cd2+ assimilation by M. aeruginosa and Cd2+ retention on M. aeruginosa surface were the primary processes involved in the PBR system. The K+ starvation triggered a 45% and 43% loss of M. aeruginosa biomass in the DWA and the DWB, respectively. Hence, the Cd2+ removal efficiency in DWB increased significantly, and this was attributed to the increased abundance of non-living cells and enhanced bioretention of Cd2+. The results revealed that continuous K+ supplementation enhanced the Cd2+ removal efficiency in the M. aeruginosa-based PBR jointly by prompting algal cell growth, Cd2+ assimilation and biosorption, as well as Cd2+ retention on the algal cells.

Adamts18 modulates the development of the aortic arch and common carotid artery.

Members of a disintegrin and metalloproteinases with thrombospondin motif (ADAMTS) family have been implicated in various vascular diseases. However, their functional roles in early embryonic vascular development are unknown. In this study, we showed that Adamts18 is highly expressed at E11.5-E14.5 in cells surrounding the embryonic aortic arch (AOAR) and the common carotid artery (CCA) during branchial arch artery development in mice. Adamts18 deficiency was found to cause abnormal development of AOAR, CCA, and the third and fourth branchial arch appendages, leading to hypoplastic carotid body, thymus, and variation of middle cerebral artery. Adamts18 was shown to affect the accumulation of extracellular matrix (ECM) components, in particular fibronectin (Fn), around AOAR and CCA. As a result of increased Fn accumulation, the Notch3 signaling pathway was activated to promote the differentiation of cranial neural crest cells (CNCCs) to vascular smooth muscle cells. These data indicate that Adamts18-mediated ECM homeostasis is crucial for the differentiation of CNCCs.

Regulation of Neural Circuit Development by Cadherin-11 Provides Implications for Autism.

Autism spectrum disorder (ASD) is a neurologic condition characterized by alterations in social interaction and communication, and restricted and/or repetitive behaviors. The classical Type II cadherins cadherin-8 (Cdh8, CDH8) and cadherin-11 (Cdh11, CDH11) have been implicated as autism risk gene candidates. To explore the role of cadherins in the etiology of autism, we investigated their expression patterns during mouse brain development and in autism-specific human tissue. In mice, expression of cadherin-8 and cadherin-11 was developmentally regulated and enriched in the cortex, hippocampus, and thalamus/striatum during the peak of dendrite formation and synaptogenesis. Both cadherins were expressed in synaptic compartments but only cadherin-8 associated with the excitatory synaptic marker neuroligin-1. Induced pluripotent stem cell (iPSC)-derived cortical neural precursor cells (NPCs) and cortical organoids generated from individuals with autism showed upregulated CDH8 expression levels, but downregulated CDH11. We used Cdh11 knock-out (KO) mice of both sexes to analyze the function of cadherin-11, which could help explain phenotypes observed in autism. Cdh11-/- hippocampal neurons exhibited increased dendritic complexity along with altered neuronal and synaptic activity. Similar to the expression profiles in human tissue, levels of cadherin-8 were significantly elevated in Cdh11 KO brains. Additionally, excitatory synaptic markers neuroligin-1 and postsynaptic density (PSD)-95 were both increased. Together, these results strongly suggest that cadherin-11 is involved in regulating the development of neuronal circuitry and that alterations in the expression levels of cadherin-11 may contribute to the etiology of autism.

LncRNA PRNCR1 Promotes Breast Cancer Proliferation and Inhibits Apoptosis by Modulating microRNA-377/CCND2/MEK/MAPK Axis.

BACKGROUND: Long non-coding RNAs (lncRNAs) have recently become the vital gene regulators in diverse cancers. In our study, we purposed to inquiry into the mechanisms of lncRNA PRNCR1 in breast cancer via microRNA-377 (miR-377)/CCND2/MEK/MAPK axis. METHODS: PRNCR1 expression in breast cancer tissues was detected, and the correlation between PRNCR1 expression and prognostic survival was analyzed. The expressions of PRNCR1 and miR-377 in breast cancer cell lines were detected. Relationships among PRNCR1, miR-377 and CCND2 were confirmed by luciferase activity, RNA pull-down or RIP assays. Breast cancer cells were introduced with silenced PRNCR1 or restored miR-377 to explore their functions in malignant phenotype of breast cancer cells. The expression of MEK/MAPK pathway-related proteins was determined by western blot analysis. RESULTS: PRNCR1 was highly expressed and miR-377 was poorly expressed in patients with breast cancer, and patients with high expression of PRNCR1 had a poor prognosis. PRNCR1 silencing or miR-377 overexpression resulted in suppressed breast cancer cell proliferation ability, blocked cell cycle process and induced apoptosis. PRNCR1 regulated CCND2 expression by competitively binding to miR-377. CCND2 activated the MEK/MAPK pathway, and after treatment with Mirdametinib, the MEK/MAPK pathway was inhibited, which was found to retard breast cancer growth. CONCLUSION: Our study highlights that lncRNA PRNCR1 may competitively bind to miR-377, leading to upregulated CCND2, which in turn activated MEK/MAPK pathway to promote breast cancer growth.

Real-Time Moving Object Detection in High-Resolution Video Sensing.

This paper addresses real-time moving object detection with high accuracy in high-resolution video frames. A previously developed framework for moving object detection is modified to enable real-time processing of high-resolution images. First, a computationally efficient method is employed, which detects moving regions on a resized image while maintaining moving regions on the original image with mapping coordinates. Second, a light backbone deep neural network in place of a more complex one is utilized. Third, the focal loss function is employed to alleviate the imbalance between positive and negative samples. The results of the extensive experimentations conducted indicate that the modified framework developed in this paper achieves a processing rate of 21 frames per second with 86.15% accuracy on the dataset SimitMovingDataset, which contains high-resolution images of the size 1920 × 1080.

Toward a Better Understanding of Neuronal Migration Deficits in Autism Spectrum Disorders.

Newborn neurons in developing brains actively migrate from germinal zones to designated regions before being wired into functional circuits. The motility and trajectory of migrating neurons are regulated by both extracellular factors and intracellular signaling cascades. Defects in the molecular machinery of neuronal migration lead to mis-localization of affected neurons and are considered as an important etiology of multiple developmental disorders including epilepsy, dyslexia, schizophrenia (SCZ), and autism spectrum disorders (ASD). However, the mechanisms that link neuronal migration deficits to the development of these diseases remain elusive. This review focuses on neuronal migration deficits in ASD. From a translational perspective, we discuss (1) whether neuronal migration deficits are general neuropathological characteristics of ASD; (2) how the phenotypic heterogeneity of neuronal migration disorders is generated; (3) how neuronal migration deficits lead to functional defects of brain circuits; and (4) how therapeutic intervention of neuronal migration deficits can be a potential treatment for ASD.

Segregated expressions of autism risk genes Cdh11 and Cdh9 in autism-relevant regions of developing cerebellum.

Results of recent genome-wide association studies (GWAS) and whole genome sequencing (WGS) highlighted type II cadherins as risk genes for autism spectrum disorders (ASD). To determine whether these cadherins may be linked to the morphogenesis of ASD-relevant brain regions, in situ hybridization (ISH) experiments were carried out to examine the mRNA expression profiles of two ASD-associated cadherins, Cdh9 and Cdh11, in the developing cerebellum. During the first postnatal week, both Cdh9 and Cdh11 were expressed at high levels in segregated sub-populations of Purkinje cells in the cerebellum, and the expression of both genes was declined as development proceeded. Developmental expression of Cdh11 was largely confined to dorsal lobules (lobules VI/VII) of the vermis as well as the lateral hemisphere area equivalent to the Crus I and Crus II areas in human brains, areas known to mediate high order cognitive functions in adults. Moreover, in lobules VI/VII of the vermis, Cdh9 and Cdh11 were expressed in a complementary pattern with the Cdh11-expressing areas flanked by Cdh9-expressing areas. Interestingly, the high level of Cdh11 expression in the central domain of lobules VI/VII was correlated with a low level of expression of the Purkinje cell marker calbindin, coinciding with a delayed maturation of Purkinje cells in the same area. These findings suggest that these two ASD-associated cadherins may exert distinct but coordinated functions to regulate the wiring of ASD-relevant circuits in the cerebellum.

Deep CNNs with Robust LBP Guiding Pooling for Face Recognition.

Pooling layer in Convolutional Neural Networks (CNNs) is designed to reduce dimensions and computational complexity. Unfortunately, CNN is easily disturbed by noise in images when extracting features from input images. The traditional pooling layer directly samples the input feature maps without considering whether they are affected by noise, which brings about accumulated noise in the subsequent feature maps as well as undesirable network outputs. To address this issue, a robust Local Binary Pattern (LBP) Guiding Pooling (G-RLBP) mechanism is proposed in this paper to down sample the input feature maps and lower the noise impact simultaneously. The proposed G-RLBP method calculates the weighted average of all pixels in the sliding window of this pooling layer as the final results based on their corresponding probabilities of being affected by noise, thus lowers the noise impact from input images at the first several layers of the CNNs. The experimental results show that the carefully designed G-RLBP layer can successfully lower the noise impact and improve the recognition rates of the CNN models over the traditional pooling layer. The performance gain of the G-RLBP is quite remarkable when the images are severely affected by noise.

A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance.

The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to improve the accuracy and robustness of state estimation with uncertain noise covariance. More specifically, at each timestep, a standard UKF will be implemented first to obtain the state estimations using the new acquired measurement data. Then an online fault-detection mechanism is adopted to judge if it is necessary to update current noise covariance. If necessary, innovation-based method and residual-based method are used to calculate the estimations of current noise covariance of process and measurement, respectively. By utilizing a weighting factor, the filter will combine the last noise covariance matrices with the estimations as the new noise covariance matrices. Finally, the state estimations will be corrected according to the new noise covariance matrices and previous state estimations. Compared with the standard UKF and other adaptive UKF algorithms, RAUKF converges faster to the actual noise covariance and thus achieves a better performance in terms of robustness, accuracy, and computation for nonlinear estimation with uncertain noise covariance, which is demonstrated by the simulation results.

A Robust Real Time Direction-of-Arrival Estimation Method for Sequential Movement Events of Vehicles.

Parameters estimation of sequential movement events of vehicles is facing the challenges of noise interferences and the demands of portable implementation. In this paper, we propose a robust direction-of-arrival (DOA) estimation method for the sequential movement events of vehicles based on a small Micro-Electro-Mechanical System (MEMS) microphone array system. Inspired by the incoherent signal-subspace method (ISM), the method that is proposed in this work employs multiple sub-bands, which are selected from the wideband signals with high magnitude-squared coherence to track moving vehicles in the presence of wind noise. The field test results demonstrate that the proposed method has a better performance in emulating the DOA of a moving vehicle even in the case of severe wind interference than the narrowband multiple signal classification (MUSIC) method, the sub-band DOA estimation method, and the classical two-sided correlation transformation (TCT) method.

A Novel Loss Recovery and Tracking Scheme for Maneuvering Target in Hybrid WSNs.

Tracking a mobile target, which aims to timely monitor the invasion of specific target, is one of the most prominent applications in wireless sensor networks (WSNs). Traditional tracking methods in WSNs only based on static sensor nodes (SNs) have several critical problems. For example, to void the loss of mobile target, many SNs must be active to track the target in all possible directions, resulting in excessive energy consumption. Additionally, when entering coverage holes in the monitoring area, the mobile target may be missing and then its state is unknown during this period. To tackle these problems, in this paper, a few mobile sensor nodes (MNs) are introduced to cooperate with SNs to form a hybrid WSN due to their stronger abilities and less constrained energy. Then, we propose a valid target tracking scheme for hybrid WSNs to dynamically schedule the MNs and SNs. Moreover, a novel loss recovery mechanism is proposed to find the lost target and recover the tracking with fewer SNs awakened. Furthermore, to improve the robustness and accuracy of the recovery mechanism, an adaptive unscented Kalman filter (AUKF) algorithm is raised to dynamically adjust the process noise covariance. Simulation results demonstrate that our tracking scheme for maneuvering target in hybrid WSNs can not only track the target effectively even if the target is lost but also maintain an excellent accuracy and robustness with fewer activated nodes.

Outer dense fibers stabilize the axoneme to maintain sperm motility.

Outer dense fibers (ODFs), as unique accessory structures in mammalian sperm, are considered to play a role in the protection of the sperm tail against shear forces. However, the role and relevant mechanisms of ODFs in modulating sperm motility and its pathological involvement in asthenozoospermia were unknown. Here, we found that the percentage of ODF defects was higher in asthenozoospermic samples than that in control samples and was significantly correlated with the percentage of axoneme defects and non-motile sperm. Furthermore, the expression levels of ODF major components (Odf1, 2, 3, 4) were frequently down-regulated in asthenozoospermic samples. Intriguingly, the positive relationship between ODF size and sperm motility existed across species. The conditional disruption of Odf2 expression in mice led to reduced sperm motility and the characteristics of asthenozoospermia. Meanwhile, the expression of acetylated α-tubulin was decreased in sperm from both Odf2 conditional knockout (cKO) mice and asthenozoospermic men. Immunofluorescence and biochemistry analyses showed that Odf2 could bind to acetylated α-tubulin and protect the acetylation level of α-tubulin in HEK293T cells in a cold environment. Finally, we found that lithium elevated the expression levels of Odf family proteins and acetylated α-tubulin, elongated the midpiece length and increased the percentage of rapidly moving sperm in mice. Our results demonstrate that ODFs are beneficial for sperm motility via stabilization of the axoneme and that hypo-expression of Odf family proteins is involved in the pathogenesis of asthenozoospermia. The lithium administration assay will provide valuable insights into the development of new treatments for asthenozoospermia.

An Acoustic Signal Enhancement Method Based on Independent Vector Analysis for Moving Target Classification in the Wild.

In this paper, we study how to improve the performance of moving target classification by using an acoustic signal enhancement method based on independent vector analysis (IVA) in the unattended ground sensor (UGS) system. Inspired by the IVA algorithm, we propose an improved IVA method based on a microphone array for acoustic signal enhancement in the wild, which adopts a particular multivariate generalized Gaussian distribution as the source prior, an adaptive variable step strategy for the learning algorithm and discrete cosine transform (DCT) to convert the time domain observed signals to the frequency domain. We term the proposed method as DCT-G-IVA. Moreover, we design a target classification system using the improved IVA method for signal enhancement in the UGS system. Different experiments are conducted to evaluate the proposed method for acoustic signal enhancement by comparing with the baseline methods in our classification system under different wild environments. The experimental results validate the superiority of the DCT-G-IVA enhancement method in the classification system for moving targets in the presence of dynamic wind noise.

Vehicle Counting and Moving Direction Identification Based on Small-Aperture Microphone Array.

The varying trend of a moving vehicle's angles provides much important intelligence for an unattended ground sensor (UGS) monitoring system. The present study investigates the capabilities of a small-aperture microphone array (SAMA) based system to identify the number and moving direction of vehicles travelling on a previously established route. In this paper, a SAMA-based acoustic monitoring system, including the system hardware architecture and algorithm mechanism, is designed as a single node sensor for the application of UGS. The algorithm is built on the varying trend of a vehicle's bearing angles around the closest point of approach (CPA). We demonstrate the effectiveness of our proposed method with our designed SAMA-based monitoring system in various experimental sites. The experimental results in harsh conditions validate the usefulness of our proposed UGS monitoring system.