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Spatiotemporal regulation of the mechanistic target of rapamycin (mTOR) pathway is pivotal for establishment of brain architecture. Dysregulation of mTOR signaling is associated with a variety of neurodevelopmental disorders. Here, we demonstrate that the UBE4B-KLHL22 E3 ubiquitin ligase cascade regulates mTOR activity in neurodevelopment. In a mouse model with UBE4B conditionally deleted in the nervous system, animals display severe growth defects, spontaneous seizures and premature death. Loss of UBE4B in the brains of mutant mice results in depletion of neural precursor cells and impairment of neurogenesis. Mechanistically, UBE4B polyubiquitylates and degrades KLHL22, an E3 ligase previously shown to degrade the GATOR1 component DEPDC5. Deletion of UBE4B causes upregulation of KLHL22 and hyperactivation of mTOR, leading to defective proliferation and differentiation of neural precursor cells. Suppression of KLHL22 expression reverses the elevated activity of mTOR caused by acute local deletion of UBE4B. Prenatal treatment with the mTOR inhibitor rapamycin rescues neurogenesis defects in Ube4b mutant mice. Taken together, these findings demonstrate that UBE4B and KLHL22 are essential for maintenance and differentiation of the precursor pool through fine-tuning of mTOR activity.

Superpixels are the result of over-segmentation of the image and provide an intermediate representation of the image data. It plays an important role in the research of computer vision and other fields. However, the existing superpixel algorithms are non-differentiable and the deep networks are usually defined over regular grid. Thus, most of the current superpixel generation algorithms are based on hand-crafted pixel features. To this end, this paper proposes an improved fast generation of superpixel algorithms with deep network. Firstly, the deep network with multiple hidden layers is directly embedded in the process of superpixel generation to extract the pixel features of the image. Secondly, this paper calculates the initial seed point position by [K-means] clustering method to signi-ficantly improve the segmentation result, and an active search method is used to ensure the correctness of the pixel label. Finally, superpixel segmentation results are obtained. On the Berkeley dataset BSDS500, the benchmark eva-luation using BSDS is compared with other literatures, and the experimental results show that the proposed algo-rithm performs relatively well in terms of the compactness and regularity of segmentation results.

Larix principis-rupprechtii is an important afforestation tree species in the North China alpine coniferous forest belt. Studying the correlations and response relationships between Larix principis-rupprechtii radial growth and climatic factors at different elevations is helpful for understanding the growth trends of L. principis-rupprechtiind its long-term sensitivity and adaptability to climate change. Pearson correlation, redundancy (RDA), and sliding analysis were performed to study the correlations and dynamic relationships between radial growth and climatic factors. The main conclusions are as follows: (1) The three-elevation standard chronologies all exhibited high characteristic values, contained rich climate information and were suitable for tree-ring climatological analyses. (2) Both temperature and precipitation restricted low-elevation L. principis-rupprechtii radial growth, while monthly maximum temperatures mainly affected mid-high-elevation L. principis-rupprechtii radial growth. (3) Mid-elevation L. principis-rupprechtii radial growth responded to climate factors with a “lag effect” and was not restricted by spring and early summer drought. (4) Long-term sliding analysis showed that spring temperatures and winter precipitation were the main climatic factors restricting L. principis-rupprechtii growth under warming and drying climate trends at different elevations. The tree-ring width index and Palmer drought severity index (PDSI) were positively correlated, indicating that L. principis-rupprechtii growth is somewhat restricted by drought. These results provide a reference and guidance for L. principis-rupprechtii management and sustainable development in different regions under warming and drying background climate trends.

Examination of the periodic differences in temperature in the Qinling Mountains at different time scales is highly important in research on the long-term evolution of the regional climate system and ecological environment. Based on February-April temperature data from 1835 to 2013 obtained at 27 weather stations in the Qinling Mountains reconstructed through tree rings, the multiscale characteristics of the early spring temperature time series on the southern and northern slopes of the Qinling Mountains and the response to climate signals were analyzed. The results indicate that the early spring temperature in the Qinling Mountains exhibits significant periodic characteristics on multiple time scales. Reconstruction at the different time scales reveals that the interannual scale change in the temperature variation on the northern slope of the Qinling Mountains plays a decisive role. The temperature on the northern slope exhibits a higher amplitude at the interannual and interdecadal scales than does that on the southern slope, and temporal differences occur at the quasi-century scale. The temperature achieves the strongest correlation with the original Atlantic Multidecadal Oscillation (AMO) sequence during the entire study period. In addition, the different time scales reveal that there exists a significant response relationship between the temperature at the interannual scale and the May sea temperature in the NINO3.4 area, which lags by one year. At the different time scales and various time ranges, the Qinling early spring temperature responds differently to the climate signals, which is an important factor leading to a lower correlation during the entire study period.

Traditional culture of the mandarin fish (Siniperca chuatsi), an important freshwater fish in China, is restricted by live bait fish, as the difficulty of utilizing plant-derived nutrients in its artificial feed hinders its industrialization of artificial feed. This study evaluated the effect of the Bacillus velezensis GY65 strain, which shows probiotic effects on digestive and bacterial infections in mandarin fish. The complete genome of B. velezensis GY65 was obtained via sequencing. Seven amylase coding genes that could improve the fish digestion of plant feeds were identified. Twelve gene clusters of secondary metabolites related to antibacterial compounds were identified using the antiSMAH database. The effects of B. velezensis GY65 on growth performance, digestive enzyme capacity, antioxidant capacity, and innate immune response of mandarin fish were evaluated. The results showed a significantly (P

Financial trading requires ever increasing data and compute resources principally to produce estimations of abnormal trading in the next unit interval within a complex environment involving an unlimited number of stakeholders dealing with a large number of financial assets. Machine-aided and AI assisted technologies are currently involved in the so-called high frequency trading (HFT). The HFT systems are used to compute unconditional stylised facts of price returns to investigate co-movements within and across the market and to apply trading rules for buying and selling before the next set of price returns are due - now increasingly in the next micro or pico seconds. Unconditional statistics cannot be applied to markets with variance breaks, so it is equally important to calculate conditional stylised facts, especially a measure of variance that can be related to volatility; such iterative calculations can overload both data and compute resources but are essential for trading. A key contributor to market volatility is the impact of the so-called market sentiment expressed by the market stakeholders - this slow speed signal has to be integrated with much faster moving price returns and this will impose a new set of constraints on data and compute resources. In this paper we focus on the latency in the computation of (a) unconditional and conditional stylised facts and the impact on trading decisions; (b) the latency which is inherent in aggregating high speed signals (price movement at intra-day/hour level) and the discrete but arbitrarily timed sentiment. We describe the use of cloud-computing services to alleviate problems of latency in (a) and (b) and compare the results with that of local desktop solutions.

Objectives: We aimed to comprehensively explore the etiology of granulomatous lobular mastitis (GLM) to optimize treatment programs. Methods: We collected 30 fresh mastitis samples for metagenomic next-generation sequencing, morphological observation, and analysis of the clinical information. Results: Of the 30 samples, 25 were GLM; pathogens were detected in 17, these were: Corynebacterium kroppenstedtii (10 of 25, 40%); C. kroppenstedtii and Pseudomonas oleovorans (3 of 25, 12%); C. kroppenstedtii and human gammaherpesvirus 4 (1 of 25, 4%); Acinetobacter baumannii and C. kroppenstedtii (1 of 25, 4%); P. oleovorans (1 of 25, 4%); and Tepidiphilus thermophilus (1 of 25, 4%). Abnormal sex hormone levels (mainly prolactin) and/or autoimmune function were found in 12 of the 25 samples. Lipophilic antibiotics (rifampicin) were found to work effectively in patients with slow-healing wounds after surgery. Conclusions: The main pathogenic factor of GLM is C. kroppenstedtii infection, but other unusual pathogens (P. oleovorans, human gammaherpesvirus 4, A. baumannii, T. thermophilus) are likely to be closely related to GLM, particularly human gammaherpesvirus 4 (Epstein-Barr virus)-associated mastitis, which may be a new entity of mastitis. Abnormal levels of sex hormones and autoimmune function are also common causes. Therefore, lipophilic antibiotics (rifampicin) and prolactin inhibitors may be an effective treatment.

The Qinling Mountains are located on the dividing line between the north and the south of China. Mt. Taibai, the study site, is the highest peak in the Qinling Mountains and also the highest peak in eastern mainland China. At Mt. Taibai, several dendroecological studies have been conducted on the relationship between tree-ring indices and climatic factors using traditional statistical methods. In this study, the response of Larix chinensis Beissn radial growth to climatic factors was explored in the treeline area of Mt. Taibai using the process-based Vaganov–Shashkin-Lite (VSL) model for the first time. The conclusions were obtained according to the analysis of the L. chinensis tree-ring samples collected from both the northern and southern slopes of Mt. Taibai. The VSL model showed that temperature limits L. chinensis growth during the entire growing season, while the model did not indicate precipitation as a limiting factor. The model showed significant positive correlations between the simulated and observed tree-ring chronologies for 1959–2013, excluding the uppermost sample site on the northern slope. However, the model performance deteriorated with increasing altitude, which may be due to the decreased sensitivity of radial growth to climatic factors above the treeline.

In this paper, we study the privacy-preserving task assignment problem in spatial crowdsourcing, where the locations of both workers and tasks, prior to their release to the server, are perturbed with Geo-Indistinguishability (a differential privacy notion for location-based systems). Different from the previously studied online setting, where each task is assigned immediately upon arrival, we target the batch-based setting, where the server maximizes the number of successfully assigned tasks after a batch of tasks arrive. To achieve this goal, we propose the k-Switch solution, which first divides the workers into small groups based on the perturbed distance between workers/tasks, and then utilizes Homomorphic Encryption (HE) based secure computation to enhance the task assignment. Furthermore, we expedite HE-based computation by limiting the size of the small groups under k. Extensive experiments demonstrate that, in terms of the number of successfully assigned tasks, the k-Switch solution improves batch-based baselines by 5.9X and the existing online solution by 1.74X, with no privacy leak.

The phonon dispersion relation, phonon group velocity and phonon density of state in GaN-based wurtzite nanofilms under prestress fields are investigated theoretically. Considering the acoustoelastic effects and spatial confinement effects, the acoustic phonons properties in stressed AlN/GaN/AlN nanofilms are derived by using the elasticity model, comparing with those in the pure AlN nanofilm and pure GaN nanofilm. Numerical simulations demonstrate that the heterogeneity in GaN-based nanofilms can modify the phonon dispersion relations of nanofilms, leading to the change of phonon group velocity and phonon density of state. The stress field can significantly affect the phonon properties of GaN-based heterostructural nanofilms, e.g. the positive stress decreases the phonon energy and group velocity while enhances the density of state. The influence of the stress field is also sensitive to the thickness of each component in heterostructural nanofilms. The present work will be useful in tuning the phonon properties through phonon engineering and strain/stress engineering to control the thermal and electrical performance in GaN-heterostructure-based electronic devices.

The bicycle is a healthy and sustainable transport mode due to its emission-free characteristics. To increase bicycle use, it is fundamental to provide bicycle-friendly environments. To better monitor bicycle environments, this study proposed the concept of bicycling environment quality (BEQ), which was defined by perceived satisfaction and conflict level. Data collection was conducted at 19 road segments in five sites located in Beijing, China. Then, speed-related and acceleration-related bicycling behavior indicators (BBIs) were extracted from data collected using sensors on mobile phones, while bicycling environment indicators (BEIs), such as bicycle flow, were extracted from recorded data. Taking the BBIs and BEIs as input attributes, a two-level BEQ classification assessment model based on a random forest (RF) algorithm was constructed. The proposed RF-based classification assessment model was able to produce approximately 77.35% overall correct classification. The results demonstrate the feasibility of using GPS data in evaluating BEQ. In addition, a novel dockless bicycle-sharing system (DBS)-based framework for bicycle traffic monitoring is discussed, which is of great significance in the sustainable development of bicycles. This study provides a theoretical method for objective BEQ assessment. It can further be used by planners and road administrators to monitor and improve BEQ and by individual cyclists for optimal route choice.

Background The coronavirus disease 2019 (COVID-19) is spreading rapidly across countries and has infected tens of millions of people all over the world. So far, the pandemic is ongoing globally, and the situation is still worsening. Methods In this retrospective, single-center cohort analysis, we included 25 adult inpatients with laboratory confirmed COVID-19 disease from the affiliated hospital of Xuzhou Medical University (Xuzhou, China). Epidemiological characterizations, clinical findings, and medical treatments were all reported. In addition, laboratory markers were investigated in terms of course of treatment. Results Epidemiological features and clinical findings were present for all 25 patients. Laboratory markers were identified due to temporal changes. After medical treatment, all patients were discharged home and recovering from the infection. Conclusions This study provides a comprehensive overview of patients with COVID-19 disease in a single hospital. Some of the laboratory markers were statistically different during the course of the disease, which might serve as indicators in identifying patients with COVID-19 disease at an early stage of the infection.

Objective: Granulomatous lobular mastitis (GLM) is a rare inflammatory disease of the breast that clinically mimics breast cancer. However, its etiology is not completely defined. The purpose of this study was to systematically study the bacteriology of GLM using advanced detection technology. Methods: Paraffin-embedded tissue from patients with GLM was collected. DNA was extracted from the samples and analyzed using next-generation sequencing (NGS) technology, and the data were processed using bioinformatics analyses. Results: A total of 40 patients were recruited into the study. A bioinformatics analysis revealed that a total of 17 genera or 19 species of pathogens were present in 39 of the GLM patients (97.5%). These included bacteria, fungi, and Mycobacterium tuberculosis complex group. Bacteria were found in 39 of the patient cases, while fungi were present in five. Only one case tested positive for M. tuberculosis complex. In addition, a single genus of pathogen was found in nine patients (23.1%), whereas 30 patients (76.9%) tested positive for multiple pathogens. Conclusions: This study profiled the microbiota of patients with GLM using NGS technology, which provides more useful information for establishing patient treatment plans. Keywords: Granulomatous lobular mastitis, Pathogens, Next-generation sequencing

Objectives: To explore the expression and pathologic significance of renalase in tumor tissues of different molecular subtypes of breast cancer. Design: Immunofluorescence methods and laser confocal scanning microscope observations were used to detect expression of renalase, estrogen receptor (ER), phospho-extracellular signal-regulated kinase 1 and 2 (p-ERK1/2), and phospho-signal transducer and activator of transcription (p-STAT3) in 58 cases of breast cancer tissue, 11 normal tissues, and 14 benign fibroadenomas. Statistical analysis of its expression in different molecular subtypes of breast cancer was employed. Results: Compared with control tissue (benign lesions and normal breast tissue), renalase was highly expressed in invasive breast cancer and the difference was significant (P