Sex differences orchestrated by androgens at single-cell resolution.

Sex differences in mammalian complex traits are prevalent and are intimately associated with androgens1-7. However, a molecular and cellular profile of sex differences and their modulation by androgens is still lacking. Here we constructed a high-dimensional single-cell transcriptomic atlas comprising over 2.3 million cells from 17 tissues in Mus musculus and explored the effects of sex and androgens on the molecular programs and cellular populations. In particular, we found that sex-biased immune gene expression and immune cell populations, such as group 2 innate lymphoid cells, were modulated by androgens. Integration with the UK Biobank dataset revealed potential cellular targets and risk gene enrichment in antigen presentation for sex-biased diseases. This study lays the groundwork for understanding the sex differences orchestrated by androgens and provides important evidence for targeting the androgen pathway as a broad therapeutic strategy for sex-biased diseases.

Spermine is a natural suppressor of AR signaling in castration-resistant prostate cancer.

In castration-resistant prostate cancer (CRPC), clinical response to androgen receptor (AR) antagonists is limited mainly due to AR-variants expression and restored AR signaling. The metabolite spermine is most abundant in prostate and it decreases as prostate cancer progresses, but its functions remain poorly understood. Here, we show spermine inhibits full-length androgen receptor (AR-FL) and androgen receptor splice variant 7 (AR-V7) signaling and suppresses CRPC cell proliferation by directly binding and inhibiting protein arginine methyltransferase PRMT1. Spermine reduces H4R3me2a modification at the AR locus and suppresses AR binding as well as H3K27ac modification levels at AR target genes. Spermine supplementation restrains CRPC growth in vivo. PRMT1 inhibition also suppresses AR-FL and AR-V7 signaling and reduces CRPC growth. Collectively, we demonstrate spermine as an anticancer metabolite by inhibiting PRMT1 to transcriptionally inhibit AR-FL and AR-V7 signaling in CRPC, and we indicate spermine and PRMT1 inhibition as powerful strategies overcoming limitations of current AR-based therapies in CRPC.

A Recognition Method for Road Hypnosis Based on Physiological Characteristics.

Road hypnosis is a state which is easy to appear frequently in monotonous scenes and has a great influence on traffic safety. The effective detection for road hypnosis can improve the intelligent vehicle. In this paper, the simulated experiment and vehicle experiment are designed and carried out to obtain the physiological characteristics data of road hypnosis. A road hypnosis recognition model based on physiological characteristics is proposed. Higher-order spectra are used to preprocess the electrocardiogram (ECG) and electromyography (EMG) data, which can be further fused by principal component analysis (PCA). The Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), and K-Nearest Neighbor (KNN) models are constructed to identify road hypnosis. The proposed model has good identification performance on road hypnosis. It provides more alternative methods and technical support for real-time and accurate identification of road hypnosis. It is of great significance to improve the intelligence and active safety of intelligent vehicles.

Flower-like TiO2 and TiO2@C composites prepared via a one-pot solvothermal method as anode materials for lithium-ion batteries: higher capacity and excellent cycling stability.

TiO2 is a promising and safe anode material for lithium-ion batteries. Nevertheless, its inferior electronic conductivity and inferior cycling capability have always limited its practical application. In this study, flower-like TiO2 and TiO2@C composites are produced by a simple one-pot solvothermal method. It is noticeable that the synthesis of TiO2 is carried out simultaneously with carbon coating. The flower-like TiO2 with a special morphology can decrease the distance of lithium ion diffusion, while the carbon coating improves the electronic conductivity of TiO2. At the same time, the carbon content of TiO2@C composites can be controlled by adjusting the amount of glucose. Compared with flower-like TiO2, TiO2@C composites have higher specific capacity and preferable cycling performance. It is noteworthy that the specific surface area of TiO2@C with a carbon content of 63.36% is 293.94 m2 g-1 and its capacity remains at 371.86 mAh g-1 after 1000 cycles at 1 A g-1. Other anode materials can also be prepared using this strategy.

Research on Recognition of Road Hypnosis in the Typical Monotonous Scene.

Road traffic safety can be influenced by road hypnosis. Accurate detection of the driver's road hypnosis is a very important function urgently required in the driver assistance system. Road hypnosis recurs frequently in a certain period, and it tends to occur in a typical monotonous scene such as a tunnel or a highway. Taking the scene of a tunnel or a highway as a typical example, road hypnosis was studied through simulated driving experiments and vehicle driving experiments. A road hypnosis recognition model based on principal component analysis (PCA) and a long short-term memory network (LSTM) was proposed, where PCA was used to extract various parameters collected by the eye tracker, and the LSTM model was constructed to identify road hypnosis. The accuracy rates of 93.27% and 97.01% in simulated driving experiments and vehicle driving experiments were obtained. The proposed method was compared with k-nearest neighbor (KNN) and random forest (RF). The results showed that the proposed PCA-LSTM model had better performance. This paper provides a novel and convenient method to realize the driver's road hypnosis detection function of the intelligent driver assistance system in practical applications.

Titanium dioxide-based anode materials for lithium-ion batteries: structure and synthesis.

Lithium-ion batteries (LIBs) have high energy density, long life, good safety, and environmental friendliness, and have been widely used in large-scale energy storage and mobile electronic devices. As a cheap and non-toxic anode material for LIBs, titanium dioxide (TiO2) has a good application prospect. However, its poor electrical conductivity leads to unsatisfactory electrochemical performance, which limits its large-scale application. In this review, the structure of three TiO2 polymorphs which are widely investigated are briefly described, then the preparation and electrochemical performance of TiO2 with different morphologies, such as nanoparticles, nanowires, nanotubes, and nanospheres, and the related research on the TiO2 composite materials with carbon, silicon, and metal materials are discussed. Finally, the development trend of TiO2-based anode materials for LIBs has been briefly prospected.

A real-time driver fatigue identification method based on GA-GRNN.

It is of great practical and theoretical significance to identify driver fatigue state in real time and accurately and provide active safety warning in time. In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. The specific work is as follows: (1) design simulated driving experiment and real driving experiment, determine the fatigue state of drivers according to the binary Karolinska Sleepiness Scale (KSS), and establish the fatigue driving sample database. (2) Improved Multi-Task Cascaded Convolutional Networks (MTCNN) and applied to face detection. Dlib library was used to extract the coordinate values of face feature points, collect the characteristic parameters of driver's eyes and mouth, and calculate the Euler Angle parameters of head posture. A fatigue identification model was constructed by using multiple characteristic parameters. (3) Genetic Algorithm (GA) was used to find the optimal smooth factor of Generalized Regression Neural Network (GRNN) and construct GA-GRNN fatigue driving identification model. Compared with K-Nearest Neighbor (KNN), Random Forest (RF), and GRNN fatigue driving identification algorithms. GA-GRNN has the best generalization ability and high stability, with an accuracy of 93.3%. This study provides theoretical and technical support for the application of driver fatigue identification.

Resource allocation algorithm of an indoor OFDMA VLC system.

In this work, a resource management algorithm is proposed for an indoor visible light communication (VLC) access network using an orthogonal frequency division multiple access (OFDMA) scheme. With OFDMA, adaptive modulation is adopted to improve the frequency spectrum efficiency of this VLC system. Specifically, the long-term time-averaged optimization problem is transformed into a series of single timeslot online problems via a Lyapunov optimization technique. Then, each user is provided with a separate queue to maintain the random arrival data by a VLC access point, and a subcarrier allocation solution is subsequently presented to maximize the transmission rate. Numerical simulation shows that compared with the best channel state information (BC) algorithm and round robin (RR) algorithm, the proposed algorithm can not only ensure the transmission rate but also greatly improve system stability. In particular, for mean arrival rate B=7Kbits/timeslot, the system stability by the proposed algorithm improves by about 53.36% and 61.36% in comparison with BC and RR algorithms, respectively. This work will benefit the design and development of indoor OFDMA VLC systems.

A Real-Time Recognition System of Driving Propensity Based on AutoNavi Navigation Data.

Driving propensity is the driver's attitude towards the actual traffic situation and the corresponding decision-making or behavior during the driving process. It is of great significance to improve the accuracy of safety early warning and reduce traffic accidents. In this paper, a real-time identification system of driving propensity based on AutoNavi navigation data is proposed. The main work includes: (1) A dynamic data acquisition method of AutoNavi navigation is proposed to obtain the time, speed and acceleration of the driver during the navigation process. (2) The dynamic data collection method of AutoNavi navigation is analyzed and verified through the dynamic data obtained in the real vehicle experiment. The principal component analysis method is used to process the experimental data to extract the driving propensity characteristics variables. (3) The fruit fly optimization algorithm combined with GRNN (generalized neural network) and the feature variable set are used to build a FOA-GRNN-based model. The results show that the overall accuracy of the model can reach 94.17%. (4) A driving propensity identification system is constructed. The system has been verified through real vehicle test experiments. This paper provides a novel and convenient method for building personalized intelligent driver assistance systems in practical applications.

Driver's Visual Attention Characteristics and Their Emotional Influencing Mechanism under Different Cognitive Tasks.

The visual attention system is the gateway to the human information processing system, and emotion is an important part of the human perceptual system. In this paper, the driver's visual attention characteristics and the influences of typical driving emotions on those were explored through analyzing driver's fixation time and identification accuracy to different visual cognitive tasks during driving. The results showed that: the increasing complexity of the cognitive object led to the improvement of visual identification speed. The memory and recall process increased drivers' fixation time to cognitive objects, and the recall accuracy decreased with the increase in time interval. The increase in the number of cognitive objects resulted in the driver improving the visual identification speed for the cognitive object at the end of the sequence consciously. The results also showed that: the visual cognitive efficiency was improved in the emotional states of anger and contempt, and was decreased in the emotional states of surprise, fear, anxiety, helplessness and pleasure, and the emotional state of relief had no significant effect on the visual cognitive efficiency. The findings reveal the driver's visual information processing mechanism to a certain extent, which are of great significance to understand the inner micro-psychology of driver's cognition.

Average signal-to-noise ratio maximization for an intelligent reflecting surface and angle diversity receiver jointly assisted indoor visible light communication system.

The intelligent reflecting surface (IRS) and angle diversity receiver (ADR) jointly assisted indoor visible light communication (VLC) system is proposed to improve average signal-to-noise ratio (ASNR) performance. Specifically, to maximize the ASNR at the receiving plane, the roll angle and yaw angle of IRS and the inclination angle of the side detector in the ADR structure are optimized simultaneously as one non-convex problem. With the bat algorithm, the optimal solution is numerically obtained. Results show that when the transmit power of the light emitting diode lamp array is 1 W, the ASNRs of this VLC system optimized by IRS and ADR are approximately 7.89 dB, 3.58 dB, and 2.09 dB higher than those of the original, IRS-assisted, and ADR-assisted VLC systems, respectively. Furthermore, the transmission rate and bit error rate performances of the original, IRS-assisted, ADR-assisted, and IRS and ADR jointly assisted indoor VLC systems are also simulated and compared; it is found that the performance improvement of the indoor VLC system jointly optimized by IRS and ADR is more evident than that of the other three VLC systems. This study will benefit the research and development of indoor VLC systems.

Transmission rate Optimization by dynamic resource allocation algorithm for RF/VLC heterogeneous networks.

In this work, a dynamic resource allocation (DRA) algorithm is proposed to optimize the transmission rate subject to the access point assignment, bandwidth and transmit power allocation in RF/VLC heterogeneous networks, which combines the visible light communication (VLC) access point (AP) and radio frequency (RF) AP. To optimize the allocation among resource block (RB), subchannel and power, the time-average transmission rate is maximized under time-average transmit power budget. Specifically, the time-average optimization problem is converted into series of single timeslot online problem by Lyapunov optimization technique. Because of its complexity and non-convexity, the problem is decomposed into three independent subproblems for which a non-iterative solution is presented on the basis of Lagrange relaxation and convex optimization theory. Numerical simulations are conducted to demonstrate the effectiveness of the proposed DRA algorithm. And the comparisons with two classical algorithms are also given in terms of transmission rate and system stability. This work will benefit the design and development of hybrid RF/VLC system.

Recognition Method of Vehicle Cluster Situation Based on Set Pair Logic considering Driver's Cognition.

The recognition of vehicle cluster situations is one of the critical technologies of advanced driving, such as intelligent driving and automated driving. The accurate recognition of vehicle cluster situations is helpful for behavior decision-making safe and efficient. In order to accurately and objectively identify the vehicle cluster situation, a vehicle cluster situation model is proposed based on the interval number of set pair logic. The proposed model can express the traffic environment's knowledge considering each vehicle's characteristics, grouping relationships, and traffic flow characteristics in the target vehicle's interest region. A recognition method of vehicle cluster situation is designed to infer the traffic environment and driving conditions based on the connection number of set pair logic. In the proposed model, the uncertainty of the driver's cognition is fully considered. In the recognition method, the relative uncertainty and relative certainty of driver's cognition, traffic information, and vehicle cluster situation are fully considered. The verification results show that the proposed recognition method of vehicle cluster situations can realize accurate and objective recognition. The proposed anthropomorphic recognition method could provide a basis for vehicle autonomous behavior decision-making.

Magnetic Field-Induced Orientation of Modified Boron Nitride Nanosheets in Epoxy Resin with Improved Flame and Wear Resistance.

In this work, self-lubricating boron nitride nanosheets (BNNs) were decorated with flame-retardant zinc ferrite (ZnFe2O4), followed by stearic acid modification to obtain magnetic and hydrophobic properties. Under the external magnetic field, the obtained ZnFe2O4-BNNs can be well ordered into one-dimensional orientation in the epoxy resin (EP) matrix-enabling improved flame retardant properties. Compared to a randomly oriented ZnFe2O4-BNN equivalent, the well-orientated ZnFe2O4-BNNs (at 10% mass fraction) reduce the peak heat release rate and CO production by 47 and 51%, respectively. Furthermore, the ZnFe2O4-BNN/EP composite monoliths demonstrate excellent durability, displaying continued superhydrophobicity under Taber abrasion, high external pressure, knife scratch, long-term exposure to acids/bases, and harsh UV irradiation. In addition, the result shows that the well-oriented ZnFe2O4-BNN/EP composite demonstrates better tribological performance and the friction coefficient is reduced by 76.9%.

Physiological and transcriptional responses of Catalpa bungei to drought stress under sufficient- and deficient-nitrogen conditions.

Many semi-arid ecosystems are simultaneously limited by soil water and nitrogen (N). We conducted a greenhouse experiment to address how N availability impacts drought-resistant traits of Catalpa bungei C. A. Mey at the physiological and molecular level. A factorial design was used, consisting of sufficient-N and deficient-N combined with moderate drought and well-watered conditions. Seedling biomass and major root parameters were significantly suppressed by drought under the deficient-N condition, whereas N application mitigated the inhibiting effects of drought on root growth, particularly that of fine roots with a diameter <0.2 mm. Intrinsic water-use efficiency was promoted by N addition under both water conditions, whereas stable carbon isotope compositions (δ13C) was promoted by N addition only under the well-watered condition. Nitrogen application positively impacted drought adaptive responses including osmotic adjustment and homeostasis of reactive oxygen species, the content of free proline, soluble sugar and superoxide dismutase activity: all were increased upon drought under sufficient-N conditions but not under deficient-N conditions. The extent of abscisic acid (ABA) inducement upon drought was elevated by N application. Furthermore, an N-dependent crosstalk between ABA, jasmonic acid and indole acetic acid at the biosynthesis level contributed to better drought acclimation. Moreover, the transcriptional level of most genes responsible for the ABA signal transduction pathway, and genes encoding the antioxidant enzymes and plasma membrane intrinsic proteins, are elevated upon drought only under sufficient-N addition. These observations confirmed at the molecular level that major adaptive responses to drought are dependent on sufficient N nutrition. Although N uptake was decreased under drought, N-use efficiency and transcription of most genes encoding N metabolism enzymes were elevated, demonstrating that active N metabolism positively contributed drought resistance and growth of C. bungei under sufficient-N conditions.

Up-regulation of c-Fos associated with neuronal apoptosis following intracerebral hemorrhage.

The proto-oncogene c-Fos is an important member of the activating protein 1 (AP-1) transcription complex involved in major cellular functions such as transformation, proliferation, differentiation, and apoptosis. The expression of c-Fos is very tightly regulated and responses rapidly and transiently to a plethora of apoptotic stimuli. However, it is still unclear how c-Fos functions on neuronal activities following intracerebral hemorrhage (ICH). In the present studies, we uncovered that the up-regulation of c-Fos is related to neuronal apoptosis following ICH probably via FasL/Fas apoptotic pathway. From the results of Western blot and immunohistochemistry, we obtained that c-Fos is significantly up-regulated surrounding the hematoma following ICH and co-locates with active caspase-3 in the neurons. Besides, electrophoretic mobility shift assay exhibits high AP-1 DNA-binding activities in ICH groups due to the increase of c-Fos expression. In addition, there are concomitant up-regulation of Fas ligand (FasL), which is the target protein of AP-1, Fas, active caspase-8, and active caspase-3 in vivo and in vitro studies. What is more, our in vitro study showed that using c-Fos-specific RNA interference in primary cortical neurons, the expression of FasL and active caspase-3 are suppressed. Thus, our results indicated that c-Fos might exert its pro-apoptotic function on neuronal apoptosis following ICH.

hABCF3, a TPD52L2 interacting partner, enhances the proliferation of human liver cancer cell lines in vitro.

In the present study, we characterized an evolutionarily conserved non-transmembrane ATP-binding cassette protein: hABCF3. Subcellular immunofluorescence staining demonstrated that hABCF3 localizes preferentially in cytoplasm, unlike its paralog protein hABCF1, which localizes in both cytoplasm and nucleus. Quantitative realtime PCR analysis revealed that hABCF3 is expressed in all tissues examined, with high expression level in heart, liver, and pancreas. Interestingly, ectopic hABCF3 promoted proliferation of human liver cancer cell lines. Moreover, knock down of hABCF3 protein expression by siRNA inhibited cell proliferation. In addition, we identified TPD52L2 (Tumor Protein D52-like 2) as a hABCF3 interacting protein via yeast two-hybrid. This interaction was further confirmed by in vivo co-immunoprecipitation and co-localization assays. Furthermore, we identified the interactional region of hABCF3 to be the first 200 amino acids uncharacterized region. Notably, the truncated version of hABCF3, which lacks the TPD52L2 binding region, remarkably impaired hABCF3-mediated cell proliferation. Taken together, these findings suggest that hABCF3 positively regulates cell proliferation, at least partially through the interaction with a tumor protein D52 protein family member: TPD52L2.

PTPN4 negatively regulates CrkI in human cell lines.

PTPN4 is a widely expressed non-receptor protein tyrosine phosphatase. Although its overexpression inhibits cell growth, the proteins with which it interacts to regulate cell growth are unknown. In this study, we identified CrkI as a PTPN4-interacting protein using a yeast two-hybrid, and confirmed this interaction using in vitro GST pull-down and co-immunoprecipitation and co-localization assays. We further determined the interactional regions as the SH3 domain of CrkI and the proline-rich region between amino acids 462 and 468 of PTPN4. Notably, overexpression of PTPN4 inhibits CrkI-mediated proliferation and wound healing of HEK293T cells, while knockdown of PTPN4 by siRNA in Hep3B cells enhances CrkI-mediated cell growth and motility. Moreover, our data show that ectopic expression of PTPN4 reduces the phosphorylation level of CrkI in HEK293T cells. These findings suggest that PTPN4 negatively regulates cell proliferation and motility through dephosphorylation of CrkI.

p75NTR signal transduction suppressed by BFAR and p75NTR interactions.

p75NTR is a low-affinity nerve growth factor receptor, which promotes cell proliferation as a positive modulator of high-affinity receptor TrkA, as well as binds with cell ligands to induce apoptosis and mediate death signals. To analyze the regulatory mechanisms of p75NTR, the present study utilized a new membrane yeast two-hybrid system to screen a human fetal brain cDNA library. Results identified BFAR, a novel protein that interacts with p75NTR. Interaction specificity was verified by membrane yeast two-hybrid co-transformation assays, in vitro GST pull-down assays, and in vitro co-immunoprecipitation assays. The fluorescent subcellular localization assay revealed that the two proteins co-localized within the cytoplasm. BFAR overexpression in PC-12 and HEK293T cells inhibited the NFκB and JNK signaling pathway, as determined with the luciferase test. Co-transfected p75NTR and BFAR in HEK293T or PC-12 cells, respectively, increased the percentage of cells in the G2/M phase, decreased the number of S-phase cells, and did not change the number of G0/G1-phase cells.

Overexpression of SCYL1-BP1 stabilizes functional p53 by suppressing MDM2-mediated ubiquitination.

Previously, we defined SCY1-like 1 binding protein 1 (SCYL1-BP1) to be a substrate of Pirh2 that binds to mouse double minute gene number 2 (MDM2). In the current study, we found that an increase in SCYL1-BP1 protein levels caused a parallel change in the amount of p53 protein due to the inhibition by SCYL-BP1 of MDM2-mediated p53 ubiquitination. SCYL1-BP1 was not able to alter the ubiquitination of p53 by human papillomavirus protein E6, indicating that the effect was specific for MDM2. Increases in the level of SCYL1-BP1 protein in cells led to the greater transcriptional activation of p21 and gadd45, reduced rate of cellular proliferation, increased levels of apoptosis and inhibition of tumorigenicity. Thus, we propose that SCYL1-BP1 is a novel regulator of the MDM2-p53 feedback loop and that it may be a potential tumor suppressor.