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Tobacco mosaic virus (TMV) is known to infect a wide range of plants, resulting in reduced yield and productivity. Novel, effective, and plant-based pesticides are required to protect plants against TMV infection. To identify novel anti-TMV agents from natural sources, we systematically studied the roots of Cynanchum paniculatum and isolated six new seco-pregnane C

Autophagy-based protein degradation is emerging as a promising technology for anti-diseases and innovative drug discovery. Here, we demonstrate a novel type of autophagy-targeting chimera (AUTAC) to degrade protein by targeting autophagy key protein LC3. The best compound 10f powerfully degraded BRD4 protein through the autophagy pathway and exhibited good anti-proliferative activity in multiple tumor cells, providing a powerful toolbox for medicinal chemists to study disease-related targets with autophagy-based degradation.

Planar, thin-layered chiral plasmonic superstructures with complex two-dimensional (2D) patterns, namely, double-layered binary stars (bi-stars) and pinwheels, were realized through DNA programmable 2D supramolecular self-assembly of gold nanorods (AuNRs). The chirality of the chiral superstructures was defined by a finite number of AuNR pairs as enantiomeric motifs, and their sizes (∼240 nm) were precisely defined by the underlying DNA template. These planar, thin-layered chiral nanoparticle superstructures exhibited prescribed shapes and sizes at the dried state on the substrate surface and are characteristic of giant anisotropy of chiroptical responses, with enhanced g-factors from the axial incident excitation as compared to the in-plane excitation. This work will inspire possibilities for the construction of 2D chiral materials, for example, chiral metasurfaces, for the on-chip manipulation of chiral light-matter interactions via programmable self-assembly of nanoparticles.

Millimeter-wave channel measurements for a meeting room, lecture room and open plan office floor were used to analyse and model the spatial consistency of channel clusters. Particularly, how the angles of arrival and delays of extracted multi-path components in each cluster varied with small changes in receiver location. We extended the KPowerMeans algorithm, for classifying captured multi-path components into clusters from the delay/angular domains, to include the location domain to allow the spatial consistency of the clusters between locations to be analysed. The observed spatial consistency in measurements was then used to validate whether the 3GPP spatial consistency procedure (3GPP SC-I) reflects real world spatial consistency. The 3GPP spatial consistency procedure for ensuring spatial consistency of cluster parameters during mobile user simulations was then applied for each environment, allowing for comparison between the ‘predicted’ cluster parameters and the measured cluster parameters. The 3GPP model/procedure showed a good fit for all environments but highlighted the impact of the environment on the amount of accuracy of the procedure.

With the application of the random sampling method in the down-sampling of point clouds data, the processing speed of point clouds has been greatly improved. However, the utilization of semantic information is still insufficient. To address this problem, we propose a point cloud semantic segmentation network called MFFRand (Multi-Scale Feature Fusion Based on RandLA-Net). Based on RandLA-Net, a multi-scale feature fusion module is developed, which is stacked by encoder-decoders with different depths. The feature maps extracted by the multi-scale feature fusion module are continuously concatenated and fused. Furthermore, for the network to be trained better, the multi-loss supervision module is proposed, which could strengthen the control of the training process of the local structure by adding sub-losses in the end of different decoder structures. Moreover, the trained MFFRand network could be connected to the inference network by different decoder terminals separately, which could achieve the inference of different depths of the network. Compared to RandLA-Net, MFFRand has improved mIoU on both S3DIS and Semantic3D datasets, reaching 71.1% and 74.8%, respectively. Extensive experimental results on the point cloud dataset demonstrate the effectiveness of our method.

Global navigation satellite system (GNSS) can provide us with three-dimensional coordinates information of any place on the earth. However, the multipath effects always cause a decrease in GNSS positioning accuracy. In this paper, we analyze and model the root mean square (RMS) delay spread (DS) in multipath channels and the GNSS pseudo-range error (PRE) based on channel measurements in an urban canyon scenario at both 1.575 GHz and 1.207 GHz. By constructing the probability density function (PDF) of RMS DS, it is found that the PDF can be well fitted by a lognormal distribution. In addition, compared with the International Telecommunication Union (ITU) standard, the mean value and standard deviation of RMS DS in the urban canyon are much smaller than those in the traditional urban micro-cellular scenario. Then, by modeling PRE as a function of the transmitter-receiver (Tx-Rx) elevation angle and RMS DS separately, the effect of the Tx-Rx elevation angle on PRE and the dependence of PRE on RMS DS are studied. It is found that the PRE increases linearly with the increases of the cotangent value of Tx-Rx elevation angle, and the fluctuation of PRE at 1.207 GHz is much larger than that at 1.575 GHz. Besides, there is a linear dependence of PRE on RMS DS, that is when RMS DS increases by 1 ns, PRE increases by 0.50 meters at 1.207 GHz and 0.53 meters at 1.575 GHz. These results are helpful for the research on multipath effects in urban canyon scenarios and the improvement of positioning accuracy for the GNSS.

In contemporary China, the rapidly urbanized cities are exposed to a broad range of natural and human-made emergencies, such as COVID-19. Responding to emergencies successfully requires widespread participation of local government sectors that engages in diversified collaboration behaviors across organizational boundaries for achieving sustainability. However, the multi-organizational collaborative process is highly dynamic and complex, as well as its outcomes are uncertain underlying the emergency response network. Examining characteristics of the collaborative process and exploring how collaborative behaviors local governmental sectors engaging in the impact their perceived outcomes is essential to understand how disastrous situations are addressed by collaborative efforts in emergency management. This research investigates diversified collaborative behaviors in emergency response and then examines this using a multi-dimensional model consisting of joint decision making, joint implementation, compromised autonomy, resource sharing, and trust building. We surveyed 148 local governments and their affiliated sectors in China in-depth understanding how collaborative processes contribute to perceived outcomes from perspectives of participating sectors in the context of a centralized political-administrative system. A structural equation model (SEM) is employed to encode multiple dimensions of the collaborative process, perceived outcomes, as well as their relationships. The empirical finding indicates that joint decision making and implementation positively affect the perceived outcomes significantly. The empirical results indicate that joint decision making and joint implementation affect perceived outcomes significantly. Instead, resource sharing and trust building do not affect the outcomes positively as expected. Additionally, compromised autonomy negatively affects the collaborative outcomes. We also discuss the institutional advantages for achieving successful outcomes in emergency management in China by reducing the degree of compromised autonomy. Our findings provide insight that can improve efforts to build and maintain a collaborative process to respond to emergencies.

Machine learning has recently drawn much attention for a variety of applications, thanks to its good performance in identification, recognition, and regression problems. One such important application is V2V communication propagation channel research. In this article, the challenges and opportunities of machine-learning-based data processing techniques for evaluation of V2V channel measurements are presented. This article reviews some state-of-the-art applications including identification of channel line-of-sight situations, tracking of MPCs, and MPC clustering. The data obtained with these methods form, inter alia, the basis for accurate channel models. Furthermore, some challenges of machine-learning-based data processing for V2V channel research are discussed as basis for future studies.

Three dimensional (3D) Multiple Input and Multiple Output (MIMO) is one of the most promising techniques for the 5th generation (5G) mobile communication system. To support its research, the property of elevation angle in 3D channel model should be accurately modeled. Conventionally, 3D channel is modeled with an assumption that the mean elevation angle of multipaths is coincided with the line-of-sight (LOS) direction. In order to investigate its authenticity and give the reliable 3D channel model, extensive 3D multiple antenna field channel measurements with 100 MHz bandwidth are conducted in three typical scenarios, including outdoor to indoor(O2I), urban microcell (UMi) and urban macrocell (UMa). The statistical characteristics and parameters are extracted and analyzed based on the measurement data. It is found that the assumption holds in the LOS condition. However, for non-line-of-sight (NLOS) condition, a difference exists between the mean elevation angle and the direction connecting transmitter and receiver, which is defined as the elevation angle offset. Then, the eigenvalue distribution and capacity are compared between the reconstructed 3D channels with and without elevation angle offset. Results show that the performance of 3D channel with angle offset fits the measurement data better whereas that without angle offset is underestimated.

Tourmaline, one of the most important hosts of boron (B) in crustal rocks, has rarely been found in natural high-pressure (HP) and ultra-HP (UHP) eclogites. Here, we report the first finding of tourmaline-bearing UHP eclogites and veins in the Dabie terrane, China. These distinctive samples occur exclusively in impure UHP marbles. Investigations on the eclogite-vein-marble system provide important insights into the origin, flow, and metasomatic effects of eclogite-facies, 11B-rich fluids in continental subduction zones. Petrologic and geochemical evidence indicates that tourmaline in the eclogites (Tur-E) formed by metasomatism due to the infiltration of a B-rich fluid under conditions of ca. 2.2–2.6 GPa and 610–660 °C. The HP veins, containing euhedral tourmaline (Tur-V) and occurring at the eclogite-marble contacts or in the interiors of eclogite lenses, represent the crystallized products of the infiltrating fluid. Systematic compositional variations along the profile from the interiors of the eclogite lenses to their margins and mass-balance calculations indicate large inputs of B, carbon, large ion lithophile elements, and light rare earth elements to the eclogites during fluid infiltration. All types of tourmaline, including the Tur-E and Tur-V as well as minor amounts of tourmaline in the marbles (Tur-M), have similar compositions (dravitic) with XMg values [= Mg/(Mg + Fe)] of 0.7–0.8. In situ analyses using laser ablation multicollector inductively coupled plasma mass spectrometry show that all of tourmaline has high δ11B values (ranging from +6 to +15‰), which suggest a 11B-rich isotope signature for the infiltrating fluid. The tourmaline B isotope data, together with the detailed field observations and whole-rock Sr-Nd isotopes, reveal that the infiltrating fluid was derived from the impure marbles. Influx of such fluid was highly channelized and was mainly achieved along lithologic boundaries between UHP marbles and eclogites or along fractures in the eclogites. This study indicates that impure marbles are an important reservoir of isotopically heavy B in deeply subducted continental slabs. This point may be of particular importance because most B reservoirs in subducted continental crust typically have light B isotopic compositions. Our results highlight that subducted metacarbonate rocks could liberate eclogite-facies, B-rich, high-δ11B fluids and thus might exert important effects on the cycle of B and its isotopes in subduction zones.

In this work, a silicon-on-insulator (SOI) lateral diffused MOSFET (LDMOS) incorporated with sidewall field plate (SEP) is presented and investigated using three-dimensional numeric simulation. A new additional electric field peak is formed, due to the compound field plate established along the n-drift region. The lateral surface electric field can be modulated, which enhances the breakdown voltage. Meanwhile, the doping concentration of n-drift region is increased, which decreases the specific on-resistance. Compared with the superjunction LDMOS, a 23.7% increase in the breakdown voltage and a 21.7% decrease in the specific on-resistance are obtained in the SFP-LDMOS device.

Bone is one of the most common sites of breast cancer metastasis and a major cause of high mortality in these patients. Thus, further understanding the molecular mechanisms regulating breast cancer-induced osteolysis is critical for the development of more effective treatments. In this study, we demonstrated that important roles sterol regulatory element-binding protein 2 (SREBP-2) play in osteoclast formation a function, and in breast cancer metastasis. SREBP-2 expression was found to be induced during the early stages of osteoclast formation under the control of the RANKL/cAMP-response element binding protein (CREB) signaling cascade. SREBP-2 is subsequently translocated into the nucleus where it participates with other transcriptional factors to induce the expression of NFATc1 required for mature osteoclast formation. Additionally, SREBP-2 was also found to be highly expressed in breast cancer tissues and correlated with a poor prognosis. SREBP-2 was similarly under the transcriptional control of CREB and its induction regulates the expression of matrix metalloproteinases (MMPs), key degradative enzymes involved in bone metastases by breast cancer cells. Accordingly, targeting of SREBP-2 with Fatostatin which specifically inhibits SCAP (SREBP cleavage-activating protein) and prevents SREBP activation, attenuated breast cancer-induced osteolysis in vivo. Collectively, our results suggest that SREBP-2 plays a critical role in regulating osteoclastogenesis and contributes to breast cancer-induced osteolysis. Thus, SREBP-2 inhibition is a potential therapeutic approach for breast cancer patients with osteolytic bone lesions.

In this paper, a new silicon-on-insulator superjunction lateral double-diffused MOSFET (SOI SJLDMOS) with a p-trench layer and stepped buried oxide, is investigated using 3D numerical simulation. The p-trench layer and stepped buried oxide distinguish it from a conventional SOI SJLDMOS. The etched buried oxide layer, with its stepped buried -oxide structure, which facilitates a more even electric field distribution via the electric field modulation effect, increases the breakdown-voltage (BV). Furthermore, the p-trench layer improves the doping concentration through compensation depletion, which further decreases the specific on-resistance (Ron,sp). The simulation indicates that the new device has a higher BV (increased by 29%) than the conventional SOI SJLDMOS. At the same time, Ron,sp decreases by 20% for the on-state for a given drift-region length.

Balance of osteoclast formation is regulated by the receptor activator of NF-κB ligand and extracellular negative regulators such as IFN-γ and IFN-β. However, very little is known about the intrinsic negative regulatory factors of osteoclast differentiation. Recently, the paired-box homeodomain transcription factor Pax6 was shown to negatively regulate receptor activator of NF-κB ligand-mediated osteoclast differentiation. However, the mechanism underlying this regulation is still unclear. In this study, we show that a p38 inhibitor (VX-745) up-regulates the expression of Pax6 during osteoclast differentiation. Subsequently, we found that β-catenin could bind to the proximal region of Pax6 promoter to induce its expression, and this action could be impaired by p38-induced ubiquitin-mediated degradation of β-catenin. Our results suggest that Pax6 is regulated by a novel p38/β-catenin pathway. Pax6 can further regulate the nuclear translocation of NF of activated T cells, cytoplasmic 1. Our study indicates that this novel p38/β-catenin/Pax6 axis contributes to negative regulation of osteoclastogenesis. In addition, our study proposes a novel approach to treat osteoclast-related diseases through the use of VX-745 complemented with the β-catenin activator SKL2001.-Jie, Z., Shen, S., Zhao, X., Xu, W., Zhang, X., Huang, B., Tang, P., Qin, A., Fan, S., Xie, Z. Activating β-catenin/Pax6 axis negatively regulates osteoclastogenesis by selectively inhibiting phosphorylation of p38/MAPK.

The radio wave is the carrier that transmits information in wireless communications. It propagates across space through a complex and dynamic mechanism. However, the radio waves are invisible, which makes it hard to design wireless communication systems. This demonstration presents a system architecture and implementation via virtual reality (VR) that can make people open the "eyes" to see the radio waves, and provide a novel method of using the radio waves designing and optimizing wireless communication systems. Users can see how the radio waves propagate in a 3D view. Furthermore, channel impulse responses (CIRs) and channel fading properties, e.g., path loss and delay spread, can be derived and visualized through the virtual interface. Also, this demo enables users to investigate the performance of base station (BS) deployment and hybrid beamforming (HBF) algorithms via VR. In a nutshell, this demo is helpful to feel, understand, and use the radio waves to improve the efficiency of wireless communication technologies and systems.

Background: Recent findings indicated a high comorbidity between attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), as well as shared genetic influences on them. The latter might contribute at least partly to the former clinical scenario. This study aimed at investigating whether SHANK genes were potential pleiotropic genes to the two said disorders, underlying their genetic overlap.Methods: This study recruited 298 boys with ADHD (including 256 family trios of 1 ADHD boy and his 2 biological parents), 134 boys with ASD, 109 boys with both ADHD and ASD, and 232 typically developing boys as community controls. They were aged between 6 and 11 years old.Results: There was no significant difference in allele frequency of a number of single nucleotide polymorphisms (SNPs) in SHANK2/SHANK3 between the three clinical groups (ADHD, ASD, and ADHD + ASD) and between the two control groups (community controls and pseudo-controls), respectively. The three clinical groups and the two control groups were thus, respectively, combined. A comparison between the two aggregated samples identified significant evidence of disease association for three SHANK2 SNPs with both ADHD and ASD, even after multiple testing correction: rs11236616 (OR = 0.762, permuted p = 0.0376), rs7106631 (OR = 0.720, permuted p = 0.0034), and rs9888288 (OR = 0.770, permuted p = 0.0407). Comparisons among individual groups pointed to a similar trend of findings.Conclusion:SHANK2 could be considered a potential pleiotropic gene underlying the genetic overlap between ADHD and ASD. This might contribute partly to their high comorbidity in the afflicted children.

Collaborative problem solving (CPS) competency is critical in the twenty-first century. The Program for International Student Assessment (PISA) launched a large-scale assessment of CPS competency for the first time in 2015. Beijing, Shanghai, Jiangsu, and Guangdong provinces in China participated the assessment and scored an average of 496, which was slightly lower than the OECD average 500 and ranked 25th among the 51 countries and economies participating in the assessment. Therefore, this research was conducted to dig into the factors predicting students’ CPS competency, and help students improve it. Most research about CPS has fallen into the construction of the CPS framework and the effectiveness of CPS; research focusing on the factors predicting CPS competency is rare. Accordingly, a hierarchical linear model (HLM) was constructed to investigate the factors predicting students’ CPS competency in the current research. The model revealed that there was a large difference of students’ CPS competency among schools. In addition, among student-level variables, gender, grade, ESCS, ICT resources, students’ attitude toward CPS, and teacher unfairness were effective in predicting students’ CPS competency; among school-level variables, school location, schools’ ESCS and the proportion of all teachers fully certified predicted students’ CPS competency positively. The findings implied that in order to enhance students’ CPS competency, CPS competency training should be permeated through all the subjects; schools should employ teachers who are fully qualified; teachers should treat each student fairly; and students should be provided with more ICT resources and etc.

Mitogen-activated protein kinase (MAPK) cascades have a universal cell signaling mechanism in eukaryotes. A typical MAPK signal transduction module comprises three kinds of sequentially phosphorylated protein kinases: MAPK, Mitogen-activated protein kinase kinase (MAPKK), and Mitogen-activated protein kinase kinase kinase (MAPKKK). However, little is known regarding the genes involved in MAPK cascades in Ophiocordyceps sinensis. Nine genes (three MAPK, three MAPKK, and three MAPKKK) were identified in this study. The MAPK, MAPKK, and MAPKKK genes were divided into three subfamilies, according to the phylogenetic analysis. TEY and TGY represented the activation domains of the MAPKs; the corresponding domains in MAPKKs were SDIWS and SDVWS, and those in the MAPKKs were GSVFYWMAPEV and GTPMYMSPEV. Transcription data analysis and quantitative real-time polymerase chain reaction showed that the MAPK cascade was related to the growth of the fruiting body. This is the first study to report a genome-wide identification of the MAPK, MAPKK, and MAPKK gene families in O. sinensis.

In view of the safety risks of personnel and tools in the insulation short stick method for live-working on distribution network, this paper analyzes the minimum safety distance requirements under different conditions by using insulation coordination idiom combined with operation mode, and analyzes the electromagnetic compatibility risk and protection requirements faced by electric tools in uninterrupted operation by using simulation calculation and simulation experiment. The minimum safety distance is 0.4m if the insulation shielding measures are taken in the insulation short stick method, and 0.9m if the insulation shielding measures are not taken. According to the characteristics of the disturbance source when the tool contacts the wire, the metal of the shell should be well connected, and the discharge air gap should be calculated between different metals with insulation isolation. Secondly, the external connecting cable must be shielded cable, and the in and out shell should be shielded.

Environmental modeling errors have significant influence on the accuracy of ray tracing (RT) based channel modeling method. The aim of this paper is to provide reference for determining the appropriate accuracy of indoor databases to achieve prediction results within tolerance. Therefore in this paper, we discuss the influence of modeling errors on the RT-based channel modeling accuracy for millimeter-wave frequency bands. Different from the previous work, our discussion mainly foucus on the indoor environments and try to analyze the relationship between the channel parameters including received power, delay spread (DS), angle spreads (AS) and the types of scatterers. Simulation results show the RT results are more sensitive to the geometric errors caused by the room boundary in the line-of-sight (LOS) case while indoor scatterers have a greater impact in the non-LOS (NLOS) case. Additionally, AS is more sensitive to geometric errors of environment than DS. These results have guiding significance for channel modeling and simulation work using RT.

Radio wave propagation in a waveguide-like structure scenario performs a specific path loss characteristic which is termed as waveguide effect. In this paper, we analyze the path loss characteristics in a waveguide-like structure scenario based on channel measurements at 28 GHz. First, three different modeling methods, including the waveguide approach, ray-tracing approach, and empirical approach, are compared and validated with the measurement results. This study suggests that the empirical dual-slope channel model can give a more accurate prediction of path loss with minimum root mean square error (RMSE). Secondly, the influence of the geometry position of antennas on path loss is investigated by using the dual-slope path loss model. Comparative analysis results reveal that a stronger waveguide effect exists when placing the antenna close to the wall and when having antenna height difference, horizontal measurements at different line-of-sight distances confirm the analysis that waveguide effect exists after the breakpoint.

In this paper, we propose a novel 3D scenario information based channel modeling method with deep learning for Vehicular-to-infrastructure (V2I) communications. Specifically, the vehicular scanning sensors are utilized to capture the point cloud information of 3D scenario directly, and then the channel characteristics are generated and mapped with the 3D scenario information by deep learning network. Benefited from the above modeling framework, the complexity of environment reconstruction and geometric calculation can be reduced greatly. The simulation results show that the prediction precision of reflection point by deep learning has significant impact on the modeling accuracy. By some efficient scenario information extraction operations, the proposed method can realize more than 95% channel modeling accuracy with much lower complexity.

A 28-year-old woman with vaginal discharge was admitted to the hospital. Colposcopy examination found several ulcers with pus in the vagina. Biopsy demonstrated extranodal natural killer/T-cell lymphoma. PET/CT scan was subsequently performed for staging. It revealed intense FDG uptake in the vagina. No FDG-avid lesion was seen in the rest of the body. A primary vaginal extranodal natural killer/T-cell lymphoma was diagnosed.

Bromodomain and extraterminal (BET) proteins bind acetylated lysine residues in histones and nonhistone proteins via tandem bromodomains and regulate chromatin dynamics, cellular processes, and disease procession. Thus targeting BET proteins is a promising strategy for treating various diseases, especially malignant tumors and chronic inflammation. Many pan-BET small-molecule inhibitors have been described, and some of them are in clinical evaluation. Nevertheless, the limited clinical efficacy of the current BET inhibitors is also evident and has inspired the development of new technologies to improve their clinical outcomes and minimize unwanted side effects. In this Review, we summarize the latest protein characteristics and biological functions of BRD4 as an example of BET proteins, analyze the clinical development status and preclinical resistance mechanisms, and discuss recent advances in BRD4-selective inhibitors, dual-target BET inhibitors, proteolysis targeting chimera degraders, and protein-protein interaction inhibitors.

Intervertebral disc degeneration (IDD) is closely related to loss of the extracellular matrix (ECM), apoptosis and inflammation in nucleus pulposus cells (NPCs). It has been reported that Zinc finger protein A20/TNFAIP3 (A20) can inhibit the activity of the NF-κB pathway and promote autophagy. Therefore, we speculated that A20 can regulate inflammation and ameliorate IDD through autophagy mediated by NF-κB in human NPCs. Our results indicated that the expression of A20 and inflammatory factors in IDD tissues was increased. A20 is an essential negative regulator in the NF-κB pathway. Constructed adenoviral shRNA and overexpression vectors for A20 could effectively regulate the inflammation, autophagy, and activity of NF-κB, which in turn affected the progression of IDD. Inhibition of NF-κB on the basis of knocking down A20 results in increased autophagy, suggesting that A20-regulated autophagy was mediated by NF-κB. In vivo, A20 overexpression could ameliorate the progression of IDD and promote autophagy at the same time, while deletion of A20 leads to low levels of autophagy and severe degeneration. In summary, A20 plays an important role in inhibiting inflammation through autophagy mediated by NF-κB in NPCs and ameliorating IDD.

The shortest path model is selected to evaluate the regional traffic accessibility. Three index factors, gross regional product, total retail sales of consumer goods, and the number of permanent residents in the region, were selected, and the weight sum was given by entropy weight method to evaluate the regional economic intensity. The gravity model adding the regional accessibility index considering traffic factors is selected to evaluate the regional linkages. By integrating the three indexes, an evaluation index system of rail transit benefits is formed to study the utility of rail transit to the economic development of surrounding areas, and to provide scientific theoretical basis and guidance for the government to carry out urban construction and rail transit management.

With the advent of the 5G era, the competition in the telecom industry is increasingly fierce, and the prediction of customer churn has become the key to the survival and development of enterprises. This paper proposes a customer churn prediction model combining K-means and XGBoost algorithm. First, K-means cluster processing is carried out on the training set, then XGBoost is used to train the clustering groups respectively, and finally, the integrated process is carried out. The results show that the model has better generalization ability.

Human dihydroorotate dehydrogenase (hDHODH) is a flavin-dependent enzyme catalyzing the fourth step of pyrimidine de novo biosynthesis. Since aberrant pyrimidine metabolism is closely related abnormal cell proliferation, hDHODH is believed to have an intimate linkage with cancers. For instance, hDHODH induces the abrogation of β-catenin degradation and cell proliferation in esophageal squamous cell carcinoma (ESCC). Thus, small molecular inhibitors targeting hDHODH has been considered as a promising strategy for cancer treatment. In recent years, in exploiting novel structural hDHODH inhibitors (hDHODHi), a candidate drug PTC299 has entered clinical trials for treating acute myelocytic leukemia (AML) and other tumors. This review discusses tumor-related research of hDHODH and highlights the structure-activity relationships of hDHODHi, providing insights into new drugs targeting hDHODH for antitumor clinical practice.

Injectors are key pieces of equipment for chemigation systems, and their hydraulic performance has a significant effect on chemigation systems and crops. In order to investigate the influence of different working parameters on hydraulic performance for a water-powered proportional injector (PI), three key parameters of inlet and injection flow rate were researched using a one-factor experimental design method. The regression equations between different factors and response variables were established through a response surface method based on one-factor experimental results. Lastly, a mathematical model of the actual injection ratio was established. Some experiments under different, randomly selected parameter combinations were carried out to verify the prediction precision of the mathematical mode. The results showed that the injection flow rate increased first within the differential pressure of 0.05 to 0.10 MPa and then tended towards stability with increasing differential pressure. The injection flow rate decreased by increasing the viscosity and the change in the injection flow rate was small enough when the viscosity was greater than 500 mPa&middot, s. The impact factors, in order of significance, for inlet flow rate were differential pressure, viscosity of injection liquid and setting injection ratio. The impact factors, in order of significance, for injection flow rate were viscosity of injection liquid, setting injection ratio and differential pressure. The regressive model for predicting the actual injection ratio was validated using an experiment and the relative deviation between calculated value and tested value was less than 5.98%, which indicated that the mathematical model had high credibility.

Using the methods of least squares and optimization, a mathematical model is established based on the running model of Joseph B. Keller, and combining the running characteristics and actual conditions of athletes. Whole marathon is divided into three phases: the starting section, the halfway section and the sprint section. Different from previous studies, this study designs athletes to accelerate in the starting and the last stage of the race. But in the middle segment, it is an uniform motion. The study finds that the model design is in line with the objective facts of the marathon. Through this model, the relative errors between theoretical results and actual competition results can be found out realistically, so as to provide scientific training basis for marathon coaches and athletes to improve their running results. At the same time, this search proves that high-level athletes use uniform speed running in the middle of the competition, which is more conducive to exerting their level and showing better performance.

In-depth profiling of transmembrane proteins in the brain leads to the identification of GPCR regulators in a disease model., Transmembrane proteins play vital roles in mediating synaptic transmission, plasticity, and homeostasis in the brain. However, these proteins, especially the G protein–coupled receptors (GPCRs), are underrepresented in most large-scale proteomic surveys. Here, we present a new proteomic approach aided by deep learning models for comprehensive profiling of transmembrane protein families in multiple mouse brain regions. Our multiregional proteome profiling highlights the considerable discrepancy between messenger RNA and protein distribution, especially for region-enriched GPCRs, and predicts an endogenous GPCR interaction network in the brain. Furthermore, our new approach reveals the transmembrane proteome remodeling landscape in the brain of a mouse depression model, which led to the identification of two previously unknown GPCR regulators of depressive-like behaviors. Our study provides an enabling technology and rich data resource to expand the understanding of transmembrane proteome organization and dynamics in the brain and accelerate the discovery of potential therapeutic targets for depression treatment.

The aim of this study is to improve the water distribution uniformity of a vertical impact sprinkler and explore the design method of the drive spoon blades. The width of straight blades (h1), the width of curved blades (h2) and number of blades (s) were chosen as the experiential variables. The suitable ranges of three variables for response surface method were determined initially by one-factor experimental design method, and 17 different drive spoons were designed according to response surface methodology. The results showed that in the one-factor experimental condition, the CU (Christiansen’s uniformity coefficient) values first increased and decreased slightly when h1 exceeded 3 mm with the increase of h1 within the variation range of the experimental factor. The CU values firstly increased and then decreased with the increase of h2. The CU values decreased rapidly when s was less than 3 or greater than 6. The relationship between CU values and h1, h2 and s was established using response surface methodology. The p-values for h1, h2 and s were 0.0359, 0.0092, 0.0212, and all of the selected factors were significant on CU. The order of parameters affecting CU were h2, h1 and s. The ideal parameters for the drive spoon blades were h1 = 6 mm, h2 = 4 mm, and s = 3. CU was greatly improved after the optimization of structure for the drive spoon blades, which increased to 87.96% from 73.12%. After optimization, the application rates within 1 to 5 m were improved and increased from 10% to 15% with an average of 10.7% under different operating pressures. The maximum application rates decreased from 9.3, 9.3, 9.4 and 8.4 mm·h−1 to 8.5, 8.4, 8.5 and 7.9 mm·h−1 with operating pressures of 300, 400, 500 and 600 kPa, respectively. The maximum application rates in the overlap area were decreased from 18, 16, 16 and 15 mm·h−1 to 16, 14, 14 and 12 mm·h−1 with operating pressures of 300, 400, 500 and 600 kPa, respectively.

Tri-polarized MIMO system can provide higher capacity, which has been proved theoretically and verified in some real simple indoor channel measurements. In this paper, we did the channel measurements using dipole to form tri-polarized MIMO antennas with 100 MHz bandwidth at 4.9 GHz carrier frequency in Urban Microcell (UMi) scenario. Typical channel propagation characteristics are analysed based on the channel measurement, including cross-polarization discrimination (XPD), correlation coefficient (CC), eigenvalue distributions of channel matrix, and capacity gain (CG). It can be observed that the tri-polarized MIMO channel has three non-zero eigenvalues which support three independent subchannels. It is worthy noted that in UMi scenario, there is a nearly threefold CG in both line-of-sight (LOS) and non-line-of-sight (NLOS) routes by analyzing CC and eigenvalue distributions. This can be well explained by density buildings and low antenna heights in UMi scenario, which leads to rich scattering environment. Therefore, the tri-polarized MIMO is promising to improve the performance in rich-scattering scenarios, e.g., UMi scenario. The results can provide insights for the application of tri-polarized MIMO systems.

Artificial joint replacement is an effective surgical method for treating end-stage degenerative joint diseases, but peripheral bacterial infection of prosthesis can compromise the effect of the surgery. Herein, antibacterial effects of titanium dioxide nanotubes (TNTs) coated with polyhexamethylene guanidine (PHMG) were examined via in vitro and in vivo experiments. TNTs with a pore diameter 46.4 ± 5.9 nm and length of 300-500 nm for the slice and 650-800 nm for the rod were fabricated by anodization. Then, 3.46 ± 0.40 mg and 1.27 ± 0.28 mg of PHMG were coated onto the TNT slice and rod, respectively. In vitro studies of the release of PHMG showed that the antibacterial agent was released in two stages: initial burst release and relatively slow release. In vitro and in vivo antibacterial studies showed that the PHMG-loaded TNTs (PHMG-TNTs) had excellent antibacterial abilities to prevent bacterial infections. Clinical pathological analysis of rabbit femurs indicated that the implanted PHMG-TNTs had no apparent pathological changes. Real-time quantitative reverse transcription polymerase chain reaction analysis of the femur tissues around the implants showed that the expression of osteogenic-related genes, including runt-related transcription factor 2, osteocalcin, alkaline phosphatase, bone sialoprotein, bone morphogenetic protein 2 and vascular endothelial growth factor A, was significantly upregulated in the PHMG-TNT implanted group as compared to the other groups. Overall, these findings provide a promising approach for the fabrication of antibacterial and bone biocompatible titanium-based implants in orthopedics.