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To reduce the weight of vehicles and save on fuel consumption, the forming analysis and process study for a 6082 aluminum alloy automobile control arm were conducted, and the results are reported here. First, the parameters of the constitutive equation of the 6082 aluminum alloy are determined, and the forming process and the dies of the stretch rolling, bending, and die-forging are proposed and discussed according to the given contours of the control arm. Then, the control arm is simulated by means of Deform-3D, the experiment results of the automobile control arm are compared with the simulation results, and the tensile strength, yield strength, and elongation of the test bars obtained from the control arm can meet the mechanical performance requirements based on the tensile test rig. Finally, the relationship of the die load, die wear, workpiece damage, and workpiece equivalent stress with different processing parameters are analyzed, and the effects of different solid solution times on the strength of control arm are discussed. The results show that when the friction coefficient is 0.3, the die temperature is 250°C, the forging velocity is 230 mm/s, the strain rate is 1s−1 and the solid solution time is 30 min, the die load, die wear, workpiece damage, workpiece equivalent stress, and the mechanical strength are then in a good state. The results of this research provide a reliable basis and analysis method for the forging of aluminum alloy automobile control arms.

Fast and accurate counting of wheat ears in field conditions is a key element for determining wheat yield. To obtain the number of wheat ears in a field, we propose a new counting algorithm based on computer vision. This algorithm counts wheat ears in remote images through semantic segmentation regression network (SSRNet). SSRNet is a multistage convolutional neural network that we propose to achieve counting problems through regression. In SSRNet, first, the original image is cropped to increase the amount of data. This method effectively solves the small sample dataset. Next, based on the cropping results, we build a fully convolutional neural network (FCNN) to segment wheat ears in field conditions. FCNN increases the accuracy of wheat ears counting by accurately segmenting wheat ears in a complex background. Then, we build a regression convolutional neural network (RCNN) to count wheat ears based on the segmentation results of FCNN. In RCNN, we propose a new activation function positive rectification linear unit (PrLU) to process the last layer of the fully connected layer, so that RCNN can effectively count the number of wheat ears in the image. Finally, a counting strategy is proposed to count the number of wheat ears in the original image. To verify the counting performance of SSRNet, we compare the counting result of SSRNet with the real value of manual statistics. The results show that the average accuracy (Acc), R², and root mean squared error (RMSE) of the SSRNet count results on the test set in this article are 0.980, 0.996, and 9.437, respectively. It can be seen from the results that our proposed method can accurately count wheat ears in field conditions. At the same time, the counting time (0.11 s) shows that SSRNet can quickly estimate the number of wheat ears in field conditions. We concluded that this study can provide important technical support for the high-throughput field wheat ears counting task in large-scale phenotyping work.

The mass variances of materials in buckets and the movements of excavation arms greatly impact powertrain vibration transmissibility in hydraulic excavators under working conditions. If the influence of mass variation among bucket contents and excavation arm motions on vibration transmissibility is not considered, then only limited improvements can be made to vibration isolation performance. In this paper, vibration transmissibility suppression for hydraulic excavators operating under working conditions were studied via multi-objective optimization for stiffness coefficients of suspension elements (SEs). First, the rigid-flexible coupling model of a hydraulic excavator with a flexible base was built using ADAMS software. In the model, the stiffness coefficients of the SEs were the targeted variables with constrained conditions, while the multi-objectives for optimization were the vibration transmissibility and energy decoupling rates of the powertrain. Vibration isolation transmissibility (VIT) of the mounting system was compared between situations with non-optimized and optimized stiffness coefficients. Finally, the amplitude changes of the resultant SE support forces were used to illustrate the effects of powertrain vibration transmissibility suppression. We found that the average value of VITs increases significantly during the optimization process for the stiffness coefficients of SEs, which indicates that the mounting system has better vibration isolation performance. The smaller amplitudes of the resultant support force illustrate the improvements to the performance of vibration transmissibility suppression of the powertrain via the optimization process.

The loop thermosyphons has advantages of high heat transmission efficiency and needing no additional power. It can quickly draw out the heat in the motorized spindle with no coolant getting into the shaft, and has a good application prospect in the field of motorized spindle cooling. However, the evaporation and condensation sections of a loop thermosyphon will be in the same pipe and at the same height under the heat conduction of the shaft. These structural changes will directly affect the flow characteristecs and heat transfer performance of the loop thermosyphon. This paper experimental studied the vapor-liquid two phase flow characteristics in a pentane loop thermosyphon. The effects of the heat input power and fill ratio on the flow characteristics were analyzed. Results show that the two-phase flow pattern transitions from stratified flow to wavy flow and finally to plug flow as fill ratio increases. The velocity of the liquid flow in the upper adiabatic section of the loop thermosyphon is on the order of 0.1 m·s-1, and it decreases with increasing heat input when the fill ratio is between 30 and 70 %.

Background Fine-scale genetic structure of ethnolinguistically diverse Chinese populations can fill the gap in the missing diversity and evolutionary landscape of East Asians, especially anthropologically informed Chinese minorities. Hmong-Mien (HM) people were one of the most important indigenous populations from South China and Southeast Asia, which were suggested to be the descendants of the Yangtze rice farmers based on linguistic and archeological evidence. Guizhou Miao, possessing a specific genetic structure, harbored a close genetic relationship with geographically close Guizhou populations and Guangxi historical people. We genotyped genome-wide SNP data in Guizhou HM-speaking populations and merged it with modern and ancient reference populations to explore the evolutionary and adaptive characteristics of Miao people via a comprehensive population genetic analysis. Results The overall genetic admixture landscape of Guizhou Miao showed genetic differentiation between them and other linguistically diverse Guizhou populations. Admixture models further confirmed that Miao people derived their primary ancestry from geographically close Guangxi Gaohuahua people. The estimated identity by descent (IBD) and effective population size further confirmed a plausible population bottleneck, contributing to their unique genetic diversity and structure pattern. We finally identified several natural selection candidate genes associated with several biological pathways. Conclusions We found Guizhou Miao with a specific genetic structure harbored a close genetic relationship with geographically close Guizhou populations and Guangxi historic people. Miao people derived their major ancestry from geographically close Guangxi Gaohuahua people and a plausible population bottleneck which contributed to the unique pattern of their genetic diversity and structure. Future ancient DNA from Shijiahe and Qujialing would further promote new insights into the origin of the Miao people.

mascRNA (MALAT1-associated small cytoplasmic RNA) is a tRNA-like cytoplasmic small noncoding RNA whose function remains elusive. We previously revealed that this small RNA negatively regulates TLR4/2-triggered proinflammatory response while positively regulates TLR3-induced antiviral response. Here, we investigated whether and how mascRNA influences the stimulator of interferon genes (STING) signaling-triggered immune response. We found that overexpression of mascRNA inhibited the expression of type I interferon (IFN) genes and proinflammatory cytokines in response to cytosolic DNA stimulation; meanwhile, the abundance of STING protein and the level of phosphorylated TBK1 and STAT1 was decreased. By contrast, depletion of mascRNA potentiated the expression of type I IFNs, increased STING protein abundance, and promoted STING-mediated phosphorylation of TBK1 and STAT1 in response to DNA stimulation. In a mouse model of DNA-induced lung injury, exogenous mascRNA mitigated the antiviral response and the severity of lung inflammation. Mechanically, mascRNA was found to promote STING for K48-linked ubiquitination and degradation in macrophages both with and without cytosolic DNA stimulation. Hence, mascRNA suppresses STING-TBK1 signaling-mediated innate immunity through promoting proteasomal degradation of STING, and this tRNA-like small RNA holds promise for the treatment of certain inflammatory diseases such as COVID-19 where aberrant STING signaling drives type I IFN immunopathology.

An implementation of a cooling structure using Two-Phase Loop Thermosiphons (TPLTs) to cool the shaft in a motorized spindle was developed and tested. For this purpose, a shaft with a cooling structure based on TPLTs was designed and tested at rotational speeds of 1000–2000 rpm and a heating power of 50–250 W. Subsequently, the temperature field distribution of a motorized spindle with TPLTs cooling structure was calculated. The results showed that the rise in temperature of the shaft with rotational TPLTs reduced by 60% to 64% and the time required to achieve thermal equilibrium reduced by 18 to 23%. The heat transfer performance of the rotational TPLTs increased with increasing rotational speed. In addition, the liquid fill ratio corresponding to the minimum thermal resistance at the same heat input tended to decrease with increasing rotational speeds. This TPLTs shaft cooling structure could cool the main components of a motorized spindle and reduce the rise in their temperature.

ABIN-1, also called TNIP1, is an ubiquitin-binding protein that serves an important role in suppressing RIPK1-independent apoptosis, necroptosis, and NF-κB activation. However, the involvement of ABIN-1 in the regulation of RIPK1-dependent apoptosis (RDA) is unknown. In this study, we found that poly(I:C) + TAK1 inhibitor 5Z-7-oxozeaenol (P5) concurrently induces RDA and necroptosis in Abin-1−/−, but not in Abin-1+/+ mouse embryonic fibroblasts (MEFs). Upon P5 stimulation, cells initially die by necroptosis and subsequently by RDA. Furthermore, we explored the therapeutic effect of ABIN-1 deficiency in necroptosis-based cancer therapy in colorectal cancer (CRC). We found that poly(I:C) + 5Z-7-oxozeaenol + IDN-6556 (P5I) yields a robust pro-necroptosis response, and ABIN-1 deficiency additionally enhances this P5I-induced necroptosis. Moreover, phase I/II cIAP inhibitor birinapant with clinical caspase inhibitor IDN-6556 (BI) alone and 5-fluorouracil with IDN-6556 (FI) alone are sufficient to induce necroptotic cell death in CRC cells by promoting auto-secretion of tumor necrosis factor (TNF); ABIN-1 deficiency amplifies the BI- or FI-induced necroptosis. Two independent xenograft experiments using HT-29 or COLO205 cells show that both BI and P5I remarkably inhibit tumor growth via necroptosis activation. For poly(I:C)-induced cell death, the sensitizing effect of ABIN-1 deficiency on cell death may be attributed to increased expression of TLR3. In TNF-induced necroptosis, ABIN-1 deficiency increases TNF-induced RIPK1 polyubiquitination by reducing the recruitment of ubiquitin-editing enzyme A20 to the TNFR1 signaling complex and induces more TNF secretion in CRC cells upon pro-necroptosis stimulation. With this combined data, ABIN-1 deficiency promotes greater sensitization of CRC cells to necroptosis.

Shaft cooling using loop thermosyphons is an ideal method for cooling motorized spindles. To investigate this application, it was necessary to investigate the heat transfer performance of loop thermosyphons while in a state of rotation. This paper describes cooling a shaft with a set of loop thermosyphons as its cooling structures. These thermosyphons’ designs are described and a series of experiments were conducted with liquid filling ratio ranging within 15% - 60% under 1000 r·min−1. The experimental results show that the optimal liquid filling ratio (FR) range of the rotating loop thermosyphons was 15%–45% and the thermal resistance would increase rapidly with FR when FR>45% under 1000 r·min−1.

Accurate counting of wheat ears in field conditions is vital to predict yield and for crop breeding. To quickly and accurately obtain the number of wheat ears in a field, we propose herein a method to count wheat ears based on fully convolutional network (FCN) and Harris corner detection. The technical procedure consists essentially of 1) constructing a dataset of wheat-ear images from acquired red-green-blue (RGB) images; 2) training a FCN as the wheat-ear segmentation model by using the constructed image dataset; 3) preparing testing images and inputting them into the segmentation model to get the initial segmentation results; 4) binarizing the initial segmentation by using the Otsu algorithm (to facilitate subsequent processing); and 5) applying Harris corner detection after extracting the wheat-ear skeleton to obtain the number of wheat ears in the images. The segmentation results show that the proposed FCN-based segmentation model segments wheat ears with an average accuracy of 0.984 and at low computational cost. An average of only 0.033 s is required to segment a 256× 256 -pixel wheat-ear image. Moreover, the segmentation result is improved by nearly 10% compared with the previous segmentation methods under conditions of wheat-ear occlusion, leaf occlusion, uneven illumination, and soil disturbance. Subsequently, the proposed counting method achieves good results, with an average accuracy of 0.974, a coefficient of determination (R2) of 0.983, and a root mean square error (RMSE) of 14.043. These metrics are all improved by 10% compared with the previous methods. These results show that the proposed method accurately counts wheat ears even under conditions of wheat-ear adhesion. Furthermore, the results provide an important technique for studying wheat phenotyping.

Corn is one of the most important food crops in the world, but there are many kinds of corn diseases, and it is difficult to diagnose by planting personnel based on experience. However, the misdiagnosis reduces production efficiency. With the development of computer technology, the use of deep learning and image recognition technology for plant disease detection has become an important research direction. We propose a convolutional neural network based on data augmentation combined with transfer learning to identify corn leaf disease models. The algorithm first increases the data by means of data augmentation to improve the generalization and accuracy of the model, and builds a convolutional neural network model based on transfer learning. Then, it uses the model for training, accelerates the training process of the convolutional neural network, and uses test dataset feedback network training results. In this study, the corn leaf images in PlantVillage were used as the dataset of our experiment to classify the four categories which consists of Corn Gray leaf spot, Corn Common rust, Corn Northern Leaf Blight and healthy leaves. We first obtained our optimization model by fine-tuning the GoogLeNet pre-training network, adjusting parameters such as optimizer and learning rate. Then we trained the optimization model, like the original GoogLeNet network, ResNet18, Vgg16, and Vgg19 networks based on transfer learning and compare the results. The results show that by using our optimized model, the average recognition accuracy of corn disease which consists of corn common leaf rust, Corn Common rust, Corn Northern Leaf Blight and healthy leaves reached 97.6%, and the recognition accuracy of each category was greater than 95%. Compared with the original GoogLeNet model, the highest accuracy rate is improved by 5.9%. Also, the effect is better when compared with other networks based on transfer learning. Our model provides new ideas for the identification of diseases, insect pests of corn and other crops.

The in vivo function of p38 mitogen-activated protein kinase (MAPK) signaling in regulating the response to simulated microgravity is still largely unclear. Using Caenorhabditis elegans as an assay system, we investigated the in vivo function of p38 MAPK signaling in regulating the response of animals to simulated microgravity and the underlying molecular mechanism. Simulated microgravity treatment significantly increased the transcriptional expressions of genes (pmk-1, sek-1, and nsy-1) encoding core p38 MAPK signaling pathway and the expression of phosphorylated PMK-1/p38 MAPK. The pmk-1, sek-1, or nsy-1 mutant was susceptible to adverse effects of simulated microgravity. The intestine-specific activity of PMK-1 was required for its function in regulating the response to simulated microgravity, and the entire p38 MAPK signaling pathway could act in the intestine to regulate the response to simulated microgravity. In the intestine, SKN-1 and ATF-7, two transcriptional factors, were identified as downstream targets for PMK-1 in regulating the response to simulated microgravity. Therefore, the activation of p38 MAPK signaling may mediate a protection mechanism for nematodes against the adverse effects of simulated microgravity. Additionally, our results highlight the potential crucial role of intestinal cells in response to simulated microgravity in nematodes.

In the assessment of breathing cracks, it is assumed that both sides of the crack will contact each other along with the vibration, causing the blades to exhibit nonlinear behaviors. Therefore, nonlinear approaches are much more sensitive to the cracks and are also capable of detecting their location and size. Recently, a nonlinearity measure-based damage location method was proposed for the distributed vibration responses of beam-like structures. However, its procedures require collecting the trajectories of the non-destructive status of structures, which introduce substantial difficulties to engineering applications. In this paper, a bicoherence-based nonlinearity measurement method is proposed for identifying the location of breathing cracks in blades. It can evaluate the extent of nonlinearity in the responses of blades under random excitations and avoids using the non-destructive status of structures. The additional nonlinearity in a blade with a breathing crack, based on distributed parameter modeling, is discussed, while the distributed responses on characteristic point were collected to estimate the degree of nonlinearity. A Total Nonlinearity Index (TNLI) was used to establish the damage indicator of the blade, and the crack was identified by finding the maximum components. Validation experiments were conducted to verify the effectiveness of the proposed method, in which a vision measurement system was employed to obtain the distributed vibration responses.

Fusarium head blight (FHB), one of the most important diseases of wheat, mainly occurs in the ear. Given that the severity of the disease cannot be accurately identified, the cost of pesticide application increases every year, and the agricultural ecological environment is also polluted. In this study, a neural network (NN) method was proposed based on the red-green-blue (RGB) image to segment wheat ear and disease spot in the field environment, and then to determine the disease grade. Firstly, a segmentation dataset of single wheat ear was constructed to provide a benchmark for the segmentation of the wheat ear. Secondly, a segmentation model of single wheat ear based on the fully convolutional network (FCN) was established to effectively realize the segmentation of the wheat ear in the field environment. An FHB segmentation algorithm was proposed based on a pulse-coupled neural network (PCNN) with K-means clustering of the improved artificial bee colony (IABC) to segment the diseased spot of wheat ear by automatic optimization of PCNN parameters. Finally, the disease grade was calculated using the ratio of the disease spot to the whole wheat ear. The experimental results show that: (1) the accuracy of the segmentation model for single wheat ear constructed in this study is 0.981. The segmentation time is less than 1 s, indicating that the model can quickly and accurately segment wheat ear in the field environment; (2) the segmentation method of the disease spot performed under each evaluation indicator is improved compared with the traditional segmentation methods, and the accuracy is 0.925 in the disease severity identification. These research results can provide important reference value for grading wheat FHB in the field environment, which also can be beneficial for real-time monitoring of other crops’ diseases under near-Earth remote sensing.

Wheat (Triticum aestivum L.) is one of the three major cereals worldwide. The FusaHum graminearum Sehw., special fugus always damages the wheat ear, and produces vomitoxin,is difficult to control and prevent, and seriously threatens the health of humans, animals and China's food security. Currently, rapidly, accurately and non-destructively diagnostic devices or systems for this disease have not been disclosed. In this study, the infected ears with different severities were picked up in key growth stages. The diseased area of wheat ear was extracted using hypergreen characteristic, and a total of 30 features of infected ears were chosen including color (Lab, HSI, HSV, YCbCr color space), texture (LBP and LLE dimension reduction), and shape (squareness, shape complexity, and eccentricity). Then using the competitive adaptive re-weighted sampling (CARS) and rough set algorithm (RS) to screen the characteristics of the diseased ear, the four characteristics with the largest contribution were determined to establish the CARS-SVM and CARS-RS-SVM models respectively. The study found that the recognition rate of CARS-SVM model is 85.4%, while CARS-RS-SVM model is 92.7%. Thus the CARS-RS-SVM was thought of as the optimal model by two indicators of identification accuracy. On the basis, a wheat scab diagnosis system based on Android mobile phone was constructed. It consists of three parts - Clients, Service-Terminal and Database. The Client was designed by Android Studio and its functions mainly include image acquisition, image storage, GPS positioning, image uploading and diagnostic results display. The Service-Terminal was completed by the mixed programming of Myeclipse and Matlab software, and Tomcat was used as the Server. It mainly implements the functions of image receiving, image preprocessing, feature extraction and selection, and classifier modeling. The MySQL was used to establish two databases: the “Disease Characteristics Database” and the “Disease Diagnosis Knowledge Base”. Finally, through samples testing and validating, the Android-based mobile terminal can real-time collect the image of Fusarium head blight and upload the server. After the target image was processed and compared by the “Disease Characteristics Database”, the appropriate diagnostic knowledge was selected from the “Disease Diagnosis Knowledge Base” and feedbacked to the client. In summary, the results of this study showed that it was helpful for the rapid and non-destructive investigation of infected FHB in the field, and it would provide a reference for the study of other crop diseases, facilitate the application and development of new technologies such as artificial intelligence and big data in agriculture.

In order to obtain a lightweight Honda energy-saving race car body, the carbon fiber materials and monocoque technology were introduced into the design of the car body. Firstly, a lightweight structural monocoque body geometric model was constructed. Then the design geometric model was subjected to static strength, and the performance simulation analysis of the front collision condition and the rollover condition showed that the designed monocoque body can meet the requirements. Finally, the monocoque body model was processed and manufactured, which was assembled and integrated on the car for physics. The experiment results showed that the designed lightweight body meet the requirements of work performance.

On the basis of previous research, this paper takes a more comprehensive study on the vibration of a vehicle with automatic transmission when engine start-stop and automatic start-stop. A 13 degrees of freedom (DOFs) vehicle dynamic model is established, and the dynamic response evaluation method is put forward. Three methods to reduce the vibration of powertrain and vehicle are analyzed, and the results show that increasing the damping of the mounting system can effectively reduce the vibration in these three methods. A novel semi-active hydraulic damping strut (HDS) as the fourth mount is designed and developed, the installation position and its outer channel size are optimized and calculated respectively based on its damping force calculation method and the design method of the powertrain mounting system (PMS). The calculation results of evaluation indexes with engine start-stop are analyzed in-depth. The optimized parameters of the semi-active HDS are taken into the 13 DOFs dynamic model to analyze the dynamic response of the engine automatic start-stop process, and the values of the evaluation indexes are decreased. To validate the effectiveness of the design method of the semi-active HDS, the experiment of the vehicle with and without the semi-active HDS are carried out, and the test results show that the seat rail acceleration are reduced with semi-active HDS introduced. The active side acceleration of the torque strut calculated by the 13 DOFs model is consistent well with the measured value with and without the semi-active HDS, which proves that the model is reasonable.

In this paper, a heat pipe assisted separation type battery thermal management system (BTMS) using porous metal foam saturated with phase change material is developed to balance the temperature in a LiFePO4 battery pack. The produced heat is first transmitted to the heat management module through heat pipes, and then is absorbed by the phase change material. An additional fan is used to enhance heat dissipation when the battery temperature exceeds the setting value. Since the filling of the phase change material and other materials inside the battery pack is not required, the proposed BTMS is safe and easy for maintenance. The performance of the BTMS is experimentally investigated using a Lab-scale battery pack with constant current discharge rates of 1C, 3C, 4C, 5C, as well as different discharge-charge cycles. The results show that the proposed system offers a more suitable temperature and can better reduce the temperature imbalance within the battery pack than other methods. Especially, under the long-time operation conditions, the reliability and performance of the proposed BTMS can be greatly improved. These results are expected to provide insights into the design and optimization of BTMS.

When large-scale centralized grid connection, it will affect the safe and stable operation of the power grid. In order to ensure the safe and stable operation of power grid after wind power grid integration, it is necessary to study the penetration rate of wind power. In this paper, the grid structure is introduced into the wind power installation layout analysis to study the penetration limit of the regional power grid. The research shows that the strength of wind power grid is the decisive condition for the stable operation of the wind power grid system.

This report details the first organocatalytic method for nitrenoid transfer and its application to intermolecular, site-selective C(sp3)–H amination., This report details the first organocatalytic method for nitrenoid transfer and its application to intermolecular, site-selective C(sp3)–H amination. The method utilizes a trifluoromethyl iminium salt as the catalyst, iminoiodinanes as the nitrogen source, and substrate as the limiting reagent. Activated, benzylic, and aliphatic substrates can all be selectively functionalized in yields up to 87%. A mechanistic proposal for the observed reactivity supported by experimental evidence invokes the intermediacy of a diaziridinium salt or related organic nitrenoid, species that have not been previously explored for the purpose of C–H amination. Finally, examples of late-stage functionalization of complex molecules highlight the selectivity and potential utility of this catalytic method in synthesis.

Preference choice on food is an important response strategy for animals living in the environment. Using assay system of preference choice on bacterial foods, OP50 and PA14, we identified the involvement of ADL sensory neurons in the control of preference choice in Caenorhabditis elegans. Both genetically silencing and ChR2-mediated activation of ADL sensory neurons significantly affected preference choice. ADL regulated preference choice by inhibiting function of G protein-coupled receptor (GPCR)/SRH-220. ADL sensory neurons might regulate preference choice through peptidergic signals of FLP-4 and NLP-10 and function of FLP-4 or NLP-10 in regulating preference choice was regulated by SRH-220. FLP-4 released from ADL sensory neurons further regulated preference choice through its receptor of NPR-4 in AIB interneurons. In AIB interneurons, NPR-4 was involved in the control of preference choice by activating the functions of ASH-2 trithorax complex consisting of SET-2, ASH-2 and WDR-5, implying the crucial role of molecular machinery of trimethylation of histone H3K4 in the preference choice control. The identified novel neuronal circuit and the underlying molecular mechanisms will strengthen our understanding neuronal basis of preference choice in animals.

A Myxococcus xanthus gene, MXAN3487, was identified by transposon mutagenesis to be required for the expression of mcuABC, an operon coding for part of the chaperone–usher (CU) system in this bacterium. The MXAN3487 protein displays sequence and structural homology to adenosine 5′-phosphosulphate (APS) kinase family members and contains putative motifs for ATP and APS binding. Although the MXAN3487 locus is not linked to other sulphate assimilation genes, its protein product may have APS kinase activity in vivo and the importance of the ATP-binding site for activity was demonstrated. Expression of MXAN3487 was not affected by sulphate availability, suggesting that MXAN3487 may not function in a reductive sulphate assimilation pathway. Deletion of MXAN3487 significantly delayed fruiting body formation and the production of McuA, a spore coat protein secreted by the M. xanthus Mcu CU system. Based on these observations and data from our previous studies, we propose that MXAN3487 may phosphorylate molecules structurally related to APS, generating metabolites necessary for M. xanthus development, and that MXAN3487 exerts a positive effect on the mcuABC operon whose expression is morphogenesis dependent.

Drosophila Ecp is a phylogenetically conserved protein with homologs in most eukaryotes. Studies on Ecp homologs in rat and human suggest those proteins might be involved in cell cycle control, cell proliferation, and learning and memory. However, the molecular function of Ecp itself remains unclear. We show that both the mRNA and protein of ecp are ubiquitously expressed during the entire fly embryogenesis and life cycle. Results of co-immunoprecipitation show that Ecp forms a stable complex with many ribosomal proteins, including dRPL5. The binding of Ecp to dRPL5 was confirmed by GST pulldown. Furthermore, Ecp was found to cosediment with ribosome subunits in a sucrose gradient. These results indicate that Ecp might be a novel ribosome associated protein interacting with dRPL5.

Inhibition of translation by mutations of a growing number of genes involved in protein synthesis could extend healthy lifespan in yeast, worm, fly and mouse as well. These genes vary from translation initiation factors to structural components of ribosomes and ribosomal RNA processing factors. ECP is a novel ribosome associated protein. Previous data supports the involvement of this gene in long term memory formation and exon guidance in Drosophila probably through its still unconfirmed functions in protein synthesis. However, the exact molecular function of ECP is still largely unknown. Our findings here show that fly lifespan could be significantly extended in ECP RNAi flies. Meanwhile, the locomotion ability of elder ECP RNAi flies was also improved remarkably. Further studies revealed an increase of mitochondria Complex IV activity in these ECP RNAi flies. A decrease of AKT and S6K phosphorylation level in contrast to an increase of AMPK phosphorylation level could also be detected in these flies. Together, these findings support a positive effect of ECP on longevity and delaying age-related impairment in locomotor behavior probably through activation of AMPK and enhancement of mitochondrial function via insulin/IGF-1 and TOR pathway.

Caenorhabditis elegans is a useful model to study the neuronal or molecular basis for behavioral choice, a specific form of decision-making. Although it has been implied that both D1-like and D2-like dopamine receptors may contribute to the control of decision-making in mammals, the genetic interactions between D1-like and D2-like dopamine receptors in regulating decision-making are still largely unclear. In the present study, we investigated the molecular control of behavioral choice between conflicting alternatives (diacetyl and Cu2+) by D1-like and D2-like dopamine receptors and their possible genetic interactions with C. elegans as the assay system. In the behavioral choice assay system, mutation of dop-1 gene encoding D1-like dopamine receptor resulted in the enhanced tendency to cross the Cu2+ barrier compared with wild-type. In contrast, mutations of dop-2 or dop-3 gene encoding D2-like dopamine receptor caused the weak tendency to cross the Cu2+ barrier compared with wild-type. During the control of behavioral choice, DOP-3 antagonistically regulated the function of DOP-1. The behavioral choice phenotype of dop-2; dop-1dop-3 triple mutant further confirmed the possible antagonistic function of D2-like dopamine receptor on D1-like dopamine receptor in regulating behavioral choice. The genetic assays further demonstrate that DOP-3 might act through Gαo signaling pathway encoded by GOA-1 and EGL-10, and DOP-1 might act through Gαq signaling pathway encoded by EGL-30 and EAT-16 to regulate the behavioral choice. DOP-1 might function in cholinergic neurons to regulate the behavioral choice, whereas DOP-3 might function in GABAergic neurons, RIC, and SIA neurons to regulate the behavioral choice. In this study, we provide the genetic evidence to indicate the antagonistic relationship between D1-like dopamine receptor and D2-like dopamine receptor in regulating the decision-making of animals. Our data will be useful for understanding the complex functions of dopamine receptors in regulating decision-making in animals.

FruB is an associated protein of FruA, a transcription factor essential for the development of Myxococcus xanthus. Degenerate oligonucleotide primers were designed based on the N-terminal amino acid sequence of FruB. Using genomic DNA as template, an approximate 110 bp fragment was generated and further served as a probe to screen a small genomic library of M. xanthus. A 4.5 kb SacI fragment was isolated on the basis of its homology to the probe. Disruption of fruB delayed the morphogenesis of fruiting bodies and depressed spore yield, suggesting that to some extent, FruB might be involved in the development of M. xanthus.

Caenorhabditis elegans is as an ideal model system for the study of mechanisms underlying learning and memory. In the present study, we employed C. elegans assay system of thermotaxis memory to investigate the possible role of serotonin neurotransmitter in memory control. Our data showed that both mutations of tph-1, bas-1, and cat-4 genes, required for serotonin synthesis, and mutations of mod-5 gene, encoding a serotonin reuptake transporter, resulted in deficits in thermotaxis memory behavior. Exogenous treatment with serotonin effectively recovered the deficits in thermotaxis memory of tph-1 and bas-1 mutants to the level of wild-type N2. Neuron-specific activity assay of TPH-1 suggests that serotonin might regulate the thermotaxis memory behavior by release from the ADF sensory neurons. Ablation of ADF sensory neurons by expressing a cell-death activator gene egl-1 decreased the thermotaxis memory, whereas activation of ADF neurons by expression of a constitutively active protein kinase C homologue (pkc-1(gf)) increased the thermotaxis memory and rescued the deficits in thermotaxis memory in tph-1 mutants. Moreover, serotonin released from the ADF sensory neurons might act through the G-protein-coupled serotonin receptors of SER-4 and SER-7 to regulate the thermotaxis memory behavior. Genetic analysis implies that serotonin might further target the insulin signaling pathway to regulate the thermotaxis memory behavior. Thus, our results suggest the possible crucial role of serotonin and ADF sensory neurons in thermotaxis memory control in C. elegans.