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Introduction: The development of small molecule modulators rooted the plant resistance mechanism represents a compelling strategy for improving plant resistance and fortifying food security. Systemins induced by wounds can activate a wide range of plant resistance responses, but compounds that regulate the systemin signaling pathway have yet to be found. Objectives: This study aimed to provide a strategy for the development of small molecule modulators based on virtual screening of systemin receptors. Methods: A systemin receptor model was established for virtual screening, leading to the identification of chemical structure with high binding affinity through molecular docking. Subsequently, the synthesized compound underwent evaluation for its potential to enhance plant resistance against viruses through frictional inoculation. The underlying mechanism of the target compound was analyzed using proteomics. Results: Through virtual screening, a promising active compound, F1, was identified and further optimized. Molecular docking showed that they had the ability to bind SR160. Some of the targeted compounds exhibited potential in enhancing plant resistance against Tobacco mosaic virus (TMV) and Cucumber mosaic virus (CMV). Notably, compound F26 showed satisfactory activity against TMV with an EC50 value of 70.6 μg/mL. The analysis of plant response following treatment with F26 indicated that it may reinforce the plant’s defense mechanisms against viruses by augmenting the wound signaling pathway.

In the context of “Industry 4.0,” the construction industry is undergoing a continuous process of digital transformation. In recent years, with the rapid development of artificial intelligence (AI) technology, AI has been successfully applied across various domains within the construction sector. This paper conducts a comprehensive review based on scientific bibliometric analysis and systematic evaluation to provide an overview of AI applications and developments in the architecture, engineering, and construction (AEC) industry, as well as to discuss future research trends. Firstly, a bibliometric analysis was carried out on 3,410 journal articles published between 2003 and 2022. This analysis examined characteristics such as annual publication trends, key researchers and their affiliations, countries of origin, collaborative relationships, prominent journals, and keyword clustering. Subsequently, through systematic review, three critical themes in the field were identified and analyzed: performance prediction, intelligent optimization, and engineering safety and risk. To gain a deeper understanding of cutting-edge AI technologies and their potential applications in the AEC sector, potential future research directions were discussed, including digital twins, blockchain, augmented reality, and virtual reality, all aimed at driving the intelligent and digital transformation of the AEC industry.

Abstract In this study, much work has been performed to accurately and efficiently develop representative actual driving cycles. Electric vehicle road tests were conducted and the associated data were gathered based on the manual driving method, and the Changsha Driving Cycle Construction (CS-DCC) method was proposed to achieve systematical construction of a representative driving cycle from the original data. The results show that the refined data exhibit greater stability and a smoother pattern in contrast to the original data after noise reduction by five-scale wavelet analysis. The Gaussian Kernel Principal Component Analysis (KPCA) algorithm is chosen to reduce the dimensionality of the characteristic matrix, and the number of principal components is selected as 5 with a cumulative contribution rate of 85.99%. The average error of the characteristic parameters between the optimized drive cycle and the total data is further reduced from 13.6 to 6.1%, with a reduction ratio of 55.1%. Meanwhile, the constructed driving cycle has prominent local characteristics compared with four standard driving cycles, demonstrating the necessity of constructing an actual driving cycle that reflects localized driving patterns. The findings present a powerful application of artificial intelligence in advancing engineering technologies.

Objective At present, it is still uncertain whether single screw has the same stability as double screws in the treatment of ulnar coronal process basal fracture (Regan–Morry type III). So, we aimed to compare the pull‐out force and anti‐rotation torque of anterior single/double screw‐cancellous bone fixation (aSSBF, aDSBF) in this fracture, and further study the influencing factors on anatomical and biomechanical stability of smart screw internal fixations. Methods A total of 63 adult volunteers with no history of elbow injury underwent elbow CT scanning with associated three‐dimensional reconstruction that enabled the measurements of bone density and fixed length of the proximal ulna and coronoid. The models of coronal process basal fracture, aSSBF and aDSBF, were developed and validated. Using the finite element model test, the sensitivity analysis of pull‐out force and rotational torque was carried out. Results The pull‐out force of aSSBF model was positively correlated with the density of the cancellous bone and linearly related to the fixed depth of the screw. The load pattern of pull‐out force of aDSBF model was similar to that of aSSBF model. The ultimate torque of aDSBF model was higher than that of aSSBF model, but the load pattern of ultimate torque of both models was similar to each other when the fracture reset was satisfactory, and the screw nut attaches closely to coronoid process. Moreover, with enhancement of initial pre‐tightening force, the increase of ultimate torque of both models was small. Conclusions In addition to three pull‐out stability factors of smart screw fixations, fracture surface fitting degree and nut fitting degree are the other two important anatomical and biomechanical stability factors of smart screw fixations both for rotational stability. When all pull‐out stability and rotational stability factors meet reasonable conditions simultaneously, single or double screw fixation methods are stable for the treatments of ulnar coronoid basal fractures.

Context: As the increasing number of pet canines, the identification of canine has attracted much attentions in the forensic field, however, the genetic diversities of pet canines still remained unknown. Aims: To explore genetic polymorphisms of 19 short tandem repeat (STR) loci and genetic relationships between the two studied canine groups and reference group. Subjects and Methods: In the present study, genetic polymorphisms of 19 STR loci and a sex-linked zinc finger locus were analyzed in a total of 594 canines in Standard Poodle and Bichon Frise groups from China. Results: A total of 166, 159 alleles were observed in the Standard Poodle, Bichon Frise groups with the corresponding allelic frequencies ranging from 0.0030–0.6108 to 0.0012–0.6148, respectively. The combined discrimination power and probability of exclusion of 19 STR loci in Standard Poodle and Bichon Frise groups were 0.9999999999999497, 0.999962884; and 0.99999999999999995, 0.999965955, respectively. Furthermore, the genetic distances between the two canine groups and Labrador retriever group were calculated, and the results indicated that Standard Poodle and Bichon Frise groups showed a closer genetic relationship, while the two canine groups had distant genetic relationships with Labrador retriever group. The result of population genetic structure revealed that genetic component distributions in the three canine groups were different. The predicted accuracies of the constructed random forest prediction model for three validation sets (25% individuals randomly selected from three populations with 808 individuals) were higher than 0.9, especially for the individuals in validation set from the Bichon Frise group is 1. Conclusions: The 19 STR loci could be used for individual identification, canine breed identification and paternity testing in the two canine groups.

The aerodynamic problems caused by high-speed train passing through tunnel become more and more serious with the increase of train speed. In view of the existing line reconstruction which is limited by the terrain and can not be equipped with additional buffer structure in tunnel, we proposes a new type of inter-stepwise buffer structure. In this paper, the flow field between train and tunnel was modeled according to the k-ε two equation turbulence model, the information exchange was realized by sliding grid technology. The pressure oscillation was calculated for the initial compression wave generated when a train enters the tunnel with buffer structure at high speed. The simulation results illuminate that the inter-stepwise buffer structure has limited effect on reducing pressure peak, but it can delay pressure rise and greatly reduce pressure gradient peak. When the buffer structure is located 60 m away from tunnel inlet, the expansion form is three-way uniform expansion, the order is first, the length is 30 m, and the cross-sectional area is 150 m2, the mitigation effect of the inter-stepwise buffer structure on tunnel aerodynamic effect is the best, and the pressure gradient mitigation effect reaches 24.66%.

Accurate modeling of threshold voltage is necessary in the integrated circuit design of strained silicon devices. Thoroughly researching the factors that affect threshold voltage and establishing a more precise threshold voltage model, can provide essential theoretical support for integrated circuit design. By solving a Poisson equation, in this paper, we demonstrate a comprehensive physical model for the threshold voltage of strained Si NMOSFETs using the gradual channel approximation theory and a quasi-two-dimensional analysis. The model investigates the physical effects such as short-channel, narrow-channel, non-uniform doping, and drain-induced barrier lowering effects on the threshold voltage. After substituting the extracted parameters into the model, a comparison was made with experimental results to validate the accuracy and correctness of the established model. Additionally, variations in the tunneling current of small-sized devices were studied. The two models provide essential references for the analysis and design of strained Si large-scale integrated circuits.

The focus of this paper is to investigate the damage characteristics and protective structure design of pontoons as an important barrier for the protection of ports. Two types of protective measures of pontoons are investigated：filling tanks with water and installing springs in tanks. In this paper, the damage characteristics of two types of pontoon side structures under the action of near-field explosion loads are simulated by using LS-DYNA explicit dynamic analysis software and the ALE algorithm. According to the numerical experiment results for filling different volumes of water in the side tanks, the volume of water for the minimum deformation of the shell plate is 100%, and for the first longitudinal bulkhead, it is 30-40%. Moreover, by applying weights to their deformations based on the actual explosion-proof performance requirements of the shell plate and the first longitudinal bulkhead, the pontoon side structure with the best explosion-proof performance can be obtained. The plastic deformation of the pontoon structure equipped with different types of springs is an order of magnitude smaller than that of the ordinary structure and of the pontoon structure filled with a water medium in the positive tanks. The explosive shock wave energy absorbed by the pontoon is effectively reduced by the addition of water or springs to the protective tanks. The minimum energy absorbed by the pontoon structure with water added in the protective tanks is 18.31% of the energy absorbed by the ordinary structure, and the corresponding volume ratio of water added in the protective tanks is 100%. The pontoon structure with springs in the side protection tanks absorbs only 7.2% of the energy absorbed by the ordinary structure. Both new side protection structures have demonstrated excellent explosion-proof performance.

As a thermally induced membrane separation process, membrane distillation (MD) has drawn more and more attention to the advantages of treating hypersaline wastewaters, especially the concentrate from the reverse osmosis (RO) process. One of the major obstacles in widespread MD application is the membrane fouling. We investigated the feasibility of direct contact membrane distillation (DCMD) for landfill leachate reverse osmosis concentrate (LFLRO) brine treatment and systematically assessed the efficiency of chemical cleaning for DCMD after processing LFLRO brine. The results showed that 80% water recovery rate was achieved when processing the LFLRO brine by DCMD, but membrane fouling occurred during the DCMD process, and manifested as the decreasing of permeate flux and the increasing of permeate conductivity. Analysis revealed that the serious flux reduction was primarily caused by the fouling layer, which consisted of organic matter and inorganic salts. Five cleaning methods were investigated for membrane cleaning, including hydrogen chloride (HCl)-sodium hydroxide (NaOH), ethylene diamine tetraacetic acid (EDTA)-NaOH, citric acid, sodium hypochlorite (NaClO) and sodium dodecyl sulphate (SDS) cleaning. Among the chemical cleaning methods investigated, the 3 wt.% SDS cleaning showed the best efficiency at recovering the performance of fouled membranes. HIGHLIGHTS The performance of LFLRO treatment using MD process was evaluated.; The membrane fouling was primarily caused by a mixture of salts and organic matters.; Removal of pollutants inside membrane pores was key to avoiding membrane wetting.; The SDS solution cleaning was most effective in recovering membrane performance.;

Abstract Ovulation rate is an extremely important factor affecting litter size in sows. It differs greatly among pig breeds with different genetic backgrounds. Long non-coding RNAs (lncRNAs) can regulate follicle development, granulosa cell growth, and hormone secretion, which in turn can affect sow litter size. In this study, we identified 3554 lncRNAs and 25,491 mRNAs in M2 follicles of Meishan and Duroc sows. The lncRNA sequence and open reading frame lengths were shorter than mRNAs, and lncRNAs had fewer exons, were less abundant, and more conserved than protein-coding RNAs. Furthermore, 201 lncRNAs were differentially expressed (DE) between breeds, and quantitative trait loci analysis of DE lncRNAs were performed. A total of 127 DE lncRNAs were identified in 119 reproduction trait-related loci. In addition, the potential target genes of lncRNAs in cis or trans configurations were predicted. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that some potential target genes were involved in follicular development and hormone secretion-related biological processes or pathways, such as progesterone biosynthetic process, estrogen metabolic process, ovarian steroidogenesis, and PI3K-Akt signaling pathway. Furthermore, we also screened 19 differentially expressed lncRNAs in the PI3K-Akt signaling pathway as candidates. This study provides new insights into the roles of lncRNAs in follicular growth and development in pigs.

Plant virus diseases seriously affect crop yield, especially tobacco mosaic virus (TMV) and cucumber mosaic virus (CMV). The development of plant immune activators has been an important direction in the innovation of new pesticides. Therefore, we designed and synthesized a series of trifluoromethyl pyridine piperazine derivatives (A1-A27), and explored the action mechanism of active compound. The antiviral activity test showed that compounds A1, A2, A3, A9, A10, A16, A17 and A21 possessed higher activities than commercialized ningnanmycin. Particularly, the in vivo antiviral activity indicated that compound A16 showed the most potent protective activity toward TMV (EC50 = 18.4 μg/mL) and CMV (EC50 = 347.8 μg/mL), compared to ningnanmycin (50.2 μg /mL for TMV, 359.6 μg/mL for CMV). The activities of defense enzyme, label -free proteomic and qRT-PCR analysis showed that compound A16 could enhance the defensive enzyme activities of superoxide dismutase (SOD),polyphenol oxidase (PPO) and phenylalanine ammonialyase (PAL), and activate the phenylpropanoid biosynthesis pathway to strenthen the antiviral activities of tobacco. This study provides reliable support for the development of new antiviral pesticides and potential antiviral mechanism.

In this study, the energy flow of an internal combustion engine (ICE) vehicle is experimentally investigated in a climate chamber under Worldwide Light-duty Test Cycle (WLTC). Each part of the tested vehicle energy loss has been compared to the similar displacement of engine or type of transmission according to the database of conventional gasoline engine passenger car. Then, an integrated simulation model for the tested vehicle is established and calibrated. After that, some technological pathways have been taken for tested vehicle fuel saving by using the calibrated simulation model. The specific fuel saving technological pathways mainly include excess air coefficient improving, engine speed decreasing when the engine resumed fuel supply, engine coolant temperature improving, engine coolant temperature rise process improving, transmission oil temperature and rise process improving, engine idle speed decreasing and transmission gear in neutral position when the vehicle speed is 0, electrical accessories power reducing, and engine cold start speed decreasing. The fuel saving degree of above technological scheme is 0.57%, 1.37%, 0.25%, 0.38%, 0.53%, 2.34%, 0.61%, and 0.59%, respectively. At last, the effects of combinatorial technological scheme to vehicle is simulated and experimented, and the fuel saving degree of them is 5.63% and 5.92%, respectively.

In the present research, the energy flow of electric vehicle batteries under different environmental temperatures was experimentally examined in a climate chamber. The energy flow characteristics, energy loss conditions, and the critical components’ operating conditions and working efficiency under different environmental temperatures were comparatively analyzed. The test results show that the environmental temperature has a profound impact on an electric vehicle’s performance and the critical components’ working conditions. The driving mileage of the tested vehicle at −7 °C, 23 °C, and 35 °C was found to be 162.89 km, 256.09 km, and 198.69 km, respectively. The environmental temperature does not have much effect on the loss of the motor and motor control unit under driving conditions, and the proportion of those at different temperatures is in all cases about 18%. The battery-recycled energy at 23 °C under braking conditions is much higher than that at −7 °C and 35 °C, leading to a longer driving range. The power battery pack thermal transfer loss at −7 °C is much greater than that at 23 °C and 35 °C due to the low charging and discharging efficiency and the high energy consumption required to warm up the battery at a low environmental temperature. The compressor energy consumption accounts for a large proportion in both braking and driving conditions at 35 °C, and the proportions are 15.25% and 12.41%, respectively. The battery state-of-charge drops the fastest at −7 °C, followed by 35 °C, due to the differences in the power demands of air conditioning, warm air positive temperature coefficient (PTC), and battery PTC in high- and low-temperature environments. The working condition of the front motor under driving conditions at 35 °C is the most severe and leads to the lowest working efficiency.

Endosperm as the storage organ of starch and protein in cereal crops largely determines grain yield and quality. Despite the fact that several pentatricopeptide repeat (PPR) proteins required for endosperm development have been identified in rice, the molecular mechanisms of many P-type PPR proteins in endosperm development remains unclear. Here, we isolated a rice floury endosperm mutant ppr5 that developed small starch grains and an abnormal aleurone layer, accompanied by decreased starch, protein, and amylose contents. Map-based cloning combined with a complementation test demonstrated that PPR5 encodes a P-type PPR protein that is localized to the mitochondria. The mutation in PPR5 caused reduced splicing efficiency of mitochondrial NADH dehydrogenase 4 (nad4) gene intron 3 and reduced complex I assembly and activity. Loss of PPR5 function greatly up-regulated expression of alternative oxidases (AOXs), reduced ATP production, and affected mitochondrial morphology. We demonstrate that PPR5, as a P-type PPR protein, is required for mitochondrial function and endosperm development by controlling the cis-splicing of mitochondrial nad4 intron 3.

Abstract Anthocyanins cause purple, brown or red colors in various tissues of rice plants, but the specific determinant factors and regulatory systems for anthocyanin biosynthesis in almost all tissues remain largely unknown. In the present study, we mapped and isolated two complementary genes, OsC1 encoding a R2R3-MYB transcriptional factor and OsDFR encoding a dihydroflavonol 4-reductase, which are responsible for the purple coloration of apiculi and stigmas in indica cultivar Xieqingzao by the map-based cloning strategy. We also identified two tissue-specific pigmentation genes, OsPa for apiculi and OsPs for stigmas, by phylogenetic analysis of all anthocyanin biosynthesis-associated bHLH transcriptional factors in maize and rice, CRISPR/Cas9 knockout and transcriptional expression analysis. The OsC1, OsPa and OsPs proteins are all localized in the nucleus while the OsDFR protein is localized in the nucleus and cytoplasm, and the OsC1 and OsDFR genes are preferentially strongly expressed in both purple-colored tissues while the OsPa and OsPs genes are preferentially strongly expressed in apiculi and stigmas, respectively. OsC1 specifically interacts with OsPa or OsPs to activate OsDFR and other anthocyanin biosynthesis genes, resulting in purple-colored apiculi or stigmas. OsC1 itself does not produce color but can produce brown apiculi when functioning together with OsPa. Loss of function of OsDFR alone leads to brown apiculi and straw-white stigmas. Genotyping and phenotyping of a panel of 176 rice accessions revealed diverse genotypic combinations of OsC1, OsDFR, OsPa and OsPs that enable accurate prediction of their apiculus and stigma pigmentation phenotypes, thus validating the general applicability of the OsC1-OsDFR-OsPa and OsC1-OsDFR-OsPs models to natural populations. Our findings disclosed the biological functions of OsC1, OsPa and OsPs, and shed light on the specific regulatory systems of anthocyanin biosynthesis in apiculi and stigmas, a further step in understanding the regulatory network of anthocyanin biosynthesis in rice.

With the rapid development of Internet technology, numerous malicious URLs have appeared, which bring a large number of security risks. Efficient detection of malicious URLs has become one of the keys for defense against cyber attacks. Deep learning methods bring new developments to the identification of malicious web pages. This paper proposes a malicious URL detection method based on a bidirectional gated recurrent unit (BiGRU) and attention mechanism. The method is based on the BiGRU model. A regularization operation called a dropout mechanism is added to the input layer to prevent the model from overfitting, and an attention mechanism is added to the middle layer to strengthen the feature learning of URLs. Finally, the deep learning network DA-BiGRU model is formed. The experimental results demonstrate that the proposed method can achieve better classification results in malicious URL detection, which has high significance for practical applications.

Researchers have proposed many models for the identification of malicious URLs in network security, but they have not achieved good results. In order to improve this defect, the current popular machine learning algorithm is combined to train the model, thus improving the accuracy of malicious URL classification. This paper proposes a model of a convolutional neural network based on genetic algorithm optimization. Firstly, the genetic algorithm was used to reduce the data dimension of the grammatical features, structural features, and probabilistic features in the extracted malicious URL text, and then the convolutional neural network was used to establish the model and classify the malicious URL. Through experimental verification, the model has achieved good results. Compared with the traditional machine learning model, it improves the accuracy of malicious URL recognition and provides a reference for malicious URL recognition.

The outbreak of the COVID-19 pandemic has caused an upsurge economic policy uncertainty (EPU). Study on the time-varying effect of EPU is of substantial implication for the central bank in implementation of monetary policy. To empirically investigate the time-varying effect of EPU, the paper considers the shock of the monetary policy implemented by China's central bank on different economic variables including interest rate, output gap, and inflationary gap using the latent threshold time-varying parameter vector autoregressive model (LT-TVP-VAR Model). Data period is chosen to be January 2015 through April 2021. Our findings show that (i) EPU has a significant threshold effect on the shock of quantitative monetary policy instrument and the shock of price-based monetary policy, and that the two types of policy are positively correlated; (ii) the price-based monetary policy instrument has a significant counter-cyclical effect on both output gap and inflationary gap; (iii) relative to the quantitative monetary policy instrument, the price-based monetary policy instrument has a more significant counter-cyclical effect on output gap; and (iv) a higher level of EPU is associated with a more significant monetary policy effect on output gap and inflationary gap.

Objective. Inflammation and pain are involved in the pathophysiology of various clinical conditions. This investigation aims to probe the analgesic and anti-inflammatory activity of Maltoamide F. Methods. The possible toxicity of Maltoamide F was evaluated by an acute toxicity test. To assess the anti-inflammatory and antinociceptive effects of Maltoamide F on rats, the models of carrageenan-caused paw edema, xylene-induced ear edema, arachidonic-acid- (AA-) induced ear edema, formalin-caused plantar edema, and cotton-pellet-induced granuloma were established. Levels of TNF-α, PGE-2, and IL-6 were detected by enzyme-linked immunosorbent assay (ELISA). Results. Maltoamide F was safe at oral doses of 1–10 mg/kg for rats. Maltoamide F (1 mg/kg, 5 mg/kg, and 10 mg/kg) notably reduced carrageenan-induced edema percentage of paws in rats and decreased levels of PGE-2, IL-6, and TNF-α in homogenates of foot tissues. Maltoamide F (1 mg/kg, 5 mg/kg, and 10 mg/kg) reduced levels of PGE-2, IL-6, and TNF-α in foot tissues of formalin-induced rats. Maltoamide F (1 mg/kg, 5 mg/kg, and 10 mg/kg) repressed AA-induced increase of ear thickness in rats and reduced levels of PGE-2, IL-6, and TNF-α in homogenates of ear tissues. Maltoamide F (1 mg/kg, 5 mg/kg, and 10 mg/kg) reduced xylene-induced weight of ear edema in rats and reduced levels of PGE-2, IL-6, and TNF-α in homogenates of ear tissues. Maltoamide F (1 mg/kg, 5 mg/kg, and 10 mg/kg) reduced levels of PGE-2, IL-6, and TNF-α in homogenates of cotton ball granuloma of cotton-pellet-induced rats. Conclusions. Maltoamide F possessed anti-inflammatory and analgesic activity in inflammatory models of rats.

Purpose: The purpose of this paper is to develop a combined model composed of grey-forecast model and Logistic-growth-curve model to improve the accuracy of forecast model of cargo throughput for the port. The authors also use the existing data of a current port to verify the validity of the combined model.Design/methodology/approach: A literature review is undertaken to find the appropriate forecast model of cargo throughput for the port. Through researching the related forecast model, the authors put together the individual models which are significant to study further. Finally, the authors combine two individual models (grey-forecast model and Logistic-growth-curve model) into one combined model to forecast the port cargo throughput, and use the model to a physical port in China to testify the validity of the model.Findings: Test by the perceptional data of cargo throughput in the physical port, the results show that the combined model can obtain relatively higher forecast accuracy when it is not easy to find more information. Furthermore, the forecast made by the combined model are more accurate than any of the individual ones.Research limitations/implications: The study provided a new combined forecast model of cargo throughput with a relatively less information to improve the accuracy rate of the forecast. The limitation of the model is that it requires the cargo throughput of the port have an S-shaped change trend.Practical implications: This model is not limited by external conditions such as geographical, cultural. This model predicted the port cargo throughput of one real port in China in 2015, which provided some instructive guidance for the port development.Originality/value: This is the one of the study to improve the accuracy rate of the cargo throughput forecast with little information.

The keratin-associated proteins (KAPs) are the structural proteins of hair fibers and are thought to play an important role in determining the physical properties of hair fibers. These proteins are activated in a striking sequential and spatial pattern in the keratinocytes of hair fibers. Thus, it is important to elucidate the mechanism that underlies the specific transcriptional activity of these genes. In this study, sheep KRTAP 3-3 and KRTAP11-1 genes were found to be highly expressed in wool follicles in a tissue-specific manner. Subsequently, the promoter regions of the two genes that contained the 5' flanking/5' untranslated regions and the coding regions were cloned. Using an in vivo transgenic approach, we found that the promoter regions from the two genes exhibited transcriptional activity in hair fibers. A much stronger and more uniformly expressed green fluorescent signal was observed in the KRTAP11-1-ZsGreen1 transgenic mice. In situ hybridization revealed the symmetrical expression of sheep KRTAP11-1 in the entire wool cortex. Consistently, immunohistochemical analysis demonstrated that the pattern of ZsGreen1 expression in the hair cortex of transgenic mice matches that of the endogenous KRTAP11-1 gene, indicating that the cloned promoter region contains elements that are sufficient to govern the wool cortex-specific transcription of KRTAP11-1. Furthermore, regulatory regions in the 5' upstream sequence of the sheep KRTAP11-1 gene that may regulate the observed hair keratinocyte specificity were identified using in vivo reporter assays.