An efficient visual servo tracker for herd monitoring by UAV.

It is a challenging and meaningful task to carry out UAV-based livestock monitoring in high-altitude (more than 4500 m on average) and cold regions (annual average - 4 °C) on the Qinghai Tibet Plateau. The purpose of artificial intelligence (AI) is to execute automated tasks and to solve practical problems in actual applications by combining the software technology with the hardware carrier to create integrated advanced devices. Only in this way, the maximum value of AI could be realized. In this paper, a real-time tracking system with dynamic target tracking ability is proposed. It is developed based on the tracking-by-detection architecture using YOLOv7 and Deep SORT algorithms for target detection and tracking, respectively. In response to the problems encountered in the tracking process of complex and dense scenes, our work (1) Uses optical flow to compensate the Kalman filter, to solve the problem of mismatch between the target bounding box predicted by the Kalman filter (KF) and the input when the target detection in the current frame is complex, thereby improving the prediction accuracy; (2) Using a low confidence trajectory filtering method to reduce false positive trajectories generated by Deep SORT, thereby mitigating the impact of unreliable detection on target tracking. (3) A visual servo controller has been designed for the Unmanned Aerial Vehicle (UAV) to reduce the impact of rapid movement on tracking and ensure that the target is always within the field of view of the UAV camera, thereby achieving automatic tracking tasks. Finally, the system was tested using Tibetan yaks on the Qinghai Tibet Plateau as tracking targets, and the results showed that the system has real-time multi tracking ability and ideal visual servo effect in complex and dense scenes.

PM2.5-induced cellular senescence drives brown adipose tissue impairment in middle-aged mice.

Airborne fine particulate matter (PM2.5) exposure is closely associated with metabolic disturbance, in which brown adipose tissue (BAT) is one of the main contributing organs. However, knowledge of the phenotype and mechanism of PM2.5 exposure-impaired BAT is quite limited. In the study, male C57BL/6 mice at three different life phases (young, adult, and middle-aged) were simultaneously exposed to concentrated ambient PM2.5 or filtered air for 8 weeks using a whole-body inhalational exposure system. H&E staining and high-resolution respirometry were used to assess the size of adipocytes and mitochondrial function. Transcriptomics was performed to determine the differentially expressed genes in BAT. Quantitative RT-PCR, immunohistochemistry staining, and immunoblots were performed to verify the transcriptomics and explore the mechanism for BAT mitochondrial dysfunction. Firstly, PM2.5 exposure caused altered BAT morphology and mitochondrial dysfunction in middle-aged but not young or adult mice. Furthermore, PM2.5 exposure increased cellular senescence in BAT of middle-aged mice, accompanied by cell cycle arrest, impaired DNA replication, and inhibited AKT signaling pathway. Moreover, PM2.5 exposure disrupted apoptosis and autophagy homeostasis in BAT of middle-aged mice. Therefore, BAT in middle-aged mice was more vulnerable to PM2.5 exposure, and the cellular senescence-initiated apoptosis, autophagy, and mitochondrial dysfunction may be the mechanism of PM2.5 exposure-induced BAT impairment.

High-precision tracking and positioning for monitoring Holstein cattle.

Enhanced animal welfare has emerged as a pivotal element in contemporary precision animal husbandry, with bovine monitoring constituting a significant facet of precision agriculture. The evolution of intelligent agriculture in recent years has significantly facilitated the integration of drone flight monitoring tools and innovative systems, leveraging deep learning to interpret bovine behavior. Smart drones, outfitted with monitoring systems, have evolved into viable solutions for wildlife protection and monitoring as well as animal husbandry. Nevertheless, challenges arise under actual and multifaceted ranch conditions, where scale alterations, unpredictable movements, and occlusions invariably influence the accurate tracking of unmanned aerial vehicles (UAVs). To address these challenges, this manuscript proposes a tracking algorithm based on deep learning, adhering to the Joint Detection Tracking (JDT) paradigm established by the CenterTrack algorithm. This algorithm is designed to satisfy the requirements of multi-objective tracking in intricate practical scenarios. In comparison with several preeminent tracking algorithms, the proposed Multi-Object Tracking (MOT) algorithm demonstrates superior performance in Multiple Object Tracking Accuracy (MOTA), Multiple Object Tracking Precision (MOTP), and IDF1. Additionally, it exhibits enhanced efficiency in managing Identity Switches (ID), False Positives (FP), and False Negatives (FN). This algorithm proficiently mitigates the inherent challenges of MOT in complex, livestock-dense scenarios.

Identification and validation of microbial biomarkers from cross-cohort datasets using xMarkerFinder.

Microbial signatures have emerged as promising biomarkers for disease diagnostics and prognostics, yet their variability across different studies calls for a standardized approach to biomarker research. Therefore, we introduce xMarkerFinder, a four-stage computational framework for microbial biomarker identification with comprehensive validations from cross-cohort datasets, including differential signature identification, model construction, model validation and biomarker interpretation. xMarkerFinder enables the identification and validation of reproducible biomarkers for cross-cohort studies, along with the establishment of classification models and potential microbiome-induced mechanisms. Originally developed for gut microbiome research, xMarkerFinder's adaptable design makes it applicable to various microbial habitats and data types. Distinct from existing biomarker research tools that typically concentrate on a singular aspect, xMarkerFinder uniquely incorporates a sophisticated feature selection process, specifically designed to address the heterogeneity between different cohorts, extensive internal and external validations, and detailed specificity assessments. Execution time varies depending on the sample size, selected algorithm and computational resource. Accessible via GitHub ( https://github.com/tjcadd2020/xMarkerFinder ), xMarkerFinder supports users with diverse expertise levels through different execution options, including step-to-step scripts with detailed tutorials and frequently asked questions, a single-command execution script, a ready-to-use Docker image and a user-friendly web server ( https://www.biosino.org/xmarkerfinder ).

How would autonomous vehicles behave in real-world crash scenarios?

Autonomous Vehicles (AVs) have the potential to revolutionize transportation systems by enhancing traffic safety. Safety testing is undoubtedly a critical step for enabling large-scale deployment of AVs. High-risk scenarios are particularly important as they pose significant challenges and provide valuable insights into the driving capabilities of AVs. This study presents a novel approach to assess the safety of AVs using in-depth crash data, with a particular focus on real-world crash scenarios. First, based on the high-definition video recording of the whole process prior to the crash occurrences, 453 real-world crashes involving 596 passenger cars from China In-depth Mobility Safety Study-Traffic Accident (CIMSS-TA) database were reconstructed. Pertinent static and dynamic elements needed for the construction of the testing scenarios were extracted. Subsequently, 596 testing scenarios were created via each passenger car's perspective within the simulation platform. Following this, each of the crash-involved passenger cars was replaced with Baidu Apollo, a famous automated driving system (ADS), for counterfactual simulation. Lastly, the safety performance of the AV was assessed using the simulation results. A logit model was utilized to identify the fifteen crucial scenario elements that have significant impacts on the test results. The findings demonstrated that the AV could avoid 363 real-world crashes, accounting for approximately 60.91% of the total, and effectively mitigated injuries in the remaining 233 unavoidable scenarios compared to a human driver. Moreover, the AV maintain a smoother speed in most of the scenarios. The common feature of these unavoidable scenarios is that the AV is in a passive state, and the crashes are not caused by the AV violating traffic rules, but rather caused by abnormal behavior exhibited by the human drivers. Additionally, seven specific scenarios have been identified wherein AVs are unable to avoid a crash. These findings demonstrate that, compared to human drivers, AVs can avoid crashes that are difficult for humans to avoid, thereby enhancing traffic safety.

Water-Ice Microstructures and Hydration States of Acridinium Iodide Studied by Phosphorescence Spectroscopy.

Ice has been suggested to have played a significant role in the origin of life partly owing to its ability to concentrate organic molecules and promote reaction efficiency. However, the techniques for studying organic molecules in ice are absorption-based, which limits the sensitivity of measurements. Here we introduce an emission-based method to study organic molecules in water ice: the phosphorescence displays high sensitivity depending on the hydration state of an organic salt probe, acridinium iodide (ADI). The designed ADI aqueous system exhibits phosphorescence that can be severely perturbed when the temperature is higher than 110 K at a concentration of the order of 10-5 M, indicating changes in hydration for ADI. Using the ADI phosphorescent probe, it is found that the microstructures of water ice, i.e., crystalline vs. glassy, can be strongly dictated by a trace amount (as low as 10-5 M) of water-soluble organic molecules. Consistent with cryoSEM images and temperature-dependent Raman spectral data, the ADI is dehydrated in more crystalline ice and hydrated in more glassy ice. The current investigation serves as a starting point for using more sensitive spectroscopic techniques for studying water-organics interactions at a much lower concentration and wider temperature range.

Rapid room-temperature phosphorescence chiral recognition of natural amino acids.

Chiral recognition of amino acids is very important in both chemical and life sciences. Although chiral recognition with luminescence has many advantages such as being inexpensive, it is usually slow and lacks generality as the recognition module relies on structural complementarity. Here, we show that one single molecular-solid sensor, L-phenylalanine derived benzamide, can manifest the structural difference between the natural, left-handed amino acid and its right-handed counterpart via the difference of room-temperature phosphorescence (RTP) irrespective of the specific chemical structure. To realize rapid and reliable sensing, the doped samples are obtained as nanocrystals from evaporation of the tetrahydrofuran solutions, which allows for efficient triplet-triplet energy transfer to the chiral analytes generated in situ from chiral amino acids. The results show that L-analytes induce strong RTP, whereas the unnatural D-analytes produce barely any afterglow. The method expands the scope of luminescence chiral sensing by lessening the requirement for specific molecular structures.

Ginsenoside Rg5 inhibits glioblastoma by activating ferroptosis via NR3C1/HSPB1/NCOA4.

BACKGROUND: The utilization of Chinese medicine as an adjunctive therapy for cancer has recently gained significant attention. Ferroptosis, a newly regulated cell death process depending on the ferrous ions, has been proved to be participated in glioma stem cells inactivation. PURPOSE: We aim to study whether ginsenoside Rg5 exerted inhibitory effects on crucial aspects of glioma stem cells, including cell viability, tumor initiation, invasion, self-renewal ability, neurosphere formation, and stemness. METHODS: Through comprehensive sequencing analysis, we identified a compelling association between ginsenoside Rg5 and the ferroptosis pathway, which was further validated through subsequent experiments demonstrating its ability to activate this pathway. RESULTS: To elucidate the precise molecular targets affected by ginsenoside Rg5 in gliomas, we conducted an intersection analysis between differentially expressed genes obtained from sequencing and a database-predicted list of transcription factors and potential targets of ginsenoside Rg5. This rigorous approach led us to unequivocally confirm NR3C1 (Nuclear Receptor Subfamily 3 Group C Member 1) as a direct target of ginsenoside Rg5, a finding consistently supported by subsequent experimental investigations. Moreover, we uncovered NR3C1's capacity to transcriptionally regulate ferroptosis -related genes HSPB1 and NCOA4. Strikingly, ginsenoside Rg5 induced notable alterations in the expression levels of both HSPB1 (Heat Shock Protein Family B Member 1) and NCOA4 (Nuclear Receptor Coactivator 4). Finally, our intracranial xenograft assays served to reaffirm the inhibitory effect of ginsenoside Rg5 on the malignant progression of glioblastoma. CONCLUSION: These collective findings strongly suggest that ginsenoside Rg5 hampers glioblastoma progression by activating ferroptosis through NR3C1, which subsequently modulates HSPB1 and NCOA4. Importantly, this novel therapeutic direction holds promise for advancing the treatment of glioblastoma.

Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits.

Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.

Isolation and Identification of Salinity-Tolerant Rhizobia and Nodulation Phenotype Analysis in Different Soybean Germplasms.

Increasing the soybean-planting area and increasing the soybean yield per unit area are two effective solutions to improve the overall soybean yield. Northeast China has a large saline soil area, and if soybeans could be grown there with the help of isolated saline-tolerant rhizobia, the soybean cultivation area in China could be effectively expanded. In this study, soybeans were planted in soils at different latitudes in China, and four strains of rhizobia were isolated and identified from the soybean nodules. According to the latitudes of the soil-sampling sites from high to low, the four isolated strains were identified as HLNEAU1, HLNEAU2, HLNEAU3, and HLNEAU4. In this study, the isolated strains were identified for their resistances, and their acid and saline tolerances and nitrogen fixation capacities were preliminarily identified. Ten representative soybean germplasm resources in Northeast China were inoculated with these four strains, and the compatibilities of these four rhizobium strains with the soybean germplasm resources were analyzed. All four isolates were able to establish different extents of compatibility with 10 soybean resources. Hefeng 50 had good compatibility with the four isolated strains, while Suinong 14 showed the best compatibility with HLNEAU2. The isolated rhizobacteria could successfully establish symbiosis with the soybeans, but host specificity was also present. This study was a preliminary exploration of the use of salinity-tolerant rhizobacteria to help the soybean nitrogen fixation in saline soils in order to increase the soybean acreage, and it provides a valuable theoretical basis for the application of saline-tolerant rhizobia.

Micro-Spherical BiOI Photocatalysts for Efficient Degradation of Residual Xanthate and Gaseous Nitric Oxide.

BiOI microspheres were synthesized using the solvothermal method for the degradation of residual xanthate and gaseous nitric oxide (NO) under visible light irradiation. The as-prepared BiOI nanomaterials were then characterized using various technologies, including XRD, FE-SEM, TEM, UV-Vis DRS, and XPS. The photodegradation results show that the removal efficiency of isobutyl sodium xanthate can reach 98.08% at an initial xanthate concentration of 120 mg/L; that of NO is as high as 96.36% at an inlet NO concentration of 11 ppm. Moreover, the effects of operational parameters such as catalyst dosage, initial xanthate concentration, and pH value of wastewater on the removal of xanthate were investigated. The results of scavenging tests and full-spectrum scanning indicate that ·O2- radicals are the main active species in xanthate degradation, and peroxide xanthate is an intermediate. The reusability of BiOI was explored through cyclic experiments. Furthermore, the reaction path and the mechanism of NO removal using BiOI were analyzed, and the main active species was also ·O2-. It is concluded that BiOI photocatalysts have high potential for wastewater treatment and waste gas clean-up in the mineral industry.

First-principles studies on the electronic and contact properties of monolayer Ga2STe-metal contacts.

Monolayer (ML) Janus III-VI compounds have attracted the use of multiple competitive platforms for future-generation functional electronics, including non-volatile memories, field effect transistors, and sensors. In this work, the electronic and interfacial properties of ML Ga2STe-metal (Au, Ag, Cu, and Al) contacts are systematically investigated using first-principles calculations combined with the non-equilibrium Green's function method. The ML Ga2STe-Au/Ag/Al contacts exhibit weak electronic orbital hybridization at the interface, while the ML Ga2STe-Cu contact exhibits strong electronic orbital hybridization. The Te surface is more conducive to electron injection than the S surface in ML Ga2STe-metal contact. Quantum transport calculations revealed that when the Te side of the ML Ga2STe is in contact with Au, Ag and Cu electrodes, p-type Schottky contacts are formed. When in contact with the Al electrode, an n-type Schottky contact is formed with an electron SBH of 0.079 eV. When the S side of ML Ga2STe is in contact with Au and Al electrodes, p-type Schottky contacts are formed, and when it is in contact with Ag and Cu electrodes, n-type Schottky contacts are formed. Our study will guide the selection of appropriate metal electrodes for constructing ML Ga2STe devices.

Optimizing ultrashort pulse in fiber laser based on artificial intelligence algorithm.

Ultrashort pulses, characterized by their short pulse duration, diverse spectral content, and high peak power, are widely used in fields including laser processing, optical storage, biomedical sciences, and laser imaging. The complex, highly-nonlinear process of ultrashort pulse evolution within fiber lasers is influenced by numerous aspects such as dispersion, loss, gain, and nonlinear effects. Traditionally, the split-step Fourier transforms method is employed for simulating ultrashort pulses in fiber lasers, which involves traversing multiple parameters within the fiber to attain the pulse's optimal state. The simulation is a significantly time-consuming process. Here, we use a neural network model to fit and predict the impact of multiple parameters on the pulse characteristics within fiber lasers, enabling parameter optimization through genetic algorithms to determine the optimal pulse duration, pulse energy, and peak power. Integrating artificial intelligence algorithms simplifies the acquisition of optimal pulse parameters and enhances our understanding of multiple parameters' impact on the pulse characteristics. The investigation of ultrashort pulse optimization based on artificial intelligence holds immense potential for laser design.

CyclicPepedia: a knowledge base of natural and synthetic cyclic peptides.

Cyclic peptides offer a range of notable advantages, including potent antibacterial properties, high binding affinity and specificity to target molecules, and minimal toxicity, making them highly promising candidates for drug development. However, a comprehensive database that consolidates both synthetically derived and naturally occurring cyclic peptides is conspicuously absent. To address this void, we introduce CyclicPepedia (https://www.biosino.org/iMAC/cyclicpepedia/), a pioneering database that encompasses 8744 known cyclic peptides. This repository, structured as a composite knowledge network, offers a wealth of information encompassing various aspects of cyclic peptides, such as cyclic peptides' sources, categorizations, structural characteristics, pharmacokinetic profiles, physicochemical properties, patented drug applications, and a collection of crucial publications. Supported by a user-friendly knowledge retrieval system and calculation tools specifically designed for cyclic peptides, CyclicPepedia will be able to facilitate advancements in cyclic peptide drug development.

Transcriptomic Analysis of PDCoV-Infected HIEC-6 Cells and Enrichment Pathways PI3K-Akt and P38 MAPK.

Porcine Deltacoronavirus (PDCoV) is a newly identified coronavirus that causes severe intestinal lesions in piglets. However, the understanding of how PDCoV interacts with human hosts is limited. In this study, we aimed to investigate the interactions between PDCoV and human intestinal cells (HIEC-6) by analyzing the transcriptome at different time points post-infection (12 h, 24 h, 48 h). Differential gene analysis revealed a total of 3560, 5193, and 4147 differentially expressed genes (DEGs) at 12 h, 24 h, and 48 h, respectively. The common genes among the DEGs at all three time points were enriched in biological processes related to cytokine production, extracellular matrix, and cytokine activity. KEGG pathway analysis showed enrichment of genes involved in the p53 signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway. Further analysis of highly expressed genes among the DEGs identified significant changes in the expression levels of BUB1, DDIT4, ATF3, GBP2, and IRF1. Comparison of transcriptome data at 24 h with other time points revealed 298 DEGs out of a total of 6276 genes. KEGG analysis of these DEGs showed significant enrichment of pathways related to viral infection, specifically the PI3K-Akt and P38 MAPK pathways. Furthermore, the genes EFNA1 and KITLG, which are associated with viral infection, were found in both enriched pathways, suggesting their potential as therapeutic or preventive targets for PDCoV infection. The enhancement of PDCoV infection in HIEC-6 was observed upon inhibition of the PI3K-Akt and P38 MAPK signaling pathways using sophoridine. Overall, these findings contribute to our understanding of the molecular mechanisms underlying PDCoV infection in HIEC-6 cells and provide insights for developing preventive and therapeutic strategies against PDCoV infection.

Case report: EGFR fusion mutation combined with EGFR amplification responds to EGFR-TKI therapy.

Given their good antitumor effects, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are standard first-line therapy for EGFR-sensitive mutations, including exon 19 deletions and exon 21 L858R mutations. EGFR fusion mutations and EGFR amplification are very rare in non-small cell lung cancer (NSCLC). We describe 2 patients with NSCLC harboring EGFR fusion mutations (EGFR-MACF1 and EGFR-GNAT3) combined with EGFR amplification. Both patients received EGFR-TKI treatment, and 1 of them showed an antitumor response.

Molecular composition and characteristics of Sediment-adsorbed Dissolved Organic Matter (SDOM) along the coast of China.

Sediment-adsorbed Dissolved Organic Matter (SDOM) in coast plays a crucial role in the terrestrial and marine carbon cycle processes of the global environment. However, understanding the transport dynamics of SDOM along the coast of China, particularly its interactions with sediments, remains elusive. In this study, we analyzed the δ13C and δ15N stable isotopic compositions, as well as the molecular characteristics of SDOM collected from coastal areas spanning the Bohai Sea (BS), Yellow Sea (YS), East China Sea (ECS), and South China Sea (SCS), by using isotope ratio mass spectrometry and Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR-MS). We identified the predominant sources of carbon and nitrogen in coastal sediments, revealing terrigenous origins for most C and N, while anthropogenic sources dominated in the SCS. Spatial variations in SDOM chemodiversity were observed, with diverse molecular components influenced by distinct environmental factors and sediment sources. Notably, lignins and saturated compounds (such as proteins/amino sugars) were the predominant molecular compounds detected in coastal SDOM. Through Mantel tests and Spearman's correlation analysis, we elucidated the significant influence of spatial environmental factors (temperature, DO, salinity, and depth) and sediment sources on SDOM molecular chemodiversity. These findings contribute to a more comprehensive understanding of the carbon cycle dynamics along the Chinese coast.

Microglial AT1R Conditional Knockout Ameliorates Hypoperfusive Cognitive Impairment by Reducing Microglial Inflammatory Responses.

Chronic cerebral hypoperfusion (CCH) can cause vascular cognitive impairment and dementia. AT1R, angiotensin II type I receptor, plays a vital role in central nervous system pathologies, but its concrete function in vascular dementia is still unclear. Herein, we investigated the effects of AT1R during CCH by conditional knockout of the microglial AT1R and candesartan treatment. Using the bilateral carotid artery stenosis (BCAS) model, we found that the AT1R is crucial in exacerbating CCH-induced cognitive impairment via regulating microglial activation. The levels of AT1R were increased in the hippocampus and the hippocampal microglia after CCH induction. Microglial AT1R conditional knockout ameliorated cognitive impairment by reducing inflammatory responses and microglial activation, and so did candesartan treatment. However, we observed restoration of cerebral blood flow (CBF) but no significant neuronal loss in the hippocampus at 28 days after BCAS. Finally, we screened three hub genes (Ctss, Fcer1g, Tyrobp) associated with CCH. Our findings indicated that microglial expression of AT1R is critical for regulating neuroinflammation in CCH, and AT1R antagonism may be a feasible and promising method for ameliorating CCH-caused cognitive impairment.

Expression, Polymorphism, and Potential Functional Sites of the BMPR1A Gene in the Sheep Horn.

Sheep horns are composed of bone and sheaths, and the BMPR1A gene is required for cartilage and osteogenic differentiation. Therefore, the BMPR1A gene may have a function related to the sheep horn, but its relationship with the sheep horn remains unclear. In this study, we first utilized RNA sequencing (RNA-seq) data to investigate the expression of the BMPR1A gene in different tissues and breeds of sheep. Second, whole-genome sequencing (WGS) data were used to explore the functional sites of the BMPR1A gene. Lastly, the allele-specific expression of the BMPR1A gene was explored. Our results indicate that BMPR1A gene expression is significantly higher in the normal horn groups than in the scurred groups. Importantly, this trend is consistent across several sheep breeds. Therefore, this finding suggests that the BMPR1A gene may be related to horn type. A total of 43 Single-Nucleotide Polymorphisms (SNPs) (F-statistics > 0.15) and 10 allele-specific expressions (ASEs) exhibited difference between the large and small horn populations. It is probable that these sites significantly impact the size of sheep horns. Compared to other polled species, we discovered ten amino acid sites that could influence horn presence. By combining RNA-seq and WGS functional loci results, we identified a functional site at position 40574836 on chromosome 25 that is both an SNP and exhibits allele-specific expression. In conclusion, we demonstrated that the BMPR1A gene is associated with horn type and identified some important functional sites which can be used as molecular markers in the breeding of sheep horns.