The Chinese Red Steppe Cattle (CRS) is a well-known dual-purpose (meat and milk) cattle breed. Here, the genetic variation and population structure of CRS were studied using 100 K SNP genotyping data. The results show that the genetic structure of CRS is different from other populations, the level of genetic diversity is high, and the level of inbreeding is low. In conclusion, our research provides the genetic basis for the prominent characteristics of CRS, which can be used to improve the breeding program of CRS in the future.PLAG1, PRKG2, DGAT1, PARP10, TONSL, ADCK5, and BMP3, most of which were enriched in pathways related to muscle growth and differentiation, milk production, and lipid metabolism. This study will contribute to understanding the genetic mechanism behind artificial selection and give an extensive reference for subsequent breeding.Chinese Red Steppe Cattle (CRS), a composite cattle breed, is well known for its milk production, high slaughter rate, carcass traits, and meat quality. Nowadays, it is widely bred in Jilin and Hebei Province and the Inner Mongolia Autonomous region. However, the population structure and the genetic basis of prominent characteristics of CRS are still unknown. In this study, we systematically describe their population structure, genetic diversity, and selection signature based on genotyping data from 61 CRS individuals with GGP Bovine 100 K chip. The results showed that CRS cattle had low inbreeding levels and had formed a unique genetic structure feature. Using two complementary methods (including comprehensive haplotype score and complex likelihood ratio), we identified 1291 and 1285 potentially selected genes, respectively. There were 141 genes annotated in common 106 overlapping genomic regions covered 5.62 Mb, including  Bos taurus indicus (indicine or zebu) and Bos taurus taurus (taurine), according to their different morphological characteristics and living habits [Domestication and selective breeding is the process by which wild individuals are bred in captivity and modified through artificial selection to be phenotypically and genetically distinct from the original ancestors ,2. Moderg habits . With thg habits . Hybridig habits . In ChinWith the availability of single nucleotide polymorphism (SNP) genotyping data, genome-wide SNP chips have been widely used to study genetic diversity, population structure, inbreeding level, effective population size, genome-wide association study, and selection feature detection in different breeds or populations worldwide ,7. At prAfter long-term selection, breeds living in different environmental conditions have formed a unique adaptive evolutionary system . DiffereChinese Red Steppe Cattle (CRS), the first composite breed for both milk and meat purposes since the founding of China, was developed by crossbreeding Shorthorn with Chinese native Mongolian cattle . The brehttps://www.ncbi.nlm.nih.gov/sra/); its parental ancestors include Shorthorn cattle , Mongolian cattle , and Angus cattle , Hereford cattle , Holstein cattle , Charolais cattle , Limousin cattle , Simmental cattle , Tibetan cattle , Kazakh cattle , as well as five local Chinese populations, Yanbian cattle , Luxi cattle , Lingnan cattle , Wenling cattle , Zhoushan cattle . Sample details are presented in Blood samples were collected from 61 CRS individuals randomly selected from the Sanjiazi Cattle Breeding Farm of Tongyu Country, Jilin Province. Cattle blood DNA was extracted with a kit from Beijing Tiangen Biotechnology. After extraction, the integrity of genomic DNA was detected with 1.0% agarose gel. The quality and quantity of the DNA were estimated using a Nanodrop 2000 nucleic acid protein analyzer . The obtained DNA bands are neat and clear without trailing, and the purity of DNA samples (OD260/OD280 = 1.8–2.0) means less degradation and less protein residue. In addition, the re-sequencing data of 245 individuals from 15 breeds were downloaded from the NCBI database on 13 October 2022.  using BWA with command ‘bwa mem’, and SNP calling was performed following the GATK pipeline v4.4.1.0 ,24. ThenHO) and expected heterozygosity (HE) were estimated using PLINK v1.9 with option ‘--hardy’ [FHOM) was calculated using PLINK v1.9 command ‘--het’ [FROH) were calculated by the total length of the ROH fragment divided by the length of the autosomal genome.In order to assess genetic diversity, the average observed heterozygosity  was also calculated in ADMIXTURE, and the graphical representation of the ADMIXTURE results was performed using R script, as suggested by the ADMIXTURE procedure. To ascertain the genetic relationship between CRS and other breeds, PLINK v1.9 was used to remove those sites with high LD with the parameter ‘-indep-pairwise 50 25 0.2′ . The graIn order to detect selection signatures under the recent or ongoing positive selection in the CRS genome, the selection sweeps were identified based on two complementary methods: the Integrated Haplotype score (iHS) and composite likelihood ratio (CLR) approach, respectively. In this study, BEAGLE v5.2 with the parameters ‘beagle gt = test.vcf out = test.beagle.vcf ne = 306′ was used to impute missing alleles and infer the haplotype phase for all individuals . The meahttps://www.ncbi.nlm.nih.gov/). In this study, enrichment analyses for genes within overlapping significant candidate regions detected using the iHS method (top 5%) and the CLR method (top 5%) were performed. To gain a better understanding of the gene functions and signaling pathways of the identified candidate genes, Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) pathway enrichment analysis were performed using KOBAS [p-value was less than 0.05 [Based on the bovine ARS-UCD1.2 reference genome annotation, we retrieved genes with candidate significant of SNP loci under selection. Furthermore, gene function was determined using the National Center for Biotechnology Information database accessed on 14 November 2022  database was used to identify the overlapping regions associated with the most plausible trait-associated selective signatures. We used the bovine database incorporated in the Animal QTL database to determine the potential overlap of these regions . The numB.taurus reference genome ARS-UCD1.2, and 61 individuals from CRS were successfully genotyped with the GGP Bovine 100 K Chip. Furthermore, a total of 82,101 common autosomal bi-allelic SNPs were detected in the merged data across 306 individuals; out of 80,871 SNPs remaining after the removal SNPs with <95% call rate, MAF < 0.03 with an average distance of 32.3 kb distributed over 29 chromosomes were obtained for subsequent analysis. The length of each chromosome, number, percentage of SNPs, and the average interval between SNPs for each chromosome are shown in Ho), average expected heterozygosity (He), the homozygosity inbreeding coefficient (FHOM), and inbreeding coefficient based on ROH (FROH) have been calculated to assess polymorphism of 16 cattle populations. The results indicated that the pi value ranged from 0.000034 to 0.000047 (HO of CRS (0.387) was higher than most commercial breeds, including Simmental (0.386), Angus (0.377), and Holstein (0.372), and the HE of CRS (0.375) was between Hereford and Angus. Overall, these results indicated high genetic diversity in CRS. As shown in S3, the results showed that the FHOM (−0.0312) in CRS was very close to zero. In addition, the FROH value of CRS was 0.088, which was lower than the three commercial cattle population of Hereford cattle (0.133), Angus cattle (0.111), and Holstein cattle (0.096), and approximately that of local Chinese cattle of Lingnan cattle (0.073), and Zhoushan cattle (0.079). The results indicating the existing breeding programs effectively avoid inbreeding.In total, 245 individuals from 15 breeds were generated and aligned to the 0.000047 . Among tK = 2 to 9, with the lowest cross-validation error value being 9  [PARP10 and AMFR) [PRKG2, ZFP90, and BMP3) [PLAG1 has been fully proven to be associated with stature and body size, which may affect the beef production of CRS [PRKG2 plays a role in growth and carcass [DGAT1 showed some positive role in the enhancement of meat and carcass fatness quality in beef cattle and obtained considerable attention, especially in animal milk production [In this study, we applied the iHS and CLR methods to detect the genomic regions under the recent selection of the CRS. Two methods showed outlier signals (top 5%) in overlapping regions and were, therefore, considered candidate selective regions. The genome-wide distribution of |iHS| values and CLR values for 100 k non-overlapping windows on autosomes is depicted in d GRINA) ,40,41, lnd AMFR) ,43, and nd BMP3) ,45. Amonn of CRS ,47,48. P carcass ,50. DGAToduction .p-value < 0.05 were observed, such as regulation of cell cycle , identical protein binding , protein-containing complex binding , and positive regulation of protein catabolic process . In addition, metabolism-related and immune-related biological functions were significant. Furthermore, eighteen significant enriched pathways were obtained, including the mRNA surveillance pathway , protein processing in the endoplasmic reticulum , cGMP-PKG signaling pathway , and cAMP signaling pathway , which are related to metabolism and protein synthesis. The functional enrichment analysis using KEGG pathways and Gene Ontology (GO) for overlapped genes were further analyzed. The significantly enriched GO terms and KEGG pathways are shown in Moreover, the cattle quantitative trait locus (QTL) database was used to identify the overlapping regions associated with the most plausible trait-associated selective signatures. In total, 436 QTLs were located within or overlapping with these 106 candidate regions . Most ofFHOM and FROH of CRS exceeded the expected value, which was lower than a lot of commercial cattle populations. In this study, the genetic diversity of CRS holds significant potential for improvements in production. Therefore, based on the existing breeding, breeding cattle with a large genetic distance should be selected to increase the population size and maintain the genetic diversity of the CRS population. In the future, we could obtain more genomic information using whole-genome data to more precisely elucidate the genetic diversity and represent a realistic estimate of total genomic inbreeding in CRS [CRS is a crossbred cattle breed in China, and it has been intensively bred for beef over the past 30 years, with characteristics of high slaughter rate, excellent meat quality, greater disease resistance, and good reproductive performance . The chag in CRS ,60. PCA and ADMIXTURE were used to investigate the genetic relationship and population-level admixture among CRS and other breeds. The results indicated that the genomic background of the CRS breed initially represents the fusion of ancestral varieties. In addition, CRS individuals were obviously separated from other cattle breeds, and the CRS breed composition stabilized over time after initial crossbreeding and subsequent artificial selection. Fst. In this study, the iHS and CLR were used to identify candidate genomic regions under positive selection with important traits in CRS [DGAT1 was documented to have a significant influence on milk production in cattle in Germany and is associated with milk production traits through GWAS [DGAT1, TONSL, CPSF1, ADCK5, GRINA, and PARP10) in the CRS that has the strongest signal for milk production traits also reported various levels of interactions in which CPSF1 as the hub gene since it interacted with all the other genes [TONSL, CPSF1, ADCK5, and DGAT1 genes are neighbors and there are coexpressions among each other [PLAG1 has well-documented associations with skeletal growth and age at puberty in cattle [PRKG2 gene deletion is associated with growth restriction [The domestication of various livestock species is one of the greatest achievements of humankind . In the s in CRS ,67. We is in CRS ,69. Prevugh GWAS ,71. Of ter genes . Additioch other . Moreovech other ,75,76,77n cattle , and it triction ,80. In ttriction . MoreoveThe results presented in this study indicated that CRS cattle have high genetic diversity, a low level of inbreeding, and have formed unique genetic features. Meanwhile, putative selection regions containing candidate genes associated with the traits of milk production, growth, and carcass traits were also identified and annotated. These findings will be very useful for conservation, management, and selection approaches in CRS cattle in the future.


Urban shrinkage has become increasingly prevalent in the context of global urbanization. Understanding its spatio-temporal characteristics and influencing factors is of great significance for promoting sustainable development and high-quality urbanization. This paper identified county-level shrinking cities in Heilongjiang Province from the perspective of urban entities. It employed spatial autocorrelation methods to analyze their spatial-temporal characteristics and explored the factors that contributed to this phenomenon. The results indicated that between 2010 and 2020, the phenomenon of urban shrinkage at the county level in Heilongjiang Province was primarily concentrated in the province's hinterland. Moreover, they exhibited characteristics of the Great Recession and Small Growth. The main factors influencing the shrinkage included the urban industrial structure, living standards, and population composition. At present, some scholars believe that the study of urban shrinkage in China is not standardized, because the calibre of statistics is often the extent of the administrative region. In China, the administrative district of a city may contain non-urban areas such as the county and rural areas under its jurisdiction. This leads to recognition that the results are not scientific, when the county seat of a city shrinks, or in the case of shrinkage in the countryside within its administrative area. The City Entity itself may still be growing, but statistics show that cities are shrinking. This leads to a blind widening of the identification results and a preference for identifying “shrinking areas” rather than “shrinking cities” .ThereforBased on the above two points, this paper can reveal its temporal and spatial characteristics with more scientific and realistic urban shrinkage recognition results, and reveal its influencing factors in long-term sequences. On the one hand, it can provide reference for improving the more scientific method of urban shrinkage recognition. On the other hand, it can also provide more realistic policy advice to local governments and provide a reference for Heilongjiang province and other provinces and countries to deal with urban shrinkage.The remaining structure of this paper is as follows: The second part is a review of the relevant literature, the third part introduces the research area, research methods and data sources, the fourth part is the empirical analysis results, the fifth part is a discussion, the sixth part is a conclusion and policy recommendations.2Literatures focus on urban shrinkage are now enriched. In some studies, a single index of population change was used to identify urban shrinkage ,21. HoweTherefore, some studies began to take more comprehensive consideration of urban shrinkage, including economic , social While the urban shrinkage identification method is constantly improving, the research topic of urban shrinkage is no longer limited to the identification of the shrinkage phenomenon. It starts to explore the spatial-temporal characteristics and causes of urban shrinkage phenomenon at the national, regional and provincial scales . However33.1Heilongjiang province is located in the northeast region, which is the main commodity grain and old industrial base of China. The seventh national census results show that China's total population grew by 72.05 million between 2010 and 2020 . However3.23.2.1Mutation detection method was often used to extract urban built-up area boundaries. Due to the gradual weakening of the outward light of the urban built-up area and the certain diffusing nature of the nighttime light, the intensity of the nighttime light inside the city is usually higher and shows a decreasing trend to the edge area. Therefore, it needs to set a certain threshold value for urban nighttime light. With the continuous increase of the threshold value, the light area and its perimeter will gradually shrink. When the threshold value is raised to a certain extent, the light intensity reaches the range of the built-up area of the city, and the light area will be broken from a complete polygon, and its perimeter will increase. At this time, the threshold value is to extract the light value of the built-up area of the city . In this23.2.2ij is the radiation value of the ith phase element in the jth region.Drawing on existing studies ，, the ni3.2.3i represents the average population change rate of the ith city, t is the year, and Pit represents the total population of the ith city in the t year.This paper draws on the “two-step diagnostic method” of shrinking cities  to initiHowever, the second step is different. The second step in the traditional two-step diagnostic method is to identify the shrinking city with the evaluation index system. This paper applies nighttime lighting data to two-step diagnostics. The second step is to identify the urban shrinkage based on L, the sum of the changes of the annual nighttime light value of each city. When L is less than 0, it is identified as urban shrinkage. The formula is as follows Eq. :(3)Lnj=∑nj represents the shrinkage degree of the jth city in the nth year, and Inj represents the average nighttime light intensity of the jth city in the nth year.L3.2.4ij is the spatial weight matrix.Moran's I index was used to analyze the spatial agglomeration characteristics of county-level urban shrinkage in Heilongjiang Province, and Getis-Ord Gi* index was used to explore the hot and cold spots of urban shrinkage and reveal their spatial characteristics. Moran's I index formula is as follows Eq. :(4)MoranWhen the Z score in the Moran's results is greater than or less than 1.96 and the P value is less than 0.05. The shrinking cities are clustered at 95 % confidence intervals. At the same time, the Getis-Ord Gi* index can also indentify regions of spatial aggregation. The formula is as follows Eq. :(5)Gi*=∑The meaning of each symbol in the formula is as above.3.2.5it is the district average nighttime light intensity for the t year of the i county. Xnit represents the n variable of the t year of the i county. βn is the coefficient of the n-th variable, ɑi represents the influencing factors that the i-th individual does not change over time. The εit is a random disturbance term for the t-year of the i-county. When ɑi are seen as random factors, the model is a random effect model.Taking 63 county-level cities in Heilongjiang as the research area, this paper analyzes the variables affecting the shrinkage of county-level cities in Heilongjiang province from 2010 to 2020. Analyze select panel data, so model as follows Eq. :(6)Yit=β3.3The nighttime light data is derived from the cross-sensor-calibrated “NPP-VIIRS-like NTL Data” from the Harvard Dataverse platform with a spatial resolution of 500 m and a preprocessed coordinate system of WGS_1984  by Gong 44.1In the 63 cities within the research area, the first step preliminarily identified 60 shrinking cities except Fuyuan City, Suifenhe City and Tahe County based on the rate of population change. 38 cities, accounting for 60.3 %, were finally identified by the change of average nighttime light intensity from 2010 to 2020. According to the size of Lij, the shrinking cities were divided into four categories by natural breakpoint method: severely shrinking cities (−1.72 to −1.47), moderately shrinking cities (−1.47 to −0.4), mildly shrinking cities (−0.4 to −0.01) and non-shrinking .Fig. 2Di4.2The Moran's I index of county level urban shrinkage level in Heilongjiang Province from 2010 to 2020 is 0.07 , indicating that there are obvious spatial correlation characteristics of county level urban shrinkage in Heilongjiang Province.In order to explore the spatial agglomeration relationship of urban shrinkage degree, Getis-Ord Gi* index was used to analyze the hot and cold spots of urban shrinkage degree . The res4.3With the year 2015 as the cut-off point, the shrinking cities of two cycles from 2010 to 2015 and 2015 to 2020 were identified respectively. In the two cycles, the variation of nighttime light intensity was calculated based on the year 2010 and 2015 respectively, and graded according to the shrinkage degree by natural breakpoint method. From 2010 to 2014, -3.92 to −3.43 were severely shrinking cities, −3.43 to −0.98 were moderately shrinking cities, and −0.98 to −0.01 were mildly shrinking cities a. From 2Between 2010 and 2015, there were 47 shrinking cities in Heilongjiang Province, accounting for 74.6 %, while between 2015 and 2020 there were 11 shrinking cities, accounting for 17.4 %. The number of shrinking cities has decreased significantly. Cities that experienced non-shrinkage in both the first and second phases are classified as G-G type cities. Cities that experienced non-shrinkage in the first phase but shrinkage in the second phase are classified as G-S type cities. Cities that experienced shrinkage in the first phase but non-shrinkage in the second phase are classified as S-G type cities. Cities that experienced shrinkage in both the first and second phases are classified as S–S type cities.Based on this, Sankey diagram is drawn . As showAnd most of the severely and moderately shrinking cities in the first phase have weakened. All shrinking cities in the second phase are mildly shrinking cities (−0.98 to −0.01) if classified by the classification criteria for the degree of shrinkage in the first phase. In order to more intuitively reflect the shrinkage characteristics of Heilongjiang province counties in two phases, Further subdivision of these four types of cities based on the degree of shrinkage is performed. , visualiBut 28 of the 39 S-G cities were still identified as shrinking cities between 2010 and 2020, accounting for 71.7 % of S-G cities and 73.6 % of all shrinking cities. The average value of nighttime light of 28 S-G shrinking cities and 10 non-S-G shrinking cities in each year was calculated to draw a line graph . From 20In summary, although the urban shrinkage in Heilongjiang Province is concentrated , the shr4.4The core characteristic of urban shrinkage is population outflow, with the departing population often being the young and productive labor force. Consequently, as population outflow occurs, the urban population structure gradually ages. This leads to an insufficient supply of labor in the urban labor market, causing some factories and businesses to choose to relocate. The changes in businesses and population pose difficulties for the upgrading of the city's industrial structure and also disrupt the balance of the city's fiscal revenue and expenditure, resulting in a decline in GDP. At this point, the economic vitality of the city starts to decline, and the reduced government revenue makes it difficult to maintain urban infrastructure, leading to a decline in the level of infrastructure. Simultaneously, the decrease in the number of businesses and the challenges in upgrading the industrial structure lead to a reduction in employment opportunities, resulting in a decline in the living standards of city residents. During this time, the city often struggles to maintain a favorable position in urban competition, leading to population outflow and further promoting population loss, which affects urban shrinkage. Furthermore, urban shrinkage in turn stimulates population outflow and economic decline, creating a cycle of repetitive processes. The theoretical analytical framework is illustrated in 4.5Taking the average nighttime light intensity of each city from 2010 to 2020 as the dependent variable. Reference to existing research ,50 and cThe regression results of the models are shown in In terms of social factors, household saving balance has a significant positive impact on both non-shrinking cities and shrinking cities. Household saving balance reflects the wealth accumulation level of urban resident and can the standard of living and employment of urban residents to a certain extent. When urban resident can obtain sufficient material returns through work and other ways in the city, It often does not choose to flow out to other cities, thus promoting the development of cities. Highway length has a significant positive effect on non-shrinking cities, which reflects the promoting effect of traffic conditions on population flow. For non-shrinking cities, better transport means they can absorb more migrants and thus boost economic growth. In addition, highway length often reflects the high level of county infrastructure construction, thus promoting the growth of non-shrinking cities.In terms of economic factors, the number of industrial enterprises above designated size has a significant negative impact on non-shrinking cities, which may be related to the development history of Heilongjiang Province. Heilongjiang Province had a comparatively strong industrial base in the early years of the China. After the reform and opening up, Heilongjiang Province was unable to achieve the timely transformation of its industrial structure, and factories in counties were often unable to absorb high-level labor force, young people were also frequently reluctant to work in industrial businesses , which r4.6In order to verify the robustness of the model in the influencing factors analysis, Model 1 and Model 2 were tested by gradually increasing variables. Among them, the number of medical beds can reflect the medical level of the city. According to existing studies, the population loss of resource-exhausted cities is more serious . TherefoIn 5Based on the “two-step diagnosis method” of shrinking cities, this paper uses cross-sensor-corrected “NPP-VIIRS-like NTL Data” to identify the urban shrinkage of county-level cities in Heilongjiang Province from 2010 to 2020 from the perspective of physical cities. Moran's I index and Getis-Ord Gi* index were used to reveal its spatial characteristics. Taking 2015 as the boundary, the temporal characteristics of county-level urban shrinkage in Heilongjiang Province were analyzed, and variables were selected from the three dimensions of population, urban economy and social life to explore the influencing factors of county-level urban shrinkage in Heilongjiang Province. The results shown that the county level cities in Heilongjiang Province have the characteristics of spatial agglomeration and “big recession, small growth” in time. It is also found that the shrinkage of county level cities in Heilongjiang Province from 2010 to 2020 is mainly in the stage between the two turnning points of population loss and economic recession. To deal with the phenomenon of urban shrinkage, we should begin by focusing on ways to enhancing inhabitants' quality of life, enhancing the governance ability of urban government, upgrading the industrial structure and adjusting the population structure.In the study, when the “two-step diagnostic method” was used to identify urban shrinkage, it was found that the identification results of the first step were significantly different from those of the second step. The shrinking cities identified by a single population index were significantly more than those identified by nighttime light intensity, and from the perspective of time characteristics, the decrease of nighttime light intensity lagged the population loss, while some of the cities with the decrease of nighttime light intensity did not have economic recession. This further proved the conclusion that there is a lag between the turnning point of population, economic activity intensity, economic level and spatial quality of shrinking cities. Therefore, although population loss is the reason for the decline in the intensity of urban economic activity, it is may not comprehensive to identify shrinking cities only from population change. In addition, this paper identified the county-level shrinking cities in Heilongjiang Province from the perspective of physical cities. The identification results based on the nighttime lights of urban built-up areas exclude the interference of non-urban areas and have stronger reality.66.1Within the research area, there are significant spatial aggregation characteristics of each shrinking city. Shrinking cities are concentrated in Xunke County, Suiling County and Qingan County, interleaved in the hinterland of Heilongjiang Province. Non-shrinking cities are mainly distributed in Hulin City, Dongning City and Suifenhe City, which are located around the Sanjiang Plain and major cities in the Northeast Eastern Economic Belt, and a large number of non-shrinking cities gather around the Hadaqi Economic Belt. It can be seen that agricultural production activities and major cities in Heilongjiang Province can promote the development of surrounding counties.6.2Taking 2015 as the boundary, the counties of Heilongjiang Province mainly shrunk in the previous phase, and the degree of shrinkage was more serious. However, after 2015, most counties are showing signs of re-growth. Therefore, more active and effective measures should be taken for the management of county-level urban shrinkage in Heilongjiang Province to cultivate the county economy vigorously and inject vitality into the economic development of counties.6.3Heilongjiang's shrinking cities are still mainly in the stage of GDP growth. According to existing studies, in the process of urban shrinkage, population loss, weakening of economic activity and recession will occur in turn. Nighttime lights reflect the intensity of economic activity in cities, and their decline tends to lag behind the decline in urban population. Among the influencing factors, per capita GDP has a negative impact on shrinking cities, which is proved the shrinkage of county-level cities in Heilongjiang Province is still in the middle stage between the turnning point of population loss and economic recession. At this time, the process of urban shrinkage is often still reversible, more active and effective measures should be adopted to take appropriate governance measures for some shrinking cities.6.4Population loss is the first step in urban shrinkage. Population tends to relocate in pursuit of a higher quality of life. Based on the above research findings, wealth accumulation of urban residents will promote the development of shrinking cities, and the proportion of urban young population will also have a promoting effect. For the urban economic conditions, the advanced degree of the industrial structure and financial status will have an impact on the urban shrinkage. The more advanced the industrial structure and the larger the proportion of financial revenue and expenditure, the more it can promote the development of shrinking cities.6.56.5.1The county-level shrinking cities in Heilongjiang Province are in the early stage of shrinkage, combined with urban characteristics to explore differentiated development strategies, still help to shrinking city to achieve re-growth. For Heilongjiang Province, agricultural production activities and the major cities around the county can promote its urban development. For the county around the northeast Sanjiang Plain, the goal should be to achieve agricultural mechanization and modernization, thus promoting the development of the county; Hadaqi economic belt, the east economic belt in northeast of the major cities surrounding the county, should pay attention to be linked with the neighboring big cities, to achieve industrial complementarity and win-win cooperation.6.5.2The shrinking county government of Heilongjiang Province should pay attention to realizing the development of “smaller and smarter growth,” get rid of the traditional lightweight growth model, properly concentrate public resources, improve urban infrastructure, and the quality of life of residents while ensuring good financial functioning.6.5.3Rural population loss in Heilongjiang Province is difficult to reverse, We should focus on improving the basic education level of the county and exploring the social security system of transferring the population from agriculture into the city. Promote the transfer of agricultural population close to urbanization, open the “money、land and people” element gathering channel, to avoid population loss exacerbated urban shrinkage.6.5.4For county cities in Heilongjiang province, agricultural production should be ensured while extending the agricultural industrial chain and promoting deep processing of agriculture. Reduce production pollution in industrial enterprises and improve the quality of the urban environment. We will actively develop tourism resources, explore growth models such as tourism with local characteristics, enhance the advanced level of industrial structure, achieve the integration of three-industry integration, create more quality jobs, and build a new growth pole in the county.7Few limitations remain. Firstly, for data accessibility reasons, this paper extracts nighttime light data from built-up areas for the two cycles around 2015 with city boundaries in 2010 and 2015. Although urban boundary expansion is a slow process, and the closer the city center, the more stable the nighttime lights, the more accurate the results can be further improved by obtaining year-by-year city boundary data through remote sensing interpretation.Secondly, for data timing stability, only eight variables are selected as influencing factors. Further consideration could be given to the integration of urban geography, natural characteristics and other factors to improve the comprehensiveness of the influencing factors.Finally, the study scale is selected for only ten years, and the urban shrinkage characteristics on the longer scale can be explored.Data will be made available on request.Junqi Huo: Data curation, Formal analysis, Methodology, Software, Visualization, Writing – original draft. Shanlin Huang: Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Validation, Writing – review & editing.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Phoenix dactylifera L.Date palm, oasis pivot, plays a vital socio-economic part in the southern area of Morocco. However, with climate change and drought intensity and frequency increasing, the Moroccan palm grove is threatened with significant genetic degradation. Genetic characterization of this resource is key element for the development of effective conservation and management strategies in the current circumstances of climate change and various biotic and abiotic stresses. To evaluate the genetic diversity of date palm populations collected from different Moroccan oases, we used simple sequence repeats (SSR) and directed amplification of mini-satellite DNA (DAMD) markers. Our results showed that used markers could efficiently assess genetic diversity in A total of 249 and 471 bands were respectively scored for SSR and DAMD, of which 100% and 92.9% were polymorphic. The polymorphic information content (PIC = 0.95), generated by the SSR primer was nearly identical to that generated by the DAMD primer (PIC = 0.98). The resolving power (Rp) was higher in DAMD than SSR . Analysis of the molecular variance (AMOVA) based on the combined data sets for both markers revealed a higher variance within populations (75%) than among populations (25%). Principal coordinate analysis (PCoA) and the ascendant hierarchical classification showed that the population of Zagora and Goulmima regions were the closest populations. The STRUCTURE analysis clustering of the 283 tested samples into seven clusters based on their genetic composition.The results drawn from this study will orient genotypes selection strategies for a successful future breeding and conservation program, particularly under climate change context.The online version contains supplementary material available at 10.1186/s43141-023-00516-7. Phoenix dactylifera L.) is a diploid (2n = 36), monocotyledonous plant [The date palm  from a total cultivated area of 1.09 million hectares. For Morocco, the production is considered to be 1 million tons over an area of 59.127 ha .Despite the availability of several cultivars, local date palm groves are seriously threatened by abiotic and biotic stresses such as, salinity, prolonged drought, and diseases  which coPhenotypic and biochemical markers have been used to assess genetic diversity of date palm, –19. HoweIndeed, a fitting molecular marker ought to be significantly heritable, and applicable to any part of the genome and should be sufficiently polymorphic to allow the discrimination of narrowly related genotypes . SSRs anDescription and genetic diversity assessment are important requirements for genetic improvement approaches, and resource management strategies. Hitherto, little is known about genetic diversity and population structure of Moroccan date palm. This research is conducted to assess genetic diversity and genetic structure present in Moroccan date palm population collected from five important Oases in southern Morocco.The current study is the first report to my knowledge on the genetic diversity assessment and population structure of 276 date palm collected from 5 different zones of Morocco. Additionally, here we also provide a correlation between Moroccan date palm genotypes and some Iraqi cultivars using DAMD and SSR markers.Phoenix dactylifera L. population in Morocco: Zagora, Errachidia, Goulmima, Tata, Tinghir. Multiple collection sites were selected from each region . Thereafter, DNA was extracted from the ground tissues by using the CTAB (Cetyl Trimethyl Ammonium Bromide) method as described by Saghai-Maroof  with minThe crushed plant tissue was combined with 1 ml pre-warmed of 2% CTAB buffer (1 M Tris–HCl (pH 8.0), 5 M NaCl, 0.5 M EDTA ethylene diamine tetra acetic acid, 2% CTAB, and 0.2% of β-mercaptoethanol, 0.2% polyvinylpyrrolidone (PVP)), and then the mixture was maintained at 65 °C in a water bath for 60 min; next, the blend was cooled in an ice bucket, and after 700 μl of an equal volume of chloroform isoamyl alcohol (24:1) were added. The tubes which contain the mixture were inverted several times for 15 min to ensure that reagents were mixed well. The mixture was then centrifuged at 13,000 rpm for 10 min.Next, the supernatant was moved to a new tube and the RNA was eliminated by adding 1 μl of RNA-ase to the mixture, which was incubated at 37 °C for 30 min. Thereafter, 700 μL of ice-cold isopropanol was added to the samples, the mixture was shaken gently and stored overnight to ensure precipitation of nucleic acids.DNA recovery was completed out by centrifuging at 13,000 rpm for 10 min at 4 °C. and washing twice with ice-cold ethanol (70%). The resulting DNA was dissolved in 200 μL of pure sterile water.The DNA concentration and quality were assessed by using a NanoDrop spectrophotometer. DNA was deemed pure when the A260/A280 ratio ranged between 1.80 and 2.0 .Phoenix dactylifera L. samples. Based on the best amplification results, only 10 SSR primers that gave clear and reproducible bands were eventually chosen for PCR amplification of the entire range of 283 Phoenix dactylifera L. genotypes.At first, a set of 30 SSR primers were screened on 10 DNA random templates of The ten polymorphic microsatellites selected were antecedently developed in date palm by , the forThe SSR loci’s were performed in a reaction volume of 10 μl consisting of 1 × buffer, 0.5 U of Taq DNA polymerase , 0.5 μM (10 pmol) of each forward and reverse primers and approximately 25 ng of genomic DNA.The amplification reactions were performed out in the Eppendorf Master cycler with initial denaturation for 1 min at 94 °C. This was followed by 35 cycles of each cycle with 30 s denaturation at 94 °C, 1 min annealing at 52 °C, 2 min extension at 72 °C. and the final extension was carried out at 72 °C for 8 min. The reactions were then held at 4 °C.Nine minisatellite DAMDs were chosen and used in this study Table  based onThe PCR composition was the same as SSR analysis. Polymerase chain reactions (PCR) were performed out according to the program as follows: initial denaturation for 3 min at 94, then 35 cycles of 45 s denaturation at 92 °C, 2 min at annealing temperature (depending on the primer’s Tm), 2 min extension at 72 °C and the Final extension was carried out at 72 °C for 5 min followed by cooling at 4 °C for an unlimited period.In order to detect polymorphism among accessions, the PCR product was transferred to 6% polyacrylamide gel (for higher resolution), using 1 × TBE as running buffer at 120 V. The amplified bands were detected by staining in an ethidium bromide solution for 5 min(10 mg/ml) and visualized under ultraviolet light in Molecular Imager_ Gel DocTM XR System. The gel profiles were photographed and recorded as digital images in a Gel Documentation System for later scoring.Each visual, clear and distinct band amplified was considered as a single allele and scored manually as present (1) or absent (0) from each SSR and DAMD profiles. Then, a binary data matrix was developed that is used for all analyses.The effectiveness of each primer used (SSR and DAMD) was assessed by calculating the polymorphic information content (PIC) using the equation h allele . Also, , percentage of polymorphic loci (PPL), number of effective alleles (Ne), expected heterozygoty (He), and Shannon’s information index (I). Molecular variance (AMOVA) was performed, to measure the partitioning of genetic variability between and within populations by the same software. The resulting distance matrices of squared Euclidean distances [GenAlex ver. 6.5 software  was usedistances  between K value.Finally, to characterize the overall genetic structure and assign individuals to populations, molecular data were analyzed using the STRUCTURE software v.2.3.4  based onPhoenix dactylifera L. The variation of the SSRs amplification frequency based on the availability of motifs in genomic DNA of different genotypes with an average of 24.9 distinct scorable bands were produced by these primers. The primer Cir 50 produced a maximum of 41 scorable bands while the primer Cir 93 generated only 15 fragments. A total of 249 DNA fragments were obtained across all 283 genotypes using the 10 SSR primers  and Rp (20.74) values were observed for the Cir 25 and Cir 48 primers, respectively; minimum values for PIC (0.83) and Rp (12.26) were recorded for primers Cir 35 and Cir 25, respectively. In general, the 10 SSR primers utilized in this research recorded an average PIC of 0.954 and an average Rp of 19.51  to 0.99 (HBV5 and HBV3) with an average PIC of 0.98. Rp values were evaluated for the eight primers, the lowest Rp value was observed in URP2R (16.87) and the highest one (36.96) in HBV5 with mean of 29.46.The presence of private alleles is a further indication of population differentiation. Private alleles were detected in Zagora, Goulmima, Errachidia, Tinghir, and Tata  with DAMD primers, while none were detected in Moroccan and Iraqi varieties Table .Phoenix dactylifera L. populations.SSR and DAMD markers disclosed various degrees of genetic variability within and between For the SSR markers, the highest values of Genetic parameters viz- observed number of alleles (Na) number of effective alleles (Ne), Shannon’s information index (I), expected heterozygosity (He), and unbiased expected heterozygosity (uHe) were obtained in the Tata population, with values of 1.984, 1.408, 0.402, 0.255, and 0.258, respectively. While the lowest values were recorded in Moroccan varieties, with values 1.394, 1.285, 0.288, 0.181, and 0.190, respectively  were observed in Zagora population with values 1.349, 1.254, 0.252, 0.160, 0.160, and 67.15% . Pairwise population PhiPT values for seven clusters ranged from 0.163 (Zagora-Goulmima) to 0.391 (Tinghir-varieties) . Whereas Errachidia population and Moroccan varieties had the lowest similarity (0.898) and the maximum genetic distance  , and the lowest genetic distance  Table .Table 7PCombined matrix of SSR and DAMD data was employed to build an UPGMA tree. The cluster analysis classified the investigated genotypes into two distinct clusters. The first cluster (I) comprised Moroccan varieties and Iraqi varieties. The second cluster (II) was segregated into two sub clusters. The first one (IIa) comprised of Tinghir and Errachidia populations, and the second sub-cluster (IIb) was split also into two groups, the first group contained Tata population and the second Group encompassed Zagora and Goulmima populations. The UPGMA tree showed in the majority of the individuals were separated according to their populations Fig. .Fig. 4UPPhoenix dactylifera L. genotypes studied. Depending on combined data from SSR and DAMD markers, PCoA illustrated 17.43% of the total variations, with the first three axes  accounted for 7.3%, 5.75%, and 4.38%, respectively.The PCoA allowed the study of the correlation between different The screen plot generated by PCoA highlighted, the grouping of Tata population with Iraqi varieties. The rally of Zagora population with Goulmima population and Moroccan varieties and one genotype from Iraq and the closeness of Errachidia population with Tinghir population Fig. .Fig. 5PrK = 1 to K = 10. The maximum value of Δk was detected at K = 7. This suggested that the most likely structure of tested samples is their distribution into seven principal clusters  for the estimation of the most likely number of genetic clusters (K), we investigated the range from ers Fig. .Fig. 6PoIndividuals are separated by vertical columns and identified by colors. The same color in different individuals shows that they are part of the same genetic cluster. Different colors in the same individual indicate the likelihood to pertain to different genetic groups.Phoenix Dactylifera L. could be grouped into seven populations. The first cluster mainly included of Tinghir and Errachidia population. The second cluster consisted of the Goulmima population. The major group of the Zagora population was split into three clusters. One of the seven clusters was containing the population of Tata and the other genetic cluster comprised Moroccan varieties, while the populations of Iraq varieties were found into both clusters.Our result indicated that the genetic structure of Phoenix dactylifera L. collection from five Moroccan regions populations.For all species evolution and adaptation, genetic variability plays an important role. So, genetic diversity assessment is a key to an effective management and breeding program. Therefore, in this study, we combined SSR and DAMD molecular markers to assess genetic variation among and within The results of this investigation revealed that both molecular markers SSR and DAMD generated high polymorphism level with 100% of PP for DAMD primers, and 92.9% for SSR primers. This polymorphism level was higher than that reported by Mirbahar et al.  and SrivThe genotyping data in this study have shown that date palm is rich in allelic variation as confirmed by previous studies , 73. In Amplified band number by DAMD were higher than those amplified by SSR markers, indeed 471 bands were amplified with an average of 59. However, the average numbers of each marker in the current study were higher than those reported earlier . The ZagP = 88.87%; DAMD: Na = 1,016(0.017) Ne = 1,231(0.006), I 0,215 and He = 0.140(0.003) uHe = 0.143 %P = 49.49%; Combined Na = 1,277(0.013) Ne = 1,277(0.005), I = 0.266(0.004) and He = 0.171(0.003) uHe = 0.175(0.003) %P = 62.81%) are a little moderate and higher in SSR. Based on these parameters, the studied populations ranked from the most diverse to the least diverse as follows: Zagora, Tata, Errachidia, Goulmima, Tinghir, Iraqi, and Moroccan varieties. Hence, our findings suggest that the Zagora and Tata populations have the highest genetic variability level. These observations suggest that Zagora and Tata populations could be involved in an effective date palm improvement and conservation strategy.The genetic parameters detected from the two markers in our findings  Ne = 1,368(0.008), I = 0.365(0.005) and He = 0.231 uHe = 0.237(0.004) %P = 29.67%). While the Al-Najm et al. [When assessing genetic relationships of the date palm cultivars using the dominant marker system iPBS Al-Najm et al.  noted a m et al.  reportedResults of AMOVA test have shown that the genetic diversity of Moroccan date palms is highly represented within populations with 75% instead than among populations with 25%. This is in accordance with genetic diversity assessment in date palm genotypes of Sudan , and TunThe presence of genetic variability within populations is a condition for adaptation and evolutionary transition. Despite date palms are mostly vegetative propagated, most genetic variations observed are essentially caused by mutations, but in the other few cases through sexual reproduction, the meiosis and fertilization lead to immense genetic diversity. Moreover, the famer management had an important impact on this diversity.However, the Nei analysis revealed low distance values between populations this is in line with AMOVA result which indicate the low diversity among populations with 25%. This finding can be explained by the same origin gene pool of Moroccan date palm. Indeed, Zehdi et al.  revealedSignificant values of similarities were obtained mostly between Zagora and Goulmima populations, as illustrated in the UPGMA dendrogram Fig. , where tGenetic variation partition in seven differentiated groups obtained with STRUCTURE regrouped Tinghir with Errachidia populations in the same cluster, and Goulmima in another one. While the latter is geographically closer to Errachidia than Tinghir. This can explained by human activities in exchanging disparate materials . Tata poSTRUCTURE and UPGMA cluster results showed that there is geo-graphical conservation of accessions. Genetic structure of date palms obtained in this study can be explained by distance geographical isolation, plant biological nature, and environmental conditions . FurtherZagora and Goulmima populations have the higher genetic diversity. Indeed, Zagora harbor 39 private alleles and Goulmima 23. These populations should be prioritized in conservation strategies.Phoenix dactylifera L. Further, AMOVA of this plant showed a high degree of variation within populations.This work provided a knowledge about genetic resources in the main distribution area of the Moroccan date palm. The SSR and DAMD markers showed adequate polymorphism and offered appropriate details for the genetic diversity assessment of Phoenix dactylifera L. preserving and conservation resources. Consequently, the sustainability of the oases, especially in the era of climate change, will be ensuring.Genetic diversity reported in our result is essential for evolutionary adaptation in climate change context and for date palm sustainable breeding purposes. Moreover, our results may be a significant guideline for the collection of core germplasm resources. So, we recommend in-situ and ex situ genetic resources management to assure the conservation of this diversity. The approach also must increase the local community awareness of the suitable farming techniques for Additional file 1: Table S1. Latitude and longitude of collected accessions.


This cross-sectional study compares recent list and net prices for Humira after rebates with announced prices of interchangeable biosimilar Humira formulations. This information contextualizes the prices announced for biosimilars and enables estimations of savings associated with their entry.In 2023, branded adalimumab (Humira) saw the end of its 20-year market exclusivity. When launching Amjevita in January 2023, the first biosimilar adalimumab marketed, Amgen established 2 versions, one with a list price 55% below Humira and a second with a list price 5% below Humira, with presumably a 50% rebate.We estimate commercial (private market and Medicare Part D) and Medicaid net prices of Humira after accounting for rebates negotiated with pharmacy benefit managers (PBMs). We then compare recent list and net prices for Humira with announced biosimilar prices.3 We then estimated the difference between gross sales and company-reported net sales from SSR Health.3 From this difference, we subtracted government discounts  and attributed the remaining amount to PBM rebates. We estimated Medicaid and 340B discounts under an established method, accounting for the Medicaid best price, as detailed in the eMethods in 5 Medicaid inflation rebates, which reimburse Medicaid for price increases above inflation, were separately estimated for original Humira and the citrate-free version introduced in 2018. Coverage gap discounts were estimated from the Medicare 5% sample. We assume both original and citrate-free Humira have the same net price after PBM rebates. This study followed the STROBE reporting guideline for cross-sectional studies.This study was exempt from institutional review board approval as research without human participants, and data were deidentified. For 2013-2020, we estimated annual gross sales as the product of list price and units sold.In 2013-2020, the list price for original Humira increased from $1153 to $2784 (141% increase) and PBM rebates increased from $28 (2.4% of list price) to $973 (34.9% of list price) A. AveragFrom 2013 to 2018, the Medicaid base rebate equaled 23.1% of list price . After 2Despite increasing rebates, the net price of Humira faced by commercial and Part D plans in 2020 was $1812, 3.5 times the launch price ($522). In 2023, the lowest-cost formulation of Amjevita had a list price of $1558, a 14% discount from the 2020 net price of Humira. Even at the 55% discount, Amjevita still costs more than double the launch price of Humira. These estimations are limited by only being able to compare the 2020 net price of Humira with current Amjevita pricing and by the lack of data to estimate discounts to federal purchasers, which are as a result included under PBM rebates.6While Amjevita is not interchangeable with Humira, interchangeable versions of Humira are anticipated to launch in the second half of 2023. These formulations may compete more directly on list price, marketing to pharmacies seeking to source lowest-cost product to generate a margin when reimbursed by an insurer at a predetermined amount for interchangeable formulations. However, the interchangeable biosimilars expected in 2023 will only be interchangeable with original Humira, but not the citrate-free version.


Cotinus is an oligo‐specific ornamentally valuable genus with a disjunct distribution in the Northern Hemisphere. Traditionally, the taxonomy of Cotinus was mainly based on leaf morphological characteristics. However, the limited availability of genomic information greatly hindered the study of molecular evolution and phylogeny of this genus. This study sequenced the chloroplast (cp) genomes of all currently recognized taxa of Cotinus, including three species and four varieties. A comparative analysis was performed to investigate their cp genome characteristics and evolution. Furthermore, we inferred the phylogenetic relationships of Cotinus based on whole cp genomes, protein‐coding genes, and nuclear ITS data. All cp genomes exhibited a typical quadripartite structure with genome sizes ranging from 158,865 to 160,155 bp. A total of 113–114 genes were identified in the genomes. Seven non‐coding and four coding regions were identified as the most divergent hotspots for potential molecular barcodes and phylogenetic markers. Selection pressure analysis showed that there had been positive selection on genes matK and rps8 in the Cotinus cp genomes. Phylogenetic results confirmed that Cotinus is a monophyletic group but the widely distributed species Cotinus coggygria is not monophyletic. The divergence‐time analysis suggested that Cotinus underwent an evolutionary divergence from the middle Eocene and rapid adaptive radiation from the middle Miocene. This study revealed new insights into the cp genome evolution and phylogeny of Cotinus and related taxa. Cotinus, and identified 11 divergence hotspots for useful molecular barcodes. Conducted the selection pressure analysis for 79 protein‐coding genes. Cotinus is a monophyletic group but Cotinus coggygria is not monophyletic. Cotinus underwent a rapid adaptive radiation from the middle Miocene.Analyzed the plastid genome evolution of  It exhibits a disjunct distribution in the Northern Hemisphere particularly in southern Europe, eastern Asia, and North America  Mill. were referred to as the Rhus complex  genomes are circular DNA molecules composed of a large single copy (LSC) region and a small single copy (SSC) region separated by a pair of inverted repeats (IR) regions  reveal the cp genome characteristics, and divergence patterns of Cotinus; (2) provide useful cp genomic resources for molecular barcodes and phylogenetically informative markers; and (3) improve our understanding of the evolutionary history and infrageneric relationships of Cotinus.Here, we sequenced and assembled the cp genomes of all currently recognized species and varieties in 22.1Cotinus were sampled and sequenced. The fresh leaves of C. nana, C. szechuanensis, C. coggygria var. cinerea, C. coggygria var. glaucophylla and C. coggygria var. pubescens were collected from the field and dried with silica gel. Voucher specimens were deposited at the Beijing Forestry University Herbarium (BJFC), Beijing. The dry leaves of C. coggygria var. coggygria were sampled from the specimen in the Beijing Forestry University Herbarium. The dry leaves of C. obovatus was provided by Prof. Libing Zhang from Missouri Botanical Garden, USA. Details of the sampling information were shown in Table Ten accessions representing three species and four varieties of Total genomic DNA was extracted from silica‐dried leaves using a modified CTAB protocol  as the reference genome. These cp genome sequences were deposited in GenBank  and 103 intergenic spacer regions (IGS) of the seven cp genomes were separately extracted, aligned using MAFFT  and Bayesian Inference (BI) methods for phylogenetic analysis. The first dataset WCG included 25 whole cp genomes from Anacardiaceae and two outgroup genomes from Burseraceae . Cotinus szechuanensis and C. coggygria var. glaucophylla lost the rpl32 gene, and the rps19 gene was lost in C. obovatus and C. coggygria var. pubescens cp genomes. All the cp genomes had 30 tRNA genes and four rRNA genes. Seven protein‐coding genes  in five taxa (except C. obovatus and C. coggygria var. pubescens), seven tRNA genes  and four rRNA genes  in all genomes were duplicated in the IR regions , followed by the LSC region (1.27%), and then the IR region  and four coding genes  were identified as the most divergent hotspot regions. These hotspot regions were all located in the LSC region except for rpl32 located in the SSC region. Concerning PICs, gene regions atpA‐atpF (7.02%) and atpF‐atpH (4.15%) had higher PICs percentages in non‐coding regions, while gene rpl22 had a higher percentage (1.54%) in coding regions.To identify the mutation hotspot regions, the percentages of variable sites and PICs were calculated in each coding and non‐coding region Figure . We defi3.4atpE, ndhG, petG, psaI, psbH, psbK, ycf3, and ycf15) with Ka/Ks = 0, and no gene with Ka/Ks = 1. Only two genes (matK and rps8) had Ka/Ks ratios greater than 1, with the values of 1.1605 and 1.5070, respectively. The remaining 68 genes showed Ka/Ks ratios of between 0.0001 and 0.8709.Using the site‐evolution models of CodeMl, non‐synonymous to synonymous nucleotide substitution rate ratios (Ka/Ks) for 78 shared protein‐coding genes were calculated Figure . Among t3.5Cotinus and related genera. However, the supported values of some nodes within Cotinus were moderate or low, especially for the PCG tree.The phylogenomic analyses were conducted based on WCG and PCG datasets Figure . The WCGCotinus clustered together, forming a monophyletic group, sister to Pistacia with high support (PP/BS: 1/100). Three species and four varieties formed two clades. One clade comprised C. nana, C. coggygria var. pubescens, C. coggygria (MT876478), C. obovatus, C. coggygria var. coggygria and C. szechuanensis. Within this clade, C. coggygria var. pubescens was sister to C. coggygria (MT876478) with high support (PP/BS: 1/100). In the WCG tree, C. coggygria var. pubescens and C. coggygria were sister to the two individuals of C. nana with moderate support (PP/BS: 0.98/72), then together sister to C. obovatus with moderate support (PP/BS: 0.99/83). This group was, in turn, sister to C. coggygria var. coggygria with higher support (PP/BS: 1/90). In the PCG tree, C. coggygria var. coggygria was sister to C. obovatus with low support (PP/BS: 0.32/25), which sister to the C. coggygria var. pubescens‐C. coggygria (MT876478) group with low support (PP/BS: 0.78/36), and then together sister to C. nana with higher support (PP/BS: 1/84). In both WCG and PCG trees, the two individuals of C. szechuanensis were the firstly diverged species in this clade with strong support. The second clade consisted of C. coggygria var. glaucophylla and two individuals of C. coggygria var. cinerea. There were high support values for the second clade in both WCG and PCG trees .Both WCG and PCG datasets showed that the sampled taxa of Cotinus formed a monophyletic group but most nodes were lower supported within Cotinus  during the middle Eocene, and the crown age of Cotinus, leading to the divergence of the genus into two clades, was estimated at 17.91 Ma (95% HPD: 11.29–25.66 Ma) in the middle Miocene. Within Cotinus, C. coggygria var. glaucophylla and C. coggygria var. cinerea were estimated to diverge at 14.82 Ma (95% HPD: 8.04–22.89 Ma) in the middle Miocene, and C. szechuanensis was suggested to diverge around similar time . Cotinus coggygria var. coggygria was estimated to diverge at 13.24 Ma (95% HPD: 7.82–19.20 Ma), and C. obovatus was estimated at 11.69 Ma (95% HPD: 6.74–17.24 Ma). Cotinus nana diverged from C. coggygria var. pubescens at 9.95 Ma (95% HPD: 5.41–14.97 Ma) in the late Miocene.Based on whole cp genomes data, the mean estimated ages and 95% HPD (highest posterior density) intervals of nodes were mapped onto the dating chronogram , Pistacia weinmannifolia Poiss. ex Franch. (37.84%), and Toxicodendron vernicifluum (Stokes) F. A. Barkley ]} clade. Cotinus szechuanensis is similar to C. coggygria var. pubescens and C. coggygria var. coggygria in habitat and leaf shape but is distinguished by its smaller leaves with conspicuous tufts of white pubescence in the primary vein axils on their lower surface. Additionally, its leaves may have a wavy margin. In geographic distribution, C. szechuanensis is restricted to the high‐mountain  regions of the arid river valley in northwestern Sichuan. Based on the analysis on leaf characteristics of C. szechuanensis and environmental factors in the dry valley of the upper Minjiang River, Li et al. , and reticulation evolution. This is especially true for the groups in which speciation was accompanied by rapid adaptive radiation ; data curation (lead); formal analysis (lead); investigation ; methodology ; resources ; software ; writing – original draft . Nan Yang: Data curation (supporting); formal analysis (supporting); investigation ; methodology ; resources . Wenpan Dong: Conceptualization ; formal analysis ; methodology ; software ; supervision ; writing – original draft . Liangcheng Zhao: Conceptualization ; funding acquisition (lead); investigation ; project administration (lead); resources ; supervision (lead); validation ; writing – original draft ; writing – review and editing (lead).This research was supported by Science and Technology Basic Resources Investigation Program of China “Survey and Germplasm Conservation of Plant Species with Extremely Small Populations in South‐west China” (Grant No. 2017FY100100).The authors declare that there is no conflict of interest.


Oryza longistaminata is a valuable genetic resource for the improvement of the domesticated Asian rice, Oryza sativa. To facilitate the conservation, management, and use of O. longistaminata germplasm, we sought to quantify the population structure and diversity of this species across its geographic range, which includes most of sub-Saharan Africa, and to determine phylogenetic relationships to other AA-genome species of rice present in Africa, including the prevalence of interspecific hybridization between O. longistaminata and O. sativa. Though past plant breeding efforts to introgress genes from O. longistaminata have improved biotic stress resistance, ratooning ability, and yield in O. sativa, progress has been limited by substantial breeding barriers. Nevertheless, despite the strong breeding barriers observed by plant breeders who have attempted this interspecific cross, there have been multiple reports of spontaneous hybrids of O. sativa and O. longistaminata (aka “Obake”) obtained from natural populations in Africa. However, the frequency and extent of such natural introgressions and their effect on the evolution of O. longistaminata had not been previously investigated. We studied 190 O. longistaminata accessions, primarily from the International Rice Research Institute genebank collection, along with 309 O. sativa, 25 Oryza barthii, and 83 Oryza glaberrima control outgroups, and 17 control interspecific O. sativa/O. longistaminata hybrids. We analyzed the materials using 178,651 single-nucleotide polymorphisms (SNPs) and seven plastid microsatellite markers. This study identified three genetic subpopulations of O. longistaminata, which correspond geographically to Northwestern Africa, Pan-Africa, and Southern Africa. We confirmed that O. longistaminata is, perhaps counterintuitively, more closely related to the Asian species, O. sativa, than the African species O. barthii and O. glaberrima. We identified 19 recent spontaneous interspecific hybrid individuals between O. sativa and O. longistaminata in the germplasm sampled. Notably, the recent introgression between O. sativa and O. longistaminata has been bidirectional. Moreover, low levels of O. sativa alleles admixed in many predominantly O. longistaminata accessions suggest that introgression also occurred in the distant past, but only in Southern Africa.The undomesticated rice relative  Oryza sativa, is projected to rise from 439 million tons to 555 million tons between 2010 and 2035 , manipulating the crossability between these two species could accelerate introgression efforts  characterize the population structure of O. longistaminata throughout its native range in sub-Saharan Africa using 190 accessions primarily from the International Rice Research Institute (IRRI) genebank, 2) quantify genetic diversity of O. longistaminata overall and among its genetic groups, and 3) determine if previous reports of spontaneous interspecific hybrids between O. sativa and O. longistaminata in Africa can be confirmed in the IRRI germplasm collection and to conduct an Africa-wide quantitative assessment of recent and past introgressions.Because hybridization with  efforts . The suc efforts . Recover efforts . In contO. longistaminata, collected from much of the species’ native geographic range in sub-Saharan Africa; this included all of the available and viable accessions in the IRRI genebank and one accession from Yunnan University , O. barthii (n = 25), and O. glaberrima (n = 83) were obtained as seeds from the USDA National Plant Germplasm System or Dr. Fengyi Hu’s perennial rice breeding program at Yunnan University, or their sequence data only were accessed via the 3k Rice Genomes Project or the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA), with one individual per accession studied for these inbreeding species  were included in the study as controls for comparison with putative interspecific hybrids observed in the O. longistaminata accessions. The interspecific hybrid controls were not counted in the O. longistaminata sample size. The control interspecific individuals were from a cross between the Thai O. sativa ssp. indica cultivar RD-23 and a Nigerian O. longistaminata accession .We studied 190 accessions of ccession , both ofPstI-HF and MspI followed by ligation to barcoded adapters; then, the samples were pooled, and 200–500-bp fragments were selected and amplified by polymerase chain reaction (PCR). Libraries were sequenced on an Illumina Hi-Seq 2000 for 100-bp single-end reads at the Roy J. Carver Biotechnology Center at the University of Illinois. Demultiplexed reads were aligned to the Nipponbare IRGSP-1.0 reference genome using Bowtie 2.2.4  and seven plastid microsatellite markers. DNA was extracted from lyophilized seedling-stage leaf tissue using the cetyltrimethylammonium bromide (CTAB) method with minor modifications for the samples sequenced in-house for this study . To idenie 2.2.4 . For allie 2.2.4 . IndividSeven plastid markers were amplified from the DNA to check for consistency between maternal and nuclear genotypes, as well as to confirm the directionality of crosses that produced putative interspecific hybrids  was chosen as optimal. To distinguish putative interspecific hybridization of O. longistaminata from model noise or variation in individual relatedness to a shared common ancestor, putative O. longistaminata interspecific hybrids were defined to have 4.4%–95.6% admixture with control outgroups. The thresholds were chosen because the minimum admixture detected in control O. sativa/O. longistaminata RILs was 4.5% . A plastid haplotype network was constructed with seven segregating microsatellites for 312 O. longistaminata individuals, 15 putative interspecific hybrids, 5 O. sativa individuals, and 3 O. barthii individuals with no missing data following To identify genetic subpopulations and assign individuals to those groups, two complementary analyses of population structure were conducted using the ADMIXTURE model in the software STRUCTURE 2.3.4  and discwas 4.5%  to obserSpatial principal component analysis (sPCA) was conducted in the R package adegenet to identify spatial patterns in genetic variation. To reduce computation time, SNPs were thinned to a minimum distance of 100 bp, and only SNPs with a minor allele frequency greater than 0.01 that had been sampled in all individuals were used, yielding 3,974 SNPs. Genotypes were pooled by accession collection site, and allele frequency was estimated per collection site before analysis; a connectivity network of the collection sites was generated using the minimum spanning method. The lagged principal scores were interpolated by the natural neighbor method in ArcGIS 10.3.1.FST (genetic differentiation among subpopulations), FIS (inbreeding coefficient), and D (Nei’s genetic diversity or expected heterozygosity) were calculated, adjusted for sample size following D  and longitude . STRUCTURE results still showed optimal K = 2 with individuals of singular group ancestry falling in Northwestern and Southern groups. However, DAPC indicated optimal K = 2, and the formerly distinct Northwestern group merged with the Pan-Africa group (data not shown). It is possible that denser geographic sampling of the entire species would maintain the Northwestern group and additionally reveal further substructure in other regions. For example, the sPCA suggested that there may be a distinct northeastern group despite sparse sampling from the northeast in the current dataset , a STRUCTURE analysis was conducted with USEPOPINFO  and O. longistaminata (African) and negligible ancestry from O. barthii (African) and O. glaberrima  and the ltivated .O. longistaminata group had low-level admixture with O. sativa  and also with O. barthii–O. glaberrima . Not all individuals showing interspecific admixture belonged to the Southern group. However, O. sativa ancestry of less than 4.5% was rare in the Northwestern Africa individuals  and Pan-Africa individuals . Ancestry from O. barthii–O. glaberrima was also rare in Northwestern Africa  and Pan-Africa  O. longistaminata groups.Notably, the results from STRUCTURE with the USEPOPINFO option indicated that all of the individuals in the Southern Africa O. longistaminata is more closely related to the Asian species O. sativa than the African species O. barthii and O. glaberrima. We report for the first time that there appear to be three main genetic subpopulations in the sampled O. longistaminata, with populations primarily structured by geographic distance. Moreover, we identified recent spontaneous interspecific hybrids of O. sativa and O. longistaminata in the IRRI genebank collection, which can be immediately useful for breeding. A further novel and notable contribution of this study was the observation of low-level admixture between O. sativa and O. longistaminata in Southern Africa only, which was likely the result of ancient hybridization upon the introduction of O. sativa to Madagascar approximately 1,000 years before the present. Additionally, we provided new nuclear and chloroplast markers for the species.Our study adds support to the current literature consensus that O. longistaminata, shared a more recent common ancestor with Asian domesticated rice, O. sativa, than the African O. glaberrima–O. barthii group had  are insensitive to photoperiod (O. longistaminata accessions collected in Ethiopia (8–12°N) were observed to flower during long days at Jinghong Rice Breeding Station in China .The mechanisms of genetic differentiation within toperiod . In the O. longistaminata groups in that all individuals had low-level estimated admixture with O. sativa  the low level of admixture with O. sativa in the Southern Africa O. longistaminata group was the result of ancient interspecific hybridizations and subsequent introgression. However, these hypotheses are not mutually exclusive: it is also possible that the Southern Africa O. longistaminata group could be the center of origin for this species and was also the first to subsequently hybridize with O. sativa.The Southern Africa group was unique among the three O. longistaminata population, but it would also be expected if the admixture was actually the result of interspecific hybridization  regardless of their geographic origin  than O. barthii–O. glaberrima  in the Southern Africa O. longistaminata group. Instead, we would expect many O. longistaminata individuals that are introgressed with O. sativa to also show a lower level of coancestry with O. barthii–O. glaberrima, representing alleles derived from a common ancestor.The proximity of the Southern Africa group to the outgroup species in the neighbor-joining tree could be consistent with the first hypothesis of greater similarity to the ancestral entified . Thus, tO. sativa admixture in O. longistaminata (ubiquitous in the Southern Africa group but rare in the Northwestern Africa and Pan-Africa groups) mirrors the historical timing and location of Asian domesticated rice cultivation in Africa. Intriguingly, recent archaeological and molecular genetic data indicate that O. sativa was introduced to southeastern Africa via Madagascar and the Comoros Islands by farmers who migrated from Southeast Asia across the Indian Ocean as early as ~1,000 years before present , then it would be reasonable to expect that similar ancient sympatric populations would have also produced interspecific progenies where they existed. Moreover, the ancient hybridization hypothesis is consistent with both the high genetic diversity and high inbreeding estimates observed for the Southern Africa O. longistaminata group because introgression of alleles from another species would be expected to increase genetic diversity, and O. sativa/O. longistaminata F1 hybrids are often self-compatible  than backcrosses to O. longistaminata. Consistent with the trends observed here, 1 interspecific hybrids from O. sativa fields where wild O. longistaminata grew sympatrically averaged 7.3% for O. longistaminata/O. sativa crosses and 2.6% for O. sativa/O. longistaminata crosses. Additionally, O. longistaminata/O. sativa F1 backcrossed to O. sativa varied among 11 cultivar backcross parents. Given that few controlled crosses between O. sativa and O. longistaminata have been attempted, it is possible that there are substantial differences in general and/or specific interspecific crossability within one or both parental species that could be used to advantage by plant breeders to facilitate introgression for rice improvement.The current study and at least three prior studies  have pro markers . Moreovein vitro . The curancestry . The preO. longistaminata into domesticated Asian rice may be desirable in breeding, the introgression of genes from domesticated Asian rice into wild populations of the African O. longistaminata may be considered undesirable genetic pollution  can be found in the article/ML: Data curation, Formal Analysis, Investigation, Visualization, Writing – original draft. LC: Supervision, Data curation, Writing – review & editing. SZ: Resources, Writing – review & editing, Investigation. FH: Resources, Writing – review & editing, Supervision. DT: Resources, Writing – review & editing. RH: Resources, Supervision, Writing – review & editing. ES: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing – original draft.


The precision and dependability of the detection results of this ic-ELISA were properly verified by HPLC in Rana catesbeianus samples. This indicated that the established ic-ELISA approach could be utilized to determine the FQs in Rana catesbeianus. In addition, this ic-ELISA, based on a broad-spectrum antibody, provides a technical reference and potential strategy for an immunoassay of hazard factors with similar structure.Fluoroquinolone (FQ) is a type of widely used antibiotic in agriculture and aquaculture, and exposure to low doses of FQs may result in the transfer of resistance between animal and human pathogens. Based on the optimization of the operating parameters, an indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) standard curve was constructed for the simultaneous detection of 13 FQs, including enrofloxacin (ENR), ciprofloxacin (CIP), sarafloxacin (SAR), ofloxacin (OFL), norfloxacin (NOR), pefloxacin mesylate (PM), pefloxacin (PEF), enoxacin (ENX), marbofloxacin (MAR), fleroxacin (FLE), lomefloxacin (LOM), danofloxacin (DAN), and difloxacin (DIF). The limit of detection (LOD, computed as IC Staphylococcus aureus and many others [Rana catesbeianus is a sort of popular edible frog, because of its tasty meat and abundant nutrition, with high protein, low fat, and low cholesterol [Rana catesbeianus has rendered it a significant economic breeding animal in China. However, under intensive high-density culture, Rana catesbeianus has a slow growth rate, low feed utilization rate, and weak resistance to bacteria and viruses. Rana catesbeianus is prone to bacterial or fungal diseases such as red-leg syndrome and chytridiomycosis [Rana catesbeianus, since field testing frequently involves the detection of a large number of samples.Fluoroquinolone (FQ) antibiotics are one of the most commonly used veterinary drugs, with a low cost and high broad-spectrum antibacterial activity against Gram-positive bacteria such as y others ,2,3. Howy others ,5,6. They others ,8,9. They others ,11. Ranalesterol ,13. Largomycosis ,15. On aomycosis ,17. It iBoth domestically and internationally, screening and confirmatory analytical procedures are frequently employed for the detection of veterinary medication residues ,19. Due Rana catesbeianus.The advantages of the enzyme-linked immunosorbent assay (ELISA) over other screening techniques include its high sensitivity, minimal instrumentation, and straightforward sample pretreatment ,30,31. T2CO3), sodium bicarbonate (NaHCO3), sodium chloride (NaCl), skimmed milk powder, acetonitrile, sodium hydroxide (NaOH), dichloromethane, n-hexane, phosphoric acid, and methanol were obtained from Aladdin Reagent Co., Ltd. . Goat anti-mouse HRP was obtained from Jackson Immunoresearch Laboratories . Chloramphenicol was obtained from Dr. Ehrenstorfer GmbH . Anti-OFL monoclonal antibody, ENR coating antigen was purchased from Landu Biotechnology Co., Ltd. . A phosphate buffer saline  was obtained by accurately weighing 9.00 g NaCl, 13.76 g Na2HPO4·12H2O, and 1.79 g NaH2PO4·2H2O and then adding ultra-pure water to 1000 mL. Phosphate buffer solution (PBST) was obtained from 995 mL PBS buffer  containing 10% Tween-20.ENR, CIP, SAR, OFL, NOR, PM, ENX, MAR, FLE, LOM, DAN, DIF, and nalidixic acid were obtained from Sigma-Aldrich . Malachite green, metronidazole, tetracycline, florfenicol, thiamphenicol, sulfamethazine, sulfamethoxazole, and Tween-20 were obtained from Macklin Biochemical Co., Ltd. . PEF, 3,3′,5,5′-Tetramethylbenzidine (TMB), dimethyl sulfoxide (DMSO), sodium carbonate . Rotary evaporator was obtained from BUCHI Corporation . Dry nitrogen blower was obtained from Qiuzuo Scientific Instrument Co., LTD. . Milli-Q water  was used in all the experiments.Ninety-six-well EIA/RIA plates were obtained from Corning Incorporated . Varioskan LUX multimode microplate reader was obtained from Thermo Fisher Scientific Co.  to measure the absorbance. XTerra MS C2SO4 (1.25 mol/L) halted the reaction in each well. The absorbance was eventually determined in a multimode microplate reader utilizing a 450 nm test wavelength [With the intention of progressing this supplied ic-ELISA, the critical experimental parametric settings, such as the concentration of coated antigen and dilution factor of antibody were modified. In order to determine the ideal ic-ELISA conditions, different concentrations of coated antigen  and a series of dilution coefficient of antibody  were selected by chessboard titration. The ic-ELISA approach could be described as follows: A 96-well plate with the coating antigen solution (100 µL/well) added was incubated at 4 °C overnight. The microwells were blocked through the addition of the blocking solution (200 µL/well) (0.5% skimmed milk powder solution) at 37 °C for 1 h, after being washed three times with PBST (0.01 mol/L PBS with 10% Tween-20). Following the cleaning of the microwells, FQs’ standard or sample solution (50 µL/well) and antibody in PBS (50 µL/well) were added to each well. The microwell plate was then incubated at 37 °C for 1 h. After washing, the 500-fold HRP-labeled secondary antibody solution (100 µL/well) was added to each well, and then the microwell plate was incubated at 37 °C for 30 min. Following cleaning again, TMB substrate solution (100 µL/well) was applied to microwells and then incubated for 15 min at 37 °C. The injection of 50 µL Hvelength .A0 is the absorbance value of well with 100 μL PBS solution added, iA is the absorbance value of the well with 50 μL antibody and 50 μL different doses of FQs’ solution added, and A is the absorbance value (at 450 nm) of the well with 50 μL antibody and 50 μL PBS solution added, respectively. An ic-ELISA approach was brought by utilizing the optimal working parameters and gradient concentration standards . The four-parameter equation was fitted with the average of three distinct experiments performed in triplicate, as reported in 50), as well as the limit of detection .Sensitivity and specificity are crucial parameters in evaluating ELISA techniques. To determine the inhibition rate (%), several FQs’ standard solution concentrations were utilized . The following is the formula for estimating the inhibition rate:Specificity was defined as the capacity of structurally or functionally related compounds to bind to the antibody, and cross-reactivity (CR) was calculated as:50 of ENR to IC50 of other antibiotics was utilized as the cross-reactivity.In the current investigation, CIP, SAR, OFL, NOR, PM, PEF, ENX, MAR, FLE, LOM, DAN, DIF, and nalidixic acid, which were similar to the structure of ENR, and additional 8 common veterinary antibiotics for aquatic products  were selected for specificity determination. The ratio of ICRana catesbeianus were acquired from nearby supermarkets in Hangzhou, Zhejiang, China. Prior to application, all samples were analyzed to ensure they were free of FQs. For edible animal tissues, such as porcine muscle, chicken muscle, fish, shrimp, porcine liver, chicken liver, and other organs, organic solvent extraction was typically utilized. The sample pretreatment method was modified according to the Ministry of China Agriculture Announcement No. 1025-8-2008 [Samples of commercial 5-8-2008 : 4.00 g Rana catesbeianus without ENR were spiked with various ENR concentrations  and concurrently assessed by HPLC and ic-ELISA. The Rana catesbeianus samples that contained PEF, DAN, MAR, FLE, OFL, NOR, CIP, LOM, and ENR (100 μg/kg each) were pitched with the purpose of determining the aggregate amount of FQs by the established ic-ELISA, with the aim of further evaluating the viability of the approach. HPLC was employed to verify the correctness of the results in samples by applying the Chinese National Standard GB 31656.3-2021 with a few modifications [18 column  was utilized. In this research, the Arc HPLC System with 2998 PDA Detector (ultraviolet detector) was utilized, the detection wavelength was 278 nm, the column temperature was 30 °C, the flow rate was 0.8 mL/min, and the injection volume was 10 μL The mobile phases were as follows: A: 0.3% phosphoric acid-5% acetonitrile aqueous solution (pH 4.00 ± 0.01 adjusted with triethylamine); B: methanol [It is vital to confirm the objectivity, accuracy, and feasibility of the established analysis approach, with the goal to demonstrate that it is capable of serving the purpose and needs of detection to evaluate the validity and precision of the supplied ic-ELISA. In this research, negative samples of ications . For themethanol . The det50 value with a suitable OD value (ranging from 0.8 to 1.2) is necessary to construct a sensitive ELISA assay. Massive errors may result from OD values that are either too high or too low, which affect the detection sensitivity of the ic-ELISA. In order to achieve the ideal outcomes, the following variables were optimized: the dilution coefficient of the antibody  and the amount of the coated antigen . The results are shown in max), which indicates the maximum binding between the antibody and coated antigen, was 1.46 when the coating antigen’s concentration was 0.05 μg/well and the dilution coefficient of the antibody was 1:32,000, which was beyond the range of the optimal OD value. The ODmax value was 0.70 when the dilution coefficient of the antibody was 1:256,000, and the lower OD value would cause the instrument reading to be inaccurate. The detection sensitivity (IC50) was 27.11, 23.83, 21.05, and 19.58 μg/L, when the coating antigen concentration was 0.05 μg/well and the dilution coefficient of the antibody was 1:32,000, 1:64,000, 1:128,000, and 1:256,000, respectively. When the coating antigen concentration was 0.10 μg/well, the half-maximal inhibitory concentration was 36.11, 30.80, 24.03, and 22.97 μg/L, when the dilution coefficient of the antibody was 1:32,000, 1:64,000, 1:128,000, and 1:256,000, respectively. When the coating antigen concentration was 0.20 μg/well, the half-maximal inhibitory concentration was 58.65, 49.24, 47.21, and 34.90 μg/L, when the dilution coefficient of the antibody was 1:64,000, 1:128,000, 1:256,000, and 1:512,000, respectively. The detection sensitivity was not as excellent as 0.05 μg/well when the coated antigen was 0.10 μg/well and 0.20 μg/well; hence, the study did not adopt these amounts. The experimental effect was optimum when the amount of the coated antigen was 0.05 μg/well and the dilution coefficient of the antibody was 1:128,000, since this resulted in an ODmax value of 0.91 and a half-maximal inhibitory concentration of 21.09 μg/L. The fitting curve tended to be smooth and a typical S-shaped curve. The ODmax value of the operating parameters had high sensitivity and was appropriate for ELISA detection.The lowest IC10 values and IC50 values were derived from the standard curves, which were employed to evaluate the detection limit and detection sensitivity of the generated ic-ELISA. Under the above-mentioned optimum operating parameters, the standard curves were obtained from various concentrations of FQs’ standard solution as the abscissa  and the inhibition rate as the ordinate. The standard inhibition curves of 13 FQs  in PBS by the ic-ELISA were fitted by Origin. The standard curve of ENR is displayed in 2 = 0.9995), and the standard curves of CIP, SAR, OFL, NOR, PM, PEF, ENX, MAR, FLE, LOM, DAN, and DIF are shown in 2 = 0.9984, 0.9964, 0.9986, 0.9923, 0.9994, 0.9991, 0.9990, 0.9976, 0.9949, 0.9981, 0.9974, 0.9978), all of which were typical S-shaped curves. The concentration of FQs in the aforementioned 13 fitting curves all remained stable when they were less than 0.01 μg/L or more than 10,000 μg/L. Utilizing this means, the detection limits (IC10) of ENR, CIP, SAR, OFL, NOR, PM, PEF, ENX, MAR, FLE, LOM, DAN, and DIF were 0.59, 0.97, 1.02, 1.15, 1.37, 1.38, 1.44, 1.66, 1.86, 2.01, 2.04, 2.71, and 3.61 μg/L, respectively, and the half-maximal inhibitory concentrations (IC50) were 19.23, 18.69, 21.55, 22.52, 21.84, 20.93, 21.96, 21.84, 21.69, 21.90, 22.35, 20.61, and 22.52 μg/L, respectively, as reported in The IC50 of ENR to the IC50 of other veterinary antibiotics. In this study, we sought to establish an ic-ELISA method capable of recognizing the majority of common FQ analogs. The IC50 values of FQs  with a similar structure to ENR and an additional eight common veterinary antibiotics  utilized in aquatic products were determined by an ic-ELISA based on an anti-OFL monoclonal antibody and an ENR coating antigen. The results presented in 50 of the above eight antibiotic veterinary drugs was greater than 15,000 μg/L, and the cross-reactivity (%) was less than 0.2%, indicating that the ic-ELISA had no obvious recognition ability for them. As a result, the established ic-ELISA approach has broad-spectrum specificity for the 13 FQs, with low cross-reactivity with nalidixic acid (<15%), and other antibiotic veterinary medications have no impact on the properties of the ic-ELISA (<0.2%).All immunoassays have the inherent property of specificity. The specificity of the established ic-ELISA was evaluated by calculating the ratio of the ICRana catesbeianus were pretreated with the modified Ministry of China Agriculture Announcement No. 1025-8-2008, the extracts were redissolved with PBS buffer. Following redissolving, the extracts were diluted with PBS by 2-fold, 4-fold, 6-fold, 8-fold, and 10-fold, and the matrix curve was generated. The matrix curve was compared with the standard curve obtained in the blank tissue. As shown in Rana catesbeianus extract sample significantly deviated from the standard curve, indicating that the matrix effect was still clearly visible; when the extract was diluted 10-fold, the matrix curve was basically consistent with the standard curve, and the matrix effect was negligible. As a consequence, this investigation utilized the 10-fold diluted Rana catesbeianus extract sample for subsequent ic-ELISA detection.In general, the recovery rate may be affected by the sample type, analyte solubility, sample preparation technique, and antibody effectiveness. In the actual analysis of food samples, compounds such as proteins and fats in complex food matrices may reduce the intensity of color development or interfere with the binding of antibodies and analytes, thus reducing the accuracy of the results. Therefore, the removal of matrix effects is primary in ELISA experiments. Typically, diluting sample extracts and preparing standard curves in blank tissue are two effective methods for minimizing matrix interference. After the sample extracts of Rana catesbeianus samples were employed by HPLC. Three various spiking concentrations of ENR  were set to confirm the viability of the established ELISA approach. The unspiked samples yielded no positive results throughout the spiking and recovery testing, which confirmed that the ELISA method had a low false positive rate and was more suitable for rapid detection in the actual field. Rana catesbeianus spiked with FQs exhibited an excellent correlation between the spiking degree and the observed concentration. The results of recovery are shown in Rana catesbeianus samples by the ic-ELISA were 93.87%, 90.39%, and 90.89%, respectively, while those by HPLC were 85.88%, 102.70%, and 92.18%, respectively. The coefficients of variation (CVs) of the ic-ELISA were 3.86%, 2.30%, and 5.11%, and those of HPLC were 7.01%, 3.18%, and 1.52%, respectively. The CVs of both approaches were less than 10%. The ic-ELISA outcomes were consistent with those of HPLC with a correlation coefficient (R2) of 0.9936. For the analysis of the ENR residues in Rana catesbeianus, the sample extraction technique and ic-ELISA were satisfactory.The recoveries of ENR in Rana catesbeianus samples by the ic-ELISA and HPLC to calculate the feasibility and practicality of the existing ic-ELISA. According to Rana catesbeianus evaluated by HPLC were 105.83, 118.30, 106.76, 106.18, 71.36, 96.93, 103.76, 94.37, and 94.11 μg/kg, respectively, and the CVs were 7.73%, 2.12%, 1.75%, 0.81%, 9.66%, 1.88%, 0.78%, 9.69%, and 2.87%, respectively. The overall contents of the aforementioned FQs were 897.60 μg/kg, and the CVs were all less than 10%, which was essentially consistent with the total concentration of the nine FQs measured by the ic-ELISA method (782.91 μg/kg) proposed in this paper. The CV of the above ic-ELISA was 8.53%, which proved that the ic-ELISA and HPLC had high accuracy. We found that the accuracy of both the ic-ELISA and HPLC results in determining the concentration of FQs in mixed samples was impacted by the competition amongst the FQs. The total concentration determined by HPLC was higher than the actual spiking concentration, and the total concentration determined by the ic-ELISA was lower than the actual spiking concentration, though still within the controllable range. These discoveries revealed that the ic-ELISA could be utilized to exactly and numerically identify the total amount of ENR, CIP, OFL, NOR, PM, PEF, MAR, FLE, LOM, and DAN in Rana catesbeianus samples.Moreover, since multiple FQs may be simultaneously present in the samples, we measured the concentrations of nine FQs  in commercial 50) was 19.23 μg/L and had significant cross-reactivity values (>85.38%) for the other 12 FQs . It was verified that the matrix effect was negligible with a 10-fold dilution of the optimized Rana catesbeianus extract samples. The outcomes of the proposed ic-ELISA were compared to those of HPLC, which showed a strong agreement between them (R2 = 0.9936). The total content of the nine FQs in Rana catesbeianus samples that were commercially accessible was effectively determined by utilizing the ic-ELISA. In conclusion, the created ic-ELISA could potentially be employed in a rapid, precise, and affordable manner to screen for the drug residues of the FQs in Rana catesbeianus.In summary, the ic-ELISA was established employing broad-spectrum-specific antibodies with comparable recognition ability for 13 FQs, including ENR, CIP, SAR, OFL, NOR, PM, PEF, ENX, MAR, FLE, LOM, DAN, and DIF. Concurrently, the approach had a cross-reactivity of less than 0.2% when detecting the other eight antibiotic veterinary drugs and was moderately sensitive to nalidixic acid. The optimized ic-ELISA demonstrated the LOD of 0.59 μg/L for ENR in PBS. The half-maximal inhibitory concentration (IC