Litsea cubeba L. essential oil (LCEO) can affect the growth of drug-resistance bacteria. However, research on stress response of drug-resistant A. baumannii under sub-lethal LCEO concentrations had been limited so far. Therefore, transcriptomic analysis of A. baumannii under 1/2 minimum inhibitory concentration  of LCEO was performed. Results of transcriptomic analysis showed that 320/352 genes were significantly up/down-regulated, respectively, in LCEO-treated A. baumannii. Both up and down-regulated genes were significantly enriched in three GO terms , which indicated that the redox state of A. baumannii was significantly affected by LCEO. LCEO may also inhibit aerobic respiration, synthesis of ketone bodies and the metabolism of some amino acids while, meanwhile, promoting fatty acid degradation of A. baumannii according to Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. The permeability and the stress of cell membrane of A. baumannii were significantly affected by LCEO. After crystal violet dyeing, the biofilm formation of A. baumannii was promoted/inhibited by extremely low/relatively high concentration of LCEO, respectively. LCEO and chloramphenicol have synergistic growth inhibitory effect against A. baumannii according to the Fractional Inhibitory Concentration Index (FICI) value = 0.375. Our results indicate that the growth of A. baumannii was inhibited by LCEO, and give insights into the stress response of A. baumannii under sub-lethal concentrations of LCEO. These results provided evidence that A. baumannii was inhibited by LCEO, and expanded knowledges of stress response of A. baumannii under sub-lethal concentration of LCEO. Lauraceae is a Lauraceae plant and widely grown in East Asia [Litsea cubeba L. gives off a smell that is similar to ginger [L. cubeba has therapeutic effects on skin, lung and breast infections [L. cubeba essential oil (LCEO) have gradually increased in recent years. Ho’s results showed that limonene, citronellal, and citronellol were the main components of LCEO in the stem of L. cubeba. The content of citral, 1,8-cineole was higher in the parts where the content of water is higher, such as flowers, twig and leaves [LC is a ast Asia . The whoo ginger . Accordifections ,4. Resead leaves . The frud leaves . In the d leaves . The antd leaves ,8, anticd leaves  and antid leaves  of LCEO d leaves ,11,12,13A. baumannii is a successful pathogen which often causes infections of humans and aquatic animals [ animals . It usua animals ,16.A. baumannii, as this pathogen has multi drug-resistant properties [Cymbopogon flexuosus) essential oil (LEO) and citral which have the ability to inhibit and kill multi drug-resistant (MDR) A. baumannii [A. baumannii has not been reported yet. Therefore, the elucidation of the mechanisms by which LCEO impacts A. baumannii would be helpful for the development and clinical utilization of LCEO.However, few antibiotics can cure infections and prevent outbreaks caused by operties . To addraumannii . The maiStaphylococcus aureus (S. aureus) were significantly affected by LCEO [A. baumannii under 1/2 minimum inhibitory concentration (MIC) of LCEO using transcriptomics.In our previous work, through transcriptomics, we found that toxin production and a variety of metabolic pathways of  by LCEO . The objLCEO was provided by Jiangxi Hongwei Natural Perfume Oil Co. LTD (China). As shown in A. baumannii  were provided by the First Affiliated Hospital of Guangxi Medical University, China. These three strains were all harboring arm-A (β-lactam resistance genes), sul2 (sulfa resistance genes), tetB (tetracycline resistance genes). A. baumannii 17 also harbors aac6′-1b (aminoglycoside resistance genes). In addition, A. baumannii 17 has a strong virulence: when 2 × 108 colony-forming units (CFU)/mL of this fresh strain was intraperitoneally injected at a dosage of 0.1 mL/10 g body weight for a mouse, the mortality rate was 100% within 12 hours (12 of 12 mice).Three strains of For each strains, 0.5 mL of bacteria was taken from the cryotube and then added to a tube with 3.5 mL tryptic soy broth (TSB) for 24 h shaking at 37 ℃, at 300 RPM. The culture medium was inoculated on tryptone soy agar (TSA) plates using an inoculation ring. After these plates were cultured for 24 h at 37 °C, a single colony was selected for inoculation to TSB culture for 6 h at 37 °C at 300 RPM shaking before subsequent trials.A. baumannii.Serial-dilution culture method was performed to obtain MIC values for different antibiotics , tween-80 and LCEO on A. baumannii 17 TSB suspensions (104 CFU/mL) respectively in a 96-well microtiter plate. After stationary culture at 37 °C for 24 h, MIC values were judged by no visible growth of A. baumannii of broth in wells [Every drug solution was two-fold diluted in TSB and equally mixed with 100 μL in wells . This teA. baumannii 17. Bacterial TSB suspensions (104 CFU/mL) were transferred into tubes, followed by tween 80 and LCEO. The final concentration of tween 80, LCEO (1/2 MIC) and LCEO (1 MIC) in corresponding groups was 1.08, 0.54 and 1.08 mg/mL. After 300 RPM shaking at 37 °C for 24 h, the OD600 was determined at intervals by a spectrophotometer. Before each detection, zero was set using a same batch of sterile TSB. This test was repeated three times.A growth curve assay was performed to investigate the growth inhibitory effect of LCEO on A. baumannii 17 culture was added with tween 80 and LCEO. The final concentration of tween 80, LCEO (1/2 MIC) and LCEO (1 MIC) in the corresponding group was 1.08 mg/mL, 0.54 and 1.08 mg/mL. Next, all samples were cultured for another 8 h. At intervals, 100 μL culture in each sample was taken, centrifuged and resuspended in 100 μL sterile phosphate-buffered saline (PBS). Subsequently, 10-fold serially diluted suspensions were plated on TSA plates and incubated 24 h at 37 °C. Colonies were counted and the CFUs/mL was calculated. This experiment was performed with at least three biological replicates.After 12 h culture at 37 °C with 300 RPM shaking, A. baumannii 17 was inoculated into fresh TSB then incubated at 37 ℃ with 250 RPM shaking. When the opioid addiction (OD) value at 600 nm of culture reached 0.8 (1 × 106 CFU/mL), ½ MIC (0.54 mg/mL) of LCEO was set as stimulation treatment, thus bacteria from the aliquot were suspended in 10 mL TSB with ½ MIC LCEO, and the bacterial from another aliquot were suspended in 10 mL TSB as control.For RNA extraction, culture of 600nm value of the culture reached 0.8 (1 × 106 CFU/mL), ½ MIC of LCEO was added in the culture, and this was the LCEO treatment group. At the same time, a control group was set without LECO. Each group had three independent samples. After 30 min incubation at 37 °C, bacterial cells were collected for RNA extraction.When the ODBy using the Total RNA Isolation System (Promega), total RNA of six cell samples was extracted. The extracted RNAs quality was checked using Agilent 2100 Bioanalyzer. Library construction and Illumina sequencing was undertaken by Novogene China.A. baumannii ATCC 17978  for data analysis. Only genes with an adjusted p-value  <  0.05 and |fold change|  >  1.5 were regarded as differentially expressed genes (DEGs).All RNA-seq reads were aligned to the genome of A. baumannii 17 triggered by LCEO, an ultraviolet (UV) light spectrophotometer  was used [A. baumannii 17  was washed with sterile water twice and then resuspended by sterile water to the same volume. The resuspended A. baumanni from the previous step was divided into 16 test tubes (4 groups and 4 duplicates). The four groups were: Control, 1/8 MIC (0.135 mg/mL of LCEO), 1/4 MIC (0.27 mg/mL of LCEO) and 1/2 MIC (0.54 mg/mL of LCEO). These 16 test tubes were incubated at 37 °C with 250 rpm shaking for 2 h. Afterwards, 16 test tubes were subjected to centrifugation under 5500 rpm for 15 min, and then the supernatant was taken for absorbance detection of OD260nm (DNA absorbance) and OD280nm (protein absorbance). Because citral (the main active component of LCEO) absorbs UV light, three control tubes with the same concentration of LCEO were set for zeroing the OD value before testing, respectively.To investigate the leakages of intracellular DNA and proteins of was used . A freshA. baumannii TSB suspensions (104 CFU/mL) respectively in a 96-well microtiter plate. After incubation at 37 °C for 36 h, the culture was removed and 200 μL methanol was added to each well for 15 min at room temperature. After that, the methanol supernatant was removed, and the plates were dried at room temperature. Then, 200 μL of 0.1% crystal violet solution was added to the wells for 15 min at room temperature. After that, the crystal violet was removed, the wells were washed gently with distilled water until the distilled water was clear and transparent, and 200 μL 33% acetic acid was added to each well. Finally, the OD450nm value of plates were read [The method applied was a slight modification of the method used in a previous work . LCEO  was used to evaluate the synergistic growth inhibitory effect of LCEO with other antibiotic . FICI = FICA + FICB = C nism: >4 ,24. ThisTo validate the RNA-seq results, 8 DEGs were selected for quantitative real-time PCR (RT-PCR) assay. The selective criteria of these 8 DEGs were: (1) in different Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways; (2) the |fold change| > 1.5; (3) 4 DEGs were up-regulated and the remaining 4 DEGs were down-regulated. These experiments were performed in triplicate.® III RT SuperMix for qPCR (+gDNA wiper) (Vazyme) was used for reverse transcription. Primers were designed by Primer-BLAST (NCBI) and provided by Vazyme (® 480 (Roche). This test was repeated three times.Total RNA was extracted from the bacteria using Bacteria RNA Plus Reagent (Vazyme) and RNA Isolater Total RNA Extraction Reagent (Vazyme). HiScripty Vazyme . The ampp < 0.05 were considered to be statistically significant.The statistical analysis of results was performed using one-way analysis of variance (ANOVA) followed by post hoc analysis with Tukey’s test using SPSS16 software. Values of A. baumannii was >108 mg/mL, which may indicate that the tween 80 has no negative effect on the growth of A. baumannii.All strains had obvious drug-resistant phenotype to some common antibiotics: amoxicillin, amikacin, sulfamonomethoxine, azithromycin . HoweverA. baumannii 17 for follow-up studies because the A. baumannii 17 harbored more drug resistance gene than other 2 strains, and A. baumannii 17 also had strong virulence phenotypes as mentioned above.We selected A. baumannii 17 was inhibited by LCEO. However, tween 80 had no such effect. Similar results were found in the time kill assay .RNA-Seq generated total 10,597,964 to 20,954,540 clean reads from LCEO-treated (AB_LCEO_treated) and control cDNA libraries, respectively . These cAs the gene expression profile of samples in the same group were highly similar, further analysis can be performed. Per Kilobase of transcript per Million mapped reads  analysis showed that 4320 total genes were expressed in LCEO-treated and non-treated groups.https://bigd.big.ac.cn/gsa (accessed on 18 August 2020).The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive  in BIG Data Center (Nucleic Acids Res 2019), Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, under accession numbers CRA003099 that is accessible at To understand and explain the results of RNA-seq, the differential expression patterns of the transcripts were analyzed between the LCEO-treated and control group. 672 genes (320 up and 352 down-regulated) were identified by differential expression analysis . Among tAccording to the gene ID and gene name of the NCBI database, 11 up-regulated genes encode 4-carboxymuconolactone decarboxylase; NAD(P)-dependent alcohol dehydrogenase; alkane 1-monooxygenase; AraC family transcriptional regulator; hypothetical protein; N/A; 3-oxoacid CoA-transferase subunit A; hypothetical protein; α/β fold hydrolase; L-lactate permease; chromate transporter. The 9 down-regulated genes encode ferredoxin reductase; acyl-CoA desaturase; VOC family protein; 4-hydroxyphenylpyruvate dioxygenase; maleylacetoacetate isomerase; amino acid permease, fumarylacetoacetase; 1,2-phenylacetyl-CoA epoxidase subunit B; SDR family oxidoreductase.Gene Ontology (GO) is an international standard classification system of gene function. By GO enrichment analysis of mRNA, functions of targeted mRNA can be obtained.All 672 DEGs underwent GO enrichment analysis; 848, 183 and 529 specific GO terms in biological process, cellular component and molecular function were reported, as shown in Ten GO terms were enriched in biological process; including oxidation-reduction process; anion transport; organic anion transport; organic acid transport; carboxylic acid transport; anion transmembrane transport; organic acid transmembrane transport; amino acid transport; ion transmembrane transport; single-organism metabolic process.Ten GO terms were enriched in cellular components; including membrane-enclosed lumen; organelle lumen; intracellular organelle lumen; nuclear part; nuclear lumen; proton-transporting two-sector ATPase complex, catalytic domain; intracellular organelle part; THO complex; chromosome; dynein complex.In the category of molecular function, 10 GO terms  were significantly enriched.A. baumannii 17.Within the 30 significantly enriched GO terms, there were six terms containing the keyword “membrane”. Combined with a recent report , LCEO haA. baumannii 17 comprehensively. We wanted to know which pathways that these 127 DEGs were involved in. Therefore, a customized KEGG enrichment analysis was performed individually based on the 127 DEGs.Previous studies have shown that LCEO has a strong antioxidant activity  ,28. It wKEGG is a database integrating genome, chemical and system functional information. KEGG pathway enrichment analysis can not only find out the pathways involved in target genes or proteins, but also analyze the significant differences of these pathways.To further identify significant changes in the biochemical pathways during LCEO stimulation, the 672 DEGs were further mapped using the KEGG database . In FiguAlso, the 127 DEGs were mapped to the KEGG database  to annotated genes in the database (background number) was not high. These suggested that the biological redox processes of In the KEGG enrichment sections below, only the results of the total 672 DEGs were discussed in detail.p = 0.0780). TCA cycle is an important aerobic pathway for the final oxidization of carbohydrates, fatty acids, proteins and other organics [A. baumannii 17, all the enriched genes were significantly down-regulated (A. baumannii 17 was inhibited by LCEO with strong reducibility.It was necessary to discuss the citrate cycle (TCA cycle) pathway first, although it was not significantly enriched  were significantly downregulated as compared with the control  were significantly downregulated in comparison with the control  ,40,41. AA. baumannii 17 were down-regulated compared with that of the control. Also, LCEO has been shown to inhibit the hexose monophophate pathway of S. aureus [A. baumannii 17.Pyruvate dehydrogenase complex (PDHC) is a mitochondrial multienzyme complex composed and it holds an important position in pyruvate metabolism pathway. PDHC is A group of rate-limiting enzymes that catalyze irreversible oxidative decarboxylation of pyruvate into acetyl-coA ,43,44. P. aureus . These rA. baumannii to some extent.In the absence of oxygen, organisms derive energy from the glycolysis which is a preparatory pathway for aerobic oxidation of glucose in most organisms. Gluconeogenesis, in turn, is a synthesis pathway of glucose from non-carbohydrate precursors . The genOxidative phosphorylation is defined as an electron transfer chain driven by substrate oxidation that is coupled to the synthesis of ATP through an electrochemical transmembrane gradient in cytoplasm . As showWe noticed that in A. baumannii 17 treated with LCEO.Acetyl-CoA, produced by the β-oxidation of fatty acids and other metabolisms, has another metabolic pathway. Finally, acetoacetic acid, -hydroxybutyric acid and acetone are formed. These three products are collectively called ketone bodies . For bacA. baumannii 17 was increased by LCEO.The oxidative decomposition (degradation) of fatty acids is one of the important pathways for cells to obtain energy . The fatA. baumannii 17 was slowed by LCEO. The degradation of fatty acid was enhanced while the synthesis of fatty acid was retarded, indicating that the cells were utilizing fatty acids to obtain energy.In the fatty acid biosynthesis pathway, hexadecanoyl-CoA is biosynthesized by acetyl-CoA by a series of reactions . In FiguS. aureus; 2: just a small proportion of genes were down-regulated in the fatty acid degradation pathway and up-regulated in the fatty acid biosynthesis pathway.Of course, some genes were down-regulated in the fatty acid degradation pathway; and some genes were up-regulated in the fatty acid biosynthesis pathway. However, we still believe that the overall trend was enhanced degradation and retarded biosynthesis of fatty acid. Because 1: in our previous work , LCEO caA. baumannii 17 increased the activity of fatty acid degradation to obtain energy.From this part, we assumed that LCEO suppressed the aerobic respiration and degradation of amino acid. At the same time, the concentration of ketone bodies used for energy storage was also decreased. In order to survive, S. aureus [S. aureus is a Gram-positive bacteria and A. baumannii 17 is a Gram-negative bacteria, which again showed that LCEO has spectral antimicrobial activity [As shown in . aureus , and ouractivity ,54,55.EnvZ (not shown in green frame as the |fold change| = 1.30) and OmpR suggests that the cells were stimulated by osmotic pressure (downshift of K+). This was probably due to damage to the cell membrane by the LCEO.As shown in A. baumannii 17 is increased as for the cell membrane and two-component system reparation.The importance and location of histidine kinases have been described above. Therefore, it is not difficult to speculate that histidine is particularly important in the repair process when the cell membrane is damaged. As shown in A. baumannii [A. baumannii 17 was damaged by the LCEO, so that the bacteria required more peptidoglycan to do the repair work.In bacteria, peptidoglycan is one of the building blocks of the cell wall . Here, aaumannii . TherefoBorrelia burgdorferi and Candida spp. [A. baumannii 17. As shown in A. baumannii 17 was significantly promoted by the extremely low concentration of LCEO (1/4096 to 1/512 MIC). This result was similar to that of Junyan’s report: low level of ampicillin stimulation can accelerate the biofilm formation of S. aureus [A. baumannii 17 was significantly reduced by the relatively high concentrations of LCEO (1/64 to 1/2 MIC). Compared to the planktonic bacteria, bacteria in biofilm are more resistant to antibiotics or reactive molecules produced by the host immune system [Studies have shown that LCEO affected the biofilm of ida spp. ,56. Ther. aureus . Howevere system . Thus, aA. baumannii 17, and no antagonistic effect was recorded. This suggested that LCEO has certain potential research value on pathogenic microbial infection.Therefore, the FICI value was used to evaluate the synergistic growth inhibitory effect of LCEO with antibiotics. Here, we randomly selected some antibiotics  for testing the synergistic growth inhibitory effect with LCEO. As shown in The qRT-PCR results of eight DEGs were very similar to those of the transcriptome analysis , indicatA. baumannii under low concentration of LCEO were reported in the present work; 320/352 DEGs were significantly up/down-regulated in LCEO-treated A. baumannii; 127 DEGs were significantly enriched in three GO terms , which indicated that the cell redox state was widely affected by 1/2 MIC of LCEO. LCEO may also inhibit the aerobic respiration, synthesis of ketone bodies and metabolism of some amino acids as well as promote fatty acid degradation of A. baumannii. Therefore, we hypothesized that LCEO, due to its inherent reductivity, extensively affected the redox reaction of cells, thus causing metabolic disorders of bacteria then exerting bacteriostatic effects. The integrity of the cell membrane of A. baumannii was damaged by sub-inhibitory concentration of LCEO. We also founded that the biofilm formation of A. baumannii was promoted/inhibited by extremely low/relatively high concentration of LCEO. LCEO and chloramphenicol have a synergistic growth inhibitory effect against A. baumannii. These results provided evidence that LCEO affects A. baumannii in multiple ways (multiple targets), and expand the knowledge of the stress response of A. baumannii under low concentration of LCEO.Evidence of transcriptomic assays for the stress response of


Arbitrary , gene-targeted  and co-dominant sequence specific (40 SSR) markers were used individually, or in combinations, to examine the genetic variability within and among 70 selected Indian mango genotypes based on geographic origin  and fruit status . The highest genetic variability was demonstrated by the East Indian populations, followed by those from South India, West India, and North India, when measured in terms of Na, Ne, H, I, PB%, Ht and Hs. Interestingly, the local genotypes of Odisha, which forms a part of East Indian populations, showed the highest diversity compared to hybrid or selection groups, suggesting that the indigenous genotypes hold a greater potential for exploiting the unique and favourable alleles. The maximum genetic variability was detected in geographical/fruit status populations with SSRs , followed by CBDPs and SCoTs, reflecting their preeminence for examining the level of genetic polymorphism and diversity. Outcome of AMOVA based analyses as well as low-to-moderate coefficient of genetic differentiation (Gst) and high gene flow (Nm) indicated a greater amount of intra-population genetic variation compared to heterogeneity at inter-population level. Information generated through this investigation could facilitate conservation and further exploitation of mango germplasm including genetic improvement through breeding. Mangifera indica L., Family: Anacardiaceae, Order: Sapindales), is one the most important fruit crops, and referred to as ‘King of fruits’ in the tropical world1. Endowed with the largest mango gene pool around the globe5, with a high degree of diversity, India is considered to be the centre of origin of mango from where it is believed to have spread progressively to tropical and subtropical provinces of the world. India's eco-geographic diversity has been responsible for a good number of fruit crop type; no wonder that India ranks second in global fruits production, next to China6. The leading mango producing States of India are Uttar Pradesh (23.06%), Andhra Pradesh (16.06%), Karnataka (9.29%), Telengana (8.54%), Bihar (7.51%), Gujarat (6.30%), Tamil Nadu (5.87%), West Bengal (4.24%) and Odisha (4.14%)7. The wild as well as cultivated forms of mangoes  in India exhibit a wide diversity of fruit forms, flavour, size and taste8.Unfortunately, at present, only a meagre number of about 20 landraces are commercially cultivated, majority of them being restricted to specific regions9.Mango  owing to uncontrolled natural outbreeding depression, if any15. The application of reliable and rapid DNA-based diagnostic techniques to discriminate/relate established genotypes and unexplored/under-explored local ones (landraces) is rewarding to improve the efficacy of genotype management for use in breeding and conservation of fruit tree species for production of certified plant material with superior fruit quality16. Besides, documentation in form of molecular atlas, as DNA fingerprints, generated for elite mango genotypes and local landraces hold significance in context of ascertaining genetic authenticity (trueness-to-type) of the conserved germplasm.Basal to species diversity is the genetic diversity, which is considered as a key precursor in studying a species, because the magnitude and range of heterogeneity in populations of such species influence its evolutionary potential17. Population diversity is widely used in conservation biology to quantify relationships and differences among populations18.Information on the extent and structure of genetic variation in germplasm collections is essential for the effective conservation, efficient management and prospective utilization of biodiversity in any crop species. In addition, knowledge of the genetic and population diversity of germplasm collections serves a solid foundation for crop improvement. It is essential to first define the population diversity within the germplasm to avoid spurious associations while performing association mapping studies20. Conservation of genetic diversity is extremely vital for the long-term subsistence of a plant species, because loss of genetic variability within populations may significantly decrease adaptability to environmental alteration and increase of disappearance risk21. Understanding the relative significance of specific processes, such as inbreeding, gene flow, genetic drift, and selection that structure diversity within and among populations can deliver means to evaluate future risk of erosion of diversity and to design effective conservation approaches for rare taxa22. Disappearance of a single population would remove any distinctive biological traits that it retains and might eventually lead to varietal elimination21. George et al.23 suggested that examining the extent of genetic diversity within and among populations can help in understanding evolutionary contrivances, such as genetic drift and can serve as an indicator of the extent of gene flow and population divergence.Determination of the extent of genetic diversity in fruit crop populations is essential to guide strategies for their conservation and sustainable utilization for genetic improvement. Estimating and understanding of the levels of variability existing within and between the populations do not only facilitate formulation of appropriate conservation strategies, as it reflects the status and survival potential of populations, but also it helps to resolve ecological, taxonomic, phylogenetic and demographic questions of great relevance25. Different PCR-based DNA marker techniques are available for studying plant population genetics. These may be classified as arbitrarily amplified DNA markers, DNA sequence based markers and gene targeted functional markers. Molecular methods differ from each other with respect to important features such as genomic abundance, level of polymorphism detected, locus specificity, reproducibility, technical requirements and cost26. Assessment of genetic diversity within and among population have been reported in horticultural crops, such as wild apricot27, bottle gourd28, apple29 and in other plants, including Christmas orchids31, mungbean32, Pinus nigra33,  Populus wulianensis34 etc. to understand spatial and temporal differences between populations. Yet, studies on Indian mangoes are limited to the cultivars of Andhra Pradesh (a State of India) and use of SSR markers alone35. However, no studies have looked at population diversity in a diverse collection of mangoes in India using a range of DNA fingerprinting techniques such as RAPD, ISSR, DAMD, SCoT, CBDP and SSR markers, neither individually nor cumulatively. Comparative studies of different molecular techniques for measuring population diversity have already been performed in apricot36, Ocimum37, bamboo38, mungbean32, etc. However, only a few reports exist pertaining to multiple marker comparison for genetic diversity in mangoes, particularly those of Thailand, Vietnam, and China39 and of Gir forest region of India40. The present investigation is a maiden effort to assess genetic variability within and among populations with geographic affiliation  and those based on fruit status , encompassing 70 Indian mango genotypes, employing individual and combination of arbitrary , gene-targeted  and sequence specific marker systems (SSR). Our work was aimed at following objectives: i) to compare the efficacy of various PCR-based markers  for analysing genetic diversity among and within populations of Indian mangoes from various geographical locations and fruit status background. ii) to investigate population differentiation based on genetic diversity parameters for further use in population and conservation genetics. iii) to estimate the gene flow among populations.The use of DNA-based markers offers a potential strategy for genetic analysis at population level. DNA markers are not influenced by environmental conditions and, therefore, can be used to help describe patterns of genetic variation among plant populationsOf a total of 80 RAPD primers subject to initial screening, 65 primers yielded clear and reproducible patterns of bands ranging in size from 100 to 3000 bp with an average of 15.91 bands per primer. Twenty-five different ISSR primers yielded clear and bright bands of sizes ranging 100–2500 bp, with an average of 18.04 bands per primer , West India (WI), North India (NI), and South India (SI) Table . AdditioCo-dominant SSR markers were able to detect highest level of variability, which was demonstrated by the highest mean values of Na (1.76), Ne (1.48), H (0.28), I (0.41) and PB% (76.1), Ht 0.31) and Hs (0.28) compared to other markers. On average, CBDP and SCoT markers closely followed SSR in terms of Na , Ne (1.42), H (0.25), I , PB% , Ht  and Hs (0.25). The RAPD, ISSR and DAMD markers exhibited a comparatively lower mean values for genetic diversity indices as compared to the other markers. Interestingly, Na was the highest (1.68) for RAPD markers among arbitrary markers while it was at par for ISSR and DAMD (1.66).The polymorphic band percentage (PB%) was also higher for RAPD (68.03%) compared to ISSR (66.33%) and DAMD (65.69%). Values for mean effective number of alleles (Ne), total genetic diversity (Ht) and genetic diversity within population (Hs) found to be more for ISSR  followed by RAPD  and DAMD  respectively, while other two crucial genetic diversity parameters, such as Nei’s genetic diversity (H) and mean Shannon’s information index (I) was unvaryingly higher for ISSR and RAPD  compared to DAMD . Genetic structure of geographical/fruit status populations was also measured using combination of various arbitrary markers (RAPD + ISSR + DAMD) and gene targeted markers (SCoT + CBDP); the latter had superior entries for genetic diversity parameters,  in comparison with the former . Hence, the gene targeted markers were more efficient than arbitrary markers for evaluating genetic diversity of different populations. The different diversity parameters indicated that Indian mango germplasm hold a considerably high level of genetic diversity. Among all the markers tested with four different populations, the estimator of population substructure or coefficient of genetic differentiation (Gst) value were more with SSR and DAMD (0.156 and 0.150) indicating that about 15–16% of the total genetic variability resided among the population. These Gst values were associated harmoniously with less levels of gene flow (Nm), of 2.714 and 2.836 with SSR and DAMD, respectively compared to other markers. These Gst and Nm were also varied for RAPD , ISSR , SCoT  and CBDP  markers respectively  exhibited the maximum variability. The extent of genetic variability level for East India population was measured in respect of several parameters, such as observed number of alleles (Na), effective number of alleles (Ne), Nei’s genetic diversity (h), Shannon’s information index (I) and percent polymorphism (PB %). Data recorded varied with RAPD , ISSR , for DAMD , CBDP , SSR , RAPD + ISSR + DAMD , and SCoT + CBDP , respectively , Ne , H , I  and PB%  by RAPD, ISSR, DAMD, CBDP and SSR markers correspondingly among the genotypes of local population (L). The exception was SCoT marker which uncovered highest Na (1.86), Ne (1.46), H (0.28), I (0.42) and PB% (85.92%) among the genotypes of hybrid population (H) (Table The population of Selection genotypes (S) exhibited higher variability than that of hybrids (H)  as noticed by ISSR markers. The SSR and CBDP markers experienced a similar trend in terms of variability quantities for selection and hybrid populations. Interestingly, CBDP and SSR markers had higher mean values of Na  across all the populations compared to SCoT and RAPD (1.80), ISSR (1.78) and DAMD (1.74). Average values for other parameters like Ne (1.51), H (0.29), I (0.45), PB% (86.95), Ht (0.32) and Hs (0.30) were highest for SSR. The gene targeted markers CBDP and SCoT had Ne , H , I , PB% , Ht  and Hs , respectively. Considering different arbitrary markers, the mean effective number of alleles (Ne), Nei’s genetic diversity (H), Shannon’s information index (I) and total genetic diversity (Ht) was found to be maximum for ISSR , followed by RAPD  and DAMD , respectively.Higher PB% values were found in RAPD (80.48) followed by ISSR (77.78) and DAMD (74.51), while another critical genetic diversity parameter, i.e. Hs (genetic diversity within population) was equally higher for ISSR and RAPD  compared to DAMD (0.22). Gene targeted markers had higher levels of diversity in terms of average Na (1.83), Ne (1.45), H (0.27), I (0.41), PB% (82.78), Ht (0.28) and Hs (0.27) than those from arbitrary ones Na (1.79), Ne (1.41), H (0.25), I (0.38), PB% (78.85), Ht (0.27) and Hs (0.25). Gst value was the highest in RAPD (0.115) followed by SSR (0.07), DAMD (0.065), ISSR (0.061), CBDP (0.054) and SCoT (0.053). This indicated the superior ability of the RAPD markers to evaluate the variation among local, hybrid and selection genotypes, whilst the trend for gene flow (Nm) among the populations was the reverse, being the highest for SCoT (8.91) followed by CBDP (8.71), ISSR (7.65), DAMD (7.19), SSR (6.56) and RAPD (3.82).PT—0.038 and 0.098 ) . RAPD data showed 9% variation partitioned among geographic populations, whereas 91% variation was existent within the geographic populations Fig. . Similar ) Figs. .Figure 1PT values for RAPD, ISSR, DAMD, SCoT, CBDP and SSR they were found to be 0.084, 0.052, 0.042, 0.027, 0.028 and 0.039, respectively , ISSRs (95%), DAMDs (96%), SCoTs (97%), CBDPs (97%) and SSRs (96%) while among population variance components were very low i.e. 11% (RAPD), 5% (ISSR), 4% , 3% . Examining the overall Φely Fig. . AMOVA bely Fig. . Cumulately Fig. .vs SI—0.91; NI vs EI—0.90), while genotypes from WI [WI vs EI (0.83)/SI (0.88)/NI (0.90)] are slightly distinct from the three populations. The same pattern of clustering was also manifested with SCoT + CBDP, but the identity values were more pronounced .To illustrate further the phylogenetic relationship between four different geographic populations, the Neighbor-joining method was employed to construct the phylogenetic tree (NJ dendrogram) of SSR, cumulative RAPD + ISSR + DAMD and SCoT + CBDP markers (Supplementary Table vs S (0.94) / H (0.94)] was distinct from the two populations. The same pattern of clustering was also manifested with SSR but the identity values were more pronounced (L vs S—0.92 / H—0.92). For RAPD + ISSR + DAMD markers, ‘H’ depicted maximum genetic identity with both populations ‘S’ and ‘L’ (0.96). The NJ dendrogram depicted that ‘H’ and ‘S’ populations were grouped together, while the farthest genetic identity was 0.91 between ‘L’ and ‘S’ populations.Similarly, Neighbor-joining method was employed to construct the phylogenetic tree (NJ dendrogram) among three fruit status populations  using SSR, cumulative RAPD + ISSR + DAMD and SCoT + CBDP markers , ISSR , SCoT , DAMD , CBDP  and SSR . The private alleles can be used as molecular signatures (ID marks) in fingerprinting studies and such data could be used in assessment of genetic purity of the populations. Most of the local populations encompass indigenous genotypes of Odisha State and these results demonstrate the potential of local germplasm for exploiting the unique and favourable alleles present therein for mango germplasm improvement programmes.Hence, such information will aid the selection of cultivars for germplasm conservation and implementation in modern-day mango breeding, by providing information on diverse genetic backgrounds in native and local genotypes.Among the mango germplasm collected from four different geographical regions, the highest genetic diversity was observed in East Indian population (EI), followed by that of South India (SI) > West India (WI) > North India (NI), suggesting that mango genotypes from the eastern and southern parts of India possess relatively higher genetic variation and has a greater capability to acclimatize and evolve than the other populations. The observed number of alleles were higher than that effective in all populations. Similar kind of observations were reported in other tree species like Apricot47. The selection of a particular type of molecular marker is important and critically depends on the intended use48. Sivaprakash et al.49 suggested that the ability of a marker system to resolve genetic variation may be directly related to the degree of polymorphism. Polymorphism in a given population is often due to the existence of genetic variants represented by the number of alleles at a locus and their frequency of distribution in a population. Comparison of RAPD, ISSR, DAMD, SSR, SCoT and CBDP analysis in respect of diversity parameters showed a substantial level of genetic variation and broad genetic base in studied mango populations. Genetic variability among Indian mangoes selected for geographical and fruit status population analysis in the present study, as estimated by parameters such as Na, Ne, h, I, PB%, Ht and Hs, were found to be the highest with SSRs, followed by gene targeted markers like CBDPs and SCoTs, thus reflecting the preeminence of the former one at levels of genetic The polymorphic band percentage (PB%) was also established to be higher in both geographical and fruit status populations for RAPD  compared to ISSR  and DAMD . The reason for higher genetic diversity revealed by SSR markers may be attributable to their multi-allelic nature, high polymorphism and information content as well as unique mechanism responsible for generating SSR allelic diversity by replication slippage. Nei’s genetic diversity, Shannon’s index, means values of effective number of alleles, observed number of allele and Percent polymorphism were also reported high in trees like Zanthoxylum spp.15, Punica granatum L.50 and Lagenaria siceraria28 using different markers.The existing variations in the nature of genotypes or group of genotypes can be identified using a specific statistical method or combination of methodsThe high levels of polymorphism obtained with different markers for geographical (> 65%) and fruit status (> 74%) populations clearly proved their usefulness in the genetic variability studies on Indian mango populations. Variation in the polymorphism in marker systems detected by different primers may be attributed to the fact that their specificity and efficiency are governed by different nucleotide sequence. The gene targeted and microsatellite markers generated abundant polymorphism, thus they could be applied to identify the plant materials having close relationships in different populations. In addition to polymorphism detection, their higher scores of Na, Ne, H, I, PB%, Ht and Hs than other studied marker systems, were perhaps because of their derivation from genic regions of the genome.51. Various parameters viz. geographical isolation, population fragmentation, breeding system and genetic drifts may be responsible for the high population differentiation52. The coefficient of gene differentiation (Gst) indicates the level of differentiation according to the scale, low (0.00–0.05), moderate (0.06–0.15), high (0.16–0.25) or very high (> 0.25)53. Gst derived gene flow (Nm) is another way to ascertain genetic variability to a population which can affect the genetic structure too. It allows members of one gene pool to mate with members of another gene pool, leading to a shift of the allele frequencies and decrease in the degree of population differentiation54. Consequently, more evident the gene flow, the lower is the degree of genetic differentiation. Estimate of genetic flow (Nm) has been classified as low (Nm < 1), moderate (Nm > 1) and extensive (Nm > 4) in population genetics55. Nm values greater than one is strong enough to prevent substantial differentiation due to genetic drift56. Geographic origin based populations were moderately structured by all the six marker systems, individually and in combination, due to Gst value of 0.10–0.15 and an overall Gst-derived estimate of gene flow of 2.71- 4.49. The moderate to extensive gene flow among the populations signifies a substantial extent of gene exchange between various populations. Mean coefficient of gene differentiation (Gst) value 0.147 indicated that about 15% genetic diversity resided among the species by arbitrary markers (RAPD + ISSR + DAMD), which is higher than the diversity informed by gene targeted markers (Gst—0.101). Gene flow estimate by gene targeted markers was found to be high (4.432) and it was lower than the gene flow estimate of arbitrary markers (2.907). These Gst and Nm were also varied for RAPD , ISSR , SCoT  and CBDP  markers, respectively. Such differentiation is in contrast to observations in cowpea  recorded for 46 different accessions of a wild plant, Amygdalusmira examined using SSR, ISSR and SSR + ISSR markers58.The genetic differentiation of a species reflects the interactions of various evolutionary processes including long-term evolutionary history, such as shifts in distribution, habitat fragmentation and population isolation, mutation, genetic drift, mating system, gene flow and natural selection28 similar to the present study. SSR and DAMD markers reflected slightly more differentiating ability depending on geography, so did the RAPDs for local, hybrid and selection populations.Investigation of an alternative population exploration based on fruit status unfolded a low-to-moderate extent of genetic differentiation and high gene flow . Gst value was highest in RAPD (0.115), followed by SSR (0.07), DAMD (0.065), ISSR (0.061), CAAT (0.054) and SCoT (0.053), which indicate the highest ability of the RAPD markers to evaluate the variation among local, hybrid and selection genotypes, whilst the trend for gene flow (Nm) among the populations was reversed, being the maximum for SCoT (8.91) followed by CBDP (8.71), ISSR (7.65), DAMD (7.19), SSR (6.56) and RAPD (3.82). Low levels of Gst and high Nm were also obtained for bottle gourd59, strawberry60, mulberry61 and Koehne58, using different marker systems. SSR and DAMD was partitioning maximum (13% and 12%) among geographic populations, whereas RAPD was partitioning maximum variation of 11% among local, hybrid and selection populations. Similar to our results, was AMOVA analysis of 19 varieties of Ficuscarica49, which showed SSR to represent 9.82% group variation, higher compared to RAPD (0.71%), ISSR (6.69%) and RAPD + ISSR (2.59%). The overall ΦPT values confirming geographic distribution had little effect on genetic diversity of mango genotypes. This study clearly indicates frequent exchange of gene pool among the populations perhaps mediated by rampant cross-pollination.These results were further supported by the AMOVA analysis which revealed that maximum (> 87%) of the total genetic diversity by all six marker systems was distributed within populations, whereas a less fraction (3–13%) of the diversity was attributed to differences among populations. Similar patterns of more genetic variation within populations were demonstrated in other perennial species; for instance, Fig. 62. Perennial and allogamous species typically exhibit higher levels of genetic diversity within, rather than between, in contrast to inbreeding or selfing annual species populations, thereby indicating the influence of biological characteristics on these parameters63. Previous reports also revealed that self-pollinating species have relatively less within-population genetic variation than out-crossing species64. Nm may be greater in outcrossing species because the pollen dispersal mechanisms which are much more developed in perennial out-crossers than in inbreds or partially self-pollinated herbaceous plants. Furthermore, the geographic distribution of a species is also highly dependent on the type of pollinators. The potential factors like widespread nature, pollination by insects may have contributed to this scattered pattern of genetic divergence leading to less population differentiation, high gene flow, and frequent gene exchange. The results of the present study suggested that more genetic variation of the species could be captured when sampling a larger number of plants from each population or geographic region. Previous studies also demonstrated that gene mutation, gene flow, population size, sampling strategy can influence genetic variation65.The levels of genetic diversity and the distribution of variability within and between plant populations have generally been interpreted as the result of the balanced combination of the reproductive system and the history of the speciesi.e. East India (EI), West India (WI), North India (NI) and South India (SI) and a dendrogram was generated. Results revealed minimum values of Nei’s genetic diversity (h) distances between EI and SI populations which were 0.07, 0.05, 0.06 for cumulative gene targeted, arbitrary and SSR markers, respectively. These two populations are neighbours to each other and hence geographical closeness might have played a role in the clustering of the provenances. Being so, both the regions share similar climatic conditions i.e. tropical and sub-tropical. However another distinctive factor contributing to such proximity in genetic diversity might be due to the latitude, longitude and altitude of the respective regions. These above mentioned factors are found to be responsible in studies with other plant species . Compared to EI and SI, varying climatic conditions  might have resulted in distinctive genetic variability in WI population in respect of all DNA marker systems employed. The same pattern of clustering among geographical populations was also manifested with SSR, cumulative RAPD + ISSR + DAMD and SCoT + CBDP markers. In the present study the genetic variability is found to be congruent with the geographical diversity. Likewise, NJ dendrogram was prepared among three fruit status populations. The NJ clustering revealed more or less similar grouping pattern for all the three methods. While Hybrid (H) and Selection (S) populations revealed closest genetic relationship, the local (L) population was distinctive.Nei’s genetic distances and identity were estimated for determining the relationships among mangoes from the four geographic populations 66 established UPGMA cluster analysis among wild species and cultivated varieties of alstroemeria (Peruvian lily) through RAPD markers, comparable to our study. Discordance between dendrograms obtained by diverse marker types could be explained by different nature of each markers , different regions coverage of the genome targeted by different marker techniques, extent of polymorphism perceived and the number of loci68. High bootstrap values at most of the nodes supported the stability of these dendrograms. Co-phenetic analysis was also done to evaluate the ‘goodness of fit’ of the resulting phylogenetic trees. Data based on RAPD + ISSR + DAMD, SCoT + CBDP and ISSR markers revealed the consistency of the inferred relationships as the co-phenetic correlation value obtained were ≥ 0.7 for all marker systems and indicated a good fit.These results were supported by population analysis of cumulative arbitrary markers, of which RAPD revealed the most genetic differentiation  and maximum variations among population (11%) in respect of determining fruit status. Aros et al.69 and jatropha70. Our studies have shown that SCoT + CBDP markers were more effective than RAPD + ISSR + DAMD markers in estimating diversity among geographical and fruit status populations. A comparative account of the gene targeted and neutral markers in detecting genetic variations in Morinda tomentosa was studied by Arya et al.61, who reported that gene targeted markers were more useful than random markers in detecting polymorphism, similar to our results. It is, therefore, advisable to employ combined and multiple marker analysis  while performing analytical assessment of genetic diversity and relationship among populations, because such markers target to different genomic fractions, thus providing complementary information and offering more accurate and conclusive results71.In the present investigation, comparisons were made between use of combinational markers, such as arbitrary dominant (RAPD + ISSR + DAMD) and gene targeted (SCoT + CBDP) type, for testing the combined ability of the markers for genetic diversity assessment among mango populations of India. Cumulative multi-marker analyses have been reported to be more informative than individual ones applied to horticultural crops like papaya12. The present study using multiple DNA marker-based diagnostic profiles of mangoes provide the means of rapid characterization of established as well as local genotypes within the populations and, thus, enable the selection of appropriate genotypes for conservation, sustainable management and commercial exploration, such as profitable utilization in bio-prospection programs and also as parents for breeding aimed at genetic improvement of this important edible plant genetic resource.Results of our investigation demonstrate that while within population the genetic diversity was high, among populations it was relatively low in magnitude. The level of genetic variation is influenced by an array of determinants, such as gene flow, geographic conditions and genetic drift. Geographic isolation may lead to a loss of genetic diversity due to reduced gene flow and genetic drift. In absence of timely steps as protective measures, the intra-population genetic diversity might decline due to inbreeding influence. Hence, genetic rescue of promising local mango landraces via in situ and ex situ conservation measures would be highly desirableIn essence, the present study demonstrates the usefulness of DNA marker systems for elucidation of the genetic variability within and among Indian mango populations based on their geographic origin or status of the fruit.The maximum genetic heterogeneity perceived for East Indian populations of mango genotypes, including local elites of the State of Odisha, indicates that they hold the highest proficiency to adapt and evolve compared to other geographical populations. SSR and gene targeted markers were more efficient than arbitrary markers for evaluating genetic diversity of different populations. SSR and DAMD markers reflected slightly more differentiating ability among geographic populations, so did the RAPDs for local, hybrid and selection populations.The high levels of polymorphism obtained with all marker systems used in the present study for population diversity analysis clearly proved their usefulness in estimating the genetic variability among Indian mango germplasm. Combined marker approach was more informative than use of individual markers in population diversity analysis. SCoT + CBDP markers proved to be more effective than RAPD + ISSR + DAMD markers with respect to parameters for evaluating diversity among populations grouped based on geographical locations or fruit status. Understanding the genetic diversity among and within populations of Indian mangoes will be a useful resource in respect of future germplasm conservation, maintenance, exploitation and breeding success, aimed at their genetic improvement.In the present investigation, we have used 70 promising Indian mango genotypes Table , encompa73 with minor modifications8. A sharp glowing band was observed indicating the presence of good quality genomic DNA. By comparing the fluorescent intensity of the bands with the standard , DNA concentration was estimated following the method described by Sambrook et al.74. Parts of stock DNA samples were diluted with appropriate amount of TE buffer to yield a working concentration of 29–40 ng/µl for downstream marker analysis. DNA samples were stored in a refrigerator (4 °C).Fresh and preserved leaves of three different ages  of 70 mango genotypes were used for DNA extraction. Extraction of total genomic DNA was carried out as described by Doyle and Doyle8. Only 208 primers out of the 40 primers screened, resulted in discrete profiles consisting of polymorphic reproducible fragments were validated for further analysis . A total of 56 CBDP primers  and microsatellite primers (SSR) selected from earlier reports87 were synthesized by Bangalore Genei, India. Detailed Primer sequence information of all markers are documented (Jena8). All amplified products  were loaded in wells and resolved on 1.5% agarose gel in 1 × TBE buffer by electrophoresis. For SSR, amplification products were resolved on 3% agarose gels. The amplified fragments were photographed using gel documentation system  and stored as digital images using the built-in software.Genotyping was performed using a total of 278 primers that included individual and combination of arbitrary , gene-targeted  and co-dominant sequence specific (72 SSR) markers using the protocol described by Jena et al.All amplifications were repeated thrice and only reproducible and consistent bands were considered for analysis. The distinct amplicons were scored visually as discrete variables using 1 for presence and 0 for absence separately for each marker and a binary matrix was obtained. Binary marker data were used for the purpose of revealing association of molecular markers with pomometric traits.Geographic origin Fruit status To evaluate variability among and within populations, 70 different mango genotypes were classified based on:88. Genetic diversity within and among populations was estimated by the method of analysis of molecular variance (AMOVA) using GenAlEx 6.502 software89 for studying molecular variations at population level. The significance of the results was tested using 9999 random permutations of the data.The basic parameters for genetic diversity such as observed number of alleles (Na), effective number of alleles (Ne), Nei's genetic diversity (H), Shannon's information index (I), polymorphic bands percentage (PB%), total genetic diversity (Ht), genetic diversity within population (Hs), coefficient of genetic differentiation (Gst) and gene flow (Nm) were calculated using POPGENE software version 1.3190 among all possible pairs to accomplish genetic similarity between the genotypes with the SIMQUAL  option of Numerical Taxonomy and Multivariate Analysis System, NTSYS-pc software version 2.0291. These similarity matrices were then run on Sequential, Agglomerative, Hierarchical and Nested (SAHN) clustering method and subjected for construction of dendrogram by the unweighted pair group method with arithmetic average (UPGMA)92 clustering algorithm with NTSYS-pc. To evaluate the relationship among different populations of Indian mangoes a neighbour joining (NJ) dendrogram was constructed based on Nei's genetic distance93. To estimate the robustness and validity of dendrogram typology and clustering bootstrap analyses were performed of 1000 bootstrap samples using the software WINBOOT94.Pairwise-similarity matrices were generated by calculating Jaccard's similarity coefficientSupplementary Information.


The Human Development Index does not follow a normal distribution. For skewed distributions, finite mixture models can provide better estimates than fixed-effects models. In this paper, the relationship between compact cities and human development is investigated by employing a finite mixture model using panel data of Chinese prefecture-level cities. In contrast to the majority of the literature, which focuses exclusively on economic density, this article examines the impact of economic and morphological density on the level of human development. The results show that the compact development model has a negative impact on the level of human development and that the intensity of the impact varies for cities with different characteristics. Human development  has gradually replaced economic growth as the ultimate goal of human activities since the twenty-first century. Where a choice is required, human development should be prioritized in terms of sequencing . ScholarProponents of the compact city concept promote high-density  and mixed-use developments  as the critical solutions to countervail the negative externalities of urban sprawl and to improve human development. Relevant empirical evidence indicates that compact urban form has a positive effect on a variety of outcomes, including improved accessibility, improved economic outcomes , reduced energy consumption, increased efficiency of public service delivery, and improved health, safety, subjective well-being, and social equity ,14,15,16In addition, some scholars have suggested that the polarizing debate over compact cities may be the result of over-focusing on the experience of high-income countries, in particular, those in North America, while ignoring other urban backgrounds ,21. UnliIn this research, by selecting an exemplary, high-density country, we would have a chance to validate the claims on the benefits of compact form on human development. Using panel data for 285 cities in China from 2000 to 2018, we calculated the compactness of city shape and constructed a human development index (hereafter HDI) for each city to model the relationship between compactness and human development. By decomposing the HDI, we explore possible influence channels through which compactness affects human development, providing additional empirical evidence for the ‘compact city’ debate. In contrast to previous arguments that compact cities can contribute to human development, the main conclusion of this study is that compact development in a high-density context can have a negative impact on human development. Both increased economic density and increased morphological density pose serious challenges to human development.The main contributions of our study can be summarized in three aspects. (1) The values of HDI does not follow a normal distribution; estimating only the average effect of the full sample may lead to biased estimation results. Therefore, we use mixtures of distributions to model the relationship between compactness and human development to refine the estimates. By employing this methodology, we could identify the heterogeneous effects. (2) Previous research has primarily focused on North American cities, ignoring the role of compactness in other context. In this paper, we use panel data from Chinese cities to examine the effect of compactness on human development. By utilizing this data, we could provide additional empirical evidence on the socioeconomic impacts of compactness in high-density cities. (3) A lot of empirical studies examine the outcomes of economic density but ignore the outcomes of morphological density. In contrast to previous research, this study employs night light data to quantify morphological density , thereby compensating for a dearth of empirical research on morphological density.The remainder of our paper is organized as follows. fiscal, the ratio of fiscal expenditure to gross domestic product (hereafter GDP)), trade openness , house prices  and in log), industrial structure , and economic density . Note that i (i = 1 … 285 cities) and t (t = 2000 … 2018 years) denote city and year, respectively.We begin by examining the total effect of city compactness on human development using a traditional panel data method, namely the fixed effects model. Consistent with previous research on the determinants of human development ,22, thisA finite mixture model (hereafter FMM) is a statistical model that presupposes the existence of unobserved groups within a population, referred to as latent classes. Each latent class has its own regression model that can be fitted. As a result, FMMs are widely used to model and analyze heterogeneous data sets with skewness ,24.region) and city size (level). As for geographical location, the cities are classified into four areas based on their location: western, central, northeast, and eastern. The cities in the western, central, northeast, and eastern areas are denoted by 1, 2, 3, and 4, accordingly. The larger the value, the more advantageous the geographical location. As a result, cities with smaller values are farther away from the coastlines. In terms of city size, cities are classified into six categories based on their commercial attractiveness. The detailed categories can be found at https://www.yicai.com/news/101063860.html (accessed on 5 December 2021). The six categories categorised in ascending order of commercial attractiveness are denoted as 5, 4, 3, 2, 1 and 0, respectively.To test the heterogeneous effects of city compactness on HDI at the prefecture-level, the finite mixture model (see Equation (2)) with covariates was established in accordance with the basic model mentioned above. We include two variables that may be useful for grouping: geographical location (it model :(3)πg′(cThe maximum likelihood estimation method is used to estimate the coefficients in Equation (2), and the likelihood function of Equation (2) can be written in a logarithmic form as follows:i belonging to a specific group g’ is calculated as follows:The parameter estimator of the finite mixture model can be obtained by estimating the above equation using the Expectation–Maximization algorithm. Further, by using the Empirical Bayes method, the posterior probability of city g′ are given by the following equations, respectively.All cities can be grouped based on the probability calculated by the above equation. At this point, the overall probability and overall classification error for all cities belonging to group G must be determined. The Akaike Information Criterion (hereafter AIC) and Bayesian Information Criterion (hereafter BIC) are used in this paper to accomplish this. The following is the corresponding calculation equation:It should be noted that before estimating FMM, the optimal grouping number LL is the log-likelihood value calculated by (4), J represents the parameter matrix, and N represents the total number of observations.In Equations (8) and (9), The variables are described in detail below. Two datasets were used to investigate the effect of city compactness on human development: the Night-time Lights dataset and the HDI dataset.First, we used the DMSP/OLS Night-time Lights dataset  from the U.S. Air Force Defense Meteorological Satellite Program (DMSP)) for 2000–2013 and the NPP/VIIRS Night-time Lights dataset (recorded using the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (NPP) satellite) for 2014–2018. The dataset contains satellite images of the earth at night that record the intensity of Earth-based lights each year. We delineated the urban footprints using the images by considering spatially contiguous lighted pixels surrounding a city’s coordinates that have a luminosity greater than a predefined threshold of 10. We then quantified the shape compactness of the urban footprints for each year. Shape compactness is defined as the degree to which a polygon’s shape deviates from a circle. Numerous indexes can be used to measure the shape compactness; for this study, we used the cohesion index, an indicator used in urban planning ,27.nCohesion, is used throughout this paper.Cohesion is a natural measure of the overall accessibility of metropolitan areas. The cohesion property of geographic shapes focuses on the proximity of objects to one another. The more cohesive the metropolitan area, the better the accessibility it offers its inhabitants. The cohesion index is defined using the average Euclidean distance (in kilometers) between two points within a polygon. Higher values of the cohesion index mean longer distances between points and less compact shapes. Note that any compactness index based on distance within a polygon is mechanically correlated with the polygon area. The footprint area was controlled in the computation of the cohesion index to disentangle the geometry effect from the city size. In addition, it is important to highlight that the normalized cohesion index, We then used the HDI dataset. The human development index is given by the expression:To clarify the long-term trend of the city compactness and human development index, we created a time-series graph see . In genefiscal, ftd, IndStr, lnHsPr, and density. These data were obtained from China City Statistical Yearbook, China Statistical Yearbook For Regional Economy, and statistical yearbooks at the provincial and city levels. Due to some missing values, we also referred to other data sources, such as the Wind Economic Database and the CEIC Data . Additionally, we introduce the relief degree of land surface (hereafter rdls) in the robustness test. The relief degree of land surface is an important factor in the macroscopic description of landforms and is often used as a control variable in economic studies. The data were obtained from http://www.geodoi.ac.cn/WebCn/doi.aspx?Id=887 (accessed on 5 December 2021). The descriptive statistics of variables are shown in To account for the effects of extraneous variables, we included several control variables: In nCohesion in Column (1) is not significant. Here, we cannot simply assume that urban compactness has no impact on human development. It is possible that the insignificance of the coefficients is due to poor model setting. According to Doğru (2017) [p-value is 0.00000, rejecting the null hypothesis of a normal distribution. It confirms that HDI does not follow a normal distribution and that the total sample could be a mix of a finite number of normal distributions. Under this circumstance, a better estimate could be obtained with FMM. It is necessary to estimate the finite mixture model.u (2017) , HDI doeThe number of latent groups is unknown prior to estimating the finite mixture model. We use the information criterion to select the best-fitting model, and the preferred model is the one with the minimum information criterion value. Cities in different groups have diverse urban features, as seen in Firstly, the coefficient of economic density reflected by population density on human development is negative for cities with various features, which contradicts prior study findings. Although the spatial concentration of economic activity in urban areas is relatively high, some experts argue that a higher density of urban growth is beneficial on average ,29. HowenCohesion on human development are also negative. The symbols of coefficients are the same for the two groups. However, by comparing the coefficient sizes between the two groups, it is found that the coefficients of the two groups are significantly different. We conclude that among cities with developed economies (higher trade openness and senior industry), urban compactness has a greater negative impact on the level of human development.Secondly, for cities with different characteristics, the coefficients of nCohesion, as it is highly predictive of the spatial distribution of economic activity in cities but uncorrelated with HDI. Like the aforementioned shape compactness of economic activity, the normalized cohesion index of the administrative division (Adm_nCohesion) reflects the extent to which the contour of administrative division deviates from the circle. nCohesion and density are consistent with the original estimation result, and the fundamental results are robust. Economic and morphological density has a detrimental effect on human development.Given that the distribution of economic activity may also be affected by human development, we use the instrumental variable methods to re-estimate the finite mixture model. The compactness of a city’s administrative area is used as an instrument for The relief degree of land surface may affect the shape of the distribution of urban economic activities and thus the level of human development. In order to eliminate the influence of terrain on HDI, this paper introduces the relief degree of land surface as control variables into the benchmark model. The re-estimation results are given in We then analyzed the relationship between city compactness and the three dimensions of the HDI . The purpose of this section was to explore whether the effect of city compactness on different dimensions of human development will change over different city environments.nCohesion are significantly negative in both column 1 and column 2. Likewise, the coefficients of density are both significantly negative. This implies that the increase in both morphological density and economic density has a negative impact on the health dimension. Increased density leads to increased competition in health care resources, and there may be a mismatch between population distribution and available health care resources. Proponents of compact cities claim that compact cities are good for the health of their residents. On the one hand, compact cities increase opportunities for walking and bicycling by reducing average travel distances [2 emissions [istances ,12, whicmissions . As air nCohesion for Group 2 is positive, while the coefficient for Group 1 is negative. This suggests that not all cities have been able to achieve economic growth and higher incomes through compact forms. We conjecture that compact development has the potential to promote economic growth and living standards of residents in cities with advanced industrial structures and high trade openness, while the concept of compact cities is not feasible in underdeveloped cities. However, due to the insignificance of the regression coefficient in this article, the conclusion requires additional testing.density is significantly negative for both two groups. This means that the higher the economic density, the lower the standard of living. That is, in high-density Chinese cities, pursuing higher economic density is unfavorable. Furthermore, comparing the coefficients of density between the two groups reveals that the negative impact is stronger for Group 1 than for Group 2. Combining the different characteristics of the two groups, we find that the impact of economic density on the standard of living is related to the role of cities in macroeconomic growth. The negative effect of economic density on the standard of living is weaker for cities with advanced industrial structures and a high degree of trade openness. This finding is consistent with the prevailing view in urban economics that cities that approach the growth frontier could support higher population densities. It has been thought that the impact of population density on economic growth is generally non-linear [Another important finding is that the coefficient of n-linear ,33,34,35n-linear , urban gn-linear ,38,39, in-linear , and stan-linear . The resWhether an advocate for compact development or for low-density development, the majority of the arguments are based on an examination of the expansion process of low-density cities. There is relatively little literature examining the impact of compactness on human development in the context of high-density cities. Besides, the majority of previous research has investigated the average effect of compact development, oblivious to the heterogeneous characteristics of urban areas. This paper, therefore, examines the impact of compactness on human development in the context of high-density cities, with due regard to the heterogeneous characteristics of different cities, to provide additional empirical evidence on this issue. The empirical results indicate that in the presence of sample heterogeneity, the average effect calculated by the fixed effects model is biased, masking the heterogeneous effects that exist in reality.Firstly, some scholars pointed out that although the spatial concentration of economic activities in urban areas is already high, on average, a higher density of urban development is desirable. This view differs from the results of this article. The empirical analysis of this paper based on the background of high-density cities shows that the pursuit of urban compactness is not good for the improvement of human development. High morphological density does not help inhabitants improve their educational levels, exacerbates the shortage of medical resources, and decreases residents’ quality of life. Similarly, the increase in economic density is also detrimental to improving human development, with effects roughly similar to morphological density. This suggests that a frequent challenge for cities in the process of compact development is the mismatch between the distribution of public services and the population. To effectively reduce congestion induced by population concentration, the spatial distribution of public services  must be properly designed. This puts forward a high request for the level of integrated urban construction, and if a city fails to meet the request, it will be unable to truly advance the city’s human development, even if it achieves compact development.Secondly, the effect size of compact cities on human development and its different dimensions varies with city characteristics. While advanced cities may be able to mitigate the negative economic effects of congestion in compact cities through agglomeration economies, they appear helpless when it comes to providing public services such as education and health care. The findings of this paper suggest that urban compactness should be considered in the context of the role of cities in economic growth, rather than simply looking at the experiences of other countries or examining the impact of urban compactness in an average sense, which may not be conducive to a deeper understanding of the role of compact patterns in promoting human development.Firstly, compact cities include both the pursuit of optimal density  and the mixed use of land. However, this article, limited by the availability of data, does not consider the impact of mixed use of land on human development. In future research, taking into account the various characteristics of compact cities and effectively testing the interaction between multiple characteristics will help draw better scientific conclusions.Secondly, economic phenomena are intrinsically specific and very sensitive to changes in the external environment. If the correct causal relationship cannot be found, the subsequent policy design may be ineffective, and the effect may even be counterproductive. By focusing on the heterogeneous characteristics of cities, this article analyzes the impact of compact cities in more detail. Monkkonen et al. (2020) , in thei


Background: The disease burden of hepatitis E remains high. We used a new method  to classify cities according to the occupational classification of hepatitis E patients across regions in China and compared the results of cluster analysis.Methods: Data on reported hepatitis E cases from 2008 to 2018 were collected from 24 cities . Traditional statistical methods were used to describe the epidemiological characteristics of hepatitis E patients, while the new method and cluster analysis were used to classify the cities by analyzing the occupational composition across regions.Results: The prevalence of hepatitis E in eastern China (Jiangsu Province) was similar to that in the south (Xiamen City) and southwest of China (Chuxiong Yi Autonomous Prefecture), but higher than that in the north (Jilin Province). The age of hepatitis E patients was concentrated between 41 and 60 years, and the sex ratio ranged from 1:1.6 to 1:3.4. Farming was the most highly prevalent occupation; other sub-prevalent occupations included retirement, housework and unemployment. The incidence of occupations among migrant workers, medical staff, teachers, and students was moderate. There were several occupational types with few or no records, such as catering industry, caregivers and babysitters, diaspora children, childcare, herders, and fishing (boat) people. The occupational similarity of hepatitis E was high among economically developed cities, such as Nanjing, Wuxi, Baicheng, and Xiamen, while the similarity was small among cities with large economic disparities, such as Nanjing and Chuxiong Yi Autonomous Prefecture. A comparison of the classification results revealed more similarities and some differences when using these two methods.Conclusion: In China, the factors with the greatest influence on the prevalence of hepatitis E are living in the south, farming as an occupation, being middle-aged or elderly, and being male. The 24 cities we studied were highly diverse and moderately similar in terms of the occupational distribution of patients with hepatitis E. We confirmed the validity of the new method on in classifying cities according to their occupational composition by comparing it with the clustering method. Hepatitis E virus (HEV) infection is a great economic burden on Chinese people. Data released by the Chinese Centre For Disease Control and Prevention show that from 2010 to 2020, the proportion of HEV cases among all infectious diseases was one in one thousand . GenotypThe relationship between occupation and HEV susceptibility remains unclear. Risky occupational populations are present. Studies in Moldova  and CubaCluster analysis has been proven to be an effective classification method when conducting age stratification of patients with diabetes , studyinThe new method  was alsoIn summary, we aimed to investigate the characteristics of occupational distributions in interregional HEV patients. In addition, we hope to confirm the validity of the new method in classification analysis by comparing it with the clustering analysis.This study is divided into four sections. The first section provides a brief overview of HEV epidemiological characteristics in terms of temporal, regional, age, gender, and occupational distributions of reported HEV cases. In the second section, the new method is used for richness, diversity, evenness, and similarity analyses. The results of the cluster analysis are presented in the third section. The final section analyzes the results of classifying cities using the new method and cluster analysis. A research flow diagram is shown in We selected 24 cities in northern, eastern, southern, and southwestern China as the study area . To compN, 121°38–131°19′E, northern) has jurisdiction over nine prefecture-level administrative regions, including eight prefecture-level cities and one autonomous prefecture .Jilin Province  governs 13 prefecture-level administrative regions .Jiangsu Province , with a total area of 170,061 square kilometers, is located at the southeast end of Fujian Province.Xiamen City  is located in the middle of Yunnan Province, with a total area of 29,000 square kilometers.Chuxiong Yi Autonomous Prefecture , Simpson diversity index (D), Shannon diversity index (H), Berger–Parker dominance index (d), Shannon evenness index (E), and Morisita–Horn similarity index (C). N represents the number of occupational classifications. The pi refers to the proportion of the ith classification, and the maximum of pi is the index d, which measures occupational dominance. Occupational diversity and evenness were evaluated using three indices: D, H, and E. If D is closer to 1 or H is larger, the diversity will be greater. The closer E is to 0.5, the better the equitability. The larger d is, the stronger the dominant occupation. Similarities among the different study areas was measured using index C. The closer C is to 1, the greater the similarity. The indices D and H were calculated from the proportion of each occupation; E was calculated by dividing H by the richness index, and C was calculated by the number of individuals in each occupation and the total number of populations by region. These indices are represented by the following equations:First, the traditional descriptive epidemiological method was adopted to analyze the temporal and regional, age and gender, and occupational distributions of the reported cases. Second, the new method  was usedN samples as N classes at the beginning, and then merges them step by step until N samples are merged into one class. In this study, each of the 24 study cities was regarded as a sample, and clustering was carried out according to the incidence of 18 occupational reports  of patients with HEV from 2008 to 2018.Third, we used the cluster analysis method , which iQ-type clustering analysis. The statistically significant level was set at P < 0.05. DataMap 6.2 software , was used to create punctuation maps.Microsoft Excel 2019 software  was used for data entry, sorting, drawing, and calculation of the six indices. The data were analyzed using IBM SPSS Statistics for Windows, version 26.0  for We found that the dynamics of prevalence varied within the provinces. In Jilin Province, the incidence of HEV in the four cities increased, while that in the other five cities showed an annual decreasing trend. In Jiangsu Province, with the exception of the incidence of HEV in the two cities that were on the rise, the other 11 cities showed a downward trend. The incidence in Xiamen City, a coastal city, has been increasing annually, while the incidence in Chuxiong Yi Autonomous Prefecture, an inland city, is decreasing.According to the radar map of age distribution in the 24 cities , the majIn terms of sex, there were significantly more males than females , and theN-value was highest in Xuzhou City (N = 17) and Lianyungang City (N = 17) of Jiangsu Province and was the lowest in Suzhou City (N = 2) and Nantong City (N = 2) of Jiangsu Province. There were more than 10 occupational types among patients with HEV in other cities, such as Jilin City (N = 16) in Jilin Province, Xiamen City (N = 14), and Chuxiong Yi Autonomous Prefecture  and Shannon diversity index (H = 1.887) of Liaoyuan City were the highest. In Jiangsu Province, the two indices were the highest in Nanjing City  and the lowest in Nantong City . In Xiamen City, Fujian Province, the Simpson diversity index (D = 0.991) was close to 1, while the Shannon diversity index (H = 0.929) was high. The Simpson diversity index (D = 0.993) of Chuxiong Yi Autonomous Prefecture in Yunnan Province was close to 1, while the Shannon diversity index (H = 0.379) was low , Zhenjiang City (E = 0.508), and Taizhou city (E = 0.484). However, the E-values of Nantong City (E = 0.004) and Suzhou City (E = 0.179) were the opposite. All nine cities in Jilin Province (E = 0.088–0.697) were away from 0.5. Similarly, the same was true for Xiamen City (E = 0.352) and Chuxiong Yi Autonomous Prefecture . However, the d-values of Baicheng City (d = 0.255) and Nanjing City (d = 0.255) were much lower.The farmer group was the occupational type with the largest Berger-Parker dominance index CC = 0.990), while Baishan City and Songyuan City have the lowest C-values (C = 0.511). Except for the above cases, the similarity coefficients among the cities in Jilin Province were higher than 0.8. The similarity coefficient between cities in Jilin Province and Chuxiong Yi Autonomous Prefecture was moderate (C = 0.506–0.901), and the similarity with Xiamen City was a little higher (C = 0.800–0.905). The similarity of occupational composition of HEV cases between the remaining 11 cities in Jiangsu Province was largely above 0.9, except for Nantong City and Suzhou City. Suzhou and Nantong Cities had the lowest similarity with most cities in Jiangsu Province (C < 0.4). The cities of Nanjing City and Wuxi City in Jiangsu Province had higher similarity coefficients with cities of Jilin Province (C = 0.8497–0.960), and Xiamen City of Fujian Province (C = 0.892–0.924). The occupational distribution among the 11 cities in Jiangsu Province was similar to that of Chuxiong Yi Autonomous Prefecture (C > 0.9). The similarity index values between Xiamen City and Chuxiong Yi Autonomous Prefecture differed significantly (C = 0.455).The similarity analysis by the new method using index From the clustering result chart of When the cities were divided into three categories, Nantong City was still divided into a separate group, nine cities in Jilin Province, Wuxi City, Nanjing City, Changzhou City, Xiamen City, and Chuxiong Yi Autonomous Prefecture were grouped together, and the remaining nine cities, including Yancheng City and Xuzhou City in Jiangsu Province, were grouped together.When the cities were divided into four categories, the results were consistent with those of when they were divided into three categories; the only difference was that Baicheng City was classified as a separate group.C > 0.8), and Nanjing and Xiamen (C = 0. 924) are similar, which is consistent with the results of the cluster analysis.Most of the cities in Jilin province were close in similarity and diversity and were classified into the same group. The similarity coefficients between Nanjing and Baishan, Jilin, Liaoyuan, and Changchun (C = 0.455), yet they were grouped together in the clustering. Nantong city and Suzhou city had the highest similarity (C = 1.000); however, the cluster analysis did not provide enough information about why these two cities were not grouped into the same category. Similarly, 11 cities in Jiangsu Province have similar occupational distribution (C > 0.9) to Chuxiong Yi Autonomous Prefecture, yet Chuxiong Yi Autonomous Prefecture is grouped with three other cities in Jiangsu Province, namely Nanjing, Wuxi, and Changzhou, by cluster analysis.In the cluster analysis, Baishan City and Songyuan City, which do not have high diversity and similarity, were nevertheless placed in the same category, and it was the same for Xiamen City and Chuxiong Yi Autonomous Prefecture. The similarity index between Xiamen, a coastal city, and Chuxiong Yi Autonomous Prefecture, an inland region, was not high  group is not susceptible to HEV, indicating that being exposed to seafood is not as contagious as other animals.The occupational distribution of HEV cases in Jiangsu Province was more balanced than in the other three regions. Unlike most cities, Baicheng and Nanjing cities have developed economies and large populations, so the dominant occupational type is not farmers. The relatively even distribution of HEV-affected occupations in Liaoyuan, Nanjing, and Xiamen cities may be due to demographic reasons, and the cities are richer in occupational types.We believe that the economic environment is a key factor in determining occupational similarity. Nanjing and Wuxi, two cities located in the southern part of Jiangsu province, have a developed economy and fewer people are engaged in HEV-related high-risk occupations, such as agriculture, compared to other cities. Similarly, Xiamen has a well-developed economy and a high degree of similarity with the Nanjing and Wuxi cities. The less economically developed Chuxiong Yi Autonomous Prefecture had lower occupational similarity with Nanjing, Wuxi, and Xiamen cities. The high incidence in the 24 cities was concentrated in the central urban areas, where there are more employment opportunities, more frequent human contact, and therefore a greater potential for transmission.N-values within Jiangsu province, such as with only two occupations in the HEV-affected population in Suzhou and Nantong, we speculate that this may be related to inaccurate and under-reported disease reporting, as well as the uneven degree of development within the same province. The results showed that the occupational distribution among HEV cases was more diverse in Liaoyuan, Nanjing, and Xiamen cities. In contrast, the opposite was true for the Nantong and Chuxiong Yi autonomous prefectures.As far as the differences in When each city is divided into two categories, it shows the difference in the distribution of occupational morbidity. Nantong City is classified as a separate category, because the incidence of hepatitis E in Nantong is entirely contributed by the peasant population. When divided into three categories, we can see the differences between cities within the same province. For example, three cities in Jiangsu Province were classified in one category with all cities in Jilin province, Xiamen city, and Chuxiong Yi Autonomous Prefecture, while the remaining 10 cities in Jiangsu Province were in another category. These cities all had similar levels of hepatitis E prevalence and similar occupational compositions of high and low prevalence.When the cities were divided into four categories, we can also find small differences in cities within the same province. For example, the city of Baicheng in Jilin Province is separated from the other eight cities in the same province, probably because Baicheng has only 10 occupations for the HEV-affected population, while all other cities have 12 or more types.From the results of the cluster analysis, we were able to classify the cities according to the incidence of the type of occupation, as well as with increasing grouping, we were able to find differences between cities within the same province.C-value, we think that when the C-value is higher than 0.8, then the two cities are more similar; if the C-value is lower than 0.5, then the similarity is lower. Further research could focus on the criteria system to improve classification accuracy.When analyzing the occupational composition of hepatitis E across regions and thus classifying cities, both methods based on the cluster analysis method and the new method yielded similar results in most cases and a few opposite results. We believe there may be several reasons for this. First, the principles of the two methods are different. The clustering method we used was analyzed in the form of defining the distance between classes, and the results obtained may be concise. The new method is a comprehensive analysis of diversity, balance, similarity, and other levels with the help of six major indicators to obtain rich results. Second, the new method does not establish a good connection between the values of each indicator and the specific criteria. For example, for the similarity coefficient We confirmed the validity in cross-regional disease occupational composition analysis, which is an extension of the method from microbial level classification to population level. The method has good feasibility and applicability, and more detailed outcome indicators can be obtained.First, we need to strengthen health education on hepatitis E prevention and control for various occupational risk groups. Awareness of hepatitis E is significantly lower than that of hepatitis B and C, especially for key occupational groups, such as farmers engaged in livestock (pig) and poultry-related farming or slaughtering, as well as retirees, housework and unemployment groups.Second, it is necessary to control the transmission of viral hepatitis by frequently testing HEV in workers of related occupations. For example, the rate of positive IgM antibodies to HEV can be used as a signal indicator.Third, the main strategies to deal with HEV in China at this stage are the development of HEV vaccines and the improvement of laboratory diagnosis rates. One study considered the strategy of HEV vaccination in women of childbearing age , and pubFirst, the regions we chose were not random, which may lead to deviations. This was a preliminary study. In the future, if possible, we will use the disease data from more regions for in-depth studies.Second, because not all cases were genotyped in the laboratory, we could not include genotypes for a detailed study due to the availability of data.Third, we could not analyze the disease severity of hepatitis E. Cases of hepatitis E are largely common and mild, with few critical illnesses and deaths. The latter tends to be common in pregnant women and in the older age group. If pregnant women are infected, serious consequences are associated not only with high mortality in the late fetal period, but also with the occurrence of preterm birth and a high probability of vertical transmission to offspring , 37. HowIn China, the factors influencing the prevalence of hepatitis E are living in the south, working as farmers, being middle-aged or elderly, and being male. The 24 cities we studied were highly diverse and moderately similar in terms of the occupational distribution of patients with hepatitis E. We confirmed the validity of the new method in classifying cities according to their occupational composition by comparing it to the clustering analysis.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.TC, XZ, and QZ designed the study. SY, JR, XC, ZZ, CL, SL, YZ, YW, JX, MY, and XL collected the data. SY, JR, XC, ZZ, MW, and ZL analyzed the data. SY and JR wrote the manuscript. All authors have read and approved the final manuscript.This study was partly supported by the Bill & Melinda Gates Foundation (INV-005834), the Science and Technology Program of Fujian Province (No. 2020Y0002), the Xiamen New Coronavirus Prevention and Control Emergency Tackling Special Topic Program (No. 3502Z2020YJ03), and the XMU Training Program of Innovation and Entrepreneurship for Undergraduates . The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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