O-glycosides and tricin-oligolignols in all grass species examined, but only show patchy occurrences in unrelated lineages in dicots. More strikingly, tricin is a lignin monomer in grasses and several other angiosperm species, representing one of the “non-monolignol” lignin monomers identified in nature. The unique biological functions of tricin especially as a lignin monomer have driven the identification and characterization of tricin biosynthetic enzymes in the past decade. This review summarizes the current understanding of tricin biosynthetic pathway in grasses and tricin-accumulating dicots. The characterized and potential enzymes involved in tricin biosynthesis are highlighted along with discussion on the debatable and uncharacterized steps. Finally, current developments of bioengineering on manipulating tricin biosynthesis toward the generation of functional food as well as modifications of lignin for improving biorefinery applications are summarized.Tricin  is a specialized metabolite which not only confers stress tolerance and involves in defense responses in plants but also represents a promising nutraceutical. Tricin-type metabolites are widely present as soluble tricin  Flavonoids are a large group of plant-specialized metabolites that are ubiquitous in vascular plants and are also found in non-vascular plant lineages except hornworts . StructuF3H) expression , and lycophytes   and the dicot alfalfa , a prototype in the type III polyketide synthase superfamily, catalyzes sequential condensation of three malonyl-CoAs with chalcone . Chalcond tricin . AlthougO-conjugates and flavone C-glycosides are biosynthesized in separate pathways. Early radiotracer experiments on Lamnaceae plants revealed that 14C-labelled flavanone aglycones could be simultaneously converted into flavone O-glycosides and C-glycosides  and flavone synthase II (FNSII), were expected to convert flavanones into flavones by direct introduction of the C2–C3 double bond  as a model system, FNSII was identified to be the primary enzyme generating the flavone nucleus for tricin biosynthesis in grasses  O-glycosides which are normally not present in wild-type plants , chrysanthemums (chrysanthemum morifolium), and carnations (Dianthus caryophyllus), all of which naturally lack delphinidin-derived anthocyanins  are rarely detected in grasses  C-glycosides, while their production of soluble and lignin-integrated tricin remains unaffected  required for syringyl (S)-lignin biosynthesis in the spikemoss Selaginella moellendorffii. CYP788A1 is involved in both 3- and 5-hydroxylations of phenylpropanoids, but it could only catalyze 5-hydroxylation after 3-O-methylation  or 5-hydroxyconiferaldehyde O-methyltransferases (CAldOMT) as they also show in vitro O-methylation activities toward 5-hydroxyconiferaldehyde, 5-hydroxyferulic acid, and caffeic acid, which are intermediates in the monolignol pathway; hence, they are also involved in S-lignin biosynthesis  and luteolin (non-methoxylated) when compared with wild-type controls -related enzymes could catalyze 3',5'-O-methylation using various flavone substrates -dependent glycosyltransferases  in several putative UGTs were also found to be directly associated with the variations of flavone O-glycoside accumulation in different natural cultivars and/or recombinant inbred lines of rice -guaiacylglycerol-β-tricin ether [(−)-salcolin A], and erythro-(−)-guaiacylglycerol-β-tricin ether [(−)-salcolin B] isolated from Sinocalamus affinis (Poaceae) were determined as 7''S,8''S and 7''R,8''S, respectively --salcolin A and (−)--salcolin B (O–4) type neolignans in Arabidopsis -salcolin A and (+)-salcolin B were isolated -salcolin A and (+)--salcolin B  in typical non-grass vascular plants . The compatibility of tricin with radical coupling was demonstrated by biomimetic oxidations of tricin with monolignols using peroxidase/hydrogen peroxide and silver (I) oxide as oxidants (via the 4'–O–β-coupling mode (O–β)-linked phenylpropane units in the lignin polymers , Medicago legumes and Trigonella foenum-graecum (family: Fabaceae); Artemisia vulgaris (family: Asteraceae), Leucas cephalotes (family: Lamiaceae), and Lonicera japonica (family: Caprifoliaceae)] ] . Meanwhiiaceae)] . Intriguiaceae)] . Hence, Three possible types of dicot enzymes, FNSIs, FNSIIs, and F2Hs, have been described for flavone nucleus formation , but thePetroselinum crispum), FNSIs were long presumed to be confined to Apiaceae  MsFBH-4 and MsFBH-10, are utilized. In in vitro enzyme assays, these CYP proteins catalyze 3'-hydroxylation of different flavonoid classes  and 5'-hydroxylation of their 3'-methoxylated derivatives which include chrysoeriol. Furthermore, apigenin is converted to 3'- and 5'-substituted flavones  when these CYP75B proteins are transiently expressed in Nicotiana benthamiana leaves. Consistent with these findings, M. truncatula MtFBH-4 knockout mutants are completely depleted in tricin O-glycosides, hence establishing an indispensable role of MtFBH-4 in tricin biosynthesis. Basically, the same reaction steps that occur in grasses , which catalyzes the final step in melatonin biosynthesis  or tricetin in vitro  but not isorhamnetin (a 3'-methoxylated flavonol; The enzymes responsible for the 3'- and 5'-avonoids . Howeverynthesis . In addiynthesis , which min vitro . Over-exCereals contribute to more than half of the world population’s daily caloric intake, but the commonly consumed polished grains, which are mainly consisting of endosperms, are poor in phytochemicals and minerals . Their cAlthough tricin and its derivatives have been characterized with many different health-promoting properties , they arMedicago legumes (Functional food crops that are fortified with tricin could be generated by engineering the entire biosynthetic pathway in edible tissues. Previously, transgenic rice seeds that accumulate tricin were generated by expression of genes from multiple species encoding rice PAL, rice CHS, parsley FNSI, soybean FNSII, blue viola F3'5'H, and rice COMT/CAldOMT . Recent  legumes  as well Miscanthus, Erianthus, switchgrass, and bamboo, which show notably high biomass productivity, are attractive lignocellulose feedstocks for various biorefinery applications (Grasses show great potential as a source of lignocellulosic biomass. A large amount of lignocellulose is produced annually as agricultural residues from worldwide cultivation of grass grain crops, including maize, wheat, rice, barley, and sorghum, as well as grass sugar crops, such as sugarcane and sweet sorghum. In addition, grass energy crops, such as ications . Becauseications . HoweverFNSII (A3'H/C5'H (CHS showed increased lignin level and reduced cell wall digestibility in leaves albeit no alteration in either lignin content or cell wall digestibility in stems (CHS-deficient maize leaf cell walls was attributed at least partially to the consequence of the increased carbon flux toward the branching monolignol biosynthesis pathway upon the blockage of the entry of the flavonoid pathway where CHS plays the major role (As tricin could serve as a nucleation site for lignification, reducing the content of tricin used for lignification may result in reduction of lignin content and biomass recalcitrance, which may in turn improve the production of fermentable sugars from biomass in the polysaccharide-oriented biorefinery processes . Indeed,FNSII  or A3'H/3'H/C5'H , 2019a din stems . The altjor role . These sO–β linkages between the tricin- and monolignol-derived lignin polymer units are comparable to the major β–O–4 linkages connecting the internal monolignol-derived lignin polymer units, suggesting that introduction of more tricin units in lignin polymers is unlikely to increase the energy for lignin depolymerization (On the other hand, increasing the levels of tricin serving as initiation sites for lignin polymerization would theoretically reduce the molecular weight of the lignin polymers, which may potentially improve the efficiency of lignin deconstruction in the polysaccharide-oriented biorefinery processes . A recenrization . NonetheMeanwhile, grass crops bioengineered toward high tricin-lignin content could bring benefits in the lignin-oriented biorefinery approaches by amplifying the supply of tricin or tricin-derived aromatic chemicals. It has been estimated that large quantity of tricin could be released from grass lignins . HoweverPL, YT, and CL wrote the manuscript with help from all the other authors. All authors contributed to the article and approved the submitted version.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. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Attention‐deficit/hyperactivity disorder (ADHD) is a neuropsychiatric disorder of substantial heritability, yet emerging evidence suggests that key risk variants might reside in the noncoding regions of the genome. Our study explored the association of lncRNAs (long noncoding RNAs) with ADHD as represented at three different phenotypic levels guided by the Research Domain Criteria (RDoC) framework: (i) ADHD caseness and symptom dimension, (ii) executive functions as functional endophenotype, and (iii) potential genetic influence on white matter architecture as brain structural endophenotype.Genotype data of 107 tag single nucleotide polymorphisms (SNP) from 10 candidate lncRNAs were analyzed in 1040 children with ADHD and 630 controls of Chinese Han descent. Executive functions including inhibition and set‐shifting were assessed by STROOP and trail making tests, respectively. Imaging genetic analyses were performed in a subgroup of 33 children with ADHD and 55 controls using fractional anisotropy (FA).RNF219‐AS1 was found to be significantly associated with ADHD caseness: with C‐allele detected as the risk genotype in the allelic model (P = 8.607E‐05) and dominant genotypic model (P = 9.628E‐05). Nominal genotypic effects on inhibition (p = 0.020) and set‐shifting (p = 0.046) were detected. While no direct effect on ADHD core symptoms was detected, mediation analysis suggested that SNP rs3908461 potentially exerted an indirect effect through inhibition function . Imaging genetic analyses detected significant associations between rs3908461 genotypes and FA values in corpus callosum, left superior longitudinal fasciculus, left posterior limb of internal capsule, left posterior thalamic radiate (include optic radiation), and the left anterior corona radiate (PFWE corrected < 0.05).One SNP rs3908461 polymorphism in RNF219‐AS1 involvement in the pathophysiology of ADHD in line with the RDoC framework.Our present study examined the potential roles of lncRNA in genetic etiological of ADHD and provided preliminary evidence in support of the potential  A key noncoding RNA variant was found to be associated with the risk of ADHD children in Chinese Han, and the mechanism of this variant affected symptom performance was through the indirect effect of inhibition control. This important DNA polymorphism locus in lncRNA could affect white matter microstructure by the imaging genetic analyses. Strikingly, only 2.94% of genomic sequences were classified as protein‐coding genes , with 97% of DNA sequences found in the noncoding regions.p < 5E‐08), which span several long noncoding RNA sequences, such as KDM4A‐AS1,LINC02497,LINC02060,TMEM161B‐AS1,LINC01288,LINC01572,MEF2C‐AS1,and LINC00461.LINC00461, which showed the highest pleiotropic effects involved in five psychiatric traits: SZ, ADHD, depression, neuroticism, and anxiety disorder.STXBP5‐AS1 was found to be associated with ADHD symptom scores in another GWAS meta‐analysis consisted of adult population‐based and case‐only cohorts of adults (p = 3.02E‐7). The gene‐based analysis showed that three lncRNAs  were also associated with ADHD symptoms (p < 0.007).BC200 RNA) was also found to be associated with ADHD in an Iranian population.Notably, the largest GWAS meta‐analysis to date performed in ADHD has reported 12 genome‐wide significant loci  analyses were further conducted to explore their genetic effects on ADHD core symptoms and executive functions. Thereafter, imaging analyses in a subgroup were performed to investigate the potential underlying brain mechanisms of ADHD‐related lncRNA variants.22.1We recruited 1670 subjects (aged between 6 and 16 years old) in the study. A total of 1040 children suffering from ADHD  were enrolled from the child psychiatric clinics at Peking University Sixth Hospital/Institute of Mental Health. Psychiatric diagnoses of ADHD and comorbidities were assessed and classified basing on the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM‐IV), meanwhile quantitative measurement of inattention and hyperactivity/impulsivity symptoms was evaluated by the ADHD rating scale‐IV (ADHD RS‐IV).For the brain structure study, a subgroup of 33 children with ADHD and 55 healthy controls were included for the magnetic resonance imaging (MRI) genetic analyses. More stringent inclusion and exclusion criteria were applied in order to control for potential confounders. Additional exclusion criteria were as follows: (i) post‐traumatic stress disorder, (ii) history of severe head injury or brain trauma, (iii) claustrophobia, and (iv) having metal implants or other conditions which are contraindication for MRI scanning. More stringent inclusion criteria included the following: (i) right hand dominant and (ii) without history of taking any psychoactive or antipsychotic drug. Signed informed consent was obtained from the parents, and verbal consent was obtained from the children before scanning. These MRI data were partial from the study of Jin et al.2.22.2.1The test included four parts consisted of Color Naming , Word Reading , Color Inhibition , and Word Inhibition . The “color interference time” is defined as the time spent on Part 3 minus that on Part 2. The “word interference time” is defined as the time spent on Part 4 minus that on Part 1. The Color and Word Interference Time scores were used to evaluate the “Inhibition” function.2.2.2TMT was used to assess set‐shifting. It includes two sections: number sequencing trail making and number‐letter switching trail making. The time spent on each section was recorded, and the set‐shifting time was represented by the discrepancy in time between “Number‐Letter Switching trail making” and “Number Sequencing trail making.”2.3KDM4A‐AS1,LINC02497,LINC00461,LINC02060,TMEM161B‐AS1,LINC01288,LINC01572,MEF2C‐AS1,LOC105379109, and RNF219‐AS1. These lncRNAs were all from the GWAS‐meta study of Demontis et alKDM4A‐AS1,LINC02497,LINC00461,LINC02060,TMEM161B‐AS1,LINC01288,LINC01572, and MEF2C‐AS1. Additionally, novel index variants from two lncRNAs  emerged in the replication GWAS‐meta analysis of the primary ADHD GWAS along with three other independent ADHD‐related GWASs.We choose candidate ten long noncoding RNAs to evaluate their associations with ADHD risk in our Chinese Han sample: http://www.broad.mit.edu/mpg/haploview/) was used to filter the SNPs with minor allele frequency (MAF) <0.05, a call rate <95%, failing the Hardy‐Weinberg equilibrium (HWE) test (p < 0.001), and yielding 328 SNPs. Finally, 107 tag‐SNPs , 1.8 × 1.8 mm in‐plane resolution.MRI scanning from a subgroup of 33 ADHD and 55 health controls was carried out with a 3.0 T Siemens Tim Trio MRI scanner, using a standard 12‐channel head coil in the Imaging Center for Brain Research, Beijing Normal University. DTI scanning was conducted with the following scan parameters: field of view: 230 × 230 mm, flip angle = 90°, matrix = 128 × 128, slice thickness: 2.5 mm, repetition time [TR]/echo time [TE] =7200/104 ms, 64 optimal nonlinear diffusion‐weighted directions with b = 1000 s/mmwww.fmrib.ox.ac.uk/fsl): (i) head motion and eddy current distortions were corrected by the “eddy” tool in the FMRIB’s Diffusion Toolbox (part of FSL); (ii) Brain Extraction Tool (BET)http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/TBSS) was applied for voxel‐wise statistics analysis.For preprocessing the DTI, all DICOM images were transferred to 4D‐Nifti file using the MRIcroN software. Original FA images were created by the following 3 steps using FMRIB Software Library (FSL) version 6.1  were carried out by SPSS v22.0 software. Before statistical analysis, the normality of continuous variables  was tested through analysis of skewness and kurtosis, with acceptable scores between −1 and 1.Statistical analyses of demographic and clinical characteristics, with chi‐square test for categorical variable (sex) and 2.5.2p < 0.05), further analyses under additive, recessive, and dominant models were also conducted. For the SNPs showing significant allelic and/or genotypic association with ADHD, analysis of covariance (ANCOVA) was further conducted to test its influence on ADHD core symptoms and cognitive functions, while controlling for gender, age, and IQ as potential confounders. All continuous variables (scores of ADHD core symptoms and cognitive functions) were first checked for normality of data distribution with acceptable scores of skewness and kurtosis between 1 and −1. Levene's test for the homogeneity of variances  was performed prior to the ANCOVA analysis. Bonferroni corrections were performed to correct for multiple comparisons, setting the significant P‐value at 1.168E‐04 for the categorical genetic analyses  and 0.008 for the quantitative genetic association analyses . Statistical analyses were performed with SPSS v22.0 software  and Haploview version 4.2. (http://www.broad.mit.edu/mpg/haploview/).Chi‐square tests were used to examine the allelic distributions of the candidate SNPs between ADHD and health controls. When the allelic model difference was nominally significance  generated from the UK Brain Expression Consortium (UKBEC).The functional information for significant SNPs was retrieved from the public bioinformatics resources. We detected the effects of positive SNPs on gene expression levels by carrying out expression quantitative trait loci (eQTL) analysis based on BRAINEAC database (2.5.4p > 0.05), comparison of FA values between the two groups was performed using analysis of variance (ANCOVA) within the framework of the general linear model (GLM) in a whole‐skeleton voxel‐based manner with TBSS, adjusting for gender, age, IQ, and ADHD diagnosis variables. Threshold‐free cluster enhancement (TFCE) was applied to obtain cluster‐wise statistics corrected for multiple comparisons. For controlling the family‐wise error (FWE), the data were null permuted 5000 times to identify the clusters at a threshold level of p < 0.05.Given the findings from the eQTL analysis and our previous findings that white matters alterations existed in many brain regions of ADHD children compared to health children,JHU DTI‐based white matter atlases in FSL were used to annotate the clusters’ position, the ICBM‐DTI‐81 white matter labels atlas provided by Laboratory of Brain Anatomical MRI (Johns Hopkins University). To further explore whether the white matter alterations have an effect on the cognitive functions, the mean FA values within each significant cluster matching to these atlases were extracted and entered into partial correlation analyses with the cognitive functional scores, after adjusting for age, gender, and IQ. The analyses were performed separately in the ADHD and control groups.3Of 1670 participants (1040 ADHD children and 630 controls) examined in this study, there was no significant difference of age between the two groups, but the IQ of children with ADHD was lower than the controls, with higher percentage of male children in the ADHD group. The same patterns were also observed in the imaging genetic analyses, and the details were summarized in Table 3.1RNF219‐AS1 and ADHD were detected under the allelic model  and dominant genotypic model , with C‐allele as risk factor  were also different between ADHD children and controls at the nominal significance levels of p < 0.05.Significant associations between the SNP rs3908461 of p = 0.020)] and Shifting time  in the C‐allele carriers than TT carriers with gender, age, and IQ adjusted; however, those association did not survive Bonferroni corrections for multiple comparisons. No genotypic effects of rs3908461 on ADHD core symptoms were identified .Quantitative analyses of ADHD core symptoms and cognitive function scores were conducted in 806 children with ADHD with available and complete data for analyses. The ANCOVA analyses Table  indicater = 0.13, P = 4.460E‐4) and ADHD total scores  were detected, likewise, the set‐shifting time and hyperactive/impulsive scores . After adjusting for the gender, age, and IQ, only weak correlation between the word interference time and the ADHD total scores remained significant  /Trail making test (“shifting time”) and ADHD core symptoms Table . The pos) Figure . Then, m) Figure . A compl) Figure : this me3.2RNF219 mRNA expression in the region of intralobular white matter  including 75 C‐allele carriers and 13 TT homozygotes for rs3908461. Whole‐skeleton voxel‐wise statistics analysis based TBSS demonstrated that the C‐allele carriers have the higher FA values than the TT carriers in two clusters, and the significant voxels are particularly located in regions of genu, body, and splenium of corpus callosum, left superior longitudinal fasciculus, left posterior limb of internal capsule, left posterior thalamic radiate (include optic radiation), and the left anterior corona radiate .Of the above regions, three white matter tracts  overlapped with our previous findings in which the significant difference of FA values existed between ADHD and healthy controls.r = −0.39, p = 0.034) in the ADHD group, while longer word interference time (means worse inhibitory) was linked to decreased FA.Second, we examined the executive function association with the structural integrity of these regions, instead of just the genotype effect. In the aforementioned three regions, we explored the correlations between the FA values and executive inhibition functions. As shown in Figure 4RNF219‐AS1 and ADHD were detected under the allelic model and dominant genotypic model, with C‐allele as risk factor. However, no direct gene effect was detected for ADHD symptom dimensions. Second, for executive function endophenotypes, positive correlations of the word interference time with hyperactive/impulsive and ADHD total scores were detected, likewise, the set‐shifting time and hyperactive/impulsive scores. Moreover, a complete mediation model was detected, showing that word interference time mediated the path between genotype and total scores; and the model suggests that the mechanism of SNP rs3908461 effects on ADHD total symptom was accounted by the indirect effect of inhibition control as the mediator. Third, for white matter architecture as the structural endophenotype, imaging genetic analyses showed significant associations between rs3908461 genotypes and FA values in corpus callosum, left superior longitudinal fasciculus, left posterior limb of internal capsule, left posterior thalamic radiate (include optic radiation), and the left anterior corona radiate.There are three key findings in our study, and the associations of lncRNAs with ADHD were detected at three different phenotypic levels. First, significant associations between the SNP rs3908461 of Interestingly, our findings are in line with the recent research findings on lncRNAs, whose roles in neurodevelopmental disorders have been implicated by their involvements in a diverse range of neuronal functions, including neurogenesis, maintenance of pluripotency, synaptogenesis, nerve cells maturation, homeostasis, transcriptional regulation as well as synaptic plasticity and strength.RNF219‐AS1 rs3908461 was significantly different between children with ADHD and controls. The SNP rs3908461 was located in the intron of a noncoding RNA gene of RNF219‐AS1 (Ring Finger Protein 219 Antisense RNA 1) which is also regarded as ORC Ubiquitin Ligase 1 Antisense RNA 1(OBI1‐AS1) (www.genecards.org). OBI1‐AS1 is a particularly interesting molecule in relation to ADHD. OBI1‐AS1 molecule has been reported to be associated with several neuropsychiatric phenotypes/traits including smoking status, alcohol drinking, total ventricular volume in Alzheimer's disease, sleep duration, and antipsychotic drug‐induced weight gain in schizophrenia in the GWAS Catalog database (www.ebi.ac.uk/gwas/). A recent transcriptome‐wide association study (TWAS) based on ADHD GWAS has found that RNF219‐AS1 was also associated with ADHD as genetically regulated gene.OBI1‐AS1 is still unclear, some studies suggest that natural antisense RNA hybridize with the endogenous mRNA to play the regulatory role.OBI1 has been found to be involved in the ubiquitin signaling pathway which regulated the DNA replication and effected cell growth and transformation.OBI1‐AS1, rs2243638, and rs9574218 as ADHD‐related risk variants,RNF219 expression in white matter while rs2243638 and rs9574218 in medulla (http://www.braineac.org/).Our first finding demonstrated that the allele distribution for RNF219‐AS1 rs3908461 on inhibition function deficits among ADHD subjects, with TT genotype (as protective factor) carriers performing better. Although no significant association was found for ADHD core symptoms, our mediation analysis found a significant indirect effect of RNF219‐AS1 rs3908461 on ADHD total symptom through executive inhibition as the mediator. Previous studies have found that children with ADHD exhibited a range of executive deficits, especially the inhibition function.RNF219‐AS1 on ADHD symptoms through inhibition function as the mediator. However, the detected association between rs3908461 and the inhibition in our study did not survive Bonferroni correction, and our findings must be regarded with caution and as preliminary, awaiting further replication.In our study, quantitative analyses detected nominal genetic effects of RNF219 mRNA expression in white matter. RNF219‐AS1 is a natural antisense transcript (NAT), whose transcript comes from the opposite strand of the adjacent protein‐coding gene RNF219. Such cis‐NAT can be partly or completely overlapping and bind to the sense strand and may regulate the activities of neighboring genes in the ways of transcription inhibition, nuclear RNA‐RNA interaction, RNA‐DNA interactions, and cytoplasmic RNA‐RNA interaction.r2 ≥ 0.8 in the 1000 Genomes, CHB population) in the bioinformatics database of HaploReg v.4.1  were shown in the Table RNF219‐AS1 (chr13:78493824–79191463) and RNF219 (chr13:79188421–79233314) were tail‐to‐tail overlaps with 3043 bp (https://genome.ucsc.edu/) aligned to the human reference genome (hg19), and rs3908461(chr13:78770857) was located in the second intron of RNF219‐AS1. We posited that the influence of rs3908461 on the expression of RNF219 gene in the brain may be the part of the transcriptional regulatory mechanism for antisense lncRNA interacted with the host gene. However, we should note that the potential genetic effect on gene expression was only found when the exon‐specific probeset exprID3518981 was used, while not for the exprID t3518971 which was derived from the mean over 13 probesets. Such phenomenon has been found in some other studies.The eQTL analyses based on the UK Brain Expression Cohort of Caucasian subjects showed that minor C‐allele increased the OBI1, we investigated the 11 key proteins which interacted with OBI1 gene in the STRING Interaction Network (https://version11.string‐db.org/) ,TOB1).OBI1 in myelination.To explore more fully the potential functional mechanisms of ) Figure  and founOur previous study has revealed that children with ADHD showed the decreased FA values in corpus callosum, the left superior longitudinal fasciculus, and the left corona radiate compared to the healthy.However, our current findings that risk‐allele carriers  were linked with increased FA values were not in line with our expectation. There could be three explanations. First functional changes could be more accurately determined by task‐based functional MRI studiesRNF219‐AS1 in the etiology of ADHD. Lastly, we only focused on the effects of variations in the DNA polymorphisms of lncRNAs to detect the correlation with ADHD. We could not sequence the actual lncRNAs, which would necessitate accessing brain tissues and therefore would not be practically feasible in human studies. Moreover, we could not explore the molecular function of RNF219‐AS1 with ADHD. Therefore, functional mechanisms could only be inferred. As an alternative strategy, in the future, we plan to analyze comprehensively the expression patterns of lncRNAs transcriptome of ADHD patients using high‐throughput sequencing technology to explore more fully the molecular mechanism by which lncRNAs influence ADHD etiology.Several limitations need be considered. First, for the functional endophenotype analysis, we only detected a marginal relationship between genetic variation and inhibitory function, and the result did not survive correction for the multiple comparisons. The correlation between inhibition and symptom score was also relatively weak. Our results should therefore be interpreted with caution. Second, the executive function endophenotypic analyses were conducted in the ADHD participants, and not in the controls, so the potential effects of lncRNA SNPs on executive function in the general population remained unexplored. Third, our sample included only participants of Chinese Han descent, then the generalizability of our findings to other ethnic groups and populations needs to be tested in the future. The genetic findings through the GWAS‐meta carried on adult/youth samples for the neurodevelopmental diseases may not be able to identify the genetic risk for childhood‐onset conditions.5RNF219‐AS1 in the pathophysiology of ADHD at different phenotypic levels, levels guided by the Research Domain Criteria (RDoC) framework: (i) ADHD caseness and symptom dimension, (ii) executive functions as functional endophenotype, and (iii) potential genetic influence of rs3908461 in RNF219‐AS1 on white matter architecture as brain structural endophenotype. LncRNAs, as the noncoding sequences widely expressed in the central nervous system, are likely to be involved in abroad spectrum of molecular functions in the brain development and thus of critical relevance to the pathogenesis of neuropsychiatric disorders included ADHD. Our findings provide preliminary support for an associations of lncRNAs in the complex pathogenesis of ADHD.Our study explored the potential involvement of lncRNA 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.Guanghui Fu, Lu Liu, and Qiujin Qian contributed conception and design of the study; Haimei Li and Guanghui Fu organized the database; Guanghui Fu, Lu Liu, Wai Chen, Yufeng Wang, and Qiujin Qian performed the statistical analysis, interpreted the results, and wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.Supplementary MaterialClick here for additional data file.


Ensete ventricosum) is a multipurpose crop extensively cultivated in southern and southwestern Ethiopia for human food, animal feed, and fiber. It has immense contributions to the food security and rural livelihoods of 20 million people. Several distinct enset landraces are cultivated for their uses in traditional medicine. These landraces are vulnerable to various human-related activities and environmental constraints. The genetic diversity among the landraces is not verified to plan conservation strategy. Moreover, it is currently unknown whether medicinal landraces are genetically differentiated from other landraces. Here, we characterize the genetic diversity of medicinal enset landraces to support effective conservation and utilization of their diversity. We evaluated the genetic diversity of 51 enset landraces, of which 38 have reported medicinal value. A total of 38 alleles across the 15 simple sequence repeat (SSR) loci and a moderate level of genetic diversity (He = 0.47) were detected. Analysis of molecular variation (AMOVA) revealed that only 2.4% of the total genetic variation was contributed by variation among the medicinal and non-medicinal groups of landraces, with an FST of 0.024. A neighbor-joining tree showed four separate clusters with no correlation to the use-values of the landraces. Except for two, all “medicinal” landraces with distinct vernacular names were found to be genetically different, showing that vernacular names are a good indicator of genetic distinctiveness in these specific groups of landraces. The discriminant analysis of the principal components also confirmed the absence of distinct clustering between the two groups. We found that enset landraces were clustered irrespective of their use-value, showing no evidence for genetic differentiation between the enset grown for ‘medicinal’ uses and non-medicinal landraces. This suggests that enset medicinal properties may be restricted to a more limited number of genotypes, might have resulted from the interaction of genotype with the environment or management practice, or partly misreported. The study provides baseline information that promotes further investigations in exploiting the medicinal value of these specific landraces.Enset ( Ensete ventricosum; also called Abyssinian banana) is a herbaceous, monocarpic perennial plant that grows from 4 to 10 m in height. It resembles and is closely related to bananas in the genus Musa, and these, together with the monotypic genus Musella, form the family Musaceae  consisting of nine districts or special districts of the Southern, Nations, Nationalities, and Peoples (SNNP) regional state of Ethiopia , 1 μl forward and reverse primers (10 mM), and 0.5 μl (5 U/μl) BioTaq DNA polymerase  and amplified using a PCR thermal cycler . The three-step amplification program consisted of initial (1) denaturation for 2 min at 95°C, (2) 35 cycles of denaturation at 95°C for 1 min, annealing at a temperature specific to each primer set (A PCR amplification was carried out in a 20 μl reaction volume containing 1.5 μl (100 mM) template DNA, 11.5 μl molecular reagent water, W 4502 , 0.75 μl dNTPs (10 mM) , 2.5 μl Taq buffer (10× Thermopol reaction buffer), 1.25 μl MgClimer set , for 1 mThe separation of the amplified product was accomplished in a 4% (w/v) agarose  gel in 1% (w/v) Tris-acetate-EDTA (TAE) buffer containing ethidium bromide, and electrophoresed at 80 V for 3 h. A standard DNA ladder of 100 bp  was loaded together with the samples to estimate molecular weight. The banding pattern was visualized using a gel documentation system  and the pictures were documented for scoring.a), the effective number of alleles (Ne), Shannon’s information index (I), observed heterozygosity (Ho), expected heterozygosity (He), un-biased expected heterozygosity (uHe), and Fixation index for each locus were computed using GENALEX version 6.503 (ST) between the two groups of landraces was estimated using GENALEX. An analysis of molecular variation (AMOVA) was performed to evaluate the relative level of genetic variations among groups, and among individuals within a group using GENALEX. The neighbor-joining (NJ) tree was constructed using the software DARwin  and expected heterozygosity (He) ranged from 0 to 0.64 and 0.18 to 0.63, respectively, and Shannon’s information index (I) ranged from 0.31 to 1.04.The polymorphic nature of some of the SSR markers was as shown in ST) was 0.024 , all landraces with the different vernacular names were distinct. The Bayesian clustering result showed the presence of four subpopulations, with some shared admixture memberships  was detected. A relatively higher He values (0.55 and 0.59) of enset were reported . Genetic differentiation values (0.037) among locations were reported on enset , althougFrom the landraces that have the same vernacular names (replicate samples), the majority were closely similar genetically and placed together in the neighbor-joining tree. This indicates that farmers have rich indigenous knowledge in identifying and naming enset landraces based on phenotypic traits, and the knowledge is shared across the growing region. However, few other replicates of landraces were placed in different clusters, indicating that genetically different landraces were given the same vernacular name. Perfect identification of genotypes using morphological traits is difficult, and the existence of homonyms has been reported previously .Except for two, all landraces with distinct vernacular names were found to be different, showing that vernacular names are good indicators of genetic distinctiveness in these specific groups of landraces. Whereas, the existence of 37 and 8 duplicates of landrace in diversity analysis of enset using four AFLP  and 12 RThe use of some of the enset landraces in traditional treatment of various human ailments in the major enset growing region of Ethiopia, SNNPR, was reported by several authors . Howeverin situ, they generate unique biochemistry with medicinal properties. Thirdly, a number of important medicinal landraces may have been omitted, or medicinal value incorrectly assigned to non-medicinal landraces. This could serve to hinder our analysis and make it more difficult to detect real genetic differentiation. This would also be an indication of a decline in the quality of indigenous knowledge. We also note that it is unlikely that the strong trust of society upon these landraces could not be developed after a very long period of use, and we have observed remarkable similar enset medicinal claims across a wide variety of distinct ethnic groups in multiple languages. Moreover, anti-bacterial and anti-fungal activities of a compound extracted from the unspecified E. ventricosum landrace  landraces used in traditional medicine was reported . Arginine is involved in collagen formation, tissue repair, and wound healing via proline, indicating a possible biochemical basis for the medicinal properties of some of the landraces.There are several possible explanations for these observations. First, all enset landraces may have a degree of medicinal value, but specific genotypes are preferred for phenotypic or cultural reasons. Second, the medicinal value may arise through genotype-environment interactions or management practices specific to those landraces i.e., they may have non-differentiated genotypes, but landrace , and a rlandrace  on the mreported . Finallyreported  detectedThe study indicated the existence of moderate level genetic diversity among enset landraces used in traditional medicine. The majority of the variation was contributed by variation among individuals, indicating low genetic differentiation among the groups. Except for two, all the landraces with distinct vernacular names were found to be genetically different. The landraces were not clustered based on their use-values, showing no evidence for genetic differentiation between landraces used in traditional medicine and those having other use-values, and the range of diversity in medicinal landraces was little different from that of landraces cultivated for food. In the future, we suggest a biochemical comparison of enset landraces growing in the same environmental and soil condition would complement our analysis, while genetic mapping and genome-wide association studies (GWAS) have the potential to identify genomic regions and genes associated with medicinal traits. The information from this study will be useful for the identification and conservation of enset landraces used in traditional medicine, and it can provide baseline information that promotes further investigations in exploiting the medicinal value of these specific landraces.The original contributions presented in the study are included in the article/GN, TF, KT, and SD designed the experiment in the context of the funded project designed by PW, JH-H, and SD. GN carried out the sample collection, primer design, and laboratory work with MB. GN and MB conducted data mining and carried out the data analysis. GN, JB, TF, and JH-H were major contributors to interpreting the data. All authors contributed background to the design of the work and manuscript writing and revision and approved the final 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. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Attention-deficit/hyperactivity disorder (ADHD) in adolescence is associated with functional impairment in several domains of life. To enable development of interventions that more effectively target functional impairment in this age group, the associations between clinical characteristics and impairment need to be clarified. The aim of this study was to investigate the associations between ADHD and functional impairment, if they varied by sex, and the potential impact of comorbid psychiatric symptoms on the associations.This was a cross-sectional study including adolescents with ADHD (n = 164) and a reference group of adolescents without ADHD (n = 106). Self-ratings and parental ratings of functional impairment in different life domains were used as outcomes in all analyses. Differences between groups were investigated with comparative analyses. General linear models (GLMs) were used to explore associations between ADHD symptoms and functional impairment in adolescents with ADHD, while adjusting for of comorbid symptoms, sex, and medication.Adolescents with ADHD displayed higher levels of functional impairment than peers without ADHD, and girls with ADHD rated higher impairment than their male counterparts. The combined ADHD presentation was associated with the highest levels of self-reported impairment, while parental ratings indicated comparable levels of overall impairment across presentations. In the adjusted GLMs, symptoms of inattention were strongly associated with self- and parent-rated impairment in school, but symptoms of hyperactivity/impulsivity were not, whereas symptoms of both inattention and hyperactivity/impulsivity were modestly associated with self-rated impairment with friends. Further, both emotional and conduct problems were associated with impairment in daily life.Our results suggest that attention difficulties, in particular, seem to impair academic functioning in adolescents with ADHD, and interventions targeting such difficulties are warranted. In addition, comorbid symptoms need to be assessed and treated, and self-reports of functioning should be included in research and clinical practice involving adolescents.The online version contains supplementary material available at 10.1186/s13034-022-00463-0. Attention-deficit/hyperactivity disorder (ADHD) is characterized by age-inappropriate and impairing symptoms of inattention and/or hyperactivity/impulsivity, and is related to functional impairment in several life domains , such asThe magnitude of academic impairment may become more pronounced in adolescence, since academic demands often increase in high school  . Many adThough ADHD symptoms and functional impairment are related, they are separate constructs. Accordingly, previous studies have shown small to moderate correlations between them  and a deA majority of adolescents with ADHD struggle with symptoms of psychiatric comorbidity , 16. A rWhen investigating the associations between ADHD and functional impairment, potential sex differences might be important to consider. In a recent population-based study, parents rated boys as more impaired than girls , while oMost studies investigating the association between clinical symptoms and functional impairment for youths with ADHD have been conducted on younger children or pooled samples of children and adolescents , 25, 26.The aim of this study was to investigate how self- and parent-rated functional impairment related to ADHD and sex, and how the symptom domains of ADHD were associated with impairment in different life domains when adjusting for comorbid symptoms. We hypothesized:(i) that adolescents with ADHD would have higher ratings of functional impairment than peers without ADHD, (ii) that the highest levels of overall impairment would be seen for ADHD-C, while the levels of impairment in school would be about the same for ADHD-C and ADHD-I, (iii) that symptoms of inattention would explain most of the variance in impairment in school, while both symptom domains would be significantly associated with impairment with peers and at home, and (iv) that the explained variance of functional impairment resulting from each ADHD domain would be attenuated when adjusting for conduct problems and emotional problems, especially in regard to impairment with peers and at home.n = 164, mean age: 16.6 years (standard deviation (SD): 0.99), 64.0% female) and a community-based sample of adolescents without ADHD , 68.9% female), with the latter serving as a reference group. The clinical sample stemmed from our previous multi-center study, evaluating psychological group treatment for adolescents with ADHD [This was a cross-sectional study including a clinical sample of adolescents with ADHD  to a set of questionnaires, completed on a digital platform from home. Exclusion criteria were an ADHD diagnosis, as reported by the parents, or clinical levels of ADHD symptoms ). For participants for whom only self-ratings were available, the Adult ADHD self-report scale for adolescents (ASRS-A)  was usedADHD diagnosis was used as a dichotomous variable to compare the clinical sample to the reference group. The variable was dichotomized as either having or not having ADHD.For the clinical sample, each participant’s sex and age were retrieved from their personal identity number, whereas this information was based on self-reports for the reference group. Sex was used as a dichotomous variable  and age as a continuous variable.Ongoing medication for ADHD was reported by the parents in the clinical sample. Medication status was used as a dichotomous variable (ADHD medication or no ADHD medication).Since the participants in the clinical sample were diagnosed with ADHD prior to the study , all eligible participants were diagnostically reassessed. Clinical psychologists performed this reassessment at the CAP units, together with the adolescents and their parents, using the module for ADHD in the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID) . The curα = 0.85 for self-ratings and α = 0.83 for parental ratings), as did the subscale for hyperactivity/impulsivity .Symptoms of inattention and hyperactivity/impulsivity were assessed with self-ratings and parental ratings on two different subscales of the ASRS-A , 40. Thiα for emotional problems was 0.71 for self-ratings and 0.66 for parental ratings, whereas Cronbach’s α for conduct problems was 0.61 for self-ratings and 0.62 for parental ratings, which indicated questionable to acceptable internal consistency for these subscales. Notably, the subscales of the SDQ should be used only to screen for emotional and behavioral difficulties, not for diagnostic purposes.Emotional problems and conduct problems were assessed with self-ratings and parental ratings on the Strengths & Difficulties Questionnaire (SDQ) –43. The adolescent at home, while the parental rating question asks whether the child’s symptoms have any negative impact on their joint family life. Impairment in each area is measured on an 11-point scale from 0  to 10 (very much), with higher scores indicating more impairment. In the current study, we investigated both overall impairment  and impairment in each area. The CSDS displayed good internal consistency  in this study.Functional impairment was measured with self-ratings and parental ratings of the Child Sheehan Disability Scale (CSDS) , 45. Then = 164 in the ADHD group, n = 106 in the reference group, power = 0.80, α = 0.05), the study was statistically powered to detect small to medium effects (d = 0.37). For comparing the outcomes between ADHD presentations , the study was powered to detect medium effects (f = 0.25). In regard to the multiple regression model, including six potential predictors , the study was powered to detect small to medium effects (f2 = 0.09).Power calculations were performed using G*power 3.1.9.6. For the group comparisons .As regards the clinical sample of adolescents with ADHD, the assumptions of normality, linearity, homoscedasticity, and the absence of multicollinearity were met. Mean differences in functional impairment  across ADHD presentations  were investigated with one-way analysis of variance, with Tukey’s post-hoc test used to explore potential differences further. To investigate the variance explained by each ADHD domain (inattention and hyperactivity/impulsivity) on the outcomes of functional impairment in adolescents with ADHD, general linear models (GLMs) were conducted in two steps and investigated in separate models for each outcome. In the first step, inattention and hyperactivity/impulsivity were introduced into the model without any further adjustments, to observe their crude effects on the outcomes. Next, conduct problems, emotional problems, sex, and medication status were added to the model, to explore if the effect sizes of the ADHD domains were preserved and if the other independent variables contributed to the explained variance of the outcomes. Partial eta squared was used as a measure of effect size . Results were considered significant at the 5% level.U = 8733.00, p = 0.95) or sex . A majority of the participants in the clinical group were on pharmacological treatment for ADHD (76.5%), and ADHD medication was more common among male than female participants . In regard to current ADHD presentation, ADHD-C was most common (44.5%), followed by ADHD-I (35.4%), ADHD UNS (18.3%), and ADHD-H (1.8%). Correlations between self- and parent-rated impairment were low to moderate for both the ADHD group  and the reference group .No differences were found between the two groups in regard to distribution of age , cognitive ability, parental mental health, teen-parent relationship, and when the ADHD diagnosis was received, which leaves the question of potential confounders unanswered. Potential protective factors of functional impairment could also be explored further, since strengthening of these factors should be of particular interest in psychosocial interventions for ADHD , 61. ThiThis study also has some strengths. To the best of our knowledge, this is one of few studies that has evaluated the association between ADHD and self- reported functional impairment for adolescents with ADHD. The use of multiple informants may have contributed to a more complete picture, while also highlighting the importance of accounting for the adolescents’ own perspectives. Investigating impairment across different life areas, rather than using one global measure of impairment, may have helped clarify the association between the examined predictor variables and the functional impairment in each life domain. Lastly, the inclusion of clinical patients recruited from several regions may arguably have strengthened the ecological validity of the study findings.Clarification of the associations between clinical characteristics and functional impairment is an important step in the development of interventions that effectively target functional impairment in adolescents with ADHD. This study replicated previous research findings suggesting that adolescents diagnosed with ADHD experience worse functioning across a broad range of important life domains, as compared with neurotypical peers. Findings from this study suggest that adolescent girls with ADHD may perceive more impairment than adolescent boys with the disorder, which needs be explored further. As regards self-ratings, the combined presentation of ADHD was found to be associated with the highest levels of functional impairment, indicating that the number of currently fulfilled ADHD symptoms could influence self-perceived impairment in daily life. Further, our study confirmed earlier evidence of inattention as a strong associated predictor of impairment in school, and indicated that interventions that can decrease symptoms of inattention and/or teach adolescents and their networks how to compensate for attentional deficits are warranted. Moreover, both emotional problems and conduct problems were significantly associated with impairment in several life domains, which highlights the need of assessing and treating comorbid symptoms in adolescents with ADHD. In addition, the poor to moderate agreement between self-ratings and parental ratings of functional impairment underscore the importance of using multiple informants, including the adolescents themselves, in both research and clinical practice with this group.Additional file 1: Table S1. Kruskal-Wallis H-test with pairwise comparisons of functional impairment across combinations of group and sex.


The improvement of technological progress can reduce the emissions of SO2 and PM2.5. Still, the results indicate that the reduction effect of these two pollutants originates from the treatment process rather than reducing the source of the production side. The inability of technological advancement to reduce CO2 emissions suggests some carbon lock-in in China’s technological advancement. The Chinese government should increase the proportion of new energy applications and reduce the production methods of polluting industries to reduce pollutants effectively.Current research on technological progress does not focus on whether there is a biased selection of technological progress based on the resulting pollutant emissions and the emission reduction effect. This paper measures green total factor productivity for 30 provinces in China from 2004–2018 and tests whether technological progress is selectively biased towards the pollutants emitted. The results find a selective bias of technological progress on pollutant emissions, and there is also heterogeneity in the selective bias across regions. The current level of technological progress is on the right side of the inverted U-shaped inflection point for SO More seriously, in 2011 and 2015, several Chinese provinces experienced PM2.5 explosions with pollution levels reaching up to 1155 μg/m3, and serious environmental pollution problems will pose a significant threat to the health of residents [2.5 and PM10 as the primary pollutants was 74.2% and 20.4%, respectively [China’s economy has been reformed and opened up for more than 40 years and has made brilliant achievements in the economic field. However, since the reform and opening up, China’s economy has been in a rough economic development model for many years, making China’s environmental pollution problem increasingly serious. According to the World Health Organization (WHO), air pollution causes nearly 7 million deaths worldwide each year. As one of the most polluted countries globally, China has endured haze pollution, acid rain, and excessive greenhouse gas emissions that continue to plague the country in the fall and winter of recent years ,2. Accorectively . Numerouectively ,9.In the face of severe environmental problems and the need to transform the economic development model, China has continued to transition to a greener economy in recent years. The key is to promote technological innovation to achieve pollution reduction and sustainable economic development . HoweverThe invention of the steam engine set off a wave of the industrial revolution. It also brought about quite serious pollution events such as the London toxic fog that caused thousands of deaths ,16. Some2.5, SO2, and CO2 levels and technological progress consistent with the inverted U-shaped relationship of the environmental Kuznets curve [2.5 [2 and have not paid attention to the bias of technological progress for multiple types of undesirable outputs [However, in the face of the multiple pollutants embedded in the environmental pollution brought about by the rough economic development, can the promotion of technology effectively reduce the emissions of all pollutants? Is the relationship between the action of air pollutants represented by PMts curve ,34? Althrve [2.5 ,36, is trve [2.5 ,36. Biasrve [2.5 ,38,39,40rve [2.5 ,42,43. M outputs ,44,45,46In this paper, based on the existing studies, we measure the green total factor productivity of Chinese provincial panel data and decompose the green technological progress from it; secondly, we verify the possible inverted U-shaped relationship between multiple air pollutants and technological progress. Then, this paper analyzes the bias of technological progress for emission reduction among different pollutants in detail to investigate whether there is a preference for different types of pollutants and whether there is heterogeneity in the bias of technological progress among different provinces in China. Finally, the selective bias of technological progress on pollution emissions is empirically analyzed by means of an econometric model to verify the analysis made in the previous paper.Compared with previous studies, the marginal contributions of this paper are as follows. (1) Verifying whether the inverted U-shaped relationship between multiple air pollutants and technological progress holds. (2) Decompose technological progress and analyze the bias of output-based technological progress for different kinds of air pollutants. (3) Analysis of the possible bias of pollutant emission reduction in different provinces in China and attempt to explain the bias that causes different biases among different provinces. (4) To verify the bias of output-based technological progress for different types of air pollutants by using econometric models. By solving the above problems, this paper hopes to provide suggestions for China to adjust its environmental protection policies.This section presents the econometric models involved in this paper, where the DEA-SBM  model is used to measure green total factor productivity and describes the process of decomposing it into technological progress and technological progress bias. The regression model is a validation of the inverted U-shaped relationship between multiple pollutants and technological progress and empirical analysis of socioeconomic factors.Among the methods for measuring total factor productivity, the DEA model approach can be used for multiple inputs and outputs and does not require constructing a production function to estimate the parameters, thus avoiding the errors associated with an artificially set production framework. Therefore, the DEA model is selected in this paper to estimate the required total factor productivity. The traditional DEA model fails to solve the problem of slack variables better when measuring efficiency evaluation. Therefore, in this paper, we adopt the SBM model proposed by Tone , with unIn this study, we use Chinese province panel data, wherein each of the 30 provinces is made a production decision unit DMU to construct the optimal production frontier of China in each period. Each province uses M kinds of inputs to obtain S kinds of desired outputs and I kinds of non-desired outputs, then the DEA-SBM model can speak about the production process of Chinese provinces as:mth input of the kth DMU, the pth desired output, and the qth undesired output, respectively. kth DMU environment, where less than 1 means that the kth DMU is inefficient.According to Equation (1), the DEA-SBM model for undesired output can be written as:TFP) growth rate is decomposed into technological change (TC) and efficiency change (EC). We further decompose technological change into output-biased technological progress (OBTC) and input-biased technological progress (IBTC) and magnitude of technological change (MATC).This study constructs the Malmquist index distance function in conjunction with the SBM model dealing with undesirable output. According to the Malmquist exponential decomposition method, the total factor productivity , the technology bias index can be decomposed into input-biased technological progress and output-biased technological progress indices as follows:After decomposed TFP Fare , decompoMATC represents the scale effect of technological progress, refers to the neutral transfer of the technological frontier, while BTC means the bias of technological progress refers to the “non-neutral” transfer of the technological frontier. IBTC and OBTC reflect the impact of input and output changes on technological progress. If IBTC (OBTC) > 1 (<1), indicates progress (regression) in input-biased technology. When IBTC and OBTC = 1, it means that the technology change is Hicks-neutral.OBTC > 1 indicates a OBTC < 1 indicates a OBTC = 1, the output-biased technological change is Hicks-neutral. When OBTC > 1 indicates a OBTC < 1 indicates a It needs to be pointed out that output-based technological progress bias refers to the ability of technological progress to produce more output when the input factors are unchanged. We draw on the ideas of Weber and Domazlicky  and Li eThis paper will focus on analyzing the output bias of technological progress. The specific descriptions of technical bias relationships are listed in 2, SO2, and PM2.5. Therefore, the quadratic term of technological progress is introduced when constructing the mechanism of the effect of technological progress on pollutants to draw relevant conclusions in favor of reducing environmental pollution.In general, the relationship between the impact of technological progress on environmental pollution has not yet reached a unified conclusion. One view is that the abatement effect of technological progress on pollutants cannot offset the environmental pollution caused by the increase in production efficiency brought about by technological progress. There is also a view that the reduction effect of technological progress and pollutants is in line with the inverted Kuznets U-curve for the environment. When a country’s technological progress is on the left side of the inflection point, and the technological progress itself is based on the fossil energy-based industrial system, the essence of its technological innovation is with pollution attributes. Its pollution reduction effect is necessarily limited. When the level of technological progress is on the right side of the inflection point, then the technological progress is biased toward the use of clean energy, with environmental attributes. The progress of technology can promote pollution reduction. According to the above idea, to further explore the relationship between technological progress and pollutants, the scatter fit of the relationship between technological progress and pollutants required for the analysis of this paper is shown in 2, SO2, and PM2.5, The model is set up as follows.(1)Labor input. Labor input is measured using the number of employed persons in each province of China, and the data are obtained from the statistical yearbooks of each province of China.(2)Capital input. The amount of completed fixed asset investment in each province of China is used to measure capital input. The data are obtained from the statistical yearbooks of each province of China.(3)Energy input. We use the data of energy consumption of each province in China; the data come from the China Energy Statistical Yearbook.(4)Desired output. Nominal GDP data of each province in China are used and deflated to real GDP using CPI index, data from China Statistical Yearbook.(5)2 is the converted emissions from energy consumption in each province, and the conversion method uses the carbon emission calculation method in the Guidelines for National Greenhouse Gas Inventories prepared by the Intergovernmental Panel on Climate Change .Undesired output. We use pollution data for each province in China, where COIn this paper, we use Chinese provincial panel data for green total factor productivity measurement. Based on the availability and reliability of the data, we set the time span of the study as 2004–2018 and apply the DEA-SBM model to measure China’s green total factor productivity based on input-output data of 30 Chinese provinces (except Tibet), and decompose the technological progress and biased technological progress from green total factor productivity. The input-output data and processing are as follows.2 represents the amount of carbon dioxide emissions to be estimated, The calculation formula is:2 is obtained from the industrial emission data of each province, and the data are obtained from the China Environmental Statistical Yearbook. PM2.5 is satellite gridded data measured by the Atmospheric Composition Analysis Group at Dalhousie University, Canada ).SOTo determine the relationship between technological progress and pollutants, this paper also includes variables such as Economic Development Level, Energy Structure, Industrial Structure, Human Resources, and Foreign Direct Investment in the econometric model. Energy Structure (ES): The proportion of coal energy consumption to total energy consumption is used to measure the regional energy consumption structure. The higher the level of this variable, the less green the region is.Industrial Structure (IS): Measured by the proportion of the output value of the secondary industry in the region’s GDP, the higher the level of this variable, the more the region’s economic development relies on the industry.Human Capital (HC): Human capital refers to the degree of knowledge, skills, and quantity of labor in the workforce. Regions with higher human capital tend to have more advanced technological standards and higher environmental awareness. Higher human capital is beneficial to local environmental improvement, and this paper uses the number of years of education per employed person to measure the level of human capital.Foreign Direct Investment (FDI): The current research findings on FDI are not uniform, and some studies suggest that foreign investment will cause the transfer of polluting industries from developed countries to developing countries, leading to environmental pollution in host countries ,52. SomeEconomic Level (EL): There is a strong correlation between the level of economic development and the environmental pollution problem. Early economic development often came at the expense of the environment, which also led to serious environmental pollution in China, and with the economic model change in recent years, China’s environmental problems have not been properly solved. In this paper, the GDP per capita of each province in China is selected to measure the economic development level of the region.The data of the above economic data variables are taken from the China Statistical Yearbook and the statistical yearbooks of each province, and the energy variables are taken from the China Environmental Statistical Yearbook, and the descriptive statistics of each indicator are shown in Table 2To better understand the technological progress of each province in China from 2004 to 2018, this paper measures the green total factor productivity of each province in China and decomposes it into technological progress and technical efficiency. Further, this paper decomposes technological progress into biased technological progress (BTC), including input-biased technological progress (IBTC) and output-biased technological progress (OBTC). The green total factor productivity and its decomposition terms for China as a whole and for each province are shown in From 2 is still on a rising trend year by year, SO2 is on a decreasing trend in general, PM2.5 is on a rising trend first and then on a decreasing trend, and the inflection point of SO2 is later than the inflection point of PM2.5. These three pollutants differ in their reduction effects. They have heterogeneity in their reduction times, indicating a certain bias in reducing different pollutants at different stages of China’s economic development process. Based on the previous principle of output-based technological progress bias, we measured the characteristics of output technology bias elements for China as a whole and each province, as shown in 2 output has been on an upward trend, while in contrast, SO2 and PM2.5 are clearly on a downward trend, with PM2.5 showing an upward and then a downward trend, a result that is corroborated by the changes in pollutant concentrations in China.With the different needs of the times, China’s economic development model is also changing, which has different requirements for the technological progress behaviors such as technological innovation and technology introduction in the production process, i.e., the production process has different factor bias for the input process and output factor process. During the pursuit of high economic growth, this brash development model determined that the production process tended to ignore environmental protection, resulting in serious environmental pollution problems. In recent years, China’s economic development model has changed from pursuing high growth to the pursuit of sustainable and high-quality economic growth, and the demand for environmental protection has been gradually increasing. Therefore, an analysis of the elements of China’s technological progress bias will allow us to analyze whether China’s technological progress is free from “carbon lock-in” and whether there is a bias for pollutant reduction among pollutants. In order to better understand whether the bias of China’s technological progress has a bias among various pollutants, the average values of pollutant concentrations in each province of China were processed, as shown in 2 < PM2.5 < SO2. The eastern region shows the output preference of PM2.5 < CO2 < SO2 < GDP. However, as time progresses, the output of PM2.5 and SO2 show a decreasing trend. In contrast, CO2 still shows an increasing trend, indicating that fossil combustion is still the main energy supply system in these regions. There is a “carbon lock-in effect” in technological progress. Still, the emission of pollutants such as PM2.5 and SO2 has decreased due to the due to China’s increased control of industrial emissions and the upgrading of environmental processes and equipment such as flue gas desulfurization treatment. There is also a shift in the pollution chain within China, with heavy polluting industries moving from economically developed regions to less economically developed regions, also contributing to pollution problems in inland provinces. The northeast, central, and western regions of China have always been economically less developed regions that rely mainly on industry, and the technology level and energy structure of these regions are less developed, and their pollution reduction capacity lags behind that of the eastern regions. The results of the above analyses show that although the overall emissions of pollutants such as PM2.5 and SO2 have been reduced in China, its production side still favors a production model with pollution attributes, and the reduction of its pollutant concentration is probably due to the increased control of pollutant production and the level of pollutant treatment processes, and CO2 emissions do not show a decreasing trend. This indicates that China’s overall energy structure is still dominated by fossil fuels as the main production system, and there is a certain “carbon lock-in effect” in its technological progress, which promotes the transformation of technology to cleaner production and energy conservation and environmental protection, while there may also be a certain pollution phenomenon caused by the expansion of production due to technological improvement.Due to the vast territory of China and the large differences in economic structure and technology levels among various regions, this paper summarizes the pollution emission bias of four major economic regions in China, including the northeast, central, eastern, and western regions, after dividing China into four major economic sub-regions, and finds that in general, the northeast, central, and western regions show GDP < CO2, PM2.5, SO2, and technological progress all show an inverted U-shaped relationship, indicating a significant increase and then decrease between pollutants and technological progress. The primary and secondary term coefficients of the variables all pass the significance level test. From the results of the model, the inflection point between technological progress and CO2 is 1.343, and the average value of LnTC in China’s provinces in 2018 is 1.130, which is still on the left side of the inflection point, so the current technological progress has not yet exerted an emission reduction effect on CO2. The inverted U-shaped inflection point of technological progress for SO2 is 1.08, and the current level of technological progress in China is already on the right side of the inflection point. The increase in the level of technological progress contributes to the reduction of SO2 concentration, which is also verified in the previous graph about SO2 concentration. The inverted U-shaped inflection point of technological progress for PM2.5 is 1.052, indicating that China’s technological level is on the right side of the inflection point. The improvement of technological progress can effectively reduce PM2.5 emissions. From the model results, there is a selective bias in the pollution emissions of technological progress in China. For CO2, technological advancement cannot reduce CO2 production, which indicates that there is a certain “carbon lock-in effect” in China’s current economic situation. However, technological advancement can effectively reduce SO2 and PM2.5 concentrations, probably because China started to control SO2 emissions in the early 20th century and has formulated a series of measures and policies to reduce SO2 pollution, and has technically realized the treatment of SO2 emissions and PM2.5 as the main pollutants of urban haze pollution, and its harm is self-evident. The government at all levels in China has made a lot of efforts to reduce haze pollution and achieve the goal of PM2.5 emission reduction. In terms of the influencing factors of pollutants, energy structure has a positive relationship with pollutant concentration, indicating that the larger the proportion of coal energy in energy consumption, the more serious the pollution. Industrial structure has a positive relationship with pollutant concentration, indicating that the greater the proportion of the industrial economy, the more serious the pollution. The coefficient of FDI is negative for CO2 and SO2 and positive for PM2.5, indicating that current foreign direct investment in China can reduce CO2 and SO2 pollution but increase PM2.5 pollution, which may be related to the production projects or production processes of foreign investment in China. The positive relationship between the level of economic development and CO2 and PM2.5 indicates that the phenomenon of economic development accompanied by environmental pollution still exists.(1)2, PM2.5, and SO2 have an inverted U-shaped relationship with technological progress. As the level of technological progress increases, SO2 and PM2.5 emissions are significantly suppressed, and the level of technology breaks the inflection point of the inverted U-shape. As for CO2, the improvement in technology level has not yet played a significant role in reducing CO2 emissions, which indicates that there is a certain “carbon locking effect” and “energy rebound effect” in China’s technological progress, and also indicates that China has not yet shifted from its crude economic development model.There is a selection bias for pollutant emissions in China’s technological progress. CO(2)2 output is steadily increasing, SO2 is decreasing, and PM2.5 is increasing and then decreasing. This is corroborated by the changes in pollutant concentrations. However, due to the vast geographical area of China, there are obvious differences in economic structure and technological level among different regions, and their output-based technological progress bias factors also differ. In general, the northeast, central, and western regions show the output bias of GDP < CO2 < PM2.5 < SO2, while the eastern region shows the output preference of PM2.5 < CO2 < SO2 < GDP. However, as time progresses, the output of both PM2.5 and SO2 shows a decreasing trend, while CO2 still shows an increasing trend, indicating that fossil combustion is still the main energy supply system in these regions, and there is a “carbon lock-in effect” in technological progress, and China’s emission treatment technologies for both PM2.5 and SO2 are more mature, achieving the emission of both pollutants. China’s emission treatment technology for PM2.5 and SO2 is more mature and has achieved the reduction of these two pollutants.From the perspective of the output-based technological progress bias factor, it can be seen that the output-based technological progress bias in CO(3)2 and PM2.5, indicating that China’s technological progress has a carbon lock-in effect and economic development is still accompanied by environmental pollution, indicating that China has not ended the brutal economic development mode during the study period and is still in the process of economic transformation.In terms of pollutant influencing factors, energy structure and industrial structure are positively related to pollutants, and its economic development is also positively related to COTechnological progress is of great importance in the process of pollution reduction. However, there are “carbon lock-in” and “energy rebound” effects in the relationship between technological progress and pollutants, increasing technological level not necessarily reducing the concentration of pollutants. To investigate the relationship between technological progress and pollutants in China, this paper uses the DEA-SBM model to measure the green total factor productivity of 30 Chinese provinces, decomposes the technological progress index from the green total factor productivity, and decomposes the technological progress index into output-based technological progress bias and input-based technological progress bias. Combining the results of China’s pollutant concentration map and output-based technological progress bias factors, this paper finds that biased emissions of pollutants exist in all regions of China. This result is corroborated by the analysis of the influencing factors of pollutants. Combining these analyses, the results show that:(1)Strengthen government support to guide technological innovation. The government should fully support technological innovation and other behaviors in terms of policies, such as subsidies and tax incentives for R&D and application of clean technologies, to promote technological progress in each region to cross the inverted U-shaped inflection point in carbon emissions. At the same time, the government should actively guide research institutes and other research institutes to cooperate with enterprises to better transform and apply clean technologies.(2)2 emissions being the primary target of all pollutants. The reduction of SO2 and PM2.5 pollution concentrations is attributed to the Chinese government controlling these two pollutants’ emissions and the technological progress of pollutant treatment processes. However, there are still pollutant outputs at the source of production. Moreover, from the results of this paper, there is a “carbon lock-in effect” in China’s economy. The coal-based energy consumption structure makes the emission of CO2 and other pollutants more serious, and increasing the proportion of new energy applications such as photovoltaic, wind power, and hydropower can effectively reduce the output of pollutants on the production side.Increase the proportion of new energy applications and eliminate the carbon lock-in effect. China’s economic model is still in transition from the pursuit of economic growth to high-quality development, and the pollution problems accompanying economic development have existed for a long time, with CO(3)Promote the development of technology to be clean and green. China’s existing production system is based on fossil energy. Transitioning to clean, green development can effectively reduce the pollutant emissions in the production process, as can strengthening technology research and development, enhancing the learning effect of foreign investment, and taking other actions to help improve the level of technological progress.(4)Actively guide the technology exchange between regions and promote the transformation of industries to a low-pollution direction. The northeast, central, and western regions show an overall preference for pollutant emissions, which is due to the less developed production levels dominating these regions. Actively guiding these regions and the developed eastern regions in technology exchange and cooperation, breaking the technical barriers between regions, and promoting the transfer and diffusion of advanced clean production technologies from the eastern regions to these regions will help these regions to improve their technology levels. The government should promote the transformation of industries in a low-pollution direction and promote the transformation of regional industries in a green direction, facing the obvious differences in economic structure and technology level between the regions that exist. To promote the transformation of regions with underdeveloped production capacity and polluting industries to low-pollution production methods, the government should introduce policies including subsidies for the renewal of clean equipment so that regions with polluting industries can end the status of rough economic development.This paper analyzes green total factor productivity and technological progress in China, and investigates the output bias of technological progress on the output relationship of multiple pollutants. The findings effectively enrich the research related to technological progress and environmental protection, and provide theoretical support for the Chinese government to adjust its environmental protection and production policies. Based on the results of the above analysis, this paper gives the following recommendations.


Bartonella spp. in mongooses and their fleas from St. Kitts. Spleen (n = 54), blood (n = 71), and pooled flea samples, all identified as Ctenocephalides felis (n = 53), were submitted to TaqMan real-time quantitative PCR (qPCR) targeting Bartonella-nuoG fragment (84 bp). Positive samples underwent further conventional PCR assays targeting five loci , subsequent sequencing, and phylogenetic and haplotype analyses. The overall occurrence of Bartonella spp. in mongooses and fleas was 51.2% (64/125 [95% CI (42.1–60.2%)]) and 62.3% (33/53) [95% CI (47.9–75.2%)]), respectively. From samples sequenced across the five loci, 50.8% (33/65) were identified as Bartonella henselae, 26.2% (17/65) were 96.74–99.01% similar by BLAST analysis to an unidentified Bartonella sp. previously reported in Japanese badgers (Meles anakuma), and 23.1% (15/65) were co-infected with both species. Nucleotide polymorphism analysis showed low diversity amongst haplotypes but did concur with phylogenetic analysis, placing the unidentified species in a separate clade from B. henselae by multiple mutational events. Our data confirms that mongooses and Ctenocephalides felis fleas collected from them are not only potential reservoirs for B. henselae but also a novel Bartonella sp. which we propose be called ‘Candidatus Bartonella kittensis’. This study aimed to molecularly survey and evaluate the genetic diversity of  Bartonella is a genus in the order Rhizobiales that contains fastidious, Gram-negative, hemotropic, pleomorphic bacteria that are typically transmitted through arthropods ) . In regies felis , or direAnimal capture and handling was approved by the Animal Use Ethics Committee of University of Montreal (CÉUA 19-Rech-1993 and 19-Rech-1945), and further endorsed by the Ross University School of Veterinary Medicine (RUSVM) Institutional Animal Care and Use Committee (IACUC #TSU7.24.19). 2 plot known to be populated with mongooses located in Saint Peter parish and consisting of subtropical dry forest.The samples utilized in this study were collected for an unrelated studying aiming to assess the epidemiology of the highly invasive mongoose and factors affecting trapping success and depopulation strategies . SamplinMongooses were captured in cages  in June 2019. Traps were baited with canned tuna in water and checked in the morning and late afternoon, daily. Captured mongooses were immobilized with Zoletil 100  at around 15–20 mg/kg intramuscularly before being euthanized via intra-cardiac injection of saturated potassium chloride (75–100 mg/kg) as per the American Veterinary Medical Association Guidelines . Death wAnimals were captured in August 2019 and January 2020, as above except that traps were baited daily and checked within 24 h. Animals were immobilized , and bled by venipuncture of the cranial vena cava. After a Passive Integrated Transponder (PIT) tag  was attached, and the animals recovered from sedation, they were released in the same trapping location. A total of 71 blood samples (0.5 to 1 cc of whole blood in EDTA) obtained from trapped mongooses were transported on ice to reach RUSVM within 5 h of collection and stored at −20 °C, until DNA extraction. n = 53), 10 mg of the macerated spleen suspensions (n = 54) and 200 µL aliquots of the whole blood samples in EDTA (n = 71) with E.Z.N.A Tissue DNA Kit  as per the manufacturer’s instructions (100 µL elution). Fleas were briefly washed with 70% alcohol at the time of microscopic identification  and then260/OD280) yielded an estimate for sample purity and ratios of 1.8 ± 0.2 were deemed pure. To minimize the negative impact of excessive DNA on qPCR efficiency ), 1 µL of DNA template and 0.4 µL of sterile nuclease-free water . qPCR assays were conducted on Low-Profile Multiplate™ unskirted PCR plates  in a CFX96 thermal cycler  [E) was calculated from the slope of the standard curve in each run using the following formula (E = 10−1/slope) [7 to 2.0 × 100) of a gBlock®  encoding an 83 bp fragment of the nuoG gene of B. henselae . The number of gBlock® copies was determined according to the formula [Xg μL−1 DNA/(gBlock® length (BP) × 660) × 6.022 × 1023 × gBlock® copies μL−1]. Bartonella henselae DNA was used as a positive control  of the mongooses were positive for Bartonella spp. with the qPCR targeting the nuoG gene  (Bartonella spp. ranged from 4.74 × 10−2 to 1.92 × 102nuoG-copies/μL (mean = 2.20 × 10), with higher concentrations observed in the blood (4.15 × 10−1 to 1.92 × 102) when compared to spleens (4.74 × 10−2 to 1.15 × 100). One third ]) of the spleen samples and 64.7% (46/71) [95% CI (52.5–75.8%)] of the whole blood samples were positive in the qPCR targeting the ± 3.076) . Thirty-nuoG qPCR . Twenty pooled (20/33) flea samples had consistent Cq values (Mean = 27.92 ± 4.46) and the quantification of Bartonella spp. ranged from 2.73× 10−1 to 6.55 × 103 nuoG-copies/μL (mean ± SD = 1.13 × 103 ± 2 × 103). A high percentage of the pooled flea samples ]) were positive for in the Bartonella-qPCR quantification assays, thus their Cq and quantification results are not reported in the present work.A total of 41/97  positive samples had inconsistent Bartonella spp. nuoG-qPCR positive samples , 95.9% (93/97) [95% CI (89.8–98.9%)] were also positive for at least one other of the genes we tested by cPCR: 92.9% (90/97) for rpoB, 87.6% (85/97) for gltA, 83.5% (81/97) for nuoG, 70.1% (68/97) for ITS and 65.0% (63/97) for ftsZ  as Bartonella sp. previously detected in M. anakuma. The remaining 15/65 (23.1%) samples were co-positive to both B. henselae and Bartonella sp.   were retrieved from a total of 65 DNA samples . From this, 33/65 (50.8%) samples were identified by BLASTn as  spleen) .Bartonella spp. gltA gene placed the 42 obtained sequences into two distinct clades  and fleas from Chile ; and the other closely related to Bartonella sp. previously detected in M. anakuma from Japan  with 100% branch support , cats from Brazil and Guatemala , a human from Brazil (EF196804), and mongooses from Grenada . The other clade, as above, included Bartonella sp. in M. anakuma from Japan (CP019788) with 100% branch support  with 100% branch support. In addition, the ITS phylogeny closely positioned the Bartonella sp. in mongooses to a previous Bartonella sp. detected in fleas from St Kitts (MT048286). Similarly, the phylogenetic trees for o clades . The firftsZ clustered the obtained sequences into a single clade containing B. henselae sequences in a dog from China (JQ009431), human from Germany (CP020742) and cat from Guatemala (KP822811). In contrast, the phylogenetic tree for Bartonella species when more than one sequence corresponding to different target genes was available. Samples 30S, 49S, 1B, 21B, 22B, 46B, 48B, 50B, 53B, 67B, 71B, 7F, 12F, 16F, and 54F clustered with B. henselae in at least one gene and Bartonella sp. from M. anakuma in another gene  and #2 (B. henselae) from Saint Kitts were separated by many mutational events. Corroborating with the phylogenetic inferences, while haplotypes #4 and #5 formed a clade that was more closely related to Bartonella sp. haplotype #6 (M. anakuma); haplotypes #1 and #2 formed a clade including B. henselae sequences from Chile and Brazil. The haplotype analysis based on 50 plotypes . Haplotyal event , whereasBartonella rpoB analyzed sequences, including 47 obtained in the present study and 30 Bartonella previously detected in domestic and wild cats worldwide, rodents, and Japanese badger, four different haplotypes were obtained , lions (South Africa), cheetahs (Zimbawe), mountain lions (USA), mongoose (Grenada), rats , and rodents (Thailand). Haplotype #4 consisted of B. henselae sequences obtained in the present study and previously detected in mongooses (Grenada), cats (Brazil), and lions (South Africa). Bartonella sp. haplotypes #1 and #2 formed a clade and arose from a common median vector which may reflect an unsampled sequence from extant species or extinct ancestral sequence  identified five haplotypes (B. henselae sequences from the present study (mongoose on St. Kitts), a human from Germany and fleas from Spain. Haplotypes #2 and #3 consisted of B. henselae from mongooses in the present study and a cat from Guatemala, respectively. Haplotypes #4 (mongoose from St. Kitts) and #5 (M. anakuma from Japan) arose from a common median vector. Haplotypes #2 and #4 were only detected in St. Kitts. The haplotype analysis of plotypes . HaplotyBartonella ITS including 25 from this study and 8 from various animal species worldwide including cats, dogs, and humans from Brazil, cheetahs from Zimbabwe, lions from Africa, and a flea from Austria  and Haplotype #4 (Bartonella sp. from M. anakuma), both separated by a median vector and several mutational events.Four haplotypes were identified from the 33 sequences used for  Austria . A commoftsZ sequences including 21 from this study yielded five haplotypes  . Of the Bartonella henselae was previously described in mongooses from Japan [Bartonella in mongooses and their fleas from St. Kitts. Bartonelloses are re-emerging infectious diseases with wildlife acting as major reservoirs for many of the zoonotic species. Traditionally viewed as self-limiting illnesses, these infections have now been implicated in a wide spectrum of human conditions, highlighting the importance of understanding the role of wildlife in the maintenance and spread of disease . Bartoneom Japan  and Grenom Japan  and in mom Japan . To the B. henselae is the most prevalent Bartonella species [B. henselae, as previously described in Japan [C. felis is the main vector for B. henselae among cats [Bartonella reservoirs in mongooses [The superorder Feliformia includes both domestic and big cats , civets, hyaenas, and mongooses . Among t species . This isin Japan  and Grenin Japan . The catong cats , commonlong cats  and is bongooses ,22. B. henselae were detected in mongooses and C. felis fleas from this study. One haplotype was not previously described in other geographic locations, while the other was widely distributed and shared between mongooses, domestic and wild cats, cat fleas, and humans [B. henselae from St. Kitts to be 100.00% identical to B. henselae strain Houston-1 from a human in Germany [B. henselae strains in both mongooses and felines of St. Kitts by culturing and multi-locus sequence typing (MLST) in the future [For each of the five loci, two haplotypes of d humans ,35,54,55 Germany ,22. Hous Germany . Therefoe future . gltA, two haplotypes of an undescribed Bartonella sp. were found circulating within the mongoose population of St. Kitts and for rpoB, nuoG and ITS, one haplotype of this species was observed. Previously detected in fleas from mongooses from the country [Bartonella sp. obtained from Japanese badgers (M. anakuma). nBLAST analysis revealed B. clarridgeiae as the closest identified species to this Bartonella sp. . According to La Scola et al., gltA and rpoB have great discriminatory power and can be used for determining novel Bartonella species based on the percentage of identity, compared to recognized species available in GenBank [Bartonella should be considered new species if a 327-bp gltA fragment shares < 96.0% or an 825-bp rpoB fragment shares < 95.4% similarity to validated species. In our study, a total of four gltA fragments met the criteria for determining a novel species . Likewise, rpoB sequences showed a low percentage of identity (95.95–6.71%) to B. clarridgeiae, however, fragments were shorter than the ones recommended by La Scola et al., precluding their use in this criterion.For  country , the seq GenBank . BartonegltA, rpoB, nuoG, ITS) revealed B. clarridgeiae as the closest identified species to this Bartonella sp. Even though the previous study of fleas from mongooses in St. Kitts [B. henselae, phylogenetic analyses based on four loci positioned the bacteria closest to Bartonella sp. detected in M. anakuma. Furthermore, the haplotype analysis (of four loci) demonstrated this unidentified species as being distinct from B. henselae, separated by many mutational events. The nBLAST findings, in addition to phylogenetic and haplotype analyzes of the four loci, support the classification of a novel species of Bartonella in mongooses and their C. felis fleas from St. Kitts, which we propose should be named ‘Candidatus Bartonella kittensis’. Bacterial culture must be performed in the future studies to fully characterize this novel species [Candidatus for incompletely described procaryotes based on gene sequencing (prior to culture), is common, as seen with Candidatus Bartonella mayotimonensis’ and ‘Candidatus Bartonella merieuxii’ [Similar to the nBLAST results, phylogenetic analysis of four loci  [2) [Bartonella nuoG [The present study reports the highest molecular occurrence (51.2%) of  (15.9%)  and Gren (15.9%)  are like (15.9%) . More sp.9%) [2)  may favolla nuoG  may havella nuoG . The qPClla nuoG . Direct Bartonella spp. nuoG-copies/µL in mongooses from St. Kitts was lower than that described in naturally infected cats from both southern Chile [Bartonella DNA copies is explained by its infection strategy, which results in chronic, asymptomatic, transient, and often undetectable infections in reservoirs species [Bartonella spp. nuoG-copies was not possible in many of the tested samples due to discrepancies in Cq values. This may be a manifestation of the Monte Carlo effect, observed in samples with low initial DNA copies [The mean number of rn Chile  and Brazrn Chile  using th species . AbsolutA copies . Bartonella DNA loads and lower occurrence were observed in the spleens when compared to blood. This could be explained by the dilution of spleen DNA samples prior to PCR amplification. However, similar findings were observed in mongooses from Grenada, where mixed tissues, including spleen, lymph node, and liver showed a lower Bartonella spp. prevalence  than blood samples  [Bartonella infections, filtering and retaining infected erythrocytes, rather than acting as an infective niche [Bartonella infections [Bartonella replicates within erythrocytes [Bartonella birtlesii recovery (CFU) from spleens in the early stages of infection compared to higher concentrations in blood seven-days post-infection [In this study, lower , 18/51) . Differeve niche . Accordifections . Moreovehrocytes , possiblnfection .Bartonella sequences from the present study and those species described worldwide. Genomic variety between various strains of B. henselae is less than 1.00% and low haplotype diversity is an expected finding [gltA gene  [gltA analyses from bats  and rodents  from Brazil, in which the diversity of Bartonella is much higher [The low haplotype diversity observed across all five genes is suggestive of high intraspecies similarities between the  finding . Finding = 0.01) . This coh higher ,13.Bartonella species adapt to specific environmental and ecological niches and co-evolve for optimal infection of a given vector and reservoir host [Candidatus Bartonella kittensis’ may reflect a species seen only in mongooses and their associated cat fleas. The potential for this novel species to infect cats through the common vector, C. felis is yet to be determined, however, this species was not observed in previous molecular surveys of cats from St. Kitts [oir host . Novel ‘t. Kitts . FurtherBartonella was prevalent in Small Indian mongooses and C. felis collected from them in St. Kitts. Mongooses and C. felis from St. Kitts are potential reservoirs for B. henselae and a novel species closely related to Bartonella sp. from Japanese badgers, proposed to be named ‘Candidatus Bartonella kittensis’. Lowly diverse