Dopaminergic system dysfunction is involved in schizophrenia (SCZ) pathogenesis and can mediate SCZ-related motor disorders. Recent studies have gradually revealed that SCZ susceptibility and the associated motor symptoms can be mediated by genetic factors, including dopaminergic genes. More importantly, polymorphisms in these genes are associated with both antipsychotic drug sensitivity and adverse effects. The study of genetic polymorphisms in the dopaminergic system may help to optimize individualized drug strategies for SCZ patients. This review summarizes the current progress about the involvement of the dopamine system in SCZ-associated motor disorders and the motor-related adverse effects after antipsychotic treatment, with a special focus on polymorphisms in dopaminergic genes. We hypothesize that the genetic profile of the dopaminergic system mediates both SCZ-associated motor deficits associated and antipsychotic drug-related adverse effects. The study of dopaminergic gene polymorphisms may help to predict drug efficacy and decrease adverse effects, thereby optimizing treatment strategies. Schizophrenia (SCZ), characterized as a combination of hallucinations, delusions, disorganization, and other cognitive or emotional deficits, shows an average prevalence of ~1%  , DAT (SLC6A3), and D2R (DRD2) in SCZ pathology, with particular interest in SNPs loci.In the next section, we will briefly discuss the implications of polymorphisms in three major dopaminergic genes, catechol-O-methyltransferase  to methionine (Met) substitution at the rs4680 loci of COMT has been widely studied. In particular, the homozygous Val allele showed remarkably reduced cortical dopamine activity , downstream of COMT, potentially regulate SCZ risk  gene are potentially associated with resistance to atypical antipsychotics in SCZ patients (Szekeres et al., COMT (Zivkovic et al., COMT A-G haplotype (Lafuente et al., Although pharmacogenetics enabled investigating the relation between antipsychotic drug effects and dopaminergic gene polymorphisms, inconsistent or even contradictory results are frequently obtained. Some studies reported no association between EPS and gene polymorphisms in D2R, DAT, and COMT genes or other dopamine metabolic or transporter genes (Tybura et al., COMT SNP may cause altered dopamine clearance levels, influencing antipsychotic effects and motor disorders. DAT is responsible for dopamine transport, and DAT expression level and protein structure may alter dopaminergic transmission strength. Dopamine targets and binds specific receptors from D1R to D4R, which have region-specific patterns (Laurier et al., We believe that the adverse effects of antipsychotics can be further interpreted in a systemic view of dopamine homeostasis, because SCZ onset and progression affect different aspects of dopamine transmission. COMT is crucial for cortical dopamine degradation to terminate dopamine action within the synaptic cleft. COMT being a major dopamine catabolic enzyme, Studies on molecular mechanisms of the dopamine system in SCZ pathogenesis and the adverse effects of antipsychotics mainly include investigation of receptor binding affinity and the downstream signal transduction pathways involved. Recently, G-protein coupled receptor dimerization was suggested in dopaminergic regulation. D1R and D2R can form receptor heterodimers (Dziedzicka-Wasylewska et al., We present a brief review of the relation of dopaminergic genes with SCZ pathogenesis and antipsychotic treatment-related adverse effects. We focused on motor deficits associated with SCZ or antipsychotic drug administration and the role of dopamine system and gene polymorphism-based modulation. We propose that dopaminergic gene polymorphisms influence both SCZ-associated motor deficits and antipsychotic drug-induced motor dysfunction . More imDopamine system aberrations are strongly associated with schizophrenia symptoms, including motor disorders, and both antipsychotic action and adverse effects, including motor disorders. Thus, investigating dopaminergic gene polymorphisms may help to predict drug efficacy and decrease adverse effects, thereby optimizing treatment strategies.JY, FJ, DJ, XL, GC and WZ collected research articles and prepared necessary materials for writing this review. LZ wrote this manuscript with the help from CZ and PS. CZ, LZ and PS revised the manuscript. All authors have approved this manuscript before submission.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.


Mycobacterium bovis, a bacterium that can elicit disease humans. Since the 1950s, the objective of the national bTB eradication program in Republic of Ireland was the biological extinction of bTB; that purpose has yet to be achieved. Objectives of the present study were to develop the statistical methodology and variance components to undertake routine genetic evaluations for resistance to bTB; also of interest was the detection of regions of the bovine genome putatively associated with bTB infection in dairy and beef breeds. The novelty of the present study, in terms of research on bTB infection, was the use of beef breeds in the genome-wide association and the utilization of imputed whole genome sequence data. Phenotypic bTB data on 781,270 animals together with imputed whole genome sequence data on 7,346 of these animals’ sires were available. Linear mixed models were used to quantify variance components for bTB and EBVs were validated. Within-breed and multi-breed genome-wide associations were undertaken using a single-SNP regression approach. The estimated genetic standard deviation (0.09), heritability (0.12), and repeatability (0.30) substantiate that genetic selection help to eradicate bTB. The multi-breed genome-wide association analysis identified 38 SNPs and 64 QTL regions associated with bTB infection; two QTL regions (both on BTA23) identified in the multi-breed analysis overlapped with the within-breed analyses of Charolais, Limousin, and Holstein-Friesian. Results from the association analysis, coupled with previous studies, suggest bTB is controlled by an infinitely large number of loci, each having a small effect. The methodology and results from the present study will be used to develop national genetic evaluations for bTB in the Republic of Ireland. In addition, results can also be used to help uncover the biological architecture underlying resistance to bTB infection in cattle.Bovine tuberculosis (bTB) is an infectious disease of cattle generally caused by  Bovine tuberculosis (bTB) is an infectious disease of ruminants and wildlife populations that also threatens human health. Clinical signs of bTB in cattle are rarely observed in developed countries due to the rigorous surveillance and culling protocols associated with bTB control and eradication programs. Nevertheless, the costs associated with bTB are excessive even in developed countries; for example, the annual operational costs of the bTB eradication program in the Republic of Ireland was €84 million in 2017 [Genetic selection for improved health has proved fruitful, particularly in Scandinavian countries where access to phenotypes are plentiful . AlthougThe objectives of the present study were to estimate the variance components for bTB infection, with the view of implementing national genetic evaluations for bTB. A second objective was to identify regions of the bovine genome associated with bTB infection in dairy and beef cattle using imputed whole genome sequence data. To our knowledge, the present study will be the first to complete a genome-wide association for bTB using whole genome sequence data and the first also to consider beef breeds.Mycobacterium bovis. All live cattle are tested at least once per annum using the Single Intradermal Comparative Tuberculin Test (SICTT); cattle that yield a positive SICTT result, termed bTB reactors, are immediately removed from their residing herd and slaughtered. In addition, all cattle slaughtered in Irish abattoirs are visually assessed for the presence of bTB lesions in relevant lymph nodes. Observed lesions in slaughtered cattle that did not fail the SICTT test are further examined in a DAFM laboratory to confirm bTB infection; cattle confirmed with bTB in a DAFM laboratory are termed slaughterhouse cases. A more detailed explanation of the testing protocol for the bTB eradication program in the Republic of Ireland can be found at https://www.agriculture.gov.ie/animalhealthwelfare/diseasecontrol/bovinetb/diseaseeradicationtb/ .Since the 1950s, the Irish Department of Agriculture Food and the Marine (DAFM) has enforced compulsory testing of all cattle in the Republic of Ireland for bTB, normally caused by st January 2000 to 10th April 2017, inclusive. Tuberculosis test results for bTB reactors and slaughterhouse cases were also provided; test results included SICTT results for bTB reactors and slaughterhouse cases as well as lesion results, for bTB reactors only, and positive laboratory results for slaughterhouse cases only. Details of test results for cattle that yielded entirely negative tuberculosis results or animals observed with lesions at slaughter but subsequently deemed not to have bTB at laboratory examination were not available to the present study. Nevertheless, information on cattle birth, inter-herd movement, death, slaughter and export events together with pedigree data were available from the Irish Cattle Breeding Federation database; these data were used to determine the animals present in each herd on the date(s) bTB reactor(s) and slaughterhouse case(s) were identified. Of the 41,104 bTB-breakdowns in the present study, 4,031,452 cattle resided in 27,029 herds during at least one bTB-breakdown. There were 150,349 bTB reactors and an additional 8,598 confirmed bTB slaughterhouse cases.Any herds that yield either a positive bTB reactor or a slaughterhouse case are, according to the national eradication program, regarded as having a bTB-breakdown. Such herds are restricted from trading and they are required to cull animals that yield any positive test result. During a bTB-breakdown, herds are also required to complete continual testing  for bTB infection; once two consecutive whole-herd tests return entirely negative results, the bTB-breakdown is complete. The time-periods of herd-level bTB-breakdowns were made available to the present study for the period 01The bTB phenotype considered in the present study was defined for each animal present during each herd-level bTB-breakdown when a bTB reactor or a slaughterhouse case was identified. Cattle that yielded a positive SICTT, lesion, or laboratory result(s) were coded as one (bTB = 1); otherwise, all other cattle present in the herd during the bTB-breakdown were coded as zero (bTB = 0).In the present study, potential bTB exposure was defined within each herd-level bTB-breakdown for each management group separately. Following bTB infection, tuberculin reactions are generally detectable within 42 days . As a reAnimals within a herd management group were deemed exposed to bTB if 1) any herd-mate was identified with a lesion at slaughter after being removed as a bTB reactor, 2) any herd-mate was identified as a slaughterhouse case, or 3) two or more herd-mates were removed from the herd as bTB reactors.Only an animal’s most recent bTB result in a given bTB-breakdown within a management group was considered; 5,146,363 records from 4,008,635 cattle in 27,029 herds remained. A total of 273,730 animals in undefined management groups  were not considered further. A further 406,915 animals not present in the herd at least 42 days prior to the start date of a bTB-breakdown were also discarded. Primiparous cows that were recorded to have calved < 545 days  or multiparous cows that calved > 666 days  from the parity median, which were likely to have been managed differently to the majority of the herd, therefore these cows were also removed. In addition, only animals deemed potentially exposed to bTB were retained. Heterosis and recombination loss coefficients were derived using methods described by VanRaden and Sanders [bTB = the binary dependent variable of the bTB phenotype ; μ = the fixed effect of the population mean; HBD = the fixed effect of the herd breakdown; het = the fixed effect of heterosis coefficient ; rec = the fixed effect of recombination loss coefficient ; sex = the fixed effect of the animal gender; life stage|age = the fixed effect of the interaction between animal life stage  and animal age fitted as a class effect ; a = the random additive genetic effect, where a ~ N with σ2a representing the additive genetic variance of the animal and A as the additive genetic relationship matrix among animals; PE = the random permanent environment effect of the animal, where PE ~ N with σ2pe representing the permanent environmental variance and I an identity matrix; e = the random residual effect, where e ~ N with σ2e representing the residual variance. The coefficient of genetic variation was calculated using the formula by Burdon [For computational reasons only, the estimation of variance components only considered bTB-breakdowns that were initiated and terminated between the years 2010 and 2017, inclusive. Also for computational reasons, only records from sires that produced at least 10 progeny were considered. Thereafter, a random sample of 3,000 bTB-breakdowns which included 156,467 phenotypes from 144,474 animals were analyzed. Variance components for bTB were estimated using an animal linear mixed model in ASReml version 3.0 [y Burdon  to adjusEBV) for bTB for all 781,270 animals in completed bTB-breakdowns. The model fitted in the genetic evaluation was the same as that described for estimating variance components; the resulting variance components from the present study were used to inform the genetic evaluations.MiX99 (release VIII/2015 version 15.0811)  was usedPhenotypes for bTB were masked  for all animals in a random 20% of herds while pedigree information for those animals were included in the analysis to estimate their breeding values. Both phenotypic and pedigree information for all other animals were included to estimate breeding values. The masked animals were subsequently categorized into one of three risk groups  based only on their  EBV. The odds of each animal yielding a positive bTB diagnosis in their lifetime was calculated per risk group using logistic regression which included a fixed effect representing herd, life stage, and age (as well as EBV risk group); only animals with an EBV reliability ≥ 10% were considered in the logistic regression. This validation process was iterated five times, such that each animal’s phenotype was masked at least once to generate its EBV. The ability of the EBV risk group to determine whether or not each masked animal was diagnosed with bTB infection during their lifetime were also measured by the area under the receiver operating curve where the EBV risk group and life stage were the other terms included in the model; only animals with an EBV reliability ≥10% were again considered. Based on random chance alone, the area under the receiver operating curve would be 0.5, whereas if the model were perfectly able to determine the phenotype of each animal, the area under the receiver operating curve would be 1.0 .Of the cattle in the edited phenotype dataset, 14,778 of those animals’ sires were genotyped. The majority of the genotyped bulls were purebred Charolais , Limousin , Holstein-Friesian , Aberdeen Angus (651), or Simmental (633) breeds. Each bull was genotyped using either a high-density genotype panel , a Bovine SNP50 panel , or a custom built International Dairy and Beef (IDB) genotyping panel . Each bull had a call rate of at least 90%. Only autosomal SNPs, which had a known chromosome and position with a SNP call rate of at least 90% within panel was retained.Bos taurus animals of multiple breeds from Run6.0 of the 1000 Bulls Genomes Project [All genotyped bulls were imputed to HD using a two-step approach in FImpute2 ; this in Project . All var Project . In totaImputation of the HD genotypes to WGS was then completed by first phasing all imputed HD genotypes using Eagle version 2.3.2  and subsRegions of poor WGS imputation accuracy, perhaps due to local mis-assemblies or mis-orientated contigs, were identified using an additional dataset of 147,309 verified parent-progeny relationships. Mendelian errors, defined as the proportion of opposing homozygotes in a parent-progeny pair, were estimated for each relationship and the subsequent Mendelian error rate per SNP was determined. To accurately identify genomic regions of poor imputation, the R package GenWin  which fiiw = is the weighting factor of the deregressed EBV of the ith animal, h2 is the heritability estimate , ith animal, and c is the genetic variance not accounted for by the SNPs .MiX99 (release VIII/2015 version 15.0811)  was used−6) were removed; 10,506,082 autosomal SNPs remained. For the within-breed analyses of the larger purebred populations of Charolais, Limousin, and Holstein-Friesian bulls, SNPs with a within-breed minor allele frequency (MAF) < 0.002 or SNPs that deviated from Hardy-Weinberg equilibrium  were removed; 17,250,600, 17,267,260, and 15,017,692 autosomal SNPs remained for the Charolais, Limousin, and Holstein-Friesian analysis, respectively.Only the 7,346 bulls that had genotype data with an effective record contribution (ERC) of at least one  were considered further ; of thesbreed which was not included in the within-breed analyses, the model fitted in all analyses was:where EBVj = the dependent variable of the deregressed EBV weighted by ERC of the jth individual; μ= the fixed effect of the population mean; SNPj = the fixed effect of allele dosage for each SNP  of the jth individual; breedj = the fixed effect of breed percentage  fitted as a covariate  of the jth individual; aj is the random effect of the jth individual; ej = the residual effect of the jth individual, ej ∼ N, with σe2 being the residual variance. The genome-wide and suggestive significance threshold were defined as P = 1 x 10−6 and P = 1 x 10−5, respectively.Using only autosomal HD genotypes, the genomic relationship matrix was constructed between bulls using Van Raden method 1 . SNP eff−5). Pairwise LD was calculated as the r2 among all SNPs within 5 Mb of the suggestive SNPs; the beginning and end of each QTL were defined by the SNPs that were furthest upstream and downstream of the suggestive SNP that had an r2 of ≥ 0.5. Overlapping QTL were merged together and considered as the same QTL.Within each analysis, QTL regions associated with bTB infection were defined based on linkage disequilibrium (LD) patterns with SNPs that surpassed the suggestive significance threshold (P < 1 x 10https://www.ensembl.org/) on the UMD 3.1 genome build. A pathway analysis was undertaken using InnateDB [The defined QTL regions were subsequently explored for the presence of candidate genes using ENSEMBL (InnateDB  using thCows (61%), followed by heifers (19%), represented the majority of the dataset after edits, with <1.5% of the dataset being bulls. After edits, the mean prevalence of bTB in the entire dataset was 7.8%. More positive tests originated from younger animals  compared to older animals , but theIllustrated in Genetic trends for AI sires born between the years 2000 and 2011 that had at least 20 progeny in at least two bTB-breakdowns are in th percentile for bTB EBV had a 1.44 (95% CI: 1.34 to 1.54) times greater odds of returning a positive bTB result compared to cattle in the best 20th percentile for bTB EBV; cattle with an intermediate bTB EBV  had, on average, a 1.20 (95% CI: 1.13 to 1.28) times greater odds of returning a positive bTB result compared to cattle in the best 20th percentile for bTB EBV. Phenotypically, the high risk EBV group  had a 1.8 percentage unit higher prevalence of positive bTB results compared to the average risk EBV group ; whereas the high risk EBV group had a 2.45 percentage unit higher prevalence of positive bTB results compared to the low risk EBV group .When only the parental average EBV of the animal was considered for predicting bTB infection in bTB-breakdown herds, the mean bTB EBV reliability for animals was 19% and the area under the receiver operating curve was 0.529 (95% CI: 0.5236 to 0.5342); when the life stage of the animal was also known, the area under the receiver operating curve increased to 0.555 (95% CI: 0.5494 to 0.5612). The odds of yielding a positive bTB result increased (P < 0.001) with bTB EBV risk group, when herd and life stage were accounted for. Cattle in the worst 20−6 . The three SNPs with the strongest (P = 3.63 x 10−8) association, rs42709904, rs799252319, and rs42898143 were all located on BTA15 where the minor allele A (multi-breed frequency: 0.005) was associated with increased resistance to bTB infection; two of these SNPs were classified as synonymous or upstream gene variants of the gene OR52E5. Notably, 6 of the 9 SNPS categorized as missense gene variants of OR52E5 were segregating yet the P-values were ≥ 0.32. For each of the 38 SNPs with a P-value < 1 x 10−6  of SNP rs133701091, which had the lowest P-value of all SNPs on BTA23 (P = 4.3 x 10−7), was associated with increased resistance to bTB infection.A Manhattan plot outlining the association between each SNP and the EBV for bTB infection in the multi-breed analysis is in −6 . Of thes1 x 10−6 , where tce versa . Located−5) with an r2 of ≥ 0.5. Those QTL ranged from 8 bp to 5. 9 Mb in length and were identified across 26 autosomes based on the multi-breed analysis. For a further 11 suggestive SNPs (P < 1 x 10−5), the QTL included only the suggestive SNP itself as no other SNP existed within 5 Mb with an r2 of ≥ 0.5. A list of all QTLs is in −5) associated with bTB infection are in Fifty-three QTL regions included ≥1 SNP that flanked 5 Mb of a suggestive SNP (P < 1 x 10−6 (−8) with bTB infection were all located on BTA6 (genetic position: 96523708 to 98691990). Thirty-nine QTL regions were identified in 15 autosomes for the Holstein-Friesians. Results from the single-SNP regression in the within-breed analyses of the beef breeds had considerably more spurious significant SNP associations, which were predominantly alleles with a low-frequency , nine , and seven , respectively. Forty-six of the 64 QTL regions from the multi-breed analysis did not overlap with any QTL region in either of the within-breed analyses. Of the 38 SNPs in the multi-breed analysis that were deemed to be associated with bTB infection at the genome-wide threshold of P = 1 x 10−6, twenty-nine of those SNPs  were not defined in a QTL in any of the within-breed analyses; generally those SNPs were fixed in the Holstein-Friesian population while they were in very low frequency, although segregating, in the Charolais and Limousin populations  had a P-value of 2.6 x 10−4 which was slightly above the cut-off threshold used in the present study for deriving QTLs. Even when a higher MAF threshold (0.01) was applied to the data, there were many QTL in the multi-breed analysis that did not overlap with any QTL from either of the within-breed analysis  as well as the moderate heritability estimate (0.12) and the repeatability estimate (0.30) for bTB infection in the present study are comparable with previous studies among cattle, even though the phenotype definition and models used sometimes differed , 8, 9. U as well www.icbf.com); 38% of his progeny in bTB infected herds (29 out 77 progeny across 34 herds) have been diagnosed with bTB infection during their lifetime. If AI companies/producers were aware of his genetic merit for bTB infection at the time of selection it is unlikely he would have been used so frequently.Results from the present study, supported by previous studies, clearly suggest that genetic selection could play a pivotal role in the eradication and control of bTB (and possibly associated diseases) in cattle populations. For example, if an animal’s EBV for bTB infection were known to producers at the time of selecting parents of the next generation, that EBV is likely to influence mating decisions. By way of example, the dairy AI bull born in 2011 which had the worst (highest) EBV for bTB infection   arising The implications of including bTB in Irish dairy and beef breeding goals is unlikely to have strong negative ramifications on other traits in each breeding goal given the lack of any consistent antagonistic genetic correlation between bTB and performance traits . This viBos taurus cattle have been restricted to just the Holstein-Friesian breed [Bos taurus breeds. The use of multi-breed genome-wide association analyses has been investigated previously for milk production [M. paratuberculosis [M. paratuberculosis population and phenotype. Sallam et al. [It is assumed that bTB is a complex polygenic trait ; therefoan breed –6, 10–12oduction  and diseoduction . Van denoduction  reportedoduction . Followirculosis –41, Sallrculosis  preformem et al.  observed−6 that flanked 1Mb of the SNP deemed most suggestive of bTB resistance by Richardson et al. [−6 was 9.85 Mb downstream.The present study identified several regions of the bovine genome associated with bTB infection, but none of the SNPs or QTL regions in the multi-breed analysis overlapped with SNPs previously reported for bTB infection; in comparison to the previous five genome-based association studies on bTB infection, each of those studies only considered Holstein-Friesian cattle and they were limited by sample size (range: 307 to 1151 cattle) , 10–12. Using 803 Holstein-Friesian sires, Raphaka et al.  reportedIn comparison to three other genome-wide associations on bTB among Holstein-Friesian cattle which documented SNPs of interest on BTA2 , BTA13 NRAMP1 gene has sometimes been shown to confer resistance to tuberculosis [NRAMP1 and bTB in cattle are inconsistent [NRAMP1 gene, where the SNP with the lowest P-value  had an allele substitution effect of 0.014, with the major T allele  being associated with increased resistance to bTB; the unfavorable minor C allele was mostly present as a heterozygous copy in the present study . For that SNP, the within-breed frequency of the favorable allele, which was T for all breeds, was 0.983 for Belgian Blue, 0.998 for Charolais, 0.986 for Hereford, 0.980 for Holstein-Friesian, 0.993 for Limousin, and 0.994 for Simmental; the favorable T allele was fixed in the Aberdeen Angus breed.In mice, the rculosis ; howevernsistent –44. In tMeles meles) are deemed to be the primary wildlife reservoir of bTB in the Republic of Ireland [http://www.agriculture.gov.ie) thus, offspring from Holstein-Friesians that are more resistant to bTB could be generated by mating Herefords that have the favorable allele with Holstein-Friesians. It could also be hypothesized that the Hereford breed which originated in the British Isles may have acquired improved resistance to bTB during its extensive time-period of exposure to bTB.Medzhitov et al.  document Ireland  and they Ireland , yet bad Ireland –53, thus Ireland , when ca Ireland  and othe Ireland –53, suggRCAN2, ENSBTAG00000022736, CYP39A1, RF00026, SLC25A27, TDRD6, and PLA2G7. Notably, 11 SNPS with P-values ≤ 1.47 x 10−4 were upstream gene variants of RCAN2 while another SNP with a P-value of 0.05 was classified as a missense gene variant. Interestingly, RCAN2 is responsible for the regulation of calcineurin 2 and calcineurin activation promotes the survival of tuberculosis within its host by preventing phagocyte maturation  of interest for resistance to bTB, previous studies have repeatedly highlighted the association between resistance to bTB infection and BTA23 , 10; theculosis; ).Breeding for resistance to bTB is a plausible strategy complementing existing approaches that aim to eradicate bTB from the Republic of Ireland (and elsewhere). Results from the present study substantiate that considerable exploitable genetic variability exists in resistance to bTB. Moreover, SNPs putatively associated with bTB infection have been identified which have not been previously linked to bTB. While results from the present study should be interpreted, our results, coupled with previous studies, suggest that olfactory receptor genes as well as regulation of calcineurin 2 may have a pivotal role in the resistance of cattle to bTB. Methods and results from the present study can be used to develop national genetic evaluations for bTB in the Republic of Ireland and elsewhere. In addition, results can be used to help uncover the biological architecture underlying resistance to bTB infection in cattle.S1 Fig(TIFF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.


One of the lines of research on organic devices is focused on their miniaturization to obtain denser and faster electronic circuits. The challenge is to build devices adding atom by atom or molecule by molecule until the desired structures are achieved. To do this job, techniques able to see and manipulate matter at this scale are needed. Scanning tunneling microscopy (STM) has been the selected technique by scientists to develop smart and functional unimolecular devices. This review article compiles the latest developments in this field giving examples of supramolecular systems monitored and fabricated at the molecular scale by bottom-up approaches using STM at the solid/liquid interface. The development of functional and smart organic materials for optoelectronics has been a challenge for researchers in the field of nanoengineering. The interest lies in the possibility of designing and developing materials with specific functionalities and integrating them in electronic devices, such as sensors , light-eA molecular device is an assembly of molecular elements designed to behave in a certain manner, operating in a specific capacity and developed for a precise function. Each element contributes with a single function cooperating for the performance of the complex molecular device. The individual components can operate as a result of an external stimulus and can be easily replaced by other elements to accomplish a desired function. Each element can be individually stimulated as a result of an external source. This idea was introduced for the first time by Drexler . He propThe development of materials at the molecular level requires specific fabrication techniques that allow visualization and manipulation of matter at this scale. This is the point that this review article aims to address, showing how molecular devices can be fabricated using a bottom-up approach based on atom-by-atom or molecule-by-molecule assembly until a functional and complex structure is achieved. Scanning Tunneling Microscopy (STM) is the elected technique to play with matter at the atomic level. Namely, STM has been used to monitor in real-time formation of highly organized self-assembled monolayers where the molecules arrange themselves into packed 2D crystals fully covering the surface of the substrate onto which they are deposited. Several high-resolution STM images of the formation of molecular systems by self-assembly have been reported revealing the parameters involved in the monolayer formation: whether they are physical parameters  or chemical parameters . All these monolayer properties are important for the design of organic devices.Recently, STM has been used to build molecular systems with multicomponents, e.g., self-assembled monolayers with more than one molecular element or vertical supramolecular structures synthesized in situ ,8,15,16.Conducting organic self-assembled and self-organized monolayers are the starting point of an organic device fabrication. They are spontaneously formed on a substrate, usually on a conducting substrate, and they can be composed of one or more than one type of molecules, depending on the aimed application. Due to the high reproducibility of this technique, it is easy to use self-assembled materials in the development of large-scale devices. The molecular ordering is strongly dependent on the intra- and intermolecular interactions, temperature, concentration, solvent and on the chemical/physical interactions with the substrate  or on the molecular recognition . The porous array can be modified for specific purposes using rational molecular design. Two methodologies are available for the fabrication of nanoporous surfaces depending on the type of building blocks: intrinsic and extrinsic ,40. NanoNanoporous monolayers developed with extrinsic building blocks depend on the self-assembly of acyclic molecules that together form extrinsic pores. Among the most used extrinsic building blocks we find trimesic acid (TMA) ,42, dehyThe solvent can play an important role in the formation of nanoporous networks. Lackinger et al. ,42 demonA second class of extrinsic building blocks are alkyl-/alkoxy-hexadehydrotribenzo[12]annulene (DBA) molecules . STM images of a self-assembled porphyrins monolayer on Cu(111) showed different molecular conformations of porphyrins as a function of the applied tip-voltage. Recently, Ferreira and co-workers  reportedThe pyrrole groups of brighter lines are in Trans conformation and the darker lines correspond to a Cis conformation. When the tip-voltage increases to 0.7 V the Trans molecules switch to a Cis conformation and the monolayer becomes homogeneous as it is indicated by the line profile of Movement is essential to life, may it be in the form of transport, translocation, contraction, or others, since ultimately biological systems rely directly or indirectly on movement. No wonder molecular motors, which have the ability of powering movement, are intrinsic to nature. Molecular motors are commonly seen in nature as, for example, in adenosine triphosphate synthase, myosin, kinesin, and dynein. These are motor proteins that use chemical energy to attain directional movement. Inspired by these biological machines, molecules and molecular complexes that can be assembled to form rotors and motors have been designed and fabricated at the nanoscale to simulate biological functions. A motor is commonly defined as an energy converter system, i.e., a system capable of converting one type of energy—e.g., electromagnetic, chemical, electrical—into kinetic energy. Specifically, a rotary motor can convert this energy into unidirectional rotary movement in a controlled manner. Rotary molecular motors are commonly composed of three components: the rotor, the axle and the stator ,67,68,69eactions ,71.In the field of molecular motors, the focus has been on studies at room temperature and some important contributions have been published with dynamic molecular systems under these conditions ,73,74,75The development of molecular motors needs to overcome various barriers. Apart from their stability at room temperature, the focus is to develop fast machines able to “walk” over longer distances. To explore how fast and how far a nanomotor can travel, the first world-wide nanocar competing event took place using the STM to control and monitor the results ,77,78. TThe first definition of a molecular wire (MW) was given by the winner of the Nobel Prize in Chemistry Jean-Marie Lehn in 1988, that defined this structure as a conducting chain of a molecule or a supramolecule which conducts electrons between two electrodes . The MW The conductance measurements at single molecule level are experimentally challenging and each system needs specific experimental protocols. The STM BJ experiments seem to be perfect taking into account that the electrodes make a contact with the molecular system. However, it is difficult to know how this affects the structure and the vibrational properties of the structure that is being analyzed.Scanning Tunneling Spectroscopy (STS) is another technique to measure electrical properties of individual wires. Its main limitation is the absence of contact between the tip and the MW that compromises the accuracy of the measurements. However, STS can be supported by STM images that can be acquired simultaneously with current measurements. This allows the precise localization of MWs ensuring that the tip is analyzing the desired structure. The most reported works about MWs are related to supramolecular structures previously synthesized in laboratory or locally synthesized in high vacuum conditions .A recent work  shows hoThe imaging allows the positioning the tip at the top of a single wire. At this moment, the individual current is measured by the application of a bias voltage between the tip and the substrate. The characterization of the conduction mechanisms is identified analyzing the evolution of the MW electrical resistance as a function of the molecular length, associating a tunneling mechanism for shorter wires with 4–5 nm and a hopping mechanism for longer wires. This work can be taken as a model to build similar supramolecular structures synthesized in situ. Each step can be controlled by imaging with molecular resolution while measuring, at the same time, the individual electrical transport.The described stepwise method opens the way for the design of a variety of MWs by changing the building blocks to optimize the conductive properties.One of the questions that we may ask when looking at the developments of unimolecular devices is “when will they be integrated in electronic circuits?” The answer can be foreseen by the fast evolution in this research field covering a wide range of applications and prototypes which are already working ,86,87,88to create unimolecular systems stable at room temperatures;to develop encapsulation methods while maintaining the integrity of the organic device.Besides the interest in biological systems, there are other challenges to overcome:A recent work, shows how it is possible to build flexible MWs stable at room temperature . MWs witThe stability of an organic device also depends on the encapsulation and this research is still at the beginning. All devices need to be encapsulated to be protected from corrosion and to avoid degradation in the presence of air. L. Moro et al. published a recent article in which he gives an overview of the requirements to develop encapsulation methods for organic devices . This isAt the moment, the main concern of scientists is to integrate the single molecule device in a final electronic circuit. To achieve this goal, it is necessary to overcome important constraints: long-term stability, biocompatibility, and environment effects.


Experimental advances have enabled the acquisition of tandem mass spectrometry and metagenomics sequencing data from tens of thousands of environmental/host-oriented microbial communities. Each of these communities contains hundreds of microbial features  and thousands of molecular features . However, with the current technology, it is very difficult to identify the microbial species responsible for the production/biotransformation of each molecular feature. Here, we develop association networks, a new approach for identifying the microbial producer/biotransformer of natural products through cooccurrence analysis of metagenomics and mass spectrometry data collected on multiple microbiomes. The human microbiome consists of thousands of different microbial species, and tens of thousands of bioactive small molecules are associated with them. These associated molecules include the biosynthetic products of microbiota and the products of microbial transformation of host molecules, dietary components, and pharmaceuticals. The existing methods for characterization of these small molecules are currently time consuming and expensive, and they are limited to the cultivable bacteria. Here, we propose a method for detecting microbiota-associated small molecules based on the patterns of cooccurrence of molecular and microbial features across multiple microbiomes. We further map each molecule to the clade in a phylogenetic tree that is responsible for its production/transformation. We applied our proposed method to the tandem mass spectrometry and metagenomics data sets collected by the American Gut Project and to microbiome isolates from cystic fibrosis patients and discovered the genes in the human microbiome responsible for the production of corynomycolenic acid, which serves as a ligand for human T cells and induces a specific immune response against infection. Moreover, our method correctly associated pseudomonas quinolone signals, tyrvalin, and phevalin with their known biosynthetic gene clusters.IMPORTANCE Experimental advances have enabled the acquisition of tandem mass spectrometry and metagenomics sequencing data from tens of thousands of environmental/host-oriented microbial communities. Each of these communities contains hundreds of microbial features  and thousands of molecular features . However, with the current technology, it is very difficult to identify the microbial species responsible for the production/biotransformation of each molecular feature. Here, we develop association networks, a new approach for identifying the microbial producer/biotransformer of natural products through cooccurrence analysis of metagenomics and mass spectrometry data collected on multiple microbiomes. The human microbiome is a complex community of microorganisms, their enzymes, and the molecules they produce/modify. Recent studies show that imbalances in human microbial ecosystems can cause disease. The majority of relationships between the microbiome and disease were discovered through microbiome-wide association studies that link disease to a relative overabundance/underabundance of microbial species using metagenome sequencing data , 2. HoweMetabolomics studies have shown that among all the molecules in the human metabolome, microbial metabolites are the ones most altered in metabolic and inflammatory disorders . These mCurrently, the majority of known microbial products and biotransformation products are discovered through the targeted analysis of specific molecules, such as short-chain fatty acids, secondary bile acids, and oral drugs in model systems  –7. Howev–Recent large-scale microbiome data sets, such as the Integrative Human Microbiome Project (iHMP)  and the In this study, we develop an efficient pipeline to discover potential microbial metabolites and microbial biotransformations by building a cooccurrence network of microbes and metabolites using high-throughput LC-MS data and metagenomics data collected over thousands of microbiota samples. Using this strategy, we identify several microbial products and microbial biotransformation products from the human microbiome. Moreover, we develop a new method for computing the false discovery rates (FDR) of the associations and using them to benchmark various metabolomics feature extraction methods and association tests. Furthermore, we develop a new method to detect clade-specific metabolites based on the cooccurrence network and the analysis of a microbial phylogenetic tree.Our pipeline  includesm/z threshold of 0.01 and a Fisher’s exact test P value threshold of 10−5. This decreased the number of molecular features from 29,567 to 18,940 for Optimus and from 74,913 to 73,275 for MS-Clustering. We additionally annotated the extracted molecular features using spectral library search , and MS-Clustering extracted 74,913 molecular features from the LC-MS/MS data (cosine similarity threshold [τ] = 0.4). We further applied deduplication using an y search  and Derey search . Using tPseudomonas and Staphylococcus aureus are anticorrelated with Gram-positive anaerobes. In this study, we obtained 23,176 molecular features from LC-MS/MS data . We further applied SPAdes (The data set for human microbiome isolates from cystic fibrosis patients (HUMAN-CF) consists of tandem mass spectrometry and metagenomics data collected from 243 microbial isolates from cultures of sputum samples from cystic fibrosis patients . Each sample contains one or a mixture of a few (from 1 to 11) different bacteria. Based on the metagenomics data of HUMAN-CF, Quinn et al.  analyzedd SPAdes , antiSMAd SPAdes , and BiGd SPAdes  to the sMicrobial natural products can be detected as positive correlations between the occurrence of the microbial species and the molecules in the association network . In addiP value threshold (PThreshold) of 10−10 for the molecular features obtained by Optimus and MS-Clustering, respectively. To explore the power of the association network , five rhamnolipids, and five pseudomonas quinolone signals (PQS) (Pseudomonas (m/z 673.40 and m/z 701.41) are significantly associated with Pseudomonas. With molecular networking (m/z 553.25 and m/z 555.38), both of which have a strong association with Pseudomonas. Pseudomonas is also significantly associated with rhamnolipid B (m/z 651.40). Moreover, Pseudomonas is positively correlated with compounds from different series of quinolones (N-oxide (m/z 258.15), 2-nonyl-4-quinolone (m/z 270.19), 2-nonylquinolin-4(1H)-one (m/z 272.20), 4-hydroxy-2-nonylquinoline-N-oxide (m/z 288.20), and 4-hydroxy-2-heptylquinoline (HHQ) (m/z 244.169). All of these molecules are known to be produced by Pseudomonas aeruginosa bacteria, playing roles in quorum sensing and virulence (At a ls (PQS) . Among tudomonas , 8 are itworking , 25, twoinolones , includilone m/z 0.19, 2-nirulence 29. We fuCorynebacterium kutscheri OTU feature (Greengenes number 13393) is positively correlated with a molecule at m/z 495.4 (P = 3 · 10−5). Dereplicator+ annotated this molecule as corynomycolenic acid .A nic acid . The BGCTC 13129 . The refDesulfovibrio species and cholic acid (P = 10−13), which is a human bile acid , and some of the Clostridiales. It is well known that stercobilin and urobilin are the end products of heme catabolism by Clostridiales through bilirubin glucuronidase and bilirubin reductase enzymes  and urobilin (m/z 591.35 [P = 5 · 10−26]), which are the products of bilirubin reductase.We observed significant positive correlations between stercobilin  and a positive correlation with 7-oxodeoxycholate (m/z 407.28 [P = 4e−10]), confirming the evidence that Enterobacteriaceae play a role in dehydrogenation of bile acids . Bacillus species are known to biotransform steroids  and n-acetylphenylalanine (m/z 207.12 [P = 3 · 10−13]). In fact, phenylalanine and n-acetylphenylalanine were not detectable in any of the subjects where Oxalobacteraceae were present. Oxalobacteraceae species are shown to be capable of consuming phenylalanine as a carbon source , tryptophan (m/z 206.07 [P = 10−27]), dihydroxyphenylacetic acid (m/z 153.056 [P = 3 · 10−11]), and tyrosine (m/z 182.08 [P = 5 · 10−13]) and a positive correlation with indolepropionate (m/z 190.018 [P = 8 · 10−11]). Clostridiales is known to biotransform the phenyl residue in these molecules (olecules .m/z 229.135 [P = 4.05 · 10−16] and m/z 245.125 [P = 1.98 · 10−9]). Dereplicator+ annotated these two features as phevalin (score of 4) and tyrvalin (score of 7). These annotations matched the adenylation specificities of the corresponding domains (Staphylococcus aureus (100% coverage and 99.46% identity), which is known for the synthesis of phevalin and tyrvalin , Pearson’s correlation test, Spearman’s correlation test, and the mutual information criterion. Our results show that Optimus and Spearman’s correlation are the best feature extraction and association methods  and 9.Recent experimental advances have enabled the acquisition of tandem mass spectrometry and shotgun metagenomics data from tens of thousands of environmental/host-oriented microbial communities through large-scale projects, including the American Gut Project and the Integrative Human Microbiome Project. Metagenome-mining studies have revealed thousands of biosynthetic enzymes with uncharacterized substrates/products from these data sets. Moreover, metabolomics studies have revealed signals for hundreds of thousands of bioactive small molecules in the mass spectral data sets.While these data sets represent a gold mine for discovering small molecules associated with the microbiota, manual analysis of billions of mass spectra in these data sets is infeasible, and new computational approaches are needed to integrate the large-scale metagenomics and tandem mass spectrometry data for systematic discovery of the unknown small-molecule products of the biosynthetic enzymes. In this regard, the following three questions need to be addressed. (i) Is the molecular feature associated with the microbiota? If so, which microbial species is it associated with? (ii) Which biosynthetic enzyme within the microbial species is it associated with? (iii) What is the chemical structure of the molecule?In this article, we developed a method for addressing the first question. Our method detects microbial natural products and microbial biotransformation products through a comparative analysis of the molecular and microbial features across multiple microbiomes. In the case of corynomycolenic acid, we further used genome mining to assign the molecule to its BGC within the genome of its microbial producer. While identification of the biosynthetic enzymes responsible for corynomycolenic acid production provides a proof of concept, novel computational methods are needed for systematic characterization of the products of the microbial biosynthetic enzymes through the association network approach.The association network detects pairwise interactions between the molecular and microbial features across thousands of microbiomes. While this method is capable of discovering microbial natural products and microbial biotransformation products, interactions that involve multiple sequential biotransformations/complex pathways cannot be handled. Moreover, many of the interactions retrieved by this method are noncausal correlations. For example, the association network finds correlating features that are caused by a confounding factor. While this results in a denser network with noncausal edges, in some scenarios, these noncausal edges can lead to the discovery of causal interactions that were missed by the network.P values, which assumes different samples are independent. While the independence assumption is natural for data sets such as that of the American Gut Project, collected from distinct individuals, confounders like health status could increase the false discovery rate. The association network approach is the first step toward detecting the complex interactions between microbial and molecular features through the comparative analysis of thousands of microbiome samples.Currently, the association network approach is based on the use of Fisher’s exact test In addition to linking BGCs to molecules, other potential applications of association networks include detection of carbon sources depleted by microorganisms, identifying biomarkers for drug metabolism, linking microbial enzymes to xenobiotic metabolism, and identifying the role of microbial metabolites in disease. Association networks provide an untargeted approach for generating/testing various hypotheses about the causal relationships between the molecules and microbes in complex communities.X is characterized by a subset of samples that X is present in, as follows: SamplesX={S∈Samples|X is present in S}. Here, S represents a sample.Consider a set of microbial community samples (Samples), a set of molecular features (Molecules), and a set of microbial features (Microbes). Here, each molecular feature is the abundance of a specific molecule (binary or continuous), and each microbial feature is the abundance of a specific microbe. Every feature The inputs to our pipeline are the untargeted mass spectrometry data and metagenomics data collected on a set of microbiome samples.The association network pipeline consists of the following steps.A, S) is the number of times an OTU A is observed in a sample S. For each OTU A, we define SamplesA={S|OTUCount>MinCount} for a threshold MinCount.(i) For microbial feature extraction, QIIME  is used When shotgun metagenomics data are available, we can quantify BGC families on top of OTUs. First, we apply SPAdes  to metagX, S) is the intensity of a feature X in a sample S. We then select a threshold MinIntensity, and for every feature X, we define SamplesX={S|FeatureIntensity>MinIntensity}. We further remove molecular features that are present in less than two samples. When LC-MS/MS data are available, we extract molecular features using the MS-Clustering algorithm ((ii) For molecular feature extraction, molecular features from the liquid chromatography-mass spectrometry (LC-MS) data are first extracted and quantified using the feature extraction algorithm Optimus . Optimuslgorithm . Since tX∈Molecules, we construct a decoy feature dX, with SamplesXd being a randomly chosen subset of Samples with size |SamplesX|.We also construct a set of decoy molecular features, DecoyMolecules . These dX, A) consisting of a molecular feature X and a microbial feature A that have a statistically significant correlation in their patterns of occurrence.(iii) To perform the association test, we then search for pairwise associations between Molecules and Microbes . More spX and A, to detect whether X and A are cooccurring, we consider the null hypothesis that the events “X is present in a sample” and “A is present in a sample” are independent. A statistically significant correlation in the patterns of occurrence of X and A is detected if the P value of Fisher’s exact test, denoted PValue, is lower than the selected threshold PThreshold, and the null hypothesis is rejected.Given two features While there are other techniques for computing the associations between the molecular and microbial features, including Pearson’s correlation, Spearman’s correlation, and mutual information criterion, in this section, we focus on the Fisher’s exact test method.For the multiple-hypothesis testing, we compute the FDR using the target-decoy approach (TDA) . We firs(iv) To build the associations network, we further construct a bipartite network where the vertices are the molecular and microbial features and there is an edge between two vertices if the corresponding features are associated .(v) We also report the associations between the molecular features and the groups of related microbial features by assigning molecular features to the clades in the phylogenetic tree that are potentially responsible for their production/biotransformation . Note thT and a molecular feature X, we first mark all the microbial features that are positively correlated to X and count the number of marked features in every clade. Then, we select the minimal clade that has at least P percent (P = 80) of features marked. If the selected clade is a proper subset of the whole tree, we assign X to this clade. We perform the steps described for every molecular feature, and for each clade, we report the set of molecular features that are assigned to it.Given a phylogenetic tree m/z values. Such features are called “duplicates.” The process of finding all groups of duplicate features and merging them into unique features is called “deduplication.” We apply deduplication to remove the redundancy in the molecular features.Feature extraction methods usually report redundant features, i.e., each single molecule is reported as multiple features with similar m/z values and a statistically significant correlation in their patterns of occurrence. Then, we build a graph in which molecular features are nodes and every putative pair of duplicates is connected by an edge. The connected components of the resulting graph are the groups of duplicate features. For the i-th group DuplicatesGroupi, a new consensus feature iY is constructed with the m/z being the average m/z of all the features in DuplicatesGroupi, and SamplesYi is defined as the unionWe consider a pair of molecular features to be duplicates if they have similar Molecular-feature extraction consists of identification and quantification of the peaks across multiple LC-MS runs and is a fundamental step in proteomics and metabolomics. Although many tools for molecular-feature extraction have been proposed, it is not clear which one is more accurate. Moreover, it is not clear how to adjust the parameters in various feature extraction methods.Here, we describe an approach to compare the various feature extraction methods in the microbiome-wide correlation studies. Given a set of microbial features and several feature extraction methods with various sets of molecular features, we apply the pairwise association pipeline to these sets to identify the method and the parameter settings that result in the highest number of pairs of cooccurring features discovered at a certain FDR level. To avoid bias toward methods that report higher numbers of molecular features, we also compare the numbers of discovered microbial features in these pairs. The FDR is estimated by the target-decoy approach (TDA) and the Benjamini-Hochberg procedure. Four different association tests are benchmarked, including Fisher’s exact test, Pearson’s correlation test, Spearman’s rank correlation test, and the mutual information criterion.https://github.com/mohimanilab/AssociationNetworks.The association networks computer code is available on GitHub at


Corydalis yanhusuo W. T. Wang (C. yanhusuo) has been traditionally used for drug addiction and pain relief in China. In our previous study, we showed that the extract of C. yanhusuo blocks dopamine receptors, demonstrating that its pharmacological activities are mostly due to the antagonistic effects of some of its components at dopamine receptors. As part of our ongoing project on C. yanhusuo, the aim of the present study is to establish a high-throughput and low-cost screening assay system and test the abilities of the isolated alkaloids from C. yanhusuo to inhibit dopamine-induced dopamine D1 receptor activity. By using our established cyclic adenosine monophosphate (cAMP)-response element (CRE)-luciferase reporter gene assay system, we identified eight alkaloids from C. yanhusuo with D1 receptor antagonistic activities. We next validated the activities of these compounds using fluorometric imaging plate reader (FLIPR) assay by measuring the intracellular Ca2+ change. Six out of eight compounds, including tetrahydropalmatine, corydaline, 13-methyldehydrocorydalmine, dehydrocorybubine, dehydrocorydaline, and columbamine, can be confirmed for their inhibitory activities. The dopamine-receptor-antagonistic effects of four compounds, including 13-methyldehydrocorydalmine, dehydrocorydaline, columbamine, and corydaline, are reported for the first time. The present study provides an important pharmacological basis to support the traditional use of C. yanhusuo in China. To date, five different subtypes of dopamine receptors D–5 have b2+, depending on the type of G protein to which the receptor is coupled [Current methods employed in the assessment of dopamine receptor activation or antagonism are mainly through determining the production of second messengers, such as cAMP or Ca coupled ,7,8. The coupled . Over th coupled . A repor coupled ,11.Corydalis yanhusuo W. T. Wang (C. yanhusuo) has been traditionally used for drug addiction and pain relief in China for centuries [C. yanhusuo alkaloids. In our previous study, we found dehydrocorybulbine, an alkaloid isolated in C. yanhusuo, as well as its crude extract exhibit antagonistic activities at dopamine receptors [C. yanhusuo may contain previously unidentified alkaloids acting on dopamine receptors that may also contribute to its pharmacological effects.enturies . It has eceptors ,14. We hC. yanhusuo, we initiated a comprehensive study in an attempt to identify new dopamine receptor antagonists from C. yanhusuo. Here, we aim to develop a low-cost luciferase reporter gene assay to identify dopamine D1 receptor antagonists from C. yanhusuo and foster a better understanding of the traditional use of C. yanhusuo.As part of our ongoing project of systematically investigating 1 receptor and CRE/Luci were stably co-transfected into human embryonic kidney-293 cells (HEK293) cells (HEK-D1/CRE/Luc2P). Activation of D1 receptors leads to the elevation of cAMP and activates the cAMP response element (CRE) and therefore induces the expression of the reporter gene luciferase. We used the natural ligand dopamine as a positive control to select the cell colony and to optimize and characterize the HEK-D1/CRE/Luc2P cell system.The cDNA plasmids of dopamine D1 receptor activation at different time points by using 1 μM of dopamine. As shown in We carried out a series of experiments to optimize the assay. First, we examined the effects of fetal bovine serum (FBS) on D1 receptor under the optimized conditions, including incubation in FBS-starved medium for 6 h. As shown in 50) value derived from nonlinear curve-fitting analysis is 1.5 nM, which is comparable to the published data [Next, we tested the dose-response curve of the natural ligand dopamine to the Dhed data ,16. The 1 receptor antagonists, we examined the inhibitory effects of haloperidol, a known nonselective dopamine receptor antagonist, at various concentrations against the stimulation of 2 nM of dopamine (50) of haloperidol in the luciferase reporter gene assay was 34 nM, which is consistent with the published data [To determine whether the luciferase reporter gene assay is suitable for HTS of Ddopamine A. The hahed data .1 receptor antagonists.Z’-factor is one of the major statistical parameters commonly used to evaluate this assay performance in HTS . We calcC. yanhusuo were tested at an initial single screening concentration of 12.5 μM. By setting an activity threshold of 50%, eight compounds, including tetrahydropalmatine (2), corydaline (4), 13-methyl-dehydrocorydalmine (5), dehydrocorybulbine (6), dehydrocorydaline (7), palmatine (8), columbamine (9), and N-methyltetrahydrocolumbamine (10), were selected for further study. Concentration–response experiments were then performed on these eight primary hit compounds to determine the IC50 values. As shown in 2 and 10 showed partial antagonist effects because they were not able to inhibit the dopamine response completely even at high concentrations. The IC50 values of the eight compounds are listed in 50 values, are dehydrocorybulbine (compound 6) and tetrahydropalmatine (compound 2).Ten alkaloids  were established as the negative control cells to test the specificity to the D2+ mobilization assay to further evaluate the hit compounds obtained from the luciferase reporter gene assay screens. The cDNA plasmids of D1-like receptors were stably transfected into HEK 293T cells. With the coexpression of Gα15 protein, D1 receptors can be redirected to mediate intracellular calcium mobilization upon stimulation. Calcium levels were monitored using fluorometric imaging plate reader (FLIPR). The assay can also distinguish potential antagonists from agonists. Dopamine stimulated the Ca2+ mobilization in HEK 293T cell expressing human D1 receptors and Gα15 with an EC50 value of 580 nM. As shown in 2, 4, 5, 6, 7, and 9, displayed concentration-dependent antagonist responses. The IC50 values were similar to those measured by luciferase assay. Compounds 8 and 10 showed weak inhibitory effects because they inhibited the dopamine D1 receptor only at very high concentrations. We used a fluorescent Ca1 receptor, which belongs to GPCRs, plays an important role in pain [C. yanhusuo have been found to act on dopamine receptors, including tetrahydropalmatine, dehydrocorybulbine, and other isoquinoline alkaloids [C. yanhusuo, we have purified a series of alkaloids from C. yanhusuo extract. In order to determine their potential effects on dopamine receptors, we set to examine the antagonistic activity on the dopamine D1 receptor by using our established luciferase reporter gene assay system.GPCRs mediate various biological functions in response to a variety of ligands. GPCRs are involved in many signal transduction pathways and have been associated with numerous human diseases such as schizophrenia , cancers in pain , hyperte in pain , and the in pain . Severallkaloids ,24,25. Iαs protein is monitored by using a CRE positioned upstream of a reporter gene. In this study, we expressed the D1 receptor and CRE in pGL4.29 vectors containing luciferase reporter genes. The activation of D1 receptors leads to the activation of adenylyl cyclase and the increase of the intracellular concentration of cAMP. The cAMP second messenger system ultimately activates CRE and induces luciferase gene expression. Luciferase catalyzes a two-step process involving the conversion of D-luciferin substrate to oxyluciferin and yields emissions of yellow/green light (550–570 nm) [1 receptors by measuring enzymatic activity in response to changes in the levels of cAMP. Compared to other GPCR assays, the luciferase reporter gene assay system is cost-effective, easy to handle, sensitive, and suitable for a large-scale culture and automation. The reporter gene system is a technology where a reporter gene is synthesized in response to the specific signalling cascade under investigation. The activation or inactivation of the signalling cascade can be measured by monitoring the reporter protein expression by its enzymatic activities linked with a variety of colorimetric, fluorescent, or luminescent readouts. For GPCR assays, the activity of a receptor coupled to a G–570 nm) . We estaC. yanhusuo in the D1 receptor antagonist tests. We next validated these compounds with a FLIPR assay by measuring the intracellular Ca2+ change. Six out of eight compounds can be confirmed for their inhibitory activities. Two out of eight compounds, compounds 8 and 10, displayed very poor antagonistic effects on dopamine D1 receptors in the FLIPR assay. Glaucine (compound 1) demonstrated a significant blockade on D1 receptors in the FLIPR assay, while in luciferase reporter gene assay, it exhibited a biphasic curve. As shown in 1/CRE/Luc2P  [Using this CRE-luciferase reporter gene assay system, we identified eight alkaloids from RE/Luc2P . CompounPR assay . The exa release . However release . Since tiferase) . On the 2) and dehydrocorybulbine (compound 6) have been reported to be the primary analgesic components in C. yanhusuo and act on dopamine receptors [1 receptors.Tetrahydropalmatine , an alkaloidal component, has been recently reported to exert analgesic [1 receptors. Dehydrocorydaline  was originally isolated from the tuber of C. yanhusuo in 2008 [1 receptors.13-methyl-dehydrocorydalmine (compound  in 2008 . However9) and corydaline (compound 4) are isoquinoline alkaloids which have been found to bind to dopamine D1 receptors [1 receptors.Columbamine . pGL4.29 (luc2P/CRE/Hygro) luciferase reporter gene was purchased from Promega . Lipofectamine 2000 was purchased from Invitrogen . Dopamine was purchased from Sigma . Fluo-4 AM was purchased from Molecular Probes Inc. .Human embryonic kidney-293 cells (HEK293) were cultured in Dulbecco’s Minimum Essential Medium (DMEM) supplemented with 10% fetal bovine serum (FBS). Dopamine DC. yanhusuo was collected from Dongyang County . The herb was authenticated by the Institute of Medication, Xiyuan Hospital of China Academy of Traditional Chinese Medicine. The extraction procedure and compound isolation were performed as previously reported [reported ,35,36.1 receptor plasmid or was stably transfected individually in HEK293 cells. Transfection was carried out with lipofectamine 2000 reagent using the protocol provided by Promega. Stable cells expressing CRE-Luciferase and D1 receptor were selected in the presence of 700 μg/mL G418 and 200 μg/mL hygromycin for 10–14 days. Stable cells expressing CRE-Luciferase were singly selected in the presence of 200 μg/mL hygromycin. The obtained stable cells were then cultured with 350 μg/mL G418 and 100 μg/mL hygromycin or only 100 μg/mL hygromycin to maintain the selective growth.The pGL4.29 (CRE/luc2P//Hygro) luciferase reporter gene was stably co-transfected with dopamine D4 cells per well. After cells became adherent, they were stimulated in serum-starved DMEM for different hours to explore the most suitable starving time. Cells were then pretreated with compounds for 1 h prior to dopamine stimulation. Afterwards, the cells were lysed with luciferase lysis buffer and the luminescence of the firefly luciferase was measured with the FlexStation 3 .The examination of CRE-luciferase activity was performed by a modification of methods as described previously ,38. HEK22+ mobilization assay was performed using Flu-4 AM reagent as reported earlier [2+ concentration was monitored at 520 nm with the excitation wavelength at 488 nm over a period of 4 min. For antagonist tests, the compounds were first incubated with the cells for 10 min before the addition of dopamine.Fluorescent Ca earlier . The comAll statistical calculations were performed using GraphPad Prism 5.0 . Data from each dose-response curve were normalized to the maximal stimulation by dopamine. At least three independent experiments were performed.


A well-behaved model chemistry previously validated for the study of the chemical reactivity of peptides was considered for the calculation of the molecular properties and structure of the Taltobulin anticancer peptide. A methodology based on Conceptual Density Functional Theory (CDFT) was chosen for the determination of the reactivity descriptors.The molecular active sites were associated with the active regions of the molecule were associated with the nucleophilic and electrophilic Fukui functions. Finally, the bioactivity scores for the Taltobulin peptide are predicted through a homology methodology relating them with the calculated reactivity descriptors. The biodiversity of the marine environment and the associated chemical diversity constitute a practically unlimited resource of new antitumor agents in the field of the development of marine bioactive substances .N-methylated tripeptides with highly alkylated unnatural amino acids, was originally isolated from the sponge Hemiasterella minor . Hemiasterlins act as potent tumor growth inhibitors [Hemiasterlins comprise a small family of naturally occurring hibitors , 3.A synthetic analogue of hemiasterlin, taltobulin (HTI-286) has been synthesized in which the 3-substituted indole ring was replaced by phenyl group. Taltobulin inhibits the polymerization of purified tubulin and disrupts microtubule organization in cells. Then, it is considered as a potent inhibitor of proliferation and has substantially less interaction with multidrug resistance protein than currently used antimicrotubule agents .Assuming that an understanding of the chemical interactions is essential for the development of new pharmaceutical drugs, in this work we will be studying the chemical reactivity properties of Talbodulin by resorting to the Conceptual DFT methodology, which will allow the determination of the global properties as well as the local properties for the prediction of the active reaction sites, both electrophilic and nucleophilic. In a similar way, the descriptors of bioactivity (bioactivity scores) will be established through a procedure described in the literature , 6 tryinThe ChemAxon Calculator Plugins for Conformers Searching available in Marvin View 17.15.0 were used to generate 3D structures from SMILES strings, and to propose low energy conformers for structure property prediction and calculation. For the molecule considered in the current study, the lowest energy conformers were used as a starting point for the geometry optimization. The geometries of all the selected conformers were optimized with the DFTBA program. The molecular structures of the five lowest energy conformers were reoptimized by resorting to the MN12SX/Def2TZVP/H2O model chemistry. The optimized structures were confirmed to be real minima by vibrational frequency analysis (no imaginary frequency).The molecular structures of the optimized conformers of Taltobulin obtained as mentioned in the previous section, and whose graphical sketch is shown in Fig. Becke has recently mentioned that the adiabatic connection and the ideas of Hohenberg, Kohn, and Sham applying only to electronic ground states is a common misconception . In thisAccording to the results obtained when studying melanoidins –13 as wecument}χ , 19, Glocument}η , 19, Elecument}ω , Electroument}ω- , Electroument}ω+  and Net ment}Δω±  were calWe now turn our attention to the local descriptors of chemical reactivity, namely the Electrophilic Fukui function nt}f-(r) , 19, 23,nt}f+(r) , 19, 23 nt}Δf(r) –28. As fnt}Δf(r) –14. The P (the octanol/water partition coefficient) = 4.43, TPSA (the molecular polar surface area) = 98.73, nAtoms (the number of atoms of the molecule) = 34, nON (the number of hydrogen bond acceptors) = 7, nOHNH (the number of hydrogen bond donors) = 3, nviol (the number of violations of the Ro5) = 0, nrotb (the number of rotatable bonds) = 11, volume (the molecular volume) = 479.94 and MW (the molecular weight) = 473.66. Although this criteria cannot always be applied in general to peptides, it can be seen from the previous results that for Taltobulin the number of violations of the Ro5 is 0, which means that Taltobulin can be considered as a druggable molecule.Within the field of Chemoinformatics applied to the discovery of new pharmaceutical drugs, it is usual to verify the drug-likeness of the involved molecules resorting to some empirical rules, as for example, the Lipinski Rule of Five (Ro5) . This caAs the next step, a new task was accomplished by resorting to the same software for the determination of the bioactivity scores for different drug targets whose values for the Taltobulin peptide are GPCR Ligand = 0.43, Ion Channel Modulator = 0.15, Kinase Inhibitor = - 0.12, Nuclear Receptor Ligand = 0.19, Protease Inhibitor = 0.68 and Enzyme Inhibitor = 0.42.These bioactivity scores for organic molecules can be interpreted as active (when the bioactivity score is > 0), moderately active (when the bioactivity score lies between − 5.0 and 0.0) and inactive (when the bioactivity score In this research note, we have presented the results of a study of the chemical reactivity of a the Taltobulin anticancer peptide on the basis of the Conceptual DFT as a tool to explain the molecular interactions, the molecular properties related to bioavailability and the bioactivity scores.However, this information is insufficient to be considered for peptidomimetics studies and additional results from other peptides will be necessary.


DNA strand displacement reactions (SDRs) provide a set of intelligent toolboxes for developing molecular computation. Whereas SDR-based logic gate circuits have achieved a high level of complexity, the scale-up for practical achievable computational tasks remains a hurdle. Switching circuits that were originally proposed by Shannon in 1938 and nowadays widely used in telecommunication represent an alternative and efficient means to realize fast-speed and high-bandwidth communication. Here we develop SDR-based DNA switching circuits (DSCs) for implementing digital computing. Using a routing strategy on a programmable DNA switch canvas, we show that arbitrary Boolean functions can be represented by DSCs and implemented with molecular switches with high computing speed. We further demonstrate the implementation of full-adder and square-rooting functions using DSCs, which only uses down to 1/4 DNA strands as compared with a dual-rail logic expression-based design. We expect that DSCs provide a design paradigm for digital computation with biomolecules. DNA strand displacement reactions can be difficult to scale up for computational tasks. Here the authors develop DNA switching circuits that achieve high-speed computing with fewer molecules. In molecular computing, molecular circuits operate by the action of orthogonal molecules12. Hence, when the orthogonality decreases with circuit scale13, the actual achievable size is restricted, which is different with electronic circuits in which all elements are driven by the same electric signal. SDR enables an enzyme-free implementation strategy to develop molecular circuits for arithmetical purpose15, which offers high selection space of orthogonal molecules16.DNA strand displacement reactions (SDRs)19. However, limitations associated with logic gate circuits emerges, which hinders the scale-up for practical achievable computational tasks as follows. (i) Typical approaches to increase the scalability involves the combination of basic gates such as AND and OR21, which nevertheless increases the use of gates26. (ii) Using uniform motif and implementing AND and OR gate with different threshold concentrations have shown high modularity and potential for constructing complex computing networks. However, the thresholding and amplifying process generally poses a limit on the computing speed5. (iii) NOT logic is difficult to implement experimentally when the ON or OFF state of an input is assigned with the presence or absence of the molecule13. As the NOT gate started produce ON signals before receiving the output of its upstream gate, the circuit might generate a false output.Recent advances in modular molecular design and programmable reaction dynamics have led to the development of SDR-based Boolean logic gates with unparalleled complexity27 established a systematic symbolic approach to design relay contacts or switching circuits (SCs). In theory, any digital circuit can be represented by a set of equations, the terms of the equations corresponding to certain switches in the circuits. SCs can implement arbitrary digital functions in an efficient and economical manner. For example, SCs form the basis of modern telecommunication that is characteristic of fast speed and high bandwidth. Previous work has theoretically proposed the implementation of SCs with “seesaw” gates28. Here we develop an SDR-based strategy to experimentally realize DNA-based SCs (DSCs) for molecular digital computing. In a typical DSC, switches act as the sole basic functional element in a circuit, the molecular design is thus uniform, which allows high modularity, programmability, and scalability. The direction of current signal transmission can be finely controlled by the difference in the free energy of molecules in the reaction pathway. We also expect the increase of the computing speed with the reduced use of orthogonal molecules.During the early stage of electronic circuits, Shannon29. Here we designed molecular switches based on SDR, to emulate such functions for constructing DSCs    Fig. . In contt1/2 < 3 min)  Fig. . When ont1/2 < 3 min; Fig. With the programmability of C domain on downstream switch molecules, the current signal from an upstream switch can be easily transmitted to multiple downstream switches (fan-out). We designed and tested a DSC with a two-output switch Fig. . As showt1/2 < 3 min, Fig. 26With the programmability of current signal strand on upstream switches, DSCs here can easily support fan-in that represents current signals from multiple upstream switches enter one downstream switch Fig. . As show27 to solve symmetric functions, we developed a programmable switch canvas with complementary switch pairs  than the logic gate circuit (t1/2 ~ 10 min) and a lower signal leakage for outputs supposed to be 0. These results suggested that even with the same molecular design, DSC showed higher computing speed and signal-to-noise ratio (SNR) than logic gates for some functions.As an example, we implemented a three-input voting logic by routing the switch canvas. As shown in Fig. 33. The direct mapping of the truth table on the programmable switch canvas generated a three-layer ten-switch DSC to implement the full-adder function   Fig. . When itin) Fig. .13, the DSC had at most 24 strands participating one computation, showing a nearly 75% reduction in required strands  and subsequent mixing by shaking. The 96-well black assay plate was then put back into the Hybrid Reader and the experiment was resumed. Fluorescence kinetics of each well was detected with intervals of 1 min or 2 min. The obtained fluorescence signal was converted to concentrations of the corresponding unquenched fluorescence strands using the calibration curve for each reporter. To construct a calibration curve, solutions containing predefined concentration of opened reporter molecules were tested  was determined by the maximum value of a parallel experiment. We used 0.4× and 0.6× as thresholds. Signals below 0.4× were treated as 0 and signals above 0.6× were treated as 1. If an output signal was between 0.4× and 0.6×, we considered it as a confusing result.Kinetic fluorescence measurements were performed using Synergy H1 Hybrid Multi-Mode Reader (BioTek) and Corning 96-well black assay plate. The temperature was kept at 20 °C throughout the reaction. Excitation and emission wavelengths used in the experiments were 510 nm and 540 nm, respectively, for TET. In general, all the circuit components, except the Input strand(s), were mixed according to the optimized molar ratio of components in TE buffer with 12.5 mM MgClSupplementary informationPeer Review File


The use of multi-parametric magnetic resonance imaging (MRI) in the evaluation of breast tuberculosis (BTB).To evaluate the value of diffusion-weighted imaging (DWI), T2-weighted (T2W) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiating breast cancer (BCA) from BTB.We retrospectively studied images of 17 patients with BCA who had undergone pre-operative MRI and 6 patients with pathologically proven BTB who underwent DCE-MRI during January 2014 to January 2015.p = 0.006). The mean T2-weighted signal intensity (T2SI) was lower for the BCA group (521.56 ± 233.73) than the BTB group . An ADC mean cut-off value of 1558.79 yielded 66% sensitivity and 94% specificity, whilst the T2SI cut-off value of 790.20 yielded 83% sensitivity and 83% specificity for differentiating between BTB and BCA. The homogeneous internal enhancement for focal mass was seen in BCA patients only.All patients were female, with the age range of BTB patients being 23–43 years and the BCA patients being 31–74 years. Breast cancer patients had a statistically significant lower mean apparent diffusion coefficient (ADC) value (1072.10 ± 365.14), compared to the BTB group (1690.77 ± 624.05, Multi-parametric MRI incorporating the DWI, T2W and DCE-MRI may be a useful tool to differentiate BCA from BTB. Breast tuberculosis and BCA may present clinically in a very similar fashion leading to potential misdiagnosis10; given that an accurate diagnosis is essential if the patient is to receive correct and timely treatment, this may be problematic.8Although breast cancer (BCA) is the most prevalent malignancy amongst South African women, accounting for 20.62%,11 It is therefore appropriate to investigate the use of newer and more complex imaging modalities in the differentiation of BCA and BTB. Studies that have used magnetic resonance imaging (MRI) to differentiate EPTB from malignant lesions are those which focused on other body parts such as the central nervous system (CNS)14 and the musculoskeletal system.16 Peng et al. used the diffusion-weighted imaging (DWI) and magnetic resonance spectroscopy (MRS) to differentiate intracranial tuberculomas from high-grade gliomas and found significant differences. The diagnostic accuracy was higher when using the minimum apparent diffusion coefficient (ADC) value from the DWI than the maximum MRS ratios of Cho/Cr, Cho/NAA and Cho/Cho.13 Magnetic resonance imaging has also been utilised in pulmonary tuberculosis (PTB) to differentiate between tuberculous and malignant nodules.20 Only one study was found in the literature which aimed to differentiate BTB from BCA with the use of MRS in four BTB patients with no comparison group.21 The authors suggested that the absence of choline peak and the presence of a strong lipid peak favoured BTB rather than BCA.21Conventional imaging with mammography and ultrasound has limited ability to differentiate between BTB and BCA.27 Diffusion-weighted imaging measures the microscopic movement of water molecules in biological tissues, with the pathologic processes altering their mobility; the detection of these changes aids in lesion characterisation.28 The ADC is derived from DWI sequences. Apparent diffusion coefficient values, measured in mm2/s, are calculated within a given area. This reflects water restriction. Tissues with high ADC values, because of increased diffusion, display a brighter signal, whereas those with lower ADC values appear darker, because of restricted diffusion.29 Most malignant lesions display lower ADC values when compared to benign or inflammatory lesions.26 Rong-Feng Qu et al. recently conducted a meta-analysis of the differential diagnosis of benign and malignant breast tumours. The authors found that the ADC values of normal breast tissues were higher than those of benign tissues, and that the values of benign lesions were higher than those of malignant tumours.23There are multiple studies that utilise DWI and ADC to distinguish malignant from benign breast disease.30 Further advantage is the ability to evaluate the breast lesion enhancement parameters and kinetic curves. It has been demonstrated that during the wash-in rate, malignant lesions demonstrated higher maximum enhancement when compared to benign lesions.31 Dynamic contrast-enhanced MRI kinetic characteristics have been shown to correlate with tumour neovascularity in which more vascular tumours demonstrate strong enhancement.32Breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) involves administration of a magnetic compatible intravenous (IV) contrast agent in order to detect and characterise lesions.33 The displayed T2 signal intensity (T2SI) is used in the characterisation of tissues and lesions.33 Studies that used the T2SI in the discrimination of benign and malignant breast lesions mainly analysed the morphologic T2SI appearance rather than the quantitative values.35 The majority of BCAs appear hypointense on T2W, compared to most benign lesions that appear hyperintense.36The T2-weighted (T2W) MRI uses the tissue transverse relaxation times to generate the signal.The purpose of our study was to evaluate the use of the DWI parameter of ADC, the DCE-MRI enhancement morphologic characteristics and the T2W parameter of T2SI value to differentiate BCA from BTB.We retrospectively identified 24 patients with histologically proven BCA  who underwent DWI, T2W and DCE-MRI during January 2014 to December 2014. Seven patients did not have a full set of images on the picture archiving and communication system (PACS) and were excluded from the study, which resulted in the final total of 17 patients.For the BTB group, we included six prospectively and consecutively identified patients with proven BTB who also underwent the DWI, T2W and DCE-MRI. Although five patients had conclusive histology from either the breast or the axillary lymph nodes, one patient had inconclusive histology from breast and axilla, but had proven concurrent PTB, for which she was receiving anti-tuberculous therapy (ATT). Her clinical and radiological features were compatible with BTB, and both the breast and the axillary nodes responded satisfactorily to ATT. All BTB patients had undergone screening investigations at the referring breast clinic, including ultrasonography, with or without mammograms, depending on their age. Following the histological confirmation of BTB, the patients were invited for a baseline MRI scan within 2 weeks of confirmation of the diagnosis. Scans were not performed within 2 weeks of a biopsy in order to avoid the presence of haematoma and/or inflammation confounding our results.®  Standard 469 mg/mL (0.5 mmol/mL) at a dosage of 0.1 mmol/kg was administered to all the patients. The IV contrast rate was 3 mL/s followed by a 20 mL saline flush administered as a bolus. The T1 dynamic phase scan time was 6 min 41 s, during which five dynamic sequences were obtained in the axial position at various time points. The DWI images with the ADC map were also acquired during the same scan. The technical parameters are reported in Magnetic resonance imaging images were retrospectively analysed following retrieval from the hospital’s PACS. Magnetic resonance imaging was performed on a 1.5 Telsa machine  using a dedicated breast coil. The patients were scanned in the prone position. A power injection of 20 mL intravenous (IV) MagnevistAll the images were read by one of the authors who is a radiologist with more than 10 years’ experience in breast radiology. The following qualitative parameters were recorded:The BCA pathological subtype from the pathology records.37 and included the following:■The enhancement pattern: Either mass-like enhancement (MASS) or non-mass enhancement (NME).■Non-mass enhancement distribution pattern: Focal, linear, segmental, regional, multiple regions or diffuse.■Non-mass enhancement internal enhancement: Homogeneous, heterogeneous, clumped and clustered ring.■MASS internal enhancement: Homogeneous, heterogeneous, rim enhancement and dark internal septations.The DCE-MRI parameters were classified using the Breast Imaging Reporting and Data System (BI-RADS) descriptorsThe presence or absence of axillary nodes was added to the above descriptors.−6 mm2/s) derived from the DWI images, and T2SI value derived from the T2W. For the quantitative parameters, the region of interest (ROI) was drawn on three contiguous axial images around the lesion circumference and the average recorded. All images were analysed on the dedicated Syngo-via  reading platform.We further recorded the ADC values  and analysed using the STATA software package . Differences in ADC value and T2SI between the two groups were assessed with a two-tailed unpaired t-test. Differences in ADC value and T2SI with enhancement pattern matching were assessed using analysis of variance (ANOVA). The results were considered significant where p < 0.05.Data were entered into an Excel spreadsheet  (Reference number BF213/13).All the patients were female. The ages of the BTB patients ranged from 23 to 43 years, and for those with BCA, 31–74 years. Three BTB patients were HIV positive, one HIV negative and two not tested. The BCA subtypes included 13 cases of invasive ductal cancer (IDC) (76.5%); 3 cases of DCIS (17.6%), of whom one had high-grade DCIS; and 1 case (5.9%) of invasive lobular cancer (ILC).The MRI morphological enhancement characteristics of the BCA patients are shown in In the patients with BTB, 3/6 (50%) had mass-like enhancement, and 3/6 (50%) had NME patterns.In the patients with BCA, 11/17 (65%) had mass-like enhancement, and 6/17 (35%) had NME patterns.Amongst the BTB patients, 3 (50%) had clumped diffuse NME, 2 (33%) showed focal mass rim and 1 (17%) demonstrated multiple regions mass rim. Axillary nodes in BTB patients demonstrated rim enhancement .Of the BCA patients, 5 (29%) had heterogeneous enhancement, 7 (41%) had homogeneous enhancement, 4 (24%) had clumped enhancement and 1 (6%) had clustered ring enhancement .The representative images demonstrating data extraction for ADC values and T2SI measurements of the BCA and BTB patients are depicted in p = 0.006). The mean T2SI for BTB was 787.7 ± 196.0, and for BCA, it was 521.6 ± 233.7 (p = 0.020)  .6 mm2/s, with an area under the curve (AUC) of 0.81 (CI 0.60% – 0.94%)  curve analysis showed a sensitivity of 66.7% (CI 22.3% – 95.7%) and specificity of 94.1% (CI 71.3% – 99.9%) for a diagnosis of BTB at a cut-off value of 152.2 × 10– 0.94%) .The corresponding values for T2SI were 83.3% specificity (CI 35.9% – 99.6%) and 82.4% sensitivity (CI 56.6% – 96.2%) at a cut-off value of 670.6, with an AUC of 0.77 (CI 0.54% – 0.91%) .p = 0.040) and T2SI (p = 0.015).These differences persisted when the two groups were matched for the patterns of mass-like enhancement (MASS) and non-mass enhancement (NME) and compared with ANOVA. Significance was shown for both mean ADC value . In contrast, Chatterjee et al.12 found similar ADC values for brain tuberculomas and brain metastases.This outcome is explicable in that malignant lesions have high cellularity with resulting restricted diffusion, yielding lower ADC values, a parameter derived from the DWI. This finding has been shown to be consistent across many studies,35 The data on the use of quantitative T2SI as a discriminator between benign and malignant breast lesions are scanty.40 Other studies in which T2SI quantitative values were used in differentiating benign from malignant lesions involve other parts of the body and not the breast.42 Henz et al.41 investigated pulmonary nodules with MRI using the quantitative parameters ADC and T2SI in a granulomatous endemic area. They found both the mean T2SI ratio and the ADC to be significant in differentiating the benign from the malignant pulmonary nodules.The studies that utilised T2SI to discriminate the benign from the malignant breast lesions predominantly focused on the qualitative T2 signal morphologic appearance rather than the quantitative value as in our study.43Post-contrast morphological analysis revealed that the homogeneous internal enhancement pattern was exclusively observed in BCA patients. This qualitative feature can be used as a further descriptor for separating the two conditions when other imaging or pathology results are equivocal. The diffuse distribution of BTB was visually associated with enlargement of the breast; although this appearance can be confused with inflammatory BCA, the presence of rim-enhancing axillary nodes is more supportive of BTB than BCA.Based on our findings, we conclude that the combination of DCE-MRI morphologic enhancement pattern, the T2SI and the quantitative DWI ADC values may provide some useful non-invasive information in distinguishing malignant from non-malignant illness  in patients with suspicious breast lesions. Development of accurate diagnostic algorithms will require accumulation of a larger patient database for BTB in particular; more broadly, however, continued investigation is appropriate in terms of the development of tests to distinguish malignant from benign disease more generally. As with mammographic and ultrasonic findings, the MRI findings alone are not sufficient to distinguish BTB and BCA with acceptable accuracy, and histology remains essential for this purpose.