Escherichia coli at several points along a concentration gradient for three different antibiotics, asking how rapidly resistance evolved and whether populations became specialized to the antibiotic concentration they were selected on. Populations selected at higher concentrations evolved resistance more slowly but exhibited equal or higher fitness across the whole gradient. Populations selected at lower concentrations evolved resistance rapidly, but overall fitness in the presence of antibiotics was lower. However, these populations readily adapted to higher concentrations upon subsequent selection. Our results indicate that resistance management strategies must account not only for the rates of resistance evolution but also for the fitness of evolved strains.Antibiotic concentrations vary dramatically in the body and the environment. Hence, understanding the dynamics of resistance evolution along antibiotic concentration gradients is critical for predicting and slowing the emergence and spread of resistance. While it has been shown that increasing the concentration of an antibiotic slows resistance evolution, how adaptation to one antibiotic concentration correlates with fitness at other points along the gradient has not received much attention. Here, we selected populations of  FurtherBacteria may be exposed to widely varying doses of antibiotics. During the course of treatment, antibiotic concentrations are generally high, but vary temporally and spatially across body tissues and organs, exposing bacteria to a variety of selection regimes ,4. In thPrevious studies have demonstrated indirectly that selection at different antibiotic concentrations results in selection for different genotypes –15, but 50; the minimum inhibitory concentration—MIC; and double the MIC—2MIC)  and subsequently measured the growth of evolved populations in all three antibiotic concentrations and in the antibiotic-free environment. We employed the same experimental design for three antibiotics  and found that populations selected at higher concentrations exhibit equal or higher fitness across all antibiotic concentrations.Here, we ask whether: (i) antibiotic concentration impacts the dynamics of resistance evolution, (ii) populations specialize to the concentration they were selected in, (iii) resistance is associated with a fitness cost, and (iv) selection at lower antibiotic concentrations constrains subsequent adaptation to higher concentrations. To address these questions, we evolved six replicate bacterial populations for 28 days (approximately 200 generations) in one of three antibiotic concentrations Escherichia coli K-12 strain to three antibiotics—tetracycline, streptomycin and nitrofurantoin. These antibiotics were chosen because they have a different mode of action and because resistance to them is commonly observed in experimental evolution studies of resistance, as well as clinical and agricultural isolates of E. coli [50, MIC and 2MIC), giving rise to 54 evolving populations, and a ‘wild-type’ population, propagated in the absence of antibiotics. EC50 is the half-maximal effective dose of a given antibiotic, i.e. the concentration of an antibiotic that results in half the OD600 reached by wild-type cells grown for 24 h in the absence of antibiotics. The MIC is the lowest antibiotic concentration that resulted in no measurable growth after 24 h; 2MIC is double the MIC. We obtained these concentrations by measuring a dose–response of the naive population by transferring 1.5 µl of overnight culture to a serial dilution of each antibiotic, and measuring OD600 after 24 h of growth  . During the selection procedure, every 24 h 1.5 µl was transferred to 1.2 ml of fresh medium with the same antibiotic concentration. Since populations evolving at MIC and 2MIC could not grow initially, we immigrated 1.5 µl from the wild-type culture to these populations at every transfer. We immigrated half as much to the populations evolving at EC50. After 28 days, we grew all populations in the absence of antibiotics for 24 h, so that all populations reached a similar density. Then, we transferred 1.5 µl of each culture into appropriate media, in order to measure the growth curves of the wild-type and of all evolved populations in (i) the absence of antibiotics and (ii) EC50, MIC and 2MIC of the antibiotic in which the populations evolved , using a BioTek H1 plate reader. From these growth curves, we determined the maximum growth rate, as the greatest slope of the log-transformed growth curve. In addition, we measured the dose–response curves of all evolved populations in the manner described above.In this study, we exposed  E. coli . We evol (b)600 value that was higher by 0.3 than that reached by the wild-type population). We tested whether overall differences in maximum growth rates depended on the selective environment by performing an analysis of variance (anova(lm) function in R) within each tested environment . To specifically test for differences between every pairwise combination of tested concentration within each antibiotic, we followed up ANOVA with Holm's corrected pairwise t-tests. Permutation tests for the maximum growth rates confirmed the conclusions . We performed one-sample t-tests (comparing with the wild-type population) in order to determine whether resistance was associated with a cost. For further details, see electronic supplementary material, S1 and S2.We performed a survival analysis (using the survreg function in R) to determine the effect of the antibiotic concentration on the time to evolve resistance , it reached an OD (c)50 and 2MIC for another nine transfer cycles at 2MIC, using the same protocol as above except without the immigration from the wild-type. We subsequently measured their growth curves at 2MIC and compared the maximum growth rates between them, in the same manner as described above. Furthermore, we tested whether differences in maximum growth rates between populations originally selected at EC50 and at 2MIC changed significantly upon further selection. To do so, we randomly paired populations selected at EC50 and 2MIC and calculated differences in maximum growth rates for both the original evolved populations and those that had undergone further selection. We performed pairwise t-tests for all possible pairings and report average p-values.We selected populations that originally evolved at EC. 3 (a)χ2 = 26.3, p < 0.0001; streptomycin: χ2 = 10.9, p < 0.005; nitrofurantoin: χ2 = 44.3, p < 0.0001). In tetracycline and nitrofurantoin, resistance emerged more slowly in populations selected at high concentrations. In streptomycin, resistance evolved most slowly at 2MIC but evolution was faster at MIC than at EC50.We observed the evolution of resistance in all populations by the end of the selection procedure. We found an effect of antibiotic concentration on rates of resistance evolution in all three antibiotic environments ( (b)50, MIC and 2MIC of the antibiotic they were selected in, as well as in the absence of antibiotics 50: t5 = −8.37, p < 0.0005; MIC: t5 = −9.17, p < 0.0005; 2MIC: t5 = −12.00, p < 0.0001).In order to analyse if resistance was associated with a fitness cost, we compared maximum growth rates in the absence of antibiotics between the wild-type population (that had evolved in the absence of antibiotics) and the evolved populations . We foun (d)50 and 2MIC for nine additional daily transfer cycles (approximately 100 generations) to high concentrations (2MIC) of the same antibiotic they were selected in, and asked if fitness differences reduced. After this further period of evolution, the differences in growth rates between populations originally selected at EC50 and at 2MIC had decreased significantly for tetracycline and streptomycin  that were selected at higher concentrations not apparently also selected at lower concentrations? Such evolutionary dynamics could result from the distribution of mutational effects (DME). Many experimental estimates of DMEs show that small-effect mutations are more abundant than mutations of large effect –29. It set al. explored the question of how antibiotic concentration influences resistance evolution, albeit by adopting different approaches [et al [et al. selected for resistance only above MIC, while we also selected below MIC, allowing for de novo evolution of resistance; (ii) our study falls in between the two studies since it encompasses the entire evolutionary process (appearance of first mutations and subsequent adaptation). The set-up considered in our study corresponds to adaptation to a sink environment with immigration from an antibiotic-free reservoir as may happen during antibiotic treatment with imperfect drug penetration. In contrast with Harmand et al. [Two recent studies by Harmand proaches ,17. In ts [et al . There ad et al. , who ideE. coli emerges through point and other chromosomal mutations [E. coli. More complete understanding of how antibiotic concentration impacts resistance evolution must further expand on our work to account for the similarities and differences between various mechanisms of resistance and means of their inheritance.While resistance to many antibiotics in utations , this isutations . Furtherutations . Finallyutations . All theutations ,36. In tManipulations of antibiotic concentrations, as well as pesticides and other xenobiotics, form an important resistance management strategy ,37–41. S


Recruitment of microorganisms to the rhizosphere varies among plant genotypes, yet an understanding of whether the microbiome can be altered by selection on the host is relatively unknown. Here, we performed a common garden study to characterize recruitment of rhizosphere microbiome, functional groups, for 20 expired Plant Variety Protection Act maize lines spanning a chronosequence of development from 1949 to 1986. This time frame brackets a series of agronomic innovations, namely improvements in breeding and the application of synthetic nitrogenous fertilizers, technologies that define modern industrial agriculture. We assessed the impact of chronological agronomic improvements on recruitment of the rhizosphere microbiome in maize, with emphasis on nitrogen cycling functional groups. In addition, we quantified the microbial genes involved in nitrogen cycling and predicted functional pathways present in the microbiome of each genotype. Both genetic relatednesses of host plant and decade of germplasm development were significant factors in the recruitment of the rhizosphere microbiome. More recently developed germplasm recruited fewer microbial taxa with the genetic capability for sustainable nitrogen provisioning and larger populations of microorganisms that contribute to N losses. This study indicates that the development of high-yielding varieties and agronomic management approaches of industrial agriculture inadvertently modified interactions between maize and its microbiome. For the past 70 years, modern industrial agriculture has been characterized by technological advances in crop breeding and high input application of nitrogenous fertilizers . AdoptioAssembly of the plant rhizosphere microbiome is driven by plant genetic and evolutionary history . Plant mThroughout the 20th century, maize breeders have made concerted efforts to optimize yield under a range of agronomic management environments , 13. SinHere, we used a germplasm chronosequence of expired Plant Variety Protection Act maize inbred lines ranging from 1949 to 1986 . These lThe goal of this study was to examine if breeding and selection of maize genotypes during the decades of increasing nitrogen application altered how maize germplasm recruits its rhizosphere microbiome, as well as microbiome function. First, we set out to determine if the bacterial and fungal rhizosphere microbiome changed across our chronosequence of maize germplasm. Second, we sought to determine if maize lines developed over the past 50 years difference in their ability to recruit microbial functional groups related to nitrification, denitrification, and nitrogen fixation. Finally, to understand how the metabolic genes of rhizosphere microorganisms change across the germplasm chronosequence, we predicted the metabolic pathways of microbes that responded to the germplasm chronosequence. These results will allow us to determine if crop breeding for yield combined with changing agricultural practices disrupted the interactions between plants and their microbiomes, with potential consequences for nutrient cycling in agroecosystems. If modern breeding has unintentionally transformed the interaction of maize with key functional groups in its microbiome, it must be rewilded to improve agroecosystem sustainability.www.panzea.org. Supplemental Fig. www.maizegdb.org) and USDA GRIN (www.ars-grin.gov). More information about the history and development of these maize lines is presented in Table Maize seed stocks were obtained from the USDA North Central Regional Plant Introduction Station  and Maize Genetics Cooperation Stock Center . Twenty inbred lines were selected for comparison: these 20 lines span a breeding period from 1949 to 1986, come from two heterotic genetic groups , and are adapted for maize production in the U.S. Corn Belt Table . The usaMaize lines were grown in greenhouse conditions to isolate the effects of inbred genotype on the microbiome. The planting medium was a combination of live and autoclaved soil mix. The live inoculum soil was collected from agricultural soil located on the Crop Sciences Research and Education Center—South Farms at the University of Illinois at Urbana-Champaign, Urbana, IL. (40°03′31.0″N 88°14′13.4″W). At the time, the soil was out of agricultural rotation (corn-soy) for at least 2 years. Inoculum soil was sieved (2 mm) then added (10%) to a steam pasteurized mix of soil: calcined clay: torpedo sand (1:1:1). An inoculum sample was collected before plant growth to characterize the microbiome before plant treatment. For each genotype, ten replicate classic 600 pots  were sown with three seeds in each. Pots were thinned a week after germination leaving only a single plant per pot for the remainder of the growth. In total, 200 plants were grown. They were placed in a completely randomized design in the greenhouse with 16 h of light and 8 h of darkness. All plants were connected to an irrigation system that fertilized plants twice a week. Plants were fertilized with a liquid nutrient solution, specifically Cal-Mag (N15-P5-K15), at a rate of 150 ppm. Nitrogen was applied as 11.8% nitrate nitrogen, 1.1% ammoniacal nitrogen, and 2.1% urea nitrogen. All plant treatments were maintained under the same fertilizer regime. While a direct comparison of greenhouse fertilization regime to field rates is difficult, the nitrogen level used in this study would be comparable to modern high fertilization levels . Rhizosphere samples of all ten replicates for each genotype were harvested for molecular analysis.amoA, nirS, nirK, nosZ, norB, and nifH genes. The Fluidigm access array IFC chip was used to prepare sequencing amplicons. This method allows for the simultaneous amplification of target functional genes using multiple primer sets . DNA sequencing was performed for bacterial, archaeal, and fungal amplicons using an HiSeq 2500 Sequencing System . Primer information is provided in supplemental Table nirK reads were trimmed to their amplicon size of 165 bp.For this experiment, we characterized the microbiome and diagnostic functional genes related to transformations that occur in the nitrogen cycle: nitrogen fixation, nitrification, and denitrification. Amplicon sequencing was performed on prokaryotic 16S rRNA genes, fungal ITS2, http://fungene.cme.msu.edu/) [Once quality preprocessing was performed, FASTQ reads were converted to FASTA format. Using USEARCH-UPARSE version 8.1 , sequencsu.edu/) . All OTUP5.The number of raw reads generated from sequencing run reads present after the quality filter, and the rarefaction level of reads per sample for 16S rRNA, ITS, and N-cycling genes are reported in supplemental Table Quantitative PCR (qPCR) was used to determine the abundance of functional genes in each of the rhizosphere microbial communities. Specific target amplification (STA), explained in , was carnifH, nosZ, norB, nirK, nirS, bacterial amoA, and archaeal amoA). The relative effect of genotype, heterotic group, genetic relatedness, and decade of germplasm development on the rhizosphere microbiome composition was assessed using permutational analysis of variance (PERMANOVA) with the “adonis” function, from the community ecology R package, “vegan” [The microbial communities were evaluated as separate datasets for each amplicon  (referred to as the genotypic mean microbiome). These mean microbial communities were generated using the “aggregate” function in base R; here this function was used to find the mean of the amplicon data matrix based on the replicates within each genotype.To control for the variance within individual genotypes when performing our analysis for a decade and heterotic group effects, we used the mean microbiome for each genotype  in R . Prior tIn this common garden study, we identified 15,072 different 16S rRNA operational taxonomic units , and 1027 fungal OTUs were identified from the ITS2 region.R2 = 0.17, p < 0.001; fungal: R2 = 0.13, p < 0.001). When performing our analysis on the genotypic mean microbiome, we revealed that a decade of germplasm development explained 16.79% of the variance in the prokaryotic microbiome. In comparison, the heterotic group explained 8.1% of the variance  but differed among heterotic groups (p = 0.028)  Fig. .Fig. 2ChnifH OTUs, 95 archaeal amoA OTUs, 200 bacterial amoA OTUs, 8632 nirK OTUs, 1186 nirS OTUs, 1068 norB OTUs, and 1864 nosZ OTUs. In response to the germplasm chronosequence, 3 of 7 nitrogen cycling genes showed changes in community membership, and 3 of 7 nitrogen cycling genes changed in copy number per ng of DNA  and heterotic group  was shown to be significantly impacted by the germplasm chronosequence and heterotic group. We found a significant change in the composition of bacterial amoA genes .Several of the denitrification genes were significantly different among the chronosequence and heterotic groups Figs. , S6.4–7.WGCNA  identifip < 0.05) showing evidence of undergoing recent selection events according to Tajima’s D statistic. Eighty-five of these regions were suggestive of a selective sweep and two of balancing selection  Fig. . These cnifH, in more recently developed germplasm (Fig. The consequences of these microbiome changes extended to the composition and abundance of microbial genes associated with nitrogen cycling observed in the rhizosphere. We saw decreases in the abundance and changes in the composition of diazotrophs, indicated by asm Fig. . The incVarious functional genes related to denitrification and nitrification increased in abundance and changed in composition through the germplasm chronosequence Fig. . While nPlant species regulate microbial enzyme production and metagenomic capacity in the rhizosphere , 63. HerIn conclusion, industrial breeding practices and agronomic management approaches have transformed maize’s interactions with its rhizosphere microbiome at a taxonomic and functional genomic level. These microbiome differences potentially alter nitrogen processing among plant cultivars and the movement of nitrogen in the agroecosystem as a whole. These changes likely occurred because of the combination of intense selection for aboveground traits and increased use of synthetic nitrogen fertilizers that reduced reliance on microbially-mediated nitrogen cycling processes. Modern agricultural practices have disrupted and accelerated the reactive nitrogen cycle. Maize has been a major contributor to this global disruption as it is one of the most farmed and fertilized crops in the world . AlteratSupplemental figures and tablesSupplemental tables S10-12


The limit for possible survival after extremely preterm birth has steadily improved and consequently, more premature neonates with increasingly lower gestational age at birth now require care. This specialized care often include intensive pharmacological treatment, yet there is currently insufficient knowledge of gestational age dependent differences in drug metabolism. This potentially puts the preterm neonates at risk of receiving sub-optimal drug doses with a subsequent increased risk of adverse or insufficient drug effects, and often pediatricians are forced to prescribe medication as off-label or even off-science. In this review, we present some of the particularities of drug disposition and metabolism in preterm neonates. We highlight the challenges in pharmacometrics studies on hepatic drug metabolism in preterm and particularly extremely (less than 28 weeks of gestation) preterm neonates by conducting a scoping review of published literature. We find that >40% of included studies failed to report a clear distinction between term and preterm children in the presentation of results making direct interpretation for preterm neonates difficult. We present summarized findings of pharmacokinetic studies done on the major CYP sub-systems, but formal meta analyses were not possible due the overall heterogeneous approaches to measuring the phase I and II pathways metabolism in preterm neonates, often with use of opportunistic sampling. We find this to be a testament to the practical and ethical challenges in measuring pharmacokinetic activity in preterm neonates. The future calls for optimized designs in pharmacometrics studies, including PK/PD modeling-methods and other sample reducing techniques. Future studies should also preferably be a collaboration between neonatologists and clinical pharmacologists. Prematurely born children represent a very fragile subset of neonates, as they often present a complex and challenging pathophysiological condition associated with increased risk of long-term morbidity and mortality. Treatment includes various pharmaceutical agents, yet there is currently insufficient knowledge of gestational age dependent differences in drug metabolism. This potentially puts the preterm at risk of receiving suboptimal drug doses with a subsequent increased risk of adverse or insufficient drug effects .Although the need for clinical research to identify optimal drug dosing in term and preterm neonates has long been acknowledged as indispensable , the proThe average human gestation is 40 weeks, and prematurity is defined as being born before 37 weeks of gestation . The global prematurity rates are approximately 10% but vary from 4 to 5% in some European countries to 15–18% in some parts of Africa and Asia . It is aAlthough there are wide variations in prematurity survival rates across regions and countries , overallAnother major driving factor for the improvement in premature survival rates has been pharmacological advancements, both prenatal, immediately post-natal and post-natal. Antenatally, the administering of a course of corticosteroids to women prior to anticipated preterm birth has been demonstrated to have a marked positive effect of subsequent preterm mortality and morbidity ever since the first randomized controlled trial of betamethasone for the prevention of respiratory distress syndrome in preterm neonates in 1972 . SubsequA huge leap in pharmacological treatment of preterm children, and possibly one of the single greatest breakthroughs in treatment of premature children, was the development of exogenous surfactant administration techniques in the 1980s and early 1990s. Since the first successful attempts in 1980  using thPharmacological treatment remains a cornerstone in postnatal care in preterm children, as demonstrated by a recent review of drug utilization studies in neonatal units that found a high mean number of drugs per infant, with eight studies reporting a very high burden (>30 drugs per infant). Drug use patterns were found to be generally uniform with antibiotics being the most frequently prescribed drug in the neonatal department . NaturalAccurate dosing is essential for a safe and effective pharmacological treatment of premature neonates. An in-depth knowledge of the anatomical and physiological particularities of preterm neonates is therefore crucial for the understanding of the drug pharmacokinetics in this population. Herein, the differences in ontogeny between the extremely, the very and the late preterm neonate should be taken into consideration .Also, most aspects of drug disposition are subject to change in case of co-morbidities, which unfortunately relatively often occurs in premature neonates. Sepsis, surgery, and (for moderate and late preterm neonates where such treatment is possible) advanced treatment such as whole body hypothermia , extracoA summary of the most important prematurity associated characteristics of pharmacokinetics in preterm neonates is presented in In preterm neonates, the immaturity of absorptive surfaces may influence drug exposure . At presThe exposure of drugs after rectal administration is generally increased in preterm neonates, e.g., paracetamol, most likely due to developmental immaturity of the hepatic metabolism rather than increased mucosal translocation . Due to The presence of a thinner stratum corneum in preterm neonates, a higher body surface area-to-weight ratio as well as higher cutaneous perfusion and hydration of the epidermis places preterm neonates at risk of adverse effects from topical exposures due to an increased absorption e.g. corticosteroids  and chloIn the extremely preterm neonate, total body fat content can be as low as 1% of the total body weight and total body water is decreasing from 85% in preterm neonates to 75% in term neonates  Sharma . Due to At the time of birth, neonates have lower concentrations of the drug-binding proteins α1-acid glycoprotein and albumin when compared to older children . The amoHigher CNS drug concentrations may occur in preterm neonates due to reduced outward drug transport, however, this area still needs to be elaborated . ChangesThe major site of drug metabolism is the liver and the drug metabolizing enzymes are broadly divided into phase I and phase II enzymes. The phase I enzymes are responsible for primary oxidation, reduction and hydrolysis processes. The most important group of enzymes involved in phase I metabolism are cytochrome (CYP) P450 enzymes with a major contribution of cytochrome P450 3A4 . HoweverPhase II enzymes are responsible for conjugate drug molecules to allow excretion. Phase II drug metabolizing enzymes are mostly transferases and include: UDP-glucuronosyltransferases (UGTs), sulfotransferases (SULTs), N-acetyltransferases (NATs), glutathione S-transferases (GSTs) and various methyltransferases .A lack of activity of metabolizing enzymes can be responsible for extreme toxicity syndromes . Severe in utero while others do not active until after birth , polymorphism and even antenatal exposure to cigarette smoke .2 in preterm neonates and term neonates, respectively  is highly dependent on gestational age and is ranging from 0.6–0.8 to 2–4 ml per minute per 1.73 mectively . For exaectively . Also, tectively .As the anatomical and physiological characteristics of preterm neonates differ significantly from older children and adults, the process of neonatal pharmacological development becomes very complex. Furthermore, neonatology represents a small sub-field of pharmacology, and as a small target population, neonates are often overlooked.Pharmaceutical companies largely refrain from proactively investing in the pediatric sector due to both economic and practical considerations, as reported by the EMA . Even acThe ethical principles of pediatric research are well known , but theDue to the stressful situation of becoming a parent to a premature child, the required informed parental consent for neonates participating in research, can be difficult to obtain. The process may require repeated discussions with the families, and thus complicate recruitment for studies during the first hours/days of life .Failure of recruitment of a sufficient number of premature neonates within the planned study period may force investigators to facilitate costly prolongations of the study or even to a premature study termination without reaching the target sample size. Failed drug trials and the general lack of pediatric clinical trials contribute to the high prevalence of off-label use in neonates.Fortunately, relatively few children are born very or extremely preterm, but the scarcity of premature neonates makes it challenging to include this population in PK studies. Traditional PK study designs involve multiple blood samples at fixed intervals and generally require the same number of samples from all subjects taken at the same time . This apA PubMed search was performed on 3 January 2022 for the terms phase I and phase II metabolism in premature children using the following search string: {“Infant, Premature” (mesh) OR “Infant, Extremely Premature” (mesh) OR “Infant, Low Birth Weight” (mesh) OR “Infant, Very Low Birth Weight” (mesh) OR “Infant, Premature, Diseases” (mesh) OR [(preterm OR prematurity OR premature OR prematurely) AND (infant* OR infancy OR baby OR babies OR neonat* OR newborn*)] OR preemi* OR premi OR preterm OR “very low birth weight” OR VLBW OR “low birth weight” OR LBW OR “very low birthweight” OR “low birthweight”} AND {[“Cytochrome P-450 Enzyme System" (mesh) OR “Cytochromes” OR Cytochrome* OR “P450”] OR [“Methyltransferases” (mesh) OR “Sulfotransferases” (mesh) OR “Acetyltransferases” (mesh) OR “Acyltransferases” (mesh) OR “Glucuronosyltransferase” (mesh) OR glucuronidation* OR Methyltransferase* OR Sulfotransferase* OR Acetyltransferase*)]} AND {[humans (Filter)] AND [newborn (Filter)]}.Manuscripts were reviewed for relevance to the topic of this review, as well as for citations related to the topic of the review by two independent reviewers (MLM and CG). In case of disagreement, a third author (ULT) would arbitrate. This review should however be considered a scoping rather than a systematic review.Our search resulted in 1206 hits, of which a total of 70 manuscripts were found relevant to the scoping review .Overall, the large heterogeneity of the studies with regards to both scope, methodology, and particularly the detail of reporting results, precludes any formal comparison, let alone meta-analyses. In particular, many studies examined neonates, but failed to distinguish between term and preterm neonates. This was the case in more than 40% of the studies. The full spectrum of prematurity was found to be explored from 22 gestational weeks and onwards. Extreme premature neonates (born before 28 GA weeks) were included in less than 55% of these studies.Furthermore, the age of the children at the time of inclusion and/or sampling  was unclear in approximately 30% of the studies. In the remaining articles the PNA varied from a few hours to 1 year. The overall mean age at the time of inclusion varied from 4 days to 1.5 months. Keeping in mind that prematurity is defined as being born before 37 weeks of gestation, this logically reduces the actual number of included neonates, who were extremely, very or even late preterm at the time of sampling. These findings elucidate how most PK studies in the youngest pediatric populations are not sufficiently transparent in the presentation of data contributions.Generally, the gestational- and postnatal ages are displayed in intervals, making an accurate estimation of the degree of prematurity impossible. Additionally, the interpretation of the strength of the contributing data becomes very difficult, as, e.g., a 2 weeks old child that was born at 26 weeks gestational age and a newborn child born at 28 weeks gestational age are not necessarily equal in terms of metabolic maturation.Most studies (approximately 70%) focused on the phase I metabolism, and the most studied CYP subclasses were CYP3A4, CYP1A2, CYP2E1, CYP2C19, and CYP2C9 either as individual or contributing enzymes. The phase II metabolism systems were studied in approximately 35% of the articles identified [with glucuronidation (notably UDP-Glucuronosyltransferase-2B7)] and sulfation being the most studied.in vivo in preterm neonates, i.e., 3A4, 1A2, and 2C9/2C19.In in vivo probe for CYP3A4 activity, and the clearance values reported illustrated a clear tendency towards reduced CYP3A4 activity in preterm neonates as compared to full born neonates and older children (Identified studies of CYP3A4 activity are displayed in children . The larchildren  includedin vivo probe for CYP2C9 (via CYP2C19 and CYP2E1 (approximately 5%). A general trend towards reduced phenobarbital clearance was observed in premature neonates. In a recent population study, a PK model was developed based on data sharing from former studies, and the maturation of clearance was predicted to be dependent on both body weight and postnatal age in preterm neonates.Identified studies of CYP2C19 and CYP2C9 activity are displayed in r CYP2C9 , althougThe activity of CYP2C19 was investigated by use of the substrate’s phenytoin and pantoprazole . Latest in vivo studies investigating CYP1A2 activity in preterm neonates  that are unlikely to elicit any pharmaceutical response or side effects. The microdosing approach has been validated for, e.g., midazolam in preterm neonates .The use of international multicenter studies, pediatric trial networks, diverse databases, biomarkers, and integration of Real-world Data, use of artificial intelligence and machine learning such as text mining and deep-learning models to extract relevant information from electronic patient records is likely to further advance neonatal pharmacology (This review highlights the insufficiencies in the current knowledge of the maturation of drug metabolizing enzymes in preterm neonates, and particularly in the very or extremely preterm neonates. We illustrate the overall heterogeneous approach to measuring and presenting the phase I and II pathways metabolism in preterm neonates, often with use of exclusively opportunistic sampling—a testament to the practical and ethical challenges in measuring pharmacokinetic activity in preterm neonates.With the advances in overall neonatal intensive care, the limit for possible survival in extremely preterm neonates has improved. Consequently, neonates with increasingly lower gestational age at birth now require care, including intensive pharmacological treatment. This calls for optimized designs of future pharmacometrics studies, preferably as multi-site/international collaboration between neonatologists and clinical pharmacologists that will allow for integration of all available techniques, including low volume plasma/blood analysis techniques, pharmacokinetic modeling, “Big Data”, and even machine learning.The understanding of the impact of growth, development, and organ maturation on the absorption, distribution, metabolism, and excretion of drugs in neonates, infants, children, and adolescents has progressed tremendously in recent decades, but it has mainly been driven by a few, but dedicated researchers; it is now time for the broader pharmacological scientific community to turn its gaze toward the most premature children.


Amyotrophic Lateral Sclerosis (ALS) is a rare, progressive, and fatal neurodegenerative disease due to upper and lower motor neuron involvement with symptoms classically occurring in adulthood with an increasing recognition of juvenile presentations and childhood neurodegenerative disorders caused by genetic variants in genes related to Amyotrophic Lateral Sclerosis. The main objective of this study is detail clinical, radiological, neurophysiological, and genetic findings of a Brazilian cohort of patients with a recent described condition known as Spastic Tetraplegia and Axial Hypotonia (STAHP) due to SOD1 deficiency and compare with other cases described in the literature and discuss whether the clinical picture related to SOD1 protein deficiency is a new entity or may be represent a very early-onset form of Amyotrophic Lateral Sclerosis.We conducted a case series report which included retrospective data from five Brazilian patients with SOD1 protein deficiency of a Brazilian reference center for Neuromuscular Disorders. Clinical data were obtained from a review of the medical records and descriptive statistics and variables were summarized using counts and percentages of the total population.SOD1 gene with completely decreased enzyme activity.All 5 patients presented with a childhood-onset neurodegenerative disorders characterized by spastic tetraplegia with axial hypotonia in all cases, with gestational history showing polyhydramnios in 4/5 and intrauterine growth restriction in 3/5 patients, with most patients initially presenting a normal motor development until the six month of life or during the first year followed by a rapidly progressive motor decline with severe dysphagia and respiratory insufficiency in all patients accompanied by cognitive impairment in 3/5 patients. All patients were homozygous for the c.335dupG (p.Cys112Trpfs*11) mutation in the This case series is the biggest data collection of the new recent clinical entity described as Spastic Tetraplegia and Axial Hypotonia (STAHP) due to SOD1 deficiency. In humans there are three different isoforms of SODs: human Cu–Zn SOD (SOD1), the mitochondrial MnSOD (SOD2) and the extracellular Cu–Zn SOD (SOD3), and impairment of their antioxidant function or overactivity due to gain of function molecular mechanisms, represents a major pathophysiology role in the development of human neurodegenerative disorders  and cancer linked to SOD1 abnormalities ; and (3) axial images .Muscle MRI study of the lower limbs were performed in a 1,5 T scanner with 4-channel phased-array coil  using a standardized protocol with axial images (T1-weighted spin-echo , short tau inversion recovery ).All patients underwent Nerve Conduction Studies (NCS) and electromyography (EMG) at least one time in the period of the study in the same laboratory with NCS of bilateral median, ulnar, peroneal, tibial, and sural nerves, and needle EMG in proximal and distal muscles of the upper and lower limbs and paravertebral regions using methods previously described .Whole exome sequencing (WES), clinical exome, and a targeted gene sequencing panel for Amyotrophic Lateral Sclerosis were performed in all five patients and their parents, respectively. WES was performed using SureSelect_AllExons_V5_ gene , clinical exome with TruSight One , and the target-panel with SureSelect Human All Exon V6 (Agilent Technologies) following the manufacturers’ instructions. The sequencing was analyzed according to the American College of Medical Genetics and Genomics recommendations. In silico variant evaluation was carried out using the prediction software MutationTaster as well as PolyPhen-2 , 9.The functional activity of superoxide dismutase activity was performed in erythrocytes using a spectrophotometric approaching according to a previous published protocol , 10, 11.Muscle biopsy was performed in all patients using an open technique in the deltoid muscle. Muscle samples stored at a temperature of − 80 °C were cut into fragments with a depth of 6–8 μm and mounted on slides, which were subsequently stained with hematoxylin and eosin, modified Gömöri trichrome, periodic acid-Schiff, Oil-red O, and submitted to histoenzymology for reduced nicotinamide adenine tetrazolium reductase, cytochrome C oxidase (COX), succinate dehydrogenase, and ATPase at two different pH values: 9.4 and 4.6. Respiratory chain enzyme activities were measured spectrophotometrically, as previously described in muscle specimens .All patients were submitted for blood tests including complete blood counts, creatinine and urea, serum creatine kinase (CPK), liver enzymes, thyroid function (TSH and free thyroxine), lipid profile, serum lactate, plasma acylcarnitine profile and urinary organic acids.All patients were evaluated with the following functional assessment scales: (1) Hammersmith Infant Neurological Examination – Section 2 – Motor Milestones (HINE-2); (2) Children’s Hospital of Philadelphia Infant Test of Neuromuscular Disorder (CHOP-INTEND) and (3) Expanded Hammersmith Functional Motor Scale for SMA (HFMSE).Descriptive statistics was applied, and variables were summarized using counts and percentages of the total population. Variables were summarized using descriptive statistics including mean, median, ranges, percentages and/or frequencies.The main clinical data are described in Table Patient 1. The patient is a Brazilian 3-year-old boy, first child of consanguineous parents (first degree cousins) of Lebanese origin. During pregnancy, polyhydramnios was noted. The patient was born at 34 weeks of pregnancy via Caesarean section due to maternal preeclampsia. The Apgar score at 1 and 5 min was 5 and 7, respectively. At birth patient was noted to have hypotonia and bilateral congenital dislocation of the hip, without respiratory distress or bulbar dysfunction. The parents reported normal development delay until 7 months when the patient was still able to maintain head control followed by progressive psychomotor decline with inability to sit, to roll, and standing. At first clinical evaluation patient presented a severe spastic tetraplegia, pyramidal features such as Babinski sign and bilateral Achilles’ clonus, axial hypotonia with cervical weakness, proximal muscle atrophy in the upper and lower limbs, fasciculations of the tongue, cervical region, and quadriceps femoris muscle groups, facial myokymia, and severe cognitive impairment.Patient 2. This patient is a 2-year-old boy, brother of patient 1, with a pregnancy history of polyhydramnios. The patient was born at 39 weeks of pregnancy by Caesarean delivery due to fetal malpresentation. The Apgar score at 1 and 5 min was 7 and 9, respectively. At birth hypotonia was noted with transient bulbar dysfunction and dysphagia. The parents reported normal development until the age of 9 months when the patient was able to maintain head control, and was stably sitting, but was thereafter followed by progressive psychomotor decline and bulbar dysfunction. At first clinical evaluation patient presented a severe spastic tetraplegia, Babinski sign, axial hypotonia with cervical weakness, proximal muscle atrophy in the upper and lower limbs and fasciculations at tongue, cervical region, biceps brachii, quadriceps femoris and tibialis anterior muscles group and cognitive impairment without language development.Patient 3. The patient is a Brazilian 7-year-old girl, second child of consanguineous parents (first degree cousins) of Lebanese origin, who after 1 year of age, developed over 2 years progressive manifestations of psychomotor deterioration, chronic respiratory insufficiency with tracheostomy and invasive mechanical ventilation after an episode of pneumonia, and swallowing difficulties requiring gastrostomy feed. Her previous motor milestones were unremarkable with the ability to walk independently at 1 year of age. Previous medical history exhibited an uncomplicated pregnancy with a natural labor at 39 weeks of pregnancy without neonatal hypotonia or events suggestive of possible hypoxic-ischemic encephalopathy. Neurological examination revealed mild spastic tetraplegia, proximal muscle weakness of upper and lower limbs, axial hypotonia, diffuse fasciculations, facial diparesis, tongue atrophy, dysarthria, scoliosis, and language impairment.. The patient is a 5-year-old boy, brother of patient 3, who presented with 3-year history of progressive psychomotor regression, chronic respiratory insufficiency, and dysphagia. His previous motor milestones were unremarkable with the ability to walk independently at 15 months of age. During pregnancy, polyhydramnios, intrauterine growth restriction and reduced fetal movements was noted. The patient was born at 36 weeks of pregnancy via Caesarean section due to maternal HELLP syndrome. The Apgar score at 1 and 5 min was 3 and 5, respectively. Neurological examination revealed moderate spastic tetraplegia, axial hypotonia, diffuse fasciculations, facial diparesis, tongue atrophy with fasciculations, scoliosis, amyotrophy, and dysarthria without cognitive impairment.Patient 4Patient 5. The patient is a 2-year-old boy, brother of patient 3 and 4, presented with 1-year history of progressive psychomotor regression and dysphagia. During pregnancy, polyhydramnios and intrauterine growth restriction was noted. The patient was born at 37 weeks of pregnancy via Caesarean section due to maternal HELLP syndrome. The Apgar score at 1 and 5 min was 7 and 9, respectively. At birth patient was normal without hypotonia or respiratory distress. His previous motor milestones were unremarkable until 1 year of age when he was able to maintain head control upright and stable sit but was never able to walk independently. Neurological examination revealed moderate spasticity in the lower limbs, brisk tendon reflexes, bilateral Babinski sign, tetraplegia with weakness of proximal and distal muscle groups, axial hypotonia, fasciculations in lower limbs, tongue atrophy, global amyotrophy, unable to sit unsupported with preserved cognition.The 5 patients performed brain and muscle MRI and specific changes are illustrated in Fig. In brain MRI studies, 4 patients presented cerebellar atrophy with preferential involvement of superior vermis cerebellar, 3 patients exhibited thin corpus callosum, 2 patients showed corticospinal tract hyperintensity and 2 patients presented unspecific white matter changes. All radiological findings of each patient are detailed in Table In our cohort, all patients disclosed chronic denervation findings characterized by large-amplitude, long-duration and polyphasic motor unit action potentials in bulbar, cervical, thoracic, and lumbosacral segments, and 4 (80%) patients had also acute denervation findings characterized by fibrillation potentials, positive waves and fasciculations in at least one of the studied segments. All neurophysiological studies are summarized in Table SOD1 gene that have been associated with the phenotype of Spastic Tetraplegia and Axial Hypotonia (STAHP). The parents of patients were segregating the variant in heterozygosity.The five patients presented in this study were homozygous for the known pathogenic frameshift variant c.335dupG (p.Cys112Trpfs*11) in the All patients exhibited lack of SOD1 activity in erythrocytes (< 2 units/mg), whereas the level of activity in heterozygous parents was half that of the normal level when compared to five healthy non-related controls. The values of superoxide dismutase functional activity for all patients, parents and controls are summarized in Fig. All patients performed muscle biopsy that showed pathological findings suggestive of neurogenic changes such as increased fiber size variability with angulated atrophic fibers rounded by hypertrophic fibers, increased number of type 2 fibers but without type grouping formation and without endomysium changes and some “target-fibers” observed in NADH-TR reaction Fig. .Fig. 5MuAll patients presented with hiperCKemia ranging between 400 and 780 UI/L, and had normal values for serum lactate, acylcarnitine profile and organic acids in urine. The CPK levels for each patient are detailed in Table In this cohort, all patients required gastrostomy for nutritional management, and all are dependent on mechanical ventilation, with 3 patients having tracheostomy and use of invasive mechanical ventilation 24 h per day, and 2 patients on non-invasive mechanical ventilation for at least 18 h per day. None of the patients are able to walk or sit in unassisted fashion. All patients presented a score less than 10 points at HINE-2 and the maximum score at CHOP-INTEND was 18 points. The detailed results of functional assessment are summarized in Table Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disorder characterized by the degeneration of upper and lower motor neurons and clinically characterized by progressive motor deficits, and varying progression of speech deterioration with heterogenous cognitive and behavioral changes .Traditionally, ALS is classified as sporadic ALS, that accounts for 90% cases, and familial ALS, when there is a context of more than one affected family member (relative) in the first or second generation with a similar disease presentation of the index patients, or with ALS-FTD presentation and that so far accounts for up to 10% of cases in large series , 14. UntThe pathophysiology of ALS is poorly understood and can rise as a consequence of multiple pathophysiological mechanisms and cellular dysfunctions, including protein misfolding and aggregation, altered RNA processing, defects in axonal transport, abnormal metabolism and accumulation of reactive oxygen species, mitochondrial dysfunctions, microglial and neuroinflammatory mechanisms, disturbances of autophagy, ubiquitin–proteasome system abnormalities and primary and secondary ion channel defects , 14–16.SOD1 gene variants were first associated to familial ALS, more than 150 variants have been described and the mechanism of SOD1 protein dysfunction in the pathophysiology of disease was partially elucidate, and new genetic therapies are emerging from recent clinical trials and are on the verge of being used in clinical practice as innovative disease-modifying therapy for the treatment of ALS [Since 1993, when t of ALS , 18.SOD1 variants leads to ALS is yet incompletely understood, with current knowledge indicating that the pathogenic variants produce a destabilization of SOD1 structure protein, with a gain of function mechanism that leads to an increase oxidative activity with excessive production of hydrogen peroxide, and raise in protein–protein interactions predisposing to increased aggregation, dimer destabilization, and oligomerization resulting in abnormal axonal transport, microglia activation, increased apoptosis, mitochondrial dysfunction and oxidative stress that at last plays a crucial roles in motor dysfunction [The exact mechanism on how function , 19–22.ALS2, SPG11, SIGMAR1, SETX, SOD1, UBQLN2 and FUS [Juvenile Amyotrophic Lateral Sclerosis (JALS) is empirically classified as a phenotypic variant of ALS with onset of disease before 25 years of age and having a slower disease progression with prolonged survival compared to adult-onset ALS. JALS has a rare frequency with an estimated prevalence of 1 case per 1.000.000 and generally associated with autosomal recessive or autosomal dominant inheritance with highly penetrant genetic variants in causative genes as  and FUS –25.The diagnosis of ALS and their variants such as JALS can be an arduous and labored challenge and since 1994 many diagnostic criteria were made and refined from the El Escorial to Gold Coast with the latter and current criteria for diagnosis of ALS is based in three statements: 1) progressive motor impairment documented by history or repeated clinical assessment, preceded by normal motor function, and; 2) presence of upper and lower motor neuron dysfunction in at least 1 body region (with upper and lower motor neuron dysfunction noted in the same body region if only one body region is involved) or lower motor neuron dysfunction in at least 2 body regions, and; 3) additional investigations excluding other disease process , 27. TheA critical review of the case described by Andersen et al. who reported on a patient with clear signs of upper motor neuron dysfunction, and some evidence of lower motor neuron dysfunction revealed by fasciculations and myokymia in electromyography, that however are insufficient to confirm a lower motor neuron involvement according to Gold Coast Criteria for ALS. Moreover, a clinical follow-up was lacking, to detect progression of disease, and there was no serial electromyography evaluation to detect further lower motor neuron dysfunction.The case reported by Park et al. refers to a six-year-old patient who presented with significant upper motor neuron dysfunction and more substantial evidence of lower motor neuron dysfunction, with multiple fasciculations of the right deltoid, right extensor digitorum, vastus medialis and tibialis anterior muscles on both sides described by muscle ultrasound and confirmed by the detection of fasciculations on electromyography without any additional neurogenic changes. Again, these exams were insufficient to establish a definitive diagnosis of ALS according to Gold Coast criteria considering the lack of long-term clinical follow-up and absence of other electromyography studies that are useful to confirm a lower motor neuron dysfunction overtime .SOD1 gene reported by Andersen et al., and Park et al. allowing us to conclude that the cases presented by these authors, and the new additional patients reported in this study represent a very early infantile-onset ALS. Regarding parental carriers that are heterozygous for the variant c.335dupG (p.Cys112Trpfs*11) in the SOD1 gene, we still cannot say anything about the future risk of developing a neurodegenerative disease, and they need long-term clinical follow-up to early detect neurological manifestations related to ALS. The absence of neurological manifestations in the parents described in the literature, and in our experience can be related to recessive mechanism of transmission, or a low penetrance for the variant c.335dupG like other variants described in SOD1 gene [Our study presents a series of five patients that typify a progressive motor. neuron disorder with undoubtful upper and lower motor neuron involvement demonstrated by clinical examination, and corroborated by neurophysiological and muscle pathological studies that fulfills all the recently proposed diagnostic criteria for ALS with the same homozygous pathogenic variant in OD1 gene –33.Sod1−/− mice that have been associated with neuromuscular, neuronal, and extra-neuronal phenotypes [The exact pathophysiological mechanism that the homozygous c.335dupG leads to the ALS phenotype observed in our cohort and the STAHP described in the literature is not completely understood. However, we can hypothesize that complete loss of function of SOD1 enzyme can produce an increased vulnerability to oxidative stress with important mitochondrial dysfunction as demonstrated by animal models like enotypes .SOD1 protein has a critical role in the function and homeostasis of motor neurons and SOD1 deficiency is related to very early-onset juvenile ALS as described in this article. This unusual “new” phenotype of infantile neurodegenerative disorder (STAHP), which is similar to ALS, and juvenile motor neuron disease, should be always recalled in the differential diagnosis of neurodegenerative disorders in childhood with progressive involvement of motor neurons .


AKT1 gene, a key component of the dopamine signalling cascade. As such, it is likely that epigenetic methylation around this SNP may affect AKT gene expression, which may in turn impact on the acute effects of THC on brain function. We investigated the genetic (AKT1 rs1130233) and epigenetic modulation of brain function during fear processing in a 2-session, double-blind, cross-over, randomized placebo-controlled THC administration, in 36 healthy males. Fear processing was assessed using an emotion (fear processing) paradigm, under functional magnetic resonance imaging (fMRI). Complete genetic and fMRI data were available for 34 participants. THC caused an increase in anxiety and transient psychotomimetic symptoms and para-hippocampal gyrus/amygdala activation. Number of A alleles at the AKT1 rs1130233 SNP, and percentage methylation at the CpG11–12 site, were independently associated with a greater effect of THC on activation in a network of brain regions including left and right parahippocampal gyri, respectively. AKT1 rs1130233 moderation of the THC effect on left parahippocampal activation persisted after covarying for methylation percentage, and was partially mediated in sections of the left parahippocampal gyrus/hippocampus by methylation percentage. These results may offer an example of how genetic and epigenetic variations influence the psychotomimetic and neurofunctional effects of THC. High doses of delta-9-tetrahydrocannabinol (THC), the main psychoactive component of cannabis, have been shown to have anxiogenic effects. Additionally, THC effects have been shown to be modulated by genotype, including the single nucleotide polymorphism (SNP) rs1130233 at the protein kinase  Worldwide, cannabis is the most popular recreational drug . CommonlAKT1 gene (rs1130233). This gene codes for the protein kinase AKT, and its rs1130233 single nucleotide polymorphism (SNP) is a synonymous coding variation that has been linked to differential expression of the AKT protein, whereby the presence of an A allele is robustly associated with decreased expression of AKT [Consistent with preclinical evidence  human exn of AKT ,21,22,23AKT is a key component of the dopamine signaling cascade [AKT activity has been suggested to be relevant for the manifestation of psychiatric symptoms, including anxiety-like behaviors [AKT1 [AKT1 gene may therefore influence sensitivity to the effects of THC on brain functioning and related behavior, especially anxiety-related manifestations. The protein kinase  cascade ,25 and aehaviors ,27. Reguehaviors ,29 and aehaviors  studies;rs [AKT1 ,32. AlteAKT1 gene is likely to reduce its gene expression and thereby indirectly reduce sensitivity to the acute effects of THC. Although we have previously demonstrated moderation of the acute effects of THC on functional brain activation by the AKT1 rs1130233 polymorphism [AKT1 rs1130233 polymorphism and methylation of CpG sites around this locus on the acute effect of THC administration on brain activation, during the processing of fear, as indexed using functional MRI. We focused on the effects of THC on fear processing-related brain activation in-light-of previous evidence that a single dose of THC modulates normal functioning of limbic regions involved in the processing of fear, in particular the amygdala, which correlated directly with the severity of anxiety induced by THC acutely [AKT1 rs1130233 polymorphism and the methylation of CpG sites around this locus.Methylation of DNA, i.e., addition of a methyl group to the cytosine pyrimidine ring of CpG dinucleotide, is one of several mechanisms of epigenetic control of gene expression, by reducing it . As suchmorphism ,34, whet acutely ,13. We hThirty-six right-handed healthy males, mean age 25.97 ± 5.8 years and IQ of 97.7 ± 6 took part in the study. None had a personal or family (first-degree relative) history of psychiatric illness. The Addiction Severity index was used to asses alcohol, cannabis and other illicit drug use  Table 1Table 1. AKT1 rs1130233 locus was unsuccessful in 1 participant, association between AKT1 rs1130233 SNP and methylation at CpG sites was investigated in 35 participants. Additionally, as another participant was unable to complete the fMRI scan under the THC condition, the effect of THC on activation compared to placebo and its correlation with percentage CpG methylation at site 11–12 were investigated in the 35 subjects. Thus, correlational analyses between genotype and THC effect on brain activation maps both with and without covarying for CpG methylation was performed in the 34 participants with completed neuroimaging and genotyping data. As genotyping at the As previously reported ,34, eachOn the morning of each session, all participants passed a urine drug screening for opiates, cocaine, amphetamines, benzodiazepines and THC, using immunometric assay kits. Venous blood samples and psychopathological ratings were taken at baseline, and one, two and three hours post drug administration. A blood sample for genotyping and methylation analysis was obtained at baseline. Psychotomimetic effects were assessed by a clinician using the positive negative symptom scale (PANSS) . SpielbeImages were acquired on a 1.5 Tesla Signa System (GE) at the Institute of Psychiatry, Psychology & Neuroscience, London. T2*—weighted images were taken using TR of 2000 ms; with 40 ms echo time; a flip angle of 90° in 16 axial planes 7 mm thick, parallel to anterior commissure posterior commissure line. To facilitate anatomical localisation of activation and high-resolution inversion recovery image dataset was acquired using a 3 mm contiguous slices and an in-plane resolution of 3 mm .Inside the scanner, participants performed the emotional (fear) processing task, which has been described in detail elsewhere ,40. The AKT1 G>A rs1130233 SNP by KBioscience  successfully for 35 out of the 36 subjects . Genotype frequencies and socio-demographic details of the 35 subjects are shown in p < 0.05) with regard to age, NART IQ or the number of years of education. Genotype frequencies for AKT1 at rs1130233 were in Hardy-Weinberg equilibrium  in the ethnically stratified sample. DNA was extracted using standard methods by researchers at the Institute of Psychiatry  and Genohttp://www.epidesigner.com, accessed on 28 July 2021). A total of 19 CpG sites were analysed in 14 CpG island blocks. This was such that CpG sites 6 and 7, 9 and 10, 11 and 12, 17 and 18, were analysed as a single site, due to their close proximity and high numbers of C and G nucleotides in between them, making them difficult to distinguish individually. Reactions were performed in duplicate and methylation analysis was carried out following established [The DNA methylation assay was carried out using previously described methods . Brieflyablished  using thGenotyping and methylation assays were carried out blind to THC response results.AKT1 rs1130233 genotype and methylation percentage at CpG sites 11–12  around this locus (tested using a t-test), which survived correction for multiple testing , we focused on methylation at these sites for subsequent analyses.As a number of CpG sites are present around the rs1130233 locus, association between genotype and methylation status at each of these sites was examined first in order to identify the specific CpG sites to be further investigated in the present study. As there was a significant association between The images were analysed using a non-parametric software package, XBAM_v4.1, that was developed at the Institute of Psychiatry, Psychology & Neuroscience (King’s College London). It is important to use non-parametric measures when analysing fMRI data as it may not follow a normal Gaussian distribution ,45. Alsox, y and z axes) and translations  that maximised the correlation between the template 3D volume and the image intensities of the volume in question. In order to smooth the data a 7.2 mm full-width-at-half-maximum Gaussian filter was applied to average the relative intensities of neighbouring voxels. Individual activation maps were created by modelling the BOLD signal using 2 gamma-variate functions for each experimental condition, peaking at 4 and 8 s to allow for variability in haemodynamic delay. A best fit between the weighted sum of these convolutions and the change over time was computed at each voxel using the constrained BOLD effects model [Firstly, correction for head motion was completed by realigning the images, to a template created by computing a 3D volume from the average intensity at each voxel throughout the whole period scanning . Realignts model . This mets model . This avts model , this pets model  using a ts model  allowingGroup activation maps were created for each task condition , and for each drug condition . Median SSQ ratios at each voxel across all individuals were determined in the observed and permutated data maps, using medians to minimize outlier effects. A null distribution of SSQ ratios was driven from the distribution of median SSQ ratios over all intracerebral voxels from the permuted data, giving group activation maps for each condition. We could then directly compare group activation at each condition using non-parametric repeated-measure analysis of variance (ANOVA) .p = 0.05 was used and the cluster-wise thresholds were chosen such that the number of false positive clusters would be <1 per brain . The data from more than one voxel is integrated into the test statistic giving greater sensitivity and allows for a reduction in the search volume or overall number of required tests for whole brain analysis, thereby helping to mitigate the problem multiple comparisons. For each drug condition, we therefore had a separate standard-space map for each of the experimental conditions  for each participant. We then employed a non-parametric repeated measures analysis of variance (ANOVA) whole-brain analysis approach to identify brain regions that were activated by THC relative to the placebo condition. We contrasting the individual brain activation maps for intense and mildly fearful faces combined (as the fear condition) with those of the neutral faces.Activated voxels were grouped into clusters of activation using a method previously described  and showAKT1 rs130233 genotype and methylation (at CpG site 11–12 around that locus) with the cerebral activation response to THC during fear processing, we followed the Baron and Kenney [AKT1 SNP rs1130233 (independent variable). Therefore we investigated the association between independent variable (genotype) and dependent variable (brain activation), then between moderator variable (methylation) and dependent variable and between moderator variable and independent variable by carrying out separate correlational analyses. Finally, to investigate the extent to which the association between genotype and THC effect on fear-related brain activation was mediated by methylation at the CpG 11–12 site, we carried out a final correlational analysis between genotype (AKT1 rs130233) and the effect of THC on brain activation during fear processing, while covarying for methylation percentage at the CpG site 11–12. As we were interested in investigating the relationship of d Kenney . mediatiAKT1 rs1130233 locus, coded as G/G = 1 G/A = 2 and A/A = 3); and (2) DNA methylation (methylation percentage at CpG site 11–12). We contrasted each of the active (‘intensely fearful faces’ and ‘mildly fearful faces’) conditions of the fear processing task with the baseline condition  to generate contrast of interest maps  for each individual participant under each drug condition. We estimated the Pearson’s product moment correlation coefficient at each voxel, in each subject’s standard space, yielding one correlation coefficient (r) per intracerebral voxel. Correlation differences between groups were estimated at each voxel by computing for each group, the r value for each subject followed by subtracting the resulting two values. A null distribution was then appropriately generated by randomly permuting subjects and their associated genotype or methylation levels between the groups (without replacement), therefore scrambling any group differences. For each permutation, the difference in correlation between the scrambled groups was calculated and then the resulting values combined for all voxels to produce a whole-brain null distribution of differences in correlation. The critical value for significance at any desired Type 1 error level in the original (non-permuted) data were then obtained from this distribution after sorting it and selecting the appropriate point from the sorted distribution. This means that the critical value for a one-tailed test thresholded at p = 0.05 would be the value of the difference in correlation in the null distribution where 95% of all the null values lay below that point. The statistical analysis was then extended to the 3D cluster level, previously described [These analysis examined the association between the median SSQ ratio under each drug condition (THC and placebo) while processing fear with: (1) genotype . However, the AKT1 rs1130233 polymorphism was retained consistent with current practice, as there was no evidence of a quality control issue and also as recent evidence suggests that while polymorphisms that are not in HWE may be less powerful, they do not tend to increase false positive results [Genotype frequencies of participants showed no difference between groups with regard to age, NART IQ and number of years of education, shown in  results .p < 0.001) and anxiety symptoms  = 49.36 ± 27.6, PLB (AUC) = 37.12 ± 22.3, p < 0.001). Additionally, a THC-induced change in total PANSS scores (THC (AUC) = 108.61 ± 16.6, PLB (AUC) = 94.49 ± 6.4, p < 0.001) and levels of sedation  = 54.98 ± 14.8, PLB (AUC) = 48.65 ± 16.2, p = 0.02; shown in our previous publication [p < 0.001) were observed.These results have been previously reported in detail by , howeverp = 0.597) or performance accuracy across all emotional conditions (p = 0.933) as well as for fear (p = 0.976). There was no statistically significant effect of drug condition on reaction time during the emotional (fear) processing task (p = 0.597) or performance accuracy across all emotion conditions (p = 0.933) as well as for fear (p = 0.976).There was no significant effect of drug condition on reaction time during the emotional (fear) processing task , such that the higher the number of risk alleles (A) the greater was the effect of THC on fear-related brain activation across a network of brain regions  correlated positively with change in STAI scores.There was a statistically significant association between the effect of THC on regional brain activation while processing fear and  regions  that inc11–12 site, such that the higher the percentage of methylation at this site, the greater was the effect of THC on fear-related brain activation across a network of brain regions . There was a significant association between the effect of THC on regional brain activation while processing fear, and methylation at CpG regions  that incr = 0.869, p ≤ 0.001) between the number of A alleles at AKT1 rs1130233 and methylation percentage at CpG sites 11–12, . As expected, there was a linear relationship , then altered AKT1 activity may therefore represent a marker for differing responses to fear processing under the acute effects of cannabis. More specifically, the THC-induced increase in brain activation in several brain regions involved in emotional processing as a function of both these genetic factors may possibly represent a genetically mediated lack of efficiency in processing emotion, similar to that found by previous studies [While viewing neutral faces, acute THC exposure decreased brain activation consistent with the known effects of cannabis  on brain studies ,54. SuchAKT1 expression [AKT1 gene expression [AKT1 action [AKT1 [AKT action even beyond acute intoxication. THC-induced dopamine release may therefore be increased in the context of genetically-determined lower AKT1 gene expression, because of reduced feedback regulation in the cascade where the AKT protein is present, as well as because of a direct action of THC in reducing the expression of the AKT protein [Presence of the A allele at this SNP has been associated with lower pression ,21,22,23pression . As bothpression . Acute Tpression  via a CBpression ,65,66 anpression , leading1 action  and THC on [AKT1 , reducin protein .AKT1 genetic variation, with mediation via methylation levels, may begin to offer examples for specific genetic markers that are associated with an increased risk for neuropsychiatric disorders following cannabis use. AKT1 signalling cascade affects dopamine 2 (D2) receptors, encoded by the DRD2 gene, known to play a key role in psychosis [AKT1 expression could result in an increased level of synaptic activation through the inhibitory effects from dopamine binding on the enzyme [AKT1 gene, rs2494732, which is in high linkage disequilibrium with rs1130233 , entails a variant—allele A—which has been shown to increase the risk of developing psychosis among cannabis users [DRD2 gene in further increasing the risk of psychosis possibly because of genetically-determined higher striatal dopamine levels [Differing neurophysiological and behavioural effects of acute THC exposure, dependent on sychosis  and decre enzyme . Consistis users  and to iAKT1 gene also warrant further research to identify their role in gene expression and how they modulate THC response. This study is further limited using a 1.5 Tesla scanner; as more powerful scanners has now become more routinely available.By covarying for methylation levels around the genotype locus, the present findings can only be used to make suggestive comments about the effect of methylation. Therefore, replication of our results is required to gain stronger evidence into the independent effect of methylation and to further investigate the specific brain regions potentially involved. Additionally, the results from this study should only be considered as preliminary due to the small number of participants. This study also only included male participants limiting the application of our findings, similar studies should be conducted including females. This single gender group however, removed the need for examination of a gender effect on methylation  and acutAKT1 SNP rs1130233 in modulating the acute effects of THC during fear processing, with these being associated with the A allele presence. Additionally, we have provided the first suggestive evidence that methylation around the SNP, may also independently modulate such acute response to THC. Finally, methylation levels mediated the effect of the AKT1 SNP rs1130233 in increasing brain activation following acute THC exposure whilst processing fear, suggesting a mechanism of further divergence in individuals’ anxiogenic responses to cannabis. In conclusion, this work further adds to existing evidence for a role of the


Sus scrofa leucomystax) have persevered against these environmental changes, including an invasion of escaped domestic pigs (Sus scrofa domesticus). Concurrently, we show evidence of successful hybridization between pigs and native wild boar in this area; however in future offspring, the pig legacy has been diluted through time. We speculate that the range expansion dynamics inhibit long-term introgression and introgressed alleles will continue to decrease at each generation while only maternally inherited organelles will persist. Using the gene flow data among wild boar, we assume that offspring from hybrid lineages will continue dispersal north at low frequencies as climates warm. We conclude that future risks for wild boar in this area include intraspecies competition, revitalization of human-related disruptions and disease outbreaks.Natural and anthropogenic disasters have the capability to cause sudden extrinsic environmental changes and long-lasting perturbations including invasive species, species expansion and influence evolution as selective pressures force adaption. Such disasters occurred on 11 March 2011, in Fukushima, Japan, when an earthquake, tsunami and meltdown of a nuclear power plant all drastically reformed anthropogenic land use. Using genetic data, we demonstrate how wild boar ( Drast2 for the CNPP and 1150 km2 for the FDNPP). In the evacuated areas, wildlife census studies have demonstrated a rewilding occurred over time, with an abundance of large mammals in both these ecological communities [Sus scrofa) saw a drastic population increase, but it was stabilized and even declined as predatory populations and disease increased [Radioactive materials were dispersed as a result from both the Chernobyl and Fukushima Dai-ichi Nuclear Power Plant (CNPP and FDNPP) accidents in 1986 and 2011, respectively , causingmunities –12. Incrncreased ; howeverHuman abandonment of such a large area at Fukushima may have provided favourable conditions for a rapid increase in those wildlife species that were able to benefit from landscapes that were formally anthropocentric . Concurr2 of urban and agricultural lands [Sus scrofa domesticus), released from abandoned farmlands [We focus on wild boar in Fukushima's evacuated area because wild boar here are experiencing: (i) sudden population expansion as evidenced by greater population abundance  and popual lands ; and https://www.pref.fukushima.lg.jp/site/portal/). The evacuation order was subsequently modified to include areas as far as 40 km northwest of the FDNPP that were also contaminated by the radioactive plume, comprising a total area of approximately 1150 km2 [Due to high-dose rates from radioactive material dispersed in March 2011, the Japanese Government issued an evacuation order for 164 845 people living within a 20 km radius of the FDNPP (1150 km2 . Beginni1150 km2 . (b)et al. [et al. [Muscle samples were collected from 191 wild boar, all of which were morphologically identified as typical wild boar in Japan , captureet al. ; and the [et al. , which b (c) (i)The mtDNA sequences provide material lineage information and can be used to identify wild boar with pig maternal ancestry for many distant generations. The mtDNA sequences were obtained from previous literature for all samples in this study ,28 . In  (ii)et al. [et al. [et al. [Nuclear microsatellite (STR) data were analysed to determine the genetic structure of wild boar and the extent of domestic pig introgression into the local wild boar population. A total of 24 STR loci were selected and genotyped for our study populations based on the allele frequencies and the amplification for each of these markers in pure species individuals . All 24et al. –32 and ret al. . For 31  [et al. , we used [et al. . In brie [et al. . Each sa (d)Our genetic data, both mtDNA and STR, were divided into two groups for analyses: (i) individual-based data analyses to assess introgression from pigs into wild boar, i.e. intraspecies hybridization in the evacuation zone or nearby areas. Samples from the period prior to the 2011 evacuations and outside Fukushima Prefecture were excluded from this group. (ii) Population-based data analyses to predict possible dispersal patterns of hybrids using gene flow and genetic structure of the native wild boar populations within the evacuated area, to the north (Miyagi and Yamagata Prefectures) and to the south (Ibaraki Prefecture) of the evacuation zone. (i)K), 10 independent runs with K = 1–10 were performed using 106 Markov chain Monte Carlo (MCMC) iterations following a burn-in of 105 iterations. STRUCTURE HARVESTER [K (LnP(D)) and ΔK [P(D) remained at 0 with each K except a high peak at K = 2 , and the highest ΔK was detected when K = 2. Taken together, K = 2 was the optimal number and we retained K = 2 to identify the proportions of admixture in wild boar and pig hybrids. For the selected K = 2, we assessed the average proportion of the membership coefficient (Q1) to the inferred clusters. We assigned each individual to the inferred clusters, using a conservative threshold Q1 ≥ 0.99 for the assignment of individuals genomes to the pig cluster, or, Q1 < 0.01 to the wild boar cluster. Admixed individuals were jointly assigned to the two clusters and were considered to have possible hybrid ancestry or were the offspring from ancestors that were a cross between wild boar and pig. Admixed individuals were considered hybrids only if neither of the thresholds were true in all independent runs. If an individual admixed in more than 50% of the runs, but not all, then the individual was considered as a ‘suggested hybrid’.The STR genetic structures and genomic mixtures between wild boar and pigs were investigated using a Bayesian clustering algorithm available in STRUCTURE v. 2.3.4 ,36. STRUARVESTER  was used) and ΔK . The LnPFor clarity, terms used in this manuscript are defined as follows. First, ‘hybridization’ refers to mixing between evolutionarily distinct lineages, whereas ‘introgression’ refers to gene flow between species as a consequence of hybridization. In this study, introgressed or hybrid wild boar were determined based on the inherited pig lineage haplotype from mtDNA, or an admixed individual based on STRUCTURE (see above), or both.Q1 values. Distances from wild boar trap sites and the FDNPP  were calculated using the geographical distance-based analysis in GenALEx v. 6.41 [Frequencies of wild boar identified as hybrids were partitioned by the corresponding evacuation zones based on GPS coordinates: initial evacuation zone, extended evacuated zone and outside the evacuation zone. To geographically evaluate wild boar considered as hybrids based on either method, two maps were created using corresponding GPS coordinates and (i) colour based on haplotype or (ii) a colour gradient scale based on  v. 6.41 . We calc v. 6.41 , and per v. 6.41 . (ii)For the subsequent analyses, only individuals that had typical mtDNA haplotypes of wild boar, i.e. J10 and J5, and assigned to the inferred wild boar cluster were used to determine gene flow among the native wild boar populations in this region, as such information could help provide predictions on future dispersal. Samples used for these genetic analyses were considered as pure strain wild boar, or wild boar with only wild boar ancestry and lineages, and are henceforth referred to as ‘pure-wild boar’. The STR data from 202 pure-wild boar, including 160 pure-wild boar from the evacuated zone and 42 pure-wild boar from the neighbouring prefectures to the north and south, were used.K and ΔK. We examined the association between the matrix of the geographical distances and Queller & Goodnights genetics relatedness (r) [Genetic structure of pure-wild boar was investigated by performing a STRUCTURE analysis and a test of isolation by distance. We ran STRUCTURE with the same setting parameters as discussed above and the same criteria were used for ness (r)  with thrness (r) .. 3 (a)MtDNA. Two typical wild boar haplotypes  and one typical pig lineage haplotype  were observed in wild boar surveyed for mtDNA. For the 191 wild boar samples from within the evacuated zone, the number (and proportion) of each haplotype was 170 (89%), three (1.6%) and 18 (9.4%) for J10, J5 and H1, respectively. In other words, 173 (90.6%) of the mtDNA haplotypes were typical for wild boar lineages and 18 (9.4%) showed evidence of pig ancestry.Nuclear STR. The STRUCTURE and PCA analysis used to investigate the introgression of pig alleles into native wild boar based on 24 loci gave similar genetic structuring compared to that obtained from mtDNA and distinguished wild boar, pig and hybridized individuals. The most probable number of clusters that captured greatest proportion of the data in the STRUCTURE analysis was K = 2 (P(D) and the ΔK were evaluated . All individuals were assigned to two clusters at K = 2, a first group comprised the 10 pigs, and a second group comprised all the wild boar within the Fukushima evacuation area with 10 admixed individuals in 100% of the independent runs and an additional five admixed individuals in more than 50% of the runs. The estimated Q1 values for all members of the first group were Q1 ≥ 0.99, while the second group consisted of 160 individuals with a Q1 < 0.01. The 10 admixed individuals in 100% of the runs and additional five admixed individuals in more than 50% of the runs ranged from 0.03 ≤ Q1 ≤ 0.51 and 0.01 ≤ Q1 ≤ 0.03, respectively P(D) increased progressively from K = 2 to 3 and then plateaued after K = 3 . Additionally, the highest ΔK was detected when K = 2 and the second highest when K = 3. Thus, the most likely number of clusters was K = 2 followed by K = 3. At K = 2, the range of the wild boar was divided into two clusters , which also indicated wild boar scattered across two genetic clusters. In other words, the Fukushima evacuated zone and northern prefectures' populations tended to overlap positions, while the southern Ibaraki population was positioned separately. In addition, the northern group wild boar collected from the period prior to 2011, suggested little genetic drift from the samples collected after 2011  was observed among all wild boar subpopulations in the southern and northern regions. However, no significant correlation was observed  for wild boar within the Fukushima evacuated zones. This result indicates that there is genetic mixture and similarity between the Fukushima evacuated area and northern prefecture's wild boar populations, while there is limited gene flow moving south.Limited gene flow or mixing between the populations from the two main regions identified by STRUCTURE, the southern and northern separation, was also evident from the association between the matrix of the geographical distances and genetics relatedness analysis . A clear significant correlation (. 4 (a)The data presented here reveal recent hybridization and genetic introgression from invasive pigs into wild boar. Hybrids and the extent of introgression from pigs were identified by maternally inherited markers and analysing multi-loci genotype data, which showed that 31 individuals, morphologically identified as wild boar, in Fukushima Prefecture had pig ancestry . In a PCA series of results showed that while a few individuals with pig ancestry were born into the Fukushima wild boar population, the proportion of pig genes in those individuals' genomes was low Our results suggest that abandoned livestock farms, inside the initial Japanese Government ordered evacuation zone (20 km radius from the FDNPP), were the source of the invasive pigs and the initial contact zone of introgression, with an indication of outward dispersal . The higWhen we compare our findings from the hybrid and pure-boar analyses to wild boar expansion trends reported in the literature, a probable prediction can be made of how hybrid lineages from pigs will disperse in the future. From the 1700s to 1970s, wild boar were thought to be regionally extinct in the northern mainland of Japan  and someThe introgression of pig genes is suggested to have contributed to the rapid population growth rates of wild boar in Europe ,47,48 anThe greater abundance and higher densities of wild boar in the Fukushima evacuated area  coupled . 5Here, using genetic markers, we demonstrated evidence of hybridization and introgression of invasive genes as a result of extrinsic environmental changes that reformed anthropogenic land use in Fukushima Prefecture in 2011. We found that there were likely successful hybridization events in the evacuation zone following a sudden and large biological invasion, that thereafter spread and diluted through time. However, a massive introgression was not observed in this area and we speculate two hypotheses for these patterns: (i) an abundant wild boar population caused increasing introgression of wild boar genes into the invasive pigs and a decreasing introgression of invasive genes into the wild boar with the increase in the distance from the invasion source. (ii) The pig legacy passed on to the next-generation hybrids was dependent on the ability of pigs to naturalize in the wild area of Japan. In either case, if the invasion occurred in an environment that was not occupied already by high densities of wild boar, or if invaders had more advantageous survival traits for the wild, then maybe the invasive pigs would have had the same successful adaption as they had in other countries. We recommend that future studies assess the fitness of these hybrids and better characterize their ecological niche using range expansion models and their ecological interactions. Such studies could determine if demic diffusion occurred after range expansion, or if natural selection played a role. Both scenarios suggest that the introgressed genes will eventually disappear in this area.Click here for additional data file.