PPARD on the therapeutic efficacy of exenatide. This research was aimed to explore the influence of PPARD gene polymorphism on the therapeutic effect of exenatide, and to identify the potential mechanism futher.Exenatide is a GLP-1R agonist that often exhibits considerable interindividual variability in therapeutic efficacy. However, there is no evidence about the impact of genetic variants in the PPARD rs2016520 and rs3777744 genotypes. A prospective clinical study was used to collect clinical indicators and peripheral blood of T2DM patients treated with exenatide monotherapy for 6 months. The SNaPshot method was used to identify PPARD rs2016520 and rs3777744 genotypes, and then we performed correlation analysis between PPARD gene variants and the efficacy of exenatide, and conducted multiple linear regression analysis of factors affecting the therapeutic effect of exenatide. HepG2 cells were incubated with exenatide in the absence or presence of a PPARδ agonist or the siPPARδ plasmid, after which the levels of GLP-1R and the ratio of glucose uptake were determined.A total of 300 patients with T2DM and 200 control subjects were enrolled to identify PPARD rs2016520 were significantly lower than those with the TT genotype, which suggested that the PPARD rs2016520 TT genotype conferred the poor exenatide response through a reduction of insulin resistance, as measured by HOMA-IR. The carriers of G alleles at rs3777744 exhibited higher levels of in waist to hip ratio (WHR), fasting plasma glucose (FPG), hemoglobin A1c (HbA1c) and HOMA-IR compared to individuals with the AA genotype following 6 months of exenatide treatment, potentially accounting for the lower failure rate of exenatide therapy among the AA homozygotes. In an insulin resistant HepG2 cell model, the PPARδ agonists enhanced exenatide efficacy on insulin resistance, with the expression of GLP-1R being up-regulated markedly.After 6 months exenatide monotherapy, we observed that homeostasis model assessment for insulin resistance (HOMA-IR) levels of the subjects with at least one C allele of the PPARD rs2016520 and rs3777744 polymorphisms are associated with exenatide monotherapy efficacy, due to the pivotal role of PPARδ in regulating insulin resistance through affecting the expression of GLP-1R. This study was registered in the Chinese Clinical Trial Register (No. ChiCTR-CCC13003536).These data suggest that the  PPARD), associated with T2DM susceptibility or abnormal indicators of metabolism  is a member of the peroxisome proliferator activated receptor family, which is widely distributed in the liver, kidney, cardiac and skeletal muscle, adipose tissue, brain, pancreatic and vasculature  and body mass index (BMI)  is associated with blood glucose, insulin level and insulin resistance, and is a key factor affecting the development of metabolic syndrome and T2DM  has risen at an astounding rate over the world . T2DM istabolism . PPARD iculature . PPARD wex (BMI) . Studiesand T2DM . More reand T2DM , 13. Curhttps://www.ncbi.nlm.nih.gov/) and JASPAR database (http://jaspar.genereg.net/), and found the potential PPARδ binding site (Exenatide is a glucagon-like peptide 1 (GLP1) analogue that exerts its pharmacological effects through activating glucagon-like peptide 1 receptor (GLP1-R). It mirrors many of the effects of GLP-1 and improve glycemic control through a combination of mechanisms, which includes glucose-dependent stimulation of insulin secretion, suppression of glucagon secretion, slowing of gastric emptying and reduction of appetite , 15. ThePPARD single nucleotide polymorphisms (SNPs) have the same influence on the therapeutic effects of exenatide. In this study, we investigated the association between PPARD variants and the efficacy of exenatide in newly diagnosed Chinese T2DM patients who received exenatide monotherapy for 6 months, and further explored the potential mechanism.Pharmacogenomic studies have identified genetic factors as an important cause of individual differences in the efficacy of hypoglycemic drugs , 21, 22.PPARD variants analysis. T2DM patients and healthy subjects were recruited from the Department of Endocrinology and Health Screening Center, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China. T2DM was diagnosed according to the 1999 World Health Organization criteria. The inclusion criteria were: newly diagnosed T2DM without drug therapy; 25 to 70 years old; Hemoglobin A1c (HbA1c) 7%-12%; BMI 20-35 kg/m2; Stable body weight (≤10% change within 3 months); Female subjects were required to use birth control pills during the three months prior to screening and during the study, or surgical contraception, or postmenopausal women. Subjects with acute or severe chronic diabetic complications, serious comorbid diseases, New York Heart Function Scale (NYHA) III~IV, severe osteoporosis or a history of fractures, alanine aminotransferase (ALT) and aspartate transaminase (AST) ≥2.5 times of upper limit, or serum creatinine level ≥133 µmol/L, severe gastrointestinal dysfunction, ongoing use of weight-loss drugs, glucocorticoids, drugs that affecting gastrointestinal motility, transplant therapy drugs, any investigational drugs, a history of pancreatitis, or serum triglyceride level ≥5 mmol/L were excluded. A total of 105 newly diagnosed T2DM patients  with different PPARD rs2016520 and rs3777744 genotypes were randomly selected to receive exenatide injection subcutaneously for 6 months and completed the follow-up. During the 1st week to the 4th week, exenatide was given 5 µg once, twice a day, after which the dose was adjusted to 10 µg once, twice a day. The protocol was approved by the Ethics Committee of the Affiliated Hospital of Xuzhou Medical University. Written informed consent was obtained from each participant before taking part in the study.A total of 300 patients with T2DM  and 200 healthy controls  were enrolled for 2, WHR = waist circumference (cm)/hip circumference (cm). Venous blood was collected both after fasting overnight and 2 h later during a standard oral glucose tolerance test. Parameters were measured before administration of exenatide, 3 months and 6 months after administration. Plasma glucose and serum lipids were detected using a Roche Cobas8000 analyzer  with standard laboratory methods. Accordingly, the levels of insulin and HbA1c were measured by an electrochemiluminescence assay  and high-performance liquid chromatography (HPLC). The homeostasis model assessment for insulin resistance (HOMA-IR) and homeostasis model assessment for beta cell function (HOMA-B) were calculated using the formula: HOMA-IR = fasting insulin (mU/L)×fasting plasma glucose (mmol/L)/22.5; homeostasis model assessment HOMA-B = 20×fasting serum insulin (FINS)/(FPG-3.5)  were calculated. BMI = body weight (kg)/height (m)FPG-3.5) .PPARD rs2016520 and rs3777744 was performed by SNaPshot assay  with the standard protocol  according to the manufacturer’s protocol. The allelic discrimination of protocol .The guideline of National Institute for Health and Care Excellence (NICE) define T2DM patients who have a ≥1.0% reduction in HbA1c or a ≥3% reduction in body weight after 6 months of treatment with GLP-1 agonists as the treatment response group, and those who do not meet these criteria are defined as Non-responders . Based o2 at 37°C. The insulin-resistant cell model was induced using the previous method  for 6 h. Subsequently, the medium was exchanged with medium containing 1% FBS, 10-6 mmol/L insulin and Exendin-4 . Cells were incubated in this medium for 12 h.The human hepatoma cell line (HepG2) was obtained from the Type Culture Collection of the Chinese Academy of Sciences , cultured in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum  and were placed in a humidified incubator containing an atmosphere of 5% COs method . HepG2 cThe transfection of plasmids (6 µg) was carried out using Lipofectamine 3000 Transfection Reagent  according to the manufacturer’s instructions. The ratio of plasmids (μg) and transfection reagents (μL) was 3:4 –29. The Glucose content was determined by the enzymatic method of the diagnostic kit using 10 μL of medium . Data were expressed as extracellular glucose consumption (nmol/mg protein) and calculated as follows: [before extracellular glucose content (nmol) - after extracellular glucose content (nmol)]/mg cellular protein , which wWestern blot analysis was performed as previously described , and theTotal RNA in HepG2 cells was isolated using Trizol Reagent  according to the manufacturer’s instructions, and the steps of RT-PCR were carried out as described previously , 30. Dathttp://www.ncss.com). In the experimental study, differences between treated and control results were compared using one-way ANOVA with a Tukey-Kramer post-test for multiple comparisons or unpaired t-test. Two-sided tests were used for all analyses, and P < 0.05 indicated statistically significant.All data were expressed as mean ± standard deviation (Mean ± SD) or percentage as appropriate. Statistical analyses were performed using SPSS software . Chi-square test was used to compare the Hardy-Weinberg equilibrium, allele frequency and genotype distribution among different groups. Linkage disequilibrium (LD) among SNPs was estimated in subjects using Haploview version 3.2. The two-sample t-test was used to compare the baseline characteristics between T2DM patients and healthy subjects. The paired Student’s t-test was applied for evaluating the parameters between the two groups before and after exenatide treatment. For parameters of normal distribution, two-sample t-test was used for comparison between two groups, and one-way analysis of variance (ANOVA) was used for comparison among multiple groups. Parameters with nonnormal distribution were analyzed by the Mann-Whitney U-test or the Kruskal-Wallis test. ANOVA for repeated measurement was used to compare the parameters collected at different treatment time points of the same patient. Statistical power was calculated by power calculator software  and 200 healthy controls  , whereas the PPARD rs2016520 variant, there was no significant difference in allele frequencies between the two groups. The genotype distributions of rs2016520 (P = 0.105) and rs3777744 (P = 0.171) SNPs were in Hardy-Weinberg equilibrium. Assessment of the LD between the variants using our control subjects revealed a relatively low disequilibrium between rs2016520 and rs3777744 (D’ = 0.110).In the present study,  female) Table 1.PPARD rs2016520 in terms of BMI (P = 0.000), WHR (P = 0.001) and TG (P = 0.006) (P = 0.000), PPG (P = 0.011), FINS (P = 0.004) and HOMA-IR (P = 0.000) levels , TG, and LDL-C values of patients with T2DM were significantly decreased, but the levels of FINS and HOMA-B increased, compared with the pretreatment values ; AA allele homozygotes had the highest response rate (84.00%), while AG heterozygous and GG homozygous had 61.36% and 54.55%, respectively (P = 0.022). No significant effects of PPARD rs2016520 variant on exenatide therapy were observed.In order to assess the association of the r groups Table 4.PPARD variant and improvement in HbA1c after exenatide treatment, a multiple linear regression model was used, with the dependent variable being the decrease in HbA1c after 6 months of exenatide treatment and the independent variables being age, gender, baseline BMI, baseline WHR, baseline HbA1c, rs2016520 and rs3777744. The results showed that the improvement of HbA1c after exenatide treatment was significantly correlated with baseline HbA1c and rs3777744, and the difference between PPARD rs3777744 AG+GG genotype and AA genotype in the improvement of HbA1c was statistically significant (P = 0.009). Higher the baseline HbA1c was, more significantly the HbA1c improved after 6 months of exenatide treatment (P = 0.000) (To further determine the correlation between = 0.000) Table 5.db/db mice and in an insulin-resistant HepG2 cell model. When compared with the db/m group, the mRNA and protein levels of PPARδ in the liver tissues of db/db group were significantly lower (P < 0.05)  and the negative control group (NC), but both mRNA and protein expression of PPARδ were significantly lower in the insulin resistant group (IR) (P < 0.05)  plasmid were transfected in HepG2 cells, and the knockdown efficiency of the three plasmids  was detected. The RT-PCR and western blot results showed the most significant reduction in the siPPARδ-3 group  of xenatide –20. The PPARD are associated with an increased risk of impaired glucose tolerance, fasting glucose elevation and insulin resistance in populations with diverse ethnic backgrounds including Chinese, Korean and Mexican  was lower than that in the data from the 1000 Genomes (36.60%)  . Comparisistance , 33.PPARD gene variants may account for individual differences in the clinical efficacy of exenatide. There is no evidence from previous studies that patients with specific PPARD gene variants have better or worse clinical efficacy of exenatide. In this study, we observed that the FINS and HOMA-IR levels of the subjects with at least one C allele of the PPARD rs2016520 were significantly lower than those with the TT genotype after 6 months of treatment, which suggested that the PPARD rs2016520 TT genotype conferred the poor exenatide response through a reduction of insulin resistance, as measured by HOMA-IR. PPARδ is engaged in glucose and lipid metabolism in the liver and exerts insulin-sensitizing effects, thereby improving hepatic insulin resistance  and rs3777744 (located in intron2) have made it more difficult to carry out functional studies. We only explored the regulatory effect of PPARδ on GLP-1R and its effect on exenatide efficacy, however, the mechanism of SNPs in PPARD influence on PPARδ has not been elucidated.Meanwhile, several shortcomings of this study need to be considered when interpreting our findings. First, the sample size is relatively small, which results in restricted statistical power and low frequency of mutant phenotypes, this may have led us to miss some meaningful results. The current study had an estimated 81-97% power (for α=0.05) to detect the difference in the parameters. Consequently, further detailed studies with expanded sample size are warranted to validate the effects of PPARD variants appear to be associated with the therapeutic response to exenatide in patients with T2DM. There may be a link between PPARδ and GLP-1R in the diabetic condition, which may be the molecular mechanism by which PPARD gene variants influence T2DM risk, insulin resistance and clinical response to exenatide. Therefore, the PPARD risk mutations may serve as exenatide response predictors based on PPARδ regulating GLP-1R expression and mediating insulin resistance. More detailed pharmacogenetic and functional studies are needed to elucidate the exact effects of PPARD variants on exenatide therapeutic efficacy, which is necessary to lay the foundation for a more precise and patient-tailored therapy for T2DM.In conclusion, the https://submit.ncbi.nlm.nih.gov/subs/biosample/SUB11888229/overview (NCBI) repository, accession number SUB11888229.The data presented in the study are deposited in the The studies involving human participants were reviewed and approved by Ethics Committee of the Affiliated Hospital of Xuzhou Medical University. The patients/participants provided their written informed consent to participate in this study. The animal study was reviewed and approved by Animal Experiment Ethics Review Committee of Xuzhou Medical University.JS contributed to conception of the article, data acquisition, statistical analysis, result interpretation, manuscript drafting and approved the final version. TW and XY designed the experiments and revised the paper. NL, RH, YY, KX, QL and TY helped with the experiments. HL contributed to data acquisition, and revised the paper. All authors contributed to the article and approved the submitted version.This work was supported by grants from the National Natural Science Foundation of China (82003866), the Science and Technology Planning Project of Xuzhou (KC20093), the Wuxi Science and Technology Development Medical and Health Guidance Project (No. CSZ0N1809), and Jiangsu Research Hospital Association for Precision Medication (No. JY202011).We thank all the volunteers in this study for their cooperation, and the physicians from the Department of Endocrinology, the Affiliated Hospital of Xuzhou Medical University for their support.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Parkinson’s disease (PD), the second most common neurodegenerative disorder worldwide, is characterized by dopaminergic neuron degeneration and α-synuclein aggregation in the substantia nigra pars compacta of the midbrain. Emerging evidence has shown that dietary intake affects the microbial composition in the gut, which in turn contributes to, or protects against, the degeneration of dopaminergic neurons in affected regions of the brain. More specifically, the Mediterranean diet and Western diet, composed of varying amounts of proteins, carbohydrates, and fats, exert contrasting effects on PD pathophysiology via alterations in the gut microbiota and dopamine levels. Interestingly, the negative changes in the gut microbiota of patients with PD parallel changes that are seen in individuals that consume a Western diet, and are opposite to those that adhere to a Mediterranean diet. In this review, we first examine the role of prominent food groups on dopamine bioavailability, how they modulate the composition and function of the gut microbiota and the subsequent effects on PD and obesity pathophysiology. We then highlight evidence on how microbiota transplant and weight loss surgery can be used as therapeutic tools to restore dopaminergic deficits through optimizing gut microbial composition. In the process, we revisit dietary metabolites and their role in therapeutic approaches involving dopaminergic pathways. Overall, understanding the role of nutrition on dopamine bioavailability and gut microbiota in dopamine-related pathologies such as PD will help develop more precise therapeutic targets to rescue dopaminergic deficits in neurologic and metabolic disorders. Parkinson’s Disease (PD) is a multifactorial, progressive neurodegenerative disease that results from a combination of genetic and environmental factors, as well as various protective and risk factors . At presIn this review, we explore these relationships by first presenting emerging evidence demonstrating the relationship between nutrition, gut microbiota, and dopamine bioavailability. Then, we briefly describe the changes seen in gut microbial composition profile following dietary interventions and dopaminergic neuronal loss as seen in PD. Lastly, we present evidence linking PD with obesity and therapeutical approaches, such as FMT and WLS, to rescuing the dopaminergic deficits that are characteristic of PD and obesity.Bacteroides in the gut, while carbohydrate-rich plant diets are linked with species within the Prevotella genus .,49.48,49Furthermore, the metabolic changes induced by high sugar diets result in altered dopaminergic signaling and gut microbial profiles. For example, a high fructose corn syrup (HFCS) diet induced glucose dysregulation that occurred in parallel with reduced dopamine release . The higOmega-3 poly-unsaturated fatty acids (PUFA), found in fish, plant oils and nuts, have also been studied in the context of dopamine and neurological disorders. Dietary omega-3 deficiency is correlated with a unique sensitivity in adolescents, leading to enhanced dopamine availability in the striatum . HoweverRecent studies demonstrate that fish oil from omega-3 PUFA prevents against oxidative damage in the prefrontal cortex via alterations in dopamine neurotransmission . In thisLactobacillus, was found to be significantly elevated after omega-3 PUFA supplementation  production and colonic inflammation while increasing hippocampal BDNF levels. The probiotic also prevented activated microglia from permeating into the hippocampus . As. AsLactoasticity . This efpocampus . Encouraved mice . SupplemRoseburia, Blautia and Bifidobacterium species  with decreased dopamine bioavailability , low proRoseburia and decreasing Bilophila over a 5-week period  has been extensively studied in recent years due to its beneficial association with neurodegenerative diseases such as PD and Alzheimer’s disease . The MD k period  86]. Th. ThRosebBifidobacterium and an overall gut enterotype that promotes inflammation .,91.Bifid disease  and prod disease . These f disease , both of disease . Additio disease . The NLR disease . These fIn addition to their effects on PD, several studies have evaluated the effects of MD and WD diets on dopamine and other related pathologies. For example, the WD and MD demonstrated opposite effects on morphine addiction. WD exaggerated anxiety and stress-behaviors via exacerbation of the hypothalamus-pituitary-adrenal (HPA) axis leading to morphine withdrawal symptoms, while MD prevented morphine re-instatement . DysreguRuminococcus, Akkermansia, Eggerthella,Enterobacteriaceae, Catabacter, Shigella, Lachnospiraceae, Streptococcus, Eschiria, Enterococcus with reductions in the concentrations of Bacteroides, Coprococcus, Prevotella, Faecalibacterium and Clostridium species. The development of pathognomonic symptoms of PD has been directly associated with some of these gut microbial alterations. For example, an abundance of Enterobacteriaceae is linked with motor symptoms of PD, specifically abnormal gait and postural instability . St. St22]. es GLP-1 , which wes GLP-1 . In a sees GLP-1 , suggestes GLP-1 . Evidences GLP-1 . Furtheres GLP-1 . Althouges GLP-1 . HoweverBacteroides uniformis in a rat model of food addiction improved binge eating, an effect mediated by NAc dopamine and prefrontal cortex D1 and D2 receptors [Akkermansia muciniphilia’s products  have been shown to modulate the mesolimbic dopaminergic signaling leading to reduced dopamine release in NAc shell [Changes in gut microbiota composition following RYGB have also been linked with other dopaminergic neural substrates, such as the reward system. For example, GF mice have increased serotonin turnover, noradrenaline, and dopamine in the striatum ,172. Fureceptors . FinallyAc shell . SCFAs, Ac shell . In factAc shell  and reguAc shell ,180. TakPrevotella, Roseburia and Eubacterium spp., while increasing Ruminococcus spp. [Substantial evidence supports the role of nutrition on restructuring gut microbiota in ways that increase susceptibility to, or confer neuroprotection against, PD. More specifically, dietary proteins, fats and carbohydrates, as part of the MD and WD, have individual, critical and varying roles in dopaminergic pathways, as well as dopamine metabolism and bioavailability. Foods rich in whole-grain cereals, wheats, nuts, seeds, PUFA, fruits and vegetables characteristic of MD, and those rich in fats, sugars and animal proteins that comprise the WD, have inverse effects on gut microbe composition and risks of PD development. Further, microbial sequencing of the parkinsonian gut has shown similarities to diet-specific changes induced by the MD and WD. For example, the Western diet induces decreases in cus spp. ,108,109,cus spp. . Thus, mcus spp. .Our review highlights therapeutic modalities that can be used to restore beneficial gut microbial concentrations, and attenuate dopaminergic and PD deficits. As such, FMT restores striatal dopamine concentrations, reduces dopaminergic neuronal loss, and decreases LPS/microglial induced neuroinflammation. Additionally, FMT is able to restore the effects of p-cresol which is a key proteolytic byproduct of the WD. WLS, on the other hand, has been shown to treat obesity and reduce resulting comorbidities by causing alterations in the gut microbiota to affect gut-brain signaling and the dopaminergic signaling pathways. WLS restores dopamine deficits by increasing dopaminergic receptor and transporter expression. RYGB surgery also increases levels of ghrelin and GLP-1, which have been positively associated with obesity, dietary interventions, and dopamine production . The speBlautia and Prevotella species [Although significant progress has been made in elucidating the mechanisms by which therapeutic modalities such as FMT and WLS that change gut microbial composition can influence dopamine-related pathologies, there remains much to be learned. PD is a multifactorial disorder that involves a combination of systemic, genetic, and environmental factors. One limitation of FMT is that nearly all studies that show restoration of dopamine functions or alleviation of PD deficits were conducted using animal models with Parkinsonian features through MPTP or rotenone-induced neurotoxicity. Similarly, some studies used donor feces from humans that were transplanted into recipient animal models , which r species . Again, WLS, on the other hand, has its own limitations. Although clear associations have shown the beneficial effects of gut microbiota and resulting effects on key gut hormones, dopamine transporters and receptors, WLS has not been well studied in direct association with PD. Several studies have focused more largely on the positive effects of WLS on reward pathways, specifically the hedonic control of food consumption. It has been shown that WLS-induced increases in striatal dopamine transmission can improve reward sensitivity, hormonal signaling and learned food avoidances . This foIt is also worth pointing out that specific changes in microbiota composition post-WLS can vary based on species differences , diet regimens, and time-course, all of which can affect its association with key aspects of the dopaminergic pathway.Nevertheless, the preliminary data linking WLS, FMT and dopamine is promising, and future studies should focus on further elucidation of the mechanisms by which these therapeutic targets can prevent, delay or restore PD deficits.


Mass spectrometric techniques can provide data on the composition of a studied sample, utilizing both targeted and untargeted approaches to solve various research problems. Analysis of compounds in the low mass range has practical implications in many areas of research and industry. Laser desorption ionization techniques are utilized for the analysis of molecules in a low mass region using low sample volume, providing high sensitivity with low chemical background. The fabrication of substrates based on nanostructures to assist ionization with well-controlled morphology may improve LDI-MS efficiency for silver nanoparticles with plasmonic properties. In this work, we report an approach for the preparation of silver nanostructured substrates applied as laser desorption ionization (LDI) plates, using the chemical vapor deposition (CVD) technique. Depending on the mass of used CVD precursor, the approach allowed the synthesis of LDI plates with tunable sensitivity for various low molecular weight compounds in both ion-positive and ion-negative modes. Reduced chemical background and sensitivity to small biomolecules of various classes  at nanomolar and picomolar detection levels for lipids such as triacylglycerols, phosphatidylethanolamines and lyso-phosphatidylcholines represent an emerging perspective for applications of LDI-MS plates for the collection of molecular profiles and targeted analysis of low molecular weight compounds for various purposes. Low molecular weight (LMW) compounds are targeted in various research fields with the aims of (i) searching for potential diseases biomarkers, e.g., gastric or prostate cancers ,2, (ii) Laser desorption ionization/mass spectrometry (LDI-MS) was firstly utilized for the analysis of proteins with cobalt nanoparticles as an inorganic matrix by Tanaka et al. . Noble mMany developments in the fabrication of various nanostructures based on noble metals such as gold and silver have been reported in the last decade . One of Chemical vapor deposition technique allows the synthesis of nanolayers of inorganic materials on the surface of 3D substrates . The sucDespite the utilization of the CVD technique for fabrication of a nanostructured layer on various substrates, rare efforts have been focused on its application in LDI-MS. The CVD technique has been used previously for fabrication of carbon nanotubes  that werThe aim of this study was to study the effect of the mass of the precursor on morphology and the LDI-MS efficiency of the obtained silver nanostructures towards low molecular weight analytes with utilization of chemical vapor deposition techniques. The LDI-MS plates synthesized with the proposed approach showed tunable sensitivity in both ion-positive and ion-negative modes. The plates can be used for the collection of molecular profiles and the analysis of small biomolecules with targeted approach at nanomolar and picomolar detection levels.Standards of low molecular weight compounds such as adonitol, glucose, fructose, shikimic acid, oleic acid, palmitic acid, cholesterol, methionine, serine, alanine and phenylalanine, all of the highest available purity, were purchased from Sigma Aldrich . Standards of various classes of lipids were purchased from Avanti Polar Lipids , including phosphatidylcholine 18:0 (<99%), lyso-PC, PE, PI and TG internal standard mixture . Solvents for the preparation of stock solutions of LC-MS grade quality (≥99.9%), such as water and chloroform, were purchased from Sigma Aldrich .5(O2CC2F5)5(H2O)3 has been used as a precursor, the synthesis and physicochemical properties of which were earlier described [5(O2CC2F5)5(H2O)3] compound has also been used as a precursor in our CVD experiments; the synthesis and physicochemical properties of the compound were described earlier + .m/z 487.11 was assigned to m/z 524.88 was assigned to m/z 515.02 and 543.02, respectively. The other plates, such as AgPs0.06 and AgPs0.11, provided molecular ions for only selected lyso-PCs. For example, the plate AgPs0.06 allowed to register 15:0 lyso-PC as m/z 598.90 and m/z 524.90, only where the value of global attenuator was 25% and parameter set ‘4_large’, while for plate AgPs0.04, registered molecular ions for all lyso-PCs and such conditions were not necessary. The plate AgPs0.11 provided molecular ions assigned to m/z 524.83 corresponding to lyso-PC 15:0. The plate AgPs0.2 showed that the signal at m/z 525.35 was assigned to lyso-PC), and the signal at m/z 538.66 probably corresponds to All of the lyso-PCs of the standard mixture were detected using plate AgPs0.04 . The sigThe other classes of lipids  might have undergone fragmentation, since their molecular ions were not detected. Due to the plasmonic properties of noble metal nanostructures, an excess of energy could lead to an enhanced fragmentation of lipids, which may complicate identification. A decrease in laser power did not result in obtaining signals corresponding to molecular ions. However, the plates could be used in the future for the collection of molecular profiles of samples, with an aim to reveal the differences and similarities between the samples, since fragments of various classes of lipids also can be characteristic.The presented approach allows for the synthesis of LDI plates with tunable sensitivity for various classes of small biomolecules. The utilization of a chemical vapor deposition technique with various values of the mass of the precursor resulted in the formation of structures with sizes 50–330 nm and up to 1 μm with irregular shapes. Small biomolecules were detected at nanomolar concentrations, while lipids were detected at the picomolar level with a reduced chemical background. Sensitivity towards low molecular weight analytes in both ion-positive and ion-negative modes is an advantage for the applications of the plates for the collection of molecular profiles as well as targeted analysis.


Persistent organic pollutants (POPs) have adverse effects on the human health and ecosystem functioning. Graphene oxide (GO) has been developed to remove trace levels of POPs from wastewater samples. However, many questions involved in these processes are still unresolved . Revealing the microscopic interactions between GO and POPs is of benefit to resolve these questions. In the present study, a quantum chemical calculation was used to calculate the molecular doping and adsorption energy between eight representative POPs and GO. The influences of GO on the thermodynamic parameters, such as the Gibbs free energy and the highest occupied molecular orbital (HOMO)-lowest unoccupied molecular orbital (LUMO) gap, were also reported. We found the molecular doping is dependent on the species of POPs. The adsorption energy of the majority of POPs on GO is between 7 and 8 kJ/mol. Consequently, the GO may make degradation of POPs in wastewater more productive and lead to a change of kinetics of the degradation of POPs. Persistent organic pollutants (POPs) denote organic chemicals that are resistant to environmental degradation through photolytic, chemical, and biological processes . They ha3O4@GO presented a high enrichment of PCBs from environmental water samples [2O4 nanocomposites could be used for the electrochemical oxidation of hydrazine [Graphene oxide (GO), the oxidized analogue of graphene, is a two-dimension structured and oxygenated planar molecular material. It has been widely used in multidisciplinary fields, such as nonlinear optical materials ,13, targ samples . Le et a samples . Koushik samples . Gupta e samples . Uddin eydrazine . Wu et aydrazine .Although the processes of removing different kinds of POPs by GO were studied profoundly, many questions involved in these processes are still unresolved. For example, the roles of π–π interaction, the effects of GO on the degradation of POPs, etc. Revealing the interactions between GO and POPs is useful not only to understand the influences of GO on POPs, but also to promote the modification of GO for better treatment of POPs in wastewater. In the present study, a semi-empirical quantum chemistry method, AM1, was used to calculate the molecular doping and adsorption energy between eight selected POPs and GO. The influence of GO on the thermodynamic parameters, such as the Gibbs free energy, was also reported. Furthermore, physical-chemistry models were implemented with the data from quantum chemical calculation to illustrate the potential significance of GO for removal of POPs in wastewater treatment.p-dioxin (TCDD), lindane, 4,4′-dibromodiphenyl ether (BDE15), and PFOS, as the representative of POPs were studied here. The information about these chemicals is listed in Several typical chemicals, naphthalene, hexachlorobutadiene, dichloro-diphenyl-trichloroethane (DDT), PCB15, 2,3,7,8-tetrachlorodibenzo-All of the optimization and vibrational frequencies analysis mentioned below were performed using Gaussian 09  with AM1 method. As a computational physics and chemistry program, Gaussian 09 software typically uses density functional theory (DFT) method for electronic and geometric structure optimization , molecular properties, vibration analysis, electrostatic potential, electron density, and multipole moments. However, given that the systems studied here were a bit large, the AM1 method was used to facilitate the investigation of molecular doping and adsorption energy. The schematic of all the procedures was summarized in The values of isolated POPs were calculated and compared to the values of POPs undergoing the influence of GO. To calculate values for isolated chemicals, it is needed to optimize the structure of studied chemicals individually and to analyze the respective vibrational frequencies. To get the values influenced by GO, we optimized the structure of studied chemicals with GO first, and then removed GO and performed vibrational frequency analysis on the corresponding studied chemicals.2O and NH3) adsorbed on the surface of graphene [Molecular doping, which means that charge transfer between the studied POPs and the surface of GO, is analyzed. As shown in graphene . The numThe effect of GO on the degradations of POPs in wastewater is analyzed. The reaction of degradation can be presented byThe reaction gets equilibrium when Equation (3) occurs.Here,  is made . Gts is lculated . GPOPs1 ne atoms .GO can decrease the energy barrier of reactions involved in degradation. Thus, no matter what is the value of Therefore, the equilibrium constant without the influence of GO is larger than that when GO is absent.1 and LUMO1) or absent (HOMO0 and LUMO0) are shown. According to the frontier molecular orbital theory [The effects of GO on the HOMO and LUMO of POPs are studied in this section. In l theory , HOMO-LUlculated . HOMO isThe HOMO-LUMO gap of several compounds with or without GO were compared. The results showed that the order of stewater ,38,39, ttion (8) .(8)kSO4On the other hand, the present results also provide ideas for the chemical removal of POPs. GO changes the In summary, we used a quantum chemical calculation to illustrate the interaction between GO and different kinds of POPs. The molecular doping is dependent on the POPs and no unified law applies to these chemicals. The adsorption energy of POPs on GO is calculated, and the majority of these values are between 7 and 8 kJ/mol. The GO increases Gibbs free energy, and it implies GO can make degradation of POPs in wastewater more productive. GO also changes


Extracellular vesicles (EVs) are lipid‐membrane enclosed nanoparticles that play significant roles in health and disease. EVs are abundant in body fluids and carry an array of molecules  that reflect the identity and activity of their cell‐of‐origin. While the advent of high throughput omics technologies has allowed in‐depth characterisation of EV compositions, how these molecular species are spatially distributed within EV structures is not well appreciated. This is particularly true of the EV surface where a plethora of molecules are reported to be both integral and peripherally associated to the EV membrane. This coronal layer or ‘atmosphere’ that surrounds the EV membrane contributes to a large, highly interactive and dynamic surface area that is responsible for facilitating EV interactions with the extracellular environment. The EV coronal layer harbours surface molecules that reflect the identity of parent cells, which is likely a highly valuable property in the context of diagnostic liquid biopsies. In this review, we describe the current understanding of the mechanical, electrostatic and molecular properties of the EV surface that offer significant biomarker potential and contribute to a highly dynamic interactome. Typically, EV surface molecules are canonical to EVs and the cell‐of‐origin and acquired from the extracellular environment. The EV surface molecular repertoire is, therefore, influenced by EV sub‐type, host cell identity and molecular state and EV biodistribution patterns , sphingolipids , glycerolipids (diacylglycerols), cholesterol and glycolipids. Comprehensive lipidomic mass spectrometry analyses of EVs derived from adipocytes  and small‐EV (<100 nm) sub‐types from adipocyte 3T3‐L1 cells showed similar concentrations of phospholipids and sphingolipids, while cholesterol was enriched in small‐EVs by 2‐fold  proteins, and 2‐fold more nuclear proteins (16.8%) compared to the EV lumen (8.3%)    on the EV surface  molecules, release growth factors and alter cell adhesion , including glycosylation, acetylation, phosphorylation, oxidation, methylation and ubiquitination. Of these, glycosylation is the most adequately characterised modification at the EV surface. Up to 85% of human extracellular proteins are glycosylated, a process by which glycans (approximately 10 monomeric carbohydrate units) are covalently attached to protein amino‐acid side chains in four ways: (1) N‐linked to asparagine, (2) O‐linked to serine, threonine or tyrosine, (3) C‐linked to tryptophan and (4) glypiation , EV surface glycan profiles show great promise as diagnostic and predictive biomarkers  and RNA nucleoproteins (RNPs) Table  Xu et a. In a st4The EV surface coronal layer carries an assortment of biologically active molecules that play important roles in modulating the extracellular environment. Through a diverse range of molecular interactions, the EV coronal layer governs EV mobility to local or distant sites, docking on recipient cell membranes, interactions with the ECM or effector molecules and the activation of signalling cascades in recipient cells. The vast array of interacting elements at the EV surface includes ECM molecules, cytokines, lipoproteins, immunoglobulins and all their respective receptors, as well as nucleic acids complexed with DNA‐ and RNA‐binding proteins Figure . General+ T‐cell function and allow tumour expansion   may contribute to molecular changes at the EV surface coronal layer. Moreover, the conditions of the surrounding medium may affect the electrostatic interactions of transiently interacting molecules at the EV surface and promote their dissociation or contact. For example, as EVs move from the circulation into the urinary system where there is a lower native pH, viscosity and molecular complexity, soluble blood molecules at the EV surface may be shed and urinary molecules acquired. As the EV biological medium may influence the composition and thickness of the EV coronal layer  as compared to monovalent ions (Na+/K+)  under acidic conditions, or interact with ions of higher valency, that lead to the compression of the surrounding electrical double layer and a higher zeta potential  and tumour‐cell surface associated markers such as EpCAM, CA125, CD19, EGFR, EGFRvIII, podoplanin and PDGFR for on‐chip capture of tumour‐EV sub‐populations (Belov et al., Membrane‐sensing peptides have also emerged as conceivable molecular probes that can be immobilised on chips for targeting the EV lipid membrane and capturing EVs (Gori et al., As EV surface molecular arrangements are not yet adequately characterised, more recent adaptations have been made to microfluidic technologies to completely omit antibodies and other molecular probes from the capture and analysis of EVs (Jalali et al., Several other methods are also under development for probe‐free capture of EVs from body fluids, offering the possibility of targeting universal EV surface properties for liquid biopsies (Gori et al., EV surface profiling through microfluidic and microarray techniques will be highly valuable for assessing panels of EV surface markers. However, in‐depth biomarker discoveries are first required to construct the EV surface molecular profile (Wu et al., 8The EV surface carries a plethora of molecules that are integral and peripherally associated to the EV membrane that interact with soluble molecules in the extracellular environment, influencing EV size, mobility and biodistribution patterns. Together, EV surface molecules form a coronal layer that surrounds the EV membrane and contributes to a large, interactive and highly dynamic surface area that facilitates functionally important interactions and downstream signalling events. In the context of clinical molecular diagnostics, EV surface molecules are critically important for the development of liquid biopsies that can target and capture disease‐specific EV populations from complex body fluids. The expansion of EV surface studies to construct a comprehensive multi‐dimensional spatial and temporal molecular map of the EV surface is warranted and will be important to further our understanding of the roles of EVs in health and disease, and to develop robust EV‐based assays for clinical molecular biology.Conceptualization: Susannah Hallal and Kimberley L. Alexander. Investigation: Susannah Hallal, Ágota Tűzesi and Kimberley L. Alexander. Visualization: Susannah Hallal and Kimberley L. Alexander. Writing – original draft: Susannah Hallal, Ágota Tűzesi, Michael E. Buckland and Kimberley L. Alexander. Writing – review & editing: Susannah Hallal, Ágota Tűzesi, Michael E. Buckland and Kimberley L. Alexander. Resources: Michael E. Buckland and Kimberley L. Alexander. Supervision: Kimberley L. Alexander. Funding acquisition: Kimberley L. Alexander. Project administration: Kimberley L. Alexander.


Antimicrobial resistance (AMR) is becoming a critical public health issue globally. The World Health Organization launched the Global Antimicrobial Resistance and Use Surveillance System (GLASS) to support the strengthening of the AMR evidence base.The article describes the evolution of national AMR surveillance systems and AMR data reporting of countries in the African continent between 2017 and 2019, and the constraints, perceived impact and value of the participation in GLASS.Data on implementation of national surveillance systems and AMR rates were submitted to GLASS between 2017 and 2019 and summarised though descriptive statistics. The information on constraints and perceived impact and value in GLASS participation was collected though a set of questionnaires.Between 2017 and 2019, Egypt, Ethiopia, Madagascar, Malawi, Mali, Mozambique, Nigeria, South Africa, Sudan, Tunisia, Uganda and Zambia submitted data to GLASS. The main constraints listed are linked to scarce laboratory capacity and capability, limited staffing, budget issues, and data management. Moreover, while the data are not yet nationally representative, high resistance rates were reported to commonly-used antibiotics, as the emerging resistance to last treatment options.Despite the limitations, more and more countries in the African continent are working towards reaching a status that will enable them to report AMR data in a complete and systematic manner. Future improvements involve the expansion of routine surveillance capacity for several countries and the implementation of surveys that allow to effectively define the magnitude of AMR in the continent. This resistance can be inherent or acquired by the inappropriate use of medicines. Recent studies position AMR as a leading cause of death around the world, with the highest burdens in low-resource settings.2Antimicrobial resistance (AMR) is defined as ‘the presence of resistance to antimicrobial medicines in infectious agents such as bacteria, viruses, fungi and parasites’3 A 2017 systematic review from Tadesse et al.,4 documenting the status of AMR in Africa, found that ‘recent AMR data was not available for more than 40% of countries’. In countries for which data were available, ‘the level of resistance to commonly prescribed antibiotics was significant’, and that the ‘quality of microbiological data is of serious concern’.3Africa remains the continent most afflicted by infectious diseases and AMR can dramatically hamper treatment effectiveness and greatly amplify disease burden and its complications.5 Two reviews of AMR in sub-Saharan Africa and one review in East Africa also revealed ‘a high prevalence of AMR to commonly-used antibiotics in clinical bacterial isolates’.7 The studies also flagged the flaws in available data and the challenges faced in low- and lower middle-income countries when implementing AMR surveillance.A second systematic review, also published in 2017 and targeting West Africa, found AMR to be common in this subregion. It particularly occurred in hospitalised patients with bloodstream infections (BSI), and both outpatient and hospitalised patients with urinary tract infection (UTI).8In 2015, the World Health Organization (WHO) launched the Global Antimicrobial Resistance and Use Surveillance System (GLASS) to support strengthening of the AMR evidence base. As stated in the GLASS Report 2020, GLASS encourages countries to move to surveillance approaches based on systems that includes epidemiological, clinical, and population-level data, rather than only on laboratory data. In addition to data collection, GLASS promotes strengthening of national AMR surveillance systems to ensure that reliable and representative information is produced. It is supported by WHO Collaborating Centres Network, involving strong commitment from participating countries and close collaborations with WHO Headquarter, Regional and Country Offices.During the early implementation phase (2015–2019), GLASS focused on collecting information on the status of existing or newly developed national AMR surveillance systems and to provide a standardised approach to the collection of AMR rates for selected bacteria causing generic infections in humans. The first data call was opened in May 2017, and it recurs every year in the same period, between 1 May and 31 August.This article aims to describe the evolution of national AMR surveillance systems and AMR data reporting capacity of African countries participating in GLASS for the first three annual GLASS data calls (2017–2019), together with a summary of reported AMR rates for selected indicators. The article also describes, for a subset of African countries, the constraints, perceived impact, and value linked to reporting data to GLASS.Ethics approval was not required for this study. Each country has its own ethical approval for AMR surveillance and in many cases routine surveillance does not require ethical clearance.The GLASS database is the source of information of countries participation and reporting, implementation of the national surveillance system, and AMR rates. The data were submitted by counties during three data calls, between 2017 and 2019. The information on constraints and perceived impact and value in GLASS participation was collected though a set of questions sent via email to countries’ AMR National Focal Points (NFPs) and WHO Regional Offices’ staff in charge of AMR activities.The GLASS AMR data call is open yearly between May and August, and countries submit the information on the implementation of the national AMR surveillance systems for the data call year, and AMR rates for the previous year.In this article, key indicators on the implementation of the national surveillance system are summarised and presented to reflect changes during three data calls (2017–2019).7 GLASS collects information on the implementation of national AMR surveillance systems through a standardised questionnaire filled in every year by the NFP.As stated in the GLASS Report 2020,7A set of indicators is then used to measure the development and strengthening of national AMR surveillance:The establishment of a National Coordinating Centre and the National Reference Laboratory. These two bodies are in charge of data management and capacity building, and are key to the coordination of the national systems.Number of surveillance sites and local laboratories performing Antimicrobial Susceptibility Testing (AST) that report AMR data to GLASS. This information allows a better understanding of the structure and capacity of the national surveillance system structure. Surveillance sites can be hospitals, clinics, or in-and outpatient community healthcare facilities with access to relevant epidemiological and laboratory support and information.Provision of External Quality Assessment. This allows a better understanding of the diagnostic capacity of the surveillance system, by checking the provision of External Quality Assessment to the National Reference Laboratory and clinical local laboratories, and the use of international standards for diagnostics and AST.Acinetobacter spp., E. coli, K. pneumoniae, Salmonella spp., S. aureus and S. pneumoniae, UTIs caused by E. coli and K. pneumonia, gastrointestinal infections caused by Salmonella spp. and Shigella spp., and genital infections caused by N. gonorrhoeae. Data are generated by the collation of results from specimens that are routinely sent to laboratories for clinical testing and includes blood, urine, stool and cervical and urethral samples. The rationale for selection of these particular specimens is that the growth of a pathogen is a proxy of infection in the associated anatomical sites. The target population under surveillance is the national population of patients seeking care in HCFs. Data to be collected includes: ‘numbers of patients with susceptible, non-susceptible, intermediate, and resistant isolates, as well as numbers of isolates with unknown susceptibility.10 Two types of unknown results are recorded. The first, ‘unknown_no_AST’, is the number of isolates with AST results that were not reported (or not performed) for a specific antibiotic. The second, ‘unknown_no_breakpoints’, is the number of isolates for which AST was performed but which had no interpretation of results available for a specific antibiotic. Additionally, countries are invited to report patients’ microbiological results , as well as demographic and epidemiological variables such as age, gender, and origin of infection in tested patients, in aggregated format.8As stated in the GLASS Reports, GLASS requires AMR data to be collected through a surveillance system that gathers results from AST for common human bacterial pathogens in four infection sites, specifically BSIs caused by The distribution of infections and bacteria analysed and submitted to GLASS by countries during the three data calls (2017–2019) is summarised by year and shown in table format.Antimicrobial resistance rates: Proportions of patients with resistant infections reported by countries during three data calls are presented for:Escherichia coli and Klebsiella pneumoniae resistant to carbapenems and third-generation cephalosporins (3GC), and BSIs caused by methicillin-resistant Staphylococcus aureus (MRSA).Bloodstream infections caused by E. coli and K. pneumoniae resistant to carbapenems and ciprofloxacin.Urinary tract infection caused by countries reported] results for > 10 patients, and for pathogen–antibiotic combinations with > 10 AST results and < 30% unknown AST results’11.As aligned to the method outlines in the GLASS Report 2016–2017, ‘rates are shown only if ata aggregation is a major limitation, as it considerably limits options for epidemiological characterization, obviating the detection and validation of data from countries … with unusual antimicrobial patterns. Furthermore, … [l]ack of a sampling strategy results in selection bias, which may affect the representativeness and precision of results. Cases are found and tested only in the population that seeks medical care, … and most data are still generated in laboratories, with no epidemiological insight.[8 Finally, it was not possible to obtain feedback from all of the African countries participating in the GLASS data calls. However, responses showed a homogeneous consensus to the global system participation and the benefits associated to it.Antimicrobial susceptibility testing varied widely among countries for the specimen–pathogen–antibiotic combinations chosen. The numbers of patients screened for resistance were still very low, suggesting that most data come from complicated and hospitalised patients. Unfortunately, it was also not possible to show the frequency of AMR for these syndrome-pathogen–antibiotic combinations in the tested population, as the needed denominator – the population of the patient for which a diagnostic sample is taken – was not always available.Although some African countries listed in this article still face important constraints while building their national AMR surveillance systems, and even if not all of them have provided AMR data, countries have shown a willingness to share information with GLASS, particularly the status and the development of their surveillance systems. Countries on the continent are working towards reaching a status that will enable them to report data in a complete and systematic manner, through the establishment of surveillance core components and by assuring the quality of AMR diagnostics. Although reported data are still not representative at a national level, and AST varied considerably among countries, the participation in GLASS is clearly linked to improved national surveillance systems, which will also result in better clinical care in prescribing the appropriate antibiotics, one of the most challenging objectives of the Global Action Plan-AMR.Future improvements involve the expansion of routine surveillance capacity for several countries and the implementation of surveys that allow for effective definition of the magnitude of AMR on the continent. Meanwhile, the evidence generated is supporting the identification of areas for further research – AMR burden in healthcare settings, improvement of diagnostic stewardship, and AMR in the human animal environment interface – and it is advocating for the continuous support of actions directed to AMR monitoring and control.22Together with both national and regional partners, African countries’ participation in GLASS is leading the way towards the further development of an efficient and reliable global surveillance system, which will be able to function in various economic and socio-political contexts, and provide vital and actionable data. Addressing antimicrobial resistance through GLASS is part of the ongoing efforts of Member States to strengthen health security, improve health systems and ensure Universal Health Coverage.


Worldwide, come out and dissemination of extended-spectrum beta-lactamases (ESBLs) producing Enterobacteriaceae has been warning the efficacy of antibiotics to treat an infection. Hospital wastewaters were a reservoir of such kind of resistant bacteria. Currently, the predominant antibiotics used for the treatment of hospitalized patients infected by Gram-negative bacteria are the β-lactam antibiotics. Therefore, it is an important source to investigate the magnitude of ESBLs producing bacteria and their antimicrobial susceptibility pattern. This study aimed to determine the occurrence of ESBLs producing Enterobacteriaceae (ESBLs-pE) and their antibiotic susceptibility pattern in wastewater released from five governmental hospitals in Addis Ababa, Ethiopia.A cross-sectional study was conducted from April 1 to May 31, 2020. A total of 100 wastewaters were collected from five governmental hospitals in Addis Ababa using a grap-sampling technique. All Enterobacteriaceae were screened for ESBLs production using cefotaxime and ceftazidime as per 29th CLSI guideline. Each screen positive for ESBLs production was confirmed by the combination disk method (CDT) and their antibiotic susceptibility pattern was done using the Kirby–Bauer disk diffusion method on Muller Hinton agar (MHA). Data were entered and summarized using SPSS version 20 software.E. coli (21.8%) and K. pneumoniae (4.8%). The most elevated resistance level of ESBL producers were observed to cefotaxime (95.8%) and amoxicillin/clavunalate (93%). 64% of tested Enterobacteriaceae isolates were multi drug resistant (MDR).Of all Enterobacteriaceae, 48.3% were confirmed ESBLs-pE. The highest ratio of ESBLs-PE was observed in the adult ward (66.7%) and laundry unit effluent (58.8%). The highest ESBL producers were E.coli and K. pneumoniae. Hence, Consistent infection prevention and control procedures should be in practice at each ward/unit.Higher magnitude of MDR and ESBLs-pE were present in the hospital wastewater. The majority of them were in the adult ward and laundry unit effluents. The most frequent ESBLs-pE was among  Wastewater refers to water used by humans and loses its quality and usefulness that embrace waste liquid of domestic, agricultural, commercial sources, industries, and hospital sources. All these anthropogenic activities generates wastewater as a result of the physical, chemical, and biological quality of water deterioration . The effE. coli, K. pneumoniae, Enterobacter cloacae, Citrobacter freundii, and Proteus mirabilis. In patients hospitalized in intensive care units (ICUs), the Enterobacteriaceae holds for about one-third of all cases of ICU-acquired pneumonia, one-third of all cases of ICU-acquired urinary tract infection, and 10–15% of ICU-acquired bloodstream infections  [E. coli (94.8%)] [Enterobacter spp. (100%)]  , and in  (100%)] , where tIn the present study, of all Enterobacteriaceae 55.1% were suspected as potential ESBLs producing, and 87.7% of them were confirmed ESBLs producing isolates. A little comparable result was reported in Dubai, UAE by Khan et al. 2020: among all isolates from municipality wastewater 57.4% suspicious and 25.7% confirmed ESBLs producer Enterobacteriaceae were reported , in NortAccording to the present study, the overall magnitude of ESBLs-pE was 48.3% which is almost in line with a study conducted in Rio de Janeiro, Brazil , and NepE. coli (45.1%), K. pneumoniae (9.9%), and Citrobacter spp. (9.9%) that is comparable results to a study conducted in, Austria with E. coli (65.6%), and K. pneumoniae (22.6%) [E.coli (29.3%) [K. pneumoniae than E. coli or other Enterobacteriaceae spp. in other studies which contradict the present study. Hence, the predominant ESBLs-pE isolate in other studies were, in Addis Ababa; Citrobacter spp. (33.3%), K. pneumonia (33.3%), and E. coli (20%) [K. pneumoniae (42.10%), and E. coli (35.09%) [K. pneumonia (41.5%), and E. coli (12.2%) [Enterobacter spp. (60%), Citrobacter spp. (40%) and E. coli (25%) [In the current study, the highest percentage of ESBLs-pE was detected in  (22.6%)  and in I (29.3%) . Howeverli (20%) , in Norteumoniae .10%, and (12.2%) , and in li (25%) . This va. The highest within-species frequency of ESBLs production was recovered among M. morganii (75%) pursued by Salmonella spp. (66.7%) and K. ozaenae (62.5%), respectively. Meanwhile, least within-species ESBLs production was found in E. cloaca (21%). The difference of the occurrence of ESBLs producer between within ESBLs producer and species might be the variation of, the number of isolates recovered from the sample, and the isolate compared with (that is comparison within among ESBLs producer Enterobacteriaceae vs. within among each species).The occurrence of ESBLs producers differs strongly within different species of EnterobacteriaceaeIn the present study, of all MDR Enterobacteriaceae, 73.4% were ESBLs producer, whereas only 26.6% of them were non-ESBLs producer Enterobacteriaceae. The magnitude of ESBLs producing and MDR Enterobacteriaceae in the wastewater were different in the five hospitals. The highest occurrence of ESBLs-pE within the hospital according to CDT identification method were found in wastewater from the ALERT (67.9%), followed by TASH (52.4%) hospitals, whereas the least ESBLs-pE were detected in the MIIRH hospital (31.2%). In contrary; the elevated MDR isolates within hospital were observed in wastewater of TASH (76.2%) and ALERT (71.4%), while the lowest ratio was found MIIRH (53.1%). Like our study report, there were different ESBLs producer occurrence within country hospital effluent, in Ibadan, Nigeria: more ESBLs producer was found in a privately-owned hospital (33.3%) than a State Government-owned hospital (29.1%) , in EuroFrom all hospital wastewater collected for this study purpose, the highest ratio of ESBLs-pE within sampling unit was observed in adult ward effluent (66.7%) followed by laundry unit (58.8%), whereas the least proportion was recovered in pediatric ward (36.9%). Meanwhile, the elevated MDR isolates within sampling unit were identified in adult ward effluent (71.4%) pursued by laundry unit (70.6%), whereas they were the lowest ratio in pediatric ward effluent (52.6%).The majority of the preceding publication on antibiotic resistant profile of pathogenic microbes has been focused towards crude hospital wastewater rather than at each refined source of it. As a result, it was difficult to compare our result directly with other studies conducted from hospital wastewater, for example a study conducted in the hospital environment in Gondar, reported from an inanimate object of medical ward, surgical ward and Gyn-obs ward ESBLs-pE of 52.6%, 10.5% and 5.3%, respectively .p > 0.05) because of the majority of medical activity performed at the afternoon time and outpatients number increasing at the afternoon due to transportation and other reasons.In this study, the magnitude of MDR and ESBLs-pE obtained from all wastewater samples were higher in the afternoon (64.5% and 52.1%) than in the morning wastewater collected (59.2% and 47.9%). This difference may be happen , AMC (93%), cefepime (90.1%), and ceftazidime (87.3%). These were in close agreement with other study done in, Northwest Ethiopia; amoxicillin/clavulanic acid (100%) and ceftazidime (100%), Dubai, UAE; from municipality wastewater, cefotaxime (86%) and ceftazidime (77%) , AustriaIn this study, the most common higher co-resistant rates among the ESBLs-pE isolates were 74.6% for ciprofloxacin and 73.2% for SXT. Aminoglycoside and cephamycine antibiotic groups such as tobramycine (40.8%) and cefoxitine (29.6%) show reduced efficacy to the ESBLs-pE. Our result was comparable with other studies taken place, in Northwest Ethiopia; ciprofloxacin 43.9%), and trimethoprim/sulfamethoxazole (SXT) (64.9%) , in Aust.9%, and In our work, the most active drugs for ESBLs producing isolates observed are meropenem, nitrofurantoin, and piperacillin/tazobactam with susceptibility 94.4%, 88.7%, and 87.3%, respectively. The findings of this study concordance with prior reports conducted in Austria; meropenem (100%), and piperacillin/tazobactam (90.6%) had good susceptibility level .s Enterobacteriaceae were 63.2%, 43.4%, 31.6% and 23.7% resistant to amoxicillin/clavulanic acid, trimethoprim/sulfamethoxazole, ciprofloxacin and Cefoxitin, respectively. However, nitrofurantoin, chloramphenicol and meropenem showed the least resistant with 7.9%, 10.5 and 10.5%, respectively. We observed in the present study ESBLs producer isolates were more resistant to the tested antibiotics than non-ESBLs producer Enterobacteriaceae. This difference might be from the resistant gene on ESBLs producer, which also contributed the isolate to develop resistance to other antibiotics too.Non-ESBLs producerOur study tried to collect the wastewater at their utmost source, which enables to take preventive measures and at large sample size (in relative to the previous study) to be representative. This study conducted at different governmental higher hospitals to display the extent of distribution of MDR and ESBLs-pE in each hospital sampling units/sites.In this study only wastewater was used, hence it was unable to differentiate the source of resistant bacteria-either it was from clinical isolates or the sewage system.Our study was unable to select all antimicrobial agents commonly used for resistance evaluation due to the fact that some of them were not available during the period of study.The major limitation of the study was that ESBL detection was only performed phenotypically using CDT method, it was better to include a genotypic method of detection.Some sources of hospital wastewater were not incorporated in the study. Therefore, to generalize the distribution of MDR and ESBLs-pE in hospital wastewater, it was better to assess all sources of wastewater in selected hospitals.It would have a better figurative data if the study also included private hospitals, wastewater found in Addis Ababa and WWTP of the city.E. coli, K. pneumoniae and Citrobacter spp. In addition, ESBLs-pE showed high rate of resistance to all tested antibiotics as compared to non-ESBLs-E. This is a warning threat to such infection via contamination of food and water from rivers and urbane drainage which will be polluted through untreated hospital wastewater. Hence, infection prevention and control implementation at each hospital is mandatory.The hospital wastewater released directly into urban sewerage systems without appropriate disinfection or treatment is a serious environmental problem of the day. In this study, there was high magnitude of MDR & ESBLs-pE (≈ 65% vs. 50%) from the wastewater of selected governmental hospitals in Addis Ababa, Ethiopia. The majority of them were in the adult ward and the laundry unit effluents. In addition, the most frequent ESBLs-pE were One of the persistence concerns due to the existence of ESBL-producing bacteria in water bodies are related to the transmission of conjugative plasmids, which additionally carry genes resistant to sulfonamides and aminoglycosides, giving the bacteria multi-resistant patterns . This phDuring sample collection in this study, we noticed the selected hospitals had neither WWTP nor wastewater stabilization pond except in TASH, where a nonfunctional waste stabilization pond was observed. Since the present study detected a high proportion of pathogenic, resistant and ESBLs-pE, indicating a higher probability of potential risk of microbial pollution of water bodies in the community, hence accelerate spreading of resistant microorganisms into the community.The high occurrence of MDR and ESBLs-pE in the present study from hospital effluent may have a severe consequence on public health. These bacteria can carry several genetic determinants which can be transmitted to another bacterium, including pathogens. This indicates a need for a highly committed and consistently hygienic treatment of effluent  at each respective ward and units to inhibit the transmission of the antibiotic resistant to another enteric pathogenic bacterium. Since all selected hospitals for this study purpose didn’t have either wastewater treatment plant or a functional wastewater stabilization pond; therefore, every concerned body should take urgent measures to minimize the devastating outcome from the discharge of hospital wastewater into the community drainages without getting appropriate treatment. We suggest additional studies to take place on the molecular epidemiology of ESBLs producing Enterobacteriaceae and their effects on patient recovery and health care burden in Addis Ababa, Ethiopia.


For the development of atypical antipsychotics, the selective positive allosteric modulation of the ionotropic GABAA receptor (GABAAR) has emerged as a promising approach. In the presented research, two unrelated methods were used for the development of QSAR models for selective positive allosteric modulation of 1-containing GABAARs with derivatives of imidazo -pyridine. The development of conformation-independent QSAR models, based on descriptors derived from local molecular graph invariants and SMILES notation, was achieved with the Monte Carlo optimization method. From the vast pool of 0D, 1D, and 2D molecule descriptors, the GA-MLR method developed additional QSAR models. Various statistical methods were utilised for the determination of the developed models’ robustness, predictability, and overall quality, and according to the obtained results, all QSAR models are considered good. The molecular fragments that have a positive or negative impact on the studied activity were obtained from the studied molecules’ SMILES notations, and according to the obtained results, nine novel compounds were designed. The binding affinities to GABAAR of designed compounds were assessed with the application of molecular docking studies and the obtained results showed a high correlation with results obtained from QSAR modeling. To assess all designed molecules’ “drug-likeness”, their physicochemical descriptors were computed and utilised for the prediction of medicinal chemistry friendliness, pharmacokinetic properties, ADME parameters, and druglike nature. Of all the psychiatric illnesses, schizophrenia is recognised as one of the most serious. This is a complex, chronic mental disorder affecting approximately 1% of the world population. Illness symptoms range from delusions to hallucinations to disorganised thinking and impaired cognitive ability . The disAntipsychotic agents are necessary for the effective rehabilitation of most schizophrenia patients. Antipsychotics are the mainstay of pharmacological therapy, but they are associated with side effects that can cause disability . Gamma-aIn the drug discovery and development process, research time and financial aspects have a high impact. Both of these limiting factors could be highly influenced by the application of in silico methods since these methods accelerate research and reduce financing by discarding unfavourable molecules. For instance, quantitative structure-activity relationship (QSAR) studies are aimed at developing a mathematical model that can predict the studied activity for molecules that have not been synthesised and discarding molecules with undesired activity. Not only can in silico methods be used to predict studied activity, but also they could be used to predict and optimise pharmacological activity (or pharmacokinetic properties), key parameters for clinical approval ,12. The The main aim of the presented research was the development of QSAR models for positive allosteric modulation of the ionotropic GABAA receptor. Two approaches were used for this purpose: first based on the Monte Carlo optimization method and conformation−independent molecular descriptors , and second based on a genetic algorithm coupled with multiple linear regression and 0D, 1D, and 2D molecular descriptors, with further determination of molecular fragments or structural requirements responsible for allosteric modulation of the ionotropic GABAA receptor. For the “final validation” of the developed QSAR models and designed molecules’ allosteric modulation potential, molecular docking studies were used and the binding affinities to GABAAR of designed compounds were assessed.The literature provided a data set of 33 imidazo -pyridine derivatives as selective positive allosteric modulators of α1-containing GABAARs . The antMolecular descriptors derivated from both SMILES notation and molecular graph were used to develop conformation-independent QSAR models with the Monte Carlo optimization method as the main computer algorithm. Local graph invariants with the most elementary concepts like walks and paths were used as molecular graph-based descriptors and their detailed mathematical definition can be found in the literature . As optik, while symbols SSk and SSSk represent the linear combinations of two and three SMILES atoms, respectively. The global features of the studied molecule, defined with global SMILES notation, used in this research were: HARD, NOSP, BOND, HALO, and ATOMPAIR, all calculated according to the published methodology -pyridine heterocyclic system . The res21 investThe calculation example of a molecule’s summarized correlation weight (DCW) related to appropriate molecular fragment contribution on pKi is presented in In the process of computer−aided design (CAD), the results from conformational−independent studies, mostly related to defined molecular fragments, were used for the design of nine novel potential inhibitors, whose structures are presented in As a template molecule (A), one of the least chemically exploited molecules from the original dataset (molecule 3) was chosen. After examination of the molecules dataset, the observation was made that the phenyl group is the least chemically modified, so CAD was focused on the addition of simple aliphatic groups in ortho, meta, and para positions. Only molecular fragments with a positive impact on pKi were selected. Results for CAD molecules with calculated pKi are presented in In the three positions, molecular fragments that have a positive impact on pKi have been added and lead to an increase in pKi: “C..........”—a methyl group or simple carbon atom; “c..., the more active the ligand is (quantified as pKi). To assess this hypothesis and to evaluate developed QSAR models’ predictability and validate them further, molecule A and all designed molecules were subjected to molecular docking studies with α1-containing GABAAR. It has to be noted that the docking protocol used in this research was validated with an appropriate protocol. This protocol was RMSD based and for all molecules, where RMSD values for all studied molecules were compared to co−crystallized ligand (diazepam) and the obtained results were lower than 1.5, validating all docking poses. In The determination of physicochemical characteristics of studied molecules is one of the first steps in the early stages of drug development preferably done with the application of computational methods and for the purpose of determining whether new compounds have features that will classify them as potential therapeutics. To classify a molecule as drug-like, it has to possess the efficacy of binding to receptors/channels, oral bioavailability, gastrointestinal absorption, optimal bioavailability, good absorption/permeation, and brain penetration. All of these features could be predicted by knowing the molecule structure, so the molecule can be discarded from further development before it is synthesized. The computation of physicochemical descriptors as well as the prediction of medicinal chemistry friendliness, druglike nature, pharmacokinetic properties, and ADME parameters of designed molecules were computed with the SwissADME web service for the purpose of drug-likeness evaluation , and theThe main aim of this research was to develop robust QSAR models with good predictability, determined using numerous statistical parameters, for a selective positive allosteric modulation of 1-containing GABAARs. The Monte Carlo optimization method was used to calculate conformation-independent models, developed based on optimal descriptors derived both from a local graph and the SMILES notation invariants. A genetic algorithm coupled with multiple linear regression was used to obtain a QSAR model from the pool of vast 0D, 1D, and 2D molecule descriptors. The evaluation of the developed QSAR models’ robustness and predictive potential was executed by applying a range of statistical parameters, and their numerical values indicate that all developed QSAR models possess high predictability. The SMILES notation descriptors, defined as molecular fragments, with their influence on selective positive allosteric modulation of 1-containing GABAARs, were defined with the application of the Monte Carlo optimization method and are used for computer-aided design of novel compounds that have higher pKi values in comparison to starting template molecules. The binding preferences of designed molecules with amino acids from the active sites of 1-containing GABAARs were determined with the application of molecular docking studies. Molecular docking studies were used to calculate “scoring functions” related to binding energies that were used further to assess the effects on 1-containing GABAARs in regards to potential selective positive allosteric modulation. According to the obtained results, good inter-correlation can be observed between molecular docking studies and developed QSAR models regarding their potential selective positive allosteric modulation. Designed molecules’ physicochemical descriptors were computed to predict medicinal chemistry friendliness, pharmacokinetic properties, druglike nature, and ADME parameters, and according to the obtained results, all designed molecules possess high drug-likeness. Further, high bioavailability, including gastrointestinal absorption and brain access, of designed molecules was determined. Results presented in this research could be used in the search for novel antipsychotic agents for schizophrenia treatment whose main target activity is selective positive allosteric modulation of 1-containing GABAARs.


In this study, RE1st was assessed either by the 15N isotope method or by a zero‐N subplot freshly superimposed on a long‐term fertilised LTE treatment plot. RELT was calculated by comparing N uptake in the total aboveground crop biomass between a long‐term fertilised and long‐term control (zero‐N) treatment. Using a mixed linear effect model, the effects of climate, crop type, experiment duration, average N rate, and soil clay content on ∆RE were evaluated. Because the experimental setup required for the calculation of ∆RE is relatively rare, only nine suitable LTEs were found. Across these nine LTEs in Europe and North America, the mean ∆RE was 24.4%  of annual N application, with higher values for winter wheat than for maize. This result shows that fertiliser‐N retained in the soil and stubble may contribute substantially to crop N uptake in subsequent years. Our results suggest that an initial recovery of 43.8%  of N application may increase to around 66.0%  on average over time. Furthermore, we found that ∆RE was not clearly related to long‐term changes in topsoil total N stock. Our findings show that the—often used—first‐year recovery of synthetic fertiliser N application does not express the full effect of fertiliser application on crop nutrition. The fertiliser contribution to soil N supply should be accounted for when exploring future scenarios on N cycling, including crop N requirements and N balance schemes.Cumulative crop recovery of synthetic fertiliser nitrogen (N) over several cropping seasons (legacy effect) generally receives limited attention. The increment in crop N uptake after the first‐season uptake from fertiliser can be expressed as a fraction (∆RE) of the annual N application rate. This study aims to quantify ∆RE using data from nine long‐term experiments (LTEs). As such, ∆RE is the difference between first season (RENine long‐term cereal experiments in Europe and USA were analysed for long‐term crop N recovery of synthetic N fertiliser.On average, and with application rates between 34 and 269 kg N/ha, crop N recovery increased from 43.8% in the first season to 66.0% in the long term.Delta recovery was larger for winter wheat than maize.Observed increases in crop N uptake were not explained by proportionate increases in topsoil total N stock. Relatively few studies have aimed at quantifying the long‐term effect of synthetic fertiliser N on soil N and crop N uptake, although the need has been recognised . While multiple‐year effects on soil N supply remain scarcely documented for synthetic N fertilisers, several estimations have been made in the UK based on trials with y et al.  calculatLTE's can be used to quantify long‐term apparent fertiliser N recovery, by comparing annual crop N uptake in plots that did or did not receive fertiliser N for many years. Long‐term recovery thereby accounts for both the continuous depletion—in the absence of fertiliser inputs—of initial soil N stock, and the possible build‐up of soil N under a regime of fertiliser input. Long‐term N response curves, therefore, show steeper yield responses to N (at low and moderate N rates) than curves from the 1‐year trials typically used to inform fertiliser recommendation systems , a long‐term increase in N recovery was observed between 1970 and 2016 Figure . HoweverOther long‐term studies assessed the residual effect of historically applied N on current crop N uptake after changing N application rates  between short‐term recovery (RE1st) and long‐term recovery (RELT) of fertiliser N in the aboveground crop biomass. We applied this method to a number of suitable cereal‐based LTEs. We hypothesized that the long‐term recovery of applied synthetic N is larger than the first‐season recovery and that this difference would be mediated by factors, including climate, crop type, experiment duration, average N application, soil clay content, calculation method for RE1st, and crop residue management.In this study, we present a new analysis of the legacy effect of synthetic fertiliser N application, that borrows elements from the above‐cited studies. The objective of this study is to quantify the contribution of synthetic fertiliser N to soil N supply by evaluating the difference  either a 15N or a new control (PK) subplot superimposed on the long‐term N‐fertilised plot is present to allow quantifying RE1st. Using the search terms ‘Long‐term’ and ‘Cereal’ and ‘15N’ and/or ‘subplot’ in Google Scholar and Web of Science, five useful experiments were selected. Another experiment was obtained from the CATCH‐C database which contains data from over 300 LTEs in Europe  at least one long‐term fertilised (NPK) and one long‐term unfertilised control (PK) plot should be present to quantify RE2.2∆RE were located in Europe and North America  was defined as the fraction of annually applied fertiliser N recovered in the aboveground crop biomass. It includes recovery of fertiliser‐N applied in the current season, as well as recovery of previously applied fertiliser N, via uptake of fertiliser‐derived soil N built up in previous seasons. It is expressed as a fraction of the annual application rate. RELT was calculated based on LTEs where fixed levels of synthetic fertiliser N were maintained over many years  and potassium (K) application at the same rate as the fertilised plot. As this method takes a zero‐N treatment as a reference, it should be referred to as ‘long‐term apparent recovery’ (as opposed to labelled N recovery), but the term ‘apparent’ is omitted for brevity in the remainder of the text.UN,LT, annual N uptake from the long‐term fertilised plot (kg N/ha). U0N,LT, annual N uptake from the long‐term non‐fertilised (control) plot (kg N/ha). N rate, amount of N applied annually (kg N/ha) to the long‐term fertilised plot.The long‐term N recovery fraction  introduction of an 0 N subplot  are to be continued unamended during the trial superimposed for the estimation of RE1st.Within the long‐term trial fields, two types of superimposed short‐term experiments were considered suitable to calculate RE2.4.11st by subtracting measured N uptake in the control subplot from the N uptake in the long‐term main plot and dividing by the long‐term N application rate . U0N,ST, N uptake from short‐term non‐fertilised (control) subplot (kg/ha), that is, where the historic long‐term N rate was discontinued in the year of observation. N rate, amount of N applied annually (kg N/ha) to the long‐term fertilised plot (as in Equation Experiments with a newly introduced control subplot (only receiving PK application without synthetic N fertiliser), enable the calculation of REEquation .(2)RE12.4.21st from observations of first‐season 15N recovery from fertiliser labelled with the 15N isotope  undergo chemical and biological transformations in the same manner. The 15N taken up by the crop was divided by the amount of 15N applied:U15N, 15N uptake (kg/ha/year). 15N application rate (kg N/ha/year).Alternatively, most of the LTEs allowed the calculation of RE2.5∆RE), was introduced to express the legacy effect of long‐term synthetic N application on crop N uptake. We define ∆RE as the difference between first season N recovery (RE1st) and long‐term N recovery (RELT) in above‐ground crop biomass, both measured in the same year.The main response variable in this analysis, delta recovery (1st) refers to the fraction of N taken up from fertiliser in the year of application , in contrast, also includes uptake of N applied in earlier years . Cereal crops  were the main focus of this study because these are the crops most commonly grown in long‐term studies.As explained, first season N recovery  is larger than the number of LTEs (11), because data from multiple years, crop types and N application rates were available for some of the LTEs  affected ∆RE was tested. This comparison was performed both on the whole dataset, but also separately on a subset of the experiments where both methods were used. The latter gives the most straightforward comparison but can be applied to a few LTEs only. As this selection reduced the sample size and the other analyses were performed using all data points, the type of method was also added as an explanatory variable for ∆RE using a mixed‐effects model from the nlme package in R  and 66.0%  of annual N application rate, respectively. For four observations, RELT exceeded 100%, meaning that the increment in N uptake (over the control treatment) was larger than the amount of N applied. Such points were retained in the overall analysis. Across all data‐points, mean ∆RE was 24.4%  of the annual N application rate.In 61 out of 66 cases, REt Figure . Mean RE3.2p = 0.002). ∆RE did not significantly differ from the other crop types. Soil clay percentage was included as a predictive variable for ∆RE in the second‐best model. However, the estimated slope of 1.07% of the annual N application rate per percent clay content was not significant (p = 0.45) when included as a sole variable. The effect of clay content on RELT seemed more evident but was not significant  was observed between retention and removal of crop residues. Crop residues were retained at two of the nine LTEs.No severe collinearity was observed between the co‐variables included in the full model , we also selected a subset of experiments with a duration between 5 and 21 years. In this period, no significant effect of duration could be found either (p = 0.399).Including experiment duration and level of N application did not improve the AICc–value of any linear mixed effect model used to explain variation in ∆RE Table . When as1st (15N or Subplot method) was included as an explanatory variable in the best model when using data from all experiments . However, when removing one outlier, the 15N method showed a significantly higher ∆RE than the Subplot method (p = 0.008). The difference between both methods amounted to a 7.4% recovery of annual N application, caused by lower RE1st values from 15N treatments compared to the Subplot treatments.The type of method to assess REs Figure . In the p = 0.41).In three out of nine experiments, total soil N data were available. Topsoil total soil N was, on average, 10% higher on fertilised plots compared to the control plots. N uptake from the soil in the fertilised plots, by contrast, increased by 86% on average, relative to unfertilised control Figure . There w44.11st. We therefore also assessed the legacy effect as a fraction of (1 − RE1st), rather than as a fraction of the N rate. However, expressing the legacy effect in this manner yielded no additional insights, as equally so, no correlations were found with explanatory variables . Moreover, in practical cases, RE1st is often unknown beforehand. Expressing ∆RE as a fraction of N application, therefore, has much more practical value. We do recognise, however, that in a true equilibrium state the sum of RE1st and ∆RE cannot exceed 1 in situations where crop residues are removed from the field (as in most LTEs here).Our results show a consistently positive ∆RE, which indicates that N originating from earlier synthetic fertiliser applications contributes to crop N uptake in years after its application. Based on our data set, the mean legacy effect of synthetic N fertiliser application (∆RE) was 24.4%  of the annual N application rate. Figure 15N studies which followed the fate of a single synthetic 15N application over multiple years  over several years, it does not allow quantification of the cumulative effect on crop N recovery of maintaining a fixed N rate over many years. Jenkinson et al. Glendining et al.  also fouIn our study, weighting was used to give more importance to observations that were based on more replicates. However, weighting can also result in a bias towards those agro‐ecological conditions for which a higher number of replicates happened to be available. Nonetheless, the estimated mean ∆RE only increased marginally (0.5%‐point) when excluding weights in the mixed‐effects model. Furthermore, the model selection results did not change when weights were excluded.4.21st calculation method were the most important factors governing ∆RE, based on the model selection results. Winter wheat showed a significantly larger ∆RE than maize  was found to affect ∆RE. However, this was only significant within the subset of experiments where both 15N and the Subplot method were available to calculate RE1st, and only so when one outlier datapoint was removed.Crop type, soil clay content, crop residue retention and REe Figure , possible Figure . Two oute Figure . Howevery Figure . Retaini15N experiments are known to underestimate RE1st . Underestimation of RE1st could be caused by phenomena collectively referred to as ‘added nitrogen interactions’ (ANI). This includes pool substitution: labelled N replacing unlabelled N that would otherwise have been immobilised, leaving more unlabelled N available for plant uptake, and so causes overestimation of the contribution of soil‐N to crop N uptake . A likely explanation is that contributions to crop uptake from remineralized N diminish over time, so the increase in ∆RE from later years will become progressively smaller.Somewhat surprisingly, the duration of the experiments did not affect ∆RE. A possible caveat is the lack of data points in this study with an experimental duration between around 20 and 80 years Figure . When daN = 66, based on nine LTEs). As discussed, the limited size of our data pool, and especially the limited number of experiments included, may have caused the lack in observed correlations between co‐variables and ∆RE, for example for the experimental duration. Moreover, the prevalence of co‐variables in our dataset did not have a balanced distribution. For example, in contrast to winter wheat, there are no observations for maize with an experimental duration of over 26 years , N yield response curves based on long‐term trials show steeper slopes than those based on short‐term trials. As also argued by Van Grinsven et al. ; Data curation ; formal analysis ; methodology ; writing – original draft ; writing – review and editing . Renske Hijbeek: Conceptualization ; formal analysis ; methodology ; supervision ; writing – review and editing . Margaret J. Glendining: Data curation ; writing – review and editing . David S. Powlson: Data curation ; writing – review and editing . Anne Bhogal: Data curation ; writing – review and editing . Ines Merbach: Data curation ; writing – review and editing . João Vasco Silva: Data curation ; writing – review and editing . Hanna J. Poffenbarger: Data curation ; writing – review and editing . Jagman Dhillon: Data curation ; writing – review and editing . Klaus Sieling: Data curation ; writing – review and editing . Hein F. M. ten Berge: Conceptualization ; methodology ; supervision ; writing – review and editing .The authors declare no potential conflict of interest.Data S1. Supporting Information.Click here for additional data file.