Meloidogyne incognita is one of the most important nematodes affecting ginger crop. Rhodopseudomonas palustris PSB-06, as effective microbial fertilizer in increasing plant growth and suppressing soil-borne disease of many crops has been reported. The combination of R. palustris PSB-06 and dazomet treatments had been proved to inhibit root-knot nematode on ginger and increase ginger yield in our preliminary study. The field experiments were conducted to elucidate the reasons behind this finding, and followed by next-generation sequencing to determine the microbial population structures in ginger root rhizosphere. The results showed that combination of R. palustris PSB-06 and dazomet treatment had a synergetic effect by achieving of 80.00% reduction in root-knot nematode numbers less than soil without treatment, and also could increase 37.37% of ginger yield through increasing the contents of chlorophyll and total protein in ginger leaves. Microbiota composition and alpha diversity varied with treatments and growth stages, soil bacterial diversity rapidly increased after planting ginger. In addition, the combined treatment could increase diversity and community composition of probiotic bacteria, and decrease those of soil-borne pathogenic fungi comparing to the soil treated with dazomet alone. Meanwhile, it could also effectively increase soil organic matter, available phosphorus and available potassium. Analysis of correlation between soil microorganisms and physicochemical properties indicated that the soil pH value and available phosphorus content were important factors that could affect soil microorganisms structure at the harvest stage. The bacterial family was more closely correlated with the soil physicochemical properties than the fungal family. Therefore, the combination of R. palustris PSB-06 and dazomet was considered as an effective method to control root-knot nematode disease and improve ginger soil conditions.Root-knot nematode,  Zingiber officinale Roscoe) is a spiced vegetable and a dietary supplement traded worldwide (Meloidogyne spp.) are one of the most economically important plant-parasitic nematodes genera infecting more than 3,000 plant species, especially vegetables  is a soil fumigant for many soil-borne pathogens and nematodes, it had been widely used to control soil-borne diseases in China, which had not only excellent control effect on neither nor soil-borne bacterial and fungal pathogens, but also plant parasitic nematodes . The dazBacillus spp., Pseudomonas spp., photosynthetic bacteria, Trichoderma spp., had strong antagonistic effects to plant pathogens, and had been used to control plant pathogenic microorganisms  was from in the Key Laboratory of Integrated Management of the Pests and Diseases on Horticultural Crops in Hunan Province, Hunan Academy of Agricultural Science (HAAS). R. palustris PSB-06 was used at the concentration of 107 cfu/g. Dazomet (CAS No. 533-74-4) was purchased from the Taian Jiangzhou Biotechnology Co., Ltd.  and used to fumigate soil.Ginger used in this study was a local crop that had been widely grown in this area. Photosynthetic bacterial agent M. incognita) seriously affects the quality and yield of ginger. The size of the experimental field was about 1,334 m2. A randomized block design with five replicates was used and each replicate contained six plots (16 m × 0.7 m each). Four treatments were: (1) R. palustris PSB-06 (5 kg/667 m2) treatment after soil fumigation with dazomet (20 kg/667 m2) (T1), the R. palustris PSB06 was applied to ginger root with irrigation on the April 18th (Germination stage), July 11th (Seedling stage) and September 8th (Vigorous growth stage), 2020, (2) soil fumigation with dazomet (20 kg/667 m2) (T2), (3) R. palustris PSB-06 (5 kg/667 m2) treatment (T3), the used method and times were the same as T1, and (4) soil without treatment . Soil fumigation with dazomet was conducted from November 25th, 2019 to March 3rd, 2020, because these fields were only planted to ginger which had high economic benefits, and the growing period of ginger was from April 18th to October 14th, 2020. Experimental field soil was prepared using a rotary cultivator and the ginger planting spacing is 18–20 cm. Three protection lines were used for each treatment to keep consistent environmental conditions for individual treatments.Field experiment was performed at the Laiwu distract, Jinan City, Shandong Province, China , according to the field experiment results obtained in 2019. In this distract, continuous cropping of ginger was a common phenomenon and root-knot nematode (The soil samples (about 600 g each) were collected, using a five-spot sampling method, from the four different treatments, and each sampling spot contained three locations or three plants. The samples were collected on April 18th (Germination stage), July 11th (Seedling stage), September 8th (Vigorous growth stage) and October 14th (Harvest stage), 2020. The soil samples collected from the same replicate plot were mixed as one composite sample and each mixed soil sample was divided into two parts and placed in two plastic bags (100 g each). The plastic bags were transported in a 4°C cooler to the laboratory for further analysis. Then one kind of soil samples was used to extract root-knot nematodes, the other soil samples were used to analyze soil microbial diversity and physicochemical property.M. incognita second-stage juveniles (J2s) in each sample was determined under an inverted microscope. The root-knot nematode index and the control effect were analyzed after gingers were harvested on the October 14th, 2020. Root gall severity was assessed using a 0–5 grades accorfing to the percentage of galled roots  as described previously (Nematodes were extracted from collected soil samples (100 g each) using the Baermann funnel method , soil saeviously . Gall inGinger plant height and tiller number, and leaf physiological activity index, including total chlorophyll, a content, b content, total protein, catalase (CAT) activity, malondialdehyde (MDA) content, peroxidase (POD) activity, and total superoxide dismutase (T-SOD) activity were analyzed using the samples collected at the seedling, vigorous growth, and harvest stages, respectively. For leaf physiological activity index analysis, the samples were prepared using commercial kits as instructed by the manufacturer . The main stem perimeter, main stem leaf number, the width of ginger, ginger number per plant, ginger yield per plant, and shoot weight per plant were analyzed after the gingers were harvested on the October 14th, 2020.A 2 g soil was taken from each collected soil subsamples and placed in a 2 ml sterile eppendorf tube. The tubes were frozen in liquid nitrogen and then, stored at −80°C prior to DNA extraction. Total DNA was extracted from individual frozen soil samples using a Fast DNA SPIN Kit as instructed . The quality and quantity of each total DNA sample were assessed using a NanoDrop2000c spectrophotometer . The integrity of each total DNA sample was checked in 1% agarose gels through electrophoresis. The primers used to amplify the V3–V4 region in the bacterial 16S rRNA gene or the fungal ITS1 region, and other PCR amplifications were prepared as described previously . The bacAll experiments were performed with five biological replicates. Statistical analyzes of ginger growth indices and disease severities were performed using the Analysis of Variance (ANOVA) and the SPSS 13.0 statistical software package . The statistical significance among the treatments was determined using the Duncan’s Multiple Range Test (DMRT) at the 5% level. The bioinformatics analysis of this study was performed with the aid of the BMK Cloud,p > 0.05). The sizes of J2s populations in these four treatments soil samples were then, significantly increased at the vigorous growth and harvest stages. However, the sizes of J2s population in the T1 treatment soil were significantly lower than those in the T2, T3, and T4 treatments soils at the vigorous growth stage  than those in the T2 and T3 treatments soils at the harvest stage (p < 0.05). The control effect of the T1 treatment was 80.00 ± 10.18%, significantly higher than those of the T2 (46.67 ± 13.33%) and T3 (40.00 ± 15.56%) treatments  than those of the T4 treatment (p > 0.05). The number of main stem leaves and the ginger number per plant were similar among the four treatments at the harvest stage. Whereas, the fresh shoot weight and main stem perimeter of the plants collected from the T3 treatment were significantly greater (p < 0.05) than that of the plants collected from the T4 treatment, but were similar to that of the plants collected from the T1 and T2 treatments.The plant height, tiller number, main stem perimeter, yield of ginger and the ginger ball width collected from the T1 treatment at the harvest stage were significantly greater (reatment . It was p > 0.05) were observed on the total chlorophyll and protein contents in the leaf samples collected from the T2 and T4 treatments at the three growth stages. The chlorophyll a and b in the leaf samples showed that their changes in them in the leaf samples were similar to that observed for the total chlorophyll contents  were observed of the CAT activities in the leaf samples collected from the four treatments at the three growth stages (p > 0.05) in four treatments (p < 0.05) than T4 treatment, and the T-SOD activities in the leaf samples collected from the T2 and T4 treatments were significantly lower (p < 0.05) than T1 and T3 treatments  of the top 16 common bacterial and 11 common fungal families from different developmental stages were shown in p < 0.05) among the four treatments at the harvest stage, but only 5 fungal families showing significant differences (p < 0.05) among the four treatments. In results in p < 0.05) than T4 treatments at the four growth stages. At the germination and harvest stages, the relative abundances of Burkholderiaceae and Xanthobacteraceae had significant differences (p < 0.05) among the four treatments. At the vigorous growth and harvest stages, the relative abundances of uncultured bacterium Gaiellales, Gemmatimonadaceae and Sphingomonadaceae had significant differences (p < 0.05) among the four treatments. For the fungal families, the relative abundances of Chaetomiaceae, Mortierellaceae and Nectriaceae was significant difference (p < 0.05) among the four treatments at the germination stage, no significant statistical differences (p > 0.05) at the harvest stage, but the Mortierellaceae showed significant difference (p < 0.05) at the harvest stage. The results of top 20 bacteria and fungi at the genus level showed that the dominant genera were different in the different treatments  as the growth stage progressed, especially in soils without dazomet treatment. Application of R. palustris PSB-06 (T1 and T3) had a considerable rise in bacterial diversity than the other treatments, no significant statistical differences (p > 0.05) were observed among the samples collected at the seedling, vigorous growth, and harvest stages. The fungal diversities significantly increased (p < 0.05) at the seedling stage, but it has a considerable decline at vigorous growth stage and considerable rise at the harvest stage again. The fungal diversity at the harvest stage was greater than those found in the samples collected at the other three growth stages, the highest Shannon and Simpson indices were all found in the T3 treatment sample collected at the harvest stage, and no significant statistical differences (p > 0.05) were observed among the samples. The full details of Shannon and Simpson indices in different growth stages or treatments were shown in the Result S5 in Microbial alpha diversity varied widely among different treatments and growth stages. For microbial-community structure, the Shannon and Simpson indices indicated the bacterial and fungal communities significantly differed among different treatments . The bacBacillus spp., and Paenibacillus spp. in the T1 and T3 treatment samples were greater than that of the T2 and T4 treatment samples at different growth stages , indicating that Dependentiae, Patescibacteria and Rokubacteria were closely correlated with the levels of soil pH value and available phosphorus (p < 0.01) were observed between the available phosphorus and Basidiomycota, Mucoromycota or Ascomycota, and the pH value and Mucoromycota  and non-MetricMulti-Dimensional Scaling (NMDS) results indicated that the bacterial and fungal populations in the T4 treatment sample were all clearly different from those of the other three treatment samples . The disosphorus . The RDAosphorus . Signifiromycota , indicatp < 0.05) at the harvest stages were also used to analyze the correlation with physicochemical properties of ginger soil (p < 0.01) were found between the bacterial family and the soil physicochemical properties (p < 0.01), indicating that the bacterial family and the soil physicochemical properties were closely correlated. The correlation between the fungal family and the soil physicochemical properties showed that significant negative correlations (p < 0.05) were only found between Aspergillaceae and the available phosphorus, indicating that the fungal family and the soil physicochemical properties were not closely correlated compared with the bacterial family  and blank control (T4), respectively. The total of chlorophyll and protein contents in the ginger leaves collected from the R. palustris PSB-06 treatments (T1 and T3) were all greater than the other treatments at the different growth stages. They indicated that R. palustris PSB-06 had positive effect on the content of chlorophyll and total protein in the ginger leaves and there appeared a strong possibility that increasing ginger yields were caused by increasing chlorophyll and total protein contents to enhance photosynthetic activities. The previous studies also showed that R. palustris PSB-06 could promote plant growth , or might had antagonistic effect on root-knot nematode. Therefore, it was necessary to apply R. palustris PSB-06 after soil dazomet fumigation in field.In our study, the combination of The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/FC, YL, and DW: designed the experiments. DW, JW, PS, and JD: performed the experiments. DW, XT, and DZ: analyzed the data. DW, FC, and YL: wrote the manuscript. All authors read and approved the final version of the manuscript.This work was supported by National Natural Science Foundation of China (no. 31871941), Natural Science Foundation of Hunan Province (no. 2022JJ40235), Changsha Municipal Natural Science Foundation (no. Kq2014177), and Shaanxi Key Laboratory of Plant Nematology (no. 2021-SKL-02).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.


Salmonella (0%–0.4%), Aeromonas (19%–26%), Vibrio (7%–43%), Pseudomonas aeruginosa (0.8%–2.3%), Staphylococcus (23%–30%), and Enterococcus (39%–66%). Shrimp had the highest odds  of being contaminated with at least one species of these bacteria, as were seafood sourced from Asia vs. North America  and Latin America and the Caribbean vs. North America  and seafood sold at the counter vs. sold frozen . Isolates exhibited pan-susceptibility  or low prevalence of resistance (<10%) to most antimicrobials tested, with few exceptions. Seafood marketed as farm-raised had lower odds of contamination with antimicrobial resistant bacteria compared to wild-caught seafood . Antimicrobial resistance genes (ARGs) were detected for various classes of medically important antimicrobials. Clinically relevant ARGs included carbapenemases  and extended spectrum β-lactamases . This population-scale study of AMR in seafood sold in the United States provided the basis for NARMS seafood monitoring, which began in 2020.In 2019, the United States National Antimicrobial Resistance Monitoring System (NARMS) surveyed raw salmon, shrimp, and tilapia from retail grocery outlets in eight states to assess the prevalence of bacterial contamination and antimicrobial resistance (AMR) in the isolates. Prevalence of the targeted bacterial genera ranged among the commodities:  The prevalence of seafood contamination with resistant bacteria was low.blaIMI-2, blaNDM-1) and ESBLs (blaCTX-M-55) were found in imported seafood.Carbapenemases  and chicken , followed by salmon (3.1 pounds per capita), canned tuna (2.2 pounds per capita), Alaska pollock (0.996 pounds per capita), and tilapia  and both spoilage-related and naturally occurring aquatic bacteria  that were known to have sufficiently high prevalence in fish and shellfish  and shrimp (n = 710) were purchased from supermarkets in participating NARMS sites: California, Georgia, Kansas, Missouri, New York, Pennsylvania, South Carolina, and South Dakota. Seafood was collected as fresh, frozen, or previously frozen raw samples. Tilapia (n = 214) also was collected from supermarkets in the above states (except for Pennsylvania) between September and December of 2019. A sample was defined as the unit that was purchased, and may have varied by purchase. For example sometimes a one pound bag of peeled frozen shrimp may have been purchased and other times a quarter pound of individual head-on-tail-on shrimp were purchased. Country of origin, raising claims (antibiotic use vs. organic and farm-raised vs. wild-caught), meat cut, and salmon variety were recorded for all samples, where applicable. Participating laboratories performed sample collection and preparation, and bacterial isolation.Between January and December of 2019, samples of salmon , 225 ml lactose broth , or 225 ml Buffered Peptone Water  in a sterile stomacher bag and stomached or blended for 2 min, followed by incubation at 35°C for 24 h. Unless otherwise noted, the enriched mixture (1 μl) was streaked onto agar plates described below.A 25 gram portion of each seafood sample was aliquoted with 225 ml of Alkaline Peptone Water  and incubated at 35°C for 18–24 h. Presumptive Vibrio characteristically appeared as green or yellow colonies. If more than one color appeared, one of each colored colony was selected. For Salmonella, 0.1 ml of lactose broth enrichment was transferred to 10 ml Rappaport-Vassiliadis (RVR10) medium (BD Difco™) and incubated at 42°C for 24 h. Each RVR10 culture was streaked to one XLT-4  and one HE agar  and incubated at 35°C for 24 h. One typical colony was selected per agar for further testing. For P. aeruginosa, BPW enrichments were streaked to either Pseudomonas Isolation Agar  or MacConkey agar  and plates were incubated at 35°C for 18–48 h. Pseudomonas spp. appeared as colorless colonies on MAC and presumptive P. aeruginosa characteristically appeared as green/blue–green colonies on PIA. One colony was selected per sample. For Enterococcus, BPW enrichments were streaked to Enterococcosel agar  or Mannitol Salt Agar  and incubated for 48 h at 35°C. One colony was selected from each sample. Staphylococcus were also isolated from MSA. After streaking with BPW enrichments, plates were incubated for 24 h at 35°C. One colony was selected per sample. For isolation of Aeromonas Cefsulodin-Irgasan-Novobiocin (CIN) agar  was incubated for 24–48 h at 25°C. Presumptive Aeromonas colonies had a pale colonies with rose red centers. One colony was selected per sample. Isolation of CRO bacteria was performed by streaking BPW enrichments onto mSuperCarba CHROMagar™  and incubating at 35°C–37°C for 18–24 h. One colony of each color (up to five from each sample) was picked. According to the package insert, the typical appearance of carbapenemase producing microorganisms is dark pink to red (E.coli), metallic blue (Coliforms), translucent, +/− natural pigmentation cream to green (Pseudomonas), Cream (Acinetobacter), colorless, natural pigmentation (other Gram-negative organisms). For all targeted bacteria, presumptive isolates were picked from their respective selective media, streaked to blood agar plates  and incubated at 35°C for 24 h. If growth was pure, colonies were swabbed to Brucella broth (BD Difco™) with 15% glycerol mixture, frozen at −60°C to −80°C, and shipped to the United States Food and Drug Administration (FDA) Center for Veterinary Medicine (CVM) for additional analyses.All samples were tested for ® 2 Compact , except for isolates grown on mSuperCarba CHROMagar™. Only a subset of presumptive mSuperCarba CHROMagar™ isolates (N = 952) were confirmed on the VITEK® 2 Compact.At FDA, all bacterial isolates received were confirmed using the VITEKSalmonella spp., P. aeruginosa, Vibrio spp., Staphylococcus spp., Enterococcus, and Aeromonas spp. isolates were tested for susceptibility to antimicrobials approved for use in aquaculture in the United States as well as other antimicrobial classes that may be used in other countries. Testing was performed at FDA CVM via the broth microdilution assay  using methods recommended by the Clinical and Laboratory Standards Institute . All 3 Salmonella and 20 P. aeruginosa underwent antimicrobial susceptibility testing (AST). Due to the large number of isolates recovered, a random subset of 179 Aeromonas isolates underwent AST. To examine associations between sample-based variables  and isolate-based variables  as described below, only one Vibrio isolate per positive sample was selected for AST. Of the selected isolates, all isolates from the following species were subjected to AST: V. parahaemolyticus (n = 91), V. cholerae (n = 30), and V. vulnificus (n = 1); and we tested a random subset of isolates of each species: V. metschnikovii (n = 53), V. fluvialis (n = 27), V. alginolyticus (n = 5) and mixed populations (n = 3). The antimicrobial classes tested on both panels were: aminoglycosides (gentamicin), β-lactam combination agents (amoxicillin-clavulanic acid), carbapenems (meropenem), cephems , folate pathway inhibitors (sulfisoxazole and trimethoprim-sulfamethoxazole), macrolides (azithromycin), penicillins (ampicillin), phenicols (chloramphenicol), quinolones , and tetracyclines (tetracycline). Isolates tested on the Sensititre™ CMV5AGNF panel were also tested against lipopeptides (colistin).te CLSI; , 2019. GEnterococcus and 210 Staphylococcus isolates on the NARMS Gram-positive antimicrobial panel  that included the following antimicrobial classes and drugs: aminoglycosides , glycopeptides (vancomycin), glycylcyclines (tigecycline), lipopeptides (daptomycin), macrolides (erythromycin), nitrofurans (nitrofurantoin), orthosomycins (avilamycin), oxazolidones (linezolid), penicillins (ampicillin), phenicols (chloramphenicol), streptogramins , quinolones (ciprofloxacin), and tetracyclines (tetracycline).We tested 385 Salmonella (interpreted as resistant if MIC ≥ 32 μg/ml) and tigecycline against Enterococcus  values was based on the CLSI clinical breakpoints for human infection treatment, when available , 2019. OSalmonella were sequenced. Of the other targeted genera , we performed WGS only on a subset of the isolates with resistance to at least one antimicrobial. Altogether, 370 isolates were sequenced including 3 Salmonella, 16 Aeromonas, 2 Enterococcus, 6 P. aeruginosa, 11 Staphylococcus, 44 Vibrio and 288 presumptive CRO. Isolates were sequenced on Illumina MiSeq™ using v3 reagent kits  with 2 × 300 bp paired-end reads. The libraries were prepared with Nextera XT kit by Illumina, and raw sequences were assembled de novo using CLC Genomic Workbench (version 10.0). ARGs were identified in the assembled genomes with AMRFinder Plus 3.8 software.® identification and when they differed, the WGS speciation was chosen for all analysis. If bacterial genera could not be resolved through in silico methods, VITEK® identification was used.A subset of presumptive CRO was randomly selected for whole genome sequencing (WGS) and all The percent of samples that tested positive was calculated by dividing the number of samples that yielded the bacterial genera or species by the total number of samples of the seafood commodity collected.The percent phenotypically resistant was calculated by dividing the number of isolates with the antimicrobial MIC at or above the CLSI clinical breakpoint for human infection treatment or the NARMS cutoff interpretive criterion by the total number of isolates of that bacterial species tested against that antimicrobial. Percent resistance was only calculated for antimicrobials with CLSI breakpoints or NARMS interpretive criteria. Isolates resistant to at least three classes of antimicrobials were considered multidrug resistant.Aeromonas, Salmonella, Staphylococcus, Enterococcus, P. aeruginosa, or Vibrio), or (2) contamination of a sample with an antimicrobial resistant isolate of the target bacterial genera . In the first set of models, commodity was included as a predictor, but commodity specific variables  were excluded. In the second set of models, multivariable regression was performed for each commodity. For both sets of models the following procedures were followed: Variables were first screened with a univariate analysis using p ≤ 0.05, then we improved model performance by grouping United Nation-derived subregions (p < 0.25 for a variable to enter the model and keeping only variables with a significance level p ≤ 0.05). All two-way interactions were evaluated. The direction and magnitude of the statistical associations were interpreted using the odds ratios (OR) with 95% CI.Two sets of multivariable logistic regression models were used ) to evaluate the association for a sample between epidemiologic risk factors  and the bregions  into resEnterococcus , shrimp , and tilapia  samples  of shrimp samples yielding isolates of this genus versus 9.0% (64/710) of salmon and 7.0% (14/214) of tilapia samples. Approximately 75% of salmon, 79% of shrimp, and 93% of tilapia samples yielded at least one presumptive CRO isolate. We identified 28 different genera among the 948 presumptive CRO isolates tested, with the most predominate being Pseudomonas , followed by Stenotrophomonas and Acinetobacter (9.54% each), Serratia (8.5%), and Aeromonas  have CLSI clinical breakpoints for human infection treatment , followed by erythromycin (3%–14%). Enterococcus faecium were also commonly resistant to quinupristin/dalfopristin, with the resistance prevalence ranging from 40% to 75%, depending on source. Prevalence of resistance in enterococci from tilapia was two to seven times higher than that in the isolates from shrimp or salmon for each chloramphenicol, erythromycin, nitrofurantoin, quinupristin-dalfopristin (E. faecium only), and streptomycin. Prevalence of tetracycline resistance in enterococci from tilapia and salmon was two times higher than that in isolates from shrimp. However, all enterococci from tilapia were susceptible to ampicillin, avilamycin, ciprofloxacin, daptomycin, gentamicin, tigecycline, and vancomycin. We found two enterococci from salmon that were resistant to avilamycin, an orthosomycin antimicrobial intended for use only in broiler chickens and weaner pigs. One of the isolates came from a product imported from Chile and the other from a product imported from Canada  were analyzed for their association with isolation of at least one of the targeted bacterial genera , 8 and fDue to low a prevalence of resistance overall in seafood, we examined the association of epidemiologic factors with resistance to at least one of the tested antimicrobials among the target genera . Using the full multivariable model with contamination of a sample with an antimicrobial resistant isolate of the target bacterial genera as the dependent variable, we found that shrimp were less resistant than salmon , and that farm-raised shrimp and salmon were 60% less likely to yield a resistant isolate. This odds ratio was most likely driven by a larger proportion of tetracycline and daptomycin-resistant isolates from wild-caught commodities . HoweverSalmonella isolates that were sequenced carried no known resistance genes despite having phenotypic resistance to at least one of the antimicrobials tested . Other genotype–phenotype comparisons were difficult to make given the lack of accepted interpretive criteria to categorize the phenotypic antimicrobial susceptibility of the isolates and the limited number of isolates sequenced, however some valuable information might be gleaned from the data. We found qnrVC genes in Vibrio susceptible to ciprofloxacin as well as tetracycline resistance genes, tet(34) and tet(35), in isolates susceptible to the drug (Thirty-three percent (26/79) of the non-CRO, non-s tested . Similars tested . Intrins plasmid . We identriaxone . The isoeillance . Althougthe drug .Salmonella contamination (<1%) than was found in another large scale FDA survey of local and imported seafood collected from processors and distributors throughout the United States  for many drugs with activity against Vibrio and Aeromonas in order to track trends over time. There has been some progress in this area  or low levels of resistance (<10%) to antimicrobials with interpretive criteria for these organisms, with the exception of ampicillin (Vibrio), daptomycin (Staphylococcus), quinupristin-dalfopristin (E. faecium) and tetracycline (Enterococcus spp.). While many P. aeruginosa isolates did have MIC values at or above 32 μg/ml for other antimicrobials including amoxicillin-clavulanic acid, ampicillin, and chloramphenicol, it is known that this organism harbors a high number of intrinsic resistance mechanisms , compared to salmon (n = 134) and shrimp (n = 193), and the low prevalence of resistance to these drugs overall. However, Enterococcus from tilapia had almost two-fold higher levels of resistance to chloramphenicol, erythromycin, nitrofurantoin, quinupristin-dalfopristin (E. faecium only), and streptomycin compared to isolates from shrimp or salmon, which could be a possible consequence of commodity-specific differences in the species composition of isolates with higher MICs. We observed a larger proportion of non-faecalis Enterococcus species among the resistant tilapia isolates -IIa spectinomycin resistance genes, few clinically relevant acquired ARGs were found, supporting previous evidence that environmental strains appear different from highly resistant clinical isolates associated with nosocomial environments  can be found in the article/HT, SA, EN, CW, GT, and PM contributed to the conception and design of the study. XL, MT-D’A, VV, RH, LM, NM’i, and LR conducted sampling. SA, SB, SY, CR-T, SS, XL, MT-D’A, VV, RH, LM, NM’i, LR, and SB-J all conducted microbial testing. CL conducted whole genome sequencing. CL and ES performed bioinformatic analysis. EN and HT performed statistical analysis. HT wrote the first draft of the manuscript. All authors contributed to the manuscript revision, read, and approved the submitted version.This work is supported by the United States Food and Drug Administration.The views expressed in this article are those of the authors and do not necessarily reflect the official policy of the Department of Health and Human Services, the United States Food and Drug Administration, or the United States Government. The opinions expressed in this article are the author’s own and do not reflect the view of the National Institutes of Health. Reference to any commercial materials, equipment, or process does not in any way constitute approval, endorsement, or recommendation by the Food and Drug Administration.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.


Silver nanoparticles (AgNPs) have the potential to be used in aquaculture, but their influence on the growth and health of aquatic organisms has not been extensively investigated. In this study, the abalone viscera hydrolysates decorated AgNPs (AVH-AgNPs) were dispersed into aquaculture water at different concentrations  to evaluate the biological effects on zebrafish (Danio rerio). The results showed that the AVH-AgNPs treatments of 6 and 9 μg/l promoted the growth and did not cause obvious damage to the gills, intestines, and livers of zebrafish. All the treatments induced catalase (CAT) and superoxide dismutase (SOD) activities and increased glutathione (GSH) content in the livers and upregulated the expression of immune related genes. The effects of 9 and 18 μg/l AVH-AgNPs treatments were more obvious. After AVH-AgNPs treatment, the abundances of some potential pathogens, such as species Plesimonas shigelloides and Pseudomonas alcaligenes and genus Flavobacterium decreased significantly. In contrast, the abundance of some beneficial bacteria that can degrade pollutants and toxins  increased significantly. Thus, the application of low concentrations (6 ~ 18 μg/l) of AVH-AgNPs in aquaculture water is relatively safe and has a positive effect on zebrafish farming. Penaeus monodon) infected with Vibrio parahaemolyticus (Litopenaeus vannamei) to white spot syndrome virus (Channa striatus) to resist heat and lead (Pb) and reduced the stress response of cells (Danio rerio) through increasing beneficial microbial populations, goblet cell density, villi length, and up-regulation of immunity related and mucin encoding genes  infected with Aeromonas salmonicida did not show death or clinical symptoms after immersing in a 100 μg/ml AgNPs solution (Oreochromis niloticus). Results revealed that 10 μg/l of AgNPs improved the growth performance and antioxidant enzyme activities, while more than 10 μg/l of AgNPs exposure could disturb physiological indicators and cause histopathological changes. Besides, the total bacterial count in water decreased with the increase of AgNPs concentration , and the abalone viscera hydrolysates (AVH) were obtained according to the previously reported method . The proA total of 600 healthy adult zebrafish were purchased from a commercial aquarium in Xiamen, Fujian, China, and acclimated to the laboratory conditions for 2 weeks. During the acclimatization period, aquaculture water conditions were maintained as follows: water temperature of 25 ± 2°C; dissolved oxygen (DO) of 7.9 ± 0.1 mg/l with 12/12 h light/dark cycle; pH 7 ± 0.2.Zebrafish were divided into four experimental groups in three replicates of 12 tanks (each tank volume is 80-L), each tank with 50 fish. The first group was a control without AVH-AgNPs addition (C0 group). The other 3 groups were added with AVH-AgNPs at doses of 6 (group C1), 9 (group C2), and 18 μg/l (group C3). All concentrations of AVH-AgNPs were selected based on the acute toxicity test . During On the 10th and 20th days of the experiment, six fish were randomly collected from each tank (fasting for 24 h before sampling) and quickly anesthetized with 0.5 g/l eugenol. The body weight and length of the fish were measured, and the liver was isolated with sterile scissors from the abdomen of the fish, immediately frozen in liquid nitrogen, and stored at −80°C until further use for quantitative analysis of antioxidant enzyme activity and immune gene expression. On the 30th day, six fish were collected from each tank to measure their body weight and length, and livers were sampled for quantitative analysis of enzyme activity and gene expression. The intestine and gill tissues were collected from these fish samples and fixed in a 4% paraformaldehyde fixative solution for subsequent histopathological analysis. Additionally, another 12 fish were randomly sampled from each tank, and the intestinal tissues were separated. The intestinal tissues of every 6 fish were pooled into one sample, and all the samples were quickly frozen in liquid nitrogen and stored at −80°C for subsequent DNA extraction.The activities of superoxide dismutase (SOD) and catalase (CAT), and glutathione (GSH) content were determined using commercial kits purchased from Nanjing Jiancheng Bioengineering Institute, Nanjing, Jiangsu, China. The determinations were carried out following the manufacturer’s protocols.2O. The relative mRNA expression levels were calculated by the 2-ΔΔCT method  according to the manufacturer’s instructions. The purity and concentration of total RNA were detected using an ultra-micro spectrophotometer . RNA was reverse transcribed into cDNA using TransScript All-in-One First-Strand cDNA Synthesis SuperMix for qPCR . The qPCR was performed with cDNA as a template by the intercalation fluorescence method to obtain the PCR melting curve. Ten microliter of the reaction mixtures consisted of 5 μl SYBR Green qPCR Master Mix , 1 μl of forward primer, 1 μl of reverse primer, and 3 μl of ddHT method . Primer via a microtome . The sections were stained with hematoxylin and eosin (HE) and observed after imaging with an ortho-fluorescence microscope .The fixed tissue was dehydrated with increasing ethanol concentrations (from 75 to 100%), cleared with xylene, and embedded in paraffin. Four-micron thick paraffin was sliced Total DNA was extracted from the intestines with the TruSeqTM DNA Sample Prep kit  according to the manufacturer’s instructions. The qualified DNAs were sent to Shanghai Majorbio Bio-pharm Technology Co., Ltd., China, for Illumina Miseq sequencing. The single long reads and original libraries were spliced by merging paired-end sequences through the Flash (v.1.2.11) program. Sequence quality was controlled and filtered by Uparse (v.7.0.1090). The reads were optimized, and operational taxonomic units (OTUs) were classified by clustering with a 97% similarity threshold using Usearch (v.7.0) and compared the database Sliva  and verified by Duncan SPSS v.18 . The differences were considered significant at p < 0.05 .The TEM images of AVH-AgNPs at 50 nm and 100 nm magnification are shown in p < 0.05) (p < 0.05), respectively. After 30 days of AVH-AgNPs treatment, no significant difference in body length was found among the four experimental groups (p > 0.05)  . All the > 0.05) .p < 0.05) (p < 0.05), and the higher concentration treatment had a higher CAT activity (The SOD and CAT activities and GSH content in zebrafish livers are shown in  < 0.05) . AVH-AgNactivity . All theactivity .The effects of AVH-AgNPs on gene expression levels of TNF-α, IL-1β, IL-10, IL-12, and DEFB1 are shown in The histological analysis of zebrafish gills, liver, and intestines are showed in After Illumina sequencing, a total of 563,537 effective sequences were obtained from 16 samples, with an average sequence length of 414.75 ± 1.33 bp. Each sample had 40,222 ~ 62,918 valid sequences, and the coverages of all samples were greater than 0.99. To avoid the analysis error caused by different sequencing depths, 40,000 sequences were normalized from each sample for subsequent analysis.AVH-AgNPs treatment had a certain effect on the alpha diversity of zebrafish gut microbiota, and different treatments had different effects. As shown in PCA showed that AVH-AgNPs affected the intestine bacterial community structure at phylum, genus, and species levels, and the effects were different in different treatments . All theThe gut microbial composition at phylum, genus, and species levels are shown in Cetobacterium (53.18%), followed by Aeromonas (7.29%) and Flavobacterium (5.4%). The genera with abundances ranged from 1 to 4%, in order of high to low, which were as follows: ZOR0006, Burkholderia-Caballeronia-Paraburkholderia, Vibrio, Plesiomonas, Rhodococcus, Halomonas, Sphingomonas and Bradyrhizobium, and others were less than 1% . The most dominant genus was  than 1% .Aeromonas veronii, Cetobacterium sp. ZOR0034, Plesimonas shigelloides, and Rhodococcus erythropolis (7.28 to 2.22%). Other abundant species were Vibrio harveyi, Firmicutes bacterium ZOR0006, Chitinibacter fontanus, and Flavobacterium cucumis (accounting for 0.87 to 0.5%). Besides, Bacillus aerophilus, Methylobacterium populi, Pseudomonas alcaligenes, Escherichia coli, Flavobacterium suncheonense, Alcaligenaceae bacterium BL-169, etc., were also detected, and their abundances were more than 0.1%  were: han 0.1% .Halomonas and Flavobacterium decreased significantly in all three AVH-AgNPs treatments. Plesimonas decreased significantly in C2 and C3 groups, while Burkholderia-Caballeronia-Paraburkholderia, Sphingomonas, and Rhodococcus increased significantly in the C3 group compared with the control group.At the genus level, in the identified genera with an abundance of more than 1%, F. cucumis decreased significantly in all three treatments, P. shigelloides, P. alcaligenes, and F. suncheonense decreased significantly in C2 and C3 groups, and C. fontanus decreased significantly in C1 and C2 groups. Alcaligenaceae bacterium BL-169 increased significantly in the C1 group, and R. erythropolis increased significantly in the C3 group.At the species level, in the identified species with an abundance of more than 0.1%, The synthesis of AgNPs mainly includes physical, chemical and biological routes. AgNPs prepared by physiochemical methods are easy to aggregate, and the chemical reagents used to stabilize the nanoparticles  are harmful and easy to cause environmental pollution . CompareSOD and CAT are the most important antioxidant enzymes for scavenging and repairing reactive oxygen species (ROS). Previous studies showed that dietary supplementation with AgNPs significantly improved the growth of poultry , weaned In the present study, low concentrations of AVH-AgNPs   were addP. shigelloides have been reported as a zoonotic pathogen of gastrointestinal diseases and are responsible for the high mortality of many farmed fish  (Acipenser sinensis) (Pseudosciaena crocea) (Cyprinus rubrofuscus)  , Chineseinensis) , Large y crocea)  and Koi ofuscus) . P. alcaaculture . The abuF. cucumis decreased significantly in all three treatments, and F. suncheonense decreased significantly in C2 and C3 groups. Both strains were isolated from greenhouse soil in Korea and had polysaccharide decomposition potential (F. cucumis was isolated from diseased fish (Genbank accession number: KU851954), suggesting a link to fish disease. In addition, there are many unknown species of Flavobacterium decreased significantly. Flavobacterium contains many aquatic pathogens and is one of the pathogenic genera of zebrafish  dispersed in aquaculture water did not cause significant damage to the morphology of gills, livers, and intestinal tissues of zebrafish and promoted the growth, induced the increase of SOD and CAT activities and GSH content, and upregulated the immune-related gene expression of zebrafish. After AVH-AgNPs treatment, some pathogenic or opportunistic pathogens significantly decreased in zebrafish intestines, while the beneficial bacteria that could degrade pollutants and improve the intestinal environment increased significantly. Therefore, applying a low concentration of AVH-AgNPs in aquaculture water is relatively safe and has positive significance in improving antioxidation and immunity, controlling intestinal pathogens, and reducing the incidence of cultured animals. Considering it might be more convenient to apply in water than in feed, we suggest that AVH-AgNPs have good application prospects in aquaculture.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.The animal study was reviewed and approved by the Animal Ethics Committee of Jimei University (Acceptance no. JMULAC201159).JN and ZY conducted the experiments and wrote the manuscript. YZ performed the statistical analysis. YM, HX, and WJ contributed to the conception and designed of the study. All authors contributed to manuscript revision, read, and approved the submitted version.This work was supported by Natural Science Foundation of Fujian Province (grant no: 2020 J01662), Xiamen Science and Technology Planning Project (grant no: 2022CXY0307) and the Program of Institute of Respiratory Diseases, Xiamen Medical College (grant no: HXJB-14), China.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.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.


The present study employed epiphytic lichens as biomonitor and passive air sampler for the assessment of fifteen (15) atmospheric polycyclic aromatic hydrocarbons (PAHs) in some major cities in three regions of Ghana. A total of 36 composite lichen samples were collected and analysed using Gas Chromatography - Tandem Mass Spectrometry (GC-MS-MS). The total PAH recorded ranged between 1909.9 ng/kg (A36) and 250,091.4 ng/kg (W15). Due to the inherent deficiencies in using a single source apportionment tool, multiple source apportionment methods including diagnostic ratios, principal component analysis/absolute principal component scores (PCA-APCS) and APCS with automatic linear model (APCS–ALM) were used to ascertain the source of PAHs in the lichens. The diagnostic ratios revealed a mix source of wood/grass and petrol/petroleum fuel combustion, with the major source ascribing to wood/grass combustion. The source apportionment confirmatory statistical test conducted with the PCA-APCS and APCS–ALM, were in good agreement with the diagnostic ratio. Both PCA-APCS and APCS–ALM suggested two significant sources (p < 0.0), with wood/grass combustion as the major (contributing 77.8%) and mix petroleum related sources being the other with 22.2% contribution of PAHs to the receptor sites. The study found PCA-APCS and especially APCS–ALM to be an effective statistical tool for PAH source apportionment in passive air samplers. To our knowledge, this is the first use of lichens for PAH monitoring in the country. Therefore, this study could serve as an inexpensive and real time bio-monitoring tool for air quality assessment in the African sub-region and the world at large.  •Epiphytic lichens was used as biomonitor for atmospheric PAH.•a]P levels suggestive of eminent risk > 10−4 were recorded for most samples studied.Elevated B[•The source apportionments conducted predicted petrol/petroleum fuel combustion as the major sources.•This is widely potentially replicated study, using epiphytic lichens for the first time in Ghana to measure atmospheric PAHs. With the exception of choosing a monitoring regime and method of analysis, the other primary challenge of environmental monitoring of PAHs is to distinguish between different sources in order to identify the main contributors of PAHs in an area of interest. In that regard, making use of passive samplers which are biomonitors and bioaccumulators is of great interest for the simplicity and rapidity with which it can be done Specifically, lichens are symbioses of two organisms, a fungal mycobiont and a photoautotrophic photobiont, which present a very remarkable ability to uptake, accumulate and keep water, nutrients and contaminants directly from the air because they have no roots The outlook for air pollution in many developing nations including Ghana, is a cause for concern. The problem of air pollution is exacerbated by the increasing rate of e-waste burning as a result of the influx of electronic waste coupled with increasing vehicular traffic and indiscriminate bush burning This study, therefore, sought to employ epiphytic lichens for the monitoring of PAH levels in the atmosphere resulting from anthropogenic activities in three cities of Ghana namely; Kumasi, Takoradi and Cape Coast and also apportion their source. To our knowledge, this is the first use of lichens for PAH monitoring in the country. Therefore, this study could serve as an inexpensive and real-time bio-monitoring tool for air quality assessment in the African sub-region and the world at large.22.1The Central, Western and Ashanti Regions are located in the coastal to the transitional forest zone of Ghana . They ex2.2piphytic lichens were collected at random from selected areas of about 10 m2 in the Ashanti, Central and Western regions of Ghana. Sampling was done from August, 2014 to December, 2014. The lichens were carefully scraped from the tree barks using a stainless steel knife. All the samples collected in an area of 10 m2 were composite to form thirty six (36) major samples. To avoid contamination, the lichens were collected at about 1.5 m above the soil and neatly packed in air-tight amber glass and transported to the laboratory in a cooler. Samples which were considered relatively clean were also collected in the same manner at the Kakum National Park  in the Central Region of Ghana to serve as the control samples. Samples were kept frozen until processing.E2.3a]A), chrysene (CHR), benzo(b + k)fluoranthene (B[b+k]F), benzo(a)pyrene (B[a]P), indeno(1.2.3.cd)pyrene (IND), dibenz(a.h)anthracene(DbA), benzo(g.h.i)perylene (B[g]P) and an alkylated PAH 2-bromonapthalene (BNAP) was purchased from Supelco Sigma-Aldrich Pty. Ltd .Analytical grade reagents were used throughout the analysis. Standard mixture (QTM PAH Mix standard) containing sixteen PAHs, including naphthalene (NAP) acenaphthylene (ACY), acenaphthene (ACE), fluorene (FLU), phenanthrene (PHE), anthracene (ANT),fluoranthene (FLT), pyrene (PYR), benz(a)anthracene . After extraction, extracts were concentrated by rotary vacuum evaporation and cleaned up using a C18 SPE column with 30 mL of acetonitrile as the eluting solvent. Subsequently, the extracts were concentrated using the rotary evaporator to about 5.0 mL and further concentrated with a gentle stream of pure NPrior to GC-MS/MS analyses, all the samples were spiked with an internal standards mix containing, naphthalene-D8, acenaphthene-D10, phenanthrene-D10, chrysene-D12 and perylene-D12 .2.5Analysis was done using Shimadzu GCMS-TQ8040 with splitless injection, MRM acquisition mode and EI ionisation in 22.83 min. The ResteK capillary column RXi-5MS (30 m × 0.25 mm × 0.25 m) was used with helium gas (purity > 99.999) as the carrier gas. The GC-MS/MS conditions were similar to that reported by Duodu et al. 2.6At least five point calibration curves were used for quantification using the internal standard method. More than 10% of the samples were spiked with pure PAH standards to estimate the efficiency of the method used. Due to the lack of matrix blank for the recovery test, 2 g sea sand (solid blank) was spiked with 100 µL QTM PAH Mix standard (20 µg/mL) and treated as a sample. In the absence of matrix-matched certified reference material, the method validation and detection limit determination were similar to that reported by Duodu et al. 2.7Analysis of variance (ANOVA) at 95% confidence level, was employed for replicate analyses conducted. Initial source assessments of the PAHs were conducted using the diagnostic PAH ratios. Further, factor analysis, specifically principal component analysis (PCA) coupled with multiple linear regression and automatic regression analysis were also employed for source apportionment of the PAHs in the lichens using IBM SPSS Statistics 25 and SigmaPlot 14.0.33.1All the data reported in this study were blank corrected. The recovery of PAH was evaluated using two different samples at different concentration levels as certified in NIST 1941b (high), and at 1.0 µg/g spiked sea sand (low). The mean recoveries of the PAHs investigated were > 80% at the high concentration level. Implying, good reproducible recoveries of PAHs in the certified material by the method with > 80% accuracy. Similarly, good reproducible mean recoveries (>80%) of most PAHs were also recorded at low levels. Here, the only exceptions were BgP and DbA with recoveries of 61% and 71%, respectively. In addition, the average recovery of Anthracene d-10 (surrogate standard) was 82%. The RF RSDs were generally < 15% for all PAHs.The limit of detection (LOD) and limit of quantification (LOQ) for replicates (n = 7), were calculated to range from 0.01 to 0.21 ng/mL (LOD) and 0.04–0.70 ng/mL (LOQ) respectively 3.2a]A, CHR, B[a]P, DbA and BgP) recorded values below the detection limits (BD) used in some samples from Western Region. However, all fifteen PAHs were detected in all samples from both Central and Ashanti Regions but for CHR in one sample from Central Region. The mean total concentrations of the 15 PAHs were between 213 and 251,225 ng/kg with an average of 15,483.6 ± 15,778 ng/kg (The mean concentrations of the fifteen (15) PAHs recorded in the lichen samples from the three regions  of Ghana are summarised in 78 ng/kg . In term78 ng/kg , 2687 ng78 ng/kg  and 191078 ng/kg , in Centa]A, CHR, B[b + k]F, B[a]P, DbA, and INP) ranged between 19 and 105,425 ng/kg accounting for about 44% of the sum of the 15 PAHs. The concentration of PAHs recorded in this study was higher than that observed by Vitali et al. Samples labelled C04, W23 and A36 were taken from a forest reserve, a hospital and a residential area, respectively  thus four to six-membered ring PAHs compared to the low molecular weight (LMW) (two- and three-membered ring) PAHs  and thisa]A, B[b+k]F, B[a]P and IND were considerably higher than the remaining PAHs. This could be attributed to the sources of the PAHs in the area. NAP and B[a]P as well as FLT, PYR, B[b+k]F, B[a]P and IND have been cited as strong markers for vegetation or biomass burning and diesel emissions, respectively The concentration of the listed PAHs NAP, FLT, PYR, BP/(BgP)] also ranged between 0.32 and 0.5 and 0–13.1, respectively. These also suggest petrogenic and fossil fuel combustion (both traffic and non-traffic emissions), with the non-traffic emission likely being wood and grass combustion From The results of the present study is comparable with that reported by Shukla et al. 3.4The use of a multivariate technique such as principal component analysis/absolute principal component scores (PCA-APCS) and automatic linear model (APCS–ALM) to support diagnostic ratio in source apportionment helps to overcome the shortcomings of diagnostics ratio. It can quantitatively estimate the contribution of the various identified sources. PCA-APCS and APCS–ALM are very useful tools for source apportionment in environmental studies and details of the methods are described and applied in Adjei et al. 2 of 0.999 and P < 0.001. The PCA extraction resulted in two (2) significant factor components after Varimax rotation . The two factor components (Source 1 and Source 2) contributed about 94.1% of the total percent variance. Factor component one contributed 82.4%, whereas component two contributed 11.7% of the total variance recorded.The PCA-APCS was used to model the mean-centred PAH concentrations with variables below the detection limit replaced by one-half of its detection limits. The results of the PCA-APCS model are shown in a]A, CHR, B[b+k]F, IND, DbA and BgP and minor contribution of B[a]P. The major presence of FLT, PYR, B[a]A, B[b+k]F, and BgP in this factor can be linked to fossil fuels combustion, particularly, diesel exhaust emissions Source 1 contributed 22.2% of PAHs to lichen samples  with siga]P loadings. Both NAP and B[a]P have been used as a marker for biomass burning The second source accounted for 77.8% of the total PAHs and was characterised by high NAP, and moderate BP , followed by FLT . This model suggests that the levels of NAP in lichens may be used to significantly predict the biomass burning source of PAHs with an accuracy of 99.7%. Naphthalene (NAP) and B[a]P are known to be important loading components in biomass burning The summary report from the APCS-ALM, again predicted that the model is 99.7% accurate in predicting the contribution of the second factor (biomass burning) to the PAHs levels recorded in the lichen samples. Though quite elaborated, the results obtained by Landis et al. 4The study reveal that the lichens in the study area recorded higher concentrations of HMW-PAHs compared with LMW-PAHs. However, the lichen samples could be useful for accumulating LMW-PAHs with least deviations compared with HMW-PAHs with high deviations. The source apportionment results from the diagnostic ratio and both PCA-APCS, and APCS-ALM methods were in good agreement predicting two significant sources of mix petroleum-related sources and most importantly wood/grass combustion (biomass burning) source. The results suggest that lichen samples in the study area could be used as bio-monitoring/passive sampler of atmospheric PAH and also for source apportionment when coupled with statistical tools like PCA-APCS and APCS–ALM. Therefore, this study could serve as an inexpensive and real-time bio-monitoring tool for air quality assessment in the African sub-region and the world at large.The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: David Kofi Essumang reports equipment, drugs, or supplies was provided by University of Cape Coast. David Kofi Essumang reports a relationship with University of Cape Coast that includes: employment. David Kofi Essumang has patent No Patent pending to No Licensee. Nothing more to declare.


Necrotizing enterocolitis (NEC) is a devastating intestinal complication that occurs mainly in very-low-birth-weight infants (VLBWI). The study's aim was to investigate the possibility of early prediction of NEC on postnatal day 1 based on superior mesenteric artery (SMA) doppler ultrasonograpy.A prospective, observational, nested case control study (ChiCTR1900026197) was conducted to enroll VLBWIs  between October 2019 and September 2021. Doppler ultrasound measurement was done during the first 12 h of life and before first feeding. Infants developing NEC (stage II or III) subsequently were included in NEC group and infants spare of NEC were included in control group.P = 0.000). The area under the receiver operating curve (AUROC) following the Logistic regression was 0.704 . The sensitivity of S/D for predicting NEC was 52.2% and the specificity was 92.7%. The critical value of S/D was 6.944 and Youden index was 0.449. Preplanned subgroup analysis confirmed that NEC infants of different stages were characterized by different SMA bloodstream. Small for gestational age (SGA) might be a confounding factor affecting intestinal bloodflow. And infants with delayed initiation or slow advancement of feeding exhibited characteristic intestinal perfusion.370 VLBWIs were enrolled (30 NEC cases). Among the ultrasound parameters, S/D was significantly higher in the NEC group (OR: 2.081, 95% CI: 1.411–3.069, In VLBWI, early SMA ultrasound shows the potential to predict NEC. It is reasonable to speculate that SMA bloodstream is related to intestinal structural and functional integrity. Annually, about 15 million preterm infants  are born globally , 3. As aBesides, there are also studies dedicated to predicting NEC and helping clinical work by identifying high-risk groups. The goal of these studies is to improve the prognosis of preterm infants, and ultrasound is one of the explorations. Superior mesenteric artery (SMA), a major branch of the descending aorta, is the main source of blood supply to the intestine . Our preThis is a prospective, observational, nested case-control study . It was approved by hospital Ethics Committee [2019 (10)]. Enrollment took place between October 2019 and September 2021. Guardians, staffs of neonatal and radiological departments were blinded to the measurements of SMA doppler ultrasound.2 90%–95%, mean blood pressure ≥30 mmHg, arterial pH > 7.25, PaCO2 35–45 mmHg, PaO2 50–80 mmHg.Inclusion criteria: (1) These infants were born in our hospital, and admitted into neonatal department quickly after birth to receive complete support and treatment; (2) Birth weight should be less than 1,500 grams; (3) Written informed consents were obtained from guardians; (4) Doppler ultrasonography should be done within 12 h of birth, when the respiration and circulation were stable. In this study, cardiopulmonary stability refers to preductal SaOExclusion criteria: (1) Refused to provide consent; (2) Participated in other studies; (3) Not admitted to neonatal department shortly after birth or just received limited supportive care at the family’s request; (4) Unable to achieve cardiopulmonary stability within 12 h; (5) Feeding couldn’t be initiated during hospitalization; (6) Major or lethal congenital anomalies.Preterm infants management protocol of the neonatal intensive care unit (NICU) recommended that first feeding should be initiated no later than 12–24 h of life, and the ultrasound should be completed before it. Infants who developed NEC (stage II–III) during hospitalization were included in NEC group, and those without NEC were included in the control group.SMA bloodstream doppler ultrasound were done by three experienced ultrasonologists, and interobserver agreement was tested prior to the study. Bloodstream were measured by CX50 ultrasound machine  with L12–3 linear probe (3–12 MHz).The probe was placed vertically and softly below the xiphoid process of the lying infant during the whole examination. The sample volume of doppler ultrasound was set near the origin of SMA with acceptable angle between soundwave and bloodstream (<30°). For measurement and calculation, continuous recording of at least 5 cardiac cycles was necessary. The average of three tests was the final result of the ultrasound examination. Direct indicators include: peak systolic velocity (PSV), end-diastolic velocity (EDV), time-averaged mean velocity (TAMV). Calculated parameters include: differential velocity , SD index (SD = PSV/EDV), pulsatility index , and resistance index .Breast milk is the default choice, and the formula is also an alternative when breast milk is unavailable.According to modified Bell`s criteria , 16, NECG*Power (Version 3.1.9.6) was used for sample size calculation. Historical data at our hospital showed an 8% incidence of NEC in VLBWIs. According to our previous study, it was assumed that the DV was 45 cm/s (standard deviation ±18 cm/s) in the NEC group and 34 cm/s (standard deviation ±13 cm/s) in the non-NEC group. With 5% significance, 90% power and 20% loss-to-follow, 328 VLBWIs (28 NEC infants and 300 Non-NEC infants) were required.The endpoint of the study was a diagnosis of NEC (stage II or III) during hospitalization. Information of obstetric conditions, perinatal history, illnesses and treatments, ultrasound measurements, nutritions was collected. Given the excellent follow-up rate, the handling of missing data was done by removal of incomplete cases.U test. Categorical variables (numbers and percentages) were tested by χ2 or Fisher's exact test as appropriate. Factors that had significant differences in the univariate test and passed the collinearity test were included in the logistic regression analysis. A receiver operating characteristic curve could be drawn based on the logistic regression analysis. All tests were two-sided and P < 0.05 were considered to be significantly different. All data analyses were performed using SPSS version 22.0 software .Continuous variables with non normal distribution were expressed as medians and quartiles, and compared by using the Mann–Whitney Preplanned subgroup analyses include: (1) NEC stage II vs. stage III, to reveal if severity of NEC is related with intestinal bloodflow; (2) The control group was divided into two subgroups  to verify the relationship between birth weight and SMA bloodstream; (3) Control group was divided into ≥32 gestational weeks and <32 gestational weeks subgroups to test the relation between ultrasound and gestational age; (4) Infants diagnosed small for gestational age (SGA)  were selected to evaluate the effect of fetal growth restriction on intestinal bloodflow.As the major supply of blood perfusion in the gut, SMA is of great importance for the structural and functional integrity of the intestine. Thus we conducted further exploratory analyses to assess the association of intestinal perfusion stability with feeding of VLBWI.A total of 451 VLBWIs were screened for eligibility during the investigation, 433 infants met the inclusion criteria . 419 VLBWIs were included . Finally there were 370 VLBWIs entered the data analysis .P = 0.009], and the NEC group infants needed longer days to reach 120 ml/kg.d of feeding (days) . According to other endpoints, the NEC group had significantly higher rates of late-onset sepsis , longer hospital stays (days) , and significantly higher in-hospital mortality than the control group .30 VLBWIs diagnosed with NEC stage II or III were included in the NEC group, while 340 VLBWIs without NEC served as control group. Details of NEC infants were listed in the χ2 = 0.921, P = 0.337], and there was also no significant difference in reverse flow during diastole .Univariate analysis of SMA doppler ultrasound between two groups detected significant differences in multiple parameters . The risP = 0.000) (P = 0.001)  . The are= 0.001) . The senP = 0.039], and stage II patients also had lower DV (cm/s) . (2) Among the control group of 340 VLBWIs spared of NEC, there were 35 extremely low birth weight infants , other infants’s birth weight are larger than ELBWIs . Although significant differences naturally existed between the two subgroups in terms of demographics, diseases, treatments, and nutritions, but there was no significant difference in ultrasound parameters between them. (3) Among the control group of 340 VLBWIs spared of NEC, there were 57 infants with gestational age ≥32 weeks and 283 infants with gestational age <32 weeks. Although there were significant differences in multiple indicators of baseline characteristics between the two subgroups, ultrasound parameters did not show significant differences between them. (4) Among the control group of 340 VLBWIs spared of NEC, there were 73 SGA infants and 267 non-SGA infants, differences existed in a number of demographics between the two subgroups. Furthermore, obvious differences could be detected in ultrasound parameters.Preplanned subgroup analyses were detailed in the Exploratory analyses were also detailed in the During the ultrasound examination, no infant had adverse reactions.In this prospective, observational, nested case-control study of 370 VLBWIs, we found differences in multiple parameters of SMA ultrasound between 2 groups, and we finally confirmed the relation between S/D and incidence of NEC by Logistic regression analysis. The receiver operating characteristic curve also preliminarily verified the reasonable predictive power of this ultrasound parameter. Subgroup analysis unveiled that SMA bloodstream was related to the severity of NEC.Murdoch et al. reported that EDV, TAMV, and PI of first day’s SMA ultrasound were related to NEC of preterm infants . 104 preSince NEC seriously affects the prognosis of preterm infants, studies have been devoted to predicting this devastating disease. Alice et al. included 40 extremely preterm infants , 11 developed NEC, 29 did not, none of 189 serum biomarkers within 2 days of age could effectively detect the risk , 20. UltIn neonatal , 22 or aSMA provides major gut perfusion, and blood supply is crucial for structural and functional integrity, which is also confirmed by our exploratory analysis. Robel et al. found that early feeding volume was affected by intestinal hemodynamic stability after birth, but VLBWIs with poor feeding tolerance were mostly SGA infants in their analysis . Jain etVLBWIs are in need of sophisticated and hierarchical management, and SMA ultrasound in early postnatal period provides this possibility. Patel et al.  reportedAlthough our study confirms the relationship between SMA bloodstream and NEC in VLBWIs, obviously there are limitations: (1) NEC stage I (suspected) infants were not included, which helped to distinguish NEC group from control group, but in fact, the in-hospital treatment, nutrition of VLBWIs with suspected NEC are also affected, even not so severe as confirmed NEC. (2) Although no significant difference was observed in the proportion of SGA in 2 groups, subgroup analysis confirmed that SGA was more prone to high-resistance bloodstream, which is consistent with other studies , 28. SGAvia SMA ultrasonography, which if timely managed, could reduce morbidity and mortality of VLBWIs. We hope that future well-designed studies will further confirm this and ultimately contribute to improving outcomes in preterm infants.In conclusion, there is now a potential for early prediction of NEC


PARK7 (DJ-1), SLC17A6 (VGLUT2), PTPRN2 (IA-2β), NR4A2 (NURR1), and other genes involved in developmental pathways, neurotransmitter packaging and release, and axon and neuron projection guidance.Evidence for epigenetic regulation playing a role in Parkinson’s disease (PD) is growing, particularly for DNA methylation. Approximately 90% of PD cases are due to a complex interaction between age, genes, and environmental factors, and epigenetic marks are thought to mediate the relationship between aging, genetics, the environment, and disease risk. To date, there are a small number of published genome-wide studies of DNA methylation in PD, but none accounted for cell type or sex in their analyses. Given the heterogeneity of bulk brain tissue samples and known sex differences in PD risk, progression, and severity, these are critical variables to account for. In this genome-wide analysis of DNA methylation in an enriched neuronal population from PD postmortem parietal cortex, we report sex-specific PD-associated methylation changes in  An estimated 5–10% of PD cases are familial and several genes have been identified that cause these inherited forms of the disease3. The remaining ~90% of cases are likely due to a complex interaction between age, genes, and environmental factors. Given that epigenetic marks are dynamic with age, sensitive to the environment, and regulate gene expression throughout the lifespan, they are considered a potential mediator of the complex relationship between aging, genetics, the environment, and disease disease5.Parkinson’s disease (PD) is the second most common neurodegenerative disorder in the US, and is characterized by progressive degeneration of dopaminergic neurons in the nigrostriatal pathway and the formation of α-synuclein-containing Lewy bodies12. In particular, previous studies have reported differential DNA methylation at PD-related genes 15, and hypomethylation of the α-syn gene (SNCA) is associated with decreased protein levels in the substantia nigra (SN) and striatum of postmortem PD brain23. In addition to these gene-specific studies, genome-wide analyses of DNA methylation from postmortem PD brain tissue have identified a number of gene regions that show differential DNA methylation in PD brains27. Finally, a case-control study identified an association between a polymorphism in PD risk and DNA methyltransferase 3B (DNMT3B), which is responsible for establishing de novo patterns of DNA methylation during embryonic development28. Taken together, these multiple lines of evidence support the role for dysregulation of DNA methylation in the etiology of PD.Evidence for the role of epigenetic regulation in PD is growing, particularly for DNA methylation31, it is critical to include sex in experiments examining the potential role for the epigenome in PD. Furthermore, the majority of existing studies of epigenetics in PD have utilized either blood or bulk brain tissue samples33. Although DNA methylation changes in blood are useful for identifying biomarkers, they may not be representative of a pathogenic mechanism in the brain. Further, analyses from bulk brain tissue cannot address the cell-type specificity of identified changes, making it difficult to determine which cell types may be driving PD-related differential DNA methylation. In a step forward for the field, one recent paper investigated DNA methylation in an enriched neuronal population using fluorescence-activated cell sorting, but only explored DNA methylation at enhancer regions, not genome-wide27. Here, we report the results from a genome-wide analysis of DNA methylation in enriched neurons from PD brain stratified by sex.However, the existing genome-wide analyses of DNA methylation in PD have not adequately addressed the effects of sex or cell-type heterogeneity. Given that men and women show differences in PD risk, disease progression, and disease severityn = 50 control, n = 50 Parkinson’s disease) from the Banner Sun Health Research Institute Brain Bank and enriched for neuronal populations using magnetic-activated cell sorting (MACS) for the neuronal marker, NeuN. Postmortem parietal cortex was used because this region develops pathology in the late stages of PD and is expected to still have robust populations of neurons, from which disease-affected gene regulatory marks can be measured. Genome-wide DNA methylation was measured using the Illumina EPIC BeadChip array paired with bisulfite treatment. Bisulfite treatment is a well-established method for measuring DNA methylation, but it actually cannot distinguish between DNA methylation and DNA hydroxymethylation35. As such, our dataset actually measures both DNA methylation and DNA hydroxymethylation without discriminating between these two epigenetic marks. Despite this important caveat, for simplicity’s sake and to match prior literature, we will discuss our results as changes in “DNA methylation.”In this study, we obtained human postmortem parietal cortex  and Parkinson’s disease (n = 50) human brain samples were obtained from archival human autopsy specimens provided by the Banner Sun Health Research Institute (BSHRI), using BSHRI’s approved institutional review board (IRB) protocols. Further details about the BSHRI’s brain samples are available in a previous publication46. We selected PD patients with mid-stage disease (Braak stage = II–III), as defined by Lewy pathology47. The cohort of control brains consisted of patients who died from non-neurologic causes and whose brains had no significant neurodegenerative disease pathology. Subjects were split by sex , and data for the sample cohort are summarized in Table N = 100), the parietal cortex was obtained. This region develops pathology late in PD; in mid-stage PD, the parietal cortex is expected to still have robust populations of neurons , providing an avenue to investigate pre-pathological changes in gene regulation.De-identified tissue samples from control . As a secondary validation, we estimated proportions of neuronal and glial cell types for all experimental MACS-sorted parietal cortex samples using the Cell Epigenotype Specific (CETS) package during EPIC array data processing. One sample from the male control group that was not one of the six with validation by flow cytometry had an estimated neuronal population of only 0.03% in the CETS analysis. This sample was removed prior to all downstream differential methylation testing. The average proportion of neurons in the remaining 99 samples was estimated to be 83.8% by CETS analysis   in males and 87 significant DMCs in the female parietal cortex associated with PD  was located within the PARK7 locus and showed male-specific hypomethylation in PD cortical neurons compared to control . This ATXN1 DMC is located within a predicted enhancer associated with weak transcriptional activity and showed female-specific hypermethylation in PD cortical neurons compared to control   Figs. , 4b49,50In our sex-stratified models for differential genomic region testing, we identified 258 significant differentially methylated regions (DMRs) in males and 214 significant DMRs in female parietal cortex by Parkinson’s disease (minimum smoothed FDR < 0.05)  includes 2 CpGs—cg21226516 and cg11209121—that are located at an exon-intron boundary in the gene body of NR4A2 and within chromatin annotated as bivalent chromatin  pathways. GOBP pathway enrichment analysis was not performed on male DMCs due to the low number of significant CpGs (n = 3) but was performed on the genes annotated to female hypomethylated DMCs and hypermethylated DMCs separately. Hypo- and hypermethylated DMCs were considered separately due to expected differences in associations between increased or decreased DNA methylation and gene regulation. Female hypermethylated DMCs did not show enrichment for any pathways, but female hypomethylated DMCs showed enrichment for 10 pathways, including several developmental pathways, neurotransmitter transport, neurotransmitter secretion, and signal release from synapse  pathways. In both males and females, hypermethylated DMRs did not show any enrichment for GOBP terms. Meanwhile, for the hypomethylated DMRs, females showed significant enrichment for 6 GOBP terms , including cell fate commitment and glucose homeostasis , including semaphorin-plexin signaling pathways involved in axon guidance and neuron projection guidance . These results confirm that this is a well-calibrated epigenetic clock where there was an approximate 1 unit increase in estimated epigenetic age with a 1 unit increase in chronological age  significantly associated with chronological age at death , SLC17A6 (VGLUT2), PTPRN2 (IA-2β), NR4A2 (NURR-1), as well as other genes involved in developmental pathways, neurotransmitter packaging, and release, and axon/neuron projection guidance , whereas the combined model produced a non-uniform histogram with a skew towards high p-values  and used bulk postmortem brain tissue samples from substantia nigra, parietal cortex, and occipital cortex60. Given these differences, the existing data do not necessarily contradict our PARK7 results.Two previous studies examining the effects of PD status on DNA methylation at the ATXN1 gene, which showed PD-related hypermethylation , which is involved in transcriptional repression of a large number of target genes and is necessary for normal brain development and function62. Expanded polyglutamine repeats in this gene cause spinocerebellar ataxia type 1 (SCA1)63. Although the ATXN1 gene has not been previously studied in the context of PD, our data showing altered epigenetic regulation of the ATXN1 gene in PD brains opens new avenues of research. It is possible that epigenetic regulation at this locus leads to changes in the expression of ATXN1 and its target genes, affecting the susceptibility of cortical neurons to PD-related dysfunction and pathology.The most significant DMC in female subjects was located in a weak enhancer region within the on Figs. , 4. ATXNNR4A2  protein, a transcription factor critical for dopaminergic neuron development and maintenance. Previous research suggests that downregulation of the NR4A2 gene in the brain may contribute to PD pathogenesis66. Supporting this idea, in a previous animal model study, we showed that developmental exposure to the organochlorine pesticide dieldrin, which is known to be associated with increased PD risk, led to sex-specific changes in DNA methylation in the Nr4a2 gene body in mice51. These previous results, along with our present data, suggest that sex-specific epigenetic regulation at the NR4A2 gene may play a role in idiopathic PD risk.In males, we also identified PD-related hypermethylation in an exon just downstream of an exon-intron boundary in the gene body of A2 Figs. , 4. NR4ASLC17A6 gene body , which has been implicated in PD pathogenesis via multiple lines of evidence67. Studies using in vivo and in vitro models show increased VGLUT2 expression in dopaminergic (DA) neurons in response to the neurotoxicants, rotenone, 6-OHDA and MPP+69. Further, deletion of VGLUT2 in mice exacerbates the neurotoxic effects of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) exposure70. Additional studies suggest that neurons that co-express VGLUT2 and VMAT2 show differentially vulnerability in PD and differences in neuronal structure72. Our analysis did not assess DNA methylation in DA neurons of the nigrostriatal pathway, which have been the subject of much of this work on VGLUT2 in the context of PD. However, the observed hypomethylation in the SLC17A6 gene in the parietal cortex suggests that this locus could show altered epigenetic regulation of gene expression during disease progression. Given the known neuroprotective role for VGLUT2, future studies should examine whether epigenetic changes at SLC17A6 are associated with decreased VGLUT2 expression and increased neuronal susceptibility.In females, we identified PD-related hypomethylation within the dy Figs. –4. SLC17PTPRN2 gene—showed exact, complete overlap in both males and females , which is expressed on dense core and synaptic vesicles. Altered methylation of this gene has been previously implicated in PD in a study of longitudinal blood samples that showed an association between hypomethylation of a different CpG within the PTPRN2 gene in whole blood and faster motor progression in PD73. In addition, deletion of this gene and the related IA-2 protein in mice leads to reduced levels of norepinephrine, dopamine (DA) and serotonin in the brain and decreased release of DA, gamma-aminobutyric acid (GABA), and glutamate from synaptosomes74. One previous study found decreased expression of PTPRN2 in the SN of PD patients, while another found increased expression in DA neurons from PD patients with LRRK2 G2019S mutations76. Interestingly, given the known role of environmental exposures in PD and work in our lab investigating pesticide exposures and PD77, another study found an association between pesticide exposure and hypomethylation at a CpG in PTPRN2 in blood78. The opposite directionality of the relationship between PTRPN2 DNA methylation and PD status in males and females suggests that differential epigenetic regulation may be important in sex differences in PD.In our regional analysis, one DMR—annotated to the nts Fig. . PTPRN2 PLXNB1, PLXNC1, and PLXNB3, three genes that encode proteins in the plexin family, which act as transmembrane receptors for the semaphorins. The semaphorin-plexin signaling pathway is a key regulator of morphology and motility in many different cell types, including those that make up the nervous system, and is known to play a role in axon guidance80. As with our gene-specific results, the sex-specificity of these networks is striking and reinforces that epigenetic regulation in PD is highly sex-specific and may contribute to the known sex differences in PD.In addition to our gene-level differences, pathway analysis of differentially methylated genes identified distinct enriched pathways in male and female subjects Fig. . Female-83. Based on this, researchers have established epigenetic clocks that use loci with the most predictable DNA methylation levels to provide estimates of epigenetic  age81. In a previous study using one of these epigenetic clocks, researchers found accelerated epigenetic aging in PD blood samples compared to control45. However, to our knowledge, no studies have tested whether epigenetic aging is accelerated in PD brain tissue. Here, we used an epigenetic clock specifically designed for human cortical tissue to estimate epigenetic age of control and PD parietal cortex samples84. In our analyses, we showed that our epigenetic clock was well-calibrated to predict chronological age at death, but found no evidence of significant epigenetic age acceleration by PD status in our cohort , but WGBS remains cost-prohibitive to scale up for a large cohort, making it unfeasible for this project. Although our study had a sample size smaller than recent recommendations published by Mansell et al after sex stratification, we experimentally controlled for multiple variables, including sex, race, and age, which were included as covariates in their estimates48. This increases our statistical power relative to the proposed minimum sample size, but future studies should include larger cohorts or be combined with publicly available data. Finally, we only analyzed the neuron-enriched population from our MACS-sorted samples. Given the growing body of evidence supporting the importance of non-neuronal cell types in PD, future work will aim to carry out similar analyses in neuron-depleted samples.Our study provides a genome-wide analysis of DNA methylation in an enriched neuronal population from both male and female PD brain tissue. Despite our study design’s strengths, there remain some limitations in our analysis that create opportunities for future studies. First, our results do not distinguish between DNA methylation and DNA hydroxymethylation, which show distinct genomic distributions and associations with gene expression in the brain, as well as differential responses to environmental exposuresDespite our experimental limitations, this study provides a genome-wide analysis of DNA methylation in enriched neurons from male and female human postmortem brain tissue. Results from this work support the idea that epigenetic regulation is an important mechanism in PD pathogenesis and point to specific genes and pathways for further study.+) nuclei were enriched from 100 mg of flash frozen parietal cortex tissue using a two-stage magnetic-assisted cell sorting (MACS) method. First, 100 mg of frozen tissue were briefly thawed on ice and homogenized in a 2 mL, 1.4 mm ceramic bead tube  with 1 mL of Nuclear Extraction Buffer (NEB) for 10 s at 4 m/s. NEB consisted of 0.32 M sucrose, 0.01 M Tris-HCl pH 8.0, 0.005 M CaCl2, 0.003 M MgCl2, 0.0001 M EDTA, and 0.1% Triton X-100, up to a stock volume of 1 L using water. Immediately prior to use, 0.001 M DTT was added to NEB. Homogenized samples were loaded into a 13 mL ultracentrifuge tube  with 4 mL of NEB. Using a glass pipette, 7 mL of sucrose solution was pipetted down the side of each sample tube to create a sucrose gradient. Sucrose solution consisted of 1.8 M sucrose, 0.01 M Tris-HCl pH 8.0, 0.003 M MgCl2, up to a stock volume of 1 L using water. Immediately prior to use, 0.001 M DTT was added to NEB. After addition of sucrose, samples were spun at 4 °C, 24,000 rpm in the Sorvall Wx+ Ultracentrifuge in a swing bucket rotor (TH-641). Once the centrifugation was complete, the supernatant and debris layer found at the concentration gradient were both removed with the use of a vacuum, while being careful not to disturb the pellet containing the nuclei at the bottom of the tube. Next, 1 mL of primary antibody  in MACS buffer was added to each nuclei pellet and placed on ice for 10 min. MACS buffer consisted of 0.5% Bovine Serum Albumin solution  in PBS pH 7.2 . Samples were then mechanically pipetted up and down 10–15 times to completely dissolve the nuclei pellet within the primary antibody-MACS buffer solution. This solution of nuclei was then transferred to a 2 mL tube and incubated for 60 min at 4 °C. After incubation, 40 µL of MACS Microbeads  were added to each sample. Samples were then inverted 4–5 times and incubated at 4 °C for 30 min. After incubation, nuclei were centrifuged at 300g for 10 min. Supernatant was then removed, and the nuclei were resuspended in 2 mL of MACS buffer and transferred to a MACS MS column  that was pre-washed with MACS buffer and attached to the Miltyeni OctoMACS™ Separator. Positive selection of NeuN+ cells was then performed according to the standard MACS MS Columns protocol available from Miltenyi Biotec. After the first round of magnetic separation, NeuN+ nuclei were run through a separate, second MACS MS column to maximize cell type enrichment.De-identified parietal cortex samples were obtained from BSHRI. NeuN-positive , and data were analyzed using FlowJo V10. Single nuclei were identified by the presence of DAPI staining in a plot of 405–450/45-width signal vs 405–450/45-area signal. These nuclei were then analyzed for NeuN expression by looking for A488 fluorescence in the 488–525/40 channel. Determination of A488 positivity was made by comparing to a sample stained only with DAPI to define the background. Percent positivity for each sample was defined as the percentage of events in the NeuN-A488 + gate, divided by the total number of events identified as Nuclei.+ nuclei using the Qiagen QIAamp DNA Micro Kit (Cat. # 56304), with some modifications to maximize yield. Given that samples were already homogenized during nuclei isolation, the sample lysis and incubation steps of the QIAamp DNA Micro Kit protocol were removed. Instead, 20 uL of proteinase K were added directly to each MACS eluate. Samples were then vortexed for 15 seconds and incubated at room temperature for 15 min. In addition, the optional carrier RNA was added to Buffer AL, the incubation time after the addition of 100% ethanol was increased to 10 min, the incubation time for the elution buffer was increased to 5 min, and the final elution step was repeated using 10 mM Tris-HCl pH 8.0.DNA was isolated from enriched NeuNIntact genomic DNA yield was quantified by Qubit fluorometry (Life Technologies). Bisulfite conversion was performed on 500 ng genomic DNA using the TrueMethyl Array kit (Cambridge Epigenetix). All conversion reactions were cleaned using SPRI-bead purification and eluted in Tris buffer. Following elution, BS-converted DNA was denatured and processed through the EPIC array protocol. The EPIC array contains ~850,000 probes that query DNA methylation at CpG sites across a variety of genomic features, including CpG islands, RefSeq genic regions, ENCODE open chromatin, ENCODE transcription factor binding sites, and FANTOM5 enhancer regions. To perform the assay, converted DNA was denatured with 0.4 N sodium hydroxide. Denatured DNA was then amplified, hybridized to the EPIC bead chip, and an extension reaction was performed using fluorophore-labeled nucleotides per the manufacturer's protocol. Array BeadChips were scanned on the Illumina iScan platform.minfi (version 1.22.1), ChAMP (version 2.14.0), posibatch (version 1.0), ENmix (version 1.12.4), CETS (version 3.03), and dplyr (version 1.0.8) packages in R. Quality control was assessed for internal control probes using the ENmix plotCtrl function. Failed probes were identified as those with a detection p-value > 0.01 in any sample. Failed probes were then removed from downstream analyses when detection p-value was > 0.01 in >5% of samples. No samples exceeded the selected threshold of failed probes (>10%) to warrant removal prior to analysis. Cross-reactive probes and probes containing SNPs were removed based upon previous identification90. After removal of technical artifacts, dye-bias correction was performed with ssNoob within minfi91. The proportion of neuronal vs. glial cells in each sample was estimated with CETS92. Samples with estimated glial cell to neuronal cell proportion > 0.90 were removed from analysis. This removed one sample from the male data set, leaving n = 62 males. Batch effects were assessed using the ChAMP package93, and then a beta value matrix for all samples was corrected for batch and positional effects using the posibatch R package94. After beta value estimation, we filtered out samples with mean DNA methylation beta value < 0.01. This beta value cutoff was instituted due to increased variability and decreased interpretability of beta values at such low levels. As a final step, we removed probes that were not annotated to a gene in the Illumina EPIC array manifest to ensure the interpretability of results after modeling. After all filtering steps, 552,332 probes remained for differential DNA methylation testing in the sex-stratified datasets. Code for data processing, filtering, and modeling is available  R package was used to test for differentially methylated CpGs (DMCs)95. This package provides functions to perform multivariate regression modeling while maintaining flexibility regarding term structure and distribution. For DMC testing, we assumed a normal distribution (standard linear regression model) and included both the mu (mean) and sigma  in models to test for differences in the mean by disease state while accounting for potential differences in variability. Linear regression was used in lieu of negative-binomial or beta regression modeling due to recent work showing that linear regression does not increase the likelihood of false positives in EPIC array-based epigenome-wide association studies48. All models were stratified by sex, and age and estimated glial cell proportion were included as covariates. Sex stratification was performed in response to a skewed, non-uniform p-value histogram that was produced by an initial model that simply included a covariate to adjust for sex . Annotation of detected differential probes was performed using the Illumina EPIC array manifests. Code for data processing, filtering, and modeling is available as supplementary files.An unadjusted DMRcate R package (version 2.8.5) was used to test for differentially methylated regions97. In this package, the model matrix was established using the following code: design = model.matrix(~factor(disease) + glial_cell_proportion + age). For DMR analysis, Lamba was set to 1000 and the minimum number of CpGs was set to 2. All models were stratified by sex, and both age and estimated glial cell proportion were once again included as covariates in the modeling. The Benjamini–Hochberg False Discovery Rate (FDR) method was used to generate minimum smoothed q-values that account for multiple testing98. For the regional analysis, the significance cutoff was set at a minimum smoothed FDR q-value < 0.05.The clusterProfiler R package (version 4.2.2) was used to determine whether differentially methylated genes were enriched for specific gene ontology biological process (GOBP) pathways99. Specifically, the enrichGO function was used to run hypergeometric over-representation tests on lists of differentially methylated gene IDs. Gene ID lists were split into hypermethylated DMCs or DMRs and hypomethylated DMCs or DMRs prior to analysis. The list of genes with annotated probes in the EPIC array manifest was used as the universe of total tested genes. Separate, sex-stratified analyses were performed for genes annotated to DMCs and DMRs. GOBP pathway enrichment analysis was not performed on male DMCs due to the low number of significant CpGs (n = 3). For enrichment analyses in clusterProfiler, redundant pathways were consolidated using the simplify function with default parameters, and significance cutoff was set at FDR q-value < 0.05.The 84. Estimates of epigenetic age (years) and known age at death (years) were then compared using standard linear regression with an age*disease interaction term. The interaction term was used to determine whether categorical PD status (control vs. PD) altered trajectories of epigenetic age compared to known chronological age. Epigenetic age regression modeling was performed on all data combined, as well as sex-stratified data. For these regression analyses, significance was set at p-value < 0.05.Epigenetic age was estimated for all parietal cortex samples using a recently published algorithm designed specifically for the human cortexFlow cytometry plotsMale DMCsFemale DMCsMale DMRsFemale DMRsGOBP terms for hypomethylated DMRsp-value histogramsR markdown for EPIC array processingknitted htmlR markdown for modeling