A Mediterranean-style eating pattern is consistently associated with a decreased diabetes risk in Mediterranean and European populations. However, results in U.S. populations are inconsistent. The objective of this study was to assess whether a Mediterranean-style eating pattern would be associated with diabetes risk in a large, nationally representative U.S. cohort of black and white men and women.n = 11,991) were included . Alternate Mediterranean Diet scores (aMed) were calculated using the mean dietary intake self-reported at visit 1 and visit 3 (1993–1995) or visit 1 only for participants censored before visit 3. Participants were followed from visit 1 through 31 December 2016 for incident diabetes. We used Cox regression models to characterize associations of aMed (quintiles as well as per 1-point higher) with incident diabetes adjusted for energy intake, age, sex, race and study center, and education (Model 1) for all participants then stratified by race and body mass index (BMI). Model 2 included potential mediating behavioral and clinical measures associated with diabetes. Results are presented as hazard ratios and 95% confidence intervals.Participants from the Atherosclerosis Risk in Communities study prospective cohort without diabetes, cardiovascular disease, or cancer at baseline  and 0.96 (0.95–0.98) for 1-point higher]. Associations were stronger for black vs white participants (interaction p < 0.001) and weaker for obese vs normal BMI (interaction p < 0.01). Associations were attenuated but statistically significant in Model 2.Over a median follow-up of 22 years, there were 4024 incident cases of diabetes. Higher aMed scores were associated with lower diabetes risk [Model 1: 0.83 (0.73–0.94) for Q5 vs Q1 (An eating pattern high in fruits, vegetables, whole grains, legumes, nuts, and fish, and moderate in alcohol was associated with a lower risk of diabetes in a community-based U.S. population. While there are cultural variations in the foods and beverages included in a Mediterranean pattern, overall it is largely plant-based, relatively high in olive oil and seafood, but low in dairy, red meat, and refined grains4. Observational and experimental studies suggest that higher adherence to a Mediterranean pattern is associated with improved cardiovascular disease risk factors7, reduced risk of cardiovascular events9, and reduced cardiovascular-related mortality10. The American Diabetes Association recommends adherence to a Mediterranean pattern, as one of several potential strategies, to prevent cardiovascular complications in individuals with diabetes. However, evidence regarding how Mediterranean pattern adherence can improve diabetes risk for U.S. populations is inconsistent11.A Mediterranean-style eating pattern (Mediterranean pattern) is one of the eating patterns recommended by the American Heart Association, American College of Cardiology, and the Dietary Guidelines for Americans to reduce chronic disease risk11. Mediterranean and European populations tend to be less racially and ethnically heterogeneous, have lower body mass indexes (BMI), be less sedentary, have larger social networks, and place a greater emphasis on rest and sleep compared to the general U.S. population13. In Mediterranean and other European settings, adherence to a Mediterranean pattern is consistently associated with a reduced risk of diabetes16. Yet, research about Mediterranean pattern adherence and diabetes risk in U.S. populations is limited and inconsistent11. Research is needed to assess whether potential benefits of a Mediterranean pattern are translatable to heterogeneous populations which place less emphasis on ideologies and behaviors of Mediterranean-like cultures. Further, benefits may vary by race and BMI. Being of a minority race and having a BMI > 25 kg/m2 are among the top recognized risk factors for diabetes in the U.S. and eating habits differ within these groups17.It is unclear if a Mediterranean pattern, independent of a Mediterranean lifestyle, can reduce diabetes risk in US adult populations17.The purpose of this study was to assess associations between Mediterranean pattern scores and incident diabetes in a U.S. community-based population of adults. We also explored consistency of associations within racial and BMI subgroups18. Investigators originally recruited middle-aged adults  from four U.S. communities  and performed baseline assessments in 1987–89 (visit 1). Participants returned for follow-up visits in 1990–92 (visit 2), 1993–95 (visit 3), 1996–98 (visit 4), 2011–13 (visit 5), 2016–17 (visit 6), and 2018–18 (visit 7). Each participating institution received ethical approval from an institutional review board and all participants provided informed consent at each visit. This study has been registered with clinicaltrials.gov (NCT00005131).We used data collected from participants in the Atherosclerosis Risk in Communities (ARIC) study. The primary aim of the ARIC study was to investigate atherosclerosis etiology and clinical sequelae as well as to assess how cardiovascular disease risk factors differ by race, sex, place, and timen = 3318); (2) implausible energy intake  derived from food frequency questionnaire (FFQ) responses or ≥10 missing FFQ items (n = 270); (3) participants identified as Asian (n = 28) or Indian (n = 14) due to small sample size; (4) participants identified as black from Maryland (n = 25) and Minnesota (n = 19) due to inability to decipher the influence of geographic region versus race with small samples19; (5) missing baseline covariates (n = 20); (6) missing follow-up time; and (7) missing food items needed to calculate the Mediterranean pattern score (n = 63).The total sample size for this analysis was 11,991 participants , 1 point for self-reported consumption below the cohort’s sex-specific median intake for red and processed meat, and 1 point for self-reported alcohol intake between 5–15 g/day for females and 10–25 g/day for males. Scores range from 0 to 9 points; higher scores presume higher adherence to a Mediterranean pattern. Designation of ARIC FFQ items for the aMed scoring system is provided in Supplementary Table Alternate Mediterranean Diet (aMed) scores, previously developed to assess Mediterranean pattern adherence in U.S. populations23. Participants who did not develop diabetes were censored for death, loss to follow-up, or administratively censored on 31 December 2016.Incident diabetes cases were identified according to the following criteria: (1) self-reported physician diagnosis, (2) self-reported use of diabetes-related medication during previous 2 weeks, (3) measured fasting blood glucose concentration ≥126 mg/dL, or (4) measured non-fasting blood glucose concentration ≥200 mg/dL. Self-reported physician diagnosis or self-reported diabetes medication usage was ascertained at study visits and via annual follow-up phone calls between study visits and after visit 4. This definition of incident diabetes has high specificity25. Height and weight were measured via standard protocols and BMI was calculated as body weight in kilograms divided by height in meters squared. Seated blood pressure was measured in triplicates separated by resting for 5 minutes with a random-zero sphygmomanometer. The mean of the second and third measurements was used in the analysis. Hypertension status was determined using the 2003 National Heart, Lung, and Blood Institute guidelines26, defined as systolic blood pressure ≥140, diastolic blood pressure ≥90 mm Hg, or current use of anti-hypertensive medication. All biomarkers measurement methods have been previously described and all ARIC protocols are available at https://sites.cscc.unc.edu/aric/cohort-manuals.Age, race, education level , smoking , and family history of diabetes  were ascertained via questionnaires at visit 1. A race-center variable was derived to represent whites and blacks at each study center. Physical activity was measured via the Baecke questionnaire, which converts self-reported physical activity from sports, leisure, and work into a 1–5 point scoreWe compared visit 1 participant characteristics and eating patterns according to aMed quintiles. We used Cox proportional hazards regression models to estimate hazard ratios (HR) and corresponding 95% confidence intervals (CI) for associations between aMed scores (according to quintiles and per 1-point higher) and incident diabetes. We tested for linear trends across quintiles by modeling quintiles as an ordinal variable. We tested for linear splines (a knot at 2 points was significant) to visually depict the shape of the relationship between aMed scores and risk of incident diabetes across the full range of aMed scores. In addition to analyzing overall aMed scores, associations between individual aMed components and incident diabetes were assessed. Follow-up time in days from study visit 1 was used as the time metric. The proportional hazard assumption was assessed via log-log plots and Schoenfeld’s residual tests. Stata version 15 statistical software was used for all analyses .Three covariate structures were used in the Cox regression analyses. Model 1 was adjusted for energy intake and demographic variables of age, sex, race-center, and education level. Model 2 included all variables in Model 1 plus behavioral variables associated with risk of developing diabetes, including smoking status and physical activity. Model 3 included all variables in Model 2 plus potential clinical mediators of diabetes including fasting glucose (mg/dL), hypertension status (yes/no), low-density lipoprotein cholesterol (mg/dL), BMI category , and family history of diabetes (yes/no) to test for a potential direct association between aMed scores and incident diabetes.27 and baseline BMI28 were chosen a priori as potential effect modifiers. Sex and education level effect modifiers were assessed post hoc. Likelihood ratio tests were used to assess interaction by categorical BMI , race (with adjustment for center rather than race-center), educational level, and sex on associations between continuous aMed scores and incident diabetes as well as quintiles of aMed and incident diabetes. If the p-value for interactions were significant (p < 0.05) using Model 1, we then conducted stratified analyses with Models 1, 2, and 3.RaceParticipants in higher aMed score quintiles were qualitatively more likely to have a higher education, have a higher physical activity level, were less likely to be current smokers and less likely to be obese compared to participants in lower aMed score quintiles Table . Age, seParticipants in higher quintiles of aMed scores had qualitatively higher intakes of total energy, percent of energy from carbohydrates, and percent of energy from protein compared to participants in lower aMed score quintiles Table . Percentp < 0.001) after controlling for energy intake and socio-demographic factors  and legumes [Model 1 HR (95% CI): 0.92 (0.86–0.98)], representing intake above sex-specific medians, and higher component scores for alcohol [Model 1 HR (95% CI): 0.83 (0.75–0.91)], representing moderate intake, were associated with a lower risk of incident diabetes after adjusting for total energy intake and socio-demographic factors. Higher component scores for red and processed meat (Model 1 HR (95% CI): 0.91 (0.84–0.97)], indicating intake below the sex-specific median, was also associated with lower risk of incident diabetes. Component scores for whole grains, vegetables, fruits, MUFA:SFA, and fish were not independently associated with diabetes risk. Results were similar for Model 2 but only alcohol remained significant in Model 3 [HR (95% CI): 0.81 (0.74–0.90)]. Results were similar when all aMed components were included in the models.Higher Mediterranean-style eating pattern scores were inversely associated with risk of incident diabetes in this prospective cohort study of 11,991 middle-aged U.S. adults followed for a median of 22 years. The results were attenuated but persisted after additional adjustment for health behaviors and clinical factors related to diabetes risk. Associations between aMed scores and incident diabetes were stronger among black compared to white participants, were stronger for normal weight compared to overweight or obese participants, and were not different for males and females. Higher nut and legume intake, moderate alcohol intake, and lower red and processed meat intake were the main drivers of the noted associations.n = 41,615)29. In a smaller but more ethnically diverse U.S. cohort, the Multi-Ethnic Study of Atherosclerosis , there was no association between Mediterranean pattern scores and diabetes risk in the overall population or within racial subgroups30. The larger sample size of the ARIC study allowed for more precise white vs black comparisons than these prior studies. We found stronger associations between Mediterranean pattern adherence and incident diabetes for black compared to white participants. This is contrary to previous research which showed inverse associations between a Dietary Approaches to Stop Hypertension-style eating pattern and diabetes risk only for white individuals in a cohort that was comprised largely of black and Hispanic individuals31. There is a need for follow-up research regarding the finding that black individuals may particularly benefit from adherence to a Mediterranean pattern because of the high risk of diabetes in this racial subgroup27.Associations between Mediterranean pattern scores and diabetes risk in U.S. cohorts are inconsistent. We found that Mediterranean pattern scores are associated with a lower risk of diabetes in a U.S. population of blacks and whites by up to 17%. Diabetes risk reductions (up to 25%) associated with Mediterranean pattern scores were previously noted in a cohort of mostly white high socioeconomic U.S. men 4. The higher quintiles in this study reported lower total fat and saturated fat intakes than the lower quintiles with limited variability in mono- and polyunsaturated fat across quintiles. To note, about half of monounsaturated fatty acids consumed by U.S. populations come from red meat, not olive oil. The associations noted between aMed scores and diabetes risk in this study are not applicable to a traditional high total and monounsaturated fat (from olive oil) Mediterranean pattern. Switching to a high-fat eating pattern of any kind could potentially cause weight-gain and increase diabetes risk because all fat types are energy dense40.The ARIC FFQ was not a priori designed to assess adherence to a Mediterranean pattern. The FFQ contains no questions about olive oil intake, which is the main staple of a Mediterranean pattern. Further, limited variation in fruit, vegetable, and whole-grain eating habits of U.S. populations, as well as the lack of adequate whole-grain related FFQ questions, may not be sufficient to correctly identify independent associations with diabetes. Due to the aMed rank-based scoring system used to assess Mediterranean pattern adherence, no quintile met commonly recommended food group intake thresholds of a more traditional Mediterranean patterns for nuts, fats, vegetables, or whole grains23. Although type 1 vs type 2 diabetes cases were indistinguishable via these ascertainment methods, 90–95% of diabetes cases in the U.S. are type 2 diabetes41. Further, type 2 diabetes most often presents in individuals over the age of 4541. We excluded diabetes cases at baseline and participant age at enrollment was >45 years. Therefore, it is assumed that incident diabetes cases in this sample are largely type 2 diabetes. Further, while dietary intake assessments were self-reported, using the average of two measurements (visit 1 and visit 3) is expected to reduce measurement error and increase precision of exposure-outcome associations42. The temporal nature of assessing Mediterranean pattern adherence at baseline with a median of 22 follow-up years is another strength of this study.Our study can address previously noted gaps in the literature about eating patterns and chronic disease risk. The observed inverse associations between Mediterranean pattern adherence and incident diabetes may be more precise and generalizable to the U.S. population than previous studies because the ARIC study is a large cohort of both men and women, and blacks and whites, representing four different U.S. regions. We also used a highly sensitive measure of incident diabetes , although largely self-reportedUnmeasured and residual confounding in observational studies can remain after multivariable adjustments. Specifically, associations between Mediterranean pattern adherence and diabetes were negated in participants who were overweight or obese. However, energy intake was highest in the fifth quintile with limited variation in BMI and physical activity across quintiles. Energy calculations from food frequency questionnaires tend to be unreliable and there was no objective measure of energy intake (such as doubly labeled water) used in the ARIC study to validate the energy intake reported in Table An eating pattern high in fruits, vegetables, whole grains, legumes, nuts, and fish, and moderate in alcohol, similar to the Mediterranean-style eating pattern assessed in this analysis and recommended by the 2015–2020 Dietary Guidelines for Americans, was associated with an overall lower risk of diabetes in a community-based U.S. population. This association was particularly strong for black and normal weight individuals but was absent for individuals who were overweight or obese. Increased awareness and promotion of healthy eating patterns for diabetes prevention in predominantly black communities may reduce disease burden. Future research is needed to assess if a calorically restrictive Mediterranean-style eating pattern, resulting in clinically meaningful weight loss, can reduce future diabetes risk in individuals who are overweight or obese. Adhering to a healthy eating pattern is an important component of an overall healthy and active lifestyle to obtain and maintain a healthy body weight and to reduce risk of adult-onset diabetes for the U.S. population.Supplemental Table S1-S4, Supplemental Figure S1


Escherichia coli (E. coli) strains harbored in the human large intestine. This polyketide-peptide genotoxin is considered to contribute to the development of colorectal cancer. The colibactin-producing (clb+) microorganisms possess a 54-kilobase genomic island (clb gene cluster). In the present study, to assess the distribution of the clb gene cluster, genotyping analysis was carried out among E. coli strains randomly chosen from the Japan Collection of Microorganisms, RIKEN BRC, Japan.Colibactin is a small genotoxic molecule produced by enteric bacteria, including certain clb gene cluster. These clb+ strains JCM5263 and JCM5491 induced genotoxicity in in vitro micronucleus (MN) tests using rodent CHO AA8 cells. Since the induction level of MN by JCM5263 was high, a bacterial umu test was carried out with a cell extract of the strain, revealing that the extract had SOS-inducing potency in the umu tester bacterium.The analysis revealed that two of six strains possessed a clb gene cluster is widely distributed in nature and clb+E. coli having genotoxic potencies is not rare among microorganisms.These results support the observations that the  Enterobacteriaceae, including certain Escherichia coli (E. coli) strains harbored in the human gut, and is involved in the etiology of colorectal cancer. The colibactin-producing (clb+) microorganisms possess a 54-kilobase genomic island (clb gene cluster) encoding polyketide synthases (PKSs), nonribosomal peptide synthetases (NRPSs), and PKS-NRPS hybrid megasynthetases [clb+E. coli strains, resulting in generation of gene mutations [clb+E. coli stimulates growth of colon tumors under conditions of host inflammation, and is found with increased frequency in inflammatory bowel disease, familial adenomatous polyposis, and colorectal cancer patients [E. coli strains isolated from a Japanese colorectal cancer patient produced colibactin and showed genotoxicity in in vitro assays [clb gene cluster among microorganisms have not been fully clarified yet.Colibactin is a small genotoxic molecule produced by thetases . Nougayrutations . The clbpatients , 3. We pclb gene cluster among E. coli strains randomly chosen from the Japan Collection of Microorganisms, with genotyping of the gene cluster. To evaluate the association between presence of the cluster and genotoxicity, we examined the genotoxicity/clastogenicity of these E. coli strains in rodent cells using the in vitro micronucleus (MN) test. Using the umu test, DNA damage in a bacterial tester strain treated with crude extracts of the E. coli was also evaluated.The present study aimed to assess the distribution of the E. coli strains (Escherichia coli (Migula 1895) Castellani and Chalmers 1919) were randomly chosen and purchased from the Japan Collection of Microorganisms at the microbe division of the RIKEN BioResource Research Center , which is participating in the National BioResource Project of the MEXT, Japan. E. coli Nissle 1917 strain was obtained from Mutaflor, Ardeypharm, GmbH. , and used as a clb+ strain [E. coli ZA227 used in the umu test was kindly supplied by Dr. Mie Watanabe-Akanuma . PCR analysis and electrophoresis for genotyping of the clb+ gene cluster was carried out with the oligonucleotide primers, as previously reported [E. coli genomic DNA was purified with MonoFas DNA Purification Kit V . Library construction and paired-end sequencing were carried out using the Miseq  with the Miseq reagent kits v2 (300 cycles). The raw sequence data were mapped by the HISAT2 program  to the genome of Nissle1917 (GCA_000714595.1) as a reference sequence. The mapped files were converted to bam files by using SAMtools , and the read coverages were generated by StringTie  and the heatmap was constructed using the CIMminer program .Six i Migula 895 Castereported . For gen5 cells/dish) were seeded in ϕ60 mm plastic cell culture dishes 1 day before the infection procedure. The bacteria were cultured until OD595 = 0.5 at 37 °C in Infection Medium (IM)  + 25 mM HEPES, 5% fetal bovine serum ). The infection was carried out with 3 mL of IM containing E. coli at the indicated multiplicity of infection (MOI) (number of bacteria per cell at the onset of infection). After being treated with bacteria for 4 h, the CHO cells were cultured for a further 20 h in cell culture medium supplemented with 200 μg/mL gentamicin . The MN test was then performed, and the number of cells with MN was recorded based on the observation of 1000 interphase cells. Relative cell growth was calculated using the formula:Bacterial infection to Chinese hamster ovary (CHO) AA8 cells and the MN test were carried out as previously described . Brieflyumu test, as previously described [E. coli cells were harvested from 10 mL of overnight culture in LB media (O.D. = 1.7–2) by centrifugation, and extracts of E. coli were prepared with 1 mL of BugBuster protein extraction reagent . The cell lysates were collected by centrifugation at 16,000×g for 20 min at 4 °C. The umu assay using ZA227/pSK1002 tester strain was conducted as previously reported [E. coli K-12, which dose not posses the clb gene cluster [clb+E. coli strains were incubated for 3 h at 37 °C. As a solvent and positive controls, 20 μL of BugBuster solution and 10 μL of 1 μg/mL 4-nitroquinoline 1-oxide (4-NQO)  were used, respectively.The DNA damaging potency of bacterial cell extracts was estimated using the escribed . BrieflyO.D. = 1.–2 by cenclb genes, i.e., 16 clb genes  by detecting each amplicon after PCR with specific primer sets to the genes. As a positive control strain, we analyzed the known clb+ strain Nissle 1917, which is a commensal strain also widely used as a probiotic treatment for intestinal disorders [clb genes  and 24%, respectively. JCM5491 and JCM20114 were hemolysin-positive strains (data not shown), therefore, their high cytotoxicity might be involved in hemolysin. Since the MN test cannot be performed under such highly-cytotoxic conditions, we tried lower-MOI treatments and found that at MOI = 6.25, JCM5491 induced MN with frequency 2.5-fold greater than that at MOI = 0  for induction of an SOS response in the umu test. The extracts were prepared using BugBuster reagent, which disrupts the cell walls and liberates the cytosol. Increased SOS responses were observed in the extracts of clb+ from both JCM5263 and Nissle 1917 compared with that of clb− JCM1649T  exhibited MN induction in CHO cells. The cell extracts of JCM5263 and Nissle 1917 also had DNA-damaging potency in a bacterial umu test. These results support the observations that clb gene clusters are widely distributed in nature and that clb+E. coli, which has genotoxic potency, is not rare among microorganisms.Genotyping analysis revealed that two of six


Rhodobiaceae and Rhodobacteraceae families of Alphaproteobacteria, and unidentified members of the Candidate division Parcubacteria. Tolerant taxa, whose abundance increased significantly with higher TCS concentrations, include the families Erythrobacteraceae (Alphaproteobacteria), Flavobacteriaceae (Bacteroidetes), Bdellovibrionaceae (Deltaproteobacteria), several families of Gammaproteobacteria, and members of the Candidate phylum Gracilibacteria. Our results demonstrate the variability of TCS sensitivity among bacteria, and that TCS can change marine bacterial composition at concentrations that have been detected in the marine environment.The antibacterial agent Triclosan (TCS) is a ubiquitous environmental contaminant due to its widespread use. Sensitivity to TCS varies substantially among eu- and pro-karyotic species and its risk for the marine environment remains to be better elucidated. In particular, the effects that TCS causes on marine microbial communities are largely unknown. In this study we therefore used 16S amplicon rDNA sequencing to investigate TCS effects on the bacterial composition in marine periphyton communities that developed under long-term exposure to different TCS concentrations. Exposure to TCS resulted in clear changes in bacterial composition already at concentrations of 1 to 3.16 nM. We conclude that TCS affects the structure of the bacterial part of periphyton communities at concentrations that actually occur in the marine environment. Sensitive taxa, whose abundance decreased significantly with increasing TCS concentrations, include the  Triclosan -phenol, CAS 3380-34-5) is an antibacterial agent commonly used in personal care products (PCP), household cleaning products, textiles, and plastics. The annual usage of TCS and has been estimated at 300 tons in USA in 2005  reductase  glass slides mounted vertically in polyethylene holders. Prior to periphyton establishment, the discs were boiled for 10 min in concentrated nitric acid, rinsed in de-ionized water, and rinsed again in 70% ethanol. The seawater flow rate in the microcosms was 220 mL min−1 giving a mean residence time of approximately 90 min. TCS solutions were made in de-ionized water by adding TCS dissolved in acetone. These TCS solutions, containing 1 permille acetone (v/v), were pumped into the system at a dilution factor of 119 times, creating constant TCS nominal exposures of 0, 0.316, 1, 3.16, 10, 31.6, 100, 316, and 1000 nM. The same amount of de-ionized water, with the same amount of acetone, but without TCS was pumped into the control microcosms. The study thus had a concentration-response experimental design based on 13 replicates sampled from seven different concentrations of TCS , are reported in Eriksson et al. . In shorCS Table . TherefoCS Table .Table 1R2) per microcosm into filter-sterilized water from the respective microcosm. The biofilm material was pelleted by centrifugation at 15,000 g for 8 min, snap-frozen in liquid nitrogen, and stored at −80 °C. DNA extraction was performed using the FastDNA spin kit for soil  due to the high extraction yield obtained with this kit , samples were pooled in equimolar amounts. The pooled samples were sequenced at the SciLifeLab SNP/SEQ next generation sequencing facility  using Illumina MiSeq with a 2 × 300 bp chemistry following the protocols of the manufacturer.The raw sequence data were analyzed with a pipeline for de-multiplexing and sequence-pair assembly implemented in Python . Differentially abundant OTUs were identified using the DESeq2 R package. Two types of analyses were implemented: (i) pair-wise analysis between the untreated controls and the samples that were exposed to 3.16, 31.6, and 316 nM TCS, and (ii) regression analysis between OTU counts and TCS concentration using all 13 samples. The resulting p values were adjusted for multiple testing according to Benjamini-Hochbergs false discovery rate (FDR). OTUs with an FDR of less than 0.05 were considered statistically significant. In the pair-wise analysis, overrepresented taxa among the significant OTUs (FDR < 0.05) were tested using Fishers’ exact test at the phylum, class, order, and family levels. Venn diagrams were used to describe the overlap of the significantly different OTUs between concentrations. All analyses were performed in the statistical language R version 3.4 . This pattern is confirmed in the Principal Component Analysis (PCA)  Fig. . MoreoveCA) Fig.  and 2.FiThe relative abundance of a total of 164 OTUs was significantly affected (FDR < 0.05) by an exposure to 3.16, 31.6 or 316 nM TCS (Supplementary Table 3). The number of significantly affected OTUs increased with TCS concentration Fig. . 10 of tParcubacteria decreased substantially at a concentration as low as 1 nM , and 316 nM (p = 0.0027) TCS, respectively. The Candidate division Parcubacteria, also called OD1, is a diverse group of bacteria, suggested to constitute a superphylum -generating compound tellurite, and TCS is well known for its ROS-mediated toxic effects in various organisms , and at 316 nM the abundance of 61, 36, and 22% of the OTUs in Alteromonadaceae, Oceanospirillaceae, and Thiotrichaceae were significantly increased. These taxonomic groups were favored only at higher concentrations of TCS . Although Pseudomonas aeruginosa belongs to Pseudomonadales, i.e. a different gammaproteobacterial order, it is worth noting that P. aeruginosa is intrinsically resistant to TCS. This resistance is believed to originate from efflux pumps, but Zhu et al.  of TCS. It is, however, currently not known to what extent other Gammaproteobacteria carry a TCS-resistant fabV gene. As reviewed by Carey and McNamara . It is possible that ecological interactions changed at intermediate TCS concentrations, favoring these taxa. For example, Verrucomicrobia can be symbionts with ciliates  and found that the overall bacterial density and community composition of 16S in a marine biofilm was affected at a high TCS concentration of 1000 nM, but that the taxa Alphaproteobacteria and Gammaproteobacteria were affected already at 10 nM. In the present study, we identified Alphaproteobacterial taxa at lower taxonomic levels to be TCS-sensitive  are particularly sensitive to TCS while Gammaproteobacteria , Flavobacteria (primarily Flavobacteriaceae), the Candidate division Gracilibacteria, the deltaproteobacterial family Bdellovibrionaceae, and the alphaproteobacterial family Erythrobacteraceae are more tolerant to TCS exposure. The results show that TCS affects marine microbial communities at low nanomolar concentrations, which are close to those found in the marine environment (Pintado-Herrera et al. We identified clear changes in community composition at 10 nM TCS, but effects on specific taxa were seen already at 1–3.16 nM. Our results show that Candidate division The raw sequence data are deposited at NCBI under the BioProject accession number PRJNA320539, and with the SRA Experiment accession numbers SRX1744264–SRX1744266, SRX1744269–SRX1744273 and SRX1744275–SRX1744279.Supplementary materialSupplementary Table 3


Pneumocystis jirovecii pneumonia (PCP) has been increasing and could be life-threatening among HIV-negative patients. This study aimed at identifying prognostic factors of PCP in patients with nephrotic syndrome.  With immunosuppressants being widely used,  We retrospectively investigated patients with nephrotic syndrome who were diagnosed with PCP. The diagnosis of PCP was based on clinical manifestations, radiological findings, and microbiological confirmatory tests. Predictors of outcome were determined with multivariate logistic regression analysis. + T lymphocyte count . The cut-off value of 71 cells/μl for the CD4+ T lymphocyte count was determined to identify patients with poor prognosis. No association was found between PCP mortality and the type of immunosuppressant used.  A total of 57 patients were included in this study. The PCP mortality was 33.3%, which increased to 48.6% if ICU admission was required and to 60% when mechanical ventilation was needed. The T lymphocyte count and CD4/CD8 ratio independently predicted the outcome of PCP, so did the CD4+ T lymphocyte count is suggested as an independent predictor of prognosis, which can be used clinically to identify patients with high risk of unfavorable outcomes. PCP is a fatal complication among nephrotic syndrome patients receiving immunosuppressive therapy. The CD4 Pneumocystis jirovecii pneumonia (PCP), a pulmonary infection caused by Pneumocystis jirovecii, has been recognized as a kind of common opportunistic infection among immunocompromised patients. PCP has emerged as a concern since the epidemic of acquired immune deficiency syndrome (AIDS) in the 1980s and thus has been comprehensively studied in HIV-positive population [pulation –4. In copulation , 6. Resepulation –9. Whilepulation , 11, butWe retrospectively investigated patients with nephrotic syndrome who were diagnosed with PCP and got treated at Peking Union College Medical Hospital, a tertiary care hospital in Beijing, China, between December 2013 and December 2018.Pneumocystis jirovecii cyst was detected in microscopic examination with Grocott's methenamine silver stain (GMS) or Pneumocystis jirovecii DNA (PCP-DNA) was revealed positive by polymerase chain reaction (PCR) assay of a sputum or bronchoalveolar lavage fluid (BALF) specimen. Patients with positive PCP-DNA specimens who did not have typical clinical and radiological features for PCP or who did not receive appropriate PCP treatments were excluded from our analysis.Nephrotic syndrome, which include a group of renal diseases with diverse etiologies, was specifically defined by the presence of heavy proteinuria (protein excretion greater than 3.5 g/24 hours), hypoalbuminemia (less than 30 g/L), and peripheral edema . The diath Revision. Demographic features, clinical characteristics, comorbidities, immunosuppressive medications, renal pathology, laboratory values, treatments, and prognosis were recorded. Laboratory findings included complete blood counts, arterial blood gas analyses, blood biochemical indexes, T lymphocyte subsets, 1, 3-β-d-glucan levels, virus PCR assays, and procalcitonin (PCT). For laboratory values with more than one measurement, the worst values within 24 hours of hospital admission were acquired for analyses. Long-term corticosteroid therapy was defined as daily treatment for more than one month. The daily dosage of corticosteroids was expressed as the prednisone equivalent . PCP mortality was defined as death rate caused by respiratory failure after PCP diagnosis.Medical records were reviewed and collected from the hospital electronic database using the codes N04 for nephrotic syndrome and J17.3 for PCP, based on the International Classification of Diseases, 10U test. Categorical variables were analyzed with Chi-square test or with Fisher's exact test, as appropriate. Logistic regression analysis was used to identify variables significantly associated with the outcome of PCP by estimating the odds ratios (OR) with 95% confidence intervals (CI). A two-tailed p value of <0.05 was considered significant.Statistical analyses were performed using Stata 14.0 SE or GraphPad Prism 6.0. The variables in the datasets were presented as mean ± SD or a number and proportion of the total (%). Continuous variables were analyzed by Mann-Whitney n = 56, 98.2%). Other immunosuppressive agents were used in combination with corticosteroids in 87.7% of patients, with cyclophosphamide  and cyclosporine A  being the most commonly used . There was a trend that nonsurvivors had longer periods of corticosteroid administration compared with survivors, which was not statistically different. Initial body temperature and oxygen saturation (SpO2) were related to PCP mortality.In order to identify risk factors for PCP mortality, 38 survivors were compared with 19 nonsurvivors . This shp=0.025), T lymphocyte , and CD4+ T lymphocyte  and a low CD4/CD8 ratio  were associated with death from PCP among nephrotic syndrome patients. Blood urea was higher in nonsurvivors than survivors (p=0.045); however, serum creatinine level and estimated glomerular filtration rate (eGFR) did not differ between the two groups  respiratory tract specimens of patients. Though the 1, 3-β-d-glucan assay is considered as a reliable indicator for PCP diagnosis [β-d-glucan between survivors and nonsurvivors  and required more mechanical ventilation  per day. Compared with survivors, nonsurvivors had a higher rate of ICU admission  were used for further analysis. By univariate regression, blood urea (p=0.061) and B lymphocyte count (p=0.145) were excluded from multivariate analysis. Mechanical ventilation and ICU admission were omitted because of their collinearity. CD4+ T lymphocyte count was correlated with T lymphocyte count  and CD4/CD8 ratio , so they were analyzed separately. Multivariate regression analysis identified T lymphocyte count  and CD4/CD8 ratio  as independent predictors of PCP-related death . T lymphocyte count + CD4/CD8 ratio model was not superior to CD4+ T lymphocyte model in predictive performance , with sensitivity and specificity both above 80%, was identified and suggested for predictive purpose. As is shown in + T lymphocyte counts lower than 71/μl, compared to those with CD4+ T lymphocyte counts ≥ 71/μl . In addition, CD4+ T lymphocyte counts below 71/μl, also indicated an increased need for respiratory support and a dramatic decrease in survival within ICU  was defined with a satisfactory specificity and sensitivity. This could be quite helpful in clinical practice for physicians to identify patients with high risk of unfavorable outcomes. In fact, the combination of T lymphocyte count and CD4/CD8 ratio was a better predictive model compared with CD4+ T lymphocyte alone, but the difference was slight, and single parameter could be more convenient for clinical use. In addition, mortality might also be associated with a reduction in B lymphocyte count; however, this observation was not confirmed in multivariate analysis. It is possible that the impact of B lymphocytes on prognosis may be insignificant under the condition of T lymphocytopenia, whereas B lymphocytes may show importance with a normal number of T lymphocytes, as is suggested in several studies [It is well established that HIV-positive patients with immune deficiency are at a high risk of PCP and lymphocytopenia. Decreased CD4e of PCP , 27. Howpatients , 21, per studies –30.The level of blood urea usually indicates protein catabolism and a negative nitrogen balance. It is an important parameter for assessing the prognosis of community-acquired pneumonia in CURB-65, a pneumonia severity scoring system . It has Pneumocystis jirovecii was only detected by PCR without the confirmation by GMS; a false positive result might be an issue. However, the diagnosis of PCP was made based on typical clinical manifestations and radiological findings in addition to microbiological tests, which maximally reduced the chances of false positive results.Our study has several limitations. It was a retrospective study and data were collected from a single institution. As medical records were reviewed, some incomplete records with missing values may affect the results of the study. Besides, for some nephrotic syndrome patients included, the underlying disorders had not been identified; thus, we were unable to figure out the possible association between different etiologies and PCP development. Finally, in some patients, + T lymphocyte count could be a useful predictor of PCP mortality among nephrotic syndrome patients, which can be easily used clinically. More robust evidence from well-designed prospective studies is needed to validate the current findings.In summary, PCP is a fatal complication in nephrotic syndrome patients receiving immunosuppressive therapy. Lymphocyte subset analysis may serve as a stratifying tool to identify those patients at high risk of PCP-related death. Decreased CD4


Ovarian cancer (OC) is the second most frequent type of gynecological cancers worldwide. In the past decades, the development of novel diagnostic and prognostic biomarkers available for OC has been limited, reflecting by the lack of specificity of such markers or very costly management. Microarray expression profiling has shown very effective results in exploring new molecular markers for patients with OC. Nonetheless, most screenings are focused on mutations or expression of molecules that are translated into proteins, corresponding to only 2% of the total human genome. In order to account for the vast majority of transcripts, in the present exploratory study, we assessed the expression levels of a comprehensive panel of noncoding RNA in different subtypes of OC. We further evaluated their association with patient overall survival (OS) and aggressive forms of the disease, such as tumor type, stage, and chemotherapy resistance. By microarray profiling in a total of 197 epithelial OC patients , we found two candidates, SNORA68 and SNORD74, which associated with OS and poor clinicopathological features. The overexpression of those two targets combined was correlated with shorter OS and progression-free survival. That association was further observed to correlate with a more aggressive form of the disease. Overall, the results indicate that a panel comprised of SNORA68 and SNORD74 may be clinically relevant, where patients could be offered a more individualized, targeted follow-up, given its further validation on future prospective clinical studies.The online version contains supplementary material available at 10.1007/s43032-020-00372-7. Globally, ovarian cancer (OC) is the eighth most common cancer for women and the second most common cause of gynecologic-associated cancer death , 2. WithGenome sequencing and gene expression profiling have been the methods of choice in clinical studies screening for potential molecular biomarkers. These methods provide tumor molecular information, which can contribute to improve diagnosis and outcome, such as prediction of chemotherapy response and impact on patient survival –10. The On this exploratory study, we investigated the association of ncRNAs across patients with different subtypes of EOC with OS, PFS, tumor type, grade, and resistance to chemotherapy. Despite the particular clinical characteristics of each subtype, we aimed to establish a mutual molecular feature across them which equally affects patient outcome. We observed that a panel of candidate snoRNAs was associated with OS and PFS. We further observed that the combination of such candidates and classification into different categories did also correlate with other clinicopathological characteristics associated to poor prognosis.www.regioner.dk), a registry including clinical biobanks, ensuring biological material of high quality for patients own treatment and biomarker research. The study was carried out according to the guidelines of the Declaration of Helsinki, including written informed consent from all subjects, and it has been approved by the Danish National Committee for Research Ethics, Capital Region . All patients were followed until either death of any cause, emigration or January 17, 2015.All tissue samples were obtained from patients enrolled in the Danish Pelvic Mass study, a national ongoing cohort initiated in 2004. Patients were diagnosed and surgically treated for EOC between October 2004 and January 2010. The exclusion criteria were non-epithelial OC, neoadjuvant chemotherapy, scarce tissue material for analysis, and a history of another cancer type. Subjects that had received primary cytoreductive surgery with the confirmation of an epithelial histologic subtype were included in this study. All patients were registered in the Danish Gynecologic Cancer Database (DGCD) , a natioTumor tissues were stored as formalin-fixed and paraffin-embedded (FFPE), and all samples were registered in RBGB/Danish Cancer Biobank. A specialized pathologist in gynecology has revised histologic diagnosis for all tissue samples. With conventional hematoxylin and eosin staining, all samples included presented a tumor presence above 50%.Total RNA was extracted from 20-μm-thick FFPE tumor sections using the RecoverAll Total Nucleic Acid Isolation Kit for FFPE samples . Samples were then hybridized to Affymetrix GeneChip miRNA 2.0 Array , following the manufacturer instructions. Briefly, RNA samples were subjected to two cycles of cDNA conversion, amplified, and labeled with biotinylated ribonucleotide analogues, generating cRNA single strands. Synthesized strands were then purified, heat-induced fragmented, and finally hybridized to the microarray chip. Microarrays were scanned in a GeneChip Scanner , and data acquisition was performed by GeneChip Command Console .2 transformation, followed by quantile normalization. Normalized data were primarily submitted to Cox univariate regression, identifying 102 probes (P < 0.05). Due to the large number of predictors, a LASSO-penalized model for Cox multivariate regression was applied, and the resulting targets were finally cross-validated (10-fold) by a last round of Cox multivariate analysis. The primary outcome for the investigation of candidate biomarkers was OS, defined as time in months, counting from the time of diagnosis to time of death, or last censored follow-up. The association between the candidate targets and the clinicopathological features of the patients were investigated by multivariate logistic regression model, considering all discovered targets combined for each feature alone. The clinical characteristics assessed were tumor type, stage, progression of disease, resistance to first line of chemotherapy, and menopause status. All analyses with the clinical features were adjusted for age and CA-125 levels. In the latter case, CA-125 was included in the analysis given its use in risk estimation of malignancy of ovarian disease. Receiver operating characteristic (ROC) curves were calculated in order to assess the efficiency of prediction of our models presented by the area under the curve (AUC). Targets with P < 0.01 were considered associated with patient survival, and a penalty alpha = 1.0 was applied for the LASSO method. All statistical analyses were performed in the R environment (https://www.R-project.org/).Raw data were background-corrected, normalized, and log-transformed by applying the robust multi-array average (RMA) method , resultiNormal ovarian epithelium and OC samples from independent cohorts were used in order to assess transcription expression of the candidate markers. The first cohort was comprised by 6 normal and 32 OC tissue samples . The secn = 24), neoadjuvant chemotherapy or ongoing palliative care (n = 15), other forms of cancer (n = 8), or ambiguous histologic classification (n = 2). A total of 197 patients were eligible for inclusion in the study. Histological subtypes were represented by 162 (82.2%) serous adenocarcinomas, 15 (7.6%) endometrioid adenocarcinomas, 11 (5.6%) mucinous adenocarcinomas, and 9 (4.6%) clear cell carcinomas. Early-stage diagnoses (FIGO I–II) accounted for 52 (26.4%) of the cases, while 145 (73.6%) were advanced stage (FIGO III–IV). Low-grade tumors were found in 20 (10.2%) patients and high grade in the remaining 177 (89.8%) subjects. Thirty-nine (19.8%) subjects were categorized with type I tumor and 158 (80.2%) with type II tumor. Briefly, type I tumors develop from benign extraovarian lesions that implant on the ovary and which can subsequently undergo malignant transformation, whereas most of type II carcinomas develop from intraepithelial carcinomas in the fallopian tube [Primarily, 246 patients with EOC were identified and included. From those, 49 subjects were excluded due to either insufficient tumor material for analysis  (Table P < 0.01). In total, 2 targets were identified—SNORA68  and SNORD74 , with their expression detected in all samples  Table . We procP < 0.0001)   and 31.3% (P = 0.028) for the overexpressed (above the median for each target) individuals, respectively   Fig. . NoteworP < 0.0001)   was responsible for our observations. To that end, we first performed a survival curve analysis in this group alone. The difference in OS was still observed in “high-risk” and “low-risk” subgroups (P = 0.0043)  and SNORD74 (P = 0.96) with the subtype.We also examined whether SNORA68 and SNORD74 would also be associated with patient PFS, by following the same classification in “high” and “low”-risk subgroups. In agreement with the observations from OS, the overexpression of these targets also showed an association with a shorter PFS compared to the other group, with 38.1% 16/42) and 21.1% (26/123) relapse of the disease within the first 12 months, respectively , stage (FIGO I–II and FIGO III–IV), disease progression (whether disease progressed until last follow-up), and primary platinum-based chemotherapy response (tumor recurrence within the first 6 months post-treatment and later), separately. We found that SNORA68 and SNORD74 were correlated with all these clinical characteristics. The overexpression of both targets showed association with tumor type II, with AUC of 0.755. It was also linked to shorter tumor progression (AUC = 0.700) and, to a lesser extent, to tumor stage (AUC = 0.667) and primary chemotherapy resistance (AUC = 0.641) Fig. . None ofOverall, our findings indicate that SNORA68 and SNORD74 performed well in predicting poor OS for EOC patients, and rather specifically to serous adenocarcinoma, they were found in all histologic subtypes examined.P = 0.00008 and P = 0.039, respectively) , the discovery of novel biomarkers diagnosing OC at an early asymptomatic stage or/and being useful in prediction of effective personalized treatment could be beneficial in order to improve the prognosis of patients and avoid complications based on ineffective traditional therapies. Currently, CA-125 protein measurement is the most accepted and employed marker for management of the disease, despite its limited specificity to OC. Early studies showed that its level fluctuates in association with other conditions, such as inflammation, menstruation, endometriosis, and other non-ovarian malignancies –24. HencIn OC, this field of investigation is quite recent and mostly limited to long noncoding RNA (lncRNA), emphasizing the role of ncRNA as emerging novel biomarkers , 29, 30.Due to the complexity of OC, the survival of a patient is highly linked to various clinicopathological outcomes, such as tumor type, stage, the relapse of the disease, and sensitivity to chemotherapy –34. HereBRCA1 or BRCA2 mutation carriers [BRCA1/2-positive and BRCA1/2-negative cases. That could potentially represent a meaningful outcome in the clinical setting, where the expression of SNORA68 and BRCA1/2 mutation status could be used in concert, in order to further predict patient response to PARP inhibitors [Given the novelty in evaluating snoRNA levels in OC, none of the targets have been previously reported. Interestingly, SNORA68 is located at the p13.1 locus on chromosome 19 (19p13.1), a region previously associated with susceptibility to both ovarian and breast cancer in the population with carriers , 36. Bolhibitors , 38.GAS5. It has been reported to act as a tumor suppressor in different types of cancer [GAS5 was shown to induce apoptosis by promoting the expression of pro-apoptotic factors, such as Bcl2-associated X (BAX), Bcl-2 homologous antagonist killer (BAK1), and cleaved-caspase 3 and 9 [GAS5 expression indicated poor prognosis in OC patients [GAS5 might be regulated by microRNA-21, a ubiquitous miRNA associated with a plethora of cancer types. Noteworthy, in line with our findings, SNORA68 and SNORD74 have been reported highly expressed in lung cancer, with the former further validated on an independent cohort [In the present study, SNORD74 was also found to be associated with patient OS and PFS. Furthermore, worse prognostic features, such as tumor type II, recurrence, and platinum-based chemotherapy resistance also showed positive correlation with overexpression of that molecule. It belongs to the box C/D snoRNA family, characterized by guiding the 2’-O-methylation of ribosomal RNA (rRNA) . Some mef cancer –44. Spec 3 and 9 . By indut cohort . SNORA68t cohort . NoteworIn summary, we demonstrated that SNORA68 and SNORD74 performed well in predicting OS and PFS. We showed that their combination performed better than each candidate alone. That combination further associated with a more aggressive form of OC—shorter PFS, high-grade serous (type II) tumors, stage, and chemotherapy resistance. Moreover, considering that single biomarkers can be sensitive in predicting tumors at the cost of very low specificity, a panel of markers can provide a more accurate outcome. To that extent, we sought into determining ncRNA predictors that could associate with a shorter OS and further poor prognosis in patients with OC. Overall, this indicates that a panel comprised of a few predictors that associates with a more aggressive form of OC might be clinically relevant in planning treatment course, by presenting a better performance than a single marker. In that regard, potentially, a patient presenting overexpression of both SNORA68 and SNORD74 could be offered a more individualized, targeted follow-up. However, considering the novelty of snoRNAs as potential biomarkers, the current study aims at as an exploratory work, where further validation and functional analyses are necessary in order to unveil how they might regulate tumorigenesis or whether they are a consequence. Nonetheless, it allows for an excessive amount of approaches for future investigation, which can benefit in overall improvements for OC cancer patients.ESM 1(PDF 869 kb)ESM 2(PDF 1030 kb)ESM 3(PDF 890 kb)ESM 4(PDF 894 kb)ESM 5(PDF 1006 kb)ESM 6(PDF 882 kb)ESM 7(XLSX 13 kb)


Procalcitonin (PCT), C-reactive protein (CRP), and neutrophil-to-lymphocyte ratio (NLR) have emerged as important markers of inflammation, and these markers, especially PCT and CRP, have been studied in patients with neutropenia. This study was designed to evaluate their value in differentiating infectious fever from tumor fever (TF) and to investigate their role in assessing outcomes in nonneutropenic lung cancer patients (NNLCPs).  This retrospective clinical study included 588 febrile NNLCPs between January 2019 and December 2019. The levels of PCT, CRP, and conventional inflammatory markers, including white blood cells (WBC) and neutrophils (NEU), were measured. NLR was defined as the ratio of the absolute neutrophil count to the absolute lymphocyte count. Patients' clinical and bacteriological data were recorded. p < 0.0001). However, PCT level was the best predictor of bacterial infections, with an area under the curve (AUC) of 0.874, followed by CRP level (AUC = 0.855) and NLR (AUC = 0.792) (p < 0.0001). Additionally, PCT level was significantly elevated in patients with bacterial infections with progressive disease after radiotherapy and chemotherapy (p < 0.01).  This study included 311 NNLCPs with bacterial infections and 277 with TF. Inflammatory markers such as PCT, CRP, WBC, and NEU levels and NLR were significantly higher in patients with bacterial infections than in those with TF ( The present study demonstrated the superiority of PCT over CRP and NLR in the diagnosis of febrile patients with bacterial infections. Additionally, PCT can be used to assess the clinical outcomes and cancer progression in NNLCPs. Patients with lung cancer are susceptible to bacterial infections owing to their compromised immune system , leadingIn such cases, bacterial infections in NNLCPs should be identified to provide appropriate and effective treatment. Most bacterial infections can be diagnosed based on clinical symptoms, inflammatory markers, radiological imaging, and microbiological data , 9. CurrSeveral inflammatory markers have been evaluated for the diagnosis of infections. Procalcitonin (PCT), a precursor of the hormone calcitonin , has emeInflammation is an important marker of outcomes in cancer. Accumulating evidence has been found regarding the role of inflammatory markers in cancer development and progression , 37–39. Thus, in the present study, we first evaluated the diagnostic value of PCT, CRP, and NLR compared with conventional biomarkers such as WBC and NEU counts in determining bacterial infections in febrile NNLCPs. Next, we assessed their usefulness in predicting clinical outcomes and cancer progression in NNLCPs. The study findings should be validated in future studies with a higher number of patients.In this retrospective clinical observational study, we included 588 NNLCPs with fever who were admitted to Shandong Cancer Hospital and Institute from January 2019 to December 2019. Clinical characteristics were collected from the patients' electronic medical records and the Ruimei laboratory information system version 6.0 .9/L. Hematological parameters and inflammatory mediators such as PCT and CRP levels were determined within 48 h of the onset of fever, and bacterial cultures were taken. Prior to the start of antibiotic treatment, all measurements were performed. Patient diagnoses were confirmed via pathological examination. At the same time, patients with certain influential factors such as immune system disease, metabolic diseases, cardiovascular disease, the use of corticosteroid drugs, and the infection of other pathogenic microorganisms  were excluded.Bacterial cultures from specimens such as blood, mid-stream urine, sputum, and drainage fluid were prepared and analyzed. For blood cultures, blood samples were collected several times during the fever cycle. If the culture result was confirmed to be positive within 24 h, two or more blood samples were collected for analysis. Sputum and mid-stream urine were collected in the early morning. All specimens were collected before antibiotic treatment and were transferred to the laboratory within 1 h after collection. The results of bacterial cultures were considered as the gold standard for the diagnosis of infection. After bacterial cultures, biotypes were identified using the Biomerieux ATB Expression system, and biotypes that were commonly contaminated by a single culture and could not be excluded were eliminated. All procedures were conducted in accordance with the manufacturers' instructions and the BC standards of the Clinical Laboratory Standards Institute .The serum PCT level was determined by a quantitative electrochemiluminescence immunometric assay using a COBAS E602 analyzer , with level of <0.05 ng/mL considered normal.Plasma CRP level was measured by immunoturbidimetry assay using Beckman Coulter analyzer AU5800 . The reference value provided by the manufacturer was <10 mg/L.For hematological studies, we collected whole blood in sterile tubes containing K2-ethylenediaminetetraacetic acid, and blood counts were estimated using automatic hematological analyzer Sysmex XN9000 . Total peripheral leukocyte, lymphocyte, monocyte, and neutrophil levels were also recorded. NLR was defined as the ratio of the absolute neutrophil count to the absolute lymphocyte count. All tests were performed according to the manufacturer's instructions.U test was used for two independent samples. Spearman's correlation was used to compare the correlation between two variables. Receiver operating characteristic (ROC) curve analysis was implemented to evaluate the effects of markers for predicting bacterial infections. The optimal cut-off points were determined using the Youden index. Data were presented as the median ± interquartile range . Significance was established at p < 0.05.Statistical analysis was performed using SPSS version 22.0 statistical software  and GraphPad Prism version 6.0 . For comparisons of nonnormal continuous variables, the Mann–Whitney N = 311) and TF group (N = 277) are shown in Staphylococcus aureus was the most common species (6.3%), followed by Streptococcus pneumoniae (4.7%). Among Gram-negative bacteria, the most frequently identified species were Klebsiella pneumoniae (21.4%) and Haemophilus influenzae (18.2%), followed by Pseudomonas aeruginosa (13.9%), Escherichia coli (9.4%), Acinetobacter baumannii (5.4%), and Moraxella catarrhalis (4.4%). Names of all the bacterial taxa are shown in A total of 588 NNLCPs were analyzed in this study . The cli9/L) than with NNLCPs without bacterial infections (5.57 × 109/L) (p < 0.0001). A significant difference in the NEU level was found between the bacteria-infected (7.15 × 109/L) and TF groups (3.82 × 109/L) (p < 0.0001) (p < 0.0001).We first confirmed whether WBC and NEU levels and NLR could be used in the diagnosis of bacterial infections for NNLCPs as shown in the bacteria-infected and TF groups .  Figure 0.0001) . As showTo determine the diagnostic accuracy of WBC, NEU, and NLR in bacterial infections, we constructed ROC curves. The analysis revealed that in NNLCPs with MDI, WBC had a discriminative power, with an AUC of 0.718 , sensitivity of 62.1%, and specificity of 72.9% compared with the TF group. For NEU, the AUC was 0.748 (95% CI 0.709–0.787), with 61.1% sensitivity and 78.3% specificity. Meanwhile, the ROC curves indicated that NLR had an AUC of 0.786 (95% CI 0.749–0.823), with 57.2% sensitivity and 90.6% specificity .In order to achieve better diagnostic accuracy, the classic inflammatory markers PCT and CRP were used. A total of 125 eligible patients were screened for their PCT and CRP levels. 69 patients were assigned to the bacteria-infected subgroup A, and the remaining 56 were assigned to the TF subgroup A .p < 0.0001) (p < 0.0001)  than patients with nonbacterial infections  .The median level and range of blood inflammatory markers  in the two subgroups are shown in  0.0001) . Similar 0.0001) . Further Figures .  Figurer = 0.222, p = 0.067 and r = 0.176, p = 0.148, respectively).To evaluate the discriminative power of inflammatory markers to predict infections in subgroup A of nonneutropenic lung cancer, we constructed ROC curves. To study blood inflammatory markers for clinical outcome assessment in NNLCPs, we analyzed the relationship between response to therapy and the levels of inflammatory markers in bacteria-infected subgroup A and TF subgroup A.p = 0.0116) (As shown in  0.0116) . RemarkaNext, we evaluated the inflammatory marker levels for clinical response assessment in TF subgroup A. Detailed treatment methods and outcomes of this group are shown in N = 191)  .Given the good correlation between PCT and the other inflammatory markers described above, we classified patients according to PCT values measured on presentation with MDI in bacteria-infected subgroup B. As shown in p = 0.0002) (As described in  0.0002) .p = 0.0057)  was higher than that of patients with non-PD-chemotherapy (the response to chemotherapy was SD and PR) in bacteria-infected subgroup B ( 0.0057) .Although other inflammatory markers were not significantly different between patients with PD and non-PD following Mann–Whitney tests analysis (data not shown), their levels tended to be higher in the PD group than in the non-PD group. Collectively, our data support our conclusion that PCT level can be used to assess the outcomes of bacteria-infected NNLCPs.It is estimated that almost 50% of patients with solid tumors and 60% of patients with hematological malignancies die from infectious complications , in whicIn our study, the febrile episodes were retrospectively classified into bacterial infections with MDI and TF. Our data demonstrated that PCT, CRP, WBC, and NEU levels and NLR were predictive of infectious fever in NNLCPs. There were significant differences in these inflammatory markers between the nonneutropenic patients with infection and those with TF. Our results are consistent with those of previous reports , 27, whiHowever, some reports have indicated that the usefulness of these markers in the diagnosis of infectious diseases in clinical practice is disputable. One study retrospectively evaluated the value of PCT level for infectious fever and TF in febrile episodes in patients with cancer . AlthougκB (NF-κB) [As mentioned above, the use of inflammatory markers as biomarkers for diagnosing bacterial infections has been previously discussed –18. Stud (NF-κB) . UnfortuAs far as clinical outcomes are concerned, little is currently known about the relationship between inflammatory markers and cancer progression in NNLCPs with bacterial infections. Previous reports focused on the value in assessing the efficacy of antibiotic treatment in patients with bacterial infections . It was Additionally, considering that inflammatory markers can predict cancer progression , 31–33, Although the usefulness for diagnosis of bacterial infections and outcome assessment in patients with febrile nonneutropenic lung cancer has been partially confirmed, several limitations should be considered in the present study. First, given it was a retrospective study with a small number of patients, the effect of confounding variables cannot be ruled out . ProspecOverall, the present study demonstrated the superiority of PCT over CRP and NLR in differentiating infectious fever from TF. Additionally, markedly increased PCT level indicated a poorer treatment response and supported our conclusion that the PCT level can help predict the clinical outcome and cancer progression in NNLCPs. Further studies are needed to fully evaluate our findings.


Approximately one in five pregnant women have obesity. Obesity is associated with an increased risk of antenatal, intrapartum, and perinatal complications, but many women with obesity have uncomplicated pregnancies. At a time where maternity services are advocating for women to make informed choices, knowledge of the chance of having an uncomplicated  pregnancy is essential. The objective of this study was to calculate the rate of uncomplicated pregnancy in women with obesity and evaluate factors associated with this outcome.This prospective cohort study was conducted using the Ontario birth registry dataset in Canada . The rate of uncomplicated or complicated composite pregnancy outcomes  were calculated for women with and without obesity. Associations between uncomplicated pregnancy and maternal characteristics were explored in a population of women with obesity but without other pre-existing co-morbidities  or obstetric risks identified in the first trimester , using log binomial regression analysis.n = 117,236) were obese. Of these 20·6% had pre-existing co-morbidities or early obstetric complicating factors. Amongst women with obesity but without early complicating factors, 58·2%  experienced pregnancy without complication; this is in comparison to 72·7% of women of healthy weight and no early complicating factors. Women with obesity and no early pregnancy complicating factors are more likely to have an uncomplicated pregnancy if they are multiparous, younger, more affluent, of White or Black ethnicity, of lower weight, with normal placental-associated plasma protein-A and/or spontaneously conceived pregnancies.Of the studied Ontario maternity population (body mass index not missing) 17·7% (The study demonstrates that over half of women with obesity but no other pre-existing medical or early obstetric complicating factors, proceed through pregnancy without adverse obstetric complication. Care in lower-risk settings can be considered as their outcomes appear similar to those reported for low-risk nulliparous women. Further research and predictive tools are needed to inform stratification of women with obesity.The online version contains supplementary material available at 10.1186/s12884-021-03663-2. Other sThis study has been reported according to the guidelines issued in the STROBE statement . This is available in Additional file The aim of this study was to calculate the rate of an uncomplicated pregnancy  in pregnant women with obesity and to determine the demographic and clinical factors which are associated with such uncomplicated pregnancies. We also set out to determine if the prediction of uncomplicated pregnancy using identified factors is feasible amongst women with obesity.This population-based cohort study was conducted using routinely collected data stored within BORN (Better Outcomes Registry and Network) Ontario. BORN is a prescribed maternal, newborn and child registry funded by the Ontario Ministry of Health and Long-Term Care. During the study period (April 2012 – March 2017), the data was entered from the pregnancies and births of 703,115 women.Women with pregnancies ongoing beyond 22 + 0 gestational weeks, with complete data on weight and the exposures of interest  were included. Women were included regardless of BMI, because a comparison was conducted between women of healthy and obese weights. Subgroups were formed through identification of early pregnancy complicating factors, defined as either pre-existing medical comorbidities or obstetric complicating factors present in the first trimester Table . Otherwi2) using maternal pre-pregnancy weight and height. Weight was estimated from two sources: pre-pregnancy weight calculated by subtracting 2 kg from the first trimester weight recorded in the Perinatal Screening database in BORN Ontario, or self-reported pre-pregnancy weight recorded in the aggregated BORN Ontario dataset. Weight recorded in the Perinatal Screening database was prioritised because this was primarily measured rather than self-reported. The method of subtracting 2 kg to calculate pre-pregnancy weight from first trimester weight was established following modelling by Cheikh Ismail et al. (2016) [Pre-pregnancy BMI was calculated (kg/m. (2016) . Height The primary outcome was the rate of uncomplicated pregnancy  in women with obesity. Uncomplicated pregnancy is a composite measure Table  defined 2, and between women with a BMI in the obese range but with or without pre-existing medical or early obstetric complicating factors.We planned to compare the rate of uncomplicated pregnancy (absence of new onset pregnancy complications) Table  between Finally, we planned to examine sociodemographic and clinical factors and determine whether they were associated with uncomplicated pregnancy in otherwise healthy women with obesity. The planned sociodemographic and clinical factors for study were based on a priori hypothesis and availability of data items: maternal age at conception, pre-pregnancy BMI , parity, race, first language (native/non-native), neighbourhood income quintiles, smoking or alcohol at first visit, timing of first trimester visit, women with adjusted placental-associated plasma protein-A (PAPP-A) < 0.3 MoM, and use of assisted reproductive techniques. Those factors which were associated with the outcome on univariable analysis were taken forward for inclusion in the multivariable regression model.The level of missingness was calculated and reported for all sociodemographic and clinical characteristics. Height was missing in 10.4% of records and imputed for these cases using single imputation according to the median height for ethnicity. All analyses were conducted only in those women with a completed set of characteristics and outcomes, after imputation of missing height.2: underweight, BMI 18.5–24.9 kg/m2: normal weight, BMI 25.0–29.9 kg/m2: overweight, BMI 30.0–34.9 kg/m2: class I obesity, BMI 35.0–39.9 kg/m2: class II obesity, and BMI ≥40.0 kg/m2: class III obesity) [The prevalence of pre-pregnancy obesity was calculated in categories of BMI as defined by the World Health Organization (BMI < 18.5 kg/mobesity) , and comThe rate of uncomplicated pregnancy was calculated using frequency (n) and percentage (%) and compared among women with obesity and with or without early pregnancy complicating factors for antenatal complication using Chi-squared tests. The maternal socio-demographic characteristics and clinical factors of otherwise-healthy women with obesity were described (mean/standard deviation (SD) or n/% as appropriate) and compared between those with complicated and uncomplicated pregnancy . Log-transformation was applied to BMI data due to non-normal distribution.Multivariable log-binomial regression models were used to estimate the adjusted relative risk (aRR) and 95% confidence intervals (95% CI) of the associations between uncomplicated pregnancy and associated sociodemographic or clinical factors, among women with obesity but no other early pregnancy complicating factors and compared to women without obesity or early pregnancy complicating factors. Potential confounders were identified by presence of a 10% change in the measure of association (crude/adjusted RR) for the exposure before and after introduction of confounders into the model. Where confounders were identified, these were used to adjust the final multivariable model.Backward stepwise logistic regression was then used, with Akaike’s Information Criteria as the stop rule, to identify factors that were independently associated with uncomplicated pregnancy. The area under the receiver operating characteristic curve (AUROC) was then used to calculate the accuracy of the multivariable model in discriminating between women with complicated and uncomplicated pregnancy.All analyses were performed using the Statistical Analysis System (SAS) for Windows, version 9.4 .n = 117,236) had a recorded BMI ≥ 30 kg/m2  of women had class I obesity, 25.1%  had class II obesity and 15.8%  of women had class III obesity.Between 2012 and 2017, there were 703,115 pregnancies with data recorded in the BORN Ontario registry. Following exclusion of 42,455 women with missing weight (6.0%), the final study population was composed of 660,660 women. Of these, 17.7% , compared to 16.5% of women with BMI 18.5–24.9 kg/m2 (p < 0.001) (Table Of women with BMI ≥30 kg/m2) BMI (‘U’-shaped curve relationship). The rate of small-for-gestational-age/growth restricted infant and antepartum bleeding decreases with advancing BMI category but other complications have no clear trend.The rate of each complicating antenatal diagnosis from the ‘complicated pregnancy’ composite outcome is presented in Table p < 0.001).Of 93,079 women with obesity but no early pregnancy complicating factors for antenatal complication, 54,191 (58.2%) had uncomplicated pregnancies. Of 24,157 women with obesity and other early pregnancy complicating factors, only 10,978 (45.4%) had uncomplicated pregnancies. The relative risk of complicated pregnancy for women with obesity and early pregnancy complicating factors, compared to otherwise healthy women who have obesity was 1.67 , smoking status , alcohol consumption , and timing of first trimester visit  were not associated with the uncomplicated pregnancy outcome and therefore not included in the multivariable model. Frequency, percentage, crude and adjusted relative risks are presented in Table Of women with obesity and no identified early pregnancy complicating factors, women with uncomplicated pregnancies were more likely to be younger, of a lower class of obesity, multiparous, Black or Caucasian ethnicity (than Asian or Other ethnicities), and in the highest two quintiles for neighbourhood income. They were less likely to have a low PAPP-A measurement, be of Asian ethnicity, and have conceived through assisted reproductive technology. On univariable analysis, first language  or overweight (BMI 25.0–29.9 kg/m2) and without early pregnancy complicating factors for antenatal complication.The characteristics predictive of uncomplicated pregnancy in women with obesity but no early pregnancy complicating factors were compared to those predictive for women of healthy weight (BMI 18.5–24.9 kg/mp < 0.0001).The predictive characteristics for women of healthy weight are summarised in Additional files Following stepwise logistic regression, maternal age, BMI, PAPP-A < 0.3 MoM, neighbourhood income quintiles 1 or 2, multiparity, ethnicity, and artificial reproductive techniques remained as independent predictors for the uncomplicated pregnancy outcome in women with obesity but no other early pregnancy complicating factors. The point estimates and 95% confidence intervals for the odds ratios are detailed in Table This study aimed to calculate the rate of uncomplicated pregnancy among pregnant women with obesity and to determine the demographic and clinical factors which are associated with such uncomplicated pregnancies.p < 0.001) for women with obesity but no early pregnancy complicating factors compared to women with obesity and early pregnancy factors (45.4%). In women with obesity but without other early pregnancy complicating factors, an uncomplicated pregnancy was more likely if they were younger, with lower BMI, multiparous, black or Caucasian ethnicity or in the highest three quintiles for neighbourhood income; and less likely if the women had a low PAPP-A measurement at prenatal screening, were of Asian ethnicity or had conceived through artificial reproductive techniques. At present, these predictive factors identified through population-level routinely collected data were not strong enough to discriminate between uncomplicated and complicated pregnancy outcomes in this group.Through this large prospective cohort study of women with obesity in Ontario, Canada, we have identified that 79.4% of women with obesity had no other early pregnancy complicating factors (obstetric or co-morbidities). Of these, 58.2% had an uncomplicated pregnancy. Uncomplicated pregnancy was significantly more likely  of women with obesity had either a pre-existing or new obstetric risk factor  at the time of admission to the maternity unit for birth [.4% of woregnancy .Where our study differs from these national cohort studies is in the comparison of complications for women with obesity with and without pre-existing complicating factors, and in the study of characteristics associated with an uncomplicated pregnancy outcome. As in Vieira et al’s proof of concept study 2017) uncomplicated pregnancy was independently associated with multiparity and younger age [ uncompliThe strengths of this study are in the large cohort used from a country with universal access to healthcare, providing an opportunity to identify risk of even rare outcomes, e.g., intrauterine fetal death, and in the methodology to stratify women with obesity according to presence or absence of early pregnancy complications which will inform pathways of prenatal of care. It is important to note the methodological limitations of using a routinely collected dataset, including our choice of using self-reported pre-pregnancy weight where measured weight was not available and the decision to impute height using single imputation for mean height in the ethnic group for the 10.4% of women for whom height was not recorded. It has previously been established that heavier women are more likely to underestimate their weight when self-reporting , 15, howIn some settings it is routine practice to manage otherwise low-risk nulliparous women in midwifery-led or primary care settings where available, if they choose to do so. The rate of complicated outcomes in the group of women with obesity appears to be similar, it therefore follows that these women with obesity should also have the option of having prenatal care in midwifery-led settings, assuming that appropriate surveillance and timely reflex referral to higher-risk care providers continues for potential complications .Confidence in risk stratification strategies for this group of women is expected to improve with the aid of decision support tools, incorporating predictive algorithms. The predictive power demonstrated in this study was limited by the absence of clinical, ultrasound and biochemical measurements. Other cohort studies have recognised that these additional factors, not present in routinely-collected registries, augment predictive power , 20. FurThe study demonstrates that over half of women with obesity, but no other pre-existing medical or early obstetric complicating factors proceed through pregnancy without adverse obstetric complication. This is similar to the rate of uncomplicated pregnancy noted in nulliparous women through an international cohort study . Whilst Additional file 1. STROBE checklistAdditional file 2: Appendix Table 1. Rate of specific antenatal complications in women with early pregnancy complicating factors, stratified by BMI groupAdditional file 3: Appendix Table 2. Characteristics associated with uncomplicated pregnancy in women of healthy weight (BMI 18.5–24.9 kg/m2) but no other early pregnancy complicating factorsAdditional file 4: Appendix Table 3. Characteristics associated with uncomplicated pregnancy in women who are overweight (BMI 25.0–29.9 kg/m) but no other early pregnancy complicating factors


An analysis method was established to determine 14 organophosphorus ester (OPE) flame retardants in fall protection equipment by combining accelerated solvent extraction (ASE) and solid-phase extraction (SPE) with high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The ASE parameters were optimized as follows: static extraction with acetonitrile at 80°C for 5 min for two cycles. The combined extract was purified with the ENVI-18 cartridge before further analysis. A HILIC column was used to separate the OPEs using an acetonitrile/water mixture as the mobile phase with the detection by the electrospray ionization mass spectrometry, which was operated under the positive mode. Under optimized conditions, the limit of detection for the target OPEs ranged in 0.015–1.33 ng/g, with a spike recovery of 71.6%–114% and a relative standard deviation of 0.8%–11.2%. The developed method was used to analyze OPEs in fall protection equipment (safety helmets and ropes), where OPEs were all detectable. Safety ropes displayed a higher concentration of OPEs than ones in safety helmets, with the pollutants being mainly triphenyl phosphate, 2-ethylhexyl diphenyl phosphate (EHDPP), tri(2-ethylhexyl) phosphate, and tri-n-butyl phosphate in the range of 11.07 ng/g‒815.53 ng/g. The EHDPP was the dominant compound in safety helmets with the concentration from 26.84 to 95.29 ng/g, while the other OPEs in safety helmets were lower than 5.136 ng/g. The potential health and environmental risks of these fall protection equipment during their use and disposal call for further attention. After the use of polybrominated diphenyl ethers (PBDEs) is banned worldwide, organophosphorus esters (OPEs), as flame retardants with excellent properties and abundant resources, are now widely used in plastics, furniture, textiles, electronic equipment, building materials, automobiles, etc. . Both thIn recent years, OPEs have been detected by a number of studies in home furniture foam , plasticSome works have studied the method for the detection of OPEs in different environmental matrices, such as water, air, dust, sediment, and biota. Commonly used detection methods include gas chromatography-tandem mass spectrometry (GC-MS) –15 and lMethanol and acetonitrile (HPLC grade) were purchased from Merck (USA). Dichloromethane (HPLC grade) was obtained from Fisher Scientific . Ammonium acetate with high purity (>97%) was obtained from Alfa Aesar . ENVI-18 cartridges  were purchased from Supelco (USA). The Milli-Q ultrapure water preparation system was supplied by a Milli-Q Advantage A10 System .μm) before injection into HPLC-MS/MS.The safety helmet and ropes were cut into small pieces (5 mm) and weighed  and then placed into the extraction cell (10 mL) of the accelerated solvent extraction instrument . Then, 10 ng internal standards were added into the sample with thorough mixing. The bottom of the cell was installed with a filter membrane and then added a certain amount of processed diatomite  to fill the cell. The extraction was carried out with acetonitrile for 5 min at 80°C and 1500 psi for two cycles. After the volume of the extract was reduced to <0.5 mL by nitrogen blowing, ultrapure water (30 mL) was added, and the diluted extract was purified using the previously reported SPE method . The cleThe analysis of OPEs was conducted in the HPLC  coupled with an electrospray ionization tandem mass spectrometry . An Analyst 1.6.2 workstation was used to process the data.μm; Thermo Fisher) using a binary mobile phase consisting of pure water (A) and acetonitrile (B) with a column temperature of 30°C at a flow rate of 0.25 mL/min using the following gradient elution procedure: 60% A at 0–5 min and then linear decreases from 60% A to 40% A over 5–8 min and to 0% A at 12 min. After phase A was returned to the original value of 60% over 12 to 15 min, the elution was maintained for 7 min in order to equilibrate the column.The chromatographic separation was carried out on an Acclaim Mixed-Mode HILIC-1 column . The key parameters are as follows: curtain gas pressure, 0.14 MPa; collision gas pressure, 0.02 MPa; ion spray voltage, 5000 V; source temperature, 600°C; gas1, 0.34 MPa; and gas2, 0.28 MPa. Additional parameters are listed in To optimize the extraction efficiency for OPEs in plastics and textiles, plastic and textile samples free of OPEs were blended with a mixture of standards (10 ng) and then subjected to ASE to investigate the key extraction parameters, including extraction solvent, temperature, and number of cycles. Generally speaking, among the abovementioned factors, the extraction solvent is the most important factor influencing the extraction efficiencies of OPEs. Therefore, it was firstly optimized under the fixed extraction temperature (80°C) and static cycles (3 cycles). After the solvent was determined, the extraction temperature was optimized under the fixed optimized solvent and static cycles (3 cycles). Finally, the static cycle times were revaluated under the optimized solvent and temperature.p < 0.05). When methanol alone was used for extraction, the extraction efficiency of all substances was lower than 65%. Therefore, acetonitrile was chosen as the extraction solvent.The extraction solvents, acetonitrile, methanol, and the mixture of methanol and acetonitrile , were optimized under the conditions at 80°C over 3 extraction static cycles. p < 0.05). Therefore, the final extraction temperature was selected as 80°C.The extraction temperature was varied at 50, 60, 80, and 100°C while other extraction parameters were fixed . p < 0.05), while there is no significant difference between two and three extraction cycles (p > 0.05), indicating that the third extraction cycle did not notably improve the extraction efficiency of OPEs. Therefore, two static cycles were considered as the optimal condition and used to extract OPEs from plastics and textiles.The number of extraction cycles was varied at 1, 2, and 3 cycles while other extraction parameters were fixed. The packing material of the Mixed-Mode HILIC-1 column has both hydrophobic alkyl chains and hydrophilic ethylene glycol end groups, thus allowing both hydrophobic retention and hydrophilic retention. The hydrophobic retention mechanism is dominant when the chromatography is operated in the reverse-phase mode. The hydrophilic ethylene glycol end groups enhance the retention of polar compounds and weaken the hydrophobic retention of nonpolar compounds, thereby effectively differentiating target compounds with varied physical and chemical properties. Consequently, multiple target analytes of diverse properties can be separated in relatively short time. The 14 kinds of OPEs in this study have large differences in various properties such as polarity, and their retention on the reversed-phase column differs strongly. Some strongly polar OPEs are poorly retained and thus not well separated from the matrix interference peaks, whereas some strongly hydrophobic components have low separation efficiency because of their longer retention time. Therefore, in this study, the Mixed-Mode HILIC-1 column was used for the HPLC-MS/MS analysis to account for the large polarity difference among the 14 kinds of target OPEs. Two kinds of combinations (acetonitrile with water and acetonitrile with 50 mmol/L ammonium acetate aqueous solution) were tested as the mobile phase with gradient elution. It was found that both systems could give sharp symmetrical peaks for all 14 OPEs, and the analytical sensitivity was high when acetonitrile/water was used. Therefore, the acetonitrile/water system was eventually chosen as the mobile phase for separation.In addition, the MS-related parameters of 14 OPEs were optimized to obtain their optimal sensitivity and stability. The optimized mass spectrometry parameters, including qualitative and quantitative ion pairs, declustering voltage (DP), inlet voltage (EP), and collision voltage (CE), are listed in S/N = 3). The result showed that the LODs of the 14 OPEs ranged in 0.015–1.33 ng/g  were measured under the optimized chromatographic and mass spectrometry conditions. The results showed that all 14 OPEs in the concentration range of 0.1–500 ng/mL showed a good linear response with a correlation coefficient of above 0.99. The limits of detection (LODs) were defined as the concentrations resulting in a signal-to-noise ratio of 3 (.33 ng/g .n = 10), which were extracted under the optimized conditions. Five nonspiked final extracts were directly run in the LC-MS/MS system, while the other five extracts were analyzed after being spiked with 10 ng of the native and isotopic standard. The standard in acetonitrile solution with the concentration of OPEs at 10 ng/mL was also analyzed simultaneously with the final extracts. The ME was calculated based on the peak areas of nonspiked and spiked extracts (Anonspiked and Aspiked) and the standard solution (Astandard) using the equation: ME% = (Aspiked − Anonspiked)/Astandard ∗ 100. As shown in The matrix effect (ME) was evaluated using OPE-free plastic and textile samples  of the OPEs to the OPE-free plastic and textile samples, and the analysis was then run under the optimized conditions to verify the effectiveness and precision of the method. Each concentration level was tested in 3 replicates. The established method is applied to the analysis of target OPEs in commercially available fall protection equipment (safety helmets and ropes). The safety helmets were divided into shell plastics and internal materials before extraction and analysis. The results showed that all OPEs were detected in the fall protection equipment except that TMP was not detected in safety helmets . The intBy optimizing the extraction conditions, separation conditions, and mass spectrometry detection parameters, an analytical method was developed for testing 14 kinds of OPEs in fall protection equipment. The developed method features accelerated solvent extraction of the analytes followed by purification with a solid-phase extraction column and finally analysis by HPLC-MS/MS. The method is rapid, sensitive, and reproducible and can readily detect OPEs in fall protection equipment  made of related materials.