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Author(s):  
Legese Chelkeba ◽  
Korinan Fanta ◽  
Temesgen Mulugeta ◽  
Tsegaye Melaku

Abstract Background Globally, antimicrobial resistance (AMR) restricted the armamentarium of the health care providers against infectious diseases, mainly due to the emergence of multidrug resistant. This review is aimed at providing contemporary bacterial profile and antimicrobial resistance pattern among pregnant women with significant bacteriuria. Methods Electronic biomedical databases and indexing services such as PubMed/MEDLINE, Web of Science, EMBASE and Google Scholar were searched. Original records of research articles, available online from 2008 to 2021, addressing the prevalence of significant bacteriuria and AMR pattern among pregnant women and written in English were identified and screened. The relevant data were extracted from included studies using a format prepared in Microsoft Excel and exported to STATA 14.0 software for the outcome measure analyses and subgrouping. Results The data of 5894 urine samples from 20 included studies conducted in 8 regions of the country were pooled. The overall pooled estimate of bacteriuria was 15% (95% CI 13–17%, I2 = 77.94%, p < 0.001) with substantial heterogeneity. The pooled estimate of Escherichia coli recovered from isolates of 896 urine samples was 41% (95% CI 38–45%) followed by coagulase-negative Staphylococci, 22% (95% CI 18–26%), Staphylococcus aureus, 15% (95% CI 12–18%), Staphylococcus saprophytic, 12% (95% CI 6–18%) Proteus mirabilis, 7% (95% CI 4–10%), Enterococcus species, 6% (0–12%), Pseudomonas aeruginosa, 4% (2–6%), Citrobacter species, 4% (95% CI 2–4%), Group B streptococcus, 3% (1–5%), and Enterobacter species, 2% (1–4%). Multidrug resistance proportions of E. coli, Klebsiella species, Staphylococcus aureus and Coagulase negative staphylococci, 83% (95% CI 76–91%), 78% (95% CI 66–90%), 89% (95% CI 83–96%), and 78% (95% CI 67–88%), respectively. Conclusion The result of current review revealed the occurrence of substantial bacteriuria among pregnant women in Ethiopia. Resistance among common bacteria (E. coli, Klebsiella species, Staphylococci species) causing UTIs in pregnant women is widespread to commonly used antibiotics. The high rate of drug resistance in turn warrants the need for regular epidemiological surveillance of antibiotic resistance and implementation of an efficient infection control and stewardship program.


Author(s):  
Daniel Grau ◽  
Nicole Grau ◽  
Quentin Gascuel ◽  
Christian Paroissin ◽  
Cécile Stratonovitch ◽  
...  

Abstract France is the first pesticide-consuming country in Europe. Glyphosate is the most used pesticide worldwide and glyphosate is detected in the general population of industrialized countries, with higher levels found in farmers and children. Little data was available concerning exposure in France. Our objective was to determine glyphosate levels in the French general population and to search for an association with seasons, biological features, lifestyle status, dietary habits, and occupational exposure. This study includes 6848 participants recruited between 2018 and 2020. Associated data include age, gender, location, employment status, and dietary information. Glyphosate was quantified by a single laboratory in first-void urine samples using ELISA. Our results support a general contamination of the French population, with glyphosate quantifiable in 99.8% of urine samples with a mean of 1.19 ng/ml + / − 0.84 after adjustment to body mass index (BMI). We confirm higher glyphosate levels in men and children. Our results support glyphosate contamination through food and water intake, as lower glyphosate levels are associated with dominant organic food intake and filtered water. Higher occupational exposure is confirmed in farmers and farmers working in wine-growing environment. Thus, our present results show a general contamination of the French population with glyphosate, and further contribute to the description of a widespread contamination in industrialized countries.


2022 ◽  
Vol 21 (1) ◽  
Author(s):  
Bernard Laubscher ◽  
Manuel Diezi ◽  
Raffaele Renella ◽  
Edward A. D. Mitchell ◽  
Alexandre Aebi ◽  
...  

Abstract Background Neonicotinoids (NN) are selective neurotoxic pesticides that bind to insect but also mammal nicotinic acetycholine receptors (nAChRs). As the most widely used class of insecticides worldwide, they are ubiquitously found in the environment, wildlife, and foods, and thus of special concern for their impacts on the environment and human health. nAChRs are vital to proper brain organization during the prenatal period and play important roles in various motor, emotional, and cognitive functions. Little is known on children’s contamination by NN. In a pilot study we tested the hypothesis that children’s cerebro-spinal fluid (CSF) can be contaminated by NN. Methods NN were analysed in leftover CSF, blood, and urine samples from children treated for leukaemias and lymphomas and undergoing therapeutic lumbar punctions. We monitored all neonicotinoids approved on the global market and some of their most common metabolites by ultra-high performance liquid chromatography-tandem mass spectrometry. Results From August to December 2020, 14 children were consecutively included in the study. Median age was 8 years (range 3–18). All CSF and plasma samples were positive for at least one NN. Nine (64%) CSF samples and 13 (93%) plasma samples contained more than one NN. Thirteen (93%) CSF samples had N-desmethyl-acetamiprid (median concentration 0.0123, range 0.0024–0.1068 ng/mL), the major metabolite of acetamiprid. All but one urine samples were positive for ≥ one NN. A statistically significant linear relationship was found between plasma/urine and CSF N-desmethyl-acetamiprid concentrations. Conclusions We have developed a reliable analytical method that revealed multiple NN and/or their metabolites in children’s CSF, plasma, and urine. Our data suggest that contamination by multiple NN is not only an environmental hazard for non-target insects such as bees but also potentially for children.


2022 ◽  
Author(s):  
Lingfei Li ◽  
Yanhai Feng ◽  
Junhui Zhang ◽  
Qiong Zhang ◽  
Jun Ren ◽  
...  

Abstract Background Diabetic nephropathy (DN) involves various structural and functional changes because of chronic glycemic assault and kidney failure. Proteinuria is an early clinical manifestation of DN, but the associated pathogenesis remains elusive. This study aimed to investigate the role of microtubule associated protein 4 (MAP4) phosphorylation (p-MAP4) in proteinuria in DN and its possible mechanisms. Methods In this study, the urine samples of diabetic patients and kidney tissues of streptozotocin (STZ)-induced diabetic mice were obtained to detect changes of microtubule associated protein 4 (MAP4) phosphorylation. A murine model of hyperphosphorylated MAP4 was established to examine the effect of MAP4 phosphorylation in DN. Podocyte was applied to explore changes of kidney phenotypes and potential mechanisms with multiple methods. Results Our results demonstrated elevated content of p-MAP4 in diabetic patients’ urine samples, and increased kidney p-MAP4 in streptozocin (STZ)-induced diabetic mice. Moreover, p-MAP4 triggered proteinuria with aging in mice, and induced epithelial-to-mesenchymal transition (EMT) and apoptosis in podocytes. Additionally, p-MAP4 mice were much more susceptible to STZ treatment and showed robust DN pathology as compared to wild-type mice. In vitro study revealed high glucose (HG) triggered elevation of p-MAP4, rearrangement of microtubules and F-actin filaments with enhanced cell permeability, accompanied with dedifferentiation and apoptosis of podocytes. These effects were significantly reinforced by MAP4 hyperphosphorylation, and were rectified by MAP4 dephosphorylation. Notably, pretreatment of p38/MAPK inhibitor SB203580 reinstated all HG-induced pathological alterations. Conclusions The findings indicated a novel role for p-MAP4 in causing proteinuria in DN. Our results indicated the therapeutic potential of MAP4 in protecting against proteinuria and related diseases.


2022 ◽  
Vol 189 (2) ◽  
Author(s):  
Víctor Vállez-Gomis ◽  
Sara Exojo-Trujillo ◽  
Juan L. Benedé ◽  
Alberto Chisvert ◽  
Amparo Salvador

Abstract A poly(methacrylic acid-co-ethylene glycol dimethacrylate)-based magnetic sorbent was used for the rapid and sensitive determination of tricyclic antidepressants and their main active metabolites in human urine. This material was characterized by magnetism measurements, zeta potential, scanning electron microscopy, nitrogen adsorption–desorption isotherms, and thermogravimetric analysis. The proposed analytical method is based on stir bar sorptive-dispersive microextraction (SBSDME) followed by liquid chromatography–tandem mass spectrometry. The main parameters involved in the extraction step were optimized by using the response surface methodology as a multivariate optimization method, whereas a univariate approach was employed to study the desorption parameters. Under the optimized conditions, the proposed method was properly validated showing good linearity (at least up to 50 ng mL−1) and enrichment factors (13–22), limits of detection and quantification in the low ng L−1 range (1.4–7.0 ng L−1), and good intra- and inter-day repeatability (relative standard deviations below 15%). Matrix effects were observed for the direct analysis of urine samples, but they were negligible when a 1:1 v/v dilution with deionized water was performed. Finally, the method was successfully applied to human urine samples from three volunteers, one of them consuming a prescribed drug for depression that tested positive for clomipramine and its main active metabolite. Quantitative relative recoveries (80–113%) were obtained by external calibration. The present work expands the applicability of the SBSDME to new analytes and new types of magnetic sorbents. Graphical abstract


2022 ◽  
Vol 8 ◽  
Author(s):  
Miriam C. Banas ◽  
Georg A. Böhmig ◽  
Ondrej Viklicky ◽  
Lionel P. Rostaing ◽  
Thomas Jouve ◽  
...  

Background: In an earlier monocentric study, we have developed a novel non-invasive test system for the prediction of renal allograft rejection, based on the detection of a specific urine metabolite constellation. To further validate our results in a large real-world patient cohort, we designed a multicentric observational prospective study (PARASOL) including six independent European transplant centers. This article describes the study protocol and characteristics of recruited better patients as subjects.Methods: Within the PARASOL study, urine samples were taken from renal transplant recipients when kidney biopsies were performed. According to the Banff classification, urine samples were assigned to a case group (renal allograft rejection), a control group (normal renal histology), or an additional group (kidney damage other than rejection).Results: Between June 2017 and March 2020, 972 transplant recipients were included in the trial (1,230 urine samples and matched biopsies, respectively). Overall, 237 samples (19.3%) were assigned to the case group, 541 (44.0%) to the control group, and 452 (36.7%) samples to the additional group. About 65.9% were obtained from male patients, the mean age of transplant recipients participating in the study was 53.7 ± 13.8 years. The most frequently used immunosuppressive drugs were tacrolimus (92.8%), mycophenolate mofetil (88.0%), and steroids (79.3%). Antihypertensives and antidiabetics were used in 88.0 and 27.4% of the patients, respectively. Approximately 20.9% of patients showed the presence of circulating donor-specific anti-HLA IgG antibodies at time of biopsy. Most of the samples (51.1%) were collected within the first 6 months after transplantation, 48.0% were protocol biopsies, followed by event-driven (43.6%), and follow-up biopsies (8.5%). Over time the proportion of biopsies classified into the categories Banff 4 (T-cell-mediated rejection [TCMR]) and Banff 1 (normal tissue) decreased whereas Banff 2 (antibody-mediated rejection [ABMR]) and Banff 5I (mild interstitial fibrosis and tubular atrophy) increased to 84.2 and 74.5%, respectively, after 4 years post transplantation. Patients with rejection showed worse kidney function than patients without rejection.Conclusion: The clinical characteristics of subjects recruited indicate a patient cohort typical for routine renal transplantation all over Europe. A typical shift from T-cellular early rejections episodes to later antibody mediated allograft damage over time after renal transplantation further strengthens the usefulness of our cohort for the evaluation of novel biomarkers for allograft damage.


Toxics ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 21
Author(s):  
Hsin-Chang Chen ◽  
Jung-Wei Chang ◽  
Yi-Chen Sun ◽  
Wan-Ting Chang ◽  
Po-Chin Huang

The development of a rapid analytical approach for determining levels of antibacterial agents, plasticizers, and ultraviolet filters in biosamples is crucial for individual exposure assessment. We developed an analytical method to determine the levels of four parabens—bisphenols A (BPA) and its analogs, triclosan (TCS), triclocarban, and benzophenone-3 (BP-3)—in human urine. We further measured the levels of these chemicals in children and adolescents. We used a supported liquid extraction (SLE) technique coupled with an isotope-dilution ultraperformance liquid chromatography-tandem mass spectrometry (ID-UPLC-MS/MS) method to assess the detection performance for these chemicals. Forty-one urine samples from 13 children and 28 adolescents were assessed to demonstrate the capability and feasibility of our method. An acceptable recovery (75.6–102.4%) and matrix effect (precision < 14.2%) in the three-level spiked artificial urine samples were achieved, and good performance of the validated ID-UPLC-MS/MS method regarding linearity, limits of detection, and quantitation was achieved. The within-run and between-run accuracy and precision also demonstrated the sensitivity and stability of this analytical method, applied after SLE. We concluded that the ID-UPLC-MS/MS method with SLE pretreatment is a valuable analytical method for the investigation of urinary antibacterial agents, plasticizers, and ultraviolet filters in humans, useful for human biomonitoring.


Author(s):  
Chanakarn Sanguarnsak ◽  
Kiattisak Promsuwan ◽  
Jenjira Saichanapan ◽  
Asamee Soleh ◽  
Kasrin Saisahas ◽  
...  

Abstract A new electrode material of phosphorus-doped multi-walled carbon nanotubes (P-MWCNTs) was developed as an electrochemical sensing element for amitriptyline (AMT). P-MWCNTs were hydrothermally synthesized and drop casted on a glassy carbon electrode (P-MWCNTs/GCE). The P-MWCNTs were morphologically, chemically and structurally characterized. The electrochemical characteristics of the P-MWCNTs/GCE were investigated by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and adsorptive stripping voltammetry (AdSV). The P-MWCNTs increased electron transfer at the GCE and the electrochemical conductivity of the electrode. Electrocatalytic activity toward the oxidation of AMT was excellent. In the optimal voltammetric condition, the P-MWCNTs/GCE produced linear ranges of 0.50 to 10 µg mL-1 and 10 to 40 µg mL-1. The limit of detection (LOD) and limit of quantification (LOQ) were 0.15 µg mL-1 (0.54 µM) and 0.52 µg mL-1 (1.80 µM), respectively. The developed sensor displayed good repeatability, reproducibility and specificity. The sensor successfully quantified AMT in pharmaceutical tablets, giving results consistent with spectrophotometric analysis. The sensor achieved recoveries from 98±2% to 101±5% from spiked urine samples. The proposed sensor could be applied to determine AMT in pharmaceutical and urine samples for forensic toxicology.


eLife ◽  
2022 ◽  
Vol 11 ◽  
Author(s):  
Wilmer Cristobal Guzman-Vilca ◽  
Manuel Castillo-Cara ◽  
Rodrigo M Carrillo-Larco

Global targets to reduce salt intake have been proposed but their monitoring is challenged by the lack of population-based data on salt consumption. We developed a machine learning (ML) model to predict salt consumption at the population level based on simple predictors and applied this model to national surveys in 54 countries. We used 21 surveys with spot urine samples for the ML model derivation and validation; we developed a supervised ML regression model based on: sex, age, weight, height, systolic and diastolic blood pressure. We applied the ML model to 54 new surveys to quantify the mean salt consumption in the population. The pooled dataset in which we developed the ML model included 49,776 people. Overall, there were no substantial differences between the observed and ML-predicted mean salt intake (p<0.001). The pooled dataset where we applied the ML model included 166,677 people; the predicted mean salt consumption ranged from 6.8 g/day (95% CI: 6.8-6.8 g/day) in Eritrea to 10.0 g/day (95% CI: 9.9-10.0 g/day) in American Samoa. The countries with the highest predicted mean salt intake were in Western Pacific. The lowest predicted intake was found in Africa. The country-specific predicted mean salt intake was within reasonable difference from the best available evidence. A ML model based on readily available predictors estimated daily salt consumption with good accuracy. This model could be used to predict mean salt consumption in the general population where urine samples are not available.


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