Journal of AOAC International最新文献

{"title":"Full Validation of an HPLC-UV Analytical Method for Azithromycin Quantification Using Comparative Approaches: Total Error and ISO-GUM for Assessment of Uncertainty.","authors":"Wafaa El-Ghaly, Asmae Elouari, Lamia Zaari Lambarki, Samir Ahid, Taha El Kamli, Adnane Benmoussa, Fadil Bakkali, Nour-Iddin Bamou, Taoufiq Saffaj, Fayssal Jhilal","doi":"10.1093/jaoacint/qsaf044","DOIUrl":"10.1093/jaoacint/qsaf044","url":null,"abstract":"<p><strong>Background: </strong>Azithromycin is a complex molecule derived from erythromycin. The control of its dosage in conventional release tablets requires the analytical validation of its method to ensure accurate quantification and provide confidence in the reliability of the results for informed decision-making.</p><p><strong>Objective: </strong>This study aims to validate an innovative method for azithromycin quantification using the accuracy profile. Additionally, a comparison is made between the uncertainty measurements calculated from the validation data using two formulas proposed by Feinberg et al. and Saffaj and Ihssane and contrasted with the ISO GUM approach.</p><p><strong>Methods: </strong>A liquid chromatography system intended for azithromycin analysis equipped with a reversed-phase C18 stationary phase consisting of octadecyl silyl vinyl polymer in a UV detector operating at 210 nm at a temperature of 40°C in isocratic elution using a mobile phase of acetonitrile and dipotassium hydrogen phosphate buffer (6.7 g/L), in the fraction of (60:40, v/v) at pH = 8.</p><p><strong>Results: </strong>The various accuracy profiles are illustrated to ensure that a known quantity of anticipated findings acquired through the method stand inside the tolerance interval of 95% and remain within the previously set acceptance limits of ±5%. Measurement uncertainty provides comparable values using both formulas of the total error approach. However, it was observed that the ISO-GUM approach tends to overestimate the expanded uncertainty. Specifically, while the ISO-GUM approach provides a rigorous framework, the use of the validation data offers a more empirical uncertainty estimation.</p><p><strong>Conclusion: </strong>The approach based on the total error grants the ability to accurately close the routine uncertainty, emphasizing a complete validation.</p><p><strong>Highlights: </strong>The proposed method is robust for pharmaceutical application, demonstrating good accuracy, with 95% of tolerance and uncertainty limits falling within the predefined acceptance limits of ±5%.</p>","PeriodicalId":94064,"journal":{"name":"Journal of AOAC International","volume":" ","pages":"506-518"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144059156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ochratoxin A in Human Milk From the MIREC Study.","authors":"Iulia Popa, The Minh Luong, Tye E Arbuckle, Jillian Ashley Martin, Terence Koerner, Jason Carere","doi":"10.1093/jaoacint/qsaf051","DOIUrl":"10.1093/jaoacint/qsaf051","url":null,"abstract":"<p><strong>Background: </strong>Ochratoxin A (OTA) is a mycotoxin produced by multiple fungal species and is found in a variety of foods. Ingestion of OTA-contaminated foods by lactating mothers can lead to OTA exposure in infants.</p><p><strong>Methods: </strong>To help assess infants' exposure to OTA, milk samples from the Maternal-Infant Research on Environmental Chemicals (MIREC) Human Milk Study were analyzed. Human milk samples were collected (n = 494) and analyzed for OTA levels by HPLC.</p><p><strong>Results and discussion: </strong>The mean OTA concentration was 7.32 ± 9.25 ng/L, with 390 (79%) test samples testing positive for OTA and a range of 4.5-192 ng/L. Based on the food consumption questionnaires distributed among participants, higher OTA levels were observed with higher consumption of cottage cheese, hot cereal, and whole-grain bread and significant differences were found in OTA levels at different sites. The mean OTA level in the analyzed milk test samples was well below the amount found in infant formulas sold in Canada, which was determined by Health Canada to be safe.</p><p><strong>Conclusions: </strong>The concentrations of OTA found in human milk in this study are well below the amount deemed safe in infant formula by Health Canada and, therefore, unlikely to be of concern to infant health.</p>","PeriodicalId":94064,"journal":{"name":"Journal of AOAC International","volume":" ","pages":"652-657"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144175586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Method Development for Determining β-Nicotinamide Mononucleotide (NMN) in Cosmetics Using m-PFC-HPLC.","authors":"Tao Lan, Wenyu Zhang, Hongtao Chu, Zhenyu Yun, Bin Qu","doi":"10.1093/jaoacint/qsaf017","DOIUrl":"10.1093/jaoacint/qsaf017","url":null,"abstract":"<p><strong>Background: </strong>As a new cosmetic ingredient, NMN is widely used in cosmetics production, but due to the lack of a detection method, QC of related products cannot be achieved.</p><p><strong>Objective: </strong>This study will develop a detection method for NMN in three matrixes (facial mask essence, emulsion, and cream) for QC of related cosmetics.</p><p><strong>Methods: </strong>Given the high ester content in facial emulsions and creams, which can hinder the detection of trace substances, a novel multi-plug filtration clean-up (m-PFC) purification column packed with multi-walled carbon nanotubes (MWCNTs) was employed to purify these matrixes. An HPLC method for NMN in three matrixes (facial mask essence, emulsion, and cream) was established. Methodological verification was conducted.</p><p><strong>Results: </strong>Results demonstrated a good linear relationship within a range of 5.0-500 μg/mL, with an LOQ of 5.0 mg/kg. The RSD of the precision experiment was less than 3%, and the RSD for six repeated experiments ranged from 1.2 to 5.3%, indicating the method's stability, reliability, and good repeatability. Recovery rates in the three cosmetic matrixes were between 93.9 and 109.4%, with an RSD below 3.7%. This method was applied to detect NMN content in seven cosmetics purchased from an e-commerce platform; NMN was not detected in some products claiming to contain NMN.</p><p><strong>Conclusion: </strong>This method had the advantages of simple operation, high sensitivity, and good accuracy, and provides technical support for cosmetic regulation.</p><p><strong>Highlights: </strong>Through this study, we should raise awareness and supervision of NMN cosmetics by establishing relevant standards.</p>","PeriodicalId":94064,"journal":{"name":"Journal of AOAC International","volume":" ","pages":"489-496"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143805210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of Neutral Detergent Fiber Analysis Methods for Feed Ingredients, Diets, and Feces of Pigs.","authors":"Yoojin Koh, Jeonghyeon Son, Beob Gyun Kim","doi":"10.1093/jaoacint/qsaf030","DOIUrl":"10.1093/jaoacint/qsaf030","url":null,"abstract":"<p><strong>Background: </strong>An accurate determination of fiber concentrations in feeds and feces is critical for the measurement of fiber digestibility in pigs. The method of AOAC INTERNATIONAL for determining amylase-treated neutral detergent fiber (aNDF; Method 2002.04) has been widely used for pig diets. To overcome the complexity of the AOAC procedure, the Ankom method is also available for determining aNDF. Although these two methods have been compared for ruminant diets and feces, a comparison of the methods for pig diets and feces has not been documented.</p><p><strong>Objective: </strong>The objective was to compare aNDF values determined by the AOAC (aNDFAOAC) and the Ankom methods (aNDFAnkom) of ingredients, diets, and feces for pigs.</p><p><strong>Methods: </strong>A total of 255 test samples, consisting of 26 feed ingredients, 39 diets, and 190 feces of pigs, were analyzed for aNDF. To compare the AOAC Method 2002.04 and Ankom methods for aNDF, regression analyses were performed with the aNDFAnkom minus the mean aNDFAnkom as an independent variable and the aNDFAOAC minus the aNDFAnkom as a dependent variable.</p><p><strong>Results: </strong>The aNDFAnkom were greater than the aNDFAOAC by 2.90% (standard error = 0.63; P < 0.001) on average for ingredients and by 2.56% (standard error = 0.34; P < 0.001) on average for diets. For feces, the aNDFAnkom were greater than the aNDFAOAC by 1.30% (standard error = 0.32; P < 0.001) on average. The differences between the aNDFAnkom and aNDFAOAC were not consistent across the data ranges represented by a linear bias (slope = -0.16; standard error = 0.04; P < 0.001) in feces.</p><p><strong>Conclusion: </strong>ANDF concentrations determined by the Ankom method were greater than from the AOAC method in pig feeds and feces.</p><p><strong>Highlights: </strong>Despite convenience, the Ankom method yields greater aNDF values compared with the AOAC method.</p>","PeriodicalId":94064,"journal":{"name":"Journal of AOAC International","volume":" ","pages":"648-651"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143733666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving Reproducibility of HPTLC Analysis for Cranberry Supplements through Digitization and Chemometric Preprocessing.","authors":"Mengliang Zhang, Jianghao Sun, Elizabeth Corwin, James M Harnly","doi":"10.1093/jaoacint/qsaf063","DOIUrl":"https://doi.org/10.1093/jaoacint/qsaf063","url":null,"abstract":"<p><strong>Background: </strong>High-performance thin-layer chromatography (HPTLC) is widely used for the identification and quality assessment of botanical supplements. However, traditional interpretation methods are subjective, and variability between plates hinders reproducibility and inter-plate comparisons.</p><p><strong>Objective: </strong>This study aimed to enhance the reproducibility and analytical utility of HPTLC by digitizing chromatograms and applying chemometric preprocessing to cranberry dietary supplement analysis.</p><p><strong>Method: </strong>Cranberry supplements of diverse dosage forms were extracted and analyzed using a standardized HPTLC protocol. Plates were derivatized with natural products and anisaldehyde reagents and imaged under multiple lighting conditions. Digital chromatograms were processed using normalization and retention factor (RF) alignment. Chemometric methods, including principal component analysis (PCA) and analysis of variance principal component analysis (ANOVA-PCA), were applied to assess variability and improve classification.</p><p><strong>Results: </strong>The digitization and preprocessing workflow significantly reduced plate-related variability while enhancing classification accuracy. RF alignment lowered between plate variance from 23% to 11%, while increasing sample-type variance from 59% to 79%. Combining data from multiple derivatization and imaging conditions improved chemical fingerprinting and enabled tighter clustering in PCA models.</p><p><strong>Conclusions: </strong>The integration of digitized HPTLC data with chemometric preprocessing modernizes the analytical workflow, improves reproducibility, and enables more robust and interpretable botanical fingerprinting. This approach supports improved quality control of botanical products and aligns with emerging standards for data transparency and reusability.</p><p><strong>Highlights: </strong>Digitization and alignment reduce HPTLC variability and enhance reproducibility. Combined profiles from multiple derivatization conditions improve sample classification. Chemometric analysis enables better interpretation and data-driven quality control and assessment for botanicals.</p>","PeriodicalId":94064,"journal":{"name":"Journal of AOAC International","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of the OnSite® Gluten Test Kit for Detection of Gluten in Selected Foods and Environmental Surfaces: AOAC Performance Tested MethodSM 012501.","authors":"Meiting Wu, Lora Benoit, Cesar Nadala, David P Cox, Bryan Ndiritu, Anna M Willie, Kissi Yesu, Mansour Samadpour","doi":"10.1093/jaoacint/qsaf060","DOIUrl":"https://doi.org/10.1093/jaoacint/qsaf060","url":null,"abstract":"<p><strong>Background: </strong>The OnSite® Gluten Test Kit is a qualitative immunochromatographic assay designed for the detection of gluten in foods and on environmental surfaces.</p><p><strong>Objective: </strong>To validate the performance of the OnSite Gluten Test Kit in rice flour, oat flour, spice mix, and bread, and on stainless steel surface.</p><p><strong>Methods: </strong>The kit was assessed for cross-reactivity, interference, detection capability of spiked and incurred gluten, recovery from stainless steel surfaces, lot-to-lot consistency, robustness, and stability.</p><p><strong>Results: </strong>Testing revealed no cross-reactivity or interference from a panel of gluten-free food items, or susceptibility to high analyte concentration. Analysis of selected spiked or incurred test materials at various estimated concentrations of gluten supported claimed detection capabilities (CDC) ranging from 5 to 20 mg/kg gluten depending on the aliquot volume and food matrix. The method detected wheat gluten present on stainless steel at a contamination level of 11 µg gluten/100 cm2 (POD 0.95, CI 0.76-1.00). Testing results also indicated consistency, robustness, and kit stability. Independent laboratory testing of select food matrixes supported the findings of the candidate laboratory.</p><p><strong>Conclusions: </strong>The performance of the OnSite Gluten Test Kit was validated on gluten spiked or incurred into rice flour, oat flour, spice mix, and bread, and on stainless steel surfaces.</p><p><strong>Highlights: </strong>The OnSite Gluten Test Kit offers an easy-to-use assay method to detect gluten in select foods and on stainless steel surfaces. The testing format affords the user flexibility in their choice of gluten detection thresholds.</p>","PeriodicalId":94064,"journal":{"name":"Journal of AOAC International","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Outlier identification method based on multi-model weighted consensus in conjunction with Monte Carlo Cross-Validation.","authors":"Yujing Wang, Zhengguang Chen, Jinming Liu, He Wang","doi":"10.1093/jaoacint/qsaf061","DOIUrl":"https://doi.org/10.1093/jaoacint/qsaf061","url":null,"abstract":"<p><strong>Background: </strong>The accurate identification and removal of outliers are fundamental to the development of a robust model.</p><p><strong>Objective: </strong>Nevertheless, relying solely on a single model for outlier identification may prove inadequate for accurately identifying all outliers, potentially leading to false positives, false negatives, and model dependence.</p><p><strong>Methods: </strong>This study introduces a method termed Monte Carlo cross-validation in conjunction with multiple models of Weighted Consensus for outlier identification (MCWC). The proposed method integrates Monte Carlo random sampling with three distinct modeling methods: Partial Least Squares Regression (PLSR), Gaussian Process Regression (GPR), and Support Vector Regression (SVR). This integration allows for the amalgamation of predictions from each model, facilitating the identification of outliers effectively.</p><p><strong>Results: </strong>This study employed a dataset comprising 305 sorghum samples as the experimental foundation. The predictive model for sorghum protein was built using the data after removing outliers using the single model method and the MCWC method, respectively. The experimental results indicate that the dataset, which was obtained by removing outliers using a single modeling method, is appropriate for further modeling with the same method. However, it is not suitable for modeling with other methods due to issues related to model dependence. After applying the MCWC method to remove outliers, the average R2 of the model prediction set was found to be 0.8525. In contrast, the average R2 of the model prediction set, obtained by applying the Monte Carlo method combined exclusively with PLSR for outlier removal, is 0.8037.</p><p><strong>Conclusion: </strong>The MCWC method exhibits superior accuracy in identifying outliers and effectively addresses challenges such as false positive, false negative, and model dependence in the process of identifying near-infrared spectral outliers. This enhances the overall predictive performance of the calibration model for spectral quantitative analysis.</p><p><strong>Highlights: </strong>A multi-model dynamic weighted consensus outlier identification for NIRS data was proposed. This dynamic weighting method effectively addresses the biases that can occur with simple averaging. The data after removing outliers using consensus methods is more suitable for modeling with a wider range of models.</p>","PeriodicalId":94064,"journal":{"name":"Journal of AOAC International","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Genetics and Environment on Cranberry Fruit Metabolites.","authors":"James Harnly, Ping Geng, James Polashock, Pei Chen, Jennifer Johnson, Nicholi Vorsa","doi":"10.1093/jaoacint/qsaf056","DOIUrl":"https://doi.org/10.1093/jaoacint/qsaf056","url":null,"abstract":"<p><p>Cranberry fruit samples of 15 genotypes (cultivars and accessions) grown in 16 locations in 4 states (MA, NJ, OR, and WI) and a Canadian province (British Columbia) were analyzed by non-targeted fuzzy chromatography-direct injection mass spectrometry (FC-DIMS). The data collected for 206 ions were analyzed by multifactorial multivariate analysis of variance-principal component analysis (MFMV-ANOVA-PCA). MFMV-ANOVA-PCA showed that sample composition varied statistically (p < 0.001) with respect to the major factors (state/province, growing location, genotype, and analytical batch) and cross factors (genotype-state/province and genotype-growing location). MFMV-ANOVA-PCA score plots verified a systematic variation with respect to 42 genotype-state/province pairs and 82 genotype-growing location pairs. MFMV-ANOVA-PCA variable loadings identified major ions that varied with each of the major factors and cross factors and 56 ions were annotated. The location-ion count matrix was transposed and analyzed by hierarchical cluster analysis producing dendrograms that grouped ions with respect to metabolic pathways for either the genotype-state/province or genotype-growing location pairs. Annotation of the ions in the hierarchical clusters allowed evaluation of the impact of genetics and location on compounds of interest. Ions expected to correlate with fruit quality measurements (brix, titratable acid, total anthocyanins, and total proanthocyanidins) were identified. This study demonstrates that mass spectral data coupled with chemometric analysis is a valuable tool for predicting the composition of specific genotypes for specific growing locations. The general design of this study can be used as a model for other food plants.</p>","PeriodicalId":94064,"journal":{"name":"Journal of AOAC International","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144188726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simultaneous determination of five alkaloids in extracted and non-extracted poppy APIs by HPLC.","authors":"QiuPing Huang, Chao Li, Ruifeng Hao, Hua Tang, Qin Feng, Huiyue Cheng, Chen Zhu, Jianhua Wang","doi":"10.1093/jaoacint/qsaf049","DOIUrl":"https://doi.org/10.1093/jaoacint/qsaf049","url":null,"abstract":"<p><strong>Background: </strong>Poppy Active Pharmaceutical Ingredients (APIs) are mainly used in the production of antitussives, analgesics, and other preparations. The alkaloid components play a major role, but the use of some alkaloids can cause dependence and toxic side effects in patients.</p><p><strong>Objective: </strong>The main aim of this study was to develop an effective and simple high-performance liquid chromatography (HPLC) for the simultaneous determination of five alkaloids in three APIs.</p><p><strong>Method: </strong>Waters XBridge C18 column (4.6 mm × 150 mm, 3.5 μm) was used as the chromatographic column. Mobile phase A was composed of 5.5 mmol/L sodium heptane sulfonate solution-acetonitrile-methanol-phosphoric acid (83:7:10:0.22, v/v/v/v), and Mobile phase B was composed of 5.5 mmol/L sodium heptane sulfonate solution-acetonitrile-methanol-phosphoric acid (60:15:25:0.45, v/v/v/v). The flow rate was 1.2 mL/min; The detection wavelength was 230 nm; The column temperature was 40 °C.</p><p><strong>Results: </strong>The HPLC method was suitable for the simultaneous determination of the contents of five alkaloids in three APIs. The verification experiment showed that the linear relationship of the five alkaloids in their respective ranges was good (R2 ≥ 0.998); The average recoveries ranged from 87.62 to 103.18%; The RSDs of repeatabilities were 0.3∼2.7%.</p><p><strong>Conclusions: </strong>In this study, a new HPLC method was developed and successfully validated. Compared with the determination method of opium alkaloids specified in Pharmacopoeia, this HPLC method does not need a complex sample pretreatment process, improves detection efficiency, avoids the use of highly corrosive reagents, and reduces the experimental risk. It can simultaneously meet the determination of five alkaloids in three APIs.</p><p><strong>Highlights: </strong>This method can simultaneously quantify five alkaloids in three poppy APIs without a complex sample pretreatment process and the application of strong corrosive solvents. It is applied to these APIs for the first time, expanding the scope of alkaloid analysis and providing new data for comparative studies of different API sources.</p>","PeriodicalId":94064,"journal":{"name":"Journal of AOAC International","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144056052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Salmonella Detection in Beijing's Surface Water: Unveiling Rare Serotypes with a Modified Moore Swab (MMS) Method.","authors":"Xueshuo Wang, Yue Dou, Jingyun Li, Yao Bai, Shenghui Cui","doi":"10.1093/jaoacint/qsae089","DOIUrl":"10.1093/jaoacint/qsae089","url":null,"abstract":"<p><strong>Background: </strong>Salmonella, a notorious foodborne pathogen with a wide range of hosts, poses a significant public health concern globally. Contaminated surface water acts as a potential source of Salmonella transmission.</p><p><strong>Objective: </strong>To optimize a Salmonella detection method from large-volume water and analyze surface water samples in Beijing and characterize Salmonella isolates from these samples by whole genome sequencing.</p><p><strong>Methods: </strong>A microbial enrichment device based on the modified Moore swab (MMS) design was optimized and validated. Thirty-five water samples were collected and analyzed for Salmonella from 11 park lakes, two rivers, and two farms. Multiple characteristics of isolates were analyzed using antibiotic antimicrobial testing and whole genome sequencing.</p><p><strong>Results: </strong>The optimized MMS unit showed high efficiency (over 80% recovery) and a low detection limit (100 cells) for enriching and isolating Salmonella from large-volume water (10 L). Compared to the conventional method, the MMS device significantly improved Salmonella detection efficiency (62.86 versus 8.57%) in Beijing's surface water. Most of the Salmonella isolates from surface water belonged to rare serotypes from water wildlife susceptible to all the tested antimicrbials.</p><p><strong>Conclusion: </strong>The study demonstrates the optimized MMS's effectiveness for on-site enrichment of pathogens from large-volume water, validates the accuracy and sensitivity of a Salmonella detection method for surface water, and reveals previously unknown information about Salmonella contamination in Beijing's public water system.</p><p><strong>Highlights: </strong>Salmonella concentrations in water are typically very low: implementation of this method would successfully realize large-volume water sampling and on-site pathogen enrichment, and significantly improve Salmonella detection efficiency in surface water.</p>","PeriodicalId":94064,"journal":{"name":"Journal of AOAC International","volume":" ","pages":"429-434"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}