Global and regional final point-of-drinking water prevalence of Vibrio pathogens: a systematic analysis with socioeconomic, global health security, and WASH indices-guided meta-regressions.

The final point-of-drinking water (FPODW) exposure to Vibrio and waterborne pathogens remains a misaim surveillance target. Therefore, the current study purposed to estimate the global and regional prevalence of Vibrio pathogens in FPODW. Vibrio-FPODW data derived from integrated databases per PRISMA protocol were fitted to a random-intercept-logistic mixed-effects and meta-regression models. The global FPODW Vibrio prevalence was 5.13% (95%CI: 2.24-11.30) with 7.76% (6.84-8.78) cross-validated value. Vibrio prevalence in different FPODW varied with the highest in unclassified (13.98%, 3.98-38.95), household stored (6.42%, 1.16-28.69), municipal (4.39%, 1.54-11.90), and bottled (1.06%, 0.00-98.57) FPODW. Regionally, FPODW Vibrio prevalence varied significantly with highest in Africa (6.31%, 0.49-47.88), then Asia (4.83%, 2.01-11.18). Similarly, it varied significantly among income classification with the highest from low-income (8.77%, 0.91-50.05), then lower-middle-income (6.16%, 2.75-13.20), upper-middle-income (0.23%, 0.00-82.04), and 0.94% (0.19-2.72) in high-income economies. Among the WHO region, it varied significantly from 1.41% (0.17-10.45) in Eastern Mediterranean, 6.31% (0.49-47.88) in Africa to 8.86% (3.85-19.06) in South-East Asia and declining among SDI-quintiles from 11.64% (3.29-33.83) in Low-SDI, 10.59% (4.58-22.61) in High-middle-SDI to 0.26% (0.01-9.09) in Middle-SDI. FPODW Vibrio prevalence was 7.31% (2.94-17.03) in the low-GHSIG, followed by 4.55% (0.00-100.00) in the upper-GHSIG, and 2.21% (0.31-14.24) in middle-GHSIG; rural (4.18%, 0.06-76.17) and urban (5.28%, 2.35-11.44) settings. Also, sample size, SDI, SDI-quintiles, and nation significantly explained 14.12%, 10.91%, 30.35%, and 87.65% variance in FPODW Vibrio prevalence, respectively as a univariate influence. Additionally, 11.90% variance in FPODW Vibrio prevalence explained mortality rate attributed to unsafe WASH services. In conclusion, the study revealed a substantial high FPODW prevalence of Vibrio calling for initiative-taking and intentional surveillances of waterborne pathogens at the neglected stage across nations in order to achieve sustainably the SDG 3.

Global and regional prevalence of Cronobacter sakazakii in powdered milk and flour.

Cronobacter sakazakii (Cz) infections linked with powdered milk/flour (PMF) are on the increase in recent times. The current study aimed at assessing worldwide and regional prevalence of Cz in PMF. Cz-PMF-directed data were conscientiously mined in four mega-databases via topic-field driven PRISMA protocol without any restriction. Bivariate analysis of datasets was conducted and then fitted to random-intercept logistic mixed-effects regressions with leave-one-study-out-cross-validation (LOSOCV). Small-study effects were assayed via Egger's regression tests. Contributing factors to Cz contamination/detection in PMF were determined using 1000-permutation-bootstrapped meta-regressions. A total of 3761 records were found out of which 68 studies were included. Sample-size showed considerable correlation with Cz positivity (r = 0.75, p = 2.5e-17), Milkprod2020 (r = 0.33, p = 1.820e-03), and SuDI (r = - 0.30, p = 4.11e-03). The global prevalence of Cz in PMF was 8.39% (95%CI 6.06-11.51, PI: 0.46-64.35) with LOSOCV value of 7.66% (6.39-9.15; PI: 3.10-17.70). Cz prevalence in PMF varies significantly (p < 0.05) with detection methods, DNA extraction method, across continents, WHO regions, and world bank regions. Nation, detection method, world bank region, WHO region, and sample size explained 53.88%, 19.62%, 19.03%, 15.63%, and 9.22% of the true differences in the Cz prevalence in PMF, respectively. In conclusion, the results indicated that national will power in the monitoring and surveillance of Cz in PMF matched with adequate sample size and appropriate detection methods will go a long way in preventing Cz contamination and infections.

Prevalence of Listeria monocytogenes in milk in Africa: a generalized logistic mixed-effects and meta-regression modelling.

Listeria outbreaks and food recalls is on the raise globally. Milk particularly is highly susceptible to Listeria as its production and storage adequately support Listeria growth. The extent of milk contamination with Listeria monocytogenes (Lm) and preventative actions to halt milk associated outbreaks in Africa are unknown. Hence, this study aimed at assessing the national and subregional prevalence of Lm in milk in Africa and identify impacting factors via generalized logistic mixed-effects (GLMEs) and meta-regression modelling. Lm-milk-specific data acquired from primary studies according to standard protocol were fitted using a GLMEs. The GLMEs was subjected to leave-one-study-out-cross-validation (LOSOCV). Factors impacting Lm prevalence in milk were assayed via a 1000-permutation-assisted meta-regression-modelling. The pooled prevalence of Lm in milk in Africa was 4.35% [2.73-6.86] with a prediction interval (PI) of 0.14-59.86% and LOSOCV value of 2.43% [1.62-3.62; PI: 0.32-16.11%]. Western Africa had the highest prevalence [20.13%, 4.13-59.59], then Southern Africa [5.85%, 0.12-75.72], Northern Africa [4.67%, 2.82-7.64], Eastern Africa [1.91%, 0.64-5.55], and there was no record from Central Africa. In term of country, Lm prevalence in milk significantly (p < 0.01) varied from 0.00 to 90.00%. Whereas the Lm prevalence was negligibly different (p = 0.77) by milk type, raw-milk had the highest prevalence [5.26%], followed by fermented-milk [4.76%], boiled-milk [2.90%], pasteurized-milk [1.64%], and powdered-milk [1.58%]. DNA extraction approach did not significantly (p = 0.07) affect Lm prevalence (Boiling [7.82%] versus Kit [7.24%]) as well as Lm detection method (p = 0.10; (ACP [3.64%] vs. CP [8.92%] vs. CS [2.27%] vs. CSP [6.82%]). Though a bivariate/multivariate combination of all tested variables in meta-regression explained 19.68-68.75% (R2) variance in Lm prevalence in milk, N, nation, and subregion singly/robustly accounted for 17.61% (F1;65 = 7.5994; p = 0.005), 63.89% (F14;52 = 4.2028; p = 0.001), and 16.54% (F3;63 = 3.4743; p = 0.026), respectively. In conclusion, it is recommended that adequate sample size should be prioritized in monitoring Lm in milk to prevent spuriously high or low prevalence to ensure robust, plausible, and credible estimate. Also, national efforts/interests and commitments to Lm monitoring should be awaken.

Socioeconomic indices guided linear mixed-effects and meta-regression modelling of the temporal, global and regional prevalence of Helicobacter pylori in environmental waters: A class I carcinogen.

Environmental waters (EW) substantially lend to the transmission of Helicobacter pylori (Hp). But the increase in Hp infections and antimicrobial resistance is often attributed to socioeconomic status. The connection between socioeconomic status and Hp prevalence in EW is however yet to be investigated. This study aimed to assess the impacts of socioeconomic indices (SI: continent, world bank region (WBR), world bank income (WBI), WHO region, Socio-demographic Index (SDI quintile), Sustainable Development Index (SuDI), and Human Development Index (HDI)) on the prevalence of Hp in EW. Hp-EW data were fitted to a generalized linear mixed-effects model and SI-guided meta-regression models with a 1000-resampling test. The worldwide prevalence of Hp in EW was 21.76% [95% confidence interval [CI]: 10.29-40.29], which declined significantly from 59.52% [43.28-74.37] in 1990-99 to 19.36% [3.99-58.09] in 2010-19 and with increasing trend in 2020-22 (33.33%, 22.66-45.43). Hp prevalence in EW was highest in North America (45.12%, 17.07-76.66), then Europe (22.38%, 5.96-56.74), South America (22.09%, 13.76-33.49), Asia (2.98%, 0.02-85.17), and Africa (2.56%, 0.00-99.99). It was negligibly different among sampling settings, WBI, and WHO regions demonstrating highest prevalence in rural location [42.62%, 3.07-94.56], HIEs [32.82%, 13.19-61.10], and AMR [39.43%, 19.92-63.01], respectively. However, HDI, sample size, and microbiological method robustly predict Hp prevalence in EW justifying 26.08%, 21.15%, and 16.44% of the true difference, respectively. In conclusion, Hp is highly prevalence in EW across regional/socioeconomic strata and thus challenged the uses of socioeconomic status as surrogate for hygienic/sanitary practices in estimating Hp infection prevalence.

Machine learning-guided determination of Acinetobacter density in waterbodies receiving municipal and hospital wastewater effluents.

A smart artificial intelligent system (SAIS) for Acinetobacter density (AD) enumeration in waterbodies represents an invaluable strategy for avoidance of repetitive, laborious, and time-consuming routines associated with its determination. This study aimed to predict AD in waterbodies using machine learning (ML). AD and physicochemical variables (PVs) data from three rivers monitored via standard protocols in a year-long study were fitted to 18 ML algorithms. The models' performance was assayed using regression metrics. The average pH, EC, TDS, salinity, temperature, TSS, TBS, DO, BOD, and AD was 7.76 ± 0.02, 218.66 ± 4.76 µS/cm, 110.53 ± 2.36 mg/L, 0.10 ± 0.00 PSU, 17.29 ± 0.21 °C, 80.17 ± 5.09 mg/L, 87.51 ± 5.41 NTU, 8.82 ± 0.04 mg/L, 4.00 ± 0.10 mg/L, and 3.19 ± 0.03 log CFU/100 mL respectively. While the contributions of PVs differed in values, AD predicted value by XGB [3.1792 (1.1040-4.5828)] and Cubist [3.1736 (1.1012-4.5300)] outshined other algorithms. Also, XGB (MSE = 0.0059, RMSE = 0.0770; R2 = 0.9912; MAD = 0.0440) and Cubist (MSE = 0.0117, RMSE = 0.1081, R2 = 0.9827; MAD = 0.0437) ranked first and second respectively, in predicting AD. Temperature was the most important feature in predicting AD and ranked first by 10/18 ML-algorithms accounting for 43.00-83.30% mean dropout RMSE loss after 1000 permutations. The two models' partial dependence and residual diagnostics sensitivity revealed their efficient AD prognosticating accuracies in waterbodies. In conclusion, a fully developed XGB/Cubist/XGB-Cubist ensemble/web SAIS app for AD monitoring in waterbodies could be deployed to shorten turnaround time in deciding microbiological quality of waterbodies for irrigation and other purposes.

Human norovirus contamination challenge in fresh produce: a global prevalence and meta-analytic assessment.

AIMS: Among fresh produce (FP)-associated foodborne infections, human noroviruses (HNoV) are the leading causative agent. The present study aimed to assess the prevalence of HNoV in FP. METHODS AND RESULTS: FP-associated HNoV records mined from 5 repositories until 25/05/2022 according to PRISMA standards were appraised, fitted to a generalized linear mixed-effects model and subgroup analysed by sample type, genogroup, and geographical location. Further, heterogeneity was assessed in the model coupled with a leave-one-out-cross-validation. The overall prevalence of HNoV in FP was 9.3% (95% confidence interval [CI] 3.7-21.7. HNoV prevalence was higher in fruits (9.8%[3.7-23.5]) than vegetables (9.4%[3.1-25.3]). Regarding geographical distribution, FP-associated HNoV prevalence varied from Africa (25.8%, 5.7-66.7), Asia (23.2%[4.6-65.0]), Europe (5.6%[0.7-33.9]), North America (12.4%[1.8-52.7]) to South America (7.5%[0.0-100.0]). HNoV GI overall prevalence in FP was 5.3% (2.5-11.1) and varied by sample type (fruits: 4.9%[1.7-13.2]; vegetables: 5.8%[1.6-18.8]). While the occurrence of GII in FP was 1.7% (0.7-3.9) and varied by sample type (fruits: 2.5%[1.0-6.5]; vegetables: 0.9%[0.2-4.9]), GIGII (detection of both GI and GII) was 0.3% (0.1-1.0) with 0.4% (0.1-2.2) and 0.2% (0.0-1.5) in fruits and vegetables, respectively. In all cases, the test for sample/regional prevalence differences were not significantly different with the exception of GII regional prevalence differences (p = 0.03). CONCLUSIONS: This study suggests that FP represents a critical vehicle for HNoV dissemination, a global and a high risk for public health.

Using machine learning models to predict the effects of seasonal fluxes on Plesiomonas shigelloides population density.

Seasonal variations (SVs) affect the population density (PD), fate, and fitness of pathogens in environmental water resources and the public health impacts. Therefore, this study is aimed at applying machine learning intelligence (MLI) to predict the impacts of SVs on P. shigelloides population density (PDP) in the aquatic milieu. Physicochemical events (PEs) and PDP from three rivers acquired via standard microbiological and instrumental techniques across seasons were fitted to MLI algorithms (linear regression (LR), multiple linear regression (MR), random forest (RF), gradient boosted machine (GBM), neural network (NN), K-nearest neighbour (KNN), boosted regression tree (BRT), extreme gradient boosting (XGB) regression, support vector regression (SVR), decision tree regression (DTR), M5 pruned regression (M5P), artificial neural network (ANN) regression (with one 10-node hidden layer (ANN10), two 6- and 4-node hidden layers (ANN64), and two 5- and 5-node hidden layers (ANN55)), and elastic net regression (ENR)) to assess the implications of the SVs of PEs on aquatic PDP. The results showed that SVs significantly influenced PDP and PEs in the water (p < 0.0001), exhibiting a site-specific pattern. While MLI algorithms predicted PDP with differing absolute flux magnitudes for the contributing variables, DTR predicted the highest PDP value of 1.707 log unit, followed by XGB (1.637 log unit), but XGB (mean-squared-error (MSE) = 0.0025; root-mean-squared-error (RMSE) = 0.0501; R2 =0.998; medium absolute deviation (MAD) = 0.0275) outperformed other models in terms of regression metrics. Temperature and total suspended solids (TSS) ranked first and second as significant factors in predicting PDP in 53.3% (8/15) and 40% (6/15), respectively, of the models, based on the RMSE loss after permutations. Additionally, season ranked third among the 7 models, and turbidity (TBS) ranked fourth at 26.7% (4/15), as the primary significant factor for predicting PDP in the aquatic milieu. The results of this investigation demonstrated that MLI predictive modelling techniques can promisingly be exploited to complement the repetitive laboratory-based monitoring of PDP and other pathogens, especially in low-resource settings, in response to seasonal fluxes and can provide insights into the potential public health risks of emerging pathogens and TSS pollution (e.g., nanoparticles and micro- and nanoplastics) in the aquatic milieu. The model outputs provide low-cost and effective early warning information to assist watershed managers and fish farmers in making appropriate decisions about water resource protection, aquaculture management, and sustainable public health protection.

Global and regional prevalence of Helicobacter pylori in drinking waters: A sustainable, human development and socio-demographic indices based meta-regression-modelling.

Helicobacter pylori (Hp) transmission dynamics via drinking water (DW) has a far much higher direct and indirect public health disease burden than previously thought. This study aimed to assess the global prevalence of Hp in DW, distributions across regions and socioeconomic indices (continent, world bank income, Human Development Index (HDI), Sustainable Development Index (SuDI), Socio-Demographic Index (SDI) quintile, and WHO regions). Hp-DW related data mined from five databases until 10/12/2022 according to PRISMA standard were quality-appraised and fitted to a generalized linear mixed-effects model. Sub-group analysis and meta-regression-modelling coupled with a 1000-permutation test (⁎) were conducted. The global prevalence of Hp in DW was 15.7% (95% confidence interval [CI]: 7.98-27.5), which varied significantly by sampling methods (Moore swabbing (61.0% [0.00-100.0]) vs. grab sampling (13.68%[6.99-25.04])) and detection technique (non-culture (21.35%[9.13-42.31]) vs. cultured-based methods (Psubgroup < 0.01)). The period 1990-99 had the highest prevalence (41.24% [0.02-99.97]). Regarding regional designations, Hp prevalence in DW was significantly different being highest in North America (61.82% [41.03-79.02]) by continents, AMR (42.66% [20.81-67.82]) by WHO group, high HDI (24.64% [10.98-46.43]) by HDI group and North America (61.90% [2.79-98.93]) by world bank region (Psubgroup < 0.01). Generally, sample preparation, SuDI grouping, and detection/confirmation techniques, have significant effects on the detection/prevalence of Hp in DW (Psubgroup < 0.01). Hp prevalence in DW was not significantly different among rural and urban DW (Psubgroup = 0.90), world bank income groups (Psubgroup = 0.15), and SDI quintiles (Psubgroup = 0.07). Among the predictors examined, only sample size (p < 0.1, R∗2(coefficient of determinant) = 15.29%), continent (p∗val = 0.04), HDI (p∗val = 0.02), HDI group (p∗val = 0.05), and microbiological methods (p < 0.1; R∗2=28.09 %) predicted Hp prevalence in DW robustly. In conclusion, Hp prevalence is still endemic in DW regardless of the regional designations/improve DW supplies.

Prevalence of Laribacter hongkongensis in food and environmental matrices: A systematic review and meta-analysis.

Laribacter hongkongensis is a human pathogen harboured in food and environmental matrices. This present study aimed to meta-analysed the prevalence of L. hongkongensis in humans, aquatic products, food/non-food animals, and environmental waters to provide update information on the pathogen. Nine electronic databases were systematically searched for articles on L. hongkongensis and a random-effects-model meta-analysis on its prevalence was conducted. Assessment of heterogeneities and publication biases across the studies was determined by using the I2 statistic and Egger's regression/rank correlation tests of funnel plot, respectively. Furthermore, a meta-regression model was explored to unravel factors influencing the prevalence. A total of 39 documents were identified, of which, 33 articles were included as 98 sub-studies for the meta-analysis, and 87 sub-studies for subgroup-analysis. Overall, the prevalence of L. hongkongesis in human, aquatic products, food/non-food animals, and environmental waters was 8.5% (95% CI: 5.8-11.7). The leave-one-out influence analysis yielded a pooled prevalence of L. hongkongensis ranging from 8.1% (95% CI: 5.4-11.3) - 8.8% (95% CI: 5.8-12.3). Sub-group analysis found that the prevalence of L. hongkongensis was highest in Amphibian (54.6%, 95% CI: 41.3-67.6), followed by Pisces (7.9%, 95% CI: 5.3-10.9), Avian (0.5%, 95% CI: 0-5.8), and Mammal (0.5%, 95% CI: 0-3.6). In addition, Egger's regression-test of funnel plot suggests presence of publication (z = 4.2, p < 0.0001) in mammal subgroup. Multivariate meta-regression showed that the prevalence was significantly influenced by source type, class, and identification/detection method with the source type, class, and detection method specifically accounted for 25.49%, 11.28%, and 3.84% of the heterogeneity, respectively. Conclusively, the prevalence of L. hongkongensis decrease in order of Amphibian (54.6%), Pisces (7.9%), Avian (0.5%) and Mammal (0.5%). Aquatic products and environments are essential sources of the pathogen.

Systematic and meta-analysis of Mycobacterium avium subsp. paratuberculosis related type 1 and type 2 diabetes mellitus.

Global increase in diabetes (DM) prevalence necessitated the need to establish the association between DM and environmental triggers including MAP (Mycobacterium avium subsp. paratuberculosis) that have been postulated to play a role in DM etiopathology for effective management. The present investigation aimed to assess the odds ratio (OR) presenting the association between MAP and DM. MAP-related DM studies were systematically retrieved from 6 databases until 31 September 2021 according to PRISMA principles for data abstraction. The abstracted dataset was fitted to the fixed-effects (FE) and random-effects (RE) models using the Mantel-Haenszel approach. Sixteen studies involving 2072 participants (1152 DM patients (957 type 1 diabetes mellitus (T1DM) & 195 type 2 diabetes mellitus (T2DM)) and 920 healthy controls) met the inclusion criteria. Results revealed a significant association between anti-MAP antibodies (abs) seroprevalence and T1DM (FE: OR 7.47, 95% CI 5.50-10.14, p value < 0.0001; RE: OR 7.92, 95% CI 4.39-14.31, p < 0.0001) and MAP DNA with T1DM (FE: OR 4.70 (95% CI 3.10-7.13, p value < 0.0001), RE: OR 3.90 (95% CI 0.93-16.38, p value = 0.06)). Both anti-MAP abs and MAP DNA based meta-analyses had medium heterogeneity (I2 = 47.2-61.0%). Meanwhile, no significant association between MAP and T2DM (FE: OR 1.13, 95% CI 0.54-2.37, p value = 0.74; RE: OR 1.19; 95% CI 0.34-4.12, p value = 0.69), its OR magnitude exceeded 1 and prediction interval (0.09-15.29) suggest possibility of association between the duo in the future. The leave-one-out sensitivity analysis depicts a robust meta-analysis in all cases. In conclusion, the study manifests a positive association between MAP and T1DM, highlighting that MAP prevention and environmental control would indubitably revolutionize T1DM management. Also, its projects possible link between MAP and T2DM as more data becomes available. However, it remains elusive whether MAP triggers T1/T2DM or a mere comorbidity in T1/T2DM. Epidemiological activities to fill the global/regional data gaps on MAP-related T1DM and T2DM are advocated in order to assess the burden of MAP-related DM and improve their clinical management.

Systematic review and meta-analysis of Mycobacterium avium subsp. paratuberculosis as environmental trigger of multiple sclerosis.

Mycobacterium avium subsp. paratuberculosis (MAP) has been identified as one of the environmental agents that causes multiple sclerosis (MS). The global prevalence of MS has been upsurging over the years; however, efforts to divulge the role of MAP in MS have been limited. As a result, the present study aimed at assessing the odd ratios (ORs) associated MAP with the risk of MS. MAP-related MS data were obtained from 6 databases using the terms 'multiple sclerosis' or 'MS' and 'paratuberculosis' without regard for time or language restrictions following PRISMA standards. A total of 2,538 participants' data from 12 studies presenting anti-MAP antibodies and MAP DNA from 4 studies were fitted in random-effects (RE) and fixed-effects (FE) meta-analytic models. Furthermore, the between-study heterogeneity was measured using I2-values with a significant limit set at an I² > 75%. Analytical rigor and publication bias was determined using leave-one-out-analytics, Egger's tests, and p-curve analysis. In the FE and RE models, anti-MAP antibodies data significantly associated MS risk with MAP as 10.71 OR (95%-CI [7.78; 14.74], p-value < 0.0001) and 12.76 OR (95%-CI [8.13; 20.02], p-value < 0.0001) respectively, with an I2 value of 34.9% (95%-CI [0.0%; 67.2%]; p-value = 0.11). Similarly, the MAP DNA dataset in FE significantly present MS risk due to MAP as 5.53 OR (95%-CI [3.54; 8.66], p-value< 0.0001) while, RE showed 5.27 OR (95%-CI [3.22; 8.60], p = 0.0017), with an I2-value = 0.0% (95%-CI [0.0%; 84.7%]; p-value = 0.71). Eggers' test, on the other hand, found publication bias in anti-MAP antibodies data (intercept = 1.61, 95% CI: 0.45 - 2.77, t = 2.72, p = 0.021), but not in MAP DNA dataset (intercept = -5.57, 95% CI: -20.44 - 9.29, t = -0.74, p = 0.54). The robustness of the meta-analyses was demonstrated by all sensitivity analyses. In addition, there is no evidence of p-hacking observed (right-skewness test (PFull < 0.001, PHalf <0.001; statistical power ≥ 94% (95%-CI: 72.5%-99%)). In conclusion, the synthesis revealed a strong association between MAP and MS, indicating that MAP is a significant environmental agent that may trigger MS. Thus, early screening of MAP in MS cases may assist in the therapeutic approach to its management/treatment. Therefore, future studies should be tailored towards the role of MAP in the severity of MS phenotypes, as well as address global data gaps and low disease surveillance.

Arcobacter species in milk contamination: a prevalence-based systematic review and meta-analysis.

AIMS: Milk is consumed raw or minimally processed and plays a role in the dissemination of pathogens of public health concerns. The present investigation is aimed at assessing the occurrence of pathogenic Arcobacter species in 2945 milk samples. METHODS AND RESULTS: Arcobacter data systematically retrieved from 5 repositories until 20/02/2022 according to PRISMA principles was logit transformed and fitted using a generalized linear mixed-effects model. The between-study heterogeneity was estimated as I2-value. Leave-one-out-cross-validation and funnel plot with Egger's tests was used to assess the hardiness and bias in the model. The global prevalence of Arcobacter genus in the milk was 12% [95%-CI: 7-19%; I2 = 87.3%, 95%-CI: 83.0-90.6%] and no publication bias observed (Eggers' test: p = 0.112). Arcobacter genus prevalence in milk was 13% (95%-CI: 5-30%), 10% (95%-CI: 1-46%), and 9% (95%-CI: 4-19%) in Europe, South America, and Asia, respectively. A. butzleri was the most prevalent (8% [95%-CI: 4-13%]), then A. cryaerophilus (0.6% [95%-CI: 0.2-33.2%]) and A. skirrowii (0.19% [95%-CI: 0.03-1.2%]). Also species-specific prevalence of A. butzleri, A. cryaerophilus, and A. skirrowii varied continentally, but the test for species-specific/continental differences were not significantly different (p > 0.5).

Arcobacter species in milk contamination: a prevalence-based systematic review and meta-analysis.

AIMS: Milk is consumed raw or minimally processed and plays a role in the dissemination of pathogens of public health concerns. The present investigation is aimed at assessing the occurrence of pathogenic Arcobacter species in 2945 milk samples. METHODS AND RESULTS: Arcobacter data systematically retrieved from five repositories until 20 February 2022 according to PRISMA principles were logit transformed and fitted using a generalized linear mixed-effects model. The between-study heterogeneity was estimated as I2-value. Leave-one-out cross-validation and funnel plot with Egger's tests were used to assess the hardiness and bias in the model. The global prevalence of Arcobacter genus in the milk was 12% [95% confidence interval (CI): 7-19%; I2 = 87.3%, 95% CI: 83.0-90.6%] and no publication bias observed (Egger's test: P = 0.112). Arcobacter genus prevalence in milk was 13% (95% CI: 5-30%), 10% (95% CI: 1-46%), and 9% (95% CI: 4-19%) in Europe, South America, and Asia, respectively. Arcobacter butzleri was the most prevalent [8% (95% CI: 4-13%)], followed by A. cryaerophilus [0.6% (95% CI: 0.2-33.2%)] and A. skirrowii [0.19% (95% CI: 0.03-1.2%)]. Also, species-specific prevalence of A. butzleri, A. cryaerophilus, and A. skirrowii varied continentally, but the test for species-specific/continental differences was not significantly different (P > 0.5).

Analytical Characterization of the Widely Consumed Commercialized Fermented Beverages from Russia (Kefir and Ryazhenka) and South Africa (Amasi and Mahewu): Potential Functional Properties and Profiles of Volatile Organic Compounds.

In this study, four commercialized indigenous fermented beverages most highly consumed in Russia (kefir and ryazhenka) and South Africa (amasi and mahewu) were analyzed for their potential health-promoting properties and flavor-forming volatile organic compounds (VOC). The analysis of antioxidant capacity demonstrated superiority of dairy-based beverages (kefir, ryazhenka and amasi) over the corn-based mahewu; however, mahewu outperformed dairy-based beverages in terms of its potential antihypertensive effect (i.e., the ability to inhibit angiotensin I converting enzyme). The fatty acid (FA) content of kefir and ryazhenka were more diverse compared to that of amasi, but included a lesser amount of branched chain FA. In terms of calculated FA nutritional indices (e.g., indices of atherogenicity and thrombogenicity), kefir and ryazhenka performed similarly and significantly better than amasi. The agreement between beverages theoretical flavor profiles, which was obtained based on the flavors of individual VOC, and consumers' flavor perception allow hypothesizing about the contribution of detected VOC to the overall products' flavor. The obtained data expand current knowledge regarding traditional fermented beverages and their values in terms of national dietary recommendations. Additionally, reported VOC profiles will promote the inclusion of traditional fermented beverages into the rations based on the flavor pairing concept (which is controversial but widely applied).

Properties of Poly-γ-Glutamic Acid Producing-Bacillus Species Isolated From Ogi Liquor and Lemon-Ogi Liquor.

Poly-γ-glutamic acid (γPGA) is a natural and promising biopolymer synthesized by Bacillus spp. during fermentation. This study isolated Bacillus spp. from ogi steep liquor (OSL) and lemon-ogi steep liquor (LOSL) using standard methods and determined the γPGA-producing ability. The antimicrobial and angiotensin-converting enzyme (ACE) inhibitory activities of γPGA polymer were evaluated and isolates were sequenced. Four isolates (TA004, TA006, TA011, TA012) selected based on phenotypic characterization and stickiness (<15 cm) showed antibacterial activity against different pathogens with the highest activity found in TA004 (22.5 mm) and least in TA011 (16.6 mm). Furthermore, time-kill assay showed that the combined γPGA polymer was more effective and demonstrated bactericidal activity over individual γPGA which are bacteriostatic in nature. All γPGA polymer exhibited ACE properties except TA011. The highest IC50 was observed in TA006 (0.11 mg/ml) and least in TA004 (0.35 mg/ml). TA004 had the highest molecular weight (261 kDa) while TA011 had the least (194.97 kDa). In addition, all γPGA exhibited characteristic peaks at 3413-3268 cm-1 and 1722-1664 cm-1 that corresponded to amine N-H stretching intensities and C = O stretching in COOH. Bacillus isolates were identified as TA004 (B. subtilis-GenBank: MH782061), TA006 (B. amyloliquefaciens- GenBank: MH782075), TA011 (B. subtilis- GenBank: MH782088), TA012 (B. subtilis- GenBank: MH782083). OSL and LOSL have the potential for developing functional foods with a valuable effect on health.

Inactivation of Listeria monocytogenes ATCC 7644 on fresh-cut tomato using nisin in combinations with organic salts

ABSTRACT The inhibition of Listeria monocytogenes ATCC 7644 on fresh-cut tomato was investigated using nisin alone, and in combinations with organic salts. Nisin at a concentration of 5000 UI/mL was introduced alone or in combination with an organic salt (sodium citrate or sodium acetate each at 3 and 5 g/100 mL each) on fresh-cut tomato previously inoculated with 108 CFU/mL of L. monocytogenes ATCC 7644. Chlorine at 200 ppm was used as a control. The inoculated samples were incubated at different temperatures (4, 10 and 25 °C) and examined at 0, 24, 48 and 72 h. The effects of the antimicrobial treatments on quality parameters of tomato (pH, soluble solids, titratable acidity and vitamin C) were also evaluated, and colour parameters were observed at the lowest storage temperature for 10 days. Both nisin and the organic salts inhibited growth of L. monocytogenes, but the combinations of two compounds were more effective. The nisin-sodium citrate (5%) combination was significantly (p ≤ 0.05) effective, while chlorine was least effective against L. monocytogenes. The quality parameters were substantially retained, especially at 4 °C, suggesting good shelf stability at a low temperature. These results substantiate the use of the cheap and eco-friendly approach to reducing this pathogen of health concern in common fresh produce.

Inactivation of Listeria monocytogenes ATCC 7644 on fresh-cut tomato using nisin in combinations with organic salts.

The inhibition of Listeria monocytogenes ATCC 7644 on fresh-cut tomato was investigated using nisin alone, and in combinations with organic salts. Nisin at a concentration of 5000UI/mL was introduced alone or in combination with an organic salt (sodium citrate or sodium acetate each at 3 and 5g/100mL each) on fresh-cut tomato previously inoculated with 10(8)CFU/mL of L. monocytogenes ATCC 7644. Chlorine at 200ppm was used as a control. The inoculated samples were incubated at different temperatures (4, 10 and 25°C) and examined at 0, 24, 48 and 72h. The effects of the antimicrobial treatments on quality parameters of tomato (pH, soluble solids, titratable acidity and vitamin C) were also evaluated, and colour parameters were observed at the lowest storage temperature for 10 days. Both nisin and the organic salts inhibited growth of L. monocytogenes, but the combinations of two compounds were more effective. The nisin-sodium citrate (5%) combination was significantly (p≤0.05) effective, while chlorine was least effective against L. monocytogenes. The quality parameters were substantially retained, especially at 4°C, suggesting good shelf stability at a low temperature. These results substantiate the use of the cheap and eco-friendly approach to reducing this pathogen of health concern in common fresh produce.

Antioxidant activities of bambara groundnut (Vigna subterranea) protein hydrolysates and their membrane ultrafiltration fractions.

In this study, the bambara protein isolate (BPI) was digested with three proteases (alcalase, trypsin and pepsin), to produce bambara protein hydrolysates (BPHs). These hydrolysates were passed through ultrafiltration membranes to obtain peptide fractions of different sizes (<1, 1-3, 3-5 and 5-10 kDa). The hydrolysates and their peptide fractions were investigated for antioxidant activities. The membrane fractions showed that peptides with sizes <3 kDa had significantly (p < 0.05) reduced surface hydrophobicity when compared with peptides >3 kDa. This is in agreement with the result obtained for the ferric reducing power, metal chelating and hydroxyl radical scavenging activities where higher molecular weight peptides exhibited better activity (p < 0.05) when compared to low molecular weight peptide fractions. However, for all the hydrolysates, the low molecular weight peptides were more effective diphenyl-1-picrylhydrazyl (DPPH) radical scavengers but not superoxide radicals when compared to the bigger peptides. In comparison with glutathione (GSH), BPHs and their membrane fractions had better (p < 0.05) reducing power and ability to chelate metal ions except for the pepsin hydrolysate and its membrane fractions that did not show any metal chelating activity. However, the 5-10 kDa pepsin hydrolysate peptide fractions had greater (88%) hydroxyl scavenging activity than GSH, alcalase and trypsin hydrolysates (82%). These findings show the potential use of BPHs and their peptide fraction as antioxidants in reducing food spoilage or management of oxidative stress-related metabolic disorders.