Food Surveillance Research Articles

Metal-organic framework-sealed heterogeneous nanoenzyme: A dual-mode core–shell sensor for sensitive determination of the chlorpyrifos residue in environment and bioaccumulation in food

Developing efficient and intelligent method for analyzing harmful agrochemicals like organophosphorus pesticides plays a crucial role in food and environmental safety surveillance. Herein, a metal–organic framework (MOF)-sealed heterogeneous nanoenzyme was designed for monitoring the bioaccumulation of chlorpyrifos in vegetables. The hybrid named CeOx@fZIF was sequentially prepared through cerium oxide (CeOx) as the core, and Cu(II)-centered zeolitic imidazolate framework (ZIF) as shell, which encapsulated fluorescence dye. The fluorescence from the encapsulated dye and the colorimetric signal from the catalytic product by the inner nanoenzyme CeOx were synchronously blocked by the outer ZIF shell of CeOx@fZIF. Under the alkaline phosphatase (ALP) enzyme-mediated reduction of Cu(II) in the ZIF shell, the obstruction of shell was relieved with the shell collapse. The enzymatic capability of inner CeOx for colorimetric catalysis and the dye fluorescence were synergistically recovered in a controllable way. Accompanied with the chlorpyrifos-inhibited capability for ALP, a fluorescence/colorimetric dual-signal sensor was fabricated. The dual-mode signal of CeOx@fZIF-based nanosystem exhibited a strong linear correlation with chlorpyrifos concentrations, achieving the detection limit of 0.2 ng/mL in fluorescence and 15 ng/mL in colorimetric. This strategy was assessed across various food matrices and had an outstanding reaction with a high percentage of recovery. Furthermore, the nanoenzyme system was employed to determine chlorpyrifos accumulation in pakchoi. The presented nanosystem exploited the feasibility of MOF-controlled nanoenzyme sensor and lighted up a facile pathway to prepare dual-mode sensor of pesticide monitoring for food and ecological environment safety.

Thiamine: An indispensable regulator of paediatric neuro-cardiovascular health and diseases.

Physicians are recommended to have a low threshold for suspecting thiamine deficiency especially in vulnerable populations. Laboratory diagnosis of thiamine deficiency needs to be implemented as a standard of care, especially in endemic regions. Further, public health policies on food fortification, mandatory supplementation, and surveillance are imperative to eliminate thiamine deficiency-induced health hazards. • South Asian countries report a higher incidence of neonatal and under-five mortalities, many of which are attributed to maternal and perinatal micronutrient deficiencies. • Preventable causes of neonatal/ infantile deaths include birth factors (low birth weight, birth asphyxia), infectious diseases (pneumonia, diarrhoea, tetanus, tuberculosis, measles, diphtheria, malaria, acute infections), deficiency diseases and genetic diseases (vitamin & mineral deficiencies, IEMs, congenital heart disease, unexplained PPHN, SIDS etc). • Acute thiamine deficiency presenting as multisystemic syndromes, has unfortunately been a long standing unresolved public health concern. However, accessible surveillance and diagnostic strategies remain elusive in most clinical settings. • Despite decades of reports and emerging guidelines, diagnosis of thiamine deficiency is often missed and policy mandates at national level are yet to be implemented even in endemic countries. • This review provides a comprehensive summary of the biochemical role of thiamine, its key functions and effects on major organ systems, the diagnostic gap, the enigmatic presentation of acute thiamine deficiency, the plausible role of thiamine in other pathologies and the preventive measures at individual and community level.

Effect of unprocessed and minimally processed foods on blood pressure in children

Abstract Background The poor eating habits of children, including a decrease in the consumption of unprocessed foods and an increase in the consumption of processed foods, have been associated with excess body weight, which is a well-established risk factor for cardiovascular diseases (CVDs), especially high blood pressure (BP). We aimed to investigate whether the consumption of unprocessed and minimally processed foods is associated with high BP in children at nine years of age. Methods Cross-sectional study of 142 Brazilian children participating in a cohort study conducted at the participant’s home. The child’s food consumption markers were evaluated using the Brazilian Food and Nutrition Surveillance System (SISVAN) and were classified by NOVA. Using a standardized procedure for approaching the child, BP was measured by the auscultatory method. Biological, socioeconomical, demographic, and anthropometric data of the mother and child were also collected. Logistic regression analysis adjusting for important predictors was used to evaluate the association between food consumption and BP. Results The prevalence of high BP in children was 20.4%, and the mean systolic and diastolic BP were significantly (p < 0.05) higher in children classified as high BP (110.1 and 71.3 mmHg, respectively). An important proportion (44.8%) of children had excess body weight (>85th percentile) and high BP when compared to eutrophic children. Not consuming healthy foods was associated with high systolic BP, even after adjustment for other important covariates (OR = 3.97; p = 0.028). Conclusions Not consuming healthy foods was associated with increased odds of children having high BP at nine years of age. Interventions promoting a healthy diet and the consumption of fruits and vegetables in childhood may contribute to preventing diseases associated with CVD, a global public health problem. Key messages • Educating parents to avoid processed foods and monitoring children’s BP are essential actions to prevent associated chronic diseases throughout life. • Public policies aimed at educating parents to encourage the consumption of healthy foods may significantly contribute to reducing adverse cardiovascular outcomes.

Surveillance of Food and Waterborne Pathogens in North-East India: Protocol for a Laboratory-Based Sentinel Surveillance Study.

Food safety is a global concern, which is often underestimated owing to challenges in investigating foodborne diseases. These challenges arise from the increased globalization of the food trade, advancements in agricultural practices, and shifts in environmental factors. In North-East India, common diarrheal outbreaks from fermented foods pose significant health risks. Despite these challenges, systematic data on foodborne pathogens is lacking in India, highlighting a crucial gap in understanding food safety issues. The aim of this research protocol is to establish an integrated surveillance system to identify enteric pathogens circulating within humans, food animals, and the environment through a health approach in North-East India, and to conduct outbreak investigations. The Indian Council of Medical Research (ICMR) initiated a surveillance study across all 8 North-East states in India, employing a centralized digital database for data collation. The project aims to enhance theinfrastructure for microbial culture, antibiotic sensitivity testing, and molecular epidemiological studies. The study involves laboratory-based surveillance of foodborne pathogens in market foods, hospitalized diarrheal patients, poultry and animal farms, slaughterhouses, butcher shops, and diarrheal outbreaks. A standardized case report form ensures consistent data collection of age, sex, signs, symptoms, and admission dates for diarrheal cases. Stool and rectal swabs will undergo testing for pathogen identification and antimicrobial resistance. Similarly, samples of market foods, food animals, and the environment will be collected. Outbreaks confirmed by the Integrated Disease Surveillance Project (IDSP) will be thoroughly investigated following standardized guidelines. In phase I, 5 surveillance centers were established across 4 states (ie, Assam [Dibrugarh and Guwahati], Tripura, Sikkim, and Arunachal Pradesh) in 2020. Following an interim phase I data assessment and the successful establishment of a streamlined system for data procurement, investigation, recording, and analysis, along with the implementation of regular training and monitoring programs, phase II expansion was initiated in 2023-24. This includes the addition of 7 more centers (including 3 veterinary centers) in the remaining 4 states (ie, Manipur, Meghalaya, Mizoram, and Nagaland), eventually covering the entire North-Eastern Region of India. Food and waterborne diseases are a constant public health problem in many countries. Key challenges to the enhancement of food safety policy include the paucity of systematic data and awareness. With this background, ICMR's initiative is the first systematic surveillance study in the country to adopt a single health approach. Data obtained from this project will help to understand the risk of acquiring food and waterborne pathogens, their transmission pathways, and antimicrobial resistance patterns. The scientific evidence generated through this project will be helpful in formulating and strengthening food safety policy and in initiating government programs to protect the health of the nation. DERR1-10.2196/56469.

A virtual assistant for primary care's food and nutrition surveillance system: Development and validation study in Brazil

ObjectiveThe study aimed to develop and validate a conversational agent (chatbot) designed to support Food and Nutrition Surveillance (FNS) practices in primary health care settings. MethodsThis mixed-methods research was conducted in three stages. Initially, the study identified barriers and challenges in FNS practices through a literature review and feedback from 655 health professionals and FNS experts across Brazil. Following this, a participatory design approach was employed to develop and validate the chatbot's content. The final stage involved evaluating the chatbot's user experience with FNS experts. ResultsThe chatbot could accurately understand and respond to 60 different intents or keywords related to FNS. Themes such as training, guidance, and access emerged as crucial for guiding FNS initiatives and addressing implementation challenges, primarily related to human resources. The chatbot achieved a Global Content Validation Index of 0.88. ConclusionThe developed chatbot represents a significant advancement in supporting FNS practices within primary health care. Practice implicationBy providing an innovative, interactive, educational tool that is both accessible and reliable, this digital assistant has the potential to facilitate the operationalization of FNS practices, addressing the critical need for effective training and counseling in developing countries.

Hazard Characterization of Antibiotic-resistant Aeromonas spp. Isolated from Mussel and Oyster Shellstock Available for Retail Purchase in Canada

Surveillance and monitoring of foods for the presence of antimicrobial-resistant (AMR) bacteria are required to assess the risks these bacteria pose to human health. Frequently consumed raw or lightly cooked, live bivalve shellfish such as mussels and oysters can be a source of exposure to AMR bacteria. This study sought to determine the prevalence of third-generation cephalosporin (3GC) and carbapenem-resistant bacteria in live mussel and oyster shellstock available for retail purchase through the course of one calendar year. Just over half of the 180 samples (52%) tested positive for the presence of 3GC-resistant bacteria belonging to thirty distinct bacterial species. Speciation of the isolates was carried out using the Bruker MALDI Biotyper. Serratia spp., Aeromonas spp., and Rahnella spp. were the most frequently isolated groups of bacteria. Antibiotic resistance testing confirmed reduced susceptibility for 3GCs and/or carbapenems in 15 of the 29 Aeromonas isolates. Based on AMR patterns, and species identity, a subset of ten Aeromonas strains was chosen for further characterization by whole genome sequence analysis. Genomic analysis revealed the presence of multiple antibiotic resistance and virulence genes. A number of mobile genetic elements were also identified indicating the potential for horizontal gene transfer. Differences in gene detection by the bioinformatic tools and databases used (ResFinder. CARD RGI, PlasmidFinder, and MobSuite) are discussed. This study highlights the strengths and limitations of using genomics tools to perform hazard characterization of diverse foodborne bacterial species.

Profiling the Enterobacterales Community Isolated from Retail Foods in England

Enterobacterales include foodborne pathogens of importance to public health and are often targeted in food surveillance programs as both safety and hygiene indicators. Furthermore, Enterobacterales are important in the context of antimicrobial resistance dissemination, also impacting infection treatment efficacy. In this study, the prevalence and characteristics of Enterobacterales in UK retail foods were examined. From 110 retail food samples, 253 Enterobacterales were recovered, with 16S rRNA sequencing revealing a diverse species community, including enteropathogens; the most common were Proteus mirabilis and Escherichia coli (18% each). Antimicrobial resistance was common, with 160/253 (63%) isolates being resistant to at least 1 antimicrobial. Resistance to all tested antimicrobials was observed. Thirteen percent of isolates were multidrug resistant, including 2 isolates each resistant to 8 or 9 of 9 antimicrobials tested. Klebsiella isolates possessed relatively higher levels of antimicrobial resistance to other species. Hafnia, Kluyvera, and Proteus isolates produced significantly higher biofilm biomass than Klebsiella (p = 0.038, 0.028, and 0.042, respectively) or Escherichia (p = 0.001, 0.008, and 0.001, respectively). Simultaneous curli fimbriae and cellulose production was noted in 7% of isolates at 37 °C, but not at 15 °C. This research demonstrates a high diversity of Enterobacterales within UK retail foods, alongside notable antimicrobial resistance phenotypes in enteropathogenic species, highlighting the need for effective surveillance and interventions.

Effect of the COVID-19 pandemic on malnutrition in socially vulnerable children in Brazil.

This article aims to evaluate the effect of the COVID-19 pandemic on malnutrition among children under two years of age enrolled in the Bolsa Família Program (BFP). Ecological study of interrupted time series (ITS), with low weight for age, stunting, and overweight as time-dependent variables of malnutrition, extracted monthly (Jan/2008 to June/2021) from the Food and Nutrition Surveillance System. The COVID-19 pandemic was the exposure, dichotomized into pre-pandemic and pandemic. In RStudio, the trend was obtained by Prais-Winsten regression, and the effect of the pandemic on the time-dependent variables was determined by SARIMA modeling, estimating the regression coefficients (RC) adjusted for trend and seasonality (α = 5%). The pandemic was associated with an increase in: i) low weight for age in the South (RC = 0.94; p < 0.001) and Southeast (RC = 1.97; p < 0.001); ii) height deficit in the Midwest (RC = 2.4; p = 0.01), South (RC = 2.15; p < 0.001) and Southeast (RC = 2.96; p < 0.001); and iii) and overweight in the North (RC = 1.51; p = 0.04), Midwest (RC = 2.29; p = 0.01), South (RC = 2.83; p < 0.001), and Southeast (RC = 0.72; p = 0.04). The pandemic increased underweight in the South and Southeast, and the double burden of malnutrition in the Midwest, South, and Southeast. In the Northeast and North, higher rates of malnutrition still persist.

Weekend Variation in Ultra-Processed Food Intake of Patients after Metabolic and Bariatric Surgery: A Cross-Sectional Study

This study analyzed changes in ultra-processed food consumption patterns during weekends in patients in the post-metabolic and bariatric surgery periods. It is a cross-sectional study, which recruited and collected data via social media from adults who underwent metabolic and bariatric surgery. The Brazil Food and Nutritional Surveillance System markers of dietary consumption and the NOVA Ultra-Processed Food Screening tools were applied to evaluate dietary patterns and ultra-processed food consumption from the previous day. A total of 1525 participants were included, with a mean age of 38 ± 8 years and a mean body mass index of 29.9 ± 5.8 kg/m2. From these, 766 (50.3%) individuals answered the questionnaire referring to a weekend day. After adjusting for confounders, ultra-processed food consumption was higher on weekends compared to weekdays (NOVA Score 3.07 vs. 2.42; p &lt; 0.01). The consumption of fruits and vegetables was lower on weekends, whereas the consumption of hamburgers/sausages, sugar-sweetened beverages, boxed/canned juice, and frozen pizza increased on weekends. Instant noodles and sandwich cookies did not show differences between weekdays and weekend days. This pattern suggests the need to monitor eating habits on weekends in individuals after metabolic and bariatric surgery.

Developing a digital data platform for surveillance of food and water-borne pathogens in North East India: insight for public health advocacy.

Robust digital infrastructure is vital and the need of the hour, especially in the healthcare sector, for real-time data generation, analysis, and quick decision-making. Food- and water-borne illnesses represent a prominent cause of morbidity and mortality worldwide. India, a developing nation with diverse cultures and food practices, poses a high risk of food-borne diseases and outbreaks, yet is often underreported and ineffectively researched. Also, the unique socio-economic and environmental factors of the Northeast (NE) region contribute to the high burden of food-borne diseases. To address these trepidations, the Indian Council of Medical Research (ICMR) has undertaken a study for the surveillance of food-borne pathogens in NE India. The present study focuses on the development of a digital database system for the systematic surveillance of foodborne disease outbreaks, aiming to address the gaps in traditional surveillance methods and improve disease detection and response capabilities. The digital system integrates mobile applications, web-based platforms, and advanced analytics tools to enable real-time data collection, dissemination, and analysis of food-borne illness data. Additionally, the secure and scalable nature of the system enhances data accuracy and accessibility, making it a valuable tool for enhancing food-borne disease surveillance efforts in resource-constrained settings.

ACOMPANHAMENTO NUTRICIONAL DE ADULTOS BENEFICIÁRIOS DO PROGRAMA BOLSA FAMÍLIA NO MUNICÍPIO DE PARAÍBA DO SUL/RJ NOS ANOS DE 2010, 2015 E 2020

The objective of the study was to monitor the nutritional status of adult beneficiaries of the Bolsa Família program in the municipality of Paraíba do Sul/RJ in the years 2010, 2015 and 2020. A retrospective analysis of data from 2041 adults aged between 20 and 59 years was carried out, divided into three moments: 2010 (n=310), 2015 (n=1049) and 2020 (n=682), beneficiaries of the Bolsa Família Program. Data were collected through publicly accessible reports from the Food and Nutrition Surveillance System (SISVAN). The variable analyzed was the classification of the nutritional status of the beneficiaries of the Bolsa Família program. In 2010, 310 adults were evaluated, where 6.13% were underweight, 51.61% were of adequate weight, i.e., in normal weight, and 42.26% were overweight, that is, within the classification of overweight, obesity grade I, II or III. In 2015, 1049 adults were evaluated, where 3.05% were underweight, 33.46% were normal weight and 63.49% were overweight. In 2020, 682 adults were evaluated, where 2.93% are underweight, 27.71% are normal weight and 69.36% are overweight. According to the analysis of data from beneficiaries in Paraíba do Sul/RJ, it was possible to observe an increase in obesity and a reduction in underweight, as has been occurring throughout the country.

Prevalence and Genomic Characterization of Multidrug-Resistant Salmonella enterica Serovar Kentucky Sequence Type 198 Circulating - Beijing Municipality, China, 2016-2023.

Highly fluoroquinolone-resistant Salmonella enterica serovar Kentucky (S. Kentucky) of sequence type (ST) 198 has emerged as a global multidrug-resistant (MDR) clone, posing a threat to public health. Whole genome sequencing and antibiotic susceptibility testing was used to characterize the population structure and evolutionary history of 54 S. Kentucky isolates recovered from food and human clinical cases in Beijing from 2016 to 2023. All 54 S. Kentucky ST198 isolates exhibited resistance to quinolones, carrying point mutations in the quinolone resistance-determining regions (gyrA_S83F and parC_S80I). Resistance to other antibiotics (folate pathway inhibitors, cephems, aminoglycosides, phenicols, rifamycin, fosfomycin, macrolides, and tetracyclines), mediated by the sul1, sul2, dfrA14, bla CTX-M, bla TEM-1B, aac(3)-Id, aadA2, aadA7, aph(3')-I, aph(3'')-Ib, rmtB, floR, arr-2, fosA, mph(A), and tet(A) genes, was also observed in different combinations. The Beijing S. Kentucky ST198 evolutionary tree was divided into clades 198.2-1 and 198.2-2, which were further differentiated into three subclades: 198.2-2A, 198.2-2B, and 198.2-2C. Compared with the extended-spectrum β-lactamase-encoding gene bla CTX-M-14b in 198.2-1, the co-existence of bla CTX-M-55 and bla TEM-1B, as well as chromosomally located qnrS1, was detected in most 198.2-2 isolates, which showed more complex MDR phenotypes. S. Kentucky ST198 outbreak isolates derived from two predominant clonal sources: 198.2-1 with cgST236434 and 198.2-2A with cgST296405. The S. Kentucky population in Beijing is genetically diverse, consisting of multiple co-circulating lineages that have persisted since 2016. Strengthening surveillance of food and humans will aid in implementing measures to prevent and control the spread of AMR.

The quality of the anthropometric data on children under five years of age in information systems in the State of São Paulo, Brazil

This paper involves the analysis of the quality of anthropometric data on children under five years of age in two information systems in the State of São Paulo. The sample included 2,117,108 children from the Food and Nutrition Surveillance System (SISVAN), and 748,551 from the State Milk Project (VIVALEITE). Initially, we evaluated the frequency of missing values and others outside the equipment spectrum and calculated the digit-to-weight preference index. After calculating height-for-age (HAZ), weight-for-age (WAZ), and body mass index-for-age (BAZ), we flagged the biologically implausible values (BIV) and calculated the standard deviation (SD). For each municipality, we calculated the mean and the SD of HAZ, WAZ, and BAZ; and plotted the SD values as a function of the mean. The digit-to-weight preference index was greater among children aged between 24 and 59 months in SISVAN. The frequency of BIV for HAZ (SISVAN 2.56%; VIVALEITE 0.98%) was higher than for WAZ (SISVAN 2.10%; VIVALEITE 0.18%). For HAZ, variations among municipalities were more pronounced in VIVALEITE than in SISVAN. The height variable presents low reliability in both systems. The weight variable reveals satisfactory quality in VIVALEITE and unsatisfactory quality in SISVAN.

Mapping and projections of obesity in the Brazilian adult population assisted in Primary Health Care: impact of the COVID-19 pandemic

Objective: To map the temporal evolution of overweight and obesity in Brazilian adults and estimate the prevalence of obesity for 2025 and 2030, evaluating the potential impact of the COVID-19 pandemic. Method: Data were collected on the nutritional status of adults from 2008 to 2021 from the Food and Nutrition Surveillance System (SISVAN), from which we calculated the prevalence and average annual rates of the variation of overweight and obesity. The projection of obesity, using linear regression, was analyzed in three scenarios: PP: with data from the pre-pandemic period (2008- 2019); outlier: with adjustment of the data trend (2008-2021), including the pandemic period, considering a return of scenario PP for projections from 2022; P: adjustment of pandemic data (2019-2021) to estimate the projection. Result: In the period 2008– 2021, we observed an average annual rate of overweight increase of 0.48 %/year. The prevalence of obesity more than doubled during this period, from 14.5% in 2008 to 32.9% in 2021 (i.e., an increase of 1.42). In the outlier scenario, the prevalence projections for obesity are 38.8% and 45.5% for 2015 and 2030, respectively. In the PP scenario (without the pandemic), the expected prevalence for the same period would be approximately 36.8% and 43.4%, respectively. Conclusion: Obesity and overweight follow an increasing trend. The COVID-19 pandemic accelerated the increase in the prevalence of obesity in Brazil and impacted its projections for the coming years.

Food safety and surveillance studies on the quality of traditional cold-pressed edible vegetable oils

This study has been conducted to investigate quality and safety of cold-pressed vegetable oils processed at cottage level industries. A total number of 75 samples of coconut, groundnut, and sesame oils collected from different districts of Tamil Nadu, analyzed to ascertain its quality and safety in compliance with the Food Safety Standard Regulations (FSSR) of FSSAI, 2011. Physico – chemical, fatty acid profile, vitamin and trace elemental analysis were carried out. Results revealed that though some of the oils samples are complied with the specification as per the standard, but on the other side 80% of the collected samples were found to fail in meeting at least for one parameter as per the requirements. Results are in deviations for the parameters such as refractive index, specific gravity, iodine value, and saponification value are also noticed and few samples are reported positive results for the presence of mineral oil and argemone oil and possibilities for adulteration. Notably, 15 samples were found to comply with the requirements for physiochemical parameters, fatty acid profiles and trace element levels which are found below permissible limits (≤0.05 mg/kg). Vitamin E was detected only in coconut oil (0.1059 to 0.1622 mg/100g). Whereas, antioxidant assay and color, remained satisfactory. Overall, the study underscores the importance of consumer awareness and adherence to established standards to ensure the integrity and safety of edible oils, highlighting the need for continued monitoring and enforcement efforts to address identified shortcomings and uphold market integrity.

Trends in Complementary Feeding Indicators in Children Aged 6-23 Months According to Participation in a Conditional Cash Transfer Program: Data from the Brazilian Food and Nutrition Surveillance System, 2015-2019.

Inadequate practices during complementary feeding are associated with malnutrition, especially in children experiencing vulnerable conditions and social inequality. The aim of this study was to evaluate the trends in complementary feeding indicators (CFIs) according to participation in a Brazilian cash transferu program-the Bolsa Família Program (BFP). This was a time-series study with secondary data from 600,138 children assisted from 2015 to 2019 and registered within the Brazilian Food and Nutrition Surveillance System. The CFIs assessed were food introduction, minimum meal frequency and appropriate consistency, minimum dietary diversity, iron-rich food, vitamin A-rich food, ultra-processed food consumption, and zero vegetable or fruit consumption. Prevalence and 95% confidence intervals were calculated for the CFIs according to BFP, the region of residence, and the child's age. The Prais-Winsten regression method was used to analyze the temporal trend. There was a steady trend for all CFIs of a healthy diet. A decrease in ultra-processed food consumption for both BFP (-10.02%) and non-BFP children (-9.34%) was observed over the years. Children residing in the North and Northeast regions and those enrolled in the BFP were more distant from the recommended feeding practices when compared to the other regions and non-BFP children. The results highlight the relevance of nutritional surveillance and the need to improve food and nutrition public policies for children aged 6-23 months, particularly for those experiencing greater social vulnerability.

Development of Interoperable Computable Phenotype Algorithms for Adverse Events of Special Interest to Be Used for Biologics Safety Surveillance: Validation Study.

Adverse events associated with vaccination have been evaluated by epidemiological studies and more recently have gained additional attention with the emergency use authorization of several COVID-19 vaccines. As part of its responsibility to conduct postmarket surveillance, the US Food and Drug Administration continues to monitor several adverse events of special interest (AESIs) to ensure vaccine safety, including for COVID-19. This study is part of the Biologics Effectiveness and Safety Initiative, which aims to improve the Food and Drug Administration's postmarket surveillance capabilities while minimizing public burden. This study aimed to enhance active surveillance efforts through a rules-based, computable phenotype algorithm to identify 5 AESIs being monitored by the Center for Disease Control and Prevention for COVID-19 or other vaccines: anaphylaxis, Guillain-Barré syndrome, myocarditis/pericarditis, thrombosis with thrombocytopenia syndrome, and febrile seizure. This study examined whether these phenotypes have sufficiently high positive predictive value (PPV) to ensure that the cases selected for surveillance are reasonably likely to be a postbiologic adverse event. This allows patient privacy, and security concerns for the data sharing of patients who had nonadverse events can be properly accounted for when evaluating the cost-benefit aspect of our approach. AESI phenotype algorithms were developed to apply to electronic health record data at health provider organizations across the country by querying for standard and interoperable codes. The codes queried in the rules represent symptoms, diagnoses, or treatments of the AESI sourced from published case definitions and input from clinicians. To validate the performance of the algorithms, we applied them to electronic health record data from a US academic health system and provided a sample of cases for clinicians to evaluate. Performance was assessed using PPV. With a PPV of 93.3%, our anaphylaxis algorithm performed the best. The PPVs for our febrile seizure, myocarditis/pericarditis, thrombocytopenia syndrome, and Guillain-Barré syndrome algorithms were 89%, 83.5%, 70.2%, and 47.2%, respectively. Given our algorithm design and performance, our results support continued research into using interoperable algorithms for widespread AESI postmarket detection.

Phenotypic and genotypic characterization of antimicrobial resistance of non-typhoidal Salmonella from retail meat in California

Antimicrobial resistance (AMR) is a global emerging problem for food safety and public health. Retail meat is one of the vehicles that may transmit antimicrobial resistant bacteria to humans. Here we assessed the phenotypic and genotypic resistance of non-typhoidal Salmonella from retail meat collected in California in 2019 by the National Antimicrobial Resistance Monitoring System (NARMS) Retail Food Surveillance program. A total of 849 fresh meat samples were collected from randomly selected grocery stores in Northern and Southern California from January to December 2019. The overall prevalence of Salmonella was 15.31 %, with a significantly higher occurrence in Southern (28.38%) than in Northern (5.22 %) California. The prevalence of Salmonella in chicken (24.01 %) was higher (p < 0.001) compared to ground turkey (5.42 %) and pork (3.08 %) samples. No Salmonella were recovered from ground beef samples. The prevalence of Salmonella in meat with reduced antibiotic claim (20.35 %) was higher (p < 0.001) than that with conventional production (11.96 %). Salmonella isolates were classified into 25 serotypes with S. Kentucky (47.73 %), S. typhimurium (11.36 %), and S. Alachua (7.58 %) as predominant serotypes. Thirty-two out of 132 (24.24 %) Salmonella isolates were susceptible to all tested antimicrobial drugs, while 75.76 % were resistant to one or more drugs, 62.88 % to two or more drugs, and 9.85 % to three or more drugs. Antimicrobials that Salmonella exhibited high resistance to were tetracycline (82/132, 62.12 %) and streptomycin (79/132, 59.85 %). No significant difference was observed between reduced antibiotic claim and conventional production in the occurrence of single and multidrug resistance. A total of 23 resistant genes, a D87Y mutation of gyrA, and 23 plasmid replicons were identified from resistant Salmonella isolates. Genotypic and phenotypic results were well correlated with an overall sensitivity of 96.85 %. S. infantis was the most resistant serotype which also harbored the IncFIB (pN55391) plasmid replicon and gyrA (87) mutation. Data from Northern and Southern California in this study helps us to understand the AMR trends in Salmonella from retail meat sold in the highly populous and demographically diverse state of California.

Machine learning approach as an early warning system to prevent foodborne Salmonella outbreaks in northwestern Italy

Salmonellosis, one of the most common foodborne infections in Europe, is monitored by food safety surveillance programmes, resulting in the generation of extensive databases. By leveraging tree-based machine learning (ML) algorithms, we exploited data from food safety audits to predict spatiotemporal patterns of salmonellosis in northwestern Italy. Data on human cases confirmed in 2015–2018 (n = 1969) and food surveillance data collected in 2014–2018 were used to develop ML algorithms. We integrated the monthly municipal human incidence with 27 potential predictors, including the observed prevalence of Salmonella in food. We applied the tree regression, random forest and gradient boosting algorithms considering different scenarios and evaluated their predictivity in terms of the mean absolute percentage error (MAPE) and R2. Using a similar dataset from the year 2019, spatiotemporal predictions and their relative sensitivities and specificities were obtained. Random forest and gradient boosting (R2 = 0.55, MAPE = 7.5%) outperformed the tree regression algorithm (R2 = 0.42, MAPE = 8.8%). Salmonella prevalence in food; spatial features; and monitoring efforts in ready-to-eat milk, fruits and vegetables, and pig meat products contributed the most to the models’ predictivity, reducing the variance by 90.5%. Conversely, the number of positive samples obtained for specific food matrices minimally influenced the predictions (2.9%). Spatiotemporal predictions for 2019 showed sensitivity and specificity levels of 46.5% (due to the lack of some infection hotspots) and 78.5%, respectively. This study demonstrates the added value of integrating data from human and veterinary health services to develop predictive models of human salmonellosis occurrence, providing early warnings useful for mitigating foodborne disease impacts on public health.

Nanobiosensors: Concepts and Emerging Clinical Applications.

Biosensors have been one of the most fascinating topics for scientists for a long time. This is because biological moieties are multifaceted and are unswervingly related to the presence of a healthy atmosphere. The biosensor approach has also endured profound changes in recent years. Biosensors have been emphasized for various applications, including food quality estimation, surveillance systems, and health and metabolic abnormality diagnostics. The advances in nanotechnology have led to a considerable potential to enhance biosensors' sensitivity, robustness, and anti-interference capabilities. Several new nanomaterials (such as nanoparticles, nanotubes, nanorods, and nanowires) have been fabricated due to the evolution of nanotechnology, and their unique features are gradually being identified, allowing for much faster detection and reproducibility. Biosensor performance has also been enhanced substantially as a result of their use. Because of their capacity to detect a wide range of compounds at deficient concentrations, nanobiosensors have sparked much interest. This article discusses biosensors based on various nanomaterials, their evolution, accompanying features, and their applications in multiple fields.