Making food systems more resilient to food safety risks by including artificial intelligence, big data, and internet of things into food safety early warning and emerging risk identification tools.

To enhance the resilience of food systems to food safety risks, it is vitally important for national authorities and international organizations to be able to identify emerging food safety risks and to provide early warning signals in a timely manner. This review provides an overview of existing and experimental applications of artificial intelligence (AI), big data, and internet of things as part of early warning and emerging risk identification tools and methods in the food safety domain. There is an ongoing rapid development of systems fed by numerous, real-time, and diverse data with the aim of early warning and identification of emerging food safety risks. The suitability of big data and AI to support such systems is illustrated by two cases in which climate change drives the emergence of risks, namely, harmful algal blooms affecting seafood and fungal growth and mycotoxin formation in crops. Automation and machine learning are crucial for the development of future real-time food safety risk early warning systems. Although these developments increase the feasibility and effectiveness of prospective early warning and emerging risk identification tools, their implementation may prove challenging, particularly for low- and middle-income countries due to low connectivity and data availability. It is advocated to overcome these challenges by improving the capability and capacity of national authorities, as well as by enhancing their collaboration with the private sector and international organizations.

Building a resilient pork supply chain to Salmonella spp.

Salmonella spp. control in pork supply chains has always been a challenging issue and insufficient control can lead to high social and economic consequences. Conventional risk management and risk management approaches and models are not sufficient to address potential food safety shocks caused by Salmonella spp., as they mainly focus on assessing measures to reduce Salmonella spp. risks instead of developing the resilience capability (e.g., flexibility to adapt to sudden changes in the risks). Our study is the first that incorporated the resilience concept to the quantitative modeling of Salmonella spp. spread in the pork supply chain. The objective of this study was to explore the resilience performance of the pork supply chain under different food safety shocks caused by Salmonella spp., and to investigate the effectiveness of interventions on reducing the impact of these shocks on the resilience performance of the chain. Scenario analysis indicated that the effectiveness of the investigated resilience strategies or interventions depended on the risk profile (i.e., default, minimum, maximum level of Salmonella spp. contamination) of the pork supply chain. For pork supply chains with minimum and default risk profiles, more attention should be paid to increasing resilience of pigs towards Salmonella spp. infection. For supply chains with maximum risk profile, the focus should be on improving the performance of the slaughterhouse, such as careful evisceration, logistic slaughtering. To conclude, enhancing resilience performance of the pork supply chain can contribute to a safe pork supply.

Applying federated learning to combat food fraud in food supply chains.

Ensuring safe and healthy food is a big challenge due to the complexity of food supply chains and their vulnerability to many internal and external factors, including food fraud. Recent research has shown that Artificial Intelligence (AI) based algorithms, in particularly data driven Bayesian Network (BN) models, are very suitable as a tool to predict future food fraud and hence allowing food producers to take proper actions to avoid that such problems occur. Such models become even more powerful when data can be used from all actors in the supply chain, but data sharing is hampered by different interests, data security and data privacy. Federated learning (FL) may circumvent these issues as demonstrated in various areas of the life sciences. In this research, we demonstrate the potential of the FL technology for food fraud using a data driven BN, integrating data from different data owners without the data leaving the database of the data owners. To this end, a framework was constructed consisting of three geographically different data stations hosting different datasets on food fraud. Using this framework, a BN algorithm was implemented that was trained on the data of different data stations while the data remained at its physical location abiding by privacy principles. We demonstrated the applicability of the federated BN in food fraud and anticipate that such framework may support stakeholders in the food supply chain for better decision-making regarding food fraud control while still preserving the privacy and confidentiality nature of these data.

PRDM16 deficiency in vascular smooth muscle cells aggravates abdominal aortic aneurysm.

Abdominal aortic aneurysm (AAA) is usually asymptomatic until life-threatening complications occur, predominantly involving aortic rupture. Currently, no drug-based treatments are available, primarily due to limited understanding of AAA pathogenesis. The transcriptional regulator PR domain-containing protein 16 (PRDM16) is highly expressed in the aorta, but its functions in the aorta are largely unknown. By RNA-seq analysis, we found that vascular smooth muscle cell-specific (VSMC-specific) Prdm16-knockout (Prdm16SMKO) mice already showed extensive changes in the expression of genes associated with extracellular matrix (ECM) remodeling and inflammation in the abdominal aorta under normal housing conditions without any pathological stimuli. Human AAA lesions displayed lower PRDM16 expression. Periadventitial elastase application to the suprarenal region of the abdominal aorta aggravated AAA formation in Prdm16SMKO mice. During AAA development, VSMCs undergo apoptosis because of both intrinsic and environmental changes, including inflammation and ECM remodeling. Prdm16 deficiency promoted inflammation and apoptosis in VSMCs. A disintegrin and metalloproteinase 12 (ADAM12) is a gelatinase that can degrade various ECMs. We found that ADAM12 is a target of transcriptional repression by PRDM16. Adam12 knockdown reversed VSMC apoptosis induced by Prdm16 deficiency. Our study demonstrated that PRDM16 deficiency in VSMCs promoted ADAM12 expression and aggravates AAA formation, which may provide potential targets for AAA treatment.

Bone morphogenetic protein 4 in perivascular adipose tissue ameliorates hypertension through regulation of angiotensinogen.

Background: Perivascular adipose tissue (PVAT), an active endocrine organ, exerts direct effect on vascular tone through paracrine. Activation of PVAT metabolism plays an inhibitory role in atherosclerosis via secreting relaxing factors. The present studies were designed to investigate the role of PVAT metabolism in regulation of hypertension. Materials and methods: Apolipoprotein E (ApoE) knockout mice with BMP4 knockout in adipose tissue or brown adipose tissue (aP2-DKO or UCP1-DKO, respectively) were used for exploring the role of impaired PVAT metabolism in hypertension. Vascular function was assessed using wire myography. The potential regulatory factor of vascular function was explored using qPCR and ELISA and further confirmed in perivascular fat cell line. Results: Knockout of BMP4 either in adipose tissue or specifically in BAT aggravates high-fat diet (HFD, 40% fat)-induced hypertension and endothelial dysfunction in ApoE-/- mice. In the meanwhile, deficiency of BMP4 also aggravates Ang II (angiotensin II) -induced hypertension and vascular remodeling in ApoE-/- mice. Moreover, deficiency of BMP4 inhibits NO release and induces ROS production. In vitro system, aortic rings pretreated with PVAT extracts from BMP4-DKO mice showed increased vasoconstriction and reduced endothelial-dependent relaxation compared with the controls. We further demonstrated that PVAT of BMP4-DKO mice expressed higher level of angiotensinogen (AGT) and Ang II compared with the controls. Conclusion: Impaired PVAT metabolism aggravates hypertension, and this effect is dependent on the activation of local renin-angiotensin-aldosterone system (RAAS). The results of this study first demonstrate the regulatory role of PVAT metabolism in hypertension.

BMP4-mediated browning of perivascular adipose tissue governs an anti-inflammatory program and prevents atherosclerosis.

Loss of perivascular adipose tissue (PVAT) impairs endothelial function and enhances atherosclerosis. However, the roles of PVAT thermoregulation in vascular inflammation and the development of atherosclerosis remains unclear. Bone morphogenetic protein 4 (BMP4) transforms white adipocyte to beige adipocyte, while promotes a brown-to-white shift in inter-scapular brown adipose tissue (BAT). Here, we found that knockdown of BMP4 in PVAT reduced expression of brown adipocyte-characteristic genes and increased endothelial inflammation in vitro co-culture system. Ablating BMP4 expression either in adipose tissues or specifically in BAT in ApoE-/- mice demonstrated a marked exacerbation of atherosclerotic plaque formation in vivo. We further demonstrated that proinflammatory factors (especially IL-1ß) increased in the supernatant of BMP4 knockdown adipocytes. Overexpression of BMP4 in adipose tissues promotes browning of PVAT and protects against atherosclerosis in ApoE-/- mice. These findings uncover an organ crosstalk between PVAT and blood endothelial cells that is engaged in atherosclerosis.

The impact of chemically enhanced primary treatment on the downstream liquid and solid train processes.

The use of chemical coagulants and flocculants to supplement chemically enhanced primary treatment (CEPT) processes is increasing in popularity as it has been demonstrated to improve carbon redirection and suspended solids and phosphorus removal. Dosing 15 mg ferric chloride/L of wastewater and poly aluminum chloride (PACl; 0.5 mg/L) to the influent of a primary clarifier successfully achieved improved carbon redirection and suspended solids removal at a full-scale WWTP. In this study, the impacts of PACl on the downstream liquid and solid train processes of the same WWTP were investigated. Compared to FeCl3 addition, a combined PACl and FeCl3 addition to the primary influent reduced the TSS and TP concentrations of the secondary clarifier effluent by 20% and 33%, respectively. Effluent BOD5 and ammonia-nitrogen concentrations of the downstream activated sludge process were not affected by the addition of a combined FeCl3 and PACl in the primary clarifier. PACl addition affects the bioavailability of carbon and hence reduced the methane production efficiency of the primary sludge by 20%-30%. However, the significant amount of carbon concentrated in the CEPT sludge would enhance the amount of energy recovered through incineration. PRACTITIONER POINTS: The chemically enhanced primary treatment process is an attractive method for carbon redirection and energy recovery. The combined FeCl3 and PACl addition in the primary clarifier improves the full scale activated sludge process effluent quality. PACl has a negative effect on methane production.

A comprehensive multiplex PCR based exome-sequencing assay for rapid bloodspot confirmation of inborn errors of metabolism.

BACKGROUND: Tandem mass spectrometry (MS MS) and simple fluorometric assays are currently used in newborn screening programs to detect inborn errors of metabolism (IEM). The aim of the study was to evaluate the clinical utility of exome sequencing as a second tier screening method to assist clinical diagnosis of the newborn. METHODS: A novel PCR-exome amplification and re-sequencing (PEARS) assay was designed and used to detect mutations in 122 genes associated with 101 IEM. Newborn bloodspots positive by biochemical testing were analysed by PEARS assay to detect pathogenic mutations relevant to the IEM. RESULTS: In initial validation studies of genomic DNA samples, PEARS assay correctly detected 25 known mutations associated with 17 different IEM. Retrospective gene analysis of newborns with clinical phenylketonuria (PKU), identified compound heterozygote phenylalanine hydroxylase (PAH) gene mutations in eight of nine samples (89%). Prospective analysis of 211 bloodspots correctly identified the two true PKU samples, yielding positive and negative predictive values of 100%. Testing of 8 true positive MS MS samples correctly identified potentially pathogenic compound heterozygote genotypes in 2 cases of citrullinemia type 1 and one case each of methylmalonic acidemia, isobutyryl-CoA dehydrogenase deficiency, short chain acyl-CoA dehydrogenase deficiency and glutaric acid type II and heterozygous genotypes in 2 cases of autosomal dominant methioninemia. Analysis of 11 of 12 false positive MS MS samples for other IEM identified heterozygous carriers in 8 cases for the relevant genes associated with the suspected IEM. In the remaining 3 cases, the test revealed compound heterozygote mutations in other metabolic genes not associated with the suspected IEM, indicating a misinterpretation of the original MS MS data. CONCLUSIONS: The PEARS assay has clinical utility as a rapid and cost effective second-tier test to assist the clinician to accurately diagnose newborns with a suspected IEM.

RPS3A positively regulates the mitochondrial function of human periaortic adipose tissue and is associated with coronary artery diseases.

Pericardial adipose tissue, which comprises both epicardial adipose tissue (EAT) and paracardial adipose tissue (PAT), has recently been recognized as a novel factor in the pathophysiology of cardiovascular diseases, especially coronary artery disease (CAD). The goal of this study was to evaluate differences in the brown-like characteristic and proteome among human EAT, PAT, and subcutaneous adipose tissue (SAT) to identify candidate molecules causing CAD. Uncoupling protein 1 (UCP-1) and other brown-related proteins were highly expressed in pericardial adipose tissue but was weakly expressed in SAT from the same non-CAD patient. Moreover, pericardial adipose tissues displayed a higher thermogenesis than SAT. However, brown-related genes were lower in CAD pericardial fat. Remarkably, there were lower levels of metabolic enzymes involved in glycolysis, tricarboxylic acid cycle, and fatty acid metabolism in pericardial adipose tissues of CAD. EAT is an organ adjacent to aortic root without anatomy barriers, which differs from PAT. We found that the expression of ribosomal protein S3A (RPS3A) was decreased in human EAT as well as in mouse perivascular adipose tissue (PVAT). Knockdown of RPS3A significantly inhibited adipocyte differentiation in preadipocytes and impaired the function of mitochondria in mature adipocytes. Moreover, RPS3A knockdown in mouse periaortic adipose tissue impaired browning of PVAT, accelerated vascular inflammation, and atherosclerosis progression. Mechanistically, RPS3A can migrate to the mitochondria to maintain the function of brown adipocytes. These findings provide compelling evidence that RPS3A was a key factor for modulating the brown fat-specific gene UCP-1 and carbon metabolic enzymes in EAT for preventing CAD.