The concentration of potentially toxic elements (PTEs) in apple fruit: a global systematic review, meta-analysis, and health risk assessment

A multi-year heavy metal analysis of 72 dark chocolate and cocoa products in the USA

Introduction

Contamination of cocoa containing products, such as dark chocolate, with heavy metals including lead, cadmium and arsenic has been reported in the US. However, a formal exploration into the significance of this contamination, nor multi-year trends in the degree or scope remain unresolved.

Methods

From 2014 to 2022, 72 consumer cocoa-containing products were purchased and analyzed for heavy metal contamination with lead (Pb), cadmium (Cd), and arsenic (As) in 4 distinct cohorts (2014, 2016, 2019, 2022). The thresholds used to assess heavy metal contamination were set to Prop 65 maximum allowable dose levels (MADLs) of 0.5 mcg/day, 4.1 mcg/day, 10 mcg/day for Pb, Cd, and As, respectively.

Results and discussion

Our analysis reports that 43, 35, and 0% of the products tested exceed Prop 65 MADLs for heavy metal concentrations, respectively, of Pb, Cd, and As, while 97.2% (70 of 72) fall below US FDA IRL limits established for Pb. Median concentrations of each metal tested were lower than even the conservative Prop 65 MADLs, indicating a potentially large effect of product outliers. This indicates that heavy metal contamination-in more than half of products tested-may not pose any appreciable risk for the average person when consumed as a single serving; however, consuming some of the products tested, or more than one serving per day in combination with non-cocoa derived sources heavy metals, may add up to exposure that would exceed the Prop 65 MADLs. Notably, "organic" products were significantly more likely to demonstrate higher levels of both Cd and Pb.

Ochratoxin A in coffee and coffee-based products: a global systematic review, meta-analysis, and probabilistic risk assessment

Contamination of food with mycotoxins can pose harmful effects on the health of consumers in the long term. Coffee contamination with mycotoxins has become a global concern. This study attempted to meta-analyze the concentration and prevalence of ochratoxin A (OTA) in coffee products and estimate consumers' health risks. The search was conducted among international databases, including Scopus, PubMed, Embase, and Web of Science, for 1 January 2010 to 1 May 2022. The concentration and prevalence of OTA in coffee products were meta-analyzed according to country subgroups. Health risk assessment was conducted based on Margin of Exposures (MOEs) using the Monte Carlo simulation (MCS) technique. The three countries that had the highest Pooled concentration of OTA in coffee were observed in Chile (100.00%), Kuwait (100.00%), and France (100.00%). The overall prevalence of OTA in coffee products was 58.01%, 95% CI (48.37-67.39). The three countries that had the highest concentration of OTA were Philippines (39.55 μg/kg) > Turkey (39.32 μg/kg) > and Panama (21.33 μg/kg). The mean of MOEs in the adult consumers in Panama (9,526) and the Philippines (8,873) was lower than 10,000, while the mean of MOEs in other countries was higher than 10,000. Therefore, monitoring and control plans should be carried out in different countries.

Computer vision based deep learning approach for toxic and harmful substances detection in fruits

Formaldehyde (CH₂O) is one of the significant chemicals mixed with different perishable fruits in Bangladesh. The fruits are artificially preserved for extended periods by dishonest vendors using this dangerous chemical. Such substances are complicated to detect in appearance. Hence, a reliable and robust detection technique is required. To overcome this challenge and address the issue, we introduce comprehensive deep learning-based techniques for detecting toxic substances. Four different types of fruits, both in fresh and chemically mixed conditions, are used in this experiment. We have applied diverse data augmentation techniques to enlarge the dataset. The performance of four different pre-trained deep learning models was then assessed, and a brand-new model named "DurbeenNet," created especially for this task, was presented. The primary objective was to gauge the efficacy of our proposed model compared to well-established deep learning architectures. Our assessment centered on the models' accuracy in detecting toxic substances. According to our research, GoogleNet detected toxic substances with an accuracy rate of 85.53 %, VGG-16 with an accuracy rate of 87.44 %, DenseNet with an impressive accuracy rate of 90.37 %, and ResNet50 with an accuracy rate of 91.66 %. Notably, the proposed model, DurbeenNet, outshone all other models, boasting an impressive accuracy rate of 96.71 % in detecting toxic substances among the sample fruits.

Optimization of apple fruit flavor by MdVHP1-2 via modulation of soluble sugar and organic acid accumulation

For fleshy fruits, the content and ratio of organic acids and soluble sugars are key factors for their flavor. Therefore, a better understanding of soluble sugar and organic acid accumulation in vacuoles is essential to the improvement of fruit quality. Vacuolar-type inorganic pyrophosphatase (V-PPase) has been found in various plants with crucial functions based on the hydrolysis of PPi. However, the effects of V-PPase on the soluble sugar and organic acid accumulation in apple fruit remain unclear. In this study, MdVHP1-2, a V-PPase protein in the vacuolar membrane, was identified. The results showed a positive correlation between the expression of MdVHP1-2 and the sugar/acid ratio during ripening of apple fruits. A series of transgenic analyses showed that overexpression of MdVHP1-2 significantly elevated the contents of soluble sugars and organic acids as well as the sugar/acid ratio in apple fruits and calli. Additionally, transient interference induced by MdVHP1-2 expression inhibited the accumulation of soluble sugars and organic acids in apple fruits. In summary, this study provides insight into the mechanisms by which MdVHP1-2 modulates fruit flavor through mediation of soluble sugar and organic acid accumulation, thereby facilitating improvement of the overall quality of apple and other fruits.

Prevalence and concentration of aflatoxin M1 and ochratoxin A in cheese: a global systematic review and meta-analysis and probabilistic risk assessment

Exposure to mycotoxins such as aflatoxins can endanger human health, especially infants and children. In this study, an attempt was made to retrieved studies related to the concentration of aflatoxin M1 (AFM1) and ochratoxin A (OTA). Search was performed in international databases such as Embase, PubMed, Scopus, and Web of Science for the period 1 January 2010 to 20 February 2023. Then, the pooled concentration in the defined subgroups was calculated using meta-analysis and the health risk assessment was conducted by margin of exposure (MOEs). Thirty-one scientific papers with 34 data reports (Sample size=2,277) were included in our study. The lowest and highest prevalence of AFM1 in cheese was related to El Salvador (12.18 %) and Serbia (100.00 %). The pooled prevalence of AFM1 was 49.85 %, 95 %CI (37.93-61.78 %). The lowest and highest prevalence of OTA in cheese was related to Türkiye (6.67 %) and Italy (44.21 %). The pooled prevalence of OTA was 35.64 %, 95 %CI (17.16-56.44 %). Health risk of AFM1 revealed that except Pakistan and Iran, MOE in the other countries was lower than 10,000 for adults and also except Pakistan, MOE for other countries was lower than 10,000 for children. Health risk of OTA revealed that except Greece, MOE in the other countries was higher than 10,000 for adults and also except Germany and Greece, MOE for other countries was higher than 10,000 for children. Therefore, it is recommended to conduct control plans to reduce the concentration of mycotoxins in cheese, especially AFM1.

Heavy metal contamination and risk assessment in winter jujube (Ziziphus jujuba Mill. cv. Dongzao)

Winter jujube (Ziziphus jujuba Mill. cv. Dongzao) is a major fresh-eating jujube fruit with various important nutrients for humans. It can absorb heavy metals from polluted air, water and soils and applied pesticides, which may pose potential threats to consumers. Here, to evaluate the content of heavy metals in winter jujube and systematically evaluate the potential risks, we collected 212 winter jujube samples from four main producing areas in China and determined the contents of eight heavy metals (Cd, Cr, Pb, Ni, Cu, Zn, As, and Mn) using inductively coupled plasma mass spectrometer (ICP-MS). Based on the integrated pollution index (IPI) evaluation standard, more than 99.06% of samples were at safe levels. Moreover, clustering analysis divided the eight heavy metals into four groups, namely Cr/Ni, Cd/Pb, Cu/Mn/Zn, and As. Importantly, none of the analyzed heavy metals posed risks to adults as indicted by the average carcinogenic and non-carcinogenic risks. Notably, Cr and Cd could pose low carcinogenic risks to children (≤12 age group) when their concentration reached the 90^th percentile. This study systematically assessed the health risks associated with heavy metal intake through winter jujube consumption and highlighted the necessity of constant heavy metal monitoring in winter jujube.