Emerging mycotoxins are mycotoxins that have emerged in recent years, encompassing more than ten different families of mycotoxins, primarily Alternaria toxins (ATs), enniatins (ENNs), and beauvericin (BEA). These contaminants are widely found in a variety of food groups including cereals, fruits and vegetables, beer, wine, beans, and potatoes. Studies have shown that multiple physiological toxicities of the emerging mycotoxins are identified in plants, animals, and various human cell lines, and their presence are associated with certain human diseases. Notably, the emerging mycotoxins are not only prevalent in food but also frequently detected in human biological samples (e.g., serum, urine, and breast milk). Furthermore, multiple risk assessment studies have indicated that dietary exposure to the emerging mycotoxins, particularly ATs, exceed safe levels in some populations, posing potential threats to both food safety and human health. This article reviewed the contamination and physiological toxicity of three major emerging mycotoxins—ATs, ENNs, and BEA—in food, as well as research progress in human exposure assessment by different risk evaluation methods (e.g., dietary contamination & intake assessment and human biomonitoring). Additionally, it discussed current research challenges and unresolved scientific issues, aiming to provide insights for the biological control of emerging mycotoxins in food and the assessment of their exposure risks in human populations.

Metabolic dysfunction-associated fatty liver disease （MAFLD）， formerly known as nonalcoholic fatty liver disease （NAFLD）， has become a common chronic liver disease worldwide. Currently， the clinical methods for diagnosing liver diseases have limitations such as invasive procedures， insufficient sensitivity， and low diagnostic accuracy， posing challenges to the early identification and precise treatment of MAFLD. In recent years， the rapid development of multi-omics techniques has provided new ideas for the precise diagnosis and treatment of MAFLD. Genomics， metabolomics， lipidomics， microbiomics， and proteomics techniques not only offer new insights into the pathogenesis of MAFLD， but also identify novel biomarkers for disease prediction， diagnosis， and staging. Meanwhile， diagnostic models constructed based on multi-omics data have shown good clinical efficacy and laid an important foundation for the development of noninvasive precise diagnostic tools for MAFLD， and therefore， it is expected to realize the transition from traditional diagnosis and treatment to precision medicine. Although the clinical application value of multi-omics markers in the early diagnosis of MAFLD has been recognized to some extent， there are still challenges in clinical translation， such as the standardization of detection， individual heterogeneity， and cost-effectiveness.

Background Deoxynivalenol (DON), a priority contaminant for food safety risk monitoring, is produced by Fusarium spp. infesting crops, and its common derivatives are 3-acetyl-DON (3A-DON) and 15-acetyl-DON (15A-DON), which have been shown to possess gastrointestinal toxicity, immunotoxicity, reproductive toxicity, and cytotoxicity. Due to the stable physicochemical properties of the DON family of toxins (DONs), they cannot be effectively removed during food processing, thus following the food chain, entering the human body, and posing health risks. Objective To understand the contamination status of DONs in commercial foods (cereals and bakery products) in Shanghai in 2022–2023, and to assess the exposure risk of DONs in pregnant women by combining their dietary consumption data. Methods Liquid chromatography tandem mass spectrometry (LC-MS/MS) was used to determine the contamination level of DONs in 1 100 food samples (cereals and baked goods) collected in 2022 and 944 samples collected in 2023 from Shanghai. The dietary monitoring data of pregnant women in Shanghai from 2016 to 2017 were adopted. The monitoring employed the food frequency questionnaire distributed among pregnant women through a combination of online telephone enquiry and offline on-site face-to-face survey to estimate their food consumption levels. An exposure assessment model was established to calculate the exposure level to DONs, and the probability distribution of the DONs exposure level in the pregnant women group in Shanghai was obtained by applying @Risk 7.5 software and simulating the calculation according to the Monte Carlo principle. With reference to the tolerable daily intake (TDI) of DONs [1.00 µg·(kg·d)⁻¹] proposed by the Joint FAO/WHO Expert Committee on Food Additives, the risk of exposure to DONs from commercial cereals and bakery products in pregnant women in Shanghai was assessed. Results DONs were detected in cereal and bakery samples collected in 2022 and 2023 with different levels of contamination. The level of DONs in cereal foods in 2023 (mean: 36.33 µg·kg⁻¹) decreased compared to 2022 (mean: 23.64 µg·kg⁻¹). However, the positive rate (71.67%) and level (mean: 51.22 µg·kg⁻¹) of DONs in bakery products increased significantly compared with 2022 (positive rate: 10.00%, mean: 24.39 µg·kg⁻¹). The mean consumption of cereals in 783 pregnant women was 222.48 g·d⁻¹ and the mean consumption of bakery products was 36.07 g·d⁻¹, and there was no statistically significant difference in the intake of all types of cereals and bakery products across the early, middle, and late stages of pregnancy. The modelled intakes of DONs via commercial cereals and bakery products for pregnant women in Shanghai were calculated to be 0.20 and 0.57 µg·(kg·d)⁻¹ in 2022 for the mean level and the 95th percentile level, respectively, and 0.16 µg·(kg·d)⁻¹ and 0.35 µg·(kg·d)⁻¹ in 2023, respectively. The results of the health risk assessment showed that pregnant women in Shanghai had 2.6% and 1.4% probability of exposure to DONs from cereal consumption in 2022 and 2023, respectively. Conclusion The risk of exposure of pregnant women in Shanghai to DONs via commercial cereals and bakery products is relatively low (1.4%-2.6%). However, considering the physical sensitivity of pregnant women, they should avoid consuming moldy grains and appropriately reduce intake of bakery products.

Objective:To explore the association between insulin resistance (IR) and genome-wide DNA methylation based on Shanghai twin study.Methods:Monozygotic twins (MZ) from Shanghai were recruited during 2012-2013, 2017-2018, and 2022-2023. Data were collected by questionnaire survey, physical examination and laboratory tests. Genome-wide DNA methylation was quantified. Generalized linear mixed effect model was applied to analyze the association between methylation level at each site and homeostatic model assessment 2-insulin resistance (HOMA2-IR). Non-paired and paired designs were used to assess the association between DNA methylation and phenotype of IR. Cluster analysis was conducted to identify the clusters of top significant sites. Generalized linear regression was performed to examine the differential methylation patterns from clusters.Results:A total of 100 MZ pairs were included in this study. Hypermethylated cg10535199-2q23.1 ( β=0.74%, P=1.51×10 -7, OR=1.06, 95% CI: 1.03-1.09) and ch.17.49619327- SPOP ( β=0.23%, P=7.54×10 -7, OR=1.17, 95% CI: 1.08-1.28) were identified with suggestive significance. After correcting for multiple testing, no sites reached genome-wide significance. There was no statistical significance in the paired analysis. Two clusters with hypomethylated ( β=-0.39%, P<0.001) and hypermethylated ( β=0.47%, P<0.001) patterns were observed for HOMA2-IR. Conclusions:IR was significantly associated with DNA methylation, and genetic factors might contribute to the association.

Objective·To compare the performance of various deep learning methods in the segmentation and classification of colorectal polyp endoscopic images,and identify the most effective approach.Methods·Four colorectal polyp datasets were collected from three hospitals,encompassing 1 534 static images and 15 videos.All samples were pathologically validated and categorized into two types:serrated lesions and adenomatous polyps.Polygonal annotations were performed by using the LabelMe tool,and the annotated results were converted into integer mask formats.These data were utilized to train various architectures of deep neural networks,including convolutional neural network(CNN),Transformers,and their fusion,aiming to develop an effective semantic segmentation model.Multiple performance indicators for automatic diagnosis of colon polyps by different architecture models were compared,including mIoU,aAcc,mAcc,mDice,mFscore,mPrecision and mRecall.Results·Four different architectures of semantic segmentation models were developed,including two deep CNN architectures(Fast-SCNN and DeepLabV3plus),one Transformer architecture(Segformer),and one hybrid architecture(KNet).In a comprehensive performance evaluation of 291 test images,KNet achieved the highest mIoU of 84.59％,significantly surpassing Fast-SCNN(75.32％),DeepLabV3plus(78.63％),and Segformer(80.17％).Across the categories of"background","serrated lesions"and"adenomatous polyps",KNet's intersection over union(IoU)were 98.91％,74.12％,and 80.73％,respectively,all exceeding other models.Additionally,KNet performed excellently in key performance metrics,with aAcc,mAcc,mDice,mFscore,and mRecall reaching 98.59％,91.24％,91.31％,91.31％,and 91.24％,respectively,all superior to other models.Although its mPrecision of 91.46％was not the most outstanding,KNet's overall performance remained leading.In inference testing on 80 external test images,KNet maintained an mIoU of 81.53％,demonstrating strong generalization capabilities.Conclusion·The semantic segmentation model of colorectal polyp endoscopic images constructed by deep neural network based on KNet hybrid architecture,exhibits superior predictive performance,demonstrating its potential as an efficient tool for detecting colorectal polyps.

3 cases with dental implant entered into the maxillary sinus by accident during posterior maxillary dental implant surgery were reported in this work.The implants were localized by CBCT scanning and removed by endoscope assisted extraction through the refined Cald-well-Luc approach under local anesthesia.The results showed that all 3 implants were successfully removed,highlighting the efficacy of en-doscopic-assisted techniques in minimizing trauma,ensuring accurate positioning and providing a clear surgical field of vision.

ObjectiveTo conduct comprehensive assessment of internal and external cadmium exposure and health risks for Shanghai residents. MethodsCadmium levels in food samples were calculated by employing two dietary exposure assessment methods， total diet study （TDS） and food frequency questionnaire （FFQ）， to estimate the daily dietary cadmium exposure of Shanghai residents. The provisional tolerable monthly intake （PTMI） of cadmium set by joint food and agriculture organization/WHO expert committee on food additives （JECFA） was applied to evaluate the health risk. Differences in dietary and urinary cadmium were compared by rank-sum test among different regions， age， gender， smoking status， and BMI groups， and the association between internal and external cadmium exposure was investigated by correlation analysis. ResultsThe mean value of urinary cadmium for 1 300 respondents was 0.542 μg·L^-1. Urinary cadmium was higher in the population in central urban and urban-rural fringe areas than in the suburban area， higher in the older age group than in the younger age group， and higher in the smoking group than in the non-smoking group （all P<0.01）. The two assessment methods showed that the mean values of daily dietary cadmium exposure for Shanghai residents were 0.306 and 0.090 μg·kg^-1， with 3.69% and 0.85% of Shanghai residents exceeding the PTMI， respectively. Correlation analyses showed that dietary exposure to cadmium based on the FFQ method was positively correlated with the urinary cadmium level when smoking status， age， gender， and BMI were adjusted. ConclusionDietary exposure to cadmium of Shanghai residents is mainly derived from vegetables， aquatic products， cereals and potatoes， and is overall at a low-risk level. Dietary exposure assessment based on FFQ and risk monitoring data can effectively estimate long-term cadmium exposure.

Objective To explore the status quo of medication belief in the patients with myasthenia gravis and analyze their influencing factors,so as to provide reference for health care professionals to develop targeted interventions.Methods A total of 145 patients with myasthenia gravis visiting the First Affiliated Hospital of Guangzhou University of Chinese Medicine from July 2021 to March 2022 were selected.The Be-liefs about Medicines Questionnaire(BMQ)was used to investigate.The multiple linear regression was used to analyze the relevant influencing factors.Results The scores of medication belief,necessity belief and con-cern belief in 145 patients were(4.17±1.23)points,(19.52±3.45)points and(18.29±4.26)points respec-tively.There was statistically significant difference between the scores of necessity belief and concern belief(P＜0.05).The education level,financial burden,duration of illness,length of medication,number of recur-rent hospitalizations,and inappropriate medication-induced exacerbations had influence on the medication be-lief scores of the patients with myasthenia gravis(P＜0.05).The duration of illness,length of medication and number of recurrent hospitalizations had the influence on the medication necessity scores of patients with my-asthenia gravis(P＜0.05).The financial burden had the influence on the medication concerns scores of the patients with myasthenia gravis(P＜0.05).Conclusion The medication belief in the patient swith myasthe-nia gravis is at a low level,and the number of recurrent hospitalizations and financial burden are the independ-ent risk factors affecting the medication belief scores in the patients with myasthenia gravis.The number of recurrent hospitalizations is an independent risk factor for the score of medication necessity dimension.

ObjectiveTo clone squalene epoxidase （SE）， a potential key rate-limiting enzyme involved in the synthesis pathway of Poria cocos triterpenes， from P. cocos and analyze for bioinformatics and expression. MethodThe total RNA was extracted by the kit and reverse-transcribed to cDNA. Specific primers were designed， and the cDNA was used as a template for cloning the SE gene， which was analyzed for bioinformatics. The expression of P. cocos qualene epoxidase（PcSE） was examined by Real-time polymerase chain reaction（Real-time PCR） in P. coco Shenzhou No. 10， Xiangjing 28， and 5.78 strains. ResultThe full length of PcSE is 1 571 bp， containing four exons and three introns. The obtained CDS sequence is 1 413 bp， encoding 470 amino acids. This protein is a hydrophobic protein with no signal peptide structure and has two transmembrane structural domains with a FAD/NAD （P） binding domain and SE structural domain localized to the mitochondrial membrane and the plasma membrane. The homologous sequence alignment with fungi of the Poriferae family is 80.92%， and the phylogenetic tree shows that PcSE protein is most closely related to P. cocos from the US. The results of Real-time PCR showed that the PcSE was expressed in all three strains， with the highest expression in 5.78 strain， and there was no significant difference in PcSE expression among the three strains. ConclusionFor the first time， the PcSE gene was cloned and analyzed from P. cocos， providing a basis for further research on the function of PcSE and the analysis of P. cocos triterpene biosynthesis pathway.

ObjectiveTo provide basic data of daily dietary intake from various food categories as well as in different regions， seasons， genders， and age groups in Shanghai residents aged 15 and over. MethodsMultistage stratified proportional probability sampling （PPS） was used to extract the samples， and food frequency questionnaire （FFQ） was used to investigate the dietary intake of the subjects in four seasons from 2012 to 2013. The weighted statistical analysis of the samples comprehensively considered the sampling design weights， the stratified adjustment weights， and the non-response adjustment weights. ResultsThe total daily dietary intake （excluding drinking water） of residents aged 15 years and above was 1 174.71 g， and the highest three daily dietary intake categories were cereals （252.31 g）， vegetables （205.36 g） and fruits （141.00 g）. The total daily dietary intake of the residents in the urban area， the suburban area and the rural area was 1 209.15 g，1 172.27 g and 948.50 g， respectively， and the total daily dietary intake in the outer suburb area was significantly lower than that in other areas （F=74.12，P<0.001）. The total daily dietary intake in different seasons was 1 232.47 g in spring， 1 166.80 g in summer， 1 241.15 g in autumn and 1 088.83 g in winter， respectively. The total daily dietary intake in winter was lower than that in other seasons （F=15.96，P<0.001）. Fruits and beverages intake showed apparent seasonality. The total daily dietary intake in male and female residents was 1 234.03 g and 1 112.32 g， respectively， and the total daily dietary intake of male was higher than that of female （F=78.59，P<0.001）. The total daily dietary intake of residents in different age groups was 1 218.64 g for 15‒44 years old， 1 141.27 g for 45‒59 years old， and 1 064.54 g for 60 years old and above （F=20.28，P<0.001）. ConclusionThe daily intake of cereals， livestock and poultry meat， aquatic products， eggs and edible oil is relatively balanced， but the daily intake of vegetables， fruits and milk is relatively insufficient for the residents aged 15 years and above in Shanghai. The daily intake of different food types shows distinguishable characteristics in urban and rural areas， seasons， age groups and genders.