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The development of automated grading equipment requires achieving high throughput and precise detection of disease spots on jujubes. However, the current algorithms are inadequate in accomplishing these objectives due to their high density, varying sizes and shapes, and limited location information regarding disease spots on jujubes. This paper proposes a method called JujubeSSD, to boost the precision of identifying disease spots in jujubes based on a single shot multi-box detector (SSD) network. In this study, a diverse dataset comprising disease spots of varied sizes and shapes, varying densities, and multiple location details on jujubes was created through artificial collection and data augmentation. The parameter information obtained from transfer learning into the backbone feature extraction network of the SSD model, which reduced the time of spot detection to 0.14 s. To enhance the learning of target detail features and improve the recognition of weak information, the traditional convolution layer was replaced with deformable convolutional networks (DCNs). Furthermore, to address the challenge of varying sizes and shapes of disease spot regions on jujubes, the path aggregation feature pyramid network (PAFPN) and balanced feature pyramid (BFP) were integrated into the SSD network. Experimental results demonstrate that the mean average precision at the IoU (intersection over union) threshold of 0.5 (mAP@0.5) of JujubeSSD reached 97.1%, representing an improvement of approximately 6.35% compared to the original algorithm. When compared to existing algorithms, such as YOLOv5 and Faster R-CNN, the improvements in mAP@0.5 were 16.84% and 8.61%, respectively. Therefore, the proposed method for detecting jujube disease spot achieves superior performance in jujube surface disease detection and meets the requirements for practical application in agricultural production.

Cytochrome P4502E1 (CYP2E1) has been suggested to play critical roles in the pathogenesis of alcoholic fatty liver (AFL), but the underlying mechanisms remains unclear. The current study was designed to evaluate whether CYP2E1 suppression by chlormethiazole (CMZ) could suppress AFL in mice, and to explore the underlying mechanisms.Mice were treated with or without CMZ (50 mg/kg bw, i.p.) and subjected to liquid diet with or without ethanol (5%, w/v) for 4 weeks. Biochemical parameters were measured using commercial kits. The protein and mRNA levels were detected by western blot and qPCR, respectively. Histopathology and immunohistochemical assay were performed with routine methods.CYP2E1 inhibition by CMZ completely blocked AFL in mice, shown as the decline of the hepatic and serum triglyceride levels, and the fewer fat droplets in the liver sections. Chronic ethanol exposure led to significant decrease of the mRNA and protein levels of peroxisome proliferator-activated receptor α (PPAR-α), which was blocked by CMZ co-treatment. CMZ co-treatment suppressed ethanol-induced oxidative stress, overproduction of tumor necrosis α (TNF-α), and decrease of protein levels of the PPAR-α co-activators including p300 and deacetylated PGC1-α. Furthermore, CMZ co-treatment led to the activation of AMP-activated protein kinase (AMPK), mitogen-activated protein kinase (MAPK), and PI3K/Akt/GSK3β pathway. However, chronic ethanol-induced decline of acyl-CoA carboxylase (ACC) and fatty acid synthase (FAS) protein levels was partially restored by CMZ, while the activation of autophagy appeared to be suppressed by CMZ.These results suggested that CMZ suppressed chronic ethanol-induced oxidative stress, TNF-α overproduction, decline of p300 protein level and deacetylation of PGC1-α, and activated AMPK, MAPK, and PI3K/Akt/GSK3β pathway, which might contribute to the activation of PPAR-α and account for the protection of CMZ against AFL.

BACKGROUND: Previous studies investigating the association between cytochrome P4502E1 (CYP2E1) polymorphisms and the risk of alcoholic liver diseases (ALD) have yielded conflicting results. Thus, a meta-analysis was performed to clarify the association between CYP2E1 polymorphisms and the risks of ALD. METHODS: A comprehensive literature search was conducted to identify the relevant studies. The fixed or random effect model was selected based on the heterogeneity test among studies. Publication bias was estimated using Begg's funnel plots and Egger's regression test. RESULTS: A total of 27 and 9 studies were finally included for the association between the CYP2E1 Pst I/Rsa I or Dra I polymorphisms and the risks of ALD, respectively. Overall, the combined results showed that homozygous genotype c2c2 was significantly associated with increase risk of ALD in worldwide populations (c2c2 vs. c1c1: OR = 3.12, 95%CI 1.91-5.11) when ALD patients were compared with alcoholics without ALD. Significant associations between CYP2E1 Pst I/Rsa I polymorphism and ALD risk were also observed in Asians (c2c2 vs. c1c1: OR = 4.11, 95%CI 2.32-7.29) and in Caucasians (c2c2/c1c2 vs. c1c1: OR = 1.58, 95%CI 1.04-2.42) when ALD patients were compared with alcoholics without ALD. However, subgroup analysis stratified by ALD types showed that CYP2E1 Pst I/Rsa I polymorphism was not significantly associated with the risks of alcoholic cirrhosis (ALC). No significant association was observed between CYP2E1 Dra I polymorphism and ALD risks. CONCLUSION: This meta-analysis suggested that CYP2E1 Pst I/Rsa I polymorphism might be not significantly associated with advanced form of ALD (ALC), but might be significantly associated with other form of ALD such as steatosis, hepatisis, fibrosis. Furthermore, CYP2E1 Dra I polymorphism might be not significantly associated with the ALD risks. Since potential confounders could not be ruled out completely, further studies were needed to confirm these results.

Background: Multilocus PCR coupled with electrospray ionization mass spectrometry (PCR/ESI-MS) is a new strategy for pathogen identification, but information about its application in fungal identification remains sparse. Methods: One-hundred and twelve strains and isolates of clinically important fungi and Prototheca species were subjected to both rRNA gene sequencing and PCR/ESI-MS. Three regions of the rRNA gene were used as targets for sequencing: the 5′ end of the large subunit rRNA gene (D1/D2 region), and the internal transcribed spacers 1 and 2 (ITS1 and ITS2 regions). Microbial identification (Micro ID), acquired by combining results of phenotypic methods and rRNA gene sequencing, was used to evaluate the results of PCR/ESI-MS. Results: For identification of yeasts and filamentous fungi, combined sequencing of the three regions had the best performance (species-level identification rate of 93.8% and 81.8% respectively). The highest species-level identification rate was achieved by sequencing of D1/D2 for yeasts (92.2%) and ITS2 for filamentous fungi (75.8%). The two Prototheca species could be identified to species level by D1/D2 sequencing but not by ITS1 or ITS2. For the 102 strains and isolates within the coverage of PCR/ESI-MS identification, 87.3% (89/102) achieved species-level identification, 100% (89/89) of which were concordant to Micro ID on species/complex level. The species-level identification rates for yeasts and filamentous fungi were 93.9% (62/66) and 75% (27/36) respectively. Conclusions: rRNA gene sequencing provides accurate identification information, with the best results obtained by a combination of ITS1, ITS2 and D1/D2 sequencing. Our preliminary data indicated that PCR/ESI-MS method also provides a rapid and accurate identification for many clinical relevant fungi. [ABSTRACT FROM AUTHOR]