Postharvest diseases cause huge postharvest losses of horticultural fresh produce. Cooling and synthetic fungicide are used as traditional postharvest preservation technology. Recently, induced resistance has been thought to be an optional and perhaps alternative preservation technology. 1-methylcyclopropylene (1-MCP) and salicylic acid (SA) are two more common chemical agents used mostly as a preservative for harvested fruit in order to achieve better quality and better taste. Many reports have also proven that 1-MCP and SA could induce postharvest fruit resistance. The purpose of this review is to summarize the role of 1-MCP and SA in postharvest fruit resistance, including the effect of 1-MCP and SA on the induced resistance as well as its involved mechanism; the effects of 1-MCP and SA on firmness, phenolic metabolism, membrane lipid metabolism, and reactive oxygen species in fruit after harvest; and the effects of 1-MCP and SA on disease resistance-related defense enzymes, proteins, signaling synthesis, and signaling pathways as well as the combined effect of 1-MCP and SA on the induced resistance and its mechanism. Meanwhile, we prospect for the future direction of increasing postharvest fruit resistance by 1-MCP and SA in more depth.

PURPOSE: MET exon 14 ( MET ex14) skipping is an actionable biomarker in non–small-cell lung cancer. However, MET variants are highly complex and diverse, and not all variants lead to exon 14 skipping. Assessing the skipping effect of unknown variants is still a key issue in molecular diagnosis. MATERIALS AND METHODS: We retrospectively collected MET variants around exon 14 from 4,233 patients with non–small-cell lung cancer who underwent next-generation sequencing testing using DNA, as well as two published data sets. RESULTS: Among the 4,233 patients, 44 unique variants including 29 novel variants (65.9%) were discovered from 53 patients. Notably, 31 samples (58.5%) failed RNA verification. Using RNA verification, nine novel skipping variants and five nonskipping variants were confirmed. We further used SpliceAI with the delta score cutoff of 0.315 to aid the classification of novel variants (sensitivity = 98.88% and specificity = 100%). When applied to the reported variants, we also found three wrongly classified nonskipping variants. Finally, an optimized knowledge-based interpretation procedure for clinical routine was built according to the mutation type and location, and five more skipping mutations from the 13 unknown variants were determined, which improved the population determination rate to 0.92%. CONCLUSION: This study discovered more MET ex14 skipping variants and optimized an innovative approach that could be adapted for the interpretation of infrequent or novel MET ex14 variants timely without experimental validation.

Purpose: To evaluate the effectiveness of using a modified lung imaging reporting and data system (Lung-RADS) for risk stratification of pure ground-glass nodules (pGGNs) in low-dose computed tomography (LDCT) for lung cancer (LC) screenings in China. Patients and Methods: Eight subjects with nine pGGNs originating from a Cancer Screening Program were enrolled as training set and 32 asymptomatic subjects with 35 pGGNs were selected as validation set from November 2013 to October 2018. The complementary Lung-RADS categories were set based on the GGN-vessel relationship (GVR). The correlations between GGN-vessel relationships and pathology were evaluated, and the diagnostic value of complementary Lung-RADS version 1.1 in discriminating malignant pGGNs were analyzed. Results: The inter-reader agreements for Lung-RADS 1.1 (intraclass correlation coefficient (ICC= 0.999) and complementary Lung-RADS 1.1 (ICC= 0.971) displayed good reliability. The combined incidence of invasive adenocarcinoma in type III and IV was more than that of benign and preinvasive diseases (30% vs 75%, P=0.013). Type II GVR between two benign (66.7%), seven preinvasive (53.8%), and six invasive (21.4%) GGN cases was statistically significant (chi(2) =5.415, P=0.019). GGN pathological groups and GVR had a significant correlation (r=0.584, P=0.00). Compared to Lung-RADS 1.1, complementary Lung-RADS 1.1 had better performance in the training set, with its sensitivity increased from 33.3% to 88.9%, accuracy increased from 44.4% to 88.9%, false-negative proportion (FNP) decreased from 66.7% to 11.1%, and the sensitivity to predict malignant nodules increased from 13.8% to 93.1%, accuracy increased from 28.6% to 80.0%, and FNP decreased from 86.2% to 6.9% in validation set. The detection rate of preinvasive disease and adenocarcinoma was increased from 12.5% to 90.6% and that of missed diagnosis decreased from 87.5% to 9.4% in the validation set, P=0.004. Conclusion: Complementary Lung-RADS 1.1 is superior to Lung-RADS 1.1 and would be beneficial for LC screening of LDCT in China.

One of the major variables affecting yield of the mushroom Agaricus bisporus is the casing layer, which directly affects the productivity and mass. Here, volatile organic compounds were extracted by headspace solid-phase microextraction and high-throughput sequencing was used to analyze the microbial community diversity. The relationship between mushroom yield at different cropping stages and the contents of volatile organic compounds and microorganisms in three different casing layers: peat, peat + soil and soil were systematically evaluated. The result shows that Benzaldehyde and (E)-2-octenal which stimulate yield, obviously increased as mushrooms grew, while 3-octanone, which inhibits yield, decreased over time in all three casing layers. However, there was not a strong correlation between the concentration of volatile compounds and yield. In addition, more than 3,000 bacterial operational taxonomic units (OTUs) by performing high throughput sequencing of the microbes were obtained in the three casing layers. Interestingly, the microbial community compositions were very similar between the three casing layers at a later cropping stage, but the community richness varied significantly in different casing layers and at different cropping stages. At the phylum level, the communities had similar structures but were quantitively very different, and this was even more obvious at the genus level. Principal component analysis revealed significant alterations in microbial community structure in different casing layers. Sphingomonas, Dongia and Achromobacter were the dominant genera at cropping stage 1, and the stage 3 were abundant in Saccharibacteria_norank, Pseudomonas, Flavobacterium and Brevundimonas, which was positively correlated with yield, while the abundance of Pseudomonas at stage 1 and Lactococcus and Bacillus at stage 3 was negatively correlated with yield. These results provide a guide for the development and agricultural application of microbial agents for yield improvement in the production of A. bisporus.