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Abstract Temozolomide (TMZ) resistance remains the major obstacle in the treatment of glioblastoma (GBM). Lactylation is a novel post‐translational modification that is involved in various tumors. However, whether lactylation plays a role in GBM TMZ resistance remains unclear. Here it is found that histone H3K9 lactylation (H3K9la) confers TMZ resistance in GBM via LUC7L2‐mediated intron 7 retention of MLH1. Mechanistically, lactylation is upregulated in recurrent GBM tissues and TMZ‐resistant cells, and is mainly concentrated in histone H3K9. Combined multi‐omics analysis, including CUT&Tag, SLAM‐seq, and RNA‐seq, reveals that H3K9 lactylation is significantly enriched in the LUC7L2 promoter and activates LUC7L2 transcription to promote its expression. LUC7L2 mediates intron 7 retention of MLH1 to reduce MLH1 expression, and thereby inhibit mismatch repair (MMR), ultimately leading to GBM TMZ resistance. Of note, it is identified that a clinical anti‐epileptic drug, stiripentol, which can cross the blood–brain barrier and inhibit lactate dehydrogenase A/B (LDHA/B) activity, acts as a lactylation inhibitor and renders GBM cells more sensitive to TMZ in vitro and in vivo. These findings not only shed light on the mechanism of lactylation in GBM TMZ resistance but also provide a potential combined therapeutic strategy for clinical GBM treatment.

Fungal diseases not only reduce the yield of edible mushrooms but also pose potential threats to the preservation and quality of harvested mushrooms. Cobweb disease, caused primarily by fungal pathogens from the Hypocreaceae family, is one of the most significant diseases affecting edible mushrooms. Deciphering the genomes of these pathogens will help unravel the molecular basis of their evolution and identify genes responsible for pathogenicity. Here, we present high-quality genome sequences of three cobweb disease fungi: Hypomyces aurantius Cb-Fv, Cladobotryum mycophilum CB-Ab, and Cladobotryum protrusum CB-Mi, isolated from Flammulina velutipes, Agaricus bisporus, and Morchella importuna, respectively. The assembled genomes of H. aurantius, C. mycophilum, and C. protrusum are 33.19 Mb, 39.83 Mb, and 38.10 Mb, respectively. This is the first report of the genome of H. aurantius. Phylogenetic analysis revealed that cobweb disease pathogens are closely related and diverged approximately 17.51 million years ago. CAZymes (mainly chitinases, glucan endo-1,3-beta-glucosidases, and secondary metabolite synthases), proteases, KP3 killer proteins, lipases, and hydrophobins were found to be conserved and strongly associated with pathogenicity, virulence, and adaptation in the three cobweb pathogens. This study provides insights into the genome structure, genome organization, and pathogenicity of these three cobweb disease fungi, which will be a valuable resource for comparative genomics studies of cobweb pathogens and will help control this disease, thereby enhancing mushroom quality.

Summary: The prognosis of glioblastoma (GBM) patients is poor, and temozolomide (TMZ) resistance has become an important obstacle to its treatment effect. A growing number of researches have revealed the special characteristics of iron metabolism in GBM chemosensitivity. Iron regulatory protein 1 (IRP1) is an important protein for maintaining intracellular iron homeostasis. IRP1 has been indicated to have additional vital roles beyond its conventional metabolic activity, but the underlying mechanisms and biological consequences remain elusive. Here, we unprecedentedly demonstrated that amplifying IRP1 signals can reverse TMZ resistance and suppress tumor growth in vivo via inhibiting NFKB2 in the noncanonical NF-κB signaling pathway. In addition, we identified that NFKB2 affected TMZ sensitivity of GBM by modulating the expression of LCN2 and FPN1. Taken together, this study established a role for the IRP1/NFKB2 pathway in regulating LCN2/FPN1 signaling axis among the progression of TMZ resistance, suggesting a potential innovative GBM therapeutic strategy.

N6-methyladenosine (m6A) is the most abundant modification in eukaryotic cells, and it regulates RNA transcription, processing, splicing, degradation, and translation. Long non-coding RNAs (lncRNAs), as transcriptional products with no or limited protein coding ability more than 200 nt in length, play an important role in epigenetic modification, mRNA transcription, splicing, stability, translation, and other biological functions. Extensive studies have shown that both m6A modification and lncRNAs are involved in the pathogenesis of various diseases, such as kinds of cancers, heart failure, Alzheimer’s disease, periodontitis, human abdominal aortic aneurysm, and obesity. To date, m6A modification has been identified as an important biological function in enrichment and regulation of lncRNAs. In this review, we summarize the role of m6A modification in the regulation and function of tumor-related lncRNAs. Moreover, we discuss the potential applications and possible future directions in the field.

This paper attempts to design an automated, efficient and intelligent tomato grading method that facilitates the graded selling of the fruit. Based on machine vision, the color images of tomatoes with different morphologies were studied, and the color, shape and size were selected as the key features. On this basis, an automated grading classifier was created based on the surface features of tomatoes, and a grading platform was set up to verify the effect of the classifier. Specifically, the Hue value distributions of tomatoes with different maturities were investigated, and the Hue value ranges were determined for mature, semi-mature and immature tomatoes, producing the color classifier. Next, the first-order Fourier descriptor (1D- FD) was adopted to describe the radius sequence of tomato contour, and an equation was established to compute the irregularity of tomato contour, creating the shape classifier. After that, a linear regression equation was constructed to reflect the relationship between the transverse diameters of actual tomatoes and tomato images, and a classifier between large, medium and small tomatoes was produced based on the transverse diameter. Finally, a comprehensive tomato classifier was built based on the color, shape and size diameters. The experimental results show that the mean grading accuracy of the proposed method was 90.7%. This means our method can achieve automated real-time grading of tomatoes.