Jingjing Jiang

The WRKY gene family is among the largest families of transcription factors (TFs) in higher plants. By regulating the plant hormone signal transduction pathway, these TFs play critical roles in some plant processes in response to biotic and abiotic stress. Various bodies of research have demonstrated the important biological functions of WRKY TFs in plant response to different kinds of biotic and abiotic stresses and working mechanisms. However, very little summarization has been done to review their research progress. Not just important TFs function in plant response to biotic and abiotic stresses, WRKY also participates in carbohydrate synthesis, senescence, development, and secondary metabolites synthesis. WRKY proteins can bind to W-box (TGACC (A/T)) in the promoter of its target genes and activate or repress the expression of downstream genes to regulate their stress response. Moreover, WRKY proteins can interact with other TFs to regulate plant defensive responses. In the present review, we focus on the structural characteristics of WRKY TFs and the research progress on their functions in plant responses to a variety of stresses.

Retinal fundus diseases can lead to irreversible visual impairment without timely diagnoses and appropriate treatments. Single disease-based deep learning algorithms had been developed for the detection of diabetic retinopathy, age-related macular degeneration, and glaucoma. Here, we developed a deep learning platform (DLP) capable of detecting multiple common referable fundus diseases and conditions (39 classes) by using 249,620 fundus images marked with 275,543 labels from heterogenous sources. Our DLP achieved a frequency-weighted average F1 score of 0.923, sensitivity of 0.978, specificity of 0.996 and area under the receiver operating characteristic curve (AUC) of 0.9984 for multi-label classification in the primary test dataset and reached the average level of retina specialists. External multihospital test, public data test and tele-reading application also showed high efficiency for multiple retinal diseases and conditions detection. These results indicate that our DLP can be applied for retinal fundus disease triage, especially in remote areas around the world.

Abstract RAS oncogenes (collectively NRAS , HRAS and especially KRAS ) are among the most frequently mutated genes in cancer, with common driver mutations occurring at codons 12, 13 and 61 1 . Small molecule inhibitors of the KRAS(G12C) oncoprotein have demonstrated clinical efficacy in patients with multiple cancer types and have led to regulatory approvals for the treatment of non-small cell lung cancer 2,3 . Nevertheless, KRAS G12C mutations account for only around 15% of KRAS -mutated cancers 4,5 , and there are no approved KRAS inhibitors for the majority of patients with tumours containing other common KRAS mutations. Here we describe RMC-7977, a reversible, tri-complex RAS inhibitor with broad-spectrum activity for the active state of both mutant and wild-type KRAS, NRAS and HRAS variants (a RAS(ON) multi-selective inhibitor). Preclinically, RMC-7977 demonstrated potent activity against RAS-addicted tumours carrying various RAS genotypes, particularly against cancer models with KRAS codon 12 mutations ( KRAS G12X ). Treatment with RMC-7977 led to tumour regression and was well tolerated in diverse RAS-addicted preclinical cancer models. Additionally, RMC-7977 inhibited the growth of KRAS G12C cancer models that are resistant to KRAS(G12C) inhibitors owing to restoration of RAS pathway signalling. Thus, RAS(ON) multi-selective inhibitors can target multiple oncogenic and wild-type RAS isoforms and have the potential to treat a wide range of RAS-addicted cancers with high unmet clinical need. A related RAS(ON) multi-selective inhibitor, RMC-6236, is currently under clinical evaluation in patients with KRAS -mutant solid tumours (ClinicalTrials.gov identifier: NCT05379985).

Pollen grains are surrounded by a sculpted wall, which protects male gametophytes from various environmental stresses and microbial attacks, and also facilitates pollination. Pollen wall development requires lipid and polysaccharide metabolism, and some key genes and proteins that participate in these processes have recently been identified. Here, we summarise the genes and describe their functions during pollen wall development via several metabolic pathways. A working model involving substances and catalytic enzyme reactions that occur during pollen development is also presented. This model provides information on the complete process of pollen wall development with respect to metabolic pathways.