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Summary: Drought, especially terminal drought, severely limits wheat growth and yield. Understanding the complex mechanisms behind the drought response in wheat is essential for developing drought‐resistant varieties. This study aimed to dissect the genetic architecture and high‐yielding wheat ideotypes under terminal drought.An automated high‐throughput phenotyping platform was used to examine 28 392 image‐based digital traits (i‐traits) under different drought conditions during the flowering stage of a natural wheat population. Of the i‐traits examined, 17 073 were identified as drought‐related. A genome‐wide association study (GWAS) identified 5320 drought‐related significant single‐nucleotide polymorphisms (SNPs) and 27 SNP clusters.A notable hotspot region controlling wheat drought tolerance was discovered, in which TaPP2C6 was shown to be an important negative regulator of the drought response. The tapp2c6 knockout lines exhibited enhanced drought resistance without a yield penalty. A haplotype analysis revealed a favored allele of TaPP2C6 that was significantly correlated with drought resistance, affirming its potential value in wheat breeding programs.We developed an advanced prediction model for wheat yield and drought resistance using 24 i‐traits analyzed by machine learning. In summary, this study provides comprehensive insights into the high‐yielding ideotype and an approach for the rapid breeding of drought‐resistant wheat. [ABSTRACT FROM AUTHOR]

Motivation: Joint extraction of entity and relation is an important research direction in Information Extraction. The number of scientific and technological biomedical literature is rapidly increasing, so automatically extracting entities and their relations from these literatures are key tasks to promote the progress of biomedical research., Results: The joint extraction of entity and relation model achieves both intra-sentence extraction and cross-sentence extraction, alleviating the problem of long-distance information dependence in long literature. Joint extraction of entity and relation model incorporates a variety of advanced deep learning techniques in this paper: (i) a fine-tuning BERT text classification pre-training model, (ii) Graph Convolutional Network learning method, (iii) Robust Learning Against Textual Label Noise with Self-Mixup Training, (iv) Local regularization Conditional Random Fields. The model implements the following functions: identifying entities from complex biomedical literature effectively, extracting triples within and across sentences, reducing the effect of noisy data during training, and improving the robustness and accuracy of the model. The experiment results prove that the model performs well on the self-built BM_GBD dataset and public datasets, enabling precise large language model enhanced knowledge graph construction for biomedical tasks., Availability and Implementation: The model and partial code are available on GitHub at https://github.com/zhaix922/Joint-extraction-of-entity-and-relation., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press.)

The CBL (Casitas B-lineage lymphoma) family, as a class of ubiquitin ligases, can regulate signal transduction and activate receptor tyrosine kinases through various tyrosine kinase-dependent pathways. There are three members of the family: c-CBL, CBL-b, and CBL-c. Numerous studies have demonstrated the important role of CBL in various cellular pathways, particularly those involved in the occurrence and progression of cancer, hematopoietic development, and regulation of T cell receptors. Therefore, the purpose of this review is to comprehensively summarize the function and regulatory role of CBL family proteins in different human tumors, as well as the progress of drug research targeting CBL family, so as to provide a broader clinical measurement strategy for the treatment of tumors., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Ren, Lv, Tao, Zhai, Chen, Yu, Zhao, Kong, Yu, Dong and Liu.)

Ubiquitination of the proteins is crucial for governing protein degradation and regulating fundamental cellular processes. Deubiquitinases (DUBs) have emerged as significant regulators of multiple pathways associated with cancer and other diseases, owing to their capacity to remove ubiquitin from target substrates and modulate signaling. Consequently, they represent potential therapeutic targets for cancer and other life-threatening conditions. USP43 belongs to the DUBs family involved in cancer development and progression. This review aims to provide a comprehensive overview of the existing scientific evidence implicating USP43 in cancer development. Additionally, it will investigate potential small-molecule inhibitors that target DUBs that may have the capability to function as anti-cancer medicines.

Single-component and competitive adsorption of tetracycline (TC) and Zn(ii) on an NH 4 Cl-induced magnetic ultra-fine buckwheat peel powder biochar (NH 4 Cl-BHP-char/Fe 3 O 4 ) was investigated in batch experiments. NH 4 Cl-BHP-char/Fe 3 O 4 exhibited a large surface area of 1119.097 m 2 g -1 and a total pore volume of 0.139 cm 3 g -1 and was easily separated from aqueous solution using a magnet. Also, adsorption was endothermic, spontaneous, and highly pH-dependent. The optimum pH of the single-component adsorption of TC and Zn(ii) was 4.0 and 6.5, respectively, and the optimum pH of co-adsorption was 6.0. The kinetics studies showed the prepared biochar could be rapidly adsorbed within 60 min, and chemical adsorption was dominant. For single-component adsorption, the maximum adsorption capacities of TC and Zn(ii) were 106.38 and 151.52 mg g -1 , respectively, and they underwent monolayer adsorption on the biochar surface. Moreover, for competitive adsorption, maximum TC and Zn(ii) adsorption capacities of 126.58 and 357.14 mg g -1 were achieved. Both film diffusion and intra-particle diffusion were found to be significant processes to facilitate adsorption. TC and Zn(ii) promoted the adsorption of each other. The proposed biochar could be used repeatedly for at least four cycles. All these results demonstrated that developed NH 4 Cl-BHP-char/Fe 3 O 4 was regarded as a low-cost alternative adsorbent to remove the heavy metal ions and antibiotic pollutants from water or wastewater., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)