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Key message: Eight selected hotspots related to ear traits were identified from two maize–teosinte populations. Throughout the history of maize cultivation, ear-related traits have been selected. However, little is known about the specific genes involved in shaping these traits from their origins in the wild progenitor, teosinte, to the characteristics observed in modern maize. In this study, five ear traits (kernel row number [KRN], ear length [EL], kernel number per row [KNR], cob diameter [CD], and ear diameter [ED]) were investigated, and eight quantitative trait loci (QTL) hotspots were identified in two maize–teosinte populations. Notably, our findings revealed a significant enrichment of genes showing a selection signature and expressed in the ear in qbdCD1.1, qbdCD5.1, qbpCD2.1, qbdED1.1, qbpEL1.1, qbpEL5.1, qbdKNR1.1, and qbdKNR10.1, suggesting that these eight QTL are selected hotspots involved in shaping the maize ear. By combining the results of the QTL analysis with data from previous genome-wide association study (GWAS) involving two natural panels, we identified eight candidate selected genes related to KRN, KNR, CD, and ED. Among these, considering their expression pattern and sequence variation, Zm00001d025111, encoding a WD40/YVTN protein, was proposed as a positive regulator of KNR. This study presents a framework for understanding the genomic distribution of selected loci crucial in determining ear-related traits. [ABSTRACT FROM AUTHOR]

Aims: To explore large‐scale brain network alterations and examine their clinical and neuropsychological relevance in patients with anti‐N‐methyl‐D‐aspartate receptor (NMDAR) encephalitis. Methods: Twenty‐four patients with anti‐NMDAR encephalitis and 26 matched healthy controls (HCs) were enrolled in our study. Based on the multimodal MRI dataset, individual morphological, structural, and functional brain networks were constructed and compared between the two groups at multiple levels. The associations with clinical/neuropsychological variables and the discriminant ability of significant alterations were further studied. Results: Multimodal network analysis revealed that anti‐NMDAR encephalitis mainly affected morphological and structural networks, but subtle alterations were observed in functional networks. Intriguingly, decreased network local efficiency was observed for both morphological and structural networks and increased nodal centrality in the lateral orbital gyrus was convergently observed among the three types of networks in the patients. Moreover, the alterations, particularly those from structural networks, accounted largely for cognitive deficits of the patients and could distinguish the diseased individuals from the HCs with excellent performance (area under the curve =0.933). Conclusions: The current study provides a comprehensive view of characteristic multimodal network dysfunction in anti‐NMDAR encephalitis, which is crucial to establish new diagnostic biomarkers and promising therapeutic targets for the disease. [ABSTRACT FROM AUTHOR]