🧬 biology

Influence of Visual and Chemical Cues on nest and bower-building behaviours of Coptodon rendalli (Boulenger, 1905) and Ooreochromis shiranus (Boulenger, 1905) in Fibre tanks

This study demonstrates that both visual and chemical cues significantly influence the nest- and bower-building behaviors of *Coptodon rendalli* and *Oreochromis shiranus*, with optimal structure dimensions observed when males and females are separated by a fine net and when water contains specific levels of soil substrate-treated cues, providing valuable insights for improving hatchery breeding conditions.

Luckson Solicitor Maurice Gondwe2026-07-07
🧬 biology

Apparent 3D-structural variant-effect signal is explained by variant category, not structure: a category-matched evaluation across nine disease loci

This study demonstrates that the apparent predictive power of a 3D chromatin structural-disruption score (ARCHCODE) for pathogenicity is largely an artifact of variant category rather than genuine structural information, as its performance collapses to chance levels when evaluated using category-matched controls, unlike established predictors such as CADD and phyloP.

Sergey Boiko2026-07-07
🧬 biology

Multi-omics integration provides insights into the symbiotic evolution of the mycoheterotrophic medicinal orchid Gastrodia elata

This study presents a chromosome-level genome assembly and pan-gene analysis of the mycoheterotrophic orchid *Gastrodia elata*, revealing extensive degeneration of photosynthetic genes, the absence of fungal-derived horizontal gene transfer despite long-term symbiosis, and the identification of specific metabolic adaptations and the expanded GAFP gene family as key mechanisms for nutrient acquisition and symbiotic homeostasis.

Yiyong Zhao, Mingjin Huang, Shanshan Luo, Linshuang Tang, Hao Yin, Daliang Liu, Zhipeng Li, Qiyu Chen, Yinjie Jiao, Meng (…)2026-07-07
🧬 biology

Reliable but Wrong? Automated Detection of Heart Rate Artifacts as a Source of Bias in Pediatric EEG Data

This study demonstrates that the widely used ICLABEL algorithm, trained primarily on adult EEG, fails to detect cardiac artifacts in pediatric data, leading to significant biases in power estimates and spurious treatment effects, thereby highlighting the critical need for supervised validation when applying automated tools to pediatric populations.

Brenna Arledge, Tori Hollen, Akhila K. Nekkanti, Elizabeth A. Skowron, Lauren E. Ethridge, David E. Bard2026-07-07