Biology subjects

Zha, R.

Publications and source records attributed to Zha, R..

4 recordsLinked to original sources

bioRxiv2026

Combining 3D-multispectral and hyperspectral imaging to identify environmental stress treatments imposed during plant growth

Non-invasive, high-throughput phenotyping tools are needed that can identify environmental effects on plant structure and function to diagnose factors responsible for reduced growth in commercial and non-commercial settings. In this study, we explored whether the integration of 3D-multispectral (3D) and 2D-hyperspectral imaging (HSI), aided by machine learning (ML), could be used to identify environmental stress treatments imposed during plant growth. Controlled environment-grown Nicotiana Benthamiana plants were subjected to a range of abiotic treatments - including different growth irradiances, heat treatment and drought stress - with the treatments resulting in differences in shoot height, biomass, leaf area and spectral reflectance. ML models were trained to identify these treatments using morphological and spectral traits measured at 27, 29, 31, and 34 days after sowing (DAS). A 3D-multispectral scanner was used to obtain information on plant height, biomass, and leaf area. A visible and near-infrared (VNIR) HSI camera provided detailed spectral information for deriving spectral indices including the Normalised Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI) and Normalized Difference Red Edge (NDRE). Manual measurements provided baseline comparative data. The 3D-multispectral scanner reliably estimated above-ground traits, with high correlations between manual and scanner-derived measurements. The ML models accurately differentiated among environmental stress treatments, with the fused 3D+HSI model achieving the best overall predictive performance across all evaluated metrics compared with models based on either imaging modality alone. Results demonstrated the effectiveness of combining 3D-multispectral and 2D-HSI data with ML analyses for non-destructive, high-throughput phenotyping. The integration of these techniques enabled non-destructive, high-throughput identification of environmental stress treatments imposed during plant growth.

plant biology↗

bioRxiv2026

A lateral linker histone binding mode scaffolds dinucleosome stacking in chromatin fibers

Linker histones are essential for chromatin compaction, yet how they contribute to higher-order fiber assembly remains poorly understood. Here, we determined cryo-electron microscopy structures of Arabidopsis dodeca-nucleosome fibers containing distinct H2A/H3 variants and linker histone H1.3, revealing a noncanonical binding mode that a laterally positioned H1.3 connects the acidic patch of one nucleosome and the DNA of the neighboring nucleosome, thereby scaffolding dinucleosomes into two-start chromatin fibers. This noncanonical binding mode is structurally conserved when H1.3 is replaced by Gallus gallus H5. Furthermore, incorporation of H2A.W and H3.3 further induces back-to-back fiber dimerization. Cryo-electron tomography and in vivo cross-linking mass spectrometry analyses support the physiological relevance of H1 lateral engagement. Our findings establish that linker histones act as active architectural scaffolds in higher-order chromatin organization.

molecular biology↗

bioRxiv2021

Humanoid robots are perceived as an evolutionary threat

Studying how we perceive humanoid robots will provide insights for a deeper understanding of human-robot interaction. Our ideas about humanoid robots are mainly informed by science fiction, and humanoid robots are generally described as an evolutionary threat in science fiction that has not been tested. The preparedness model has emphasized that the fear module is automatically activated by evolutionary threats, and its underlying neural circuit is centered on the amygdala. We hypothesized that if humanoid robots are perceived as an evolutionary threat even though humanoid robots are manmade, modern objects, we would expect to observe a monocular advantage for humanoid robots and an amygdala response to unconsciously presented humanoid robots that were previously only evident in evolutionary threats. Here, we observed a monocular advantage for the perception of humanoid robots the same as an evolutionary threat (i.e., snakes). Our neuroimaging analysis indicated that unconscious presentation of humanoid robot vs. human images led to significant amygdala activation. Despite a positive humanoid robot-related association had been established by associative learning (as evidenced by results of successfully weakening the negative implicit attitude to humanoid robots and enhancing functional connectivity between the amygdala and hippocampus), the amygdala could still automatically and quickly detect humanoid robots. Our results reveal that processing of information about humanoid robots displays automaticity with regard to recruitment of visual pathway and amygdala activation. Our findings that humans apparently perceive humanoid robots as an evolutionary threat may help inform redefinition of human-robot interaction and robot ethics.

neuroscience↗

bioRxiv2020

Impulsivity and Thought Suppression in Behavioral Addiction: Associated Neural Connectivity and Neural Networks

Impulsivity and thought suppression are two psychological traits that have great variation in healthy population. In extreme cases, both are closely related to mental illness and play an important role in behavioral addiction. We have known the role of the top-down mechanism in impulsivity and thought suppression, but we do not know how the related neural nuclei are functionally connected and interact with each other. In the study, we selected excessive internet users (EIU) as our target population and investigated the relationship between thought suppression and impulsivity in the following aspects: their correlations to psychological symptoms; the associated neural networks; and the associated brain morphometric changes. We acquired data from 131 excessive internet users, with their psychological, resting-state fMRI and T1-MRI data collected. With the whole brain analysis, graph theory analysis, replication with additional brain atlas, replication with additional MRI data, and analysis of brain structure, we found that: (i) implusivity and thought suppression shared common neural connections in the top-down mechanism; (ii) thought suppression was associated with the neural network that connected to the occipital lobe in the resting-state brain but not the morphometric change of the occipital lobe. The study confirmed the overlap between impulsivity and thought suppression in terms of neural connectivity and suggested the role of thought suppression and the occipital network in behavioral addiction. Studying thought suppression provided a new insight into behavioral addiction research. The neural network study helped further understanding of behavioral addiction in terms of information interaction in the brain.

neuroscience↗