DEFECTIVE KERNEL1 regulates cellulose synthesis and affects primary cell wall mechanics

The cell wall is one of the defining features of plants, controlling cell shape, regulating growth dynamics and hydraulic conductivity, as well as mediating plants interactions with both the external and internal environments. Here we report that a putative mechanosensitive Cys-protease DEFECTIVE KERNEL1 (DEK1) influences the mechanical properties of primary cell walls and regulation of cellulose synthesis. Our results indicate that DEK1 is an important regulator of cellulose synthesis in epidermal tissue of Arabidopsis thaliana cotyledons during early post-embryonic development. DEK1 is involved in regulation of cellulose synthase complexes (CSCs) by modifying their biosynthetic properties, possibly through interactions with various cellulose synthase regulatory proteins. Mechanical properties of the primary cell wall are altered in DEK1 modulated lines with DEK1 affecting both cell wall stiffness and the thickness of the cellulose microfibril bundles in epidermal cell walls of cotyledons

On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving

The pursuit of autonomous driving technology hinges on the sophisticated integration of perception, decision-making, and control systems. Traditional approaches, both data-driven and rule-based, have been hindered by their inability to grasp the nuance of complex driving environments and the intentions of other road users. This has been a significant bottleneck, particularly in the development of common sense reasoning and nuanced scene understanding necessary for safe and reliable autonomous driving. The advent of Visual Language Models (VLM) represents a novel frontier in realizing fully autonomous vehicle driving. This report provides an exhaustive evaluation of the latest state-of-the-art VLM, GPT-4V(ision), and its application in autonomous driving scenarios. We explore the model's abilities to understand and reason about driving scenes, make decisions, and ultimately act in the capacity of a driver. Our comprehensive tests span from basic scene recognition to complex causal reasoning and real-time decision-making under varying conditions. Our findings reveal that GPT-4V demonstrates superior performance in scene understanding and causal reasoning compared to existing autonomous systems. It showcases the potential to handle out-of-distribution scenarios, recognize intentions, and make informed decisions in real driving contexts. However, challenges remain, particularly in direction discernment, traffic light recognition, vision grounding, and spatial reasoning tasks. These limitations underscore the need for further research and development. Project is now available on GitHub for interested parties to access and utilize: \url{https://github.com/PJLab-ADG/GPT4V-AD-Exploration

Comorbid depressive symptoms can aggravate the functional changes of the pain matrix in patients with chronic back pain: A resting-state fMRI study

ObjectiveThe purposes of this study are to explore (1) whether comorbid depressive symptoms in patients with chronic back pain (CBP) affect the pain matrix. And (2) whether the interaction of depression and CBP exacerbates impaired brain function.MethodsThirty-two patients with CBP without comorbid depressive symptoms and thirty patients with CBP with comorbid depressive symptoms were recruited. All subjects underwent functional magnetic resonance imaging (fMRI) scans. The graph theory analysis, mediation analysis, and functional connectivity (FC) analysis were included in this study. All subjects received the detection of clinical depressive symptoms and pain-related manifestations.ResultCompared with the CBP group, subjects in the CBP with comorbid depressive symptoms (CBP-D) group had significantly increased FC in the left medial prefrontal cortex and several parietal cortical regions. The results of the graph theory analyses showed that the area under the curve of small-world property (t = −2.175, p = 0.034), gamma (t = −2.332, p = 0.023), and local efficiency (t = −2.461, p = 0.017) in the CBP-D group were significantly lower. The nodal efficiency in the ventral posterior insula (VPI) (t = −3.581, p = 0.0007), and the network efficiency values (t = −2.758, p = 0.008) in the pain matrix were significantly lower in the CBP-D group. Both the topological properties and the FC values of these brain regions were significantly correlated with self-rating depression scale (SDS) scores (all FDR corrected) but not with pain intensity. Further mediation analyses demonstrated that pain intensity had a mediating effect on the relationship between SDS scores and Pain Disability Index scores. Likewise, the SDS scores mediated the relationship between pain intensity and PDI scores.ConclusionOur study found that comorbid depressive symptoms can aggravate the impairment of pain matrix function of CBP, but this impairment cannot directly lead to the increase of pain intensity, which may be because some brain regions of the pain matrix are the common neural basis of depression and CBP

Arabinogalactan proteins – Multifunctional glycoproteins of the plant cell wall

Arabinogalactan-proteins (AGPs) are cell wall glycoproteins that make up a relatively small component of the extracellular matrix of plants yet have significant influence on wall mechanics and signalling. Present in walls of algae, bryophytes and angiosperms, AGPs have a wide range of functional roles, from signalling, cell expansion and division, embryogenesis, responses to abiotic and biotic stress, plant growth and development. AGPs interact with and influence wall matrix components and plasma membrane proteins to regulate developmental pathways and growth responses, yet the exact mechanisms remain elusive. Comprising a large gene family that is highly diverse, from minimally to highly glycosylated members, varying in their glycan heterogeneity, can be plasma membrane bound or secreted into the extracellular matrix, have members that are highly tissue specific to those with constitutive expression; all these factors have made it extremely challenging to categorise AGPs many qualities and roles. Here we attempt to define some key features of AGPs and their biological functions

Remote Sensing Monitoring of Soil Salinity in Weigan River–Kuqa River Delta Oasis Based on Two-Dimensional Feature Space

Soil salinization is a serious resource and ecological problem globally. The Weigan River–Kuqa River Delta Oasis is a key region in the arid and semi-arid regions of China with prominent soil salinization. The saline soils in the oasis are widely distributed over a large area, causing great harm to agricultural development and the environment. Remote sensing monitoring can provide a reference method for the management of regional salinization. We extracted the spectral indices and performed a correlation analysis using soil measurement data and Sentinel-2 remote sensing data. Then, two-dimensional feature space inversion models for soil salinity were constructed based on the preferred spectral indices, namely, the canopy response salinity index (CRSI), composite spectral response index (COSRI), normalized difference water index (NDWI), and green atmospherically resistant vegetation index (GARI). The soil salinity in a typical saline zone in the Weigan River–Kuqa River Delta Oasis was monitored and analyzed. We found that the inversion of the CRSI-COSRI model was optimal (R2 of 0.669), followed by the CRSI-NDWI (0.656) and CRSI-GARI (0.604) models. Therefore, a model based on the CRSI-COSRI feature space can effectively extract the soil salinization information for the study area. This is of great significance to understanding the salinization situation in the Weigan River–Kuqa River Delta Oasis, enriching salinization remote sensing monitoring methods, and solving the soil salinization problem in China

Redox-dependent effects of phosphate on arsenic speciation in paddy soils

Capsule: Contrasting effects of phosphate on As speciation were observed. In suboxic soils, phosphate inhibited Fe and As reduction, but in anoxic soils, phosphate stimulated Fe and As reduction.</p

<i>WAKL8</i> Regulates Arabidopsis Stem Secondary Wall Development

Wall-associated kinases/kinase-likes (WAKs/WAKLs) are plant cell surface sensors. A variety of studies have revealed the important functions of WAKs/WAKLs in regulating cell expansion and defense in cells with primary cell walls. Less is known about their roles during the development of the secondary cell walls (SCWs) that are present in xylem vessel (XV) and interfascicular fiber (IF) cells. In this study, we used RNA-seq data to screen Arabidopsis thaliana WAKs/WAKLs members that may be involved in SCW development and identified WAKL8 as a candidate. We obtained T-DNA insertion mutants wakl8-1 (inserted at the promoter region) and wakl8-2 (inserted at the first exon) and compared the phenotypes to wild-type (WT) plants. Decreased WAKL8 transcript levels in stems were found in the wakl8-2 mutant plants, and the phenotypes observed included reduced stem length and thinner walls in XV and IFs compared with those in the WT plants. Cell wall analysis showed no significant changes in the crystalline cellulose or lignin content in mutant stems compared with those in the WT. We found that WAKL8 had alternative spliced versions predicted to have only extracellular regions, which may interfere with the function of the full-length version of WAKL8. Our results suggest WAKL8 can regulate SCW thickening in Arabidopsis stems

Understanding major NOM properties controlling its interactions with phosphorus and arsenic at goethite-water interface

Among natural organic matter (NOM), oxyanions and metal (hydr)oxides, a complicated interaction exists in natural aquatic and terrestrial systems and in waste waters. Effects of seven types of NOM (four humic acids (HA), three fulvic acids (FA)) that vary in properties on the adsorption of oxyanions, including phosphate, arsenate and arsenite, at goethite-water interface were quantitatively studied. Results show that the adsorption of oxyanions to goethite is decreased by the presence of NOM, especially for phosphate and arsenate at low pH. In general, the effects of the three FA are similar, which are more effective than HA in reducing oxyanion adsorption at low pH (<6). Differences were observed between the four HA in their competition with oxyanions. The adsorption of phosphate, arsenate and arsenite in the presence of NOM are well described with both the NOM-CD (CD: Charge Distribution) and LCD (Ligand and Charge Distribution) model. The NOM-CD model is relatively simple to use, whereas the LCD model can better reveal different factors in the interaction, including the spatial distribution of adsorbed NOM on oxide surface. According to these two models: site density of carboxylic groups, protonation constant of carboxylic groups, and particle size of NOM are major properties of NOM determining its effect on oxyanion adsorption to oxides. At relatively low loadings, morphological change of adsorbed NOM takes place, and the degree of morphological change of adsorbed NOM depends on the particle size, site density of carboxylic groups and aromaticity of NOM. The influence of particle size on the interaction becomes more important at higher NOM loadings. The results suggested that the fixation or removal efficiency of phosphate, arsenate and arsenite with iron oxides (e.g. goethite) can be significantly decreased by the presence of NOM, especially when NOM rich in acidic and aromatic groups.</p

Construction of Fusion Protein with Carbohydrate-Binding Module and Leaf-Branch Compost Cutinase to Enhance the Degradation Efficiency of Polyethylene Terephthalate

Poly(ethylene terephthalate) (PET) is a manufactured plastic broadly available, whereas improper disposal of PET waste has become a serious burden on the environment. Leaf-branch compost cutinase (LCC) is one of the most powerful and promising PET hydrolases, and its mutant LCCICCG shows high catalytic activity and excellent thermal stability. However, low binding affinity with PET has been found to dramatically limit its further industrial application. Herein, TrCBM and CfCBM were rationally selected from the CAZy database to construct fusion proteins with LCCICCG, and mechanistic studies revealed that these two domains could bind with PET favorably via polar amino acids. The optimal temperatures of LCCICCG-TrCBM and CfCBM-LCCICCG were measured to be 70 and 80 °C, respectively. Moreover, these two fusion proteins exhibited favorable thermal stability, maintaining 53.1% and 48.8% of initial activity after the incubation at 90 °C for 300 min. Compared with LCCICCG, the binding affinity of LCCICCG-TrCBM and CfCBM-LCCICCG for PET has been improved by 1.4- and 1.3-fold, respectively, and meanwhile their degradation efficiency on PET films was enhanced by 3.7% and 24.2%. Overall, this study demonstrated that the strategy of constructing fusion proteins is practical and prospective to facilitate the enzymatic PET degradation ability