Relationships between xylem embolism and tree functioning during drought, recovery, and recurring drought in Aleppo pine

Recent findings suggest that trees can survive high levels of drought-induced xylem embolism. In many cases, the embolism is irreversible and, therefore, can potentially affect post-drought recovery and tree function under recurring droughts. We examined the development of embolism in potted Aleppo pines, a common species in hot, dry Mediterranean habitats. We asked (1) how post-drought recovery is affected by different levels of embolism and (2) what consequences this drought-induced damage has under a recurring drought scenario. Young trees were dehydrated to target water potential (Ψx) values of −3.5, −5.2 and −9.5 MPa (which corresponded to ~6%, ~41% and ~76% embolism), and recovery of the surviving trees was measured over an 8-months period (i.e., embolism, leaf gas-exchange, Ψx). An additional group of trees was exposed to Ψx of −6.0 MPa, either with or without preceding drought (Ψx of −5.2 MPa) to test the effect of hydraulic damage during repeated drought. Trees that reached −9.5 MPa died, but none from the other groups. Embolism levels in dying trees were on average 76% of conductive xylem and no tree was dying below 62% embolism. Stomatal recovery was negatively proportional to the level of hydraulic damage sustained during drought, for at least a month after drought relief. Trees that experienced drought for the second time took longer to reach fatal Ψx levels than first-time dehydrating trees. Decreased stomatal conductance following drought can be seen as “drought legacy,” impeding recovery of tree functioning, but also as a safety mechanism during a consecutive drought

Physics-Guided Inverse Regression for Crop Quality Assessment

We present an innovative approach leveraging Physics-Guided Neural Networks (PGNNs) for enhancing agricultural quality assessments. Central to our methodology is the application of physics-guided inverse regression, a technique that significantly improves the model's ability to precisely predict quality metrics of crops. This approach directly addresses the challenges of scalability, speed, and practicality that traditional assessment methods face. By integrating physical principles, notably Fick`s second law of diffusion, into neural network architectures, our developed PGNN model achieves a notable advancement in enhancing both the interpretability and accuracy of assessments. Empirical validation conducted on cucumbers and mushrooms demonstrates the superior capability of our model in outperforming conventional computer vision techniques in postharvest quality evaluation. This underscores our contribution as a scalable and efficient solution to the pressing demands of global food supply challenges

Toward Transformable Photonics: Reversible Deforming Soft Cavities, Controlling Their Resonance Split and Directional Emission

We report on reversible and continuously deformable soft micro-resonators and the control of their resonance split and directional emission. Assisted by computerized holographic-tweezers, functioning as an optical deformer of our device, we gradually deform the shape and change the functionality of a droplet whispering-gallery cavity. For example, we continuously deform hexagonal cavities to rectangular ones and demonstrate switching to directionally emitting mode-of-operation, or splitting a resonant mode to a 10-GHz separated doublet. A continuous trend of improving spatial light modulators and tweezers suggests that our method is scalable and can control the shape and functionality of many individual devices. We also demonstrate optional solidification, proving the feasibility of transformer-enabled applications, including in printing optical circuits and multiwavelength optical networks

NAF-1 and mitoNEET are central to human breast cancer proliferation by maintaining mitochondrial homeostasis and promoting tumor growth

Mitochondria are emerging as important players in the transformation process of cells, maintaining the biosynthetic and energetic capacities of cancer cells and serving as one of the primary sites of apoptosis and autophagy regulation. Although several avenues of cancer therapy have focused on mitochondria, progress in developing mitochondria-targeting anticancer drugs nonetheless has been slow, owing to the limited number of known mitochondrial target proteins that link metabolism with autophagy or cell death. Recent studies have demonstrated that two members of the newly discovered family of NEET proteins, NAF-1 (CISD2) and mitoNEET (mNT; CISD1), could play such a role in cancer cells. NAF-1 was shown to be a key player in regulating autophagy, and mNT was proposed to mediate iron and reactive oxygen homeostasis in mitochondria. Here we show that the protein levels of NAF-1 and mNT are elevated in human epithelial breast cancer cells, and that suppressing the level of these proteins using shRNA results in significantly reduced cell proliferation and tumor growth, decreased mitochondrial performance, uncontrolled accumulation of iron and reactive oxygen in mitochondria, and activation of autophagy. Our findings highlight NEET proteins as promising mitochondrial targets for cancer therapy

Stomatal optimisation based on xylem hydraulics (SOX) improves land surface model simulation of vegetation responses to climate

This is the final version. Available on open access via the DOI in this record•Land surface models (LSMs) typically use empirical functions to represent vegetation responses to soil drought. These functions largely neglect recent advances in plant ecophysiology that link xylem hydraulic functioning with stomatal responses to climate. •We developed an analytical stomatal optimisation model based on xylem hydraulics (SOX) to predict plant responses to drought. Coupling SOX to the Joint UK Land Environment Simulator (JULES) LSM, we conducted a global evaluation of SOX against leaf- and ecosystem-level observations. •SOX simulates leaf stomatal conductance responses to climate for woody plants more accurately and parsimoniously than the existing JULES stomatal conductance model. An ecosystem-level evaluation at 70 eddy flux sites shows that SOX decreases the sensitivity of gross primary productivity (GPP) to soil moisture, which improves the model agreement with observations and increases the predicted annual GPP by 30% in relation to JULES. SOX decreases JULES root mean squared error in GPP by up to 45 % in evergreen tropical forests, and can simulate realistic patterns of canopy water potential and soil water dynamics at the studied sites. •SOX provides a parsimonious way to incorporate recent advances in plant hydraulics and optimality theory into LSMs, and an alternative to empirical stress factors.Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil)Natural Environment Research Council (NERC

Effect of SARS-CoV-2 proteins on vascular permeability.

Severe acute respiratory syndrome (SARS)-CoV-2 infection leads to severe disease associated with cytokine storm, vascular dysfunction, coagulation, and progressive lung damage. It affects several vital organs, seemingly through a pathological effect on endothelial cells. The SARS-CoV-2 genome encodes 29 proteins, whose contribution to the disease manifestations, and especially endothelial complications, is unknown. We cloned and expressed 26 of these proteins in human cells and characterized the endothelial response to overexpression of each, individually. Whereas most proteins induced significant changes in endothelial permeability, nsp2, nsp5_c145a (catalytic dead mutant of nsp5), and nsp7 also reduced CD31, and increased von Willebrand factor expression and IL-6, suggesting endothelial dysfunction. Using propagation-based analysis of a protein–protein interaction (PPI) network, we predicted the endothelial proteins affected by the viral proteins that potentially mediate these effects. We further applied our PPI model to identify the role of each SARS-CoV-2 protein in other tissues affected by coronavirus disease (COVID-19). While vali-dating the PPI network model, we found that the tight junction (TJ) proteins cadherin-5, ZO-1, and β-catenin are affected by nsp2, nsp5_c145a, and nsp7 consistent with the model prediction. Overall, this work identifies the SARS-CoV-2 proteins that might be most detrimental in terms of endothelial dysfunction, thereby shedding light on vascular aspects of COVID-1