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"Lu, Dan"
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Autonomous assembly : designing for a new era of collective construction
\"We are now on the brink of a new era in construction - that of autonomous assembly. For some time, the widespread adoption of robotic and digital fabrication technologies has made it possible for architects and academic researchers to design non-standard, highly customised structures. These technologies have largely been limited by scalability, focusing mainly on top-down, bespoke fabrication projects, such as experimental pavilions and structures. Autonomous assembly and bottom-up construction techniques hold the promise of greater scalability, adaptability and potentially evolved design possibilities. By capitalising on the advances made in swarm robotics, the collective construction of the animal/insect kingdom, and advances in physical computational, programmable materials or self-assembly, architects and designers are now able to build from the bottom up. This issue presents future scenarios of autonomous assembly by highlighting the viability of decentralised, collective assembly systems, demonstrating the potential to deliver reconfigurable and adaptive solutions.\"--Back cover.
Book
Nrf2 protects against seawater drowning-induced acute lung injury via inhibiting ferroptosis
Background
Ferroptosis is a new type of nonapoptotic cell death model that was closely related to reactive oxygen species (ROS) accumulation. Seawater drowning-induced acute lung injury (ALI) which is caused by severe oxidative stress injury, has been a major cause of accidental death worldwide. The latest evidences indicate nuclear factor (erythroid-derived 2)-like 2 (Nrf2) suppress ferroptosis and maintain cellular redox balance. Here, we test the hypothesis that activation of Nrf2 pathway attenuates seawater drowning-induced ALI via inhibiting ferroptosis.
Methods
we performed studies using Nrf2-specific agonist (dimethyl fumarate), Nrf2 inhibitor (ML385), Nrf2-knockout mice and ferroptosis inhibitor (Ferrostatin-1) to investigate the potential roles of Nrf2 on seawater drowning-induced ALI and the underlying mechanisms.
Results
Our data shows that Nrf2 activator dimethyl fumarate could increase cell viability, reduced the levels of intracellular ROS and lipid ROS, prevented glutathione depletion and lipid peroxide accumulation, increased
FTH1
and
GPX4
mRNA expression, and maintained mitochondrial membrane potential in MLE-12 cells. However, ML385 promoted cell death and lipid ROS production in MLE-12 cells. Furthermore, the lung injury became more aggravated in the Nrf2-knockout mice than that in WT mice after seawater drowning.
Conclusions
These results suggested that Nrf2 can inhibit ferroptosis and therefore alleviate ALI induced by seawater drowning. The effectiveness of ferroptosis inhibition by Nrf2 provides a novel therapeutic target for seawater drowning-induced ALI.
Journal Article
Machine learning assisted hybrid models can improve streamflow simulation in diverse catchments across the conterminous US
Incomplete representations of physical processes often lead to structural errors in process-based (PB) hydrologic models. Machine learning (ML) algorithms can reduce streamflow modeling errors but do not enforce physical consistency. As a result, ML algorithms may be unreliable if used to provide future hydroclimate projections where climates and land use patterns are outside the range of training data. Here we test hybrid models built by integrating PB model outputs with an ML algorithm known as long short-term memory (LSTM) network on their ability to simulate streamflow in 531 catchments representing diverse conditions across the Conterminous United States. Model performance of hybrid models as measured by Nash-Sutcliffe efficiency (NSE) improved relative to standalone PB and LSTM models. More importantly, hybrid models provide highest improvement in catchments where PB models fail completely (i.e. NSE < 0). However, all models performed poorly in catchments with extended low flow periods, suggesting need for additional research.
Journal Article
Research Progress on NK Cell Receptors and Their Signaling Pathways
Natural killer cells (NK cells) play an important role in innate immunity. NK cells recognize self and nonself depending on the balance of activating receptors and inhibitory receptors. After binding to their ligands, NK cell receptors trigger subsequent signaling conduction and then determine whether NK is activated or inhibited. Furthermore, NK cell response includes cytotoxicity and cytokine release, which is tightly related to the activation of NK cell-activating receptors and the inhibition of inhibitory receptors on the surfaces of NK cells. The expression and function of NK cell surface receptors also alter in virus infection, tumor, and autoimmune diseases and influence the occurrence and development of diseases. So, it is important to understand the mechanism of recognition between NK receptors and their ligands in pathological conditions and the signaling pathways of NK cell receptors. This review mainly summarizes the research progress on NK cell surface receptors and their signal pathways.
Journal Article
Raw biomass electroreforming coupled to green hydrogen generation
Despite the tremendous progress of coupling organic electrooxidation with hydrogen generation in a hybrid electrolysis, electroreforming of raw biomass coupled to green hydrogen generation has not been reported yet due to the rigid polymeric structures of raw biomass. Herein, we electrooxidize the most abundant natural amino biopolymer chitin to acetate with over 90% yield in hybrid electrolysis. The overall energy consumption of electrolysis can be reduced by 15% due to the thermodynamically and kinetically more favorable chitin oxidation over water oxidation. In obvious contrast to small organics as the anodic reactant, the abundance of chitin endows the new oxidation reaction excellent scalability. A solar-driven electroreforming of chitin and chitin-containing shrimp shell waste is coupled to safe green hydrogen production thanks to the liquid anodic product and suppression of oxygen evolution. Our work thus demonstrates a scalable and safe process for resource upcycling and green hydrogen production for a sustainable energy future.
The scale-up of the coupling of water electroreduction (HER) with organic electrooxidation remains challenging. Here the authors address this challenge by coupling HER with electrooxidation of raw biomass chitin, cogenerating acetate and green hydrogen safely at high current density.
Journal Article
Community detection combining topology and attribute information
Community structures detection is critical in the analysis of features and functions of complex networks. Traditional methods are mostly concerned with the topology information of networks when conducting community detection, and can only describe the community structures from one aspect. For a more comprehensive analysis of the network, there is often attribute information available and it is a good complement to topology information. In this paper, we propose two parameter-free models based on nonnegative matrix factorization (NMF for short), Topology and Attribute NMF (TANMF for short) and Topology and Attribute Symmetrical NMF (TASNMF for short), combining topology information and attribute information for community structures detection. In addition, the multiplicative update rules are designed and the convergence is proved. Systematic experiments on both the synthetic and the real networks demonstrate the effectiveness and efficiency of our methods.
Journal Article
Phospholipase iPLA2β averts ferroptosis by eliminating a redox lipid death signal
Ferroptosis, triggered by discoordination of iron, thiols and lipids, leads to the accumulation of 15-hydroperoxy (Hp)-arachidonoyl-phosphatidylethanolamine (15-HpETE-PE), generated by complexes of 15-lipoxygenase (15-LOX) and a scaffold protein, phosphatidylethanolamine (PE)-binding protein (PEBP)1. As the Ca
2+
-independent phospholipase A
2
β (iPLA
2
β,
PLA2G6
or
PNPLA9
gene) can preferentially hydrolyze peroxidized phospholipids, it may eliminate the ferroptotic 15-HpETE-PE death signal. Here, we demonstrate that by hydrolyzing 15-HpETE-PE, iPLA
2
β averts ferroptosis, whereas its genetic or pharmacological inactivation sensitizes cells to ferroptosis. Given that
PLA2G6
mutations relate to neurodegeneration, we examined fibroblasts from a patient with a Parkinson’s disease (PD)-associated mutation (fPD
R747W
) and found selectively decreased 15-HpETE-PE-hydrolyzing activity, 15-HpETE-PE accumulation and elevated sensitivity to ferroptosis. CRISPR-Cas9-engineered
Pnpla9
R748W/R748W
mice exhibited progressive parkinsonian motor deficits and 15-HpETE-PE accumulation. Elevated 15-HpETE-PE levels were also detected in midbrains of rotenone-infused parkinsonian rats and α-synuclein-mutant
Snca
A53T
mice, with decreased iPLA
2
β expression and a PD-relevant phenotype. Thus, iPLA
2
β is a new ferroptosis regulator, and its mutations may be implicated in PD pathogenesis.
Ca
2+
-independent phospholipase A
2
β cleaves an oxidized form of phosphatidylethanolamine (PE) involved in ferroptosis such that increases in PE sensitize cells to ferroptosis. A mutant allele of the enzyme links neurodegeneration and ferroptosis.
Journal Article
Application of ALSO course in standardized training Resident in Obstetric
Objective
To explore the teaching effect of Advanced Life Support in Obstetrics (ALSO) Course in the standardized training resident in obstetric.
Methods
60 residents of obstetrics from January 2021 to December 2022 were randomly divided into two groups, observation group and control group. The experimental group used ALSO teaching method, and the control group used traditional teaching method. The teaching effect was evaluated by theoretical examination, direct observation of procedural skills (DOPS) scale and mini clinical evaluation (Mini-CEX) scale.
Results
The theoretical achievements of the observation group were significantly higher than that of the control group (
P
< 0.05). The pre-procedural preparation, safe analgesia, technique of procedure, aseptic technique, seeks help when necessary, post-procedural management, communication skills, humanistic care and overall performance score of the DOPS in the experimental group were higher than those in the control group (
P
< 0.05). The organization efficiency, humanistic qualities, manipulative skills, clinical judgment, medical interviewing skills and overall clinical competence score of the Mini-CEX in the experimental group were higher than those in the control group (
P
< 0.05).
Conclusions
ALSO teaching method has an ideal effect in the standardization training of residents of obstetrics, indicating the prospect of active in-depth research and expanded application.
Journal Article
Magnesium Deficiency Triggers SGR–Mediated Chlorophyll Degradation for Magnesium Remobilization
Magnesium (Mg) is a relatively mobile element that is remobilized in plants under Mg-limited conditions through transport from old to young tissues. However, the physiological and molecular mechanisms underlying Mg remobilization in plants remain poorly understood. In this study, we investigated Mg remobilization in rice (Oryza sativa) as facilitated through a Mg dechelatase gene involved in chlorophyll degradation, STAY-GREEN (OsSGR). We first observed that mid-aged leaves of rice are more susceptible to Mg deficiency. Expression of OsSGR was specifically upregulated by Mg deficiency, and the response was more pronounced in mid-aged leaves. Knockout of OsSGR exhibited the stay-green phenotype, which hindered the mobility of Mg from mid-aged leaves to young developing leaves. This decline in Mg mobility was associated with inhibited growth of developing leaves in mutants under Mg-limited conditions. Furthermore, Mg deficiency enhanced reactive oxygen species (ROS) generation in mid-aged leaves. ROS levels, particularly hydrogen peroxide, in turn, positively regulated OsSGR expression, probably through chloroplast-to-nucleus signaling, which triggers chlorophyll degradation to protect mid-aged leaves from photodamage. Taken together, these results show that OsSGR-mediated chlorophyll degradation contributes to not only internal remobilization of Mg from mid-aged leaves to developing leaves, but also photooxidative protection of mid-aged leaves under Mg-limited conditions. ROS appear to act as feedback regulators of OsSGR expression to precisely govern chlorophyll degradation in mid-aged leaves where Mg and photosynthetic capacities are relatively high.
Journal Article
Streamflow Simulation in Data-Scarce Basins Using Bayesian and Physics-Informed Machine Learning Models
Hydrologic predictions at rural watersheds are important but also challenging due to data shortage. Long short-term memory (LSTM) networks are a promising machine learning approach and have demonstrated good performance in streamflow predictions. However, due to its data-hungry nature, most LSTM applications focus on well-monitored catchments with abundant and high-quality observations. In this work, we investigate predictive capabilities of LSTM in poorly monitored watersheds with short observation records. To address three main challenges of LSTM applications in data-scarce locations, i.e., overfitting, uncertainty quantification (UQ), and out-of-distribution prediction, we evaluate different regularization techniques to prevent overfitting, apply a Bayesian LSTM for UQ, and introduce a physics-informed hybrid LSTM to enhance out-of-distribution prediction. Through case studies in two diverse sets of catchments with and without snow influence, we demonstrate that 1) when hydrologic variability in the prediction period is similar to the calibration period, LSTM models can reasonably predict daily streamflow with Nash–Sutcliffe efficiency above 0.8, even with only 2 years of calibration data; 2) when the hydrologic variability in the prediction and calibration periods is dramatically different, LSTM alone does not predict well, but the hybrid model can improve the out-of-distribution prediction with acceptable generalization accuracy; 3) L2 norm penalty and dropout can mitigate overfitting, and Bayesian and hybrid LSTM have no overfitting; and 4) Bayesian LSTM provides useful uncertainty information to improve prediction understanding and credibility. These insights have vital implications for streamflow simulation in watersheds where data quality and availability are a critical issue.
Journal Article