PAFAH2 suppresses synchronized ferroptosis to ameliorate acute kidney injury.

Synchronized ferroptosis contributes to nephron loss in acute kidney injury (AKI). However, the propagation signals and the underlying mechanisms of the synchronized ferroptosis for renal tubular injury remain unresolved. Here we report that platelet-activating factor (PAF) and PAF-like phospholipids (PAF-LPLs) mediated synchronized ferroptosis and contributed to AKI. The emergence of PAF and PAF-LPLs in ferroptosis caused the instability of biomembranes and signaled the cell death of neighboring cells. This cascade could be suppressed by PAF-acetylhydrolase (II) (PAFAH2) or by addition of antibodies against PAF. Genetic knockout or pharmacological inhibition of PAFAH2 increased PAF production, augmented synchronized ferroptosis and exacerbated ischemia/reperfusion (I/R)-induced AKI. Notably, intravenous administration of wild-type PAFAH2 protein, but not its enzymatically inactive mutants, prevented synchronized tubular cell death, nephron loss and AKI. Our findings offer an insight into the mechanisms of synchronized ferroptosis and suggest a possibility for the preventive intervention of AKI.

14-3-3 proteins contribute to autophagy by modulating SINAT-mediated degradation of ATG13.

In multicellular eukaryotes, autophagy is a conserved process that delivers cellular components to the vacuole or lysosome for recycling during development and stress responses. Induction of autophagy activates AUTOPHAGY-RELATED PROTEIN 1 (ATG1) and ATG13 to form a protein kinase complex that initiates autophagosome formation. However, the detailed molecular mechanism underlying the regulation of this protein complex in plants remains unclear. Here, we determined that in Arabidopsis thaliana, the regulatory proteins 14-3-3λ and 14-3-3κ redundantly modulate autophagy dynamics by facilitating SEVEN IN ABSENTIA OF ARABIDOPSIS THALIANA (SINAT)-mediated proteolysis of ATG13a and ATG13b. 14-3-3λ and 14-3-3κ directly interacted with SINATs and ATG13a/b in vitro and in vivo. Compared to wild-type (WT), the 14-3-3λ 14-3-3κ double mutant showed increased tolerance to nutrient starvation, delayed leaf senescence, and enhanced starvation-induced autophagic vesicles. Moreover, 14-3-3s were required for SINAT1-mediated ubiquitination and degradation of ATG13a. Consistent with their roles in ATG degradation, the 14-3-3λ 14-3-3κ double mutant accumulated higher levels of ATG1a/b/c and ATG13a/b than the WT upon nutrient deprivation. Furthermore, the specific association of 14-3-3s with phosphorylated ATG13a was crucial for ATG13a stability and formation of the ATG1-ATG13 complex. Thus, our findings demonstrate that 14-3-3λ and 14-3-3κ function as molecular adaptors to regulate autophagy by modulating the homeostasis of phosphorylated ATG13.

Exploring the neuroprotective role of artesunate in mouse models of anti-NMDAR encephalitis: insights from molecular mechanisms and transmission electron microscopy.

BACKGROUND: The pathway involving PTEN-induced putative kinase 1 (PINK1) and PARKIN plays a crucial role in mitophagy, a process activated by artesunate (ART). We propose that patients with anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis exhibit insufficient mitophagy, and ART enhances mitophagy via the PINK1/PARKIN pathway, thereby providing neuroprotection. METHODS: Adult female mice aged 8-10 weeks were selected to create a passive transfer model of anti-NMDAR encephalitis. We conducted behavioral tests on these mice within a set timeframe. Techniques such as immunohistochemistry, immunofluorescence, and western blotting were employed to assess markers including PINK1, PARKIN, LC3B, p62, caspase3, and cleaved caspase3. The TUNEL assay was utilized to detect neuronal apoptosis, while transmission electron microscopy (TEM) was used to examine mitochondrial autophagosomes. Primary hippocampal neurons were cultured, treated, and then analyzed through immunofluorescence for mtDNA, mtROS, TMRM. RESULTS: In comparison to the control group, mitophagy levels in the experimental group were not significantly altered, yet there was a notable increase in apoptotic neurons. Furthermore, markers indicative of mitochondrial leakage and damage were found to be elevated in the experimental group compared to the control group, but these markers showed improvement following ART treatment. ART was effective in activating the PINK1/PARKIN pathway, enhancing mitophagy, and diminishing neuronal apoptosis. Behavioral assessments revealed that ART ameliorated symptoms in mice with anti-NMDAR encephalitis in the passive transfer model (PTM). The knockdown of PINK1 led to a reduction in mitophagy levels, and subsequent ART intervention did not alleviate symptoms in the anti-NMDAR encephalitis PTM mice, indicating that ART's therapeutic efficacy is mediated through the activation of the PINK1/PARKIN pathway. CONCLUSIONS: At the onset of anti-NMDAR encephalitis, mitochondrial damage is observed; however, this damage is mitigated by the activation of mitophagy via the PINK1/PARKIN pathway. This regulatory feedback mechanism facilitates the removal of damaged mitochondria, prevents neuronal apoptosis, and consequently safeguards neural tissue. ART activates the PINK1/PARKIN pathway to enhance mitophagy, thereby exerting neuroprotective effects and may achieve therapeutic goals in treating anti-NMDAR encephalitis.

Photoaged Nanopolystyrene Affects Neurotransmission to Induce Transgenerational Neurotoxicity in Caenorhabditis elegans.

Nanopolystyrene (NPS), a frequently employed nanoplastic, is an emerging environmental contaminant known to cause neurotoxicity in various organisms. However, the potential for transgenerational neurotoxic effects, especially from photoaged NPS (P-NPS), remains underexplored. This study investigated the aging of virgin NPS (V-NPS) under a xenon lamp to simulate natural sunlight exposure, which altered the physicochemical characteristics of the NPS. The parental generation (P0) of Caenorhabditis elegans was exposed to environmental concentrations (0.1-100 µg/L) of V-NPS and P-NPS, with subsequent offspring (F1-F4 generations) cultured under NPS-free conditions. Exposure to 100 µg/L P-NPS resulted in more pronounced deterioration in locomotion behavior in the P0 generation compared to V-NPS; this deterioration persisted into the F1-F2 generations but returned to normal in the F3-F4 generations. Additionally, maternal exposure to P-NPS damaged dopaminergic, glutamatergic, and serotonergic neurons in subsequent generations. Correspondingly, there was a significant decrease in the levels of dopamine, glutamate, and serotonin, associated with reduced expression of neurotransmission-related genes dat-1, eat-4, and tph-1 in the P0 and F1-F2 generations. Further analysis showed that the effects of P-NPS on locomotion behavior were absent in subsequent generations of eat-4(ad572), tph-1(mg280), and dat-1(ok157) mutants, highlighting the pivotal roles of these genes in mediating P-NPS-induced transgenerational neurotoxicity. These findings emphasize the crucial role of neurotransmission in the transgenerational effects of P-NPS on locomotion behavior, providing new insights into the environmental risks associated with exposure to photoaged nanoplastics.

Climate risk and renewable energy technological innovation: An institutional environment perspective.

To explore whether climate risk (CR) affects renewable energy technological innovation (RETI) and its boundary conditions, this study examines the relationship between CR and RETI as moderated by institutional environment. Based on panel data of 60 countries for the period 2000-2019, we show that CR is not conducive to RETI, and that its negative marginal impact shows an inverted U-shaped trend with the improvement of RETI. Heterogeneity analysis shows that floods and storms have the greatest negative impacts on RETI, and that innovations in solar and wind energy technologies are more vulnerable to the adverse shocks of CR. Furthermore, CR has a greater adverse effect on RETI in developing countries than in developed countries. However, the institutional environment, especially the economic institutional environment, can work to mitigate the negative effect of CR on RETI. Our findings not only enrich the research on the economic consequences of CR but also provide effective ways to mitigate the adverse impact of CR on RETI from the perspective of institutional environment.

How does climate change risk affect energy poverty? International evidence.

Based on cross-country data from 2002 to 2019, we explore the impact of climate change risk (CCR) on energy poverty (EP), and the moderating role in the CCR-EP nexus is also discussed. The empirical results suggest that CCR can exacerbate EP, especially for rural areas. Moderating effect analysis shows that financial development, technological innovation, and adaptation readiness can modify the negative impacts of CCR on EP to some extent. Moreover, the impact of CCR on EP is heterogeneous, demonstrating that CCR is more likely to exacerbate EP in countries with low economic development, low economic freedom, high carbon intensity, and the Africa region. Our findings emphasize the challenge of balancing EP alleviation with climate change response and provide the policy guidance to promote coordinated development of CCR management and energy supply security.

Factors affecting nurses' emergency competencies in public health emergency: A cross-sectional study based on the stress-coping adaptation model.

OBJECTIVES: To investigate the factors associated with stress, resilience, coping styles, and emergency competencies when nurses are faced with a public health emergency. DESIGN: This study used a cross-sectional design. SAMPLE: Study data came from a survey of 646 nurses who were from a tertiary hospital in Southern China in March-June 2022. METHODS: Participants responded to self-report questionnaires through a web-based survey. Stress, resilience, emergency competencies, and response to public emergencies were assessed using the Perceived Stress Scale, Connor-Davidson Resilience Scale, the core competencies of nurses in public health emergencies, and a simplified coping style questionnaire. RESULTS: A total of 646 nurses participated in this study. Slightly over half of the participants were ≤30 years old, and almost all were female. Resilience, positive coping, and negative coping were positively correlated with emergency competencies. Multiple linear regression analysis demonstrated that resilience, working years, and participation in the treatment of infectious diseases were significant predictors of emergency competencies. CONCLUSION: The findings suggest that nurses require additional training in emergency management and clinical practice to enhance their emergency competencies. More interventions and social support should be provided to improve nurses' resilience and positive coping strategies when they encounter public health emergencies.

A survey and systematic assessment of computational methods for drug response prediction.

Drug response prediction arises from both basic and clinical research of personalized therapy, as well as drug discovery for cancers. With gene expression profiles and other omics data being available for over 1000 cancer cell lines and tissues, different machine learning approaches have been applied to drug response prediction. These methods appear in a body of literature and have been evaluated on different datasets with only one or two accuracy metrics. We systematically assess 17 representative methods for drug response prediction, which have been developed in the past 5 years, on four large public datasets in nine metrics. This study provides insights and lessons for future research into drug response prediction.

Arabidopsis SINAT Proteins Control Autophagy by Mediating Ubiquitylation and Degradation of ATG13.

In eukaryotes, autophagy maintains cellular homeostasis by recycling cytoplasmic components. The autophagy-related proteins (ATGs) ATG1 and ATG13 form a protein kinase complex that regulates autophagosome formation; however, mechanisms regulating ATG1 and ATG13 remain poorly understood. Here, we show that, under different nutrient conditions, the RING-type E3 ligases SEVEN IN ABSENTIA OF ARABIDOPSIS THALIANA1 (SINAT1), SINAT2, and SINAT6 control ATG1 and ATG13 stability and autophagy dynamics by modulating ATG13 ubiquitylation in Arabidopsis (Arabidopsis thaliana). During prolonged starvation and recovery, ATG1 and ATG13 were degraded through the 26S proteasome pathway. TUMOR NECROSIS FACTOR RECEPTOR ASSOCIATED FACTOR1a (TRAF1a) and TRAF1b interacted in planta with ATG13a and ATG13b and required SINAT1 and SINAT2 to ubiquitylate and degrade ATG13s in vivo. Moreover, lysines K607 and K609 of ATG13a protein contributed to K48-linked ubiquitylation and destabilization, and suppression of autophagy. Under starvation conditions, SINAT6 competitively interacted with ATG13 and induced autophagosome biogenesis. Furthermore, under starvation conditions, ATG1 promoted TRAF1a protein stability in vivo, suggesting feedback regulation of autophagy. Consistent with ATGs functioning in autophagy, the atg1a atg1b atg1c triple knockout mutants exhibited premature leaf senescence, hypersensitivity to nutrient starvation, and reduction in TRAF1a stability. Therefore, these findings demonstrate that SINAT family proteins facilitate ATG13 ubiquitylation and stability and thus regulate autophagy.

Scientific Landscape of Oxidative Stress in Stroke: From a Bibliometric Analysis to an in-Depth Review.

Stroke is an acute cerebrovascular disease resulting from either obstruction or rupture of a blood vessel in the brain. Oxidative stress (OS), referred to a status where cellular oxidative capacities overwhelm antioxidative defenses, is involved in the pathophysiology of stroke. The bibliometric analysis and in-depth review aim to depict the research trend of OS in stroke. Relevant scientific publications were acquired from the Web of Science Core Collection database. Scientific landscape of OS in stroke was illustrated by general quantitative trend, impactful journals, and co-authorship of various academic units (i.e., countries/regions, organizations, and authors). Furthermore, theme analysis predicting the hot research issues and frontiers was performed. 15,826 documents regarding OS in stroke were obtained over a time span of more than 20 years from 1992 to 2021. The overall tendency of publication counts was continuously on the rise. Bibliometric analysis indicated China and the United States were predominant in this study field, as reflected by their high publication counts and intensive collaboration with other countries. Current key research areas of OS in stroke may lie in the investigation of neuroinflammation, and interaction among multiple cell death mechanisms including apoptosis, autophagy, and ferroptosis to search for effective treatments. Moreover, another hot topic could be the association between air pollution and stroke, and its underlying mechanisms. As the exploration of OS in stroke is speculated to be a continuous hot spot in the future, this article may be helpful for researchers to conduct future studies with the understanding of influential academic forces and research highlights.

A predictive model for prognosis in very low birth weight infants with late-onset sepsis.

OBJECTIVES: This study aims to develop a predictive model to assess the probability of poor prognosis in very low birth weight infants (VLBWI) with late-onset sepsis (LOS). METHODS: A total of 309 eligible VLBWI with LOS were included in the study. Logistic regression was used to determine prognostic factors for VLBWI with LOS. A nomogram incorporating these factors was created to predict the probability of poor prognosis. Poor prognosis includes death and survival with severe complications. RESULTS: In the developmental cohort, the incidence of poor prognosis was 59.5% (147/247). Forward stepwise logistic regression analysis showed that HCO3, albumin (ALB), ionized calcium (iCa), blood urea nitrogen (BUN), gestational age (GA), and birth weight (BW) were independent predictors of poor prognosis in VLBWI with LOS. The predictive model showed good discrimination and calibration. In the developmental cohort, the prediction model had a sensitivity of 83.7%, a specificity of 74.0%, and a C-index of 0.845 (95% confidence interval: 0.795-0.894). CONCLUSION: Our study identified independent predictors of poor prognosis in VLBWI with LOS and used them to construct a predictive model. This model can help clinicians to identify high-risk groups with poor prognosis early and provide important clinical reference information. IMPACT: This article highlights the development of a predictive model to assess the probability of poor prognosis in very low birth weight infants with late-onset sepsis (LOS). The model constructed in this manuscript was the first model to predict the poor prognosis of VLBWI with LOS. We mean a poor prognosis that includes death and some severe complications that may lead to long-term disability. Clinicians can use the model's scoring results to assess a patient's condition and accurately identify the occurrence of poor prognosis.

Modification and Solubility Enhancement of Rice Protein and Its Application in Food Processing: A Review.

Rice protein is a high-quality plant-based protein source that is gluten-free, with high biological value and low allergenicity. However, the low solubility of rice protein not only affects its functional properties such as emulsification, gelling, and water-holding capacity but also greatly limits its applications in the food industry. Therefore, it is crucial to modify and improve the solubility of rice protein. In summary, this article discusses the underlying causes of the low solubility of rice protein, including the presence of high contents of hydrophobic amino acid residues, disulfide bonds, and intermolecular hydrogen bonds. Additionally, it covers the shortcomings of traditional modification methods and the latest compound improvement methods, compares various modification methods, and puts forward the best sustainable, economical, and environmentally friendly method. Finally, this article lists the uses of modified rice protein in dairy, meat, and baked goods, providing a reference for the extensive application of rice protein in the food industry.

Epidemic versus economic performances of the COVID-19 lockdown: A big data driven analysis.

Lockdown measures have been a "panacea" for pandemic control but also a violent "poison" for economies. Lockdown policies strongly restrict human mobility but mobility reduce does harm to economics. Governments meet a thorny problem in balancing the pros and cons of lockdown policies, but lack comprehensive and quantified guides. Based on millions of financial transaction records, and billions of mobility data, we tracked spatio-temporal business networks and human daily mobility, then proposed a high-resolution two-sided framework to assess the epidemiological performance and economic damage of different lockdown policies. We found that the pandemic duration under the strictest lockdown is less about two months than that under the lightest lockdown, which makes the strictest lockdown characterize both epidemiologically and economically efficient. Moreover, based on the two-sided model, we explored the spatial lockdown strategy. We argue that cutting off intercity commuting is significant in both epidemiological and economical aspects, and finally helped governments figure out the Pareto optimal solution set of lockdown strategy.

[Association of phthalate and polycyclic aromatic hydrocarbon exposure during early pregnancy with premature delivery: A cohort study].

OBJECTIVE: To explore the relationship of the exposure to phthalate esters (PAE) and polycyclic aromatic hydrocarbons (PAH) with clinical premature delivery during early pregnancy. METHODS: We conducted a baseline questionnaire survey among 821 pregnant women undergoing prenatal examination in Hubei Provincial Maternal and Child Health Care Hospital, collected their morning urine samples and followed them up to the outcomes of pregnancy. We quantitatively analyzed 10 PAE and 10 PAH metabolites in the urine samples, followed by Mann-Whitney U test, chi-square test, and logistic regression analysis. RESULTS: The detection rate of the 5 factors exposed to was >80% while that of phthalic acid monobenzyl ester (MBzP) was <50% in PAEs; that of the 5 factors exposed to was >80%, that of 3-hydroxyphene (3-OHPHE) was 86.91% while that of 4-hydroxyphene (4-OHPHE) was <50% in PAHs. Logistic regression analysis showed that the risk of premature delivery was higher in the high MBzP- than in the low MBzP-exposure group (aOR = 2.26, 95% CI: 1.17－4.39). CONCLUSION: High MBzP-exposure may be a risk factor for premature delivery.

Anti-NMDAR encephalitis induced in mice by active immunization with a peptide from the amino-terminal domain of the GluN1 subunit.

BACKGROUND: Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a recently discovered autoimmune syndrome associated with psychosis, dyskinesia, and seizures. However, the underlying mechanisms of this disease remain unclear, in part because of a lack of suitable animal models. METHODS: This study describes a novel female C57BL/6 mouse model of anti-NMDAR encephalitis that was induced by active immunization against NMDARs using an amino terminal domain (ATD) peptide from the GluN1 subunit (GluN1356-385). RESULTS: Twelve weeks after immunization, the immunized mice showed significant memory loss. Furthermore, antibodies from the cerebrospinal fluid of immunized mice decreased the surface NMDAR cluster density in hippocampal neurons which was similar to the effect induced by the anti-NMDAR encephalitis patients' antibodies. Immunization also impaired long-term potentiation at Schaffer collateral-CA1 synapses and reduced NMDAR-induced calcium influx. CONCLUSION: We established a novel anti-NMDAR encephalitis model using active immunization with peptide GluN1356-385 targeting the ATD of GluN1. This novel model may allow further research into the pathogenesis of anti-NMDAR encephalitis and aid in the development of new therapies for this disease.

Droplet rolling angle model of micro-nanostructure superhydrophobic coating surface.

The droplet rolling angle is one of the important indicators to measure the coating's hydrophobic performance, but the specific factors affecting the droplet rolling angle on the micro-nanostructured superhydrophobic coating surface are not yet known. Based on the rolling mechanism of droplets on rough surfaces, and from the perspective of coating microscopic energy conservation, this paper points out that the micron-scale morphology and the nanoscale morphology can comprehensively affect the droplet rolling angle. From the above perspective, a mathematical model of the droplet rolling angle on the micro-nanostructure superhydrophobic coating surface was established. The model shows that the droplet rolling angle is positively correlated with the ratio of nano-sized pillar width to spacing, the ratio of micron-sized papilla radius to spacing, and the liquid-gas interfacial tension, and is negatively correlated to the droplet intrinsic contact angle, droplet volume and droplet density. The droplet rolling angle calculated by the presented model is in good agreement with the experimentally tested results. This model can provide good accuracy in predicting the droplet rolling angle on the micro-nanostructured superhydrophobic coating surface.

The interaction between reward and the task-irrelevant emotional context in memory.

Reward improves task performance while the emotional contexts irrelevant to the task impair task performance. An interaction between reward and the task-irrelevant emotional context has been discovered by some studies using perceptual tasks. However, it is unclear that how memory performance would be affected by both variables. This study aimed to answer this question and explore the role of arousal induced by emotional stimuli, to which was seldomly paid attention by previous studies. We conducted two experiments with the study-test paradigm. The first difference between the experiments was the way that the emotional stimuli were presented. They were presented with the words (Experiment 1) or separately (Experiment 2). The second difference was that the manipulation of the emotional arousal was phasic (Experiment 1) or tonic (Experiment 2). Both experiments showed that the reward effect was greater in emotional context compared to the neutral context, which is not only due to the poorer memory of no reward-associated words but also the better memory of reward-associated words in emotional contexts especially in negative one. These results supported the view that emotional arousal enhanced the memory of high priority stimuli (reward-associated words) and impaired the memory of low priority stimuli (no reward-associated words).

Impacts of COVID-19 pandemic on user behaviors and environmental benefits of bike sharing: A big-data analysis.

The COVID-19 pandemic spreads rapidly around the world, and has given rise to huge impacts on all aspects of human society. This study utilizes big data techniques to analyze the impacts of COVID-19 on the user behaviors and environmental benefits of bike sharing. In this study, a novel method is proposed to calculate the trip distances and trajectories via a python package OSMnx so as to accurately estimate the environmental benefits of bike sharing. In addition, we employ the topological indices arising from complex network theory to quantitatively analyze the transformation of user behavior pattern of bike sharing during the COVID-19 pandemic. The results show that this pandemic has impacted the user behaviors and environmental benefits of bike sharing in Beijing significantly. During the pandemic, the estimated reductions of energy consumption and emissions on 6th Feb decreased to approximately 1 in 17 of those on a normal day, and the environmental benefits at most recovered to 70% of those in normal days. The impacts of COVID-19 on the environmental benefits in different districts are different. Furthermore, the decline of average strength and strength distribution obeying exponential distribution but with different slope rates suggests that people are less likely to take bike sharing to the places where were popular before. The pandemic has also increased the average trip time of bike sharing. Our research may facilitate the understanding of the impacts of COVID-19 pandemic on our society and environment, and also provide clues to adapt to this unprecedented pandemic so as to respond to similar events in the future.

1.6 Million transactions replicate distributed PV market slowdown by COVID-19 lockdown.

Solar PV has seen a spectacular market development in recent years and has become a cost competitive source of electricity in many parts of the world. Yet, prospective observations show that the coronavirus pandemic could impact renewable energy projects, especially in the distributed market. Tracking and attributing the economic footprint of COVID-19 lockdowns in the photovoltaic sector poses a significant research challenge. Based on millions of financial transaction records and 44 thousand photovoltaic installation records, we tracked the spatio-temporal sale network of the distributed photovoltaic market and explored the extent of market slowdown. We found that a two-month lockdown duration can be assessed as a high-risk threshold value. When the lockdown duration exceeds the threshold value, the monthly value-added loss reaches 67.7%, and emission reduction capacity is cut by 64.2% over the whole year. We show that risks of a slowdown in PV deployment due to COVID-19 lockdowns can be mitigated by comprehensive incentive strategies for the distributed PV market amid market uncertainties.