Triiodothyronine induces a proinflammatory monocyte/macrophage profile and impedes cardiac regeneration.

Neonatal mouse hearts can regenerate post-injury, unlike adult hearts that form fibrotic scars. The mechanism of thyroid hormone signaling in cardiac regeneration warrants further study. We found that triiodothyronine impairs cardiomyocyte proliferation and heart regeneration in neonatal mice after apical resection. Single-cell RNA-Sequencing on cardiac CD45-positive leukocytes revealed a pro-inflammatory phenotype in monocytes/macrophages after triiodothyronine treatment. Furthermore, we observed that cardiomyocyte proliferation was inhibited by medium from triiodothyronine-treated macrophages, while triiodothyronine itself had no direct effect on the cardiomyocytes in vitro. Our study unveils a novel role of triiodothyronine in mediating the inflammatory response that hinders heart regeneration.

N6-Methyladenosine (m6A) Sequencing Reveals Heterodera glycines-Induced Dynamic Methylation Promoting Soybean Defense.

Unraveling the intricacies of soybean cyst nematode (Heterodera glycines) race 4 resistance and susceptibility in soybean breeding lines-11-452 (highly resistant) and Dongsheng1 (DS1, highly susceptible)-was the focal point of this study. Employing cutting-edge N6-methyladenosine (m6A) and RNA sequencing techniques, we delved into the impact of m6A modification on gene expression and plant defense responses. Through the evaluation of nematode development in both resistant and susceptible roots, a pivotal time point (3 days postinoculation) for m6A methylation sequencing was identified. Our sequencing data exhibited robust statistics, successful soybean genome mapping, and prevalent m6A peak distributions, primarily in the 3' untranslated region and stop codon regions. Analysis of differential methylation peaks and differentially expressed genes revealed distinctive patterns between resistant and susceptible genotypes. In the highly resistant line (11-452), key resistance and defense-associated genes displayed increased expression coupled with inhibited methylation, encompassing crucial players such as R genes, receptor kinases, and transcription factors. Conversely, the highly susceptible DS1 line exhibited heightened expression correlated with decreased methylation in genes linked to susceptibility pathways, including Mildew Locus O-like proteins and regulatory elements affecting defense mechanisms. Genome-wide assessments, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, and differential methylation peak/differentially expressed gene overlap emphasized the intricate interplay of m6A modifications, alternative splicing, microRNA, and gene regulation in plant defense. Protein-protein interaction networks illuminated defense-pivotal genes, delineating divergent mechanisms in resistant and susceptible responses. This study sheds light on the dynamic correlation between methylation, splicing, and gene expression, providing profound insights into plant responses to nematode infection.

The propagation behavior of reaction wave for Ni/Al clad particle composites under shock loading.

Prior studies indicate that the reaction wave can propagate from the impact surface, but the possibility and the influencing factors of the reaction wave formation are still unclear. This work investigates the propagation behavior of the shock-induced reaction wave for Ni/Al clad particle composites with varying stoichiometry (from 0.5 to 0.75 of the Ni mole fraction) through molecular dynamics simulations. It is found that the solid-state reaction processes with or without wave propagation strongly depend on the conjunction of stoichiometry and shock intensity. Within the cases of wave propagation, the calculated propagation velocity (in the range of 135-170 m/s) increases linearly or exponentially with the Ni mole fraction. Furthermore, the thermodynamic criteria for the reaction wave formation, including Al melting at the collision surface and higher temperature gradient, are established by analysis of the shock-induced high-entropy layer. In addition, microstructural characterization reveals the intrinsic mechanisms of the propagation of the reaction wave and the formation of additional reaction wave, namely, the dissolution of Ni into Al and the coalescence of reaction zones. Apart from the propagation behavior, the initial stoichiometry influences the crystallization-dissolution of B2-NiAl during reaction processes, notably through an exponential growth relationship between maximum crystallinity and the Ni mole fraction. These findings may provide a physical basis for improving traditional reaction rate models to break through phenomenological understanding.

The longevity protein p66Shc is required for neonatal heart regeneration.

The longevity protein p66Shc is essential for the senescence signaling that is involved in heart regeneration and remodeling. However, the exact role of p66Shc in heart regeneration is unknown. In this study, we found that p66Shc deficiency decreased neonatal mouse cardiomyocyte (CM) proliferation and impeded neonatal heart regeneration after apical resection injury. RNA sequencing and functional verification demonstrated that p66Shc regulated CM proliferation by activating ß-catenin signaling. These findings reveal the critical role of p66Shc in neonatal heart regeneration and provide new insights into senescence signaling in heart regeneration.

Modeling Indirect Greenhouse Gas Emissions Sources from Urban Wastewater Treatment Plants: Integrating Machine Learning Models to Compensate for Sparse Parameters with Abundant Observations.

Electricity consumption and sludge yield (SY) are important indirect greenhouse gas (GHG) emission sources in wastewater treatment plants (WWTPs). Predicting these byproducts is crucial for tailoring technology-related policy decisions. However, it challenges balancing mass balance models and mechanistic models that respectively have limited intervariable nexus representation and excessive requirements on operational parameters. Herein, we propose integrating two machine learning models, namely, gradient boosting tree (GBT) and deep learning (DL), to precisely pointwise model electricity consumption intensity (ECI) and SY for WWTPs in China. Results indicate that GBT and DL are capable of mining massive data to compensate for the lack of available parameters, providing a comprehensive modeling focusing on operation conditions and designed parameters, respectively. The proposed model reveals that lower ECI and SY were associated with higher treated wastewater volumes, more lenient effluent standards, and newer equipment. Moreover, ECI and SY showed different patterns when influent biochemical oxygen demand is above or below 100 mg/L in the anaerobic-anoxic-oxic process. Therefore, managing ECI and SY requires quantifying the coupling relationships between biochemical reactions instead of isolating each variable. Furthermore, the proposed models demonstrate potential economic-related inequalities resulting from synergizing water pollution and GHG emissions management.

Deformation, damage, and reaction characteristics during the collision between Ni and Al nanoparticles.

The exothermic reaction during the collision between nanoparticles is of importance for the engineering applications of energetic powder materials. This work investigates collision-induced nanoparticle deformation, damage and reaction characteristics in a reactive Ni/Al system via molecular dynamics simulations. The morphological changes and reaction process are explored thoroughly for a wide range of impact velocities v and initial particle radius R. For lower impact velocities (1 km s-1 ≤ v ≤ 1.5 km s-1), the fully melted Al gradually clad the plastic deformed Ni nanoparticles to form an Al-shell/Ni-core structure, and the morphology ultimately develop into a nearly spherical shape possessing minimal surface energy. During this period, the self-sustaining reaction driven by the diffusion of Ni atoms into molten Al leads to slow melting of Ni nanoparticles, and the reaction and melting rates increase with the decrease of the particle radius. There exists one critical radius (R = 10 nm) beyond which the reaction is severely blocked due to the occurrence of fracture behavior at v = 1.5 km s-1. For intermediate velocities (2 km s-1 ≤ v < 3 km s-1), collision-induced debris clouds are observed, which satisfies the power-law distribution in the size of debris and results in an obvious reduction of the final reaction degree. Interestingly, we found that the reactive component in generated debris is lower for the larger-radius nanoparticle, which is also responsible for the lower final reaction degree and thermal kinetic energy. For higher velocities (v ≥ 3 km s-1), the occurrence of spallation damage reduces the contact area due to the formed micro-voids within Al and Ni nanoparticles and consequently the final reaction degree further.

Atomistic study on reaction kinetics and reactivity of Ni/Al clad particles composites under shock loading.

In prior research on shock-induced reaction, the interfacial crystallization of intermetallics, which plays an important role in solid-state reaction kinetics, has not been explored in detail. This work comprehensively investigates the reaction kinetics and reactivity of Ni/Al clad particle composites under shock loading with molecular dynamics simulations. It is found that the reaction acceleration in a small particle system or the reaction propagation in a large particle system breaks down the heterogeneous nucleation and continuous growth of B2 phase at the Ni/Al interface. This makes the generation and dissolution of B2-NiAl show a staged pattern consistent with chemical evolution. Importantly, the crystallization processes are appropriately described by the well-established Johnson-Mehl-Avrami kinetics model. With the increase in Al particle size, the maximum crystallinity and growth rate of B2 phase decrease and the value of the fitted Avrami exponent decreases from 0.55 to 0.39, showing a good agreement with the solid-state reaction experiment. In addition, the calculations of reactivity reveal that the reaction initiation and propagation will be retarded, but the adiabatic reaction temperature can be elevated when Al particle size increases. An exponential decay relationship is found between the propagation velocity of the chemical front and the particle size. As expected, the shock simulations at non-ambient conditions indicate that elevating the initial temperature significantly enhances the reactivity of large particle systems and results in a power-law decrease in the ignition delay time and a linear-law increase in the propagation velocity.

Atomic insights into shock-induced alloying reaction of premixed Ni/Al nanolaminates.

In material processing and handling processes, premixed interlayer often replace the ideal Ni/Al interface, which would become a new origin of alloying reaction. This work investigates shock-induced reaction mechanism and kinetics of premixed Ni/Al nanolaminates with molecular dynamics simulations and theoretical analysis. The reaction is found to be driven by the crystallization evolution in premixed interlayer and the diffusion of premixed atoms. Among them, multi-stage reaction patterns are strongly manifested by the crystallization evolution characteristics. Specifically, "crystallization-dissolution-secondary growth" and "crystallization-dissolution" of B2 phase respectively correspond to the solid-state and solid-liquid reaction cases, where crystallizations are fitted well by Johnson-Mehl-Avrami kinetics model. Interestingly, the different growth mechanisms of B2 grain are revealed, namely nuclei coalescence and atomic diffusion. Moreover, the analysis of microscopic diffusion theory indicates a certain non-random diffusion nature for solid-state reaction initiation, but near-purely random diffusion for solid-liquid reaction initiation. The diffused Al atoms possess a limited diffusion coefficient and enhanced diffusion correlation, resulting in extremely slow mixing rate in Ni layer. In addition, the influence law of Ni concentration in premixed interlayer on reactivity parameters can be quantitatively described by a quadratic function.

Bilateral central retinal artery occlusion as a presenting manifestation of systemic lupus erythematosus: a case-based review.

Central retinal artery occlusion (CRAO) is an ophthalmic emergency that typically results in permanent vision damage even despite vigorous treatment. In this article, we describe a case of acute vaso-occlusive retinopathy that presented as the primary manifestation of SLE in the absence of elevated levels of APLAs. After treatment with intravenous steroids, immunoglobulin, intrathecal injection of dexamethasone, plasma exchange, and intravenous cyclophosphamide, SLE was well controlled in the patient, but her vision was permanently lost in the left eye. We also go over a brief review of the currently available literature on retinal vaso-occlusive disease present in SLE. The pathology mechanism of CRAO is related to immune complex-mediated "vasculitis", which is typically associated with neuropsychiatric lupus. However, the literature review identified antiphospholipid antibody syndrome (APS) in only 6 of 19 patients, indicating that other mechanisms besides APS are associated with CRAO. Systemic immunosuppression and anticoagulants are required for the treatment of this severe vaso-occlusive retinopathy. Early recognition and aggressive intervention may prevent severe loss of vision.

The intricate role of annexin A2 in kidney: a comprehensive review.

Annexin A2 (Anxa2) is a calcium (Ca2+)-regulated phospholipid binding protein composed of a variable N-terminus and a conserved core domain. This protein has been widely found in many tissues and fluids, including tubule cells, glomerular epithelial cells, renal vessels, and urine. In acute kidney injury, the expression level of this protein is markedly elevated in response to acute stress. Moreover, Anxa2 is a novel biomarker and potential therapeutic target with prognostic value in chronic kidney disease. In addition, Anxa2 is associated not only with clear-cell renal cell carcinoma differentiation but also the formation of calcium-related nephrolithiasis. In this review, we discuss the characteristics and functions of Anxa2 and focus on recent reports on the role of Anxa2 in the kidney, which may be useful for future research.

Improving Robustness of High-Low-Order Coupled Networks against Malicious Attacks Based on a Simulated Annealing Algorithm.

Malicious attacks can cause significant damage to the structure and functionality of complex networks. Previous research has pointed out that the ability of networks to withstand malicious attacks becomes weaker when networks are coupled. However, traditional research on improving the robustness of networks has focused on individual low-order or higher-order networks, lacking studies on coupled networks with higher-order and low-order networks. This paper proposes a method for optimizing the robustness of coupled networks with higher-order and low-order based on a simulated annealing algorithm to address this issue. Without altering the network's degree distribution, the method rewires the edges, taking the robustness of low-order and higher-order networks as joint optimization objectives. Making minimal changes to the network, the method effectively enhances the robustness of coupled networks. Experiments were conducted on Erdos-Rényi random networks (ER), scale-free networks (BA), and small-world networks (SW). Finally, validation was performed on various real networks. The results indicate that this method can effectively enhance the robustness of coupled networks with higher-order and low-order.

Reticulon-1A mediates diabetic kidney disease progression through endoplasmic reticulum-mitochondrial contacts in tubular epithelial cells.

Recent epidemiological studies suggest that some patients with diabetes progress to kidney failure without significant albuminuria and glomerular injury, suggesting a critical role of kidney tubular epithelial cell (TEC) injury in diabetic kidney disease (DKD) progression. However, the major risk factors contributing to TEC injury and progression in DKD remain unclear. We previously showed that expression of endoplasmic reticulum-resident protein Reticulon-1A (RTN1A) increased in human DKD, and the increased RTN1A expression promoted TEC injury through endoplasmic reticulum (ER) stress response. Here, we show that TEC-specific RTN1A overexpression worsened DKD in mice, evidenced by enhanced tubular injury, tubulointerstitial fibrosis, and kidney function decline. But RTN1A overexpression did not exacerbate diabetes-induced glomerular injury or albuminuria. Notably, RTN1A overexpression worsened both ER stress and mitochondrial dysfunction in TECs under diabetic conditions by regulation of ER-mitochondria contacts. Mechanistically, ER-bound RTN1A interacted with mitochondrial hexokinase-1 and the voltage-dependent anion channel-1 (VDAC1), interfering with their association. This disengagement of VDAC1 from hexokinase-1 resulted in activation of apoptotic and inflammasome pathways, leading to TEC injury and loss. Thus, our observations highlight the importance of ER-mitochondrial crosstalk in TEC injury and the salient role of RTN1A-mediated ER-mitochondrial contact regulation in DKD progression.

Single polymeric microfiber waveguide platform for sensitive detection and discrimination of DNA methylation.

The development of a rapid and sensitive detection platform for DNA and DNA methylation in complex biological environments has attracted considerable attention. Herein, we describe a detection platform for p16 and p16 methylation in buffer and serum based on a single polymeric fluorescent microfiber waveguide with sandwich-structured hybridization designs. The target p16 could be captured by oligonucleotides conjugated on the surface of polymeric microfibers and oligonucleotides conjugated with gold nanoparticles, resulting in quenching the out-coupled tip emission of the microfiber waveguide. Then the restriction digestion enzyme HpaII was applied to specifically recognize the unmethylated 5'-CCGG-3' site and cut the formed sandwich structure. The gold nanoparticles could be removed from the surface of chitosan fiber so that the out-coupled tip emission of the polymeric fluorescent microfiber would be partially recovered. It is noteworthy that the proposed polymeric microfiber waveguide platform exhibited selective and sensitive detection of p16 with a low limit of 2 pM and excellent analytical performance of methylation as low as 5% difference. This strategy avoids the use of traditional PCR-based amplification and tedious operative processes, and we envisage that this technique could be extended to various DNA methylation analyses, which is meaningful for early clinical diagnosis of diseases.

Intestinal microbiota dysbiosis in acute kidney injury: novel insights into mechanisms and promising therapeutic strategies.

In recent years, the clinical impact of intestinal microbiota-kidney interaction has been emerging. Experimental evidence highlighted a bidirectional evolutionary correlation between intestinal microbiota and kidney diseases. Nonetheless, acute kidney injury (AKI) is still a global public health concern associated with high morbidity, mortality, healthcare costs, and limited efficient therapy. Several studies on the intestinal microbiome have improved the knowledge and treatment of AKI. Therefore, the present review outlines the concept of the gut-kidney axis and data about intestinal microbiota dysbiosis in AKI to improve the understanding of the mechanisms of the intestinal microbiome on the modification of kidney function and response to kidney injury. We also introduced the future directions and research areas, emphasizing the intervention approaches and recent research advances of intestinal microbiota dysbiosis during AKI, thereby providing a new perspective for future clinical trials.

Ball Screw Fault Diagnosis Based on Wavelet Convolution Transfer Learning.

The ball screw is the core component of the CNC machine tool feed system, and its health plays an important role in the feed system and even in the entire CNC machine tool. This paper studies the fault diagnosis and health assessment of ball screws. Aiming at the problem that the ball screw signal is weak and susceptible to interference, using a wavelet convolution structure to improve the network can improve the mining ability of signal time domain and frequency domain features; aiming at the challenge of ball screw sensor installation position limitation, a transfer learning method is proposed, which adopts the domain adaptation method as jointly distributed adaptation (JDA), and realizes the transfer diagnosis across measurement positions by extracting the diagnosis knowledge of different positions of the ball screw. In this paper, the adaptive batch normalization algorithm (AdaBN) is introduced to enhance the proposed model so as to improve the accuracy of migration diagnosis. Experiments were carried out using a self-made lead screw fatigue test bench. Through experimental verification, the method proposed in this paper can extract effective fault diagnosis knowledge. By collecting data under different working conditions at the bearing seat of the ball screw, the fault diagnosis knowledge is extracted and used to identify and diagnose the position fault of the nut seat. In this paper, some background noise is added to the collected data to test the robustness of the proposed network model.

Fragility Induced by Interdependency of Complex Networks and Their Higher-Order Networks.

The higher-order structure of networks is a hot research topic in complex networks. It has received much attention because it is closely related to the functionality of networks, such as network transportation and propagation. For instance, recent studies have revealed that studying higher-order networks can explore hub structures in transportation networks and information dissemination units in neuronal networks. Therefore, the destruction of the connectivity of higher-order networks will cause significant damage to network functionalities. Meanwhile, previous works pointed out that the function of a complex network depends on the giant component of the original(low-order) network. Therefore, the network functionality will be influenced by both the low-order and its corresponding higher-order network. To study this issue, we build a network model of the interdependence of low-order and higher-order networks (we call it ILH). When some low-order network nodes fail, the low-order network's giant component shrinks, leading to changes in the structure of the higher-order network, which further affects the low-order network. This process occurs iteratively; the propagation of the failure can lead to an eventual network crash. We conducted experiments on different networks based on the percolation theory, and our network percolation results demonstrated a first-order phase transition feature. In particular, we found that an ILH is more fragile than the low-order network alone, and an ILH is more likely to be corrupted in the event of a random node failure.

Optimal Sensor Placement of the Artificial Lateral Line for Flow Parametric Identification.

The multi-sensor artificial lateral line system (ALLS) can identify the flow-field's parameters to realize the closed-loop control of the underwater robotic fish. An inappropriate sensor placement of ALLS may result in inaccurate flow-field parametric identification. Therefore, this paper proposes a method to optimize the sensor placement configuration of the ALLS, which mainly included three algorithms, the feature importance algorithm based on mean and variance (MVF), the feature importance algorithm based on distance evaluation (DF), and the information redundancy (IR) algorithm. The optimal sensor placement performance selected by this method is verified by simulation. In addition, further experimental verification was conducted using the ALLS. Compared with the uniform sensor placement configuration mentioned in recent studies, the experimental results suggest that the optimal sensor placement method can achieve a more effective prediction of the flow-field parameters, therefore strengthening the underwater robotic fish's perception and control function.

Mitochondrial dysfunction and the AKI-to-CKD transition.

Acute kidney injury (AKI) has been widely recognized as an important risk factor for the occurrence and development of chronic kidney disease (CKD). Even milder AKI has adverse consequences and could progress to renal fibrosis, which is the ultimate common pathway for various terminal kidney diseases. Thus, it is urgent to develop a strategy to hinder the transition from AKI to CKD. Some mechanisms of the AKI-to-CKD transition have been revealed, such as nephron loss, cell cycle arrest, persistent inflammation, endothelial injury with vascular rarefaction, and epigenetic changes. Previous studies have elucidated the pivotal role of mitochondria in acute injuries and demonstrated that the fitness of this organelle is a major determinant in both the pathogenesis and recovery of organ function. Recent research has suggested that damage to mitochondrial function in early AKI is a crucial factor leading to tubular injury and persistent renal insufficiency. Dysregulation of mitochondrial homeostasis, alterations in bioenergetics, and organelle stress cross talk contribute to the AKI-to-CKD transition. In this review, we focus on the pathophysiology of mitochondria in renal recovery after AKI and progression to CKD, confirming that targeting mitochondria represents a potentially effective therapeutic strategy for the progression of AKI to CKD.

MicroRNA-214 targets COX-2 to antagonize indoxyl sulfate (IS)-induced endothelial cell apoptosis.

Cardiovascular disease (CVD) serves as the major cause of mortality in chronic kidney disease (CKD) patients. The injury of endothelium associated with the long-term challenge of uremic toxins including the toxic indoxyl sulfate (IS) is one of key pathological factors leading to CVD. However, the mechanisms of uremic toxins, especially the IS, resulting in endothelial injury, remain unclear. miR-214 was reported to contribute to the pathogenesis of cardiovascular diseases, while its role in IS-induced endothelial cell apoptosis is unknown. In this study, we investigated the role of microRNA-214 (miR-214) in IS-induced endothelial cell apoptosis and the underlying mechanisms using mouse aortic endothelial cells (MAECs). Following IS treatment, miR-214 was significantly downregulated in MAECs in line with enhanced cell apoptosis. Meanwhile, COX-2 was upregulated at both mRNA and protein levels along with increased secretion of PGE2 in medium. To define the role of miR-214 in IS-induced endothelial cell apoptosis, we modulated miR-214 level in MAECs and found that overexpression of miR-214 markedly attenuated endothelial cell apoptosis, while antagonism of miR-214 deteriorated cell death after IS challenge. Further analyses confirmed that COX-2 is a target gene of miR-214, and the inhibition of COX-2 by a specific COX-2 inhibitor NS-398 strikingly attenuated IS-induced endothelial cell apoptosis along with a significant blockade of PGE2 secretion. In conclusion, this study demonstrated an important role of miR-214 in protecting against endothelial cell damage induced by IS possibly by direct downregulation of COX-2/PGE2 axis.

The PLATZ Transcription Factor GL6 Affects Grain Length and Number in Rice.

Grain size is one of the key determinants of grain yield. Although a number of genes that control grain size in rice (Oryza sativa) have been identified, the overall regulatory networks behind this process remain poorly understood. Here, we report the map-based cloning and functional characterization of the quantitative trait locus GL6, which encodes a plant-specific plant AT-rich sequence- and zinc-binding transcription factor that regulates rice grain length and spikelet number. GL6 positively controls grain length by promoting cell proliferation in young panicles and grains. The null gl6 mutant possesses short grains, whereas overexpression of GL6 results in large grains and decreased grain number per panicle. We demonstrate that GL6 participates in RNA polymerase III transcription machinery by interacting with RNA polymerase III subunit C53 and transcription factor class C1 to regulate the expression of genes involved in rice grain development. Our findings reveal a further player involved in the regulation of rice grain size that may be exploited in future rice breeding.