Elucidating and forecasting the organochlorine pesticides in suspended particulate matter by a two-stage decomposition based interpretable deep learning approach.

Accurately predicting the concentration of organochlorine pesticides (OCPs) presents a challenge due to their complex sources and environmental behaviors. In this study, we introduced a novel and advanced model that combined the power of three distinct techniques: Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Variational Mode Decomposition (VMD), and a deep learning network of Long Short-Term Memory (LSTM). The objective is to characterize the variation in OCPs concentrations with high precision. Results show that the hybrid two-stage decomposition coupled models achieved an average symmetric mean absolute percentage error (SMAPE) of 23.24 % in the empirical analysis of typical surface water. It exhibited higher predictive power than the given individual benchmark models, which yielded an average SMAPE of 40.88 %, and single decomposition coupled models with an average SMAPE of 29.80 %. The proposed CEEMDAN-VMD-LSTM model, with an average SMAPE of 13.55 %, consistently outperformed the other models, yielding an average SMAPE of 33.53 %. A comparative analysis with shallow neural network methods demonstrated the advantages of the LSTM algorithm when coupled with secondary decomposition techniques for processing time series datasets. Furthermore, the interpretable analysis derived by the SHAP approach revealed that precipitation followed by the total phosphorus had strong effects on the predicted concentration of OCPs in the given water. The data presented herein shows the effectiveness of decomposition technique-based deep learning algorithms in capturing the dynamic characteristics of pollutants in surface water.

ResNet diagnosis of rotor faults in oil transfer pumps.

To address rotor imbalance and misalignment in oil transfer pumps, an innovative diagnostic framework using Residual Network (ResNet) is proposed. The model incorporates advanced signal processing algorithms and strategic sensor placement to enhance diagnostic efficacy. A fault simulation test rig captured vibration signals from eight key measurement points on the pump. One-dimensional and multi-dimensional signal processing techniques generated comprehensive datasets for training and validating the model. Sensor placement optimization, focusing on the bearing seat's axial direction, inlet flange's vertical direction, and outlet flange's axial direction, increased rotor fault sensitivity. Time-frequency data processed via Short-Time Fourier Transform (STFT) achieved the highest diagnostic accuracy, surpassing 98 %. This study highlights the importance of optimal signal processing and precise sensor placement in improving the accuracy of diagnosing rotor faults in oil transfer pumps, thus enhancing the operational reliability and efficiency of energy transportation systems.

Mechanochemistry: Fundamental Principles and Applications.

Mechanochemistry is an emerging research field at the interface of physics, mechanics, materials science, and chemistry. Complementary to traditional activation methods in chemistry, such as heat, electricity, and light, mechanochemistry focuses on the activation of chemical reactions by directly or indirectly applying mechanical forces. It has evolved as a powerful tool for controlling chemical reactions in solid state systems, sensing and responding to stresses in polymer materials, regulating interfacial adhesions, and stimulating biological processes. By combining theoretical approaches, simulations and experimental techniques, researchers have gained intricate insights into the mechanisms underlying mechanochemistry. In this review, the physical chemistry principles underpinning mechanochemistry are elucidated and a comprehensive overview of recent significant achievements in the discovery of mechanically responsive chemical processes is provided, with a particular emphasis on their applications in materials science. Additionally, The perspectives and insights into potential future directions for this exciting research field are offered.

Cardioprotection of voluntary exercise against breast cancer-induced cardiac injury via STAT3.

Exercise is an effective way to alleviate breast cancer-induced cardiac injury to a certain extent. However, whether voluntary exercise (VE) activates cardiac signal transducer and activator of transcription 3 (STAT3) and the underlying mechanisms remain unclear. This study investigated the role of STAT3-microRNA(miRNA)-targeted protein axis in VE against breast cancer-induced cardiac injury.VE for 4 weeks not only improved cardiac function of transgenic breast cancer female mice [mouse mammary tumor virus-polyomavirus middle T antigen (MMTV-PyMT +)] compared with littermate mice with no cancer (MMTV-PyMT -), but also increased myocardial STAT3 tyrosine 705 phosphorylation. Significantly more obvious cardiac fibrosis, smaller cardiomyocyte size, lower cell viability, and higher serum tumor necrosis factor (TNF)-α were shown in MMTV-PyMT + mice compared with MMTV-PyMT - mice, which were ameliorated by VE. However, VE did not influence the tumor growth. MiRNA sequencing identified that miR-181a-5p was upregulated and miR-130b-3p was downregulated in VE induced-cardioprotection. Myocardial injection of Adeno-associated virus serotype 9 driving STAT3 tyrosine 705 mutations abolished cardioprotective effects above. Myocardial STAT3 was identified as the transcription factor binding the promoters of pri-miR-181a (the precursor of miR-181a-5p) and HOX transcript antisense RNA (HOTAIR, sponged miR-130b-3p) in isolated cardiomyocytes. Furthermore, miR-181a-5p targeting PTEN and miR-130b-3p targeting Zinc finger and BTB domain containing protein 20 (Zbtb20) were proved in AC-16 cells. These findings indicated that VE protects against breast cancer-induced cardiac injury via activating STAT3 to promote miR-181a-5p targeting PTEN and to promote HOTAIR to sponge miR-130b-3p targeting Zbtb20, helping to develop new targets in exercise therapy for breast cancer-induced cardiac injury.

TNFSF11/TNFRSF11A Axis Amplifies HDM-Induced Airway Remodeling by Strengthening TGFß1/STAT3 Action.

PURPOSE: Asthma, an airway inflammatory disease, involves multiple tumor necrosis factors (TNF). TNF ligand superfamily member 11 (TNFSF11) and its known receptor, TNF receptor superfamily 11A (TNFRSF11A), has been implicated in asthma; however, the related mechanisms remain unknown. METHODS: The serum and bronchial airway of patients with asthma and healthy subjects were examined. The air-liquid interface of primary human bronchial epithelial (HBE) cells, and Tnfsf11+/- mouse, Tnfrsf11a+/- mouse, and a humanized HSC-NOG-EXL mouse model were established. This study constructed short hairpin RNA (shRNA) of TNFSF11, TNFRSF11A, transforming growth factor ß1 (TGFß1), and transforming growth factor ß receptor type 1 (TGFßR1) using lentivirus to further examine the ability of TNFSF11 protein. RESULTS: This study was the first to uncover TNFSF11 overexpression in the airway and serum of asthmatic human subjects, and the TNFSF11 in serum was closely correlated with lung function. The TNFSF11/TNFRSF11A axis deficiency in Tnfsf11+/- or Tnfrsf11a+/- mice remarkably attenuated the house dust mite (HDM)-induced signal transducer and activator of transcription 3 (STAT3) action and remodeling protein expression. Similarly, the HDM-induced STAT3 action and remodeling protein expression in HBE cells decreased after pretreatment with TNFSF11 or TNFRSF11A shRNA. Meanwhile, the expression of the remodeling proteins induced by TNFSF11 significantly decreased after pretreatment with-stattic (inhibitor of STAT3 phosphorylation) in HBE cells. The STAT3 phosphorylation and remodeling protein expression induced by TNFSF11 obviously decreased after pretreatment with TGFß1 or TGFßR1 shRNA in HBE cells. The above results also verified that blocking TNFSF11 with denosumab alleviated airway remodeling via the TGFß1/STAT3 signaling in the humanized HSC-NOG-EXL mice with HDM-induced asthma. CONCLUSIONS: TGFß1/STAT3 action was closely correlated with TNFSF11/TNFRSF11A axis-mediated airway remodeling. This study presented a novel strategy that blocks the TNFSF11/TNFRSF11A axis to exert a protective effect against asthma.

Sucrose Phosphate Synthase Genes in Plants: Its Role and Practice for Crop Improvement.

Plants convert solar energy and carbon dioxide into organic compounds through photosynthesis. Sucrose is the primary carbonate produced during photosynthesis. Sucrose phosphate synthase (SPS) is the key enzyme controlling sucrose biosynthesis in plants. There are at least three SPS gene families in higher plants, named A, B, and C. However, in monocotyledonous plants from Poaceae, there are at least five SPS gene families, named A, B, C, DIII, and DIV. Each family of SPS genes in different plants shows a divergent expression pattern. So different families of SPS genes participate in diverse biological functions, including sucrose accumulation, plant growth and production, and abiotic stress tolerance. SPS activity in plants is regulated by exogenous factors through gene expression and reversible protein phosphorylation. It is a practicable way to improve crop traits through SPS gene transformation. This work analyzes the cloning, phylogeny, and regulatory mechanism of the SPS gene in plants, reviews its biological function as well as its role in crop improvement, and discusses the challenges and future perspectives. This paper can serve as a reference for further study on plant SPS genes and eventually for crop improvement.

Inhibition of glycosphingolipid synthesis with eliglustat in combination with immune checkpoint inhibitors in advanced cancers: preclinical evidence and phase I clinical trial.

Glycosphingolipids (GSLs) are abundantly expressed in cancer cells. The effects of GSL-targeted immunotherapies are not fully understood. Here, we show that the inhibition of GSL synthesis with the UDP-glucose ceramide glucosyltransferase inhibitor eliglustat can increase the exposure of the major histocompatibility complex (MHC) and tumour antigen peptides, enhancing the antitumour response of CD8+ T cells in a range of tumour models. We therefore conducted a proof-of-concept phase I trial on the combination of eliglustat and an anti-PD-1 antibody for the treatment of advanced cancers (NCT04944888). The primary endpoints were safety and feasibility, and the secondary endpoint was antitumor activity. All prespecified endpoints were met. Among the 31 enrolled patients, only 1 patient experienced a grade 3 adverse event (AE), and no grade 4 AEs were observed. The objective response rate was 22.6% and the disease control rate reached 71%. Of the 8 patients with proficient mismatch repair/microsatellite stable (pMMR/MSS) colorectal cancer, one achieved complete response and two each had partial response and stable disease. In summary, inhibiting the synthesis of GSLs might represent an effective immunotherapy approach.

Impact of Air Pollutants on Lung Function and Inflammatory Response in Asthma in Shanghai.

Objective: Air pollution is a leading public health issue. This study investigated the effect of air quality and pollutants on pulmonary function and inflammation in patients with asthma in Shanghai. Methods: The study monitored 27 asthma outpatients for a year, collecting data on weather, patient self-management [daily asthma diary, peak expiratory flow (PEF) monitoring, medication usage], spirometry and serum markers. To explore the potential mechanisms of any effects, asthmatic mice induced by ovalbumin (OVA) were exposed to PM 2.5. Results: Statistical and correlational analyses revealed that air pollutants have both acute and chronic effects on asthma. Acute exposure showed a correlation between PEF and levels of ozone (O 3) and nitrogen dioxide (NO 2). Chronic exposure indicated that interleukin-5 (IL-5) and interleukin-13 (IL-13) levels correlated with PM 2.5 and PM 10 concentrations. In asthmatic mouse models, exposure to PM 2.5 increased cytokine levels and worsened lung function. Additionally, PM 2.5 exposure inhibited cell proliferation by blocking the NF-κB and ERK phosphorylation pathways. Conclusion: Ambient air pollutants exacerbate asthma by worsening lung function and enhancing Th2-mediated inflammation. Specifically, PM 2.5 significantly contributes to these adverse effects. Further research is needed to elucidate the mechanisms by which PM 2.5 impacts asthma.

Identification of O-arylated huperzinines as novel cholinergic anti-inflammatory pathway agonists against gout arthritis.

Lycodine alkaloids are important natural products with diverse biological effects. In this manuscript, we set out the first structural optimization of the 2-pyridone moiety of Lycodine alkaloid via selective O-arylation under metal-free conditions and obtained a series of potent bioactive molecules against monosodium urate (MSU)-induced IL-1ß production. Further investigations demonstrated that these natural product derivatives could activate the neuro-immunomodulatory cholinergic anti-inflammatory pathway (CAP) to block the initial phase of NLRP3 inflammasome activation. Compared with the clinical drugs hydrocortisone and indomethacin, as well as commercially available CAP agonists GTS-21 and pnu282987, 3k and 3q possessed greater potency against MSU-induced IL-1ß production. Meanwhile, these molecules possessed less cytotoxicity against promonocytic THP-1 macrophages when compared with colchicine. This work reports a concise strategy for direct modification of 2-pyridone moiety from natural Lycodine alkaloids, and provides novel frameworks for discovering CAP activators and drugs for gout arthritis.

Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography: The ACCURATE-CT Study.

BACKGROUND: ArteryFlow Technology (AccuFFRct) is a novel noninvasive method for calculating fractional flow reserve (FFR) from coronary computed tomography angiography (CCTA). The accuracy of AccuFFRct has not been adequately assessed. OBJECTIVES: This study sought to evaluate the diagnostic performance of AccuFFRct in detecting lesion-specific ischemia. METHODS: This prospective study enrolled 339 patients with 404 vessels. CCTA-derived FFR was calculated using an on-site computational fluid dynamics-based method and compared with invasive FFR. The performance of AccuFFRct was comprehensively analyzed in all lesions and subgroups, including "gray zone" lesions, various lesion classifications, clinical presentations, stenosis severities, and lesion locations. RESULTS: Using FFR ≤0.80 as a reference standard, the overall diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for AccuFFRct were 90.6% (95% CI: 87.3%-93.3%), 90.9% (95% CI: 85.1%-94.9%), 90.4% (95% CI: 86.1%-93.8%), 85.3% (95% CI: 79.8%-89.5%), and 94.2% (95% CI: 90.8%-96.4%), respectively. Good correlation and agreement were found between the computed AccuFFRct and measured FFR. AccuFFRct showed superior discrimination ability to CCTA (AUC: 0.93 [95% CI: 0.89-0.95] vs 0.77 [95% CI: 0.72-0.81]; P < 0.001) and quantitative coronary angiography (AUC: 0.93 [95% CI: 0.89-0.95] vs 0.89 [95% CI: 0.85-0.92]; P = 0.048) for identifying functionally significant stenosis. Notably, AccuFFRct maintained high diagnostic accuracy across the spectrum of lesion classifications, clinical presentations, stenosis severities, lesion locations, and in the gray zone. Furthermore, in the cohort with ≥70% stenosis, AccuFFRct could significantly reduce the rate of un-necessary invasive tests (33.1% vs 6.6%; P < 0.001). CONCLUSIONS: The study confirms the potential of AccuFFRct as a noninvasive alternative to invasive FFR for detecting ischemia in coronary artery disease and to risk stratify patients. The results highlight AccuFFRct's robust diagnostic ability across a wide range of lesion classifications, clinical presentations, stenosis severities, lesion locations, and in the gray zone. (Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography [ACCURATE-CT]; NCT04426396).

A sensitive enzyme-free electrochemical sensor based on ZnWO4@co-MNPC@MIP for specific recognition and determination of chloramphenicol in milk sample.

We have carefully built a new chloramphenicol (CAP) electrochemical sensor, which takes the zinc tungstate @ cobalt magnetic nanoporous carbon @ molecularly imprinted polymer (ZnWO4@Co-MNPC@MIP) as the core. First, we successfully prepared Co-MNPC nanomaterials using an efficient one-step hydrothermal method and a direct carbonization method. Next, we recombined ZnWO4 with Co-MNPC and synthesized the completely new ZnWO4@Co-MNPC complex by using the hydrothermal method. To further improve its performance, we combined ZnWO4@Co-MNPC with a molecular imprinted polymer and coated a molecular imprinted (MIP) shell on the surface of ZnWO4@Co-MNPC by precipitation polymerization. This shell not only gives the sensor a new performance but also gives it a stronger peak current, resulting in a more accurate detection of CAP. Under optimal conditions, the ZnWO4@Co-MNPC@MIP (MMIP) electrode has a stronger CAP detection peak current than the one-component electrode, with a fairly wide linear range: 0.007-200 µM and 200-1400 µM. Even more surprisingly, the detection limit is as low as 0.0027 µM, which allows the sensor to maintain excellent selectivity and stability in the face of various interferences, making it an excellent electrochemically modified electrode. Compared to magnetic non-molecular imprint sensors (MNIPs), MMIP sensors have higher detection efficiency. After practical application, we found that the ZnWO4@Co-MNPC@MIP modified electrode was satisfactory in milk samples.

LD-CSNet: A latent diffusion-based architecture for perceptual Compressed Sensing.

Compressed Sensing (CS) is a groundbreaking paradigm in image acquisition, challenging the constraints of the Nyquist-Shannon sampling theorem. This enables high-quality image reconstruction using a minimal number of measurements. Neural Networks' potent feature induction capabilities enable advanced data-driven CS methods to achieve high-fidelity image reconstruction. However, achieving satisfactory reconstruction performance, particularly in terms of perceptual quality, remains challenging at extremely low sampling rates. To tackle this challenge, we introduce a novel two-stage image CS framework based on latent diffusion, named LD-CSNet. In the first stage, we utilize an autoencoder pre-trained on a large dataset to represent natural images as low-dimensional latent vectors, establishing prior knowledge distinct from sparsity and effectively reducing the dimensionality of the solution space. In the second stage, we employ a conditional diffusion model for maximum likelihood estimates in the latent space. This is supported by a measurement embedding module designed to encode measurements, making them suitable for a denoising network. This guides the generation process in reconstructing low-dimensional latent vectors. Finally, the image is reconstructed using a pre-trained decoder. Experimental results across multiple public datasets demonstrate LD-CSNet's superior perceptual quality and robustness to noise. It maintains fidelity and visual quality at lower sampling rates. Research findings suggest the promising application of diffusion models in image CS. Future research can focus on developing more appropriate models for the first stage.

Fusing Ta-doped Li7La3Zr2O12 grains using nanoscale Y2O3 sintering aids for high-performance solid-state lithium batteries.

Solid-state lithium batteries have advantages of high energy density and usage safety and are considered as promising next-generation power sources. Among them, the garnet-type oxide electrolyte has become a widely studied inorganic electrolyte due to its high ionic conductivity and chemical stability. In this paper, nanoscale Y2O3 (NYO) particles are introduced as sintering aids for fabricating Ta-doped Li7La3Zr2O12 (LLZTO) ceramics, and the sintering effects of various NYO ratios on the properties of LLZTO are investigated. Among the samples, the LLZTO-5%NYO sample exhibits the highest ionic conductivity (7.39 × 10-4 S cm-1) and the lowest activation energy (0.17 eV). At various current densities, the polarization voltage of LLZTO-5%NYO is also the lowest without a short circuit. The full cells of LFP|LLZTO-5%NYO|Li exhibit a high capacity of 163.9 mA h g-1 with a high initial coulombic efficiency of 97.4%, and the capacity retention rate is up to 98.1% after 50 cycles. This work may inspire the development of analogous solid-state electrolytes and lithium batteries.

Enhanced native chemical ligation by peptide conjugation in trifluoroacetic acid.

Chemical ligation of peptides is increasingly used to generate proteins not readily accessible by recombinant approaches. However, a robust method to ligate "difficult" peptides remains to be developed. Here, we report an enhanced native chemical ligation strategy mediated by peptide conjugation in trifluoroacetic acid (TFA). The conjugation between a carboxyl-terminal peptide thiosalicylaldehyde thioester and a 1,3-dithiol-containing peptide in TFA proceeds rapidly to form a thioacetal-linked intermediate, which is readily converted into the desired native amide bond product through simple postligation treatment. The effectiveness and practicality of the method was demonstrated by the successful synthesis of several challenging proteins, including the SARS-CoV-2 transmembrane Envelope (E) protein and nanobodies. Because of the ability of TFA to dissolve virtually all peptides and prevent the formation of unreactive peptide structures, the method is expected to open new opportunities for synthesizing all families of proteins, particularly those with aggregable or colloidal peptide segments.

Intraoperative hypotension is associated with decreased long-term survival in older patients after major noncardiac surgery: Secondary analysis of three randomized trials.

STUDY OBJECTIVE: To assess the association of intraoperative hypotension with long-term survivals in older patients after major noncardiac surgery mainly for cancer. DESIGN: A secondary analysis of databases from three randomized trials with long-term follow-up. SETTING: The underlying trials were conducted in 17 tertiary hospitals in China. PATIENTS: Patients aged 60 to 90 years who underwent major noncardiac thoracic or abdominal surgeries (≥ 2 h) in a single center were included in this analysis. EXPOSURES: Restricted cubic spline models were employed to determine the lowest mean arterial pressure (MAP) threshold that was potentially harmful for long-term survivals. Patients were arbitrarily divided into three groups according to the cumulative duration or area under the MAP threshold. The association between intraoperative hypotension exposure and long-term survivals were analyzed with the Cox proportional hazard regression models. MEASUREMENTS: Our primary endpoint was overall survival. Secondary endpoints included recurrence-free and event-free survivals. MAIN RESULTS: A total of 2664 patients (mean age 69.0 years, 34.9% female sex, 92.5% cancer surgery) were included in the final analysis. MAP < 60 mmHg was adopted as the threshold of intraoperative hypotension. Patients were divided into three groups according to duration under MAP < 60 mmHg (<1 min, 1-10 min, and > 10 min) or area under MAP <60 mmHg (< 1 mmHg⋅min, 1-30 mmHg⋅min, and > 30 mmHg⋅min). After adjusting confounders, duration under MAP < 60 mmHg for > 10 min was associated with a shortened overall survival when compared with the < 1 min patients (adjusted hazard ratio [HR] 1.31, 95% confidence interval [CI] 1.09 to 1.57, P = 0.004); area under MAP < 60 mmHg for > 30 mmHg⋅min was associated with a shortened overall survival when compared with the < 1 mmHg⋅min patients (adjusted HR 1.40, 95% CI 1.16 to 1.68, P < 0.001). Similar associations exist between duration under MAP < 60 mmHg for > 10 min or area under MAP < 60 mmHg for > 30 mmHg⋅min and recurrence-free or event-free survivals. CONCLUSIONS: In older patients who underwent major noncardiac surgery mainly for cancer, intraoperative hypotension was associated with worse overall, recurrence-free, and event-free survivals.

Discovering transformation products of pharmaceuticals in domestic wastewaters and receiving rivers by using non-target screening and machine learning approaches.

Wastewater treatment plants (WWTPs) are an important source of pharmaceuticals in surface water, but information about their transformation products (TPs) is very limited. Here, we investigated occurrence and transformation of pharmaceuticals and TPs in WWTPs and receiving rivers by using suspect and non-target analysis as well as target analysis. Results showed identification of 113 pharmaceuticals and 399 TPs, including mammalian metabolites (n = 100), environmental microbial degradation products (n = 250), photodegradation products (n = 44) and hydrolysis products (n = 5). The predominant parent pharmaceuticals (n = 37) and transformation products (n = 68) were mainly derived from antimicrobials, accounting for 32.7 % and 17.0 %, respectively. The identified compounds were found in the influent (387-428) and effluent (227-400) of WWTPs, as well as upstream (290-451) and downstream (322-416) of receiving rivers, most predominantly from antimicrobials, followed by analgesic and antipyretic drugs. A total of 399 identified TPs were transformed by 110 pathways, of which the oxidation reaction was predominant (27.0 %), followed by photodegradation reaction (10.7 %). Of the 399 TPs, 49 (with lower PNECs) were predicted to be more toxic than their parents. Compounds with potential high risks (hazard quotient >1 and risk index (RI) > 0.1) were found in the WWTP influent (126), effluent (53) and river (61), and the majority were from the antimicrobial and antihypertensive classes. In particular, the potential risks (RI) of TPs from roxithromycin and irbesartan were found higher than those for their corresponding parents. The findings from this study highlight the need to monitor TPs from pharmaceuticals in the environment.

Tumour vasculature at single-cell resolution.

Tumours can obtain nutrients and oxygen required to progress and metastasize through the blood supply1. Inducing angiogenesis involves the sprouting of established vessel beds and their maturation into an organized network2,3. Here we generate a comprehensive atlas of tumour vasculature at single-cell resolution, encompassing approximately 200,000 cells from 372 donors representing 31 cancer types. Trajectory inference suggested that tumour angiogenesis was initiated from venous endothelial cells and extended towards arterial endothelial cells. As neovascularization elongates (through angiogenic stages SI, SII and SIII), APLN+ tip cells at the SI stage (APLN+ TipSI) advanced to TipSIII cells with increased Notch signalling. Meanwhile, stalk cells, following tip cells, transitioned from high chemokine expression to elevated TEK (also known as Tie2) expression. Moreover, APLN+ TipSI cells not only were associated with disease progression and poor prognosis but also hold promise for predicting response to anti-VEGF therapy. Lymphatic endothelial cells demonstrated two distinct differentiation lineages: one responsible for lymphangiogenesis and the other involved in antigen presentation. In pericytes, endoplasmic reticulum stress was associated with the proangiogenic BASP1+ matrix-producing pericytes. Furthermore, intercellular communication analysis showed that neovascular endothelial cells could shape an immunosuppressive microenvironment conducive to angiogenesis. This study depicts the complexity of tumour vasculature and has potential clinical significance for anti-angiogenic therapy.

Models of sepsis-induced acute kidney injury.

Sepsis-induced acute kidney injury (S-AKI) is one of the most serious life-threatening complications of sepsis. The pathogenesis of S-AKI is complex and there is no effective specific treatment. Therefore, it is crucial to choose suitable preclinical models that are highly similar to human S-AKI to study the pathogenesis and drug treatment. In this review, we summarized recent advances in the development models of S-AKI, providing reference for the reasonable selection of experimental models as basic research and drug development of S-AKI.

Constructed Mott-Schottky Heterostructure Catalyst to Trigger Interface Disturbance and Manipulate Redox Kinetics in Li-O2 Battery.

Lithium-oxygen batteries (LOBs) with high energy density are a promising advanced energy storage technology. However, the slow cathodic redox kinetics during cycling causes the discharge products to fail to decompose in time, resulting in large polarization and battery failure in a short time. Therefore, a self-supporting interconnected nanosheet array network NiCo2O4/MnO2 with a Mott-Schottky heterostructure on titanium paper (TP-NCO/MO) is ingeniously designed as an efficient cathode catalyst material for LOBs. This heterostructure can accelerate electron transfer and influence the charge transfer process during adsorption of intermediate by triggering the interface disturbance at the heterogeneous interface, thus accelerating oxygen reduction and oxygen evolution kinetics and regulating product decomposition, which is expected to solve the above problems. The meticulously designed unique structural advantages enable the TP-NCO/MO cathode catalyst to exhibit an astounding ultra-long cycle life of 800 cycles and an extraordinarily low overpotential of 0.73 V. This study utilizes a simple method to cleverly regulate the morphology of the discharge products by constructing a Mott-Schottky heterostructure, providing important reference for the design of efficient catalysts aimed at optimizing the adsorption of reaction intermediates.