Reconstruction for beam blockage of lidar based on generative adversarial networks.

Doppler lidar is an active laser remote sensing instrument. However, beam blockage caused by low-altitude obstacles is a critical factor affecting the quality of lidar data. To reconstruct the line of sight velocities (LOSV) in areas with beam blockages and to evaluate the effectiveness of reconstruction results, the LOSV-filling network (LFnet) approach based on generative adversarial networks (GANs) and an evaluation scheme based on the degree of blockage are proposed in this paper. The LFnet comprises two adversarial models. The first adversarial model captures the structural features of LOSV to output the edge map, and the second adversarial fills in the blockage area using the edge map. We have built a packaged dataset consisting of training, validation and test datasets with mask sets. Then the sensitivity of the reconstruction effectiveness with different shielding conditions is studied, to reveal the mechanism of shielding influencing the reconstruction. A series of indicators were used to evaluate the model's performance, including the traditional indicators and the proposed indicator of root mean square error (RMSE). Finally, LFnet was demonstrated in a practical application in an airport. The complete process of an easterly gust front is reconstructed with RMSE less than 0.85 m/s, which has significance for flight safety.

Sequential covariate-adjusted randomization via hierarchically minimizing Mahalanobis distance and marginal imbalance.

In comparative studies, covariate balance and sequential allocation schemes have attracted growing academic interest. Although many theoretically justified adaptive randomization methods achieve the covariate balance, they often allocate patients in pairs or groups. To better meet the practical requirements where the clinicians cannot wait for other participants to assign the current patient for some economic or ethical reasons, we propose a method that randomizes patients individually and sequentially. The proposed method conceptually separates the covariate imbalance, measured by the newly proposed modified Mahalanobis distance, and the marginal imbalance, that is the sample size difference between the 2 groups, and it minimizes them with an explicit priority order. Compared with the existing sequential randomization methods, the proposed method achieves the best possible covariate balance while maintaining the marginal balance directly, offering us more control of the randomization process. We demonstrate the superior performance of the proposed method through a wide range of simulation studies and real data analysis, and also establish theoretical guarantees for the proposed method in terms of both the convergence of the imbalance measure and the subsequent treatment effect estimation.

Covalent Bonding of Salen Metal Complexes with Pyrene Chromophores to Porous Polymers for Photocatalytic Hydrogen Evolution.

The development of low-cost and efficient photocatalysts to achieve water splitting to hydrogen (H2) is highly desirable but remains challenging. Herein, we design and synthesize two porous polymers (Co-Salen-P and Fe-Salen-P) by covalent bonding of salen metal complexes and pyrene chromophores for photocatalytic H2 evolution. The catalytic results demonstrate that the two polymers exhibit excellent catalytic performance for H2 generation in the absence of additional noble-metal photosensitizers and cocatalysts. Particularly, the H2 generation rate of Co-Salen-P reaches as high as 542.5 µmol g-1 h-1, which is not only 6 times higher than that of Fe-Salen-P but also higher than a large amount of reported Pt-assisted photocatalytic systems. Systematic studies show that Co-Salen-P displays faster charge separation and transfer efficiencies, thereby accounting for the significantly improved photocatalytic activity. This study provides a facile and efficient way to fabricate high-performance photocatalysts for H2 production.

High-Throughput Screening and Prediction of Nucleophilicity of Amines Using Machine Learning and DFT Calculations.

Nucleophilic index (NNu) as a significant parameter plays a crucial role in screening of amine catalysts. Indeed, the quantity and variety of amines are extensive. However, only limited amines exhibit an NNu value exceeding 4.0 eV, rendering them potential nucleophiles in chemical reactions. To address this issue, we proposed a computational method to quickly identify amines with high NNu values by using Machine Learning (ML) and high-throughput Density Functional Theory (DFT) calculations. Our approach commenced by training ML models and the exploration of Molecular Fingerprint methods as well as the development of quantitative structure-activity relationship (QSAR) models for the well-known amines based on NNu values derived from DFT calculations. Utilizing explainable Shapley Additive Explanation plots, we were able to determine the five critical substructures that significantly impact the NNu values of amine. The aforementioned conclusion can be applied to produce and cultivate 4920 novel hypothetical amines with high NNu values. The QSAR models were employed to predict the NNu values of 259 well-known and 4920 hypothetical amines, resulting in the identification of five novel hypothetical amines with exceptional NNu values (>4.55 eV). The enhanced NNu values of these novel amines were validated by DFT calculations. One novel hypothetical amine, H1, exhibits an unprecedentedly high NNu value of 5.36 eV, surpassing the maximum value (5.35 eV) observed in well-established amines. Our research strategy efficiently accelerates the discovery of the high nucleophilicity of amines using ML predictions, as well as the DFT calculations.

Highly Stretchable, Transparent, Self-Healing Ion-Conducting Elastomers for Long-Term Reliable Human Motion Detection.

The flexible electronic sensor is a critical component of wearable devices, generally requiring high stretchability, excellent transmittance, conductivity, self-healing capability, and strong adhesion. However, designing ion-conducting elastomers meeting all these requirements simultaneously remains a challenge. In this study, a novel approach is presented to fabricate highly stretchable, transparent, and self-healing ion-conducting elastomers, which are synthesized via photo-polymerization of two polymerizable deep eutectic solvents (PDESs) monomers, i.e., methacrylic acid (MAA)/choline chloride (ChCl) and itaconic acid (IA)/ChCl. The as-prepared ion-conducting elastomers possess outstanding properties, including high transparency, conductivity, and the capability to adhere to various substrates. The elastomers also demonstrate ultra-stretchability (up to 3900%) owing to a combination of covalent cross-linking and noncovalent cross-linking. In addition, the elastomers can recover up to 3250% strain and over 94.5% of their original conductivity after self-healing at room temperature for 5 min, indicating remarkable mechanical and conductive self-healing abilities. When utilized as strain sensors to monitor real-time motion of human fingers, wrist, elbow, and knee joints, the elastomers exhibit stable and strong repetitive electrical signals, demonstrating excellent sensing performance for large-scale movements of the human body. It is anticipated that these ion-conducting elastomers will find promising applications in flexible and wearable electronics.

[Chemical composition and pharmacological effects of Cinnamomum camphora chvar. borneol essential oil: a review].

Cinnamomum camphora chvar. borneol, a rare camphor tree variant recently identified in China, is distinguished by its high concentration of D-borneol, also known as " plant gold" due to its significant value. The essential oil extracted from this variant,rich in monoterpenes and sesquiterpenes, demonstrates a broad spectrum of pharmacological activities, including analgesic, antiinflammatory, antioxidant, cognition-enhancing, anti-bacterial, and insecticidal effects. These properties, underscored by extensive research, highlight the oil's potential in the biomedical, chemical, and food sectors as a valuable commodity. Nonetheless, the safety profile of this valuable oil remains poorly characterized, with its chemical composition and therapeutic efficacy subject to variations in the factors like geographic origin, harvesting timing, part used for extraction, and processing techniques. Such variability poses challenges to its clinical application and hampers the efficient exploitation of this resource. This review synthesizes current studies on C. camphora chvar. borneol essential oil and provides a detailed examination of its chemical and pharmacological profiles. In this study, we discuss existing research gaps and propose strategies for advancing its clinical use and industrial application, aiming to provide a foundational reference for future investigations and the resolution of its commercial and therapeutic challenges.

Improving prediction accuracy of laser-induced shock wave velocity prediction using neural networks.

The velocity of laser-induced shock waves affects the efficiency and efficacy of laser-based processes. The ability to accurately estimate shock wave velocity is critical for optimizing experimental combinations, creating laser-based systems, and assuring desired results. Traditional approaches to predict shock wave velocity involve empirical equations and analytical models based on simplified assumptions. However, these methods often lack accuracy and fail to capture the complex dynamics of laser-matter interactions. To overcome these limitations, we used a combination of an artificial neural network and a genetic algorithm to predict shock wave velocity. In this method, the neural network structure is dynamically designed. The optimization method does this by modifying the neural network's weights and figuring out the network's structure on our behalf. Based on the findings, our suggested technique worked very well; it surpassed other comparison methods by achieving the lowest average errors in terms of RMSE and MAE, which are 4.38 and 3.74, respectively. Moreover, the analysis has shown that our proposed method has a high level of reliability in predicting impulsive wave velocity using a neural network.

Computational models of bone fracture healing and applications: a review.

Fracture healing is a very complex physiological process involving multiple events at different temporal and spatial scales, such as cell migration and tissue differentiation, in which mechanical stimuli and biochemical factors assume key roles. With the continuous improvement of computer technology in recent years, computer models have provided excellent solutions for studying the complex process of bone healing. These models not only provide profound insights into the mechanisms of fracture healing, but also have important implications for clinical treatment strategies. In this review, we first provide an overview of research in the field of computational models of fracture healing based on CiteSpace software, followed by a summary of recent advances, and a discussion of the limitations of these models and future directions for improvement. Finally, we provide a systematic summary of the application of computational models of fracture healing in three areas: bone tissue engineering, fixator optimization and clinical treatment strategies. The application of computational models of bone healing in clinical treatment is immature, but an inevitable trend, and as these models become more refined, their role in guiding clinical treatment will become more prominent.

Multi-Strategy Improved Dung Beetle Optimization Algorithm and Its Applications.

The dung beetle optimization (DBO) algorithm, a swarm intelligence-based metaheuristic, is renowned for its robust optimization capability and fast convergence speed. However, it also suffers from low population diversity, susceptibility to local optima solutions, and unsatisfactory convergence speed when facing complex optimization problems. In response, this paper proposes the multi-strategy improved dung beetle optimization algorithm (MDBO). The core improvements include using Latin hypercube sampling for better population initialization and the introduction of a novel differential variation strategy, termed "Mean Differential Variation", to enhance the algorithm's ability to evade local optima. Moreover, a strategy combining lens imaging reverse learning and dimension-by-dimension optimization was proposed and applied to the current optimal solution. Through comprehensive performance testing on standard benchmark functions from CEC2017 and CEC2020, MDBO demonstrates superior performance in terms of optimization accuracy, stability, and convergence speed compared with other classical metaheuristic optimization algorithms. Additionally, the efficacy of MDBO in addressing complex real-world engineering problems is validated through three representative engineering application scenarios namely extension/compression spring design problems, reducer design problems, and welded beam design problems.

pH­responsive nanozyme cascade catalysis: A strategy of BiVO4 application for modulation of pathological wound microenvironment.

Persistent inflammation and bacterial infection commonly occur during the wound healing process, necessitating urgent development of effective strategies for treating drug-resistant bacterial infections. In this study, bismuth vanadate (BiVO4) was successfully synthesized as an antibacterial agent that promotes wound healing. Through In vitro antibacterial experiments, it was observed that the prepared BiVO4 exhibited excellent performance in catalyzing H2O2 to produce hydroxyl radicals (OH) at a lower concentration (0.2 mg mL-1), resulting in significant antibacterial effects against Gram-negative Extended-Spectrum ß-Lactamases-Producing Escherichia coli (ESBL-E. coli) strains. Furthermore, biosafety tests, cell scratch experiments, and ESBL-E. coli infected wound rat model experiments demonstrated high biocompatibility of BiVO4 with a cell survival rate exceeding 85 %. Additionally, BiVO4 promoted the production of vascular endothelial growth factors and fibroblasts migration while contributing to collagen production, effectively facilitating immune reconstruction at the wound site. By integrating peroxidase (POD)-like under acidic conditions (pH 4) and catalase (CAT)-like catalytic activities at under neutral conditions (pH 7), BiVO4 exhibited the ability to activate free radical sterilization and accelerate wound healing by activating O2. Therefore, our findings provide evidence for a dual enzyme regulatory mechanism involving antibacterial properties and promotion of wound tissue reconstruction for potential application in both antibacterial treatment and wound healing.

Facile construction of copper-doped metal organic framework as a novel visible light-responsive photocatalyst for contaminant degradation.

ABSTRACTMetal-organic frameworks (MOFs) with photocatalytic activity have garnered significant attentions in environmental remediation. Herein, copper-doped zeolitic imidazolate framework-7 (Cu-doped ZIF-7) was synthesized rapidly and easily using a microwave-assisted technique. Various analytical and spectroscopic methods were employed to access the framework, morphology, light absorption, photo-electrochemical and photocatalytic performance of the synthesized materials. Compared to ZIF-7, Cu/ZIF-7 (molar ratio of Cu2+ to Zn2+ is 1:1) demonstrates superior visible light absorption ability, narrower band gap, enhanced charge separation capability, and reduced electron-hole recombination performance. Under visible light irradiation, Cu/ZIF-7 serves as a Fenton-like catalyst and demonstrates exceptional activity for contaminant degradation, while virgin ZIF-7 remains inactive. With the addition of 9.8 mmol H2O2 and exposure to visible light for 30 min, 10 mg of Cu/ZIF-7 can completely decompose RhB solution (10 mg/L, 50 mL). The synergistic effect of the Cu/ZIF-7/H2O2/visible light system is attributed to visible light photocatalysis and Fenton-like reactions. Cu/ZIF-7 demonstrates excellent catalytic performance stability, with only a slight decrease in degradation efficiency from an initial 97.0% to 95.4% over four cycles. Additionally, spin-trapping ESR measurements and active species trapping experiments revealed that h+ and ·OH occupied a significant position for Rhodamine B (RhB) degradation. Degradation intermediate products of Rhodamine B have been identified using UPLC-MS, and the degradation pathways have been proposed and discussed. This work offers a facile and efficient technique for developing MOF-based visible light photocatalysts for water purification.

Urchin-like CO2-responsive magnetic microspheres for highly efficient organic dye removal.

CO2-responsive materials have emerged as promising adsorbents for the remediation of refractory organic dyes-contaminated wastewater without the formation of byproducts or causing secondary pollution. However, realizing the simultaneous adsorption-separation or complete removal of both anionic and cationic dyes, as well as achieving deeper insights into their adsorption mechanism, still remains a challenge for most reported CO2-responsive materials. Herein, a novel type of urchin-like CO2-responsive Fe3O4 microspheres (U-Fe3O4 @P) has been successfully fabricated to enable ultrafast, selective, and reversible adsorption of anionic dyes by utilizing CO2 as a triggering gas. Meanwhile, the CO2-responsive U-Fe3O4 @P microspheres exhibit the capability to initiate Fenton degradation of non-adsorbable cationic dyes. Our findings reveal exceptionally rapid adsorption equilibrium, achieved within a mere 5 min, and an outstanding maximum adsorption capacity of 561.2 mg g-1 for anionic dye methyl orange upon CO2 stimulation. Moreover, 99.8% of cationic dye methylene blue can be effectively degraded through the Fenton reaction. Furthermore, the long-term unresolved interaction mechanism of organic dyes with CO2-responsive materials is deciphered through a comprehensive experimental and theoretical study by density functional theory. This work provides a novel paradigm and guidance for designing next-generation eco-friendly CO2-responsive materials for highly efficient purification of complex dye-contaminated wastewater in environmental engineering.

Development of a risk prediction model for subsequent infection after colonization with carbapenem-resistant Enterobacterales: a retrospective cohort study.

BACKGROUND: Colonization of carbapenem-resistant Enterobacterale (CRE) is considered as one of vital preconditions for infection, with corresponding high morbidity and mortality. It is important to construct a reliable prediction model for those CRE carriers with high risk of infection. METHODS: A retrospective cohort study was conducted in two Chinese tertiary hospitals for patients with CRE colonization from 2011 to 2021. Univariable analysis and the Fine-Gray sub-distribution hazard model were utilized to identify potential predictors for CRE-colonized infection, while death was the competing event. A nomogram was established to predict 30-day and 60-day risk of CRE-colonized infection. RESULTS: 879 eligible patients were enrolled in our study and divided into training (n = 761) and validation (n = 118) group, respectively. There were 196 (25.8%) patients suffered from subsequent CRE infection. The median duration of subsequent infection after identification of CRE colonization was 20 (interquartile range [IQR], 14-32) days. Multisite colonization, polymicrobial colonization, catheterization and receiving albumin after colonization, concomitant respiratory diseases, receiving carbapenems and antimicrobial combination therapy before CRE colonization within 90 days were included in final model. Model discrimination and calibration were acceptable for predicting the probability of 60-day CRE-colonized infection in both training (area under the curve [AUC], 74.7) and validation dataset (AUC, 81.1). Decision-curve analysis revealed a significantly better net benefit in current model. Our prediction model is freely available online at https://ken-zheng.shinyapps.io/PredictingModelofCREcolonizedInfection/ . CONCLUSIONS: Our nomogram has a good predictive performance and could contribute to early identification of CRE carriers with a high-risk of subsequent infection, although external validation would be required.

Molecular mechanisms, targets and clinical potential of berberine in regulating metabolism: a review focussing on databases and molecular docking studies.

Background: Metabolic imbalance is the common basis of many diseases. As natural isoquinoline alkaloid, berberine (BBR) has shown great promise in regulating glucose and lipids metabolism and treating metabolic disorders. However, the related mechanism still lacks systematic research. Aim: To discuss the role of BBR in the whole body's systemic metabolic regulation and further explore its therapeutic potential and targets. Method: Based on animal and cell experiments, the mechanism of BBR regulating systemic metabolic processes is reviewed. Potential metabolism-related targets were summarized using Therapeutic Target Database (TTD), DrugBank, GeneCards, and cutting-edge literature. Molecular modeling was applied to explore BBR binding to the potential targets. Results: BBR regulates the whole-body metabolic response including digestive, circulatory, immune, endocrine, and motor systems through adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR), sirtuin (SIRT)1/forkhead box O (FOXO)1/sterol regulatory element-binding protein (SREBP)2, nuclear factor erythroid 2-related factor (Nrf) 2/heme oxygenase (HO)-1, and other signaling pathways. Through these reactions, BBR exerts hypoglycemic, lipid-regulating, anti-inflammatory, anti-oxidation, and immune regulation. Molecular docking results showed that BBR could regulate metabolism targeting FOXO3, Nrf2, NAD(P)H quinone oxidoreductase 1 (NQO1), glutathione peroxidase (Gpx) 4 and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA). Evaluating the target clinical effects, we found that BBR has the therapeutic potential of anti-aging, anti-cancer, relieving kidney disease, regulating the nervous system, and alleviating other chronic diseases. Conclusion: This review elucidates the interaction between potential targets and small molecular metabolites by exploring the mechanism of BBR regulating metabolism. That will help pharmacologists to identify new promising metabolites interacting with these targets.

Clinical efficacy and molecular mechanism of Chinese medicine in the treatment of autoimmune thyroiditis.

ETHNOPHARMACOLOGICAL RELEVANCE: Autoimmune Thyroiditis (AIT) is a common refractory autoimmune disease of the endocrine system that may eventually lead to complete loss of thyroid function, with subsequent severe effects on the metabolism. Because of the deficiency in current clinical management of AIT, the need for alternative therapies is highlighted. With its multi-component and multi-target characteristics, Chinese medicine has good potential as an alternative therapy for AIT. AIM OF THE STUDY: The aim of this study was to systematically summarize the clinical efficacy and safety evaluation of TCM and its active ingredients in the treatment and regulation of AIT. Additionally, we provide an in-depth discussion of the relevant mechanisms and molecular targets to understand the protective effects of traditional Chinese medicine on AIT and explore new ideas for clinical treatment. MATERIALS AND METHODS: The literature related to "Hashimoto", "autoimmune thyroiditis", "traditional Chinese medicine," and "Chinese herbal medicine" was systematically summarized and reviewed from Web of Science Core Collection, PubMed, CNKI, and other databases. Domestic and international literature were analyzed, compared, and reviewed. RESULTS: An increasing number of studies have demonstrated that herbal medicines can intervene in immunomodulation, with pharmacological effects such as antibody lowering, anti-inflammatory, anti-apoptotic thyroid follicular cells, regulation of intestinal flora, and regulation of estrogen and progesterone levels. The signaling pathways and molecular targets of the immunomodulatory effects of Chinese herbal medicine for AIT may include Fas/FasL, Caspase, BCL-2, and TLRs/MyD88/NF-κB et al. CONCLUSIONS: The use of Chinese herbs in the treatment and management of AIT is clinically experienced, satisfactory, and safe. Future studies may evaluate the influence of herbal medicines on the occurrence and development of AIT by modulating the interaction between immune factors and conventional signaling pathways.

Upregulation of GPR133 expression impaired the phagocytosis of macrophages in recurrent spontaneous miscarriage.

Decidual macrophages are the second-largest immune cell group at the maternal-foetal interface. They participate in apoptotic cell removal, and protect the foetus from microorganisms or pathogens. Dysfunction of decidual macrophages gives rise to pregnancy complications such as preeclampsia and recurrent spontaneous miscarriage (RSM). However, the mechanisms by which decidual macrophages are involved in the occurrence of adverse pregnancy outcomes have not been elucidated. Here we integrated DNA methylation and gene expression data from decidua macrophages to identify potential risk factors related to RSM. GPR133 was significantly hypomethylated and upregulated in decidual macrophages from RSM patients. Further demethylation analysis demonstrated that GPR133 expression in decidual macrophages was significantly increased by 5-Aza-dC treatment. In addition, the influence of GPR133 on the phagocytic ability of macrophages was explored. Phagocytosis was impaired in the decidual macrophages of RSM patients with increased GPR133 expression. Increased GPR133 expression induced by demethylation treatment in the decidual macrophages of healthy control patients led to a significant decrease in phagocytic function. Importantly, knockdown of GPR133 resulted in a significant improvement in the phagocytic function of THP-1 macrophages. In conclusion, the existing studies have shown the influence of GPR133 on the phagocytic function of decidual macrophages and pregnancy outcomes, providing new data and ideas for future research on the role of decidual macrophages in RSM.

The relationship between atrial cardiopathy biomarkers and prognosis of patients with acute ischemic stroke after endovascular treatment.

Thromboembolism is a possible consequence of underlying atrial cardiopathy, which can occur even before the onset of atrial fibrillation. Our objective was to examine the association between biomarkers of atrial cardiopathy and outcomes of acute ischemic stroke (AIS) following endovascular treatment (EVT). We conducted a retrospective study that collected data from patients with AIS who underwent EVT and compared the outcomes between those with and without atrial cardiopathy. Neurological function was assessed using the modified Rankin Scale (mRS), with an mRS score >2 indicating poor function at day 90. Additionally, we evaluated secondary consequences, including symptomatic intracerebral hemorrhage (sICH), early neurological deterioration (END), and malignant cerebral edema (MCE). Our study included 87 patients (77.6 â€‹% male; mean age 60.93 â€‹± â€‹12.47 years). Among these patients, 29 (33.3 â€‹%) had atrial cardiopathy, while the remaining 58 (66.7 â€‹%) did not. In the atrial cardiopathy group, 12 patients (41.4 â€‹%) had poor functional outcomes (mRS>2), compared to 19 (32.8 â€‹%) in the non-atrial cardiopathy group. We observed sICH in 22 (25.3 â€‹%) patients, END in 14 (16.1 â€‹%) patients, MCE in 11 (12.6 â€‹%) patients, and two (2.3 â€‹%) patients who died in the hospital. We found that patients with PTFV1>5000 â€‹µV/ms (OR: 8.39, 95 â€‹% CI: 1.43-105.95, P â€‹= â€‹0.02) and NT-proBNP>250 â€‹pg/mL (OR: 5.09, 95 â€‹% CI: 1.20-27.63, P â€‹= â€‹0.03) had significantly higher risk of END. After adjusting for covariates in the Firth logistic regression, we further found that atrial cardiopathy was significantly associated with END, as revealed by both univariate (OR: 6.31, 95 â€‹% CI: 1.42-59.87, P â€‹= â€‹0.01) and multivariable firth regression models (Modle 1, OR: 7.10, 95 â€‹% CI: 1.57-67.38, P â€‹< â€‹0.01; Modle 2, OR: 7.82, 95 â€‹% CI: 1.69, 76.36, P â€‹< â€‹0.01; Modle 3, OR: 8.59, 95 â€‹% CI: 1.72-91.70, P â€‹< â€‹0.01). Moreover, we observed that atrial cardiopathy was associated with an increased risk of END in AIS patients with large artery atherosclerosis (LAA) receiving EVT. Therefore, clinicians should consider atrial cardiopathy as a possible underlying cause of AIS in their patients. Further investigation is warranted to elucidate the relationship between atrial cardiopathy and AIS's occurrence, progression, and prognosis.

Comparison of pulmonary artery sarcoma and pulmonary thromboembolism according to clinical and computed tomography pulmonary angiography and magnetic resonance imaging characteristics: a single-center retrospective study.

Background: Pulmonary artery sarcoma (PAS) is a very rare malignancy with a poor prognosis; however, its clinical manifestations and imaging findings are often indistinguishable from pulmonary thromboembolism (PTE). We thus aimed to accurately diagnose PAS by comparing the clinical and computed tomography pulmonary angiography (CTPA) and magnetic resonance imaging (MRI) imaging characteristics of PAS and PTE. Methods: This case-control study retrospectively enrolled 20 patients with PAS (from March 2017 to September 2022), 40 patients with central acute PTE, and 40 patients with central chronic PTE (from January 2021 to December 2022) in the China-Japan Friendship Hospital. The following clinical and imaging findings were compared between the three groups: initial symptoms; D-dimer, C-reactive protein, and N-terminal pro B-type natriuretic peptide levels; wall-eclipsing sign (WES); scope of lesion involvement; and morphological characteristics. Signal intensity was also observed on different MRI sequences. Results: The D-dimer level in PAS was significantly lower than that in central acute PTE (P<0.001). The WES was present in 17 cases of PAS (85.0%), which was a greater proportion than that of the central acute PTE and chronic PTE groups (all P values <0.001). The involvement of the pulmonary valve or right ventricular outflow tract was observed in five PAS cases but none of the central acute PTE or chronic PTE cases (all P values =0.001). In 19 PAS cases (95.0%), the lesions grew expansively in the central pulmonary artery. The proximal margin of 18 patients with PAS (90.0%) was bulging or lobulated. Nine cases of PAS (45.0%) showed aneurysm-like dilatation (grape-like sign) of the distal pulmonary artery, representing significantly greater proportion than that of the central acute PTE and chronic PTE groups (all P values <0.001). In 37 patients with central acute PTE (92.5%), the clots were observed to be floating in the pulmonary artery lumen with saddle, tubular or polypoid shape. Eccentric filling defects attached to the pulmonary artery wall were observed in 32 cases of central chronic PTE (80.0%). On MRI, PAS lesions were hyperintense on fat-suppressed T2-weighted imaging and diffusion-weighted imaging, demonstrating heterogeneous enhancement. Conclusions: Comprehensive analysis of the clinical data and imaging features on CTPA and MRI can aid in the accurate differential diagnosis of PAS and PTE.

Ion exchange-assisted surface passivation toward highly stable red-emitting fluoride phosphors for light-emitting diodes.

A facile and environmentally friendly ion exchange-assisted surface passivation (IASP) strategy is presented for synthesizing red emitting Mn4+-activated fluoride phosphors. A substantial, pristine Mn4+-free shell layer, applied as a coating to Mn4+ doped potassium fluorosilicate K2SiF6:Mn4+ (KSFM) phosphors, enhances both water resistance and luminescence efficiency. The stability test of fluoride in water at ambient temperature and boiling water demonstrates that IASP-treated KSFM phosphors are highly water resistant. Furthermore, both the negative thermal temperature (NTQ) fitting results and the photoluminescence (PL) decay confirm that the IASP process effectively passivates surface defects, leading to enhanced luminescence performance. The maximum internal quantum yield (QYi) of the IASP-KSFM phosphor is 94.24%. A white LED realized a high color rendering index (CRI) of 93.09 and luminous efficiency (LE) of 149.48 lm/W. This work presented a novel technique for the development of stable fluoride phosphors and has the potential to increase the use of KSFM phosphors in plant supplementary lighting systems and white light-emitting diodes.

Podocyte programmed cell death in diabetic kidney disease: Molecular mechanisms and therapeutic prospects.

Diabetic kidney disease (DKD) is the primary cause of chronic kidney and end-stage renal disease. Glomerular podocyte loss and death are pathological hallmarks of DKD, and programmed cell death (PCD) in podocytes is crucial in DKD progression. PCD involves apoptosis, autophagy, ferroptosis, pyroptosis, and necroptosis. During DKD, PCD in podocytes is severely impacted and primarily characterized by accelerated podocyte apoptosis and suppressed autophagy. These changes lead to a gradual decrease in podocyte numbers, impairing the glomerular filtration barrier function and accelerating DKD progression. However, research on the interactions between the different types of PCD in podocytes is lacking. This review focuses on the novel roles and mechanisms of PCD in the podocytes of patients with DKD. Additionally, we summarize clinical drugs capable of regulating podocyte PCD, present challenges and prospects faced in developing drugs related to podocyte PCD and suggest that future research should further explore the detailed mechanisms of podocyte PCD and interactions among different types of PCD.