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Abstract Macrophages are crucial in the heart’s development, function, and injury. As part of the innate immune system, they act as the first line of defense during cardiac injury and repair. After events such as myocardial infarction or myocarditis, numerous macrophages are recruited to the affected areas of the heart to clear dead cells and facilitate tissue repair. This review summarizes the roles of resident and recruited macrophages in developing cardiovascular diseases. We also describe how macrophage phenotypes dynamically change within the cardiovascular disease microenvironment, exhibiting distinct pro-inflammatory and anti-inflammatory functions. Recent studies reveal the values of targeting macrophages in cardiovascular diseases treatment and the novel bioengineering technologies facilitate engineered macrophages as a promising therapeutic strategy. Engineered macrophages have strong natural tropism and infiltration for cardiovascular diseases aiming to reduce inflammatory response, inhibit excessive fibrosis, restore heart function and promote heart regeneration. We also discuss recent studies highlighting therapeutic strategies and new approaches targeting engineered macrophages, which can aid in heart injury recovery.

Abstract Background Coronary artery calcification is commonly found in patients with type 2 diabetes mellitus (T2DM), which may compromise the diagnostic accuracy of coronary computed tomography angiography (CTA). Computed tomography-derived fractional flow reserve (CT-FFR), which integrates coronary anatomy with functional assessment, holds the potential to become a powerful diagnostic tool for evaluating calcified lesions. Objective We aim to assess the prognostic value of CT-FFR for calcific lesions in patients with T2DM and unstable angina (UA). Methods We conducted a retrospective study involving 3,392 patients who were diagnosed with T2DM and UA who underwent coronary CTA, with at least one visible calcification site. Of those, 1,091 patients and 1,372 vessels were recommended by cardiovascular specialists and completed invasive coronary angiography (ICA) and invasive fractional flow reserve (FFR) measurements. Simultaneously, those patients also underwent CT-FFR measurements and were divided into two groups based on CT-FFR values: one group with CT-FFR > 0.80 and the other with CT-FFR ≤ 0.80. Demographics, clinical data, the diagnostic performance of CT-FFR, analysis of calcified lesions on CTA, and major adverse events during follow-up were recorded. Results The diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the area under the curve (AUC) of CT-FFR were 84.8%, 84.6%, 85.1%, 84.7%, 85.0%, and 84.8%, respectively, per patient, and 82.2%, 80.3.2%, 81.8%, 79.7%, 81.1%, and 82.9% respectively, per vessel. For lesion and calcification characteristics, the degree of stenosis, lesion length, rate of bifurcation lesions, diffusive lesions, occlusion, calcium volume, and coronary artery calcification score (CACS) were significantly higher in the CT-FFR ≤ 0.8 group compared to the CT-FFR > 0.8 group. In contrast, the minimum cross-sectional area was smaller in the CT-FFR ≤ 0.8 group than in the CT-FFR > 0.8 group. Major adverse cardiovascular and cerebrovascular events (MACCE) at the 3-year follow-up was significantly higher in the CT-FFR ≤ 0.8 group compared to the CT-FFR > 0.8 group. The CT-FFR value is an independent predictor of MACCE at the 3-year follow-up. Conclusion CT-FFR demonstrated significant diagnostic performance using invasive FFR as the reference standard and proved to be an important predictive tool for assessing prognosis not only in calcified lesions but also in lesions with a CACS score of zero in patients with T2DM and UA. CT-FFR may serve as a valuable tool for guiding treatment decisions in these patients. Graphical abstract

Abstract Background The hippocampus, with its complex subfields, is linked to numerous neuropsychiatric traits. While most research has focused on its global structure or a few specific subfields, a comprehensive analysis of hippocampal substructures and their genetic correlations across a wide range of neuropsychiatric traits remains underexplored. Given the hippocampus’s high heritability, considering hippocampal and subfield volumes (HASV) as endophenotypes for neuropsychiatric conditions is essential. Methods We analyzed MRI-derived volumetric data of hippocampal and subfield structures from 41,525 UK Biobank participants. Genome-wide association studies (GWAS) on 24 HASV traits were conducted, followed by genetic correlation, overlap, and Mendelian randomization (MR) analyses with 10 common neuropsychiatric traits. Polygenic risk scores (PRS) based on HASV traits were also evaluated for predicting these traits. Results Our analysis identified 352 independent genetic variants surpassing a significance threshold of 2.1 × 10−9 within the 24 HASV traits, located across 93 chromosomal regions. Notably, the regions 12q14.3, 17q21.31, 12q24.22, 6q21, 9q33.1, 6q25.1, and 2q24.2 were found to influence multiple HASVs. Gene set analysis revealed enrichment of neural differentiation and signaling pathways, as well as protein binding and degradation. Of 240 HASV-neuropsychiatric trait pairs, 75 demonstrated significant genetic correlations (P

Abstract Advancements in human-engineered heart tissue have enhanced the understanding of cardiac cellular alteration. Nevertheless, a human model simulating pathological remodeling following myocardial infarction for therapeutic development remains essential. Here we develop an engineered model of myocardial repair that replicates the phased remodeling process, including hypoxic stress, fibrosis, and electrophysiological dysfunction. Transcriptomic analysis identifies nine critical signaling pathways related to cellular fate transitions, leading to the evaluation of seventeen modulators for their therapeutic potential in a mini-repair model. A scoring system quantitatively evaluates the restoration of abnormal electrophysiology, demonstrating that the phased combination of TGFβ inhibitor SB431542, Rho kinase inhibitor Y27632, and WNT activator CHIR99021 yields enhanced functional restoration compared to single factor treatments in both engineered and mouse myocardial infarction model. This engineered heart tissue repair model effectively captures the phased remodeling following myocardial infarction, providing a crucial platform for discovering therapeutic targets for ischemic heart disease.

Abstract Mutations in the nuclear envelope (NE) protein lamin A/C (encoded by LMNA), cause a severe form of dilated cardiomyopathy (DCM) with early-onset life-threatening arrhythmias. However, molecular mechanisms underlying increased arrhythmogenesis in LMNA-related DCM (LMNA-DCM) remain largely unknown. Here we show that a frameshift mutation in LMNA causes abnormal Ca2+ handling, arrhythmias and disformed NE in LMNA-DCM patient-specific iPSC-derived cardiomyocytes (iPSC-CMs). Mechanistically, lamin A interacts with sirtuin 1 (SIRT1) where mutant lamin A/C accelerates degradation of SIRT1, leading to mitochondrial dysfunction and oxidative stress. Elevated reactive oxygen species (ROS) then activates the Ca2+/calmodulin-dependent protein kinase II (CaMKII)-ryanodine receptor 2 (RYR2) pathway and aggravates the accumulation of SUN1 in mutant iPSC-CMs, contributing to arrhythmias and NE deformation, respectively. Taken together, the lamin A/C deficiency-mediated ROS disorder is revealed as central to LMNA-DCM development. Manipulation of impaired SIRT1 activity and excessive oxidative stress is a potential future therapeutic strategy for LMNA-DCM.

Abstract Glycosphingolipids (GSLs) are essential components of cell membranes, particularly enriched in the nervous system. Altered molecular distributions of GSLs are increasingly associated with human diseases, emphasizing the significance of lipidomic profiling. Traditional GSL analysis methods are hampered by matrix effect from phospholipids and the difficulty in distinguishing structural isomers. Herein, we introduce a highly sensitive workflow that harnesses magnetic TiO2 nanoparticle-based selective enrichment, charge-tagging Paternò–Büchi reaction, and liquid chromatography-tandem mass spectrometry. This approach enables mapping over 300 distinct GSLs in brain tissues by defining sugar types, long chain bases, N-acyl chains, and the locations of desaturation and hydroxylation. Relative quantitation of GSLs across multiple structural levels provides evidence of dysregulated gene and protein expressions of FA2H and CerS2 in human glioma tissue. Based on the structural features of GSLs, our method accurately differentiates human glioma with/without isocitrate dehydrogenase genetic mutation, and normal brain tissue.

Accurate, rapid, and automated landslide detection is crucial for early warning, emergency management, and landslide mechanism analysis. Increasingly general-purpose detection models are being deployed for these complex and dynamic tasks involving features that are difficult to characterize. However, these models are computationally expensive and memory-hungry, while the accuracy and detection efficiency remain wanting. To address the above problems, this paper proposes an end-to-end model with high-precision and lightweight design for integrated landslide detection and segmentation. Here, we customized the backbone utilizing the advanced Efficient MOdel (EMO), and further used the linear cheap operation from GhostNet to reduce computational complexity. As a result, the total parameters of our models were reduced by up to 48.13%, compared to the baseline. Building on this, we employed a dynamic detection head with multiple attention mechanisms, and proposed a lightweight attention enhancement module for strengthened multi-scale feature extraction and fusion. The results demonstrate that our model outperforms the baseline on all metrics, achieving an outstanding F1 score of 96.75%.

Background Glioblastoma (GBM) is an aggressive primary brain tumor with a high recurrence rate and poor prognosis. Necroptosis, a pathological hallmark of GBM, is poorly understood in terms of its role in prognosis, tumor microenvironment (TME) alteration, and immunotherapy.Methods & Results We assessed the expression of 55 necroptosis-related genes in GBM and normal brain tissues. We identified necroptosis-stratified clusters using Uni-Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression to establish the 10-gene Glioblastoma Necroptosis Index (GNI). GNI demonstrated significant prognostic efficacy in the TCGA dataset (n = 160) and internal validation dataset (n = 345) and in external validation cohorts (n = 591). The GNI-high subgroup displayed a mesenchymal phenotype, lacking the IDH1 mutation, and MGMT methylation. This subgroup was characterized by significant enrichment in inflammatory and humoral immune pathways with prominent cell adhesion molecules (CD44 and ICAM1), inflammatory cytokines (TGFB1, IL1B, and IL10), and chemokines (CX3CL1, CXCL9, and CCL5). The TME in this subgroup showed elevated infiltration of M0 macrophages, neutrophils, mast cells, and regulatory T cells. GNI-related genes appeared to limit macrophage polarization, as confirmed by immunohistochemistry and flow cytometry. The top 30% high-risk score subset exhibited increased CD8 T cell infiltration and enhanced cytolytic activity. GNI showed promise in predicting responses to immunotherapy and targeted treatment.Conclusions Our study highlights the role of necroptosis-related genes in glioblastoma (GBM) and their effects on the tumor microenvironment and patient prognosis. TheGNI demonstrates potential as a prognostic marker and provides insights into immune characteristics and treatment responsiveness.

The initial contraction of the heart during the embryonic stage necessitates a substantial energy supply, predominantly derived from mitochondrial function. However, during embryonic heart development, mitochondria influence beyond energy supplementation. Increasing evidence suggests that mitochondrial permeability transition pore opening and closing, mitochondrial fusion and fission, mitophagy, reactive oxygen species production, apoptosis regulation, Ca2+ homeostasis, and cellular redox state also play critical roles in early cardiac development. Therefore, this review aims to describe the essential roles of mitochondrial non-energetic function embryonic cardiac development.

In order to elucidate the basic properties of Vigna radiata 7S (Vr7S) globulin genes and their expression patterns during seed growth and development, the physicochemical properties, structural characteristics, protein tertiary structures, phylogenetic relationship and expression profiles of 10 Vr7S globulin genes were studied using bioinformatics and reverse transcription-polymerase chain reaction (RT-PCR). The results showed that the proteins encoded by the Vr7S globulin genes consisted of 246 to 594 amino acid residues, with isoelectric point (pI) ranging from 5.02 to 6.40, and molecular mass ranging from 27.82 to 70.02 kDa. All Vr7S globulin genes contained 3–7 exons, 2–6 introns, and 5–8 conserved motifs. Vr7S B1 had one conserved cupin domain, while the other nine genes contained two cupin domains. Vr7S globulin had four types of tertiary structures including α-helix and β-chain. In the conserved cupin domain, 67 conserved amino acid residues were shared by mung bean and other species, and mung bean 7S globulin genes had the closest homology adzuki bean 7S globulin genes followed by those of French bean, pigeon pea and soybean. The RNA sequencing (RNA-Seq) and RT-PCR expression profiles of mung bean seeds at different development stages showed that the expression level of the Vr7S globulin genes increased with the maturity of mung bean seeds, which was consistent with the expression pattern of 7S globulin genes in other legume species. These results indicated that the Vr7S globulin genes played a positive role in regulating the generation of mung bean seed storage protein. This study may lay a foundation for further analyzing the biological function of the Vr7S globulin genes in the seed development of mung bean.

Abstract 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.

Abstract Tissue engineered heart valves (TEHVs) demonstrates the potential for tissue growth and remodel, offering particular benefit for pediatric patients. A significant challenge in designing functional TEHV lies in replicating the anisotropic mechanical properties of native valve leaflets. To establish a biomimetic TEHV model, we employed melt-electrowriting (MEW) technology to fabricate an anisotropic PCL scaffold. By integrating the anisotropic MEW-PCL scaffold with bioactive hydrogels (GelMA/ChsMA), we successfully crafted an elastic scaffold with tunable mechanical properties closely mirroring the structure and mechanical characteristics of natural heart valves. This scaffold not only supports the growth of valvular interstitial cells (VICs) within a 3D culture but also fosters the remodeling of extracellular matrix of VICs. The in vitro experiments demonstrated that the introduction of ChsMA improved the hemocompatibility and endothelialization of TEHV scaffold. The in vivo experiments revealed that, compared to their non-hydrogel counterparts, the PCL-GelMA/ChsMA scaffold, when implanted into SD rats, significantly suppressed immune reactions and calcification. In comparison with the PCL scaffold, the PCL-GelMA/ChsMA scaffold exhibited higher bioactivity and superior biocompatibility. The amalgamation of MEW technology and biomimetic design approaches provides a new paradigm for manufacturing scaffolds with highly controllable microstructures, biocompatibility, and anisotropic mechanical properties required for the fabrication of TEHVs.

BackgroundLarge-scale prospective cohort studies on diabetic foot ulcers risk factor screening in China are limited. Therefore, this prospective cohort study aimed to explore the predictive risk factors for diabetic foot ulcers to provide clinicians with concise and effective clinical indicators for identifying a high-risk diabetic foot and guiding the prevention of diabetic foot ulcers.MethodsPatients with diabetes who visited the Department of Endocrinology of Peking University First Hospital from October 2017 to December 2018 were selected as research participants by convenience sampling. A total of 968 patients were included. After enrollment, a dedicated person collected and recorded all baseline data. A dedicated telephone follow-up was conducted every 12–24 months to evaluate whether the endpoint event had occurred. All patients were followed up for an average of 61 (57–71) months, with 95% of them followed up for more than 60 months. According to the occurrence of endpoint events, they were divided into the DFU and non-DFU groups. The data between the two groups were analyzed using independent-sample t-test, Wilcoxon rank sum test, and chi square test. We used univariate and multivariate logistic regression analysis to analyze the factors that affected the occurrence of diabetic foot ulcers.Results and conclusionsAfter the 5-year follow-up, the incidence of diabetic foot was 25.83%. Multivariate logistic regression analysis revealed that body mass index (odds ratio: 1.046; 95% confidence interval: 1.001–1.093), abnormal pinprick sensation (odds ratio: 4.138; 95% confidence interval: 1.292–13.255), history of fungal foot infection (odds ratio: 2.287; 95% confidence interval: 1.517–3.448), abnormal 128-Hz tuning fork test (odds ratio: 2.628; 95% confidence interval: 1.098–6.294), and HbA1c≥ 8% (odds ratio: 1.522; 95% confidence interval: 1.014–2.284) were independent predictors of diabetic foot. Our study highlights clinically relevant indicators that may help to prevent the occurrence of diabetic foot and guide timely interventions.

Abstract Calcific Aortic Valve Disease (CAVD) is prevalent among the elderly as the most common valvular heart disease. Currently, no pharmaceutical interventions can effectively reverse or prevent CAVD, making valve replacement the primary therapeutic recourse. Extensive research spanning decades has contributed to the establishment of animal and in vitro cell models, which facilitates a deeper understanding of the pathophysiological progression and underlying mechanisms of CAVD. In this review, we provide a comprehensive summary and analysis of the strengths and limitations associated with commonly employed models for the study of valve calcification. We specifically emphasize the advancements in three-dimensional culture technologies, which replicate the structural complexity of the valve. Furthermore, we delve into prospective recommendations for advancing in vivo and in vitro model studies of CAVD.

Minerals, metallurgy, and other production activities will cause a large number of heavy metal elements to leak into the natural environment. A large number of heavy metal elements have been found in the farmland soil, where the adsorption of plants enhances the enrichment. Here, we have selected a region with three terraces to conduct a whole-area soil sample collection and satellite hyperspectral data processing study to explore the role of terrain in this enrichment process. Five spectral transformation methods and four feature enhancement algorithms were designed, and the content extraction model was established to quantitatively retrieve eight heavy metal elements. The results indicates that the three terraces are the source state, transition state, and stable state of heavy metals respectively with the decrease of elevation; The correlation coefficient of various heavy metal elements exceeds 0.92, and the enrichment pattern is consistent although slope and aspect have no significant correlation with the enrichment of heavy metal elements; Local Cd exceeds 30.00%, Hg exceeds 10 times, and As exceeds 48.30% according to the indicator provisions of Chinese national standard (GB 15618-2018). Such knowledge extends our understanding of the abundance, migration, and enrichment of heavy metals from the perspective of topography, which is crucial for pollution assessment and soil remediation.

In recent years, RS and GIS technologies have played an increasingly important role in various aspects of rainfall induced landslide research. In order to systematically understand their application situation, this paper extensively used various visualization analysis technologies for in-depth analysis of 1,161 documents collected by the WOS data platform in the past 27 years by combining quantitative and qualitative methods. Then, this article focuses on sub domain analysis from four aspects: landslide detection and monitoring, prediction models, sensitivity mapping, and risk assessment. The study found that the number of literature in this field has steadily increased and is expected to continue to rise. This literature review has attracted widespread attention from the academic community, but it is challenging to meet research needs. Frequent and effective cooperation between countries, institutions, and authors is very beneficial for promoting progress in this field. The future development direction is a new intelligent hybrid model that integrates multiple research methods. This study can provide researchers in this field with the core research force, hot topic evolution, and future development trends of future rainfall-induced landslides and contribute to landslide prevention and control decision-making and achieving the United Nations’sustainable development goals.

Abstract Ultrasonic testing (UT) is increasingly combined with machine learning (ML) techniques for intelligently identifying damage. Extracting significant features from UT data is essential for efficient defect characterization. Moreover, the hidden physics behind ML is unexplained, reducing the generalization capability and versatility of ML methods in UT. In this paper, a generally applicable ML framework based on the model interpretation strategy is proposed to improve the detection accuracy and computational efficiency of UT. Firstly, multi-domain features are extracted from the UT signals with signal processing techniques to construct an initial feature space. Subsequently, a feature selection method based on model interpretable strategy (FS-MIS) is innovatively developed by integrating Shapley additive explanation (SHAP), filter method, embedded method and wrapper method. The most effective ML model and the optimal feature subset with better correlation to the target defects are determined self-adaptively. The proposed framework is validated by identifying and locating side-drilled holes (SDHs) with 0.5λ central distance and different depths. An ultrasonic array probe is adopted to acquire FMC datasets from several aluminum alloy specimens containing two SDHs by experiments. The optimal feature subset selected by FS-MIS is set as the input of the chosen ML model to train and predict the times of arrival (ToAs) of the scattered waves emitted by adjacent SDHs. The experimental results demonstrate that the relative errors of the predicted ToAs are all below 3.67% with an average error of 0.25%, significantly improving the time resolution of UT signals. On this basis, the predicted ToAs are assigned to the corresponding original signals for decoupling overlapped pulse-echoes and reconstructing high-resolution FMC datasets. The imaging resolution is enhanced to 0.5λ by implementing the total focusing method (TFM). The relative errors of hole depths and central distance are no more than 0.51% and 3.57%, respectively. Finally, the superior performance of the proposed FS-MIS is validated by comparing it with initial feature space and conventional dimensionality reduction techniques.

The Xiaoxinganling Mountains–Sanjiang Plain region represents a crucial ecological security barrier for the Northeast China Plain and serves as a vital region for national grain production. Over the past two decades, the region has undergone numerous ecological restoration projects. Nevertheless, the combined impact of enhanced vegetation greening and global climate change on the regional hydrological cycle remains inadequately understood. This study employed the distributed hydrological model ESSI-3, reanalysis datasets, and multi-source satellite remote sensing data to quantitatively evaluate the influences of climate change and vegetation dynamics on regional hydrological processes. The study period spans from 2000 to 2020, during which there were significant increases in regional precipitation and leaf area index (p < 0.05). The hydrological simulation results exhibited strong agreement with observed river discharge, evapotranspiration, and terrestrial water storage anomalies, thereby affirming the ESSI-3 model’s reliability in hydrological change assessment. By employing both a constant scenario that solely considered climate change and a dynamic scenario that integrated vegetation dynamics, the findings reveal that: (1) Regionally, climate change driven by increased precipitation significantly augmented runoff fluxes (0.4 mm/year) and water storage components (2.57 mm/year), while evapotranspiration trends downward, attributed primarily to reductions in solar radiation and wind speed; (2) Vegetation greening reversed the decreasing trend in evapotranspiration to an increasing trend, thus exerting a negative impact on runoff and water storage. However, long-term simulations demonstrated that regional runoff fluxes (0.38 mm/year) and water storage components (2.21 mm/year) continue to increase, mainly due to precipitation increments surpassing those of evapotranspiration; (3) Spatially, vegetation greening altered the surface soil moisture content trend in the eastern forested areas from an increase to a decrease. These findings suggested that sub-regional ecological restoration initiatives, such as afforestation, significantly influence the hydrological cycle, especially in areas with higher vegetation greening. Nevertheless, persistent increases in precipitation could effectively mitigate the moisture deficits induced by vegetation greening. The study’s outcomes provide a basis for alleviating concerns regarding potential water consumption risks associated with future ecological restoration and extensive vegetation greening projects, thereby offering scientific guidance for sustainable water resource management.

Abstract A lipidome comprises thousands of lipid species, many of which are isomers and isobars. Liquid chromatography-tandem mass spectrometry (LC-MS/MS), although widely used for lipidomic profiling, faces challenges in differentiating lipid isomers. Herein, we address this issue by leveraging the orthogonal separation capabilities of hydrophilic interaction liquid chromatography (HILIC) and trapped ion mobility spectrometry (TIMS). We further integrate isomer-resolved MS/MS methods onto HILIC-TIMS, which enable pinpointing double bond locations in phospholipids and sn-positions in phosphatidylcholine. This system profiles phospholipids at multiple structural levels with short analysis time (

Crop change detection study is the foundation of agricultural sustainability. The inherent high spectral resolution of hyperspectral images, combined with multi-temporal datasets, facilitates the detection of subtle changes. To enhance the accuracy and applicability of hyperspectral change detection in agricultural scenes, this paper introduces a fast hyperspectral change detection approach for agricultural crops based on low-rank matrix and morphological feature extraction (FLRaMF). The goal is to improve detection precision and computational efficiency of the change detection process. The method initially employs rapid low-rank matrix extraction to separate changing and non-changing pixels in the spectral domain. Subsequently, spatial information is introduced using attribute profiles, restricting spectral anomalies through hyperspectral morphology, which ultimately improves the detection results. This study utilized four hyperspectral change detection datasets in agricultural crop scenarios, optimizing and analyzing parameters. Experimental results and analysis indicate that the FLRaMF method can achieve higher detection accuracy with reduced computation cost in unsupervised, default parameter scenarios when performing agricultural crop change detection tasks.

As a toxic Volatile Organic Pollutant (TVOC), formaldehyde has a toxic effect on microorganisms, consequently inhibiting the biochemical process of formaldehyde wastewater treatment. Therefore, the selective degradation of formaldehyde is of great significance in achieving high-efficiency and low-cost formaldehyde wastewater treatment. This study constructed a heterogeneous Fe-ZSM-5/H2O2 Fenton system f or the selective degradation of target compounds. By immobilizing Fe3+ onto the surface of a ZSM-5 molecular sieve, Fe-ZSM-5 was prepared successfully. XRD, BET and FT-IR spectral studies showed that Fe-ZSM-5 was mainly composed of micropores. The influences of different variables on formaldehyde-selective heterogeneous Fenton degradation performance were studied. The 93.7% formaldehyde degradation and 98.2% selectivity of formaldehyde compared with glucose were demonstrated in the optimized Fenton system after 360 min. Notably, the resultant selective Fenton oxidation system had a wide range of pH suitability, from 3.0 to 10.0. Also, the Fe-ZSM-5 was used in five consecutive cycles without a significant drop in formaldehyde degradation efficiency. The use of reactive oxygen species scavengers indicated that the hydroxyl radical was the primary active species responsible for degrading formaldehyde. Furthermore, great degradation performance was acquired with high concentrations of formaldehyde for this system, and the degradation efficiency was more than 95.0%.

This paper aims to investigate a new method that uses buoyant gas mixed with air to control the floating height of scientific balloons. Firstly, the static characteristics and thermophysical properties of mixed-gas balloons are analyzed. Subsequently, the inflation model and the thermal-dynamic coupled model are established. Furthermore, based on theoretical research, a GUI program is compiled to simulate the ascent of mixed-gas balloons. Finally, flight tests are conducted. As the balloon volume expands to the maximum, the vertical velocity begins to decay and eventually oscillates around 0 m/s, which is consistent with the simulation. In addition, there is a noticeable shift in which the balloon starts to float after climbing to the target altitude, and the difference values between the test and the simulation are less than 350 m. Moreover, the trajectory results are similar to the prediction, and the errors of the end position are less than 2.5 km in horizontal distance. Consequently, this paper provides guidance for balloon-designated ceiling height technology which can allow a single balloon system to be used for tests at multiple heights.

Abstract Introduction Pulmonary infections are frequent in immunocompromised hosts (ICH), and microbial detection is difficult. As a new method, next‐generation sequencing (NGS) may offer a solution. Objectives This study aimed to assess the impact of NGS‐assisted pathogenic detection on the diagnosis, treatment, and outcomes of ICH complicated by pulmonary infection and radiographic evidence of bilateral diffuse lesions. Methods This study enrolled 356 patients with ICH complicated by pulmonary infection that were admitted to Zhongshan Hospital, Fudan University, from November 17, 2017, to November 23, 2018, including 102 and 254 in the NGS and non‐NGS groups, respectively. Clinical characteristics, detection time, rough positive rate, effective positive rate, impact on anti‐infective treatment plan, 30‐day/60‐day mortality, and in‐hospital mortality were compared. Results NGS‐assisted pathogenic detection reduced detection time (28.2 h [interquartile range (IQR) 25.9–29.83 h] vs. 50.50 h [IQR 47.90–90.91 h], P

IntroductionThe distinction between multiple primary lung cancer (MPLC) and intrapulmonary metastasis (IPM) holds clinical significance in staging, therapeutic intervention, and prognosis assessment for multiple lung cancer. Lineage tracing by clinicopathologic features alone remains a clinical challenge; thus, we aimed to develop a multi-omics analysis method delineating spatiotemporal heterogeneity based on tumor genomic profiling.MethodsBetween 2012 and 2022, 11 specimens were collected from two patients diagnosed with multiple lung cancer (LU1 and LU2) with synchronous/metachronous tumors. A novel multi-omics analysis method based on whole-exome sequencing, transcriptome sequencing (RNA-Seq), and tumor neoantigen prediction was developed to define the lineage. Traditional clinicopathologic reviews and an imaging-based algorithm were performed to verify the results.ResultsSeven tissue biopsies were collected from LU1. The multi-omics analysis method demonstrated that three synchronous tumors observed in 2018 (LU1B/C/D) had strong molecular heterogeneity, various RNA expression and immune microenvironment characteristics, and unique neoantigens. These results suggested that LU1B, LU1C, and LU1D were MPLC, consistent with traditional lineage tracing approaches. The high mutational landscape similarity score (75.1%), similar RNA expression features, and considerable shared neoantigens (n = 241) revealed the IPM relationship between LU1F and LU1G which were two samples detected simultaneously in 2021. Although the multi-omics analysis method aligned with the imaging-based algorithm, pathology and clinicopathologic approaches suggested MPLC owing to different histological types of LU1F/G. Moreover, controversial lineage or misclassification of LU2’s synchronous/metachronous samples (LU2B/D and LU2C/E) traced by traditional approaches might be corrected by the multi-omics analysis method. Spatiotemporal heterogeneity profiled by the multi-omics analysis method suggested that LU2D possibly had the same lineage as LU2B (similarity score, 12.9%; shared neoantigens, n = 71); gefitinib treatment and EGFR, TP53, and RB1 mutations suggested the possibility that LU2E might result from histology transformation of LU2C despite the lack of LU2C biopsy and its histology. By contrast, histological interpretation was indeterminate for LU2D, and LU2E was defined as a primary or progression lesion of LU2C by histological, clinicopathologic, or imaging-based approaches.ConclusionThis novel multi-omics analysis method improves the accuracy of lineage tracing by tracking the spatiotemporal heterogeneity of serial samples. Further validation is required for its clinical application in accurate diagnosis, disease management, and improving prognosis.

Water environment health assessment is one of the vital fields closely related to the quality of human life. The change of material contained in water will lead to the reflectance change of hyperspectral remote sensing data. According to this phenomenon, the water quality parameters are calculated to achieve the purpose of water quality monitoring. Series knowledge graphs in this field are drawn after analyzing 564 publications from WOS (Web of Science) and EI (The Engineering Index) databases since 1994 with the support of VOSviewer and CiteSpace. Including statistics of documents publication time, contribution analysis, the influence of publications and journals, and the influence of funding institutions. It is concluded that the research trend of hyperspectral water quality monitoring is the machine learning algorithm based on UAV (Unmanned Aerial Vehicle) hyperspectral instrument data by analyzing scientific research cooperation, keyword analysis, and research hotspots. The whole picture of the research is obtained in this field from four subfields: application scenarios, data sources, water quality parameters, and monitoring algorithms in this paper. It is summarized that the miniaturization, integration, and intelligence of hyperspectral sensors will be the research trend in the next 10 years or even longer. The conclusions have significant reference values for this field.

In-depth structural characterization of lipids provides a new means to investigate lipid metabolism. In this study, we have conducted deep profiling of total fatty acids (FAs) from RAW 264.7 macrophages by utilizing charge-tagging Paternò-Büchi derivatization of carbon-carbon double bond (C=C) and reversed-phase liquid chromatography-tandem mass spectrometry. A series of FAs exhibiting unusual site(s) of unsaturation was unearthed, with their identities being confirmed by observing anticipated compositional alterations upon desaturase inhibition. The data reveal that FADS2 Δ 6-desaturation can generate n-11 C=C in the odd-chain monounsaturated fatty acids (MUFAs) as well as n-10 and n-12 families of even-chain MUFAs. SCD1 Δ 9-desaturation yields n-6, n-8, and n-10 of odd-chain MUFAs, as well as n-5, n-7, and n-9 families of even-chain MUFAs. Besides n-3 and n-6 families of polyunsaturated fatty acids (PUFAs), the presence of n-7 and n-9 families of PUFAs indicates that the n-7 and n-9 isomers of FA 18:1 can be utilized as substrates for further desaturation and elongation. The n-7 and n-9 families of PUFAs identified in RAW 264.7 macrophages are noteworthy because their C=C modifications are achieved exclusively via de novo lipogenesis. Our discovery outlines the metabolic plasticity in fatty acid desaturation which constitutes an unexplored rewiring in RAW264.7 macrophages.

Soil oxides are important diagnostic indicators for soil quality assessment, and their content has a positive effect on adsorption of heavy metals, remediation of pollution, and enhancement of organic matter enrichment. Moreover, soil oxides are affected by multiple environmental factors such as soil pH, geomorphological, and elevation, and their distribution is highly regional. In this study, 421 ground soil samples and 2 hyperspectral satellite data were collected. The content distribution of 8 main oxides in soil, including SiO2, Al2O3, Fe2O3, MgO, CaO, Na2O, K2O, and Corg. were obtained according to the process of data preprocessing, spectral transformation, feature extraction, band combination, and model establishment. The results indicated that the homogenization spectral transformation method is the most suitable; The calculation accuracy of complex spectral characteristic parameters is inferior to that of characteristic bands; The difference model is more suitable for the extraction of soil oxide content in this study area; The average content of SiO2 and CaO shows a decreasing trend with the elevation increasing; The average content of SiO2 and Fe2O3 shows an upward trend with the increase of slope; East is the main geomorphic direction of soil oxide enrichment. SiO2, Al2O3, and MgO are the three soil oxides with the highest correlation. The response relationship between soil oxides, topography and pH is discussed, and the distribution rule of soil oxides and environmental determinants are obtained, which provides a set of technical schemes for digital soil research. This study can extract the content of soil components in a large area, analyze the causes, and provide a new technical scheme for soil investigation and treatment.

Introduction. Copper foam material has various advantages. It has been proved effective in enhanced boiling heat transfer, but also increases pump power consumption. Grooved copper foam is a solution to achieve good balance between boiling heat transfer characteristics and pump power consumption. Material and Methods. Grooveless and grooved copper foam in open space was studied. Copper foam specifications comprised the combination of porosities of 70, 80 and 90%, and pore densities of 90 and 110 PPI. The grooved copper foams have two specifications: 11 and 17 grooves. The corresponding rib widths are 2 and 1 mm, with groove depth 2.9 mm and width 0.6 mm. The flow boiling experimental system of copper foam sample includes four parts: a heating water reservoir, pump, a test section, and a data acquisition system. In the test section, liquid water turns into vapor and carries the heat away from a copper block surface, and then vapor condenses into liquid water in the terminal reservoir. Results. Grooved copper foam samples presented significantly higher efficiency than grooveless ones. Grooved copper foams can increase the critical heat flux and heat transfer coefficient, compared with grooveless ones. Seventeen-grooved samples showed more excellent performance than 11-grooved ones. Visual observation disclosed that the stratified flow pattern dominated in moderate and high heat flux for grooved copper foam with open space. Covering vapor mass was more effective to be formed above 17-grooved samples, compared with 11-grooved ones. It indicated more vigorous boiling behavior occurs in 17-grooved sample. Discussion and Conclusion. The number of grooves has a significant impact on boiling heat transfer. Grooved copper foam samples present a significantly higher critical heat flux and heat transfer coefficient. Structural parameters such as porosity and pore density, play a relatively secondly role in heat transfer argumentation. Visual observation shows there exists a cyclic alternation of flow patterns: bubbly flow, annular flow and mass vapor formation for grooved samples. Forming vapor mass is more effective to be formed in 17-grooved samples, compared to 11-grooved ones. It indicates more vigorous boiling behavior occurs in 17-grooved samples.

The safety of spike-based adenovirus type-5 vectored COVID-19 vaccine is evaluated, showing it neither affects the survival and function of human cardiac cells and engineered heart tissues nor aggravates heart damage in mice after ischemic injury.

A multi-energy (ME) system can coordinate local energy sources and users and optimize the supply of various energy forms, to maximize the comprehensive utilization efficiency of energy. As the scale of the multi-energy system becomes more extensive and the physical connections of different energy forms become diversified, the coupling of various forms of energy becomes closer. Such development has brought significant challenges to safe operations and effective regulation of the system and equipment. However, no efficient and easy-to-use dynamic simulation method is available for multi-energy systems. It has become an urgent problem how to fully use the existing rich models and algorithms of conventional energy systems to construct the dynamic simulations of multi-energy systems. Based on the multi-energy system’s structure, components, and model characteristics, this paper studies the mechanism of cross-energy-form dynamic coupling, proposes the critical techniques of multi-energy hybrid simulation and verifies the effectiveness and accuracy of the methods through case tests.

BackgroundMalignant hypertrophic cardiomyopathy (HCM) phenotypes have potential risks of severe heart failure, fatal arrhythmia, and sudden cardiac death. Therefore, it is critical to predict the clinical outcomes of these patients. It was reported recently that the alpha kinase 3 (ALPK3) gene was involved in the occurrence of HCM. Herein we reported a girl with HCM, while whole-exome sequencing found novel compound heterozygous variants in ALPK3 gene, which identified a potential association.Case presentationWe reported a 14-year-girl who suffered from clinical manifestations of cardiac failure, with sudden cardiac arrest before admission. The heartbeat recovered after cardiopulmonary resuscitation, though she remained unconscious without spontaneous breath. The patient stayed comatose when she was admitted. Physical examination indicated enlargement of the heart boundary. Laboratory results revealed a significant increment of myocardial markers, while imaging demonstrated hypertrophy of the left heart and interventricular septum. Whole-exome sequencing (WES) identified a compound heterozygous variant in ALPK3 gene consisting of c.3907_3922del and c.2200A>T, which was inherited from her parents. Both variants (p.G1303Lfs*28 and p.R734*) were disease-causing evaluated by MutationTaster (probability 1.000). The crystal structure of the complete amino acid sequence is predicted and evaluated by AlphaFold and SWISS-MODEL software (July, 2022), which revealed three domains. Moreover, both variants resulted in a wide protein-truncating variant and damaged protein function. Thus, a novel compound heterozygous variant in ALPK3 associated with HCM was diagnosed.ConclusionWe described a young patient with ALPK3-associated HCM who experienced sudden cardiac arrest. Through WES, we identified a compound heterozygous variant in the ALPK3 gene, c.3907_3922del and c.2200A>T, which were inherited from the patient's parents and resulted in a truncated protein, indirectly causing the symptoms of HCM. In addition, WES provided clues in evaluating potential risks of gene variants on fatal clinical outcomes, and the nonsense and frameshift variants of ALPK3 were related to adverse clinical outcomes in HCM patients, which required implantable cardioverter defibrillator (ICD) timely.

Heart muscle cells exhibit exquisitely organized subcellular features that enable efficient and coordinated heart muscle contraction, but little is known about how it is achieved. Here the authors show that CMYA5 organizes cardiomyocyte calcium release units and aligns them to sarcomeres, leading to abnormal calcium release, cardiac dysfunction, and inability to tolerate pressure overload, when absent.

Abstract Cellular organelles play fundamental roles in almost all cell behaviors. Mitochondria have been reported to be functionally linked to various biological processes, including reprogramming and pluripotency maintenance. However, very little about the role of mitochondria has been revealed in human early development and lineage specification. Here, we reported the characteristics and function of mitochondria during human definitive endoderm differentiation. Using a well-established differentiation system, we first investigated the change of mitochondrial morphology by comparing undifferentiated pluripotent stem cells, the intermediate mesendoderm cells, and differentiated endoderm cells, and found that mitochondria were gradually elongated and matured along differentiation. We further analyzed the expression pattern of mitochondria-related genes by RNA-seq, indicating that mitochondria became active during differentiation. Supporting this notion, the production of adenosine triphosphate (ATP) and reactive oxygen species (ROS) was increased as well. Functionally, we utilized chemicals and genome editing techniques, which could interfere with mitochondrial homeostasis, to determine the role of mitochondria in human endoderm differentiation. Treatment with mitochondrial inhibitors, or genetic depletion of mitochondrial transcription factor A (TFAM), significantly reduced the differentiation efficiency of definitive endoderm. In addition, the defect in endoderm differentiation due to dysfunctional mitochondria could be restored to some extent by the addition of ATP. Moreover, the clearance of excessive ROS due to dysfunctional mitochondria by N-acetylcysteine (NAC) improved the differentiation as well. We further found that ATP and NAC could partially replace the growth factor activin A for definitive endoderm differentiation. Our study illustrates the essential role of mitochondria during human endoderm differentiation through providing ATP and regulating ROS levels, which may provide new insight for metabolic regulation of cell fate determination.

Human health risk assessment of chemicals is essential but often relies on time-consuming and animal and labor-extensive procedures. Here, we develop a population-based, quantitative in vitro to in vivo extrapolation (QIVIVE) approach which depended on cellular effects monitored by in vitro assays, considered chemical internal concentration determined by LC-MS/MS, extrapolated into in vivo target tissue concentration through physiologically based pharmacokinetic (PBPK) modelling, and assessed populational health risk using in silico modelling. By applying this QIVIVE approach to 6:2 chlorinated polyfluorinated ether sulfonate (6:2 Cl-PFESA), as a representative of the emerging pollutants, we find that 6:2 Cl-PFESA disturbed lipid homeostasis in HepG2 cells through enhancement of lipid accumulation and fatty acid β-oxidation, during which miR-93-5p served as a key event towards toxicity and thus, could serve as an efficient toxicity marker for risk assessment; further, the disruption potency of lipid homeostasis of 6:2 Cl-PFESA for the most of studied populations in China might be of moderate concern. Together, our approach improved the reliability of QIVIVE during human health risk assessment, which can readily be used for other chemicals.

Using peripheral blood mononuclear cell (PBMC) reprogramming technology, a human-induced pluripotent stem cell (iPSC) line was produced from a patient who presents classic clinical features of arrhythmogenic right ventricular cardiomyopathy (ARVA) and carries a de novo laminin subunit alpha 2 (LAMA2) heterozygous mutation (NM_000426.3: c.8842G > A, p.G2948S). This mutation was not inherited from his parents, who also present normal cardiac phenotype. This iPSC line demonstrates a normal karyotype. Pluripotency and differentiation capacity has been confirmed in vitro. This cell line can help in efforts to understand the pathogenic mechanism between LAMA2 mutation and ARVC.

Accurate segmentation and detection of rice seedlings is essential for precision agriculture and high-yield cultivation. However, current methods suffer from high computational complexity and poor robustness to different rice varieties and densities. This article proposes 2 lightweight neural network architectures, LW-Segnet and LW-Unet, for high-precision rice seedling segmentation. The networks adopt an encoder–decoder structure with hybrid lightweight convolutions and spatial pyramid dilated convolutions, achieving accurate segmentation while reducing model parameters. Multispectral imagery acquired by unmanned aerial vehicle (UAV) was used to train and test the models covering 3 rice varieties and different planting densities. Experimental results demonstrate that the proposed LW-Segnet and LW-Unet models achieve higher F1-scores and intersection over union values for seedling detection and row segmentation across varieties, indicating improved segmentation accuracy. Furthermore, the models exhibit stable performance when handling different varieties and densities, showing strong robustness. In terms of efficiency, the networks have lower graphics processing unit memory usage, complexity, and parameters but faster inference speeds, reflecting higher computational efficiency. In particular, the fast speed of LW-Unet indicates potential for real-time applications. The study presents lightweight yet effective neural network architectures for agricultural tasks. By handling multiple rice varieties and densities with high accuracy, efficiency, and robustness, the models show promise for use in edge devices and UAVs to assist precision farming and crop management. The findings provide valuable insights into designing lightweight deep learning models to tackle complex agricultural problems.

The study of lipid metabolism relies on the characterization of the lipidome, which is quite complex due to the structure variations of the lipid species. New analytical tools have been developed recently for characterizing fine structures of lipids, with C=C location identification as one of the major improvements. In this study, we studied the lipid metabolism reprograming by analyzing glycerol phospholipid compositions in breast cancer cell lines with structural specification extended to the C=C location level. Inhibition of the lipid desaturase, stearoyl-CoA desaturase 1, increased the proportion of n-10 isomers that are produced via an alternative fatty acid desaturase 2 pathway. However, there were different variations of the ratio of n-9/n-7 isomers in C18:1-containing glycerol phospholipids after stearoyl-CoA desaturase 1 inhibition, showing increased tendency in MCF-7 cells, MDA-MB-468 cells, and BT-474 cells, but decreased tendency in MDA-MB-231 cells. No consistent change of the ratio of n-9/n-7 isomers was observed in SK-BR-3 cells. This type of heterogeneity in reprogrammed lipid metabolism can be rationalized by considering both lipid desaturation and fatty acid oxidation, highlighting the critical roles of comprehensive lipid analysis in both fundamental and biomedical applications.