Search

In recent years, significant advances in unmanned aerial vehicle (UAV) technology and hyperspectral remote sensing have spurred rapid and innovative developments in UAV-based hyperspectral image (HSI) classification across a range of fields, including environmental monitoring, precision agriculture, forest health assessment, and disaster management. Compared to spaceborne platforms, the spectra of ground objects observed by UAV platforms exhibit notable variations, presenting more pronounced challenges for accurate classification. This article provides an in-depth and systematic review of UAV HSI classification techniques, systematically examining the evolution from traditional machine learning approaches, such as sparse coding, compressed sensing, and kernel methods, to cutting-edge deep learning frameworks, including convolutional neural networks, Transformer models, recurrent neural networks, graph convolutional networks, generative adversarial networks, and hybrid models. Although traditional methods demonstrate effectiveness in certain scenarios, their limitations become increasingly apparent when dealing with high-dimensional, nonlinear spectral data. In contrast, deep learning-based models excel at capturing intricate relationships between spectral and spatial features, significantly boosting classification accuracy and emerging as the dominant paradigm in the field. The WHU-Hi hyperspectral remote sensing dataset is utilized as a case study to elucidate the advantages and limitations of various deep learning methods through rigorous qualitative and quantitative comparisons. The potential of UAV hyperspectral image classification techniques in addressing high-dimensional data and complex scenarios is also thoroughly described. Furthermore, this article delves into cutting-edge research trends, such as lightweight model development, hyperspectral large models, multisource data fusion, and model interpretability, while also highlighting future trends for UAV hyperspectral remote sensing classification technology, particularly in real-time monitoring and intelligent applications.

Under special conditions such as night, rain, and fog, visible light imaging technology often performs poorly, while radar and other imaging technologies are limited due to their high costs. Infrared imaging technology, based on the principle of thermal radiation, can provide clear imaging effects under these extreme conditions and has a relatively low cost of use. Therefore, it has been widely applied in various fields, including military, medical, industrial, and agricultural applications. However, due to the limitations of infrared wavelengths and imaging technology, traditional infrared imaging devices struggle to capture rich texture information, leading to infrared images that lack texture details and have low resolution, which significantly restricts the further research and application of infrared imaging technology in various fields. In recent years, with the widespread attention to infrared imaging technology, researchers have proposed various new infrared image enhancement techniques. Despite this, the lack of texture information in ordinary infrared images leads to the enhancement effect of existing technologies being unsatisfactory. Therefore, we have conducted a systematic investigation of the research advancements in the field of infrared image enhancement, encompassing infrared image enhancement methods, related datasets, and evaluation metrics, with the aim of exploring a research solution that could potentially break through current technological limitations. Based on these investigations, we have evaluated the performance of various representative infrared image enhancement methods, with the hope of providing a reference for future research. In addition, this article also provides a comprehensive introduction to the potential applications of infrared image enhancement technology and discusses significant research directions for the future.

Currently, RGB-thermal (RGB-T) object detection algorithms have demonstrated excellent performance, but issues such as modality failure caused by fog, strong light, sensor damage, and other conditions can significantly impact the detector's performance. This article proposes a multimodal object detection method named diffusion enhanced object detection network (DENet), aiming to address modality failure problems caused by nonroutine environments, sensor anomalies, and other factors, while suppressing redundant information in multimodal data to improve model accuracy. First, we design a multidimensional incremental information generation module based on a diffusion model, which reconstructs the unstable information of RGB-T images through the reverse diffusion process using the original fusion feature map. To further address the issue of redundant information in existing RGB-T object detection models, a redundant information suppression module is introduced, minimizing cross-modal redundant information based on mutual information and contrastive loss. Finally, a kernel similarity-aware illumination module (KSIM) is introduced to dynamically adjust the weighting of RGB and thermal features by incorporating both illumination intensity and the similarity between modalities. KSIM can fine-tune the contribution of each modality during fusion, ensuring a more precise balance that improves recognition performance across diverse conditions. Experimental results on the DroneVehicle and VEDAI datasets show that DENet performs outstandingly in multimodal object detection tasks, effectively improving detection accuracy and reducing the impact of modality failure on performance.

Multitemporal remote sensing images offer multiple views of Earth observation, enabling the integration of temporal information to effectively mitigate issues caused by clouds, shadows, seasonal changes, and atmospheric reflection. This integration significantly reduces the uncertainty and noise of images, facilitating a more comprehensive and accurate extraction of essential ground object features. However, most land cover classification models based on deep learning focus on interpreting single-temporal remote sensing images, and multitemporal remote sensing datasets are relatively scarce, leading to challenges in model training. To address these issues, this article proposes a cross-temporal self-supervised learning method with superpixel mask (CTS2L-sm) for multitemporal land cover classification. Specifically, we design a superpixel-based masking strategy to replace the fixed-size patch masking strategy used in masked image modeling (MIM), which prevents the complete occlusion of small-scale remote sensing scenes and more effectively preserves structural information. To further enhance the integration of multitemporal information, we introduce a cross-temporal attention module (CTAM) in both forward and backward to extract cross-temporal features. The resulting multitemporal denoised homogeneous features, when fused with each temporal feature, significantly improve classification accuracy. CTS2L-sm combines these denoised homogeneous features extracted by CTAM with single-temporal features and simultaneously reconstructs the original remote sensing images across all temporal, extending the MIM strategy from single-temporal to multitemporal self-supervised training. Experimental results on the WUSU and FUSU datasets demonstrate the effectiveness and superiority of the proposed CTS2L-sm compared to several state-of-the-art methods.

Abstract Objective Neuroendocrine cervical carcinoma (NECC) is a rare but highly aggressive tumor. The clinical management of NECC follows neuroendocrine neoplasms and cervical cancer in general. However, the diagnosis and prognosis of NECC remain dismal. The aim of this study was to identify a specific protein signature for the diagnosis of NECC. Methods Protein and gene expression data for NECC and other cervical cancers were retrieved or downloaded from self-collected samples or public resources. Eleven machine-learning algorithms were packaged into 66 combinations, of which we selected the optimal algorithm, including randomForest, SVM-RFE, and LASSO, to select key NECC specific dysregulated proteins (kNsDEPs). The diagnostic effect of kNsDEPs was validated by a set of predictive models and immunohistochemical staining method. The dysregulation patterns of kNsDEPs were further investigated in other neuroendocrine carcinomas. Results Our results showed that NECC displays distinctive biological characteristics, such as HPV18 infection, and exhibits unique molecular features, particularly an enrichment in cytoskeleton-related functions. Furthermore, secretagogin (SCGN), adenylyl cyclase-associated protein 2 (CAP2), and calcyclin-binding protein (CACYBP) were identified as kNsDEPs. These kNsDEPs play a central role in cytoskeleton protein binding and showcase robust diagnostic ability and specificity for NECC. Moreover, the concurrent upregulation of SCGN and CACYBP, along with the downregulation of CAP2, represents a unique feature of NECC, distinguishing it from other neuroendocrine carcinomas. Conclusions This study uncovers the significance of kNsDEPs and elucidates their regulated networks in the context of NECC. It highlights the pivotal role of kNsDEPs in NECC diagnosis, thus offering promising prospects for the development of diagnostic biomarkers for NECC.

Proteins are essential macromolecules that perform functions according to their conformational dynamics. Studying the conformational changes induced by protein mutations is the standard approach used to understand the mechanisms underlying mutation-related physiological and pathological processes. To enhance efficiency and decrease the expense of biological experiments, we introduce a method to generate mutated proteins through adversarial attacks on the AlphaFold2 (AF2) model. We explored the structure change of adversarial protein sequences predicted by AF2 compared to the wild type protein’s structure. CASP14 experiments indicated that altering only three residues via replacement, deletion, or insertion led to a 46.61 points difference in AF2’s predictions, according to the Local Distance Difference Test (lDDT). We applied this method to the transmembrane lipid transporter SPNS2 to identify crucial residues and suggest potential alternative conformations, thereby streamlining the experimental phase in structure determination and mechanistic studies.

Abstract To explore the association between 25-hydroxy vitamin D [25-(OH)-D], interleukin-4 (IL-4), and interferon-γ (IFN-γ) in children with Mycoplasma pneumoniae (MP) infection-related asthma. Logistic analysis was conducted to compare general data in MP asthma and MP non-asthma groups. The level of 25-(OH)-D, IL-4, and IFN-γ were detected and compared between groups. Moreover, the receiver operating characteristic curve (ROC) was applied to test the predictive value of each variable. The results of logistic regression analysis demonstrated that recurrent upper respiratory tract infections and collective living are related to the incidence of MP infection whether with asthma or without asthma. IL-4 and IFN-γ in MP asthma group were significantly higher than those in MP non-asthma group and control group (p

AIM: To investigate the underlying factors by establishing a new paradigm for assessing control ability under stereopsis testing conditions. METHODS: This was a prospective observational study. We evaluated the control ability of intermittent exotropia (IXT) patients in three conditions: natural 2D optotype viewing, 2D optotype viewing with polarized glasses, and 3D optotype viewing with polarized glasses. Recording with a smartphone, we captured videos to analyze the accurate time of spontaneous exodeviation and subsequent realignment before and after breaking fusion. Additionally, the correlation of stereopsis were also analyzed. RESULTS: A total of 48 patients (age range: 4-33y; 54.17% male) participated in the study. When viewing 3D optotypes with polarized glasses, their median control scores were 1 (interquartile range, 0-4) at distance and 0 (0-1) at near. These scores were significantly better than those observed under natural viewing conditions, which were 2.5 (1-5) at a distance and 1 (0-3) at near (Friedman test, P=0.049). Furthermore, those subjects who exhibited exophoria (realignment within 2 seconds) while viewing 3D optotypes with polarized glasses were more likely to have measurable stereo vision (Kendall's τb=-0.344, P=0.018). CONCLUSION: IXT patients exhibit enhanced control ability when using polarized glasses to view 3D optotypes, notably improving realignment capabilities. This expands our understanding of current tests and offers a potentially sensitive method for assessing IXT severity.

Abstract Non-small cell lung cancer (NSCLC) constitutes a significant portion of lung cancers and cytotoxic drugs (e.g. cisplatin) are currently the first-line treatment. However, NSCLC has developed resistance to this drug, which limits the therapeutic effect and thus affects prognosis. NSCLC sc-RNA-seq data were downloaded from the GEO database and Ku Leuven Laboratory for Functional Epigenetics, and bulk RNA-seq data were obtained from the TCGA database. The “Seurat” package was employed for scRNA-seq data processing, and the uniform manifold approximation and projection (UMAP) were applied for downscaling and cluster identification. Use the FindAllMarkers function to find differential genes (DEGs) for tumor stem cells. Then, we performed univariate regression analyses on the DEGs to identify potential prognostic genes. We created a machine learning framework based on potential prognostic genes, which combines 10 machine learning methods and their 101 combinations to get the optimal prognostic risk model. The model was evaluated in the training set and validation set. A nomogram was developed to provide physicians with a quantitative tool for prognosis prediction. Finally, we evaluated the expression and functionality of SLC2A1. We discovered 22 cell clusters containing 218379 cells by examining single-cell RNA sequencing datasets (GSE148071, KU_lom, GSE131907, GSE136246, GSE127465). Tumour cells were isolated for subpopulation analysis and 162 differential genes from SOX2_cancer were obtained. After univariate Cox analysis, we found 23 genes with prognostic potential prognostic value and utilized them to develop 101‑combination machine learning computational framework. We eventually picked the best performing ‘StepCox[both] + RSF’, which includes 8 genes. The model has a relatively high prediction accuracy in both TCGA and GEO datasets. In in vitro investigations, targeted suppression of the SLC2A1 gene resulted in significant reductions in proliferation, invasion and migration in A549 cells. In addition, a significant reduction in cisplatin resistance was seen in A549/DDP cells. The outcomes demonstrated the precision and credibility of the prognostic model for NSCLC, highlighting its potential significance in the treatment and prognosis of individuals affected by this disease. SLC2A1 may become a promising prognostic marker and a potential therapeutic target, offering valuable insights to inform clinical treatment decisions.

Abstract Purpose Lung adenocarcinoma (LUAD) significantly contributes to cancer-related mortality worldwide. The heterogeneity of the tumor immune microenvironment in LUAD results in varied prognoses and responses to immunotherapy among patients. Consequently, a clinical stratification algorithm is necessary and inevitable to effectively differentiate molecular features and tumor microenvironments, facilitating personalized treatment approaches. Methods We constructed a comprehensive single-cell transcriptional atlas using single-cell RNA sequencing data to reveal the cellular diversity of malignant epithelial cells of LUAD and identified a novel signature through a computational framework coupled with 10 machine learning algorithms. Our study further investigates the immunological characteristics and therapeutic responses associated with this prognostic signature and validates the predictive efficacy of the model across multiple independent cohorts. Results We developed a six-gene prognostic model (MYO1E, FEN1, NMI, ZNF506, ALDOA, and MLLT6) using the TCGA-LUAD dataset, categorizing patients into high- and low-risk groups. This model demonstrates robust performance in predicting survival across various LUAD cohorts. We observed distinct molecular patterns and biological processes in different risk groups. Additionally, analysis of two immunotherapy cohorts (N = 317) showed that patients with a high-risk signature responded more favorably to immunotherapy compared to those in the low-risk group. Experimental validation further confirmed that MYO1E enhances the proliferation and migration of LUAD cells. Conclusion We have identified malignant cell-associated ligand–receptor subtypes in LUAD cells and developed a robust prognostic signature by thoroughly analyzing genomic, transcriptomic, and immunologic data. This study presents a novel method to assess the prognosis of patients with LUAD and provides insights into developing more effective immunotherapies.

Background: Osteocytes are the main stress-sensing cells in bone. The substances secreted by osteocytes under mechanical loading play a crucial role in maintaining body homeostasis. Osteocytes have recently been found to release exosomes into the circulation, but whether they are affected by mechanical loading or participate in the regulation of systemic homeostasis remains unclear. Methods: We used a tail-suspension model to achieve mechanical unloading on osteocytes. Osteocyte-specific CD63 reporter mice were used for osteocyte exosome tracing. Exosome detection and inhibitor treatment were performed to confirm the effect of mechanical loading on exosome secretion by osteocytes. Co-culture, GW4869 and exosome treatment were used to investigate the biological functions of osteocyte-derived exosomes on brown adipose tissue (BAT) and primary brown adipocytes. Osteocyte-specific Dicer KO mice were used to screen for loading-sensitive miRNAs. Dual luciferase assay was performed to validate the selected target gene. Results: Firstly, we found the thermogenic activity was increased in BAT of mice subjected to tail suspension, which is due to the effect of unloaded bone on circulating exosomes. Further, we showed that the secretion of exosomes from osteocytes is regulated by mechanical loading, and osteocyte-derived exosomes can reach BAT and affect thermogenic activity. More importantly, we confirmed the effect of osteocyte exosomes on BAT both in vivo and in vitro. Finally, we discovered that let-7e-5p contained in exosomes is under regulation of mechanical loading and regulates thermogenic activity of BAT by targeting Ppargc1a. Conclusion: Exosomes derived from osteocytes are loading-sensitive, and play a vital role in regulation on BAT, suggesting that regulation of exosomes secretion can restore homeostasis. The translational potential of this article: This study provides a biological rationale for using osteocyte exosomes as potential agents to modulate BAT and even whole-body homeostasis. It also provides a new pathological basis and a new treatment approach for mechanical unloading conditions such as spaceflight.

Abstract Purpose Recent studies have increasingly linked Ephrin receptor B2 (EPHB2) to cancer progression. However, comprehensive investigations into the immunological roles and prognostic significance of EPHB2 across various cancers remain lacking. Methods We employed various databases and bioinformatics tools to investigate the impact of EPHB2 on prognosis, immune infiltration, genome instability, and response to immunotherapy. Validation of the correlation between EPHB2 expression and M2 macrophages included analyses using bulk and single-cell transcriptomic datasets, spatial transcriptomics, and multi-fluorescence staining. Moreover, we performed cMap web tool to screen for EPHB2-targeted compounds and assessed their potential through molecular docking and dynamics simulations. Additionally, in vitro validation using lung adenocarcinoma (LUAD) cell lines was conducted to confirm the bioinformatics predictions about EPHB2. Results EPHB2 dysregulation was observed across multiple cancer types, where it demonstrated significant diagnostic and prognostic value. Gene Set Enrichment Analysis (GSEA) indicated that EPHB2 is involved in enhancing cellular proliferation, invasiveness of cancer cells, and modulation of the anti-cancer immune response. Furthermore, it is emerged as a pan-cancer marker for M2 macrophage infiltration, supported by integrated analyses of transcriptomics and multiple fluorescence staining. In LUAD cells, knockdown of EPHB2 expression led to a decrease in both cell proliferation and migratory activity. Conclusion EPHB2 expression may serve as a pivotal indicator of M2 macrophage infiltration, offering vital insights into tumor dynamics and progression across various cancers, including lung adenocarcinoma, highlighting its significant prognostic and therapeutic potential for further exploration.

Purpose: To investigate the characteristics of horizontal rectus muscle insertion sites in patients with infantile esotropia (IE) and acute acquired concomitant esotropia (AACE). Methods: The medical records of 166 IE patients and 261 AACE patients who underwent horizontal rectus muscle surgeries were reviewed retrospectively, including age at surgery, spherical equivalent (SE), and angle of esodeviation at near and distance. The limbus-insertion distances (LID) and widths of the medial rectus (MR) and lateral rectus (LR) muscles were measured intraoperatively using a caliper. The insertion parameters and clinical features were compared between different ages and types of esotropia, and a correlation analysis was performed between these variables. Results: In IE patients under 12 years old, the MR LID was positively correlated with age, whereas the LR LID was negatively correlated with the angle of esodeviation at distance. In IE patients over 12 years old, the LR width was negatively correlated with the angle of esodeviation at near. In AACE patients, the MR LID was negatively correlated with the angle of esodeviation at distance, whereas the LR width was negatively correlated with the SE. Conclusions: The LID and width of the horizontal rectus muscle insertions were not significantly different in age-matched patients with IE and AACE. In IE patients, the LR insertion parameters were correlated with the angle of esodeviation, but in AACE patients, the MR LID was correlated with the angle of esodeviation. The clinical significance of these findings still needs to be investigated further.

BackgroundFluticasone propionate is a synthetic trifluoro-substituted glucocorticoid, a highly selective glucocorticoid receptor agonist. Fluticasone propionate nebuliser suspensions is an inhaled corticosteroid with the low systemic bioavailability which provides a low risk (benefit outcome without the adverse effects that accompany systemically administered corticosteroids), referred as a first-line preventive agent for patients with persistent asthma. China has become one of the countries with the highest asthma mortality rate in the world in the past years. It urgently needs good generic drugs to help ease patients’ burden and improve their quality of life.ObjectiveThe primary objective of this study was to evaluate the bioequivalence of fluticasone propionate nebuliser suspensions between test formulation (generic product) and reference formulation (original product, Flixotide Nebules®) with the pharmacokinetic parameters as the endpoint indicators and the secondary objective was to evaluate the safety of two inhalated fluticasone propionate nebuliser suspensions under the condition of fasting in healthy Chinese subjects.MethodsThe bioequivalence study was conducted with a single-center, randomized, open-label, single-dose, two sequences, two-period crossover design. 24 healthy subjects were randomly assigned into T-R and R-T sequence groups with 12 patients in each group. The subjects were administered 1 mg (2 mL:0.5 mg,plastic ampoules) of generic fluticasone propionate nebuliser suspension as a test formulation or Flixotide Nebules® as reference formulation and cross administration after sufficient washout period (5 days) for the second period study. The blood sample was collected at predetermined time points up to 48 h and the plasma concentration of fluticasone propionate was determined by HPLC-MS/MS in healthy subjects after inhalation of test or reference formulation. The non-compartment model method (NCA module) of the WinNonlin® software (version 8.3) was used to calculate the pharmacokinetic parameters (Cmax, AUC0-t, AUC0-∞) between the test formulation and the reference formulation were within the predefined range of 80.00% and 125.00%, bioequivalence of both formulations was demonstrated.ResultsThe 90% confidence intervals of the T/R ratio of the geometric mean of Cmax, AUC0-t, and AUC0-∞ for both formulations were 90.24%–112.68%, 96.99%–112.27% and 96.41%–111.59% respectively, which were all within the bioequivalent range of 80%–125%. No severe, suspicious or unexpected serious adverse reactions were reported.ConclusionThe test and reference formulations of fluticasone propionate nebuliser suspension were pharmacokinetic bioequivalent and were well tolerated and safe in all subjects.

Dendrite growth and detrimental parasitic side reactions at the anode–electrolyte interface severely restrain the reversibility and cyclability of aqueous zinc‐ion batteries. Due to the lowest surface energy in Zn metal with a hexagonal close‐packed structure, (002) facet can effectively alleviate these side effects. In contrast to several existing works on (002) texturization, single‐crystalline Zn successfully grown using a Bridgman method in this work offers a fundamental understanding on this issue. The perfect atomic arrangement of the low‐surface‐energy (002) cleavage planes, without any grain boundaries, not only kinetically enables an epitaxial deposition inhibiting dendrite formation but also thermodynamically endows the most stable state restraining the side reactions. As a result, the single‐crystalline Zn(002) anode demonstrates a cycling stability over 4800 h (6.7 month) at 2 mA cm−2 in symmetric batteries. Zn(002)//Cu asymmetric batteries achieve a high average Coulombic efficiency of 99.92% over 500 cycles at 10 mA cm−2, enabling a fundamental demonstration of interface engineering for advancing batteries.

Diabetic nephropathy (DN) poses a significant risk to individuals with diabetes. Inflammation plays a crucial role in DN pathogenesis. Lycorine hydrochloride (LH) is derived from Lycoris radiata (L'Hér.). This herb has been identified as a potent anti-inflammatory molecule. Further studies indicated that LH displayed therapeutic potential against metabolic disorders, renal dysfunction, and fibrosis in a high-fat diet and streptozotocin-induced (HFD/STZ)-induced DN mouse model. Mechanistically, LH mitigated renal inflammation in DN mice by targeting NF-κB pathways and the NLRP3 inflammasome verified by in vivo study. In vitro, LH inhibited NLRP3 inflammasome activation induced by nigericin (Ng), monosodium urate (MSU), and ATP, reduced caspase-1 activation, and IL-1β release. Additionally, LH suppressed the NF-κB IS-induced activation, prevented nuclear translocation of NF-κB, and subsequently reduced the expression of downstream proteins COX2 and iNOS. Collectively, these results indicated that LH primarily improved hyperglycemia-induced renal function by reducing inflammation by targeting NF-κB and NLRP3 inflammasome, implying it is a promising therapeutic agent for DN.

ABSTRACTCoarse – and fine-grained bimodal-structures in a Al-Mg base alloy with rare earth elements of Sc/Zr is produced due to the ultrafast nonequilibrium solidification occurs in laser-induced molten pools during laser powder bed fusion (LPBF) additive manufacturing. A novel high-fidelity cellular automaton (CA) algorithm incorporating numerical calculations of molt-pool temperature fields elucidates the formation and evolution of the bimodal-structure. Subsequent heat treatment induces precipitation of Al3(Sc/Zr) particles within the grains, synergistically enhancing strength and plasticity of the LPBF-processed alloy. The crystal plastic finite element method (CPFEM) is used to reveal the synergistic effect between the strength and plasticity during the material tensile procedure. The bimodal-structure exhibits good fatigue resistance but intriguing anisotropy under low stress cyclic loading. It is proved that differentiated distribution patterns relative to the principal stress direction of the bimodal-structure have a significant influence on its fatigue performance. Numerical evolutionary of the bimodal grain deformation reflects this phenomenon.

Trifunctionalization serves as an efficient method for rapidly enhancing molecular complexity by incorporating three functional groups from simple, readily available raw materials. Herein, we describe an electrochemical trifunctionalization protocol for allylarenes that enables the synthesis of a diverse range of dibromoacetoxylated and trihalogenated products. Further gram-scale synthesis and divergent transformation of products demonstrate potential application in the pharmaceutical industry. Mechanistic studies reveal the process involves a cascade oxidative difunctionalization of CC bond and oxidative functionalization of benzylic C–H bond.

Highlights Fundamental principles for designing synergistic composite catalysts are reviewed. The synergistic effect between various active sites, promoting electrocatalytic performance in different reactions are highlighted. The challenges and perspectives for multiple active sites catalysts are discussed.

Abstract Background Advanced maternal age may affect the intrauterine environment and increase the risk of neurodevelopmental disorders in offspring. Thyroid hormones are critical for fetal neurological development but whether maternal age influences fetal thyroid hormone levels in euthyroid mothers is unknown. Objective This study evaluated the association between cord blood thyroid hormones and maternal age, fetal sex, maternal thyroid function, and other perinatal factors. Methods The study population consisted of 203 healthy women with term singleton pregnancies who underwent elective cesarean section. Maternal levels of free T3 (fT3), free T4 (fT4) and TSH before delivery, and cord levels of fT3, fT4 and TSH were measured. Spearman’s correlation coefficient and multiple linear regression analyses were performed to determine the correlation between cord thyroid hormone parameters and maternal characteristics. Results There were no significant differences in maternal serum or cord blood thyroid hormone levels between male and female births. In multivariate linear regression analysis, maternal age and maternal TSH values were negatively associated with the cord blood levels of fT3 in all births, after adjusting for confounding factors. Maternal age was more closely associated with the cord blood levels of fT3 in female than in male births. Conclusion The inverse association between maternal age and cord blood levels of fT3 in euthyroid pregnant women suggested an impact of maternal aging on offspring thyroid function.

Abstract The convergence of cultural and aesthetic elements in timber structures from China’s Tang Dynasty (618–907 AD) and traditional Japanese architecture provides a rich tapestry of architectural evolution and cross-cultural exchanges. Addressing the challenge of distinguishing and understanding the intricate styles of these structures is significant for both historical comprehension and preservation efforts. This research introduces an innovative approach by integrating the Multi-Head Attention (MHA) mechanism into the YOLOv8 model, enhancing the detection of architectural features with improved precision and recall. Our novel YOLOv8-MHA model not only demonstrates a notable improvement in recognizing intricate architectural details but also significantly advances the state of the art in object detection within complex settings. Quantitative results underscore the model’s effectiveness, achieving a precision of 95.6%, a recall of 85.6%, and a mean Average Precision (mAP@50) of 94% across various Intersection over Union (IoU) thresholds. These metrics highlight the model’s superior capability to accurately identify and classify architectural elements, especially within environments rich with nuanced details, utilizing the enhanced YOLOv8-MHA algorithm. The application of our model extends beyond mere architectural analysis; it offers new insights into the intricate interplay of cultural identity and adaptability inherent in East Asian architectural heritage. The study establishes a solid foundation for the meticulous classification and analysis of architectural styles in timber structures within an expansive cultural and historical context, thereby enriching our understanding and preservation of these traditions.

Abstract Introduction Dichoptic training has emerged as a promising rehabilitation approach for improving binocular visual function in patients with strabismus. A prospective observational study design was employed to assess the effectiveness of online video game-based dichoptic training in rehabilitating binocular visual function in patients who had undergone an operation for intermittent exotropia. Methods A total of 64 patients who had undergone an operation for intermittent exotropia were recruited and divided into the training group and the control group based on whether they would receive the dichoptic training. The dichoptic training was conducted for 3 months in the training group and the control group would not accept any form of orthoptic therapy. Assessments of binocular visual functions and deviation were conducted at baseline, 3-month and 6-month follow-up. Results Twenty-nine participants in the training group (mean 9.69 ± 2.66 years old) and 26 participants in the control group (mean 8.41 ± 2.64 years old) completed follow-up. At both 3- and 6-month follow-ups, the training group showed superior distance stereopsis compared to the control group, with near stereopsis only showing significant difference at the 6-month follow-up. Additionally, the training group exhibited significantly less distance exo-deviation drift than the control group at these times, and no significant difference was observed in near exo-deviation drift between the groups. The control group had a significantly higher rate of suboptimal surgical outcomes at both the 3- and 6-month follow-up. However, no significant differences were observed in simultaneous perception and fusion functions between the two groups. Conclusions Online video game-based dichoptic training has the potential to become a novel postoperative rehabilitation strategy for patients with intermittent exotropia.

Abstract Background Thesium chinense Turcz. (Named as Bai Rui Cao in Chinese) and its preparations (e.g., Bairui Granules) have been used to treat inflammatory diseases, such as acute mastitis, lobar pneumonia, tonsillitis, coronavirus disease 2019 (COVID-19), and upper respiratory tract infection. However, the material basis, pharmacological efficiency, and safety have not been illustrated. Methods Anti-inflammatory activity-guided isolation of constituents has been performed using multiple column chromatography, and their structures were elucidated by NMR spectroscopy and ECD calculations. The inhibitory effects on lung inflammation and safety of the crude ethanol extract (CE), Bairui Granules (BG), and the purified active constituents were evaluated using lipopolysaccharide (LPS)-stimulated acute lung inflammation (ALI) mice model or normal mice. Results Seven new compounds (1–7) and fifty-six known compounds (8–63) were isolated from T. chinense, and fifty-four were reported from this plant for the first time. The new flavonoid glycosides 1–2, new fatty acids 4–5, new alkaloid 7 as well as the known constituents including flavonoid aglycones 8–11, lignans 46–54, alkaloids 34 and 45, coumarins 57, phenylpropionic acids 27, and simple aromatic compounds 39, 44 and 58 exhibited anti-inflammatory activity. Network pharmacology analysis indicated that anti-inflammation of T. chinense was attributed to flavonoids and alkaloids by regulating inflammation-related proteins (e.g., TNF, NF-κB, TGF-β). Furthermore, constituents of T. chinense including kaempferol-3-O-glucorhamnoside (KN, also named as Bairuisu I, 19), astragalin (AG, Bairuisu II, 12), and kaempferol (KF, Bairuisu III, 8), as well as CE and BG could alleviate lung inflammation caused by LPS in mice by preventing neutrophils infiltration and the expression of the genes for pro-inflammatory cytokines NLRP3, caspase-1, IL-1β, and COX-2. After a 28-day subacute toxicity test, BG at doses of 4.875 g/kg and 9.750 g/kg (equivalent to onefold and twofold the clinically recommended dose) and CE at a dose of 11.138 g/kg (equivalent to fourfold the clinical dose of BG) were found to be safe and non-toxic. Conclusions The discovery of sixty-three constituents comprehensively illustrated the material basis of T. chinense. T. chinense and Bairui Granules could alleviate lung inflammation by regulating inflammation-related proteins and no toxicity was observed under the twofold of clinically used doses.

Abstract The viral polymerase complex, comprising the large protein (L) and phosphoprotein (P), is crucial for both genome replication and transcription in non-segmented negative-strand RNA viruses (nsNSVs), while structures corresponding to these activities remain obscure. Here, we resolved two L–P complex conformations from the mumps virus (MuV), a typical member of nsNSVs, via cryogenic-electron microscopy. One conformation presents all five domains of L forming a continuous RNA tunnel to the methyltransferase domain (MTase), preferably as a transcription state. The other conformation has the appendage averaged out, which is inaccessible to MTase. In both conformations, parallel P tetramers are revealed around MuV L, which, together with structures of other nsNSVs, demonstrates the diverse origins of the L-binding X domain of P. Our study links varying structures of nsNSV polymerase complexes with genome replication and transcription and points to a sliding model for polymerase complexes to advance along the RNA templates.

Abstract DEAD-box helicase 17 (DDX17) is a typical member of the DEAD-box family with transcriptional cofactor activity. Although DDX17 is abundantly expressed in the myocardium, its role in heart is not fully understood. We generated cardiomyocyte-specific Ddx17-knockout mice (Ddx17-cKO), cardiomyocyte-specific Ddx17 transgenic mice (Ddx17-Tg), and various models of cardiomyocyte injury and heart failure (HF). DDX17 is downregulated in the myocardium of mouse models of heart failure and cardiomyocyte injury. Cardiomyocyte-specific knockout of Ddx17 promotes autophagic flux blockage and cardiomyocyte apoptosis, leading to progressive cardiac dysfunction, maladaptive remodeling and progression to heart failure. Restoration of DDX17 expression in cardiomyocytes protects cardiac function under pathological conditions. Further studies showed that DDX17 can bind to the transcriptional repressor B-cell lymphoma 6 (BCL6) and inhibit the expression of dynamin-related protein 1 (DRP1). When DDX17 expression is reduced, transcriptional repression of BCL6 is attenuated, leading to increased DRP1 expression and mitochondrial fission, which in turn leads to impaired mitochondrial homeostasis and heart failure. We also investigated the correlation of DDX17 expression with cardiac function and DRP1 expression in myocardial biopsy samples from patients with heart failure. These findings suggest that DDX17 protects cardiac function by promoting mitochondrial homeostasis through the BCL6-DRP1 pathway in heart failure.

Developing antibacterial and biocompatible coatings remains a challenge. A promising new thought is addressed to control the ion release behaviors through the design of the phases, structures, and morphologies of the products. In this study, TiO2-CuxO/Ag coatings were prepared via co-sputtering combined with annealing, the changes brought by different annealing temperatures were characterized, the physical, electrochemical, and antibacterial properties were concerned, and the relationship between biological performance and ions-releasing behavior was investigated. Results showed that the TiO2-CuxO/Ag coatings performed the morphologies of larger Ag particles seeded like islands on the dense CuO, such features improved the hydrophilicity and corrosion resistance of the Ti substrate. Rising the annealing temperature further enhanced the surface roughness, hydrophilicity, Young's modulus, hardness, and dynamic coefficient of friction of the coatings. Within the initial 3 h of soaking, both metal ions contributed to playing the antibacterial roles and produced a synergistic enhancement effect to satisfy the reduction of Staphylococcus aureus to 99.9%. In the next 3–120 h soaking, Ag releasing was suppressed and Cu releasing maintained its slow and stable trend, which made sure that the MC3T3-E1 cells could proliferate and adhere on the negatively charged coating surface, and copper oxide nanoparticles were phagocytized by cells. Among all TiO2-CuxO/Ag coatings, the M500 sample displayed superior performances on the surface roughness, contact angle, mechanical Young's modulus, and surface hardness, also realized the aim of killing pathogenic bacteria first and then activating cell survival, which enabled it to be potentially applied in clinical treatment.

Abstract Wogonin is a natural flavone compound from the plant Scutellaria baicalensis, which has a variety of pharmacological activities such as anti-cancer, anti-virus, anti-inflammatory, and immune regulation. However, the potential mechanism of wogonin remains unknown. This study was to confirm the molecular mechanism of wogonin for acute monocytic leukemia treatment, known as AML-M5. The potential action targets between wogonin and acute monocytic leukemia were predicted from databases. The compound-target-pathway network and protein-protein interaction network (PPI) were constructed. The enrichment analysis of related targets and molecular docking were performed. The network pharmacological results of wogonin for AML-M5 treatment were verified using the THP-1 cell line. 71 target genes of wogonin associated with AML-M5 were found. The key genes TP53, SRC, AKT1, RELA, HSP90AA1, JUN, PIK3R1, and CCND1 were preliminarily found to be the potential central targets of wogonin for AML-M5 treatment. The PPI network analysis, GO analysis and KEGG pathway enrichment analysis demonstrated that the PI3K/AKT signaling pathway was the significant pathway in the wogonin for AML-M5 treatment. The antiproliferative effects of wogonin on THP-1 cells of AML-M5 presented a dose-dependent and time-dependent manner, inducing apoptosis, blocking the cell cycle at the G2/M phase, decreasing the expressions of CCND1, CDK2, and CyclinA2 mRNA, as well as AKT and p-AKT proteins. The mechanisms of wogonin on AML-M5 treatment may be associated with inhibiting cell proliferation and regulating the cell cycle via the PI3K/AKT signaling pathway.