Involution Transformer based U-Net for Landmark Detection in Ultrasound Images for Diagnosis of Infantile DDH.

The B-mode ultrasound based computer-aided diagnosis (CAD) has demonstrated its effectiveness for diagnosis of Developmental Dysplasia of the Hip (DDH) in infants, which can conduct the Graf's method by detecting landmarks in hip ultrasound images. However, it is still necessary to explore more valuable information around these landmarks to enhance feature representation for improving detection performance in the detection model. To this end, a novel Involution Transformer based U-Net (IT-UNet) network is proposed for hip landmark detection. The IT-UNet integrates the efficient involution operation into Transformer to develop an Involution Transformer module (ITM), which consists of an involution attention block and a squeeze-and-excitation involution block. The ITM can capture both the spatial-related information and long-range dependencies from hip ultrasound images to effectively improve feature representation. Moreover, an Involution Downsampling block (IDB) is developed to alleviate the issue of feature loss in the encoder modules, which combines involution and convolution for the purpose of downsampling. The experimental results on two DDH ultrasound datasets indicate that the proposed IT-UNet achieves the best landmark detection performance, indicating its potential applications.

Simulating short-term light responses of photosynthesis and water use efficiency in sweet sorghum under varying temperature and CO2 conditions.

Climate change, characterized by rising atmospheric CO2 levels and temperatures, poses significant challenges to global crop production. Sweet sorghum, a prominent C4 cereal extensively grown in arid areas, emerges as a promising candidate for sustainable bioenergy production. This study investigated the responses of photosynthesis and leaf-scale water use efficiency (WUE) to varying light intensity (I) in sweet sorghum under different temperature and CO2 conditions. Comparative analyses were conducted between the A n-I, g s-I, T r-I, WUEi-I, and WUEinst-I models proposed by Ye et al. and the widely utilized the non-rectangular hyperbolic (NRH) model for fitting light response curves. The Ye's models effectively replicated the light response curves of sweet sorghum, accurately capturing the diminishing intrinsic WUE (WUEi) and instantaneous WUE (WUEinst) trends with increasing I. The fitted maximum values of A n, g s, T r, WUEi, and WUEinst and their saturation light intensities closely matched observations, unlike the NRH model. Despite the NRH model demonstrating high R 2 values for A n-I, g s-I, and T r-I modelling, it returned the maximum values significantly deviating from observed values and failed to generate saturation light intensities. It also inadequately represented WUE responses to I, overestimating WUE. Across different leaf temperatures, A n, g s, and T r of sweet sorghum displayed comparable light response patterns. Elevated temperatures increased maximum A n, g s, and T r but consistently declined maximum WUEi and WUEinst. However, WUEinst declined more sharply due to the disproportionate transpiration increase over carbon assimilation. Critically, sweet sorghum A n saturated at current atmospheric CO2 levels, with no significant gains under 550 µmol mol-1. Instead, stomatal closure enhanced WUE under elevated CO2 by coordinated g s and T r reductions rather than improved carbon assimilation. Nonetheless, this response diminished under simultaneously high temperature, suggesting intricate interplay between CO2 and temperature in modulating plant responses. These findings provide valuable insights into photosynthetic dynamics of sweet sorghum, aiding predictions of yield and optimization of cultivation practices. Moreover, our methodology serves as a valuable reference for evaluating leaf photosynthesis and WUE dynamics in diverse plant species.

Cost-Sensitive Weighted Contrastive Learning Based on Graph Convolutional Networks for Imbalanced Alzheimer's Disease Staging.

Identifying the progression stages of Alzheimer's disease (AD) can be considered as an imbalanced multi-class classification problem in machine learning. It is challenging due to the class imbalance issue and the heterogeneity of the disease. Recently, graph convolutional networks (GCNs) have been successfully applied in AD classification. However, these works did not handle the class imbalance issue in classification. Besides, they ignore the heterogeneity of the disease. To this end, we propose a novel cost-sensitive weighted contrastive learning method based on graph convolutional networks (CSWCL-GCNs) for imbalanced AD staging using resting-state functional magnetic resonance imaging (rs-fMRI). The proposed method is developed on a multi-view graph constructed using the functional connectivity (FC) and high-order functional connectivity (HOFC) features of the subjects. A novel cost-sensitive weighted contrastive learning procedure is proposed to capture discriminative information from the minority classes, encouraging the samples in the minority class to provide adequate supervision. Considering the heterogeneity of the disease, the weights of the negative pairs are introduced into contrastive learning and they are computed based on the distance to class prototypes, which are automatically learned from the training data. Meanwhile, the cost-sensitive mechanism is further introduced into contrastive learning to handle the class imbalance issue. The proposed CSWCL-GCN is evaluated on 720 subjects (including 184 NCs, 40 SMC patients, 208 EMCI patients, 172 LMCI patients and 116 AD patients) from the ADNI (Alzheimer's Disease Neuroimaging Initiative). Experimental results show that the proposed CSWCL-GCN outperforms state-of-the-art methods on the ADNI database.

Histopathology language-image representation learning for fine-grained digital pathology cross-modal retrieval.

Large-scale digital whole slide image (WSI) datasets analysis have gained significant attention in computer-aided cancer diagnosis. Content-based histopathological image retrieval (CBHIR) is a technique that searches a large database for data samples matching input objects in both details and semantics, offering relevant diagnostic information to pathologists. However, the current methods are limited by the difficulty of gigapixels, the variable size of WSIs, and the dependence on manual annotations. In this work, we propose a novel histopathology language-image representation learning framework for fine-grained digital pathology cross-modal retrieval, which utilizes paired diagnosis reports to learn fine-grained semantics from the WSI. An anchor-based WSI encoder is built to extract hierarchical region features and a prompt-based text encoder is introduced to learn fine-grained semantics from the diagnosis reports. The proposed framework is trained with a multivariate cross-modal loss function to learn semantic information from the diagnosis report at both the instance level and region level. After training, it can perform four types of retrieval tasks based on the multi-modal database to support diagnostic requirements. We conducted experiments on an in-house dataset and a public dataset to evaluate the proposed method. Extensive experiments have demonstrated the effectiveness of the proposed method and its advantages to the present histopathology retrieval methods. The code is available at https://github.com/hudingyi/FGCR.

EXPRESS: Clinical Outcomes and Clinico-Pathological Correlations in Children with MPO-ANCA-Associated Glomerulonephritis Showing Renal Arteritis.

OBJECTIVE: The aim of this study was to evaluate the clinical features, pathological characteristics and prognosis in myeloperoxidase (MPO)-antineutrophil cytoplasmic antibodies-associated glomerulonephritis (AAGN) with renal arteritis. METHODS: The study involved 97 children from five pediatric clinical centers with MPO-AAGN who exhibited distinct clinical features. The patients were divided into AAGN-A+ and AAGN-A-, based on the presence or absence of arteritis, and the disparities in clinical, histopathological characteristics, and prognosis between the two groups were evaluated. RESULT: In contrast to the AAGN-A- group, the children in the AAGN-A+ group exhibited more pronounced clinical symptoms and renal pathological injury. Arteritis positively moderately correlated with the serum creatinine (Scr), IL-6 (interleukin-6), urinary neutrophil gelatinase-associated lipocalin (NGAL), negatively moderately correlated with serum complement C3. The renal survival rate in the AAGN-A+ group was significantly poorer than AAGN-A- group (χ2=4.278, P=0.039). Arteritis showed a good predictive value for end-stage kidney disease (ESKD), and C3 deposition and arteritis were independent risk factors for the development of ESKD in children with MPO-AAGN. CONCLUSION: Arteritis is a significant pathological change observed in children with MPO-AAGN, and the formation of arteritis may be related to the inflammatory response and activation of the complement system.

Systemic immune-inflammation index and all-cause and cause-specific mortality in sarcopenia: a study from National Health and Nutrition Examination Survey 1999-2018.

Background: Sarcopenia, common in the elderly, often linked to chronic diseases, correlates with inflammation.The association between SII and mortality in sarcopenia patients is underexplored, this study investigates this relationship in a U.S. adult cohort. Methods: We analyzed 1999-2018 NHANES data, focusing on 2,974 adults with sarcopenia. Mortality outcomes were determined by linking to National Death Index (NDI) records up to December 31, 2019. Using a weighted sampling design, participants were grouped into three groups by the Systemic Immune-Inflammation Index (SII). We used Cox regression models, adjusting for demographic and clinical variables, to explore SII's association with all-cause and cause-specific mortality in sarcopenia, performing sensitivity analyses for robustness. Results: Over a median follow-up of 9.2 years, 829 deaths occurred. Kaplan-Meier analysis showed significant survival differences across SII groups. The highest SII group showed higher hazard ratios (HRs) for all-cause and cause-specific mortality in both crude and adjusted models. The highest SII group had a higher HR for all-cause(1.57, 1.25-1.98), cardiovascular(1.61, 1.00-2.58), cancer(2.13, 1.32-3.44), and respiratory disease mortality(3.21, 1.66-6.19) in fully adjusted models. Subgroup analyses revealed SII's association with all-cause mortality across various demographics, including age, gender, and presence of diabetes or cardiovascular disease. Sensitivity analyses, excluding participants with cardiovascular diseases, those who died within two years of follow-up, or those under 45 years of age, largely reflected these results, with the highest SII group consistently demonstrating higher HRs for all types of mortality in both unadjusted and adjusted models. Conclusion: Our study is the first to demonstrate a significant relationship between SII and increased mortality risks in a sarcopenia population.

Systematic Optimization of Universal Real-Time Hypersensitive Fast Detection Method for HBsAg in Serum Based on SERS.

Hepatitis B virus (HBV) is a major cause of liver cirrhosis and hepatocellular carcinoma, with HBV surface antigen (HBsAg) being a crucial marker in the clinical detection of HBV. Due to the significant harm and ease of transmission associated with HBV, HBsAg testing has become an essential part of preoperative assessments, particularly for emergency surgeries where healthcare professionals face exposure risks. Therefore, a timely and accurate detection method for HBsAg is urgently needed. In this study, a surface-enhanced Raman scattering (SERS) sensor with a sandwich structure was developed for HBsAg detection. Leveraging the ultrasensitive and rapid detection capabilities of SERS, this sensor enables quick detection results, significantly reducing waiting times. By systematically optimizing critical factors in the detection process, such as the composition and concentration of the incubation solution as well as the modification conditions and amount of probe particles, the sensitivity of the SERS immune assay system was improved. Ultimately, the sensor achieved a sensitivity of 0.00576 IU/mL within 12 min, surpassing the clinical requirement of 0.05 IU/mL by an order of magnitude. In clinical serum assay validation, the issue of false positives was effectively addressed by adding a blocker. The final sensor demonstrated 100% specificity and sensitivity at the threshold of 0.05 IU/mL. Therefore, this study not only designed an ultrasensitive SERS sensor for detecting HBsAg in actual clinical serum samples but also provided theoretical support for similar systems, filling the knowledge gap in existing literature.

Mitochondrial tRNA pseudouridylation governs erythropoiesis.

Pseudouridine is the most prevalent RNA modification, and its aberrant function is implicated in various human diseases. However, the specific impact of pseudouridylation on hematopoiesis remains poorly understood. In this study, we investigated the role of tRNA pseudouridylation in erythropoiesis and its association with mitochondrial myopathy, lactic acidosis, and sideroblastic anemia syndrome (MLASA) pathogenesis. By utilizing patient-specific induced pluripotent stem cells (iPSCs) carrying a genetic PUS1 mutation and a corresponding mutant mouse model, we demonstrated impaired erythropoiesis in MLASA iPSCs and anemia in the MLASA mouse model. Both MLASA iPSCs and mouse erythroblasts exhibited compromised mitochondrial function and impaired protein synthesis. Mechanistically, we revealed that PUS1 deficiency resulted in reduced mitochondrial tRNA levels due to pseudouridylation loss, leading to aberrant mitochondrial translation. Screening of mitochondrial supplements aimed at enhancing respiration or heme synthesis showed limited effect in promoting erythroid differentiation. Interestingly, the mTOR inhibitor rapamycin facilitated erythroid differentiation in MLASA-iPSCs by suppressing mTOR signaling and protein synthesis, and consistent results were observed in the MLASA mouse model. Importantly, rapamycin treatment effectively ameliorated anemia phenotypes in the MLASA patient. Our findings provide novel insights into the crucial role of mitochondrial tRNA pseudouridylation in governing erythropoiesis and present potential therapeutic strategies for anemia patients facing challenges related to protein translation.

Interplay of IL-17A/IL-17RA signaling with microbial homeostasis in systemic anti-tumoral responses.

Enteric IL-17RA deficiency leads to gut dysbiosis, consequently initiating the proliferation of tumors at remote locations. The deficiency or blockade of enteric IL-17RA induces the secretion of IL-17A by B cells and Th17 cells in response to microbial signals, resulting in a systemic elevation of IL-17A and fostering the growth of remote tumors. This figure was created with BioRender.com.

Metabolomics distinguishes different grades of Scrophularia ningpoensis hemsl: Towards a biomarker discovery and quality evaluation.

In managing unique complexities associated with Chinese medicinal quality assessment, metabolomics serves as an innovative tool. This study proposes an analytical approach to assess differing qualities of Scrophularia ningpoensis （S. ningpoensis）Hemsl by identifying potential biomarker metabolites and their activity with the corresponding secondary metabolites. The methodology includes four steps; first, a GC-MS based metabolomics exploration of the Scrophularia ningpoensis Hemsl. Second, a multivariate statistical analysis (PCA, PLS-DA, OPLS-DA) for quality assessment and biomarker identification. Third, the application of ROC analysis and pathway analysis based on identified biomarkers. Finally, validation of the associated active ingredients by HPLC. The analysis showed distinct metabolite profiles across varying grades of S. ningpoensis Hemsl, establishing a grading dependency relationship. Select biomarkers (gluconic Acid, d-xylulose, sucrose, etc.) demonstrated robust grading performances. Further, the Pentose Phosphate Pathway, deemed as most influential in grading, was tied to the synthesis of key constituents (iridoids, phenylpropanoids). HPLC validation tests affirm a decreasing trend in harpagoside and cinnamic acid levels between first and third-grade samples. In conclusion, this GC-MS based metabolomics combined HPLC method offers a sound approach to assess and distinguish quality variations in S. ningpoensis Hemsl samples.

Radiomics model based on MRI to differentiate spinal multiple myeloma from metastases: A two-center study.

Purpose: Spinal multiple myeloma (MM) and metastases are two common cancer types with similar imaging characteristics, for which differential diagnosis is needed to ensure precision therapy. The aim of this study is to establish radiomics models for effective differentiation between them. Methods: Enrolled in this study were 263 patients from two medical institutions, including 127 with spinal MM and 136 with spinal metastases. Of them, 210 patients from institution I were used as the internal training cohort and 53 patients from Institution II were used as the external validation cohort. Contrast-enhanced T1-weighted imaging (CET1) and T2-weighted imaging (T2WI) sequences were collected and reviewed. Based on the 1037 radiomics features extracted from both CET1 and T2WI images, Logistic Regression (LR), AdaBoost (AB), Support Vector Machines (SVM), Random Forest (RF), and multiple kernel learning based SVM (MKL-SVM) were constructed. Hyper-parameters were tuned by five-fold cross-validation. The diagnostic efficiency among different radiomics models was compared by accuracy (ACC), sensitivity (SEN), specificity (SPE), area under the ROC curve (AUC), YI, positive predictive value (PPV), negative predictive value (NPY), and F1-score. Results: Based on single-sequence, the RF model outperformed all other models. All models based on T2WI images performed better than those based on CET1. The efficiency of all models was boosted by incorporating CET1 and T2WI sequences, and the MKL-SVM model achieved the best performance with ACC, AUC, and F1-score of 0.862, 0.870, and 0.874, respectively. Conclusions: The radiomics models constructed based on MRI achieved satisfactory diagnostic performance for differentiation of spinal MM and metastases, demonstrating broad application prospects for individualized diagnosis and treatment.

Analysis of related factors of CRA in lung cancer patients with different serum iron levels: A retrospective cohort study.

BACKGROUND: Serum iron, an essential component of hemoglobin (Hb) synthesis in vivo, is a crucial parameter for evaluating the body's iron storage and metabolism capacity. Iron deficiency leads to reduced Hb synthesis in red blood cells and smaller red blood cell volume, ultimately resulting in iron-deficiency anemia. Although serum iron cannot independently evaluate iron storage or metabolism ability, it can reflect iron concentration in vivo and serve as a good predictor of iron-deficiency anemia. Therefore, exploring the influence of different serum iron levels on anemia and diagnosing and treating iron deficiency in the early stages is of great significance for patients with lung cancer. AIM: This study aims to explore the related factors of cancer-related anemia (CRA) in lung cancer and construct a nomogram prediction model to evaluate the risk of CRA in patients with different serum iron levels. METHODS: A single-center retrospective cohort study was conducted, including 1610 patients with lung cancer, of whom 1040 had CRA. The relationship between CRA and its influencing factors was analyzed using multiple linear regression models. Lung cancer patients were divided into two groups according to their serum iron levels: decreased serum iron and normal serum iron. Each group was randomly divided into a training cohort and a validation cohort at a ratio of 7:3. The influencing factors were screened by univariate and multivariate logistic regression analyses, and nomogram models were constructed. The area under the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the models. RESULTS: CRA in lung cancer is mainly related to surgery, chemotherapy, Karnofsky Performance Status (KPS) score, serum iron, C-reactive protein (CRP), albumin, and total cholesterol (p < 0.05). CRA in lung cancer patients with decreased serum iron is primarily associated with albumin, age, and cancer staging, while CRA in lung cancer patients with normal serum iron is mainly related to CRP, albumin, total cholesterol, and cancer staging. The area under the ROC curve of the training cohort and validation cohort for the prediction model of lung cancer patients with decreased serum iron was 0.758 and 0.760, respectively. Similarly, the area under the ROC curve of the training cohort and validation cohort for the prediction model of lung cancer patients with normal serum iron was 0.715 and 0.730, respectively. The calibration curves of both prediction models were around the ideal 45° line, suggesting good discrimination and calibration. DCA showed that the nomograms had good clinical utility. CONCLUSION: Both models have good reliability and validity and have significant clinical value. They can help doctors better assess the risk of developing CRA in lung cancer patients. CRP is a risk factor for CRA in lung cancer patients with normal serum iron but not in patients with decreased serum iron. Therefore, whether CRP and the inflammatory state represented by CRP will further aggravate the decrease in serum iron levels, thus contributing to anemia, warrants further study.

Cation Bimetallic MOF Anchored Carbon Fiber for Highly Efficient Microwave Absorption.

Carbon fiber (CF) is a potential microwave absorption (MA) material due to the strong dielectric loss. Nevertheless, owing to the high conductivity, poor impedance matching of carbon-based  materials results in limited MA performance. How to solve this problem and achieve excellent MA performance remains a principal challenge. Herein, taking full advantage of CF and excellent impedance matching of bimetallic metal-organic frameworks (MOF) derivatives layer, an excellent microwave absorber based on micron-scale 1D CF and NiCoMOF (CF@NiCoMOF-800) is developed. After adjusting the oxygen vacancies of the bimetallic MOF, the resultant microwave absorber presented excellent MA properties including the minimum reflection loss (RLmin ) of -80.63 dB and wide effective absorption bandwidth (EAB) of 8.01 GHz when its mass percent is only 5 wt.% and the thickness is 2.59 mm. Simultaneously, the mechanical properties of the epoxy resin (EP)-based coating with this microwave absorber are effectively improved. The hardness (H), elastic modulus (E), bending strength, and compressive strength of CF@NiCoMOF-800/EP coating are 334 MPa, 5.56 GPa, 82.2 MPa, and 135.8 MPa, which is 38%, 15%, 106% and 53% higher than EP coating. This work provides a promising solution for carbon materials achieving excellent MA properties and mechanical properties.

Zhuang-Gu-Fang intervenes vasculogenic and osteogenic coupling in GK rats through Notch1/Noggin/VEGF pathway.

Background: Zhuang-Gu-Fang (ZGF) has been proved to treat osteoporosis in ovariectomized rats by increasing osteogenic related factors Leptin, Ghrelin and Peptide YY(PYY). However, the mechanism of ZGF in the treatment of diabetic osteoporosis (DOP) remains unclear. The aim of this study was to explore the therapeutic effect of ZGF on DOP and its potential molecular mechanism. Methods: Using GK rats as models, the pharmacodynamic effects of ZGF on bone loss were evaluated by hematoxylin-eosin (H&E) staining and micro-computed.tomography (micro-CT). The expression levels of CD31 and endomucin (Emcn) were detected by immunofluorescence to assess the role of ZGF in angiogenic osteogenic coupling. Finally, real-time quantitative PCR (RT-PCR) and Western Blot (WB)were used to detect the expression levels of osteogenic and angiogenesis-related genes and proteins Notch1, Noggin and vascular endothelial growth factor (VEGF). Results: Administration of ZGF demonstrated a significant mitigation of bone loss attributable to elevated glucose levels. H&E staining and micro-CT showed that ZGF notably improved the integrity of the trabecular and cortical bone microarchitecture. Moreover, ZGF was found to augment the density of type H vessels within the bone tissue, alongside elevating the expression levels of Osterix, a transcription factor pivotal for bone formation. Furthermore, our findings suggest that ZGF facilitates the activation of the Notch1/Noggin/VEGF pathway, indicating a potential mechanism through which ZGF exerts its osteoprotective effects. Conclusion: Our results suggest that ZGF potentially facilitates the formation of type H vessels through the Notch1/Noggin/VEGF pathway. This action not only enhances angiogenic-osteogenic coupling but also contributes to the improvement of bone structure and density. Consequently, ZGF emerges as a promising therapeutic agent for the prevention and management of DOP, offering a novel approach by leveraging angiogenesis-dependent osteogenesis.

Evaluation of the Efficacy of Three Times Titanium Plate Gradual Fixation Method in the Treatment of Extracapsular Condylar Fractures.

OBJECTIVE: An improved method of treating inwardly dislocated mandibular extracapsular condylar fracture-three times titanium plate gradual fixation method was introduced, and the clinical efficacy of this method was evaluated. METHODS: Twenty patients with extracapsular condylar fractures who underwent surgical treatment using the three times titanium plate gradual restoration and fixation method in the Department of Oral Craniomaxillofacial Surgery of the Ninth People's Hospital of Shanghai from November 2020 to June 2023 were selected as the study subjects. RESULTS: After condylar restoration 22 sides reached healing and 1 side was basically healed; in 3 months after the operation, the degree of opening the mouth and the type of the opening of the mouth reached normal, and 1 case had mildly poor occlusion, which required to be further adjusted through orthodontics, and there was no temporomandibular function disorder or facial nerve function damage. CONCLUSION: Three times of gradual fixation with a titanium plate can make the condylar process achieve precise and stable repositioning, and make the surgical process orderly, and it is a kind of reliable fixation method for extracapsular condylar fractures.

Error detection using a multi-channel hybrid network with a low-resolution detector in patient-specific quality assurance.

PURPOSE: This study aimed to develop a hybrid multi-channel network to detect multileaf collimator (MLC) positional errors using dose difference (DD) maps and gamma maps generated from low-resolution detectors in patient-specific quality assurance (QA) for Intensity Modulated Radiation Therapy (IMRT). METHODS: A total of 68 plans with 358 beams of IMRT were included in this study. The MLC leaf positions of all control points in the original IMRT plans were modified to simulate four types of errors: shift error, opening error, closing error, and random error. These modified plans were imported into the treatment planning system (TPS) to calculate the predicted dose, while the PTW seven29 phantom was utilized to obtain the measured dose distributions. Based on the measured and predicted dose, DD maps and gamma maps, both with and without errors, were generated, resulting in a dataset with 3222 samples. The network's performance was evaluated using various metrics, including accuracy, sensitivity, specificity, precision, F1-score, ROC curves, and normalized confusion matrix. Besides, other baseline methods, such as single-channel hybrid network, ResNet-18, and Swin-Transformer, were also evaluated as a comparison. RESULTS: The experimental results showed that the multi-channel hybrid network outperformed other methods, demonstrating higher average precision, accuracy, sensitivity, specificity, and F1-scores, with values of 0.87, 0.89, 0.85, 0.97, and 0.85, respectively. The multi-channel hybrid network also achieved higher AUC values in the random errors (0.964) and the error-free (0.946) categories. Although the average accuracy of the multi-channel hybrid network was only marginally better than that of ResNet-18 and Swin Transformer, it significantly outperformed them regarding precision in the error-free category. CONCLUSION: The proposed multi-channel hybrid network exhibits a high level of accuracy in identifying MLC errors using low-resolution detectors. The method offers an effective and reliable solution for promoting quality and safety of IMRT QA.

In-Plane Elastic Properties of 3D-Printed Graded Hierarchical Hexagonal Honeycombs.

In this study, the graded hierarchical hexagonal honeycomb (GHHH) integrating gradient design and hierarchical design was fabricated using the 3D-printing technique, and its in-plane elastic properties were investigated theoretically, experimentally, and numerically. Theoretical solutions were developed based on the Euler beam theory to predict the effective elastic modulus and Poisson's ratio of GHHH, and theoretical values were in good agreement with the experimental and numerical results. The effect of gradient design and hierarchical design on the in-plane elastic properties of GHHH was also analyzed and compared. Results showed that the hierarchical design has a more significant effect on Poisson's ratio and adjusting the internal forces of GHHH compared with the gradient design. In addition, it was found that GHHH exhibited higher stiffness compared with regular hexagonal honeycomb (RHH), graded hexagonal honeycomb (GHH), and vertex-based hierarchical hexagonal honeycomb (VHHH) under the constraint of the same relative density, respectively. Specifically, the effective elastic modulus of GHHH can be enhanced by 119.82% compared to that of RHH. This research will help to reveal the effect of integrating hierarchical design and gradient design on the in-plane elastic properties of honeycombs.

Palladium-Catalyzed Cascade Heck Coupling and Allylboration of Iododiboron Compounds via Diboryl Radicals.

Geminal bis(boronates) are versatile synthetic building blocks in organic chemistry. The fact that they predominantly serve as nucleophiles in the previous reports, however, has restrained their synthetic potential. Herein we disclose the ambiphilic reactivity of α-halogenated geminal bis(boronates), of which the first catalytic utilization was accomplished by merging a formal Heck cross-coupling with a highly diastereoselective allylboration of aldehydes or imines, providing a new avenue for rapid assembly of polyfunctionalized boron-containing compounds. We demonstrated that this cascade reaction is highly efficient and compatible with various functional groups, and a wide range of heterocycles. In contrast to a classical Pd(0/II) scenario, mechanistic experiments and DFT calculations have provided strong evidence for a catalytic cycle involving Pd(I)/diboryl carbon radical intermediates.

Biophilic Positive Carbon Dot Exerts Antifungal Activity and Augments Corneal Permeation for Fungal Keratitis.

Fungal keratitis (FK) is an infectious eye disease that poses a significant risk of blindness. However, the effectiveness of conventional antifungal drugs is limited due to the intrinsic ocular barrier that impedes drug absorption. There is an urgent need to develop new therapeutic strategies to effectively combat FK. Herein, we synthesized an ultrasmall positively charged carbon dot using a simple stage-melting method. The carbon dot can penetrate the corneal barrier by opening the tight junctions, allowing them to reach the lesion site and effectively kill the fungi. The results both in vitro and in vivo demonstrated that it exhibited good biocompatibility and antifungal activity, significantly improving the therapeutic effect in a mouse model of FK. Therefore, this biophilic ultrasmall size and positive carbon dot, characterized by its ability to penetrate the corneal barrier and its antifungal properties, may offer valuable insights into the design of effective ocular nanomedicines.

Exosomal lncRNA HEIH, an essential communicator for hepatocellular carcinoma cells and macrophage M2 polarization through the miR-98-5p/STAT3 axis.

Part of human long noncoding RNAs (lncRNAs) has been elucidated to play an essential role in the carcinogenesis and progression of hepatocellular carcinoma (HCC), a type of malignant tumor with poor outcomes. Tumor-derived exosomes harboring lncRNAs have also been implicated as crucial mediators to orchestrate biological functions among neighbor tumor cells. The recruitment of tumor-associated macrophages (TAMs) exerting M2-like phenotype usually indicates the poor prognosis. Yet, the precise involvement of tumor-derived lncRNAs in cross-talk with environmental macrophages has not been fully identified. In this study, we reported the aberrantly overexpressed HCC upregulated EZH2-associated lncRNA (HEIH) in tumor tissues and cell lines was positively correlated with poor prognosis, as well as enriched exosomal HEIH levels in blood plasma and cell supernatants. Besides, HCC cell-derived exosomes transported HEIH into macrophages for triggering macrophage M2 polarization, thereby in turn promoting the proliferation, migration, and invasion of HCC cells. Mechanistically, HEIH acted as a miRNA sponge for miR-98-5p to up-regulate STAT3, which was then further verified in the tumor xenograft models. Collectively, our study provides the evidence for recognizing tumor-derived exosomal lncRNA HEIH as a novel regulatory function through targeting miR-98-5p/STAT3 axis in environmental macrophages, which may shed light on the complicated tumor microenvironment among tumor and immune cells for HCC treatment.