Dynamic influence of maternal education on height among Chinese children aged 0-18 years.

Background: Maternal education is one of key factors affecting nurturing environment which significantly impacts children's height levels throughout their developmental stages. However, the influence of maternal education on children's height is less studied. This study aims to investigate the dynamic influence of maternal education on children's height among Chinese children aged 0-18 years. Methods: Children undergoing health examinations from January 2021 to September 2023 were included in this study. Clinical information including height, weight, maternal pregnancy history, blood specimens for bone metabolism-related indicators and maternal education level was collected. Children's height was categorized into 14 groups based on age and gender percentiles, following WHO 2006 growth standards. One-way analysis of variance (ANOVA), linear regression, chi-square test and Fisher's exact test were applied for data analysis. Results: A total of 6269 samples were collected, including 3654 males and 2615 females, with an average age of 8.38 (3.97) for males and 7.89 (3.55) for females. Significant correlations between maternal education level, birth weight, birth order, weight percentile, vitamin D, serum phosphorus, alkaline phosphatase levels, and children's height were identified. Birth weight's influence on height varied across age groups. Compared with normal birth weight children, low birth weight children exhibited catch-up growth within the first 6 years and a subsequent gradual widening of the height gap from 6 to 18 years old. Remarkably, the impact of maternal education on height became more pronounced among children above 3-6 years old, which can mitigate the effect of low birth weight on height. Conclusion: We found that weight percentile, birth weight, birth order, bone marker levels, and maternal education level have significant effect on height. Maternal education attenuates the impact of low birth weight on height. The findings indicated that maternal education plays a consistent and critical role in promoting robust and healthy growth.

Obesity Paradox in Patients with Acute Coronary Syndrome: Is Malnutrition the Answer?

BACKGROUND: Obesity paradox has been reported in patients with cardiovascular disease, showing an inverse association between obesity as defined by BMI (in kg/m2) and prognosis. Nutritional status is associated with systemic inflammatory response and affects cardiovascular disease outcomes. OBJECTIVES: This study sought to examine the influence of obesity and malnutrition on the prognosis of patients with acute coronary syndrome (ACS). METHODS: This study included consecutive patients diagnosed with ACS and underwent coronary angiogram between January 2009 and February 2023. At baseline, patients were categorized according to their BMI as follows: underweight (<18), normal weight (18-24.9), overweight (25.0-29.9), and obese (>30.0). We assessed the nutritional status by Prognostic Nutritional Index (PNI). Malnutrition was defined as a PNI value of <38. RESULTS: Of the 21,651 patients with ACS, 582 (2.7%) deaths from any cause were observed over 28.7 months. Compared with the patient's state of normal weight, overweight, and obesity were associated with decreased risk of all-cause mortality. Malnutrition was independently associated with poor survival (hazards ratio: 2.64; 95% CI: 2.24, 3.12; P < 0.001). In malnourished patients, overweight and obesity showed a 39% and 72% reduction in the incidence of all-cause mortality, respectively. However, in nourished patients, no significant reduction in the incidence of all-cause mortality was observed (all P > 0.05). CONCLUSIONS: Obesity paradox appears to occur in patients with ACS. Malnutrition may be a significant independent risk factor for prognosis in patients with ACS. The obesity paradox is influenced by the status of malnutrition.

A real-world clinicopathological model for predicting pathological complete response to neoadjuvant chemotherapy in breast cancer.

Purpose: This study aimed to develop and validate a clinicopathological model to predict pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients and identify key prognostic factors. Methods: This retrospective study analyzed data from 279 breast cancer patients who received NAC at Zhejiang Provincial People's Hospital from 2011 to 2021. Additionally, an external validation dataset, comprising 50 patients from Lanxi People's Hospital and Second Affiliated Hospital, Zhejiang University School of Medicine from 2022 to 2023 was utilized for model verification. A multivariate logistic regression model was established incorporating clinical, ultrasound features, circulating tumor cells (CTCs), and pathology variables at baseline and post-NAC. Model performance for predicting pCR was evaluated. Prognostic factors were identified using survival analysis. Results: In the 279 patients enrolled, a pathologic complete response (pCR) rate of 27.96% (78 out of 279) was achieved. The predictive model incorporated independent predictors such as stromal tumor-infiltrating lymphocyte (sTIL) levels, Ki-67 expression, molecular subtype, and ultrasound echo features. The model demonstrated strong predictive accuracy for pCR (C-statistics/AUC 0.874), especially in human epidermal growth factor receptor 2 (HER2)-enriched (C-statistics/AUC 0.878) and triple-negative (C-statistics/AUC 0.870) subtypes, and the model performed well in external validation data set (C-statistics/AUC 0.836). Incorporating circulating tumor cell (CTC) changes post-NAC and tumor size changes further improved predictive performance (C-statistics/AUC 0.945) in the CTC detection subgroup. Key prognostic factors included tumor size >5cm, lymph node metastasis, sTIL levels, estrogen receptor (ER) status and pCR. Despite varied pCR rates, overall prognosis after standard systemic therapy was consistent across molecular subtypes. Conclusion: The developed predictive model showcases robust performance in forecasting pCR in NAC-treated breast cancer patients, marking a step toward more personalized therapeutic strategies in breast cancer.

Neoadjuvant chemotherapy-induced remodeling of human hormonal receptor-positive breast cancer revealed by single-cell RNA sequencing.

Hormone receptor-positive breast cancer (HR+ BC) is known to be relatively insensitive to chemotherapy, and since chemotherapy has remained the major neoadjuvant therapy for HR+ BC, the undetermined mechanism of chemoresistance and how chemotherapy reshapes the immune microenvironment need to be explored by high-throughput technology. By using single-cell RNA sequencing and multiplexed immunofluorescence staining analysis of HR+ BC samples (paired pre- and post-neoadjuvant chemotherapy (NAC)), the levels of previously unrecognized immune cell subsets, including CD8+ T cells with pronounced expression of T-cell development (LMNA) and cytotoxicity (FGFBP2) markers, CD4+ T cells characterized by proliferation marker (ATP1B3) expression and macrophages characterized by CD52 expression, were found to be increased post-NAC, which were predictive of chemosensitivity and their antitumor function was also validated with in vitro experiments. In terms of immune checkpoint expression of CD8+ T cells, we found their changes were inconsistent post-NAC, that LAG3, VSIR were decreased, and PDCD1, HAVCR2, CTLA4, KLRC1 and BTLA were increased. In addition, we have identified novel genomic and transcriptional patterns of chemoresistant cancer cells, both innate and acquired, and have confirmed their prognostic value with TCGA cohorts. By shedding light on the ecosystem of HR+ BC reshaped by chemotherapy, our results uncover valuable candidates for predicting chemosensitivity and overcoming chemoresistance in HR+ BC.

Integrated transcriptomics, proteomics, and functional analysis to characterize the tissue-specific small extracellular vesicle network of breast cancer.

Small extracellular vesicles (sEVs) are essential mediators of intercellular communication within the tumor microenvironment (TME). Although the biological features of sEVs have been characterized based on in vitro culture models, recent evidence indicates significant differences between sEVs derived from tissue and those derived from in vitro models in terms of both content and biological function. However, comprehensive comparisons and functional analyses are still limited. Here, we collected sEVs from breast cancer tissues (T-sEVs), paired normal tissues (N-sEVs), corresponding plasma (B-sEVs), and tumor organoids (O-sEVs) to characterize their transcriptomic and proteomic profiles. We identified the actual cancer-specific sEV signatures characterized by enriched cell adhesion and immunomodulatory molecules. Furthermore, we revealed the significant contribution of cancer-associated fibroblasts in the sEV network within the TME. In vitro model-derived sEVs did not entirely inherit the extracellular matrix- and immunity regulation-related features of T-sEVs. Also, we demonstrated the greater immunostimulatory ability of T-sEVs on macrophages and CD8+ T cells compared to O-sEVs. Moreover, certain sEV biomarkers derived from noncancer cells in the circulation exhibited promising diagnostic potential. This study provides valuable insights into the functional characteristics of tumor tissue-derived sEVs, highlighting their potential as diagnostic markers and therapeutic agents for breast cancer.

CD24hiCD27+ Bregs within Metastatic Lymph Nodes Promote Multidrug Resistance in Breast Cancer.

PURPOSE: Axillary lymph nodes (LN) are the primary and dominant metastatic sites in breast cancer. However, the interaction between tumor cells and immune cells within metastatic LNs (mLN) remains poorly understood. In our study, we explored the effect of CD24hiCD27+ regulatory B cells (Breg) within mLNs on orchestrating drug resistance of breast cancer cells. EXPERIMENTAL DESIGN: We collected mLN samples from patients with breast cancer who had received standard neoadjuvant therapy (NAT) and analyzed the spatial features of CD24hiCD27+ Bregs through multicolor immunofluorescence staining. The effect of CD24hiCD27+ Bregs on drug resistance of breast cancer cells was evaluated via in vitro experiments. A mouse model with mLNs was used to evaluate the strategies with blocking the interactions between Bregs and breast cancer for improving tumor regression within mLNs. RESULTS: In patients with breast cancer who had received NAT, there is a close spatial correlation between activated CD24hiCD27+ Bregs and residual tumor cells within mLNs. Mechanistically, CD24hiCD27+ Bregs greatly enhance the acquisition of multidrug resistance and stem-like features of breast cancer cells by secreting IL6 and TNFα. More importantly, breast cancer cells further promote the activation of CD24hiCD27+ Bregs via CD40L-dependent and PD-L1-dependent proximal signals, forming a positive feedback pattern. PD-L1 blockade significantly attenuates the drug resistance of breast cancer cells induced by CD24hiCD27+ Bregs, and addition of anti-PD-L1 antibody to chemotherapy improves tumor cell remission in mLNs. CONCLUSIONS: Our study reveals the pivotal role of CD24hiCD27+ Bregs in promoting drug resistance by interacting with breast cancer cells in mLNs, providing novel evidence for an improved strategy of chemoimmunotherapy combination for patients with breast cancer with mLNs.

A comparative study on the influence of single and combined ultrasounds assisted flake graphite flotation.

Ultrasound has emerged as a promising technique for improving the mineral flotation performance. However, limited research exists regarding the influence of different ultrasound types on the flotation process. Specifically, the impact of combined ultrasound and the comparison of horn- and bath-type ultrasounds on flotation have not been fully investigated. To address this knowledge gap, a comprehensive study to explore the effects of different ultrasonic pretreatments on the flotation of flake graphite was conducted. A Box-Behnken design is employed to analyze the effects of combined ultrasound on graphite flotation. By characterizing the properties of graphite samples before and after the ultrasonic treatment, the aim is to elucidate the mechanism underlying the impact of ultrasound on graphite flotation. The experimental results indicated that the ultrasonic cavitation intensity exerted a significant influence on the graphite flotation recovery. Both horn- and bath- type ultrasounds contributed to flotation, but horn-type ultrasound demonstrated a more pronounced effect, leading to a 7% increase in flotation recovery, whereas bath-type ultrasound resulted in only a 2% increase. Furthermore, the cavitation intensity of combined ultrasound was found to be higher than that of single-frequency ultrasound in the same duration. However, the performance of graphite flotation was better with short duration combined ultrasound pretreatment, while the opposite trend was observed for a long duration ultrasound pretreatment. These findings may inform the development of more efficient and effective ultrasonic pretreatments for flotation separation processes.

Optimization of Tungsten Heavy Alloy Cutting Parameters Based on RSM and Reinforcement Dung Beetle Algorithm.

Tungsten heavy alloys (WHAs) are an extremely hard-to-machine material extensively used in demanding applications such as missile liners, aerospace, and optical molds. However, the machining of WHAs remains a challenging task as a result of their high density and elastic stiffness which lead to the deterioration of the machined surface roughness. This paper proposes a brand-new multi-objective dung beetle algorithm. It does not take the cutting parameters (i.e., cutting speed, feed rate, and depth of cut) as the optimization objects but directly optimizes cutting forces and vibration signals monitored using a multi-sensor (i.e., dynamometer and accelerometer). The cutting parameters in the WHA turning process are analyzed through the use of the response surface method (RSM) and the improved dung beetle optimization algorithm. Experimental verification shows that the algorithm has better convergence speed and optimization ability compared with similar algorithms. The optimized forces and vibration are reduced by 9.7% and 46.47%, respectively, and the surface roughness Ra of the machined surface is reduced by 18.2%. The proposed modeling and optimization algorithms are anticipated to be powerful to provide the basis for the parameter optimization in the cutting of WHAs.

Online small-object anti-fringe sorting of tobacco stem impurities based on hyperspectral superpixels.

The use of tobacco stems as raw material for cigarettes reduces cost and improves the flammability of cigarettes. However, various impurities, such as plastic, reduce the purity of tobacco stems, degrade the quality of cigarettes, and endanger the health of smokers. Therefore, the correct classification of tobacco stems and impurities is crucial. This study proposes a method based on hyperspectral image superpixels and the use of light gradient boosting machine (LightGBM) classifier to categorize tobacco stems and impurities. First, the hyperspectral image is segmented using superpixels. Second, the gray-level co-occurrence matrix extracts the texture features of superpixels. Subsequently, an improved LightGBM is applied and trained with the spectral and textural features of superpixels as a classification model. Several experiments were implemented to evaluate the performance of the proposed method. The results show that the classification performance based on superpixels is better than that based on single-pixel points. The classification model based on superpixels (10 × 10 px) achieved the highest impurity recognition rate (93.8%). This algorithm has already been applied to industrial production in cigarette factories. It exhibits considerable potential in overcoming the influence of interference fringes to promote the intelligent industrial application of hyperspectral imaging.

Exploration of prognosis and immunometabolism landscapes in ER+ breast cancer based on a novel lipid metabolism-related signature.

Introduction: Lipid metabolic reprogramming is gaining attention as a hallmark of cancers. Recent mounting evidence indicates that the malignant behavior of breast cancer (BC) is closely related to lipid metabolism. Here, we focus on the estrogen receptor-positive (ER+) subtype, the most common subgroup of BC, to explore immunometabolism landscapes and prognostic significance according to lipid metabolism-related genes (LMRGs). Methods: Samples from The Cancer Genome Atlas (TCGA) database were used as training cohort, and samples from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), Gene Expression Omnibus (GEO) datasets and our cohort were applied for external validation. The survival-related LMRG molecular pattern and signature were constructed by unsupervised consensus clustering and least absolute shrinkage and selection operator (LASSO) analysis. A lipid metabolism-related clinicopathologic nomogram was established. Gene enrichment and pathway analysis were performed to explore the underlying mechanism. Immune landscapes, immunotherapy and chemotherapy response were further explored. Moreover, the relationship between gene expression and clinicopathological features was assessed by immunohistochemistry. Results: Two LMRG molecular patterns were identified and associated with distinct prognoses and immune cell infiltration. Next, a prognostic signature based on nine survival-related LMRGs was established and validated. The signature was confirmed to be an independent prognostic factor and an optimal nomogram incorporating age and T stage (AUC of 5-year overall survival: 0.778). Pathway enrichment analysis revealed differences in immune activities, lipid biosynthesis and drug metabolism by comparing groups with low- and high-risk scores. Further exploration verified different immune microenvironment profiles, immune checkpoint expression, and sensitivity to immunotherapy and chemotherapy between the two groups. Finally, arachidonate 15-lipoxygenase (ALOX15) was selected as the most prominent differentially expressed gene between the two groups. Its expression was positively related to larger tumor size, more advanced tumor stage and vascular invasion in our cohort (n = 149). Discussion: This is the first lipid metabolism-based signature with value for prognosis prediction and immunotherapy or chemotherapy guidance for ER+ BC.

Chemotherapy-induced exosomal circBACH1 promotes breast cancer resistance and stemness via miR-217/G3BP2 signaling pathway.

BACKGROUND: Chemoresistance involves metastasis and aggressiveness of breast cancer (BC). Chemotherapy-elicited exosomes have been reported to be associated with drug resistance and pro-metastatic capacity of BC cells. Non-coding RNAs (ncRNAs) are enriched in exosomes, which participated in generation, progression, and resistance of BC. However, the mechanism underlying the chemoresistance and metastasis in BC cells mediated by the BC-derived exosomal ncRNAs remained to be elucidated. METHODS: The effects of PTX-induced exosomal circBACH1 on BC cell function were assessed using RNA Binding Protein Immunoprecipitation (RIP), dual luciferase reporter gene, tube formation, CCK-8, and Western Blot assays. The circBACH1 and miR-217 expression levels were detected using quantitative real-time PCR (RT-qPCR) and Immunohistochemistry (IHC) assays in BC tissues and precancerous tissues of BC patients. RESULTS: CircBACH1 expression was increased in paclitaxel-treated BC-derived exosomes (PTX-EXO) and BC tissue. PTX-EXO was shown to promote PTX-resistance and angiogenesis through upregulation circBACH1. Downregulation of circBACH1 improved PTX-sensitiveness by suppressing the cell viability, stemness, migration, and angiogenesis of BC cells. Moreover, we found that miR-217 interacted with circBACH1 and targeted GTPase-activating SH3 domain-binding protein 2 (G3BP2) in BC cells. CircBACH1 combined miR-217 cotransfection suppressed the expression of G3BP2 proteins compared with circBACH1 treatment in MCF-7 cells. In addition, downregulation of G3BP2 suppressed BC cell migration. CONCLUSIONS: These results demonstrated that PTX-induced exosomal circBACH1 promoted stemness and migration of BC cells by sponging miR-217 to upregulate the expression of G3BP2, which provided a new therapeutic target for PTX-resistance and progression of BC via circBACH1/miR-217/G3BP2 axis.

Multiomics technologies for comprehensive tumor microenvironment analysis in triple-negative breast cancer under neoadjuvant chemotherapy.

Triple-negative breast cancer (TNBC) is one of the most aggressive breast cancer subtypes and is characterized by abundant infiltrating immune cells within the microenvironment. As standard care, chemotherapy remains the fundamental neoadjuvant treatment in TNBC, and there is increasing evidence that supplementation with immune checkpoint inhibitors may potentiate the therapeutic efficiency of neoadjuvant chemotherapy (NAC). However, 20-60% of TNBC patients still have residual tumor burden after NAC and require additional chemotherapy; therefore, it is critical to understand the dynamic change in the tumor microenvironment (TME) during treatment to help improve the rate of complete pathological response and long-term prognosis. Traditional methods, including immunohistochemistry, bulk tumor sequencing, and flow cytometry, have been applied to elucidate the TME of breast cancer, but the low resolution and throughput may overlook key information. With the development of diverse high-throughput technologies, recent reports have provided new insights into TME alterations during NAC in four fields, including tissue imaging, cytometry, next-generation sequencing, and spatial omics. In this review, we discuss the traditional methods and the latest advances in high-throughput techniques to decipher the TME of TNBC and the prospect of translating these techniques to clinical practice.

CircRNA7632 down-regulation alleviates endothelial cell dysfunction in Kawasaki disease via regulating IL-33 expression.

Kawasaki disease (KD) is a form of idiopathic vasculitis frequently accompanied by coronary artery lesions, which involves endothelial dysfunction. Recent studies have demonstrated that circular RNAs (circRNAs) are implicated in many cardiovascular diseases. However, few studies have examined the role of circRNAs on endothelial dysfunction in KD. In this study, we investigated the role of circ7632 on endothelial-mesenchymal transition (EndoMT) in KD and then explored the underlying mechanism. Children diagnosed with KD and age-matched healthy controls (HC) were included. Sera samples were collected. Primary human umbilical vein endothelial cells (HUVECs) were obtained and incubated with 15% HC and KD serum for 48 h. The mRNA and protein expression of mesenchymal markers vimentin and α-smooth muscle actin (α-SMA) and endothelial marker zonula occludens-1 (ZO-1) in HUVECs transfected with plasmid-circ7632 and si-circ7632 were detected by RT-qPCR and Western blot analysis. CCK8, scratch test, and migration test were performed to examine the effect of circ7632 on the cell proliferation and migration. The circ7632 level was higher in HUVECs treated by KD serum than in HUVECs treated with HC serum. Overexpression of circ7632 significantly increased vimentin and α-SMA expression, decreased ZO-1 expression, and also decreased cell proliferation. Down-regulation of circ7632 expression got the opposite results. RNA-seq analysis, and confirmatory experiment displayed that down-regulation of circ7632 decreased IL-33 expression, and IL-33 silencing mitigated KD serum-mediated EndoMT. Our study revealed that circ7632 level was elevated in KD serum-treated HUVECs. Circ7632 down-regulation could alleviate EndoMT likely through decreasing IL-33 expression. The circ7632 may become a potential therapeutic target for KD.

MMST: A Multi-Modal Ground-Based Cloud Image Classification Method.

In recent years, convolutional neural networks have been in the leading position for ground-based cloud image classification tasks. However, this approach introduces too much inductive bias, fails to perform global modeling, and gradually tends to saturate the performance effect of convolutional neural network models as the amount of data increases. In this paper, we propose a novel method for ground-based cloud image recognition based on the multi-modal Swin Transformer (MMST), which discards the idea of using convolution to extract visual features and mainly consists of an attention mechanism module and linear layers. The Swin Transformer, the visual backbone network of MMST, enables the model to achieve better performance in downstream tasks through pre-trained weights obtained from the large-scale dataset ImageNet and can significantly shorten the transfer learning time. At the same time, the multi-modal information fusion network uses multiple linear layers and a residual structure to thoroughly learn multi-modal features, further improving the model's performance. MMST is evaluated on the multi-modal ground-based cloud public data set MGCD. Compared with the state-of-art methods, the classification accuracy rate reaches 91.30%, which verifies its validity in ground-based cloud image classification and proves that in ground-based cloud image recognition, models based on the Transformer architecture can also achieve better results.

Radiation-induced tumor immune microenvironments and potential targets for combination therapy.

As one of the four major means of cancer treatment including surgery, radiotherapy (RT), chemotherapy, immunotherapy, RT can be applied to various cancers as both a radical cancer treatment and an adjuvant treatment before or after surgery. Although RT is an important modality for cancer treatment, the consequential changes caused by RT in the tumor microenvironment (TME) have not yet been fully elucidated. RT-induced damage to cancer cells leads to different outcomes, such as survival, senescence, or death. During RT, alterations in signaling pathways result in changes in the local immune microenvironment. However, some immune cells are immunosuppressive or transform into immunosuppressive phenotypes under specific conditions, leading to the development of radioresistance. Patients who are radioresistant respond poorly to RT and may experience cancer progression. Given that the emergence of radioresistance is inevitable, new radiosensitization treatments are urgently needed. In this review, we discuss the changes in irradiated cancer cells and immune cells in the TME under different RT regimens and describe existing and potential molecules that could be targeted to improve the therapeutic effects of RT. Overall, this review highlights the possibilities of synergistic therapy by building on existing research.

Effect of ultrasound power on HCl leaching kinetics of impurity removal of aphanitic graphite.

This study aimed to investigate the effect of ultrasonic power and temperature on the impurity removal rate during conventional and ultrasonic-assisted leaching of aphanitic graphite. The results showed that the ash removal rate increased gradually (∼50 %) with the increase in ultrasonic power and temperature but deteriorated at high power and temperature. The unreacted shrinkage core model was found to fit the experimental results better than other models. The Arrhenius equation was used to calculate the finger front factor and activation energy under different ultrasonic power conditions. The ultrasonic leaching process was significantly influenced by temperature, and the enhancement of the leaching reaction rate constant by ultrasound was mainly reflected in the increase of the pre-exponential factor A. Ultrasound treatment improved the efficiency of impurity mineral removal by destroying the inert layer formed on the graphite surface, promoting particle fragmentation, and generating oxidation radicals. The poor reactivity of hydrochloric acid with quartz and some silicate minerals is a bottleneck limiting the further improvement of impurity removal efficiency in ultrasound-assisted aphanitic graphite. Finally, the study suggests that introducing fluoride salts may be a promising method for deep impurity removal in the ultrasound-assisted hydrochloric acid leaching process of aphanitic graphite.