PLUNC inhibits invasion and metastasis in nasopharyngeal carcinoma by inhibiting NLRP3 inflammasome activation.

Nasopharyngeal carcinoma (NPC) is a malignant tumor that occurs in the nasopharynx. Palate, lung, and nasal epithelium clone (PLUNC) has been identified as an early secreted protein that is specifically expressed in the nasopharynx. The aim of this study was to determine the role and mechanism of PLUNC in NPC. We used mRNA sequencing (seq) combined with ribosome-nascent chain complex (RNC)-seq to determine the biological role of PLUNC. The expression of epithelial-to-mesenchymal transition (EMT)-related molecules was detected by western blotting. Then, cell migration and invasion were detected by wound healing and Transwell chamber assays. NPC cells were injected into the tail vein of nude mice to explore the biological role of PLUNC in vivo. The sequencing results showed that PLUNC inhibited the progression of NPC and its expression was correlated with that of NOD-like receptors. Experiments confirmed that PLUNC inhibited the invasion and metastasis of NPC cells by promoting the ubiquitination degradation of NLRP3. PLUNC overexpression in combination with the treatment by MCC950, an inhibitor of NLRP3 inflammasome activation, was most effective in inhibiting NPC invasion and metastasis. In vivo experiments also confirmed that the combination of PLUNC overexpression and MCC950 treatment effectively inhibited the lung metastasis of NPC cells. In summary, our research suggested that PLUNC inhibited the invasion and metastasis of NPC by inhibiting NLRP3 inflammasome activation, and targeting the PLUNC-NLRP3 inflammasome axis could provide a new strategy for the diagnosis and treatment of NPC patients.

APLNR inhibited nasopharyngeal carcinoma growth and immune escape by downregulating PD-L1.

BACKGROUND: APLNR is a G protein-coupled receptor and our previous study had revealed that APLNR could inhibit nasopharyngeal carcinoma (NPC) growth and metastasis. However, the role of APLNR in regulating PD-L1 expression and immune escape in NPC is unknown. METHODS: We analyzed the expression and correlation of APLNR and PD-L1 in NPC tissues and cells. We investigated the effect of APLNR on PD-L1 expression and the underlying mechanism in vitro and in vivo. We also evaluated the therapeutic potential of targeting APLNR in combination with PD-L1 antibody in a nude mouse xenograft model. RESULTS: We found that APLNR was negatively correlated with PD-L1 in NPC tissues and cells. APLNR could inhibit PD-L1 expression by binding to the FERM domain of JAK1 and blocking the interaction between JAK1 and IFNGR1, thus suppressing IFN-γ-mediated activation of the JAK1/STAT1 pathway. APLNR could also inhibit NPC immune escape by enhancing IFN-γ secretion and CD8+ T-cell infiltration and reducing CD8+ T-cell apoptosis and dysfunction. Moreover, the best effect was achieved in inhibiting NPC growth in nude mice when APLNR combined with PD-L1 antibody. CONCLUSIONS: Our study revealed a novel mechanism of APLNR regulating PD-L1 expression and immune escape in NPC and suggested that APLNR maybe a potential therapeutic target for NPC immunotherapy.

Prognostic value and immunological role of MMRN1: a rising star in cancer.

BACKGROUND: Multimerin 1 (MMRN1) is a factor V binding protein, which can support platelet adhesion and thrombus formation. In recent years, the role of MMRN1 in cancer has begun to attract attention. But systematic studies in this area are lacking. Therefore, we used bioinformatics methods to analyze MMRN1 in tumors to reveal the possible role of MMRN1. METHODS: Using the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database, we obtained relevant data for analyzing MMRN1. Using Gene Expression Profiling Interactive Analysis (GEPIA), Human Protein Atlas (HPA), TCGA, GeneMANIA, and cBioPortal, we explored the potential role of MMRN1 in different types of tumors. Tumor Immune System Interactions and Drug Bank (TISIDB) and Sangerbox were used to analyze the correlation between MMRN1 and tumor immunity. Gene set cancer analysis (GSCA) and UALCAN were used to analyze the methylation of MMRN1. GSCA was also used to analyze the drug sensitivity of MMRN1. RESULTS: MMRN1 is down-regulated in most cancer types and is closely related to the prognosis of cancer patients. Interestingly, in most tumors, MMRN1 is positively correlated with immune -related genes. In addition, we observed different levels of methylation and mutations in different types of tumors. Drug sensitivity analysis found that MMRN1 was negatively correlated with several drugs, including GW-2580 and TL-1-85, suggesting that it can be used to develop potential anticancer therapies. CONCLUSION: Our analysis demonstrated a significant relationship between MMRN1 and prognosis, tumor immunity, and drug sensitivity of several tumors. As a rising star in cancer, it needs further research.

A comparative study of two pelvimetry methods: 3D models based on CT and MRI.

INTRODUCTION AND HYPOTHESIS: To compare 3D models based on magnetic resonance imaging (MRI) and 3D models based on computed tomography (CT) in pelvimetry. METHODS: A retrospective analysis of 141 patients who underwent both pelvic 3D MRI and 3D CT pelvimetry for gynecological diseases from December 2009 to October 2020 was performed. The two pelvimetry methods were compared by paired Student's t test, Pearson's correlation coefficient, Bland-Altman analysis and intraclass correlation coefficient (ICC). RESULTS: The differences between methods for each diameter were statistically significant, except for those of the posterior sagittal diameter of the pelvic inlet (t:-0.71, P = 0.5) and the anteroposterior pelvic outlet diameter (t:0.02, P = 0.98). 3D MRI and 3D CT pelvimetry strongly correlated with each other (r: min 0.7, max: 0.96, P < 0.01). The Bland-Altman results indicate that the difference points of each pelvic diameter line greater than 95 % are within the 95 % limits of agreement. The ICC was good to very good for all pelvimetric measurements using either MRI-3D (ICC: 0.64-0.98) or CT-3D (ICC: 0.72-0.98) between the two readers. CONCLUSIONS: 3D MRI and 3D CT pelvimetry have good agreement and reproducibility, indicating that 3D MRI is reliable for pelvimetry.

Nurses' perspectives on workplace environment needs associated to resilience: a qualitative descriptive study.

Objective: The purpose of this study was to explore the demands of nurses on the workplace environment related to psychological resilience. Methods: A qualitative descriptive design was employed for this study. Purposeful sampling was chosen from a tertiary hospital in Henan Province, China. Semi-structured in-depth interviews were conducted with 20 nurses. The interview data was analyzed using the Colaizzi's method and results were reported following the COREQ standards. Results: Analysis of the interview data revealed three main themes: (1) Career Support and Development, (2) Practical Support & Development, and (3) Personal Support and Development. Conclusion: The perspectives of nurses for a workplace environment demands needs to be appreciated, and in addition, it is worth noting that the key role of building a good workplace environment in strengthening the resilience of nurses emphasizes the need for careful consideration. Nursing administrators should formulate policies and measures from multiple perspectives based on the real needs of nurses in terms of professional, practical, and personal dimensions.

Breaks for Precision Medicine in Cancer: Development and Prospects of Spatiotemporal Transcriptomics.

With the development of the social economy and the deepening understanding of cancer, cancer has become a significant cause of death, threatening human health. Although researchers have made rapid progress in cancer treatment strategies in recent years, the overall survival of cancer patients is still not optimistic. Therefore, it is essential to reveal the spatial pattern of gene expression, spatial heterogeneity of cell populations, microenvironment interactions, and other aspects of cancer. Spatiotemporal transcriptomics can help analyze the mechanism of cancer occurrence and development, greatly help precise cancer treatment, and improve clinical prognosis. Here, we review the integration strategies of single-cell RNA sequencing and spatial transcriptomics data, summarize the recent advances in spatiotemporal transcriptomics in cancer studies, and discuss the combined application of spatial multiomics, which provides new directions and strategies for the precise treatment and clinical prognosis of cancer.

Copper homeostasis and cuproptosis in mitochondria.

Mitochondria serve as sites for energy production and are essential for regulating various forms of cell death induced by metal metabolism, targeted anticancer drugs, radiotherapy and immunotherapy. Cuproptosis is an autonomous form of cell death that depends on copper (Cu) and mitochondrial metabolism. Although the recent discovery of cuproptosis highlights the significance of Cu and mitochondria, there is still a lack of biological evidence and experimental verification for the underlying mechanism. We provide an overview of how Cu and cuproptosis affect mitochondrial morphology and function. Through comparison with ferroptosis, similarities and differences in mitochondrial metabolism between cuproptosis and ferroptosis have been identified. These findings provide implications for further exploration of cuproptotic mechanisms. Furthermore, we explore the correlation between cuproptosis and immunotherapy or radiosensitivity. Ultimately, we emphasize the therapeutic potential of targeting cuproptosis as a novel approach for disease treatment.

Translatomics to explore dynamic differences in immunocytes in the tumor microenvironment.

Protein is an essential component of all living organisms and is primarily responsible for life activities; furthermore, its synthesis depends on a highly complex and accurate translation system. For proteins, the regulation at the translation level exceeds the sum of that during transcription, mRNA degradation, and protein degradation. Therefore, it is necessary to study regulation at the translation level. Imbalance in the translation process may change the cellular landscape, which not only leads to the occurrence, maintenance, progression, invasion, and metastasis of cancer but also affects the function of immune cells and changes the tumor microenvironment. Detailed analysis of transcriptional and protein atlases is needed to better understand how gene translation occurs. However, a more rigorous direct correlation between mRNA and protein levels is needed, which somewhat limits further studies. Translatomics is a technique for capturing and sequencing ribosome-related mRNAs that can effectively identify translation changes caused by ribosome stagnation and local translation abnormalities during cancer occurrence to further understand the changes in the translation landscape of cancer cells themselves and immune cells in the tumor microenvironment, which can provide new strategies and directions for tumor treatment.

The immune escape mechanism of nasopharyngeal carcinoma.

Tumor cells are known for being able to evade immune system surveillance, a hallmark of malignancy. Complicated immune escape mechanisms in the tumor microenvironment (TME) provide favorable conditions for tumor invasion, metastasis, treatment resistance, and recurrence. Epstein-Barr virus (EBV) infection is closely related to the pathogenesis of nasopharyngeal carcinoma (NPC), and the co-existence of EBV-infected NPC cells and tumor-infiltrating lymphocytes represents a distinctive, highly heterogeneous, and suppressive TME that supports immune escape and promotes tumorigenesis. Understanding the complex interaction between EBV and NPC host cells and focusing on the immune escape mechanism of TME may help to identify specific immunotherapy targets and to develop effective immunotherapy drugs.

Correction: Unassisted Clinicians Versus Deep Learning-Assisted Clinicians in Image-Based Cancer Diagnostics: Systematic Review With Meta-analysis.

[This corrects the article DOI: 10.2196/43832.].

Causal inference for recurrent events via aggregated marginal odds ratio.

Researchers often work with treatments and outcomes that vary over time. For example, psychologists are interested in the curative effect of cognitive behavior therapies on patients' recurrent depression symptoms. While there are various causal effect measures designed for one-time treatment, the causal effect measures for time-varying treatment and recurrent events are relatively under-developed. In this article, a new causal measure is proposed to quantify the causal effect of time-varying treatments on recurrent events. We suggest estimators with robust standard errors that are based on various weight models for both conventional causal measures and the proposed measure in different time settings. We outline the approaches and describe how using some stabilized inverse probability weight models are more advantageous than others. We demonstrate that the proposed causal estimand can be consistently estimated for study periods of moderate length, and the estimation results are compared under different treatment settings with various weight models. We also find that the proposed method is suitable for both absorbing and nonabsorbing treatments. The methods are applied to the 1997 National Longitudinal Study of Youth as an illustrative example.

Anatomy of the internal iliac vein around the sacral promontory based on CT three-dimensional (3D) reconstruction.

INTRODUCTION AND HYPOTHESIS: The area around the sacral promontory (SP) is the targeted location of various pelvic operations. We examined the internal iliac vein (IIV) configurations around the SP by computed tomography angiography (CTA) three-dimensional (3D) reconstruction to describe its anatomy and provide accurate anatomical parameters for relevant operations to reduce intraoperative vascular injury. METHODS: We retrospectively studied 2078 CTA 3D model datasets from Nanfang Hospital patients examined for gynecological diseases from December 2009 to October 2020. The IIVs of the above cases were divided into standard and variant IIVs, and variant IIVs were subdivided into different subtypes. To compare the size of the avascular area around the SP between standard and variant IIVs, we selected the two subtypes with the highest variation rate for comparison with the standard IIV type. RESULTS: The most common types of variant IIVs were 5a (5.15%) and 3a (5.05%). The results showed larger values in the standard group than in the 3a and 5a groups for the confluence of common iliac vein (CCIV) height (37.73±12.05 vs. 28.93±10.17 vs. 27.27±7.58 mm, P < 0.05), distance between the iliac vessels (49.47±9.47 mm vs. 37.08±9.36 vs. 37.73±8.94 mm, P < 0.05), and SP exposure width (44.94±6.39 mm vs. 36.83±8.29 vs. 36.93±7.91, P < 0.05). CONCLUSIONS: Variant IIVs may increase the risk of surgery by reducing the avascular area compared with standard IIVs. Therefore, when operating around the SP, special attention should be given to variant IIVs and avoiding vascular injury.

Unassisted Clinicians Versus Deep Learning-Assisted Clinicians in Image-Based Cancer Diagnostics: Systematic Review With Meta-analysis.

BACKGROUND: A number of publications have demonstrated that deep learning (DL) algorithms matched or outperformed clinicians in image-based cancer diagnostics, but these algorithms are frequently considered as opponents rather than partners. Despite the clinicians-in-the-loop DL approach having great potential, no study has systematically quantified the diagnostic accuracy of clinicians with and without the assistance of DL in image-based cancer identification. OBJECTIVE: We systematically quantified the diagnostic accuracy of clinicians with and without the assistance of DL in image-based cancer identification. METHODS: PubMed, Embase, IEEEXplore, and the Cochrane Library were searched for studies published between January 1, 2012, and December 7, 2021. Any type of study design was permitted that focused on comparing unassisted clinicians and DL-assisted clinicians in cancer identification using medical imaging. Studies using medical waveform-data graphics material and those investigating image segmentation rather than classification were excluded. Studies providing binary diagnostic accuracy data and contingency tables were included for further meta-analysis. Two subgroups were defined and analyzed, including cancer type and imaging modality. RESULTS: In total, 9796 studies were identified, of which 48 were deemed eligible for systematic review. Twenty-five of these studies made comparisons between unassisted clinicians and DL-assisted clinicians and provided sufficient data for statistical synthesis. We found a pooled sensitivity of 83% (95% CI 80%-86%) for unassisted clinicians and 88% (95% CI 86%-90%) for DL-assisted clinicians. Pooled specificity was 86% (95% CI 83%-88%) for unassisted clinicians and 88% (95% CI 85%-90%) for DL-assisted clinicians. The pooled sensitivity and specificity values for DL-assisted clinicians were higher than for unassisted clinicians, at ratios of 1.07 (95% CI 1.05-1.09) and 1.03 (95% CI 1.02-1.05), respectively. Similar diagnostic performance by DL-assisted clinicians was also observed across the predefined subgroups. CONCLUSIONS: The diagnostic performance of DL-assisted clinicians appears better than unassisted clinicians in image-based cancer identification. However, caution should be exercised, because the evidence provided in the reviewed studies does not cover all the minutiae involved in real-world clinical practice. Combining qualitative insights from clinical practice with data-science approaches may improve DL-assisted practice, although further research is required. TRIAL REGISTRATION: PROSPERO CRD42021281372; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=281372.

Bio-inspired switchable soft adhesion for the boost of adhesive surfaces and robotics applications: A brief review.

In nature, millions of creatures, such as geckos, tree frogs, octopuses, etc., have evolved fantastic switchable adhesion capabilities to climb swiftly on vertical even inverted surfaces or hunt for prey easily, adapting to harsh and unpredictable environments. Notably, these fascinating adhesive behaviors depend on interfacial forces (friction, van der Waals force, capillary force, vacuum suction, etc.), which primarily originate from the interactions between the soft micro/nanostructures evolved in the natural creatures and objects. Over the past few decades, these biological switchable adhesives have inspired scientists to explore and engineer desirable artificial adhesives. In this review, we summarized the state-of-the-art research on the ultra-fast adhesive motion of three types of biological organisms (gecko, tree frog, and octopus). Firstly, the basic adhesion principles in the three representative organisms, including micro/nanostructures, interfacial forces, and fundamental adhesion models, are reviewed. Then, we discussed the adhesion mechanisms of the prominent organisms from the perspective of soft contacts between micro/nanostructures and the substrates. Later, the mechanics-guided design principles of artificial adhesive surfaces, as well as the smart adhesion strategies, are summarized. The applications of these bio-inspired switchable adhesives are demonstrated, including wearable electronic devices, soft grippers, and climbing robots. The challenges and opportunities in this fast-growing field are also discussed.

Metabolic dialogs between B cells and the tumor microenvironment: Implications for anticancer immunity.

Immunometabolism, a branch of biology describing the link between immunity and metabolism, is an emerging topic in cancer immunology. It is currently well accepted that B cells and tertiary lymph structures formed by them are associated with favorable outcomes when patients undergo cancer immunotherapy. Understanding the determinants of B-cell fate and function in cancer patients is necessary for improving cancer immunotherapy. Accumulating evidence points to the tumor microenvironment being a critical metabolic hurdle to an efficient antitumor B-cell response. At the same time, several B-cell-derived metabolites have recently been reported to inhibit anticancer immunity. In this literature review, key B-cell immunometabolism studies and the metabolic life of B cells were summarized. Then, we discussed the intrinsic metabolic pathways of B cells themselves and how the tumor microenvironment and B cells in tumors metabolically influence each other. Finally, we pointed out key questions to provide some inspiration for further study of the role of B-cell immunometabolism in the antitumor immune response.

BaGFN: Broad Attentive Graph Fusion Network for High-Order Feature Interactions.

Modeling feature interactions is of crucial significance to high-quality feature engineering on multifiled sparse data. At present, a series of state-of-the-art methods extract cross features in a rather implicit bitwise fashion and lack enough comprehensive and flexible competence of learning sophisticated interactions among different feature fields. In this article, we propose a new broad attentive graph fusion network (BaGFN) to better model high-order feature interactions in a flexible and explicit manner. On the one hand, we design an attentive graph fusion module to strengthen high-order feature representation under graph structure. The graph-based module develops a new bilinear-cross aggregation function to aggregate the graph node information, employs the self-attention mechanism to learn the impact of neighborhood nodes, and updates the high-order representation of features by multihop fusion steps. On the other hand, we further construct a broad attentive cross module to refine high-order feature interactions at a bitwise level. The optimized module designs a new broad attention mechanism to dynamically learn the importance weights of cross features and efficiently conduct the sophisticated high-order feature interactions at the granularity of feature dimensions. The final experimental results demonstrate the effectiveness of our proposed model.

Robust Displacement Sensing by Direct-Current Triboelectric Nanogenerator Via Intelligent Waveform Recognition.

A triboelectric nanogenerator (TENG) facilitates the advancement of self-powered displacement sensors, which are important for many autonomous intelligent microsystems. However, the amplitude-based displacement sensing of conventional TENG-based sensors still suffers significantly from varying charge densities in harsh environments. Benefiting from the combination of intelligent signal processing algorithms and direct-current TENG sensors, this study proposes an environmentally robust character-based displacement sensing method that eliminates the influences of varying charge density in principle. The experimental results show that under drastically changing air humidity and other harsh environments, the sensing of threshold and maximum displacement has far superior consistency and stability than that of traditional amplitude-based TENG sensors, providing a novel route to realize reliable self-powered displacement sensing in environment-variable applications.

Associations between congenital heart disease and air pollutants at different gestational weeks: a time-series analysis.

Exposure to air pollution during pregnancy has been linked to birth defects. But the directions of studies on the associations between air pollutants exposure and effect on the incidence of congenital heart disease (CHDs) were inconsistent. To date, few studies were concentrated on the effects of both particulate matter and gaseous air pollutant exposure on CHDs across the full gestational week simultaneously. Our study aimed to investigate the critical exposure windows for each air pollutant throughout 40 gestational weeks. Data on CHDs, air pollution, and meteorological factors from 2013 to 2019 were collected in Lanzhou, China. A distributed lag nonlinear model combined with a quasi-Poisson regression model was applied to evaluate the weekly exposure-lag-response association between air pollutants levels and CHDs, and the subgroup analyses were conducted by gender (baby boy and baby girl). The study included 1607 mother-infant pairs. The results demonstrated that exposure of pregnant women to particulate matter ≤ 5 µm (PM2.5) at lag 1-4 weeks was significantly associated with the risk of CHDs, and the strongest effects were observed in the lag 1 week (1.150, 95%CI 1.059-1.248). For exposure to particulate matter ≤ 10 µm (PM10) at lag 1-3 weeks, the strongest effects were observed in the lag 1 week (1.075, 95% CI 1.026-1.128). For exposure to sulfur dioxide (SO2) at lag 1-4 weeks, the strongest effects were observed in the lag 1 week (1.154, 95% CI 1.025-1.299). For exposure to carbon monoxide (CO) at lag 1-3 weeks, the strongest effects were observed in the lag 1 week (1.089, 95% CI 1.002-1.183). For exposure to ozone (O3) concentration at lag 9-15 weeks, the strongest effects were observed in the lag 15 weeks (1.628, 95% CI 1.001-2.649). The cumulative effects of PM2.5, PM10, SO2, and CO along weeks with a maximum of 1.609 (95%CI 1.000-2.589), 1.286 (95%CI 1.007-1.641), 1.648 (95%CI 1.018-2.668), and 1.368 (95%CI 1.003, 1.865), respectively. The effects were obvious in the initial gestational weeks too. Through the gender stratification analysis, the air pollutants with significant effects were PM2.5 for baby boys and PM2.5, PM10, SO2, CO, NO2, and O3 for baby girl. For the relationship between CHDs and air pollution in Lanzhou, PM2.5, PM10, SO2, CO, and O3 played an important role in the initial gestational weeks, especially for baby girl.

Association between air pollutants and neural tube defects during pregnancy in Lanzhou, China: a time series analysis.

Few studies have evaluated the association between air pollutants and neural tube defects (NTDs). Moreover, the existing research ignores the lag effect of air pollution on health and provides inconsistent epidemiological evidence. We aim to estimate the association between air pollution and NTDs during the first trimester of pregnancy and identify specific susceptible windows. Birth data was collected from the Birth Defects Surveillance Network in Lanzhou from September 1, 2014, to December 31, 2019. Air quality and meteorological data were collected from ambient air monitoring stations and China Meteorological Data Network. The log connection function of the Poisson distribution function is used to establish a DLNM model to estimate the exposure-effect relationship and exposure-lag relationship association between air pollutants levels and NTDs. There were 320,787 perinatal infants in Lanzhou from September 1, 2014, to December 31, 2019, and 486 cases of NTDs (1.5‰). The result indicates that exposure to inhalable particles (PM10) at lag 2-4 weeks was significantly associated with the risk of NTDs, with the most significant impact at the lag 2 week (RR=1.048, 95%CI, 1.015-1.084). Exposure to fine particulate matter (PM2.5) at the lag 2 week was significantly associated with the risk of NTDs, with the most significant impact at the lag 2 week (RR=1.077, 95%CI, 1.004-1.155). Exposure to sulfur dioxide (SO2) and nitrogen dioxide (NO2) at lag 3-6weeks was significantly associated with the risk of NTDs, with the most significant impact at the lag 4 week (RR=1.220, 95%CI, 1.105-1.348; RR=1.143, 95%CI, 1.048-1.245). This study provides further evidence that exposure to air pollutants in the first trimester of pregnancy significantly increases the risk of neural tube defects.

Educating the whole person: Broad extracurricular involvement and prevalence of purpose and thriving among college students in China.

College students in China can choose from a wide variety of university organized extra-curricular activities (EAs), which are intended to enrich and deepen the learning experience, and reflect an educational policy goal to cultivate the whole and well-rounded person. These activities are also consistent with another policy goal, which is to foster optimal student outcomes like life purpose development. This study examined associations between EA involvement and life purpose and associations between EA involvement and thriving attributes of resourcefulness/resilience and life satisfaction among 332 undergraduate students enrolled at 20 universities across China. Measures of EA involvement, purpose resourcefulness/resilience, and life satisfaction were adapted to the Chinese culture, language, and student population. Four clusters of students emerged, representing varying degrees of well-roundedness according to their EA involvement. Patterns of associations examined between and within clusters supported the general hypothesis that more frequent and well-rounded EA involvement is positively associated with purpose and life-satisfaction, but not with resilience/resourcefulness. The significance of the findings for future research and practice are discussed.