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The spatiotemporal distribution of atmospheric environmental severity in Tibet was evaluated and predicted based on polycarbonate (PC) chromatic aberrations. This study collected the annual average data (April 2021 to March 2022) of eight types of environmental factors from 10 typical atmospheric sites in Tibet. The climatic characteristics and climate distribution areas were analyzed to obtain accurate input to evaluate environmental severity. Natural environmental tests were conducted at 10 sites to analyze the regulation of PC degradation. The results showed that the gloss decreased and chromatic aberration gradually increased during PC aging, and mechanical properties, such as tensile strength and tensile strain at break, decreased with fluctuations. Thus, chromatic aberration was selected as a PC aging evaluation index owing to its excellent performance. Pearson’s correlation analysis was used to determine the information redundancy hidden in various environmental factors and geographic information coordinates. The environmental parameters were further optimized, and the factors highly related to PC aging were sunshine time, altitude, average relative humidity, and precipitation time. The “environmental material” mapping model with excellent training precision and generalizability was established using the Back Propagation Artificial Neural Network. By inputting the environmental data of 28 cities in Tibet into the well-built models, the severity was predicted and visualized to form spatial distribution maps using the Griddate interpolation method. The results showed that the low-altitude areas in eastern Tibet presented low severity. By training with different learning accuracies, the results revealed that low learning precision caused insufficient training and led to low prediction accuracy, whereas high learning precision led to overfitting and a prediction of the local minimum. The meteorological data of the 28 cities in Tibet were loaded into a well-trained artificial neural network model to predict the chromatic aberration value of PC aging in 28 cities in Tibet. A spatial distribution map of severity in Tibet was obtained based on the Griddate interpolation calculation. The results indicated that severity was much higher in summer than in winter, and the severity of the northwest area was the highest even in winter. The exact quantitative evaluations of severity played a significant role in the safety service for the equipment and facilities in Tibet.

Abstract Background In the current treatment of non-small cell lung cancer (NSCLC), traditional chemotherapy causes high toxicity, so it is necessary to develop safe chemical drug delivery vehicles clinically. Chemotherapy monotherapy is prone to drug resistance. Chemotherapy combined with other therapies such as nucleic acid drugs is an effective way to avoid drug resistance and the toxicity of continuous chemotherapy. In this study, chemotherapy and siRNA therapy were combined to treat paclitaxel-resistant NSCLC in order to increase efficacy and reduce toxicity. This study aims to develop a cabazitaxel-loaded human serum albumin nanoparticles (CTX-HSA-NPs) to improve the toxicity of traditional CTX-Tween 80 and increase targeting, and to develop a TGFβ-1 siRNA lipid Nanoparticles (TGFβ-1 siRNA LNP) combined with chemotherapy in the treatment of paclitaxel-resistant NSCLC. Results This study prepared CTX-HSA-NPs and TGFβ-1 siRNA LNP had small particle size, high encapsulation efficiency (EE). CTX-HSA-NPs lyophilized powder has high stability after dissolved. The antitumor effect of CTX-HSA-NPs on paclitaxel-resistant NSCLC was higher than that of CTX-Tween, and the toxicity was 1.8 times lower than that of CTX-Tween. More importantly, the combined treatment of TGFβ-1 siRNA LNP and CTX-HSA-NPs could effectively improve the antitumor efficacy of paclitaxel-resistant NSCLC in vivo and in vitro. The results of tumor immunohistochemistry showed that TGFβ-1 siRNA LNP significantly inhibited the expression of TGFβ-1, and compared with other groups, the expression of P-gp after low-dose CTX-HSA-NPs treatment was lower, which did not cause obvious drug resistance. Conclusions The antitumor effect of CTX-HSA-NPs on paclitaxel-resistant NSCLC was higher than that of CTX-Tween, and the toxicity was lower than that of CTX-Tween. TGFβ-1 siRNA LNP can treat paclitaxel-resistant NSCLC by inhibiting the express of TGFβ-1 mRNA. The combined treatment of TGFβ-1 siRNA LNP and CTX-HSA-NPs could effectively improve the antitumor efficacy of paclitaxel-resistant NSCLC. A combination therapy of chemotherapy and nucleic acid drugs could be an effective approach for treating paclitaxel-resistant NSCLC.

Abstract Background Effective treatment of glioma requires a nanocarrier that can cross the blood–brain barrier (BBB) to target the tumor lesion. In the current study, elemene (ELE) and cabazitaxel (CTX) liposomes were prepared by conjugating liposomes with transferrin (Tf) and embedding the cell membrane proteins of RG2 glioma cells into liposomes (active-targeting biomimetic liposomes, Tf-ELE/CTX@BLIP), which exhibited effective BBB infiltration to target glioma. Results The findings showed that Tf-ELE/CTX@BLIP was highly stable. The liposomes exhibited highly significant homologous targeting and immune evasion in vitro and a 5.83-fold intake rate compared with classical liposome (ELE/CTX@LIP). Bioluminescence imaging showed increased drug accumulation in the brain and increased tumor penetration of Tf-ELE/CTX@BLIP in orthotopic glioma model nude mice. Findings from in vivo studies indicated that the antitumor effect of the Tf-ELE/CTX@BLIP led to increased survival time and decreased tumor volume in mice. The average tumor fluorescence intensity after intravenous administration of Tf-ELE/CTX@BLIP was 65.2, 12.5, 22.1, 6.6, 2.6, 1.5 times less compared with that of the control, CTX solution, ELE solution, ELE/CTX@LIP, ELE/CTX@BLIP, Tf-ELE/CTX@LIP groups, respectively. Histopathological analysis showed that Tf-ELE/CTX@BLIP were less toxic compared with administration of the CTX solution. Conclusion These findings indicate that the active-targeting biomimetic liposome, Tf-ELE/CTX@BLIP, is a promising nanoplatform for delivery of drugs to gliomas. Graphic Abstract

Chondroitin sulfate-mediated albumin corona nanoparticles were readily prepared without any chemical reaction, and their active tumor targeting and therapeutic effects were examined. Negatively charged chondroitin sulfate (CS) and positively charged doxorubicin (DOX) self-assembled into nanoparticles (CS-DOX-NPs) via electrostatic interactions. Bovine serum albumin (BSA) was then adsorbed on the surface of CS-DOX-NPs to form albumin corona nanoparticles (BC-DOX-NPs) protected from endogenous proteins. Due to the dual effect of BSA and CS, BC-DOX-NPs interacted with the gp60, SPARC and CD44 receptors on tumor cells, facilitating their rapid and efficient transcytosis and improving their accumulation and uptake within tumor tissues. The simultaneous presence of BSA and CS also allowed BC-DOX-NPs to target CD44 efficiently, leading to greater cellular uptake and cytotoxicity against 4T1 cells than CS-DOX-NPs or free DOX. Intravenous injection of BC-DOX-NPs into orthotopic 4T1 tumor-bearing mice led to greater drug accumulation at the tumor site than with CS-DOX-NPs or free DOX, resulting in significant inhibition of tumor growth and lower exposure of major organs to the drug.

Since it is low in cost and low in toxicity and has good biodegradability, gas-liquid-foam three-phase flow has been widely used in industrial fire protection. Due to the different characteristics of gas, liquid, and foam, liquid precipitation is liable to occur under static conditions, resulting in unstable performance of the mixture. To improve fire extinguishing efficiency, it is of great significance to study the separation process of gas-liquid-foam. In the present study, the effects of the surface tension (range from 0.04 to 0.07) and initial liquid volume fraction (range from 0.2 to 0.5) on the gas-liquid-foam separation process are investigated with the numerical tool Fluent. The liquid volume fraction is mainly influenced by two inverse effects: (a) the transformation of liquid into foam, and (b) the liquid drainage and bursting of foam. In the separation process, the volume fraction of small foam decreases monotonically while the volume fraction of medium and large foam increases slightly. Since the volume fraction of small foam is much greater than medium and large foam and its bursting process is dominant, the liquid volume fraction presents a monotonic increasing trend. The volume of the separated liquid increases almost linearly with time at various surface tensions and initial volume fractions, and the increase rate is about 0.004. In the range of the surface tension examined, the separation process is insensitive to the surface tension, resulting in almost the same drainage time. On the other hand, the separation process depends on the initial liquid volume fraction non-monotonically; namely, when the initial volume fraction is small, with the increase of the initial volume fraction, the liquid is more easily separated from the mixture, and when the initial volume fraction is over a critical value (about 0.4), the separation process is decelerated.

Malignant tumors are life-threatening, and chemotherapy is one of the common treatment methods. However, there are often many factors that contribute to the failure of chemotherapy. The multidrug resistance of cancer cells during chemotherapy has been reported, since tumor cells’ sensitivity decreases over time. To overcome these problems, extensive studies have been conducted to reverse drug resistance in tumor cells. Elemene, an extract of the natural drug Curcuma wenyujin, has been found to reverse drug resistance and sensitize cancer cells to chemotherapy. Mechanisms by which elemene reverses tumor resistance include inhibiting the efflux of ATP binding cassette subfamily B member 1(ABCB1) transporter, reducing the transmission of exosomes, inducing apoptosis and autophagy, regulating the expression of key genes and proteins in various signaling pathways, blocking the cell cycle, inhibiting stemness, epithelial–mesenchymal transition, and so on. In this paper, the mechanisms of elemene’s reversal of drug resistance are comprehensively reviewed.

Abstract Background Obesity is characterized by excessive fat accumulation, which is related with abnormal pluripotency of mesenchymal stem cells (MSCs). Recently, there is growing evidence that the disorder of maternal vitamin D (VD) intake is a well-known risk factor for long-term adverse health outcomes to their offspring. Otherwise, less is known of its repercussion and underlying mechanisms on the different differentiation potential of MSCs. Methods Four-week-old female C57BL/6J mice were fed with different VD reproductive diets throughout the whole pregnancy and lactation. The characteristics of BMSCs from their seven-day male offspring, VDR knockdown establishment of HuMSCs and HuMSCs under the different VD interventions in vitro were confirmed by flow cytometry, RT-PCR, and immunofluorescence. The roles of VD on their mitochondrial dysfunction and differentiation potential were also investigated. Then their remaining weaned male pups were induced by administrating high-fat-diet (HFD) for 16 weeks and normal fat diet was simultaneously as controls. Their lipid accumulation and adipocytes hypertrophy were determined by histological staining and related gene expressions. Results Herein, it was proved that imbalance of early-life VD intake could significantly aggravate the occurrence of obesity by inducing the adipogenesis through affecting the VD metabolism and related metabolites (P

Abstract Exposure to nutritional or environmental factors in early life determines susceptibility to nonalcoholic fatty liver disease (NAFLD). The effect of paternal preconceptional n‐3 polyunsaturated fatty acids (n‐3 PUFAs) on offspring NAFLD development remains unknown. Herein, a mouse model that weaning male mice (F0) received diet supplementation of normal n‐3 PUFA content (n‐6:n‐3 PUFA ratio = 4.3:1) or high n‐3 PUFA content (n‐6:n‐3 ratio = 1.5:1) for 12 weeks, and an n‐3 PUFA‐deficient diet as control, was used for the production of next generation. The F1 and F2 offspring were generated by mating F0 and F1 male mice with virgin female mice, respectively, and after weaning, were fed a high‐fat diet to induce NAFLD. The paternal n‐3 PUFA supplementation improved the scores of steatosis, inflammation and ballooning, and the fibrosis in the liver of two generations, with expressional upregulation of genes associated with fat oxidation (Atgl, Ppara, or Cpt1a), and downregulation of inflammatory genes (Ccl2, Tnf‐α, F4/80, CD206, or CD11c) and fibrosis genes (Tgf‐β, Timp1, or Col1a1). The lessened brown adipose tissue whitening, altered gut bacterial compositions, and altered expression of the imprinted genes (H19, Igf2, and Plagl1) might mediate the impact of paternal n‐3 PUFAs on offspring's NAFLD development, which was dose‐dependent. The data indicate that preconceptional higher paternal intake of n‐3 PUFAs might have intergenerational and transgenerational alleviating impact on obesity‐associated NAFLD development in the offspring through multiple pathways.

AbstractAcute myocardial infarction, characterized by high morbidity and mortality, has now become a serious health hazard for human beings. Conventional surgical interventions to restore blood flow can rapidly relieve acute myocardial ischemia, but the ensuing myocardial ischemia-reperfusion injury (MI/RI) and subsequent heart failure have become medical challenges that researchers have been trying to overcome. The pathogenesis of MI/RI involves several mechanisms, including overproduction of reactive oxygen species, abnormal mitochondrial function, calcium overload, and other factors that induce cell death and inflammatory responses. These mechanisms have led to the exploration of antioxidant and inflammation-modulating therapies, as well as the development of myocardial protective factors and stem cell therapies. However, the short half-life, low bioavailability, and lack of targeting of these drugs that modulate these pathological mechanisms, combined with liver and spleen sequestration and continuous washout of blood flow from myocardial sites, severely compromise the expected efficacy of clinical drugs. To address these issues, employing conventional nanocarriers and integrating them with contemporary biomimetic nanocarriers, which rely on passive targeting and active targeting through precise modifications, can effectively prolong the duration of therapeutic agents within the body, enhance their bioavailability, and augment their retention at the injured myocardium. Consequently, these approaches significantly enhance therapeutic effectiveness while minimizing toxic side effects. This article reviews current drug delivery systems used for MI/RI, aiming to offer a fresh perspective on treating this disease.

Purpose: This study aimed to investigated the key chemical components and the effect of the aqueous extract of Schisandra sphenanthera (SSAE) on alcoholic liver disease (ALD) and the related molecular mechanism. Methods: This study employed UPLC-Q-TOF-MS/MS to identify the chemical compositions in SSAE. ALD rat model was established through oral administration of white spirit. Transcriptome sequencing, weighted gene co-expression network construction analysis (WGCNA), and network pharmacology were used to predict key compositions and pathways targeted by SSAE for the treatment of ALD. Enzyme-linked immunosorbent assay (ELISA), biochemical kits, hematoxylin-eosin (HE) staining, Western blotting (WB) analysis, and immunohistochemical analysis were used to validate the mechanism of action of SSAE in treating ALD. Results: Active ingredients such as schisandrin A, schisandrol A, and schisandrol B were found to regulate the PI3K/AKT/IKK signaling pathway. Compared to the model group, the SSAE group demonstrated significant improvements in cellular solidification and tissue inflammation in the liver tissues of ALD model rats. Additionally, SSAE regulated the levels of a spartate aminotransferase (AST), alanine aminotransferase (ALT), alcohol dehydrogenase (ADH), and aldehyde Dehydrogenase (ALDH) in serum (P

As a response of the coastal oceans to more severe anthropogenic disturbance, increasing coastal primary production has been more frequently observed in recent years. This raises the question of how this progressive change reshapes the long-term carbon sequestration in the coastal oceans. With this question in mind, we investigated the sediment organic matter (OM) preserved on the shelf of the northern South China Sea (NSCS) where high primary production has been observed. Across this sediment core, relatively low total organic carbon content of around 0.60% was observed. Fatty acids with less carbon numbers exhibit exponential decreases downward with degradation rate constants ranging from 0.10 to 0.17 y-1, no matter they were from single sources (14:0 presumably from marine OM and ai-15:0, i-15:0, 15:0 from bacterial OM) or mixed sources (16:0). Meanwhile fatty acids with more carbon numbers, either 18:0 and 24:0 from mixed sources, or 26:0 and 28:0 presumably from terrestrial input, were less varied in concentrations with depth. This demonstrates a preferential decomposition of labile fatty acids during the early diagenesis of coastal sediment organic matter. A decrease of labile fatty acids δ13C values was observed with the decomposition, from which kinetic isotope fractionations were predicted ranging from 0.7 to 1.5‰. This provides an isotopic constraint of the mixing model to quantify labile organic matter from terrestrial input and local phytoplankton production, from which declined contribution of local phytoplankton production to labile fatty acids was identified in more recent sediment. This finding together with the low organic carbon content and rapid removal of fatty acids in the top sediment, demonstrates the poor preservation of labile organic matter on the shelf of NSCS, implying that the increasing primary production has not enhanced the coastal carbon sequestration yet, but rather leads to more intensified respiration with a potential risk to increase the CO2 outgassing from the coastal oceans.

Allergic respiratory diseases can increase serum carcinoembryonic antigen levels. We report three cases experiencing allergic symptoms that proved refractory to inhaled corticosteroids but exhibited a positive response to long-term treatment with oral corticosteroids. This response was characterized by a synchronous alteration in serum eosinophil counts and carcinoembryonic antigen levels. Immunofluorescence assays indicated localized carcinoembryonic antigen production within eosinophils. In addition, we conducted a systematic review of patients exhibiting similar characteristics on PubMed. After comprehensively reviewing this unique pathophysiological condition, we herein introduced a novel term “Allergic hyper-carcinoembryonic antigen syndrome,” defined by the following criteria: (1) recurrent asthmatic attacks; (2) eosinophilia or pulmonary eosinophilic infiltrations accompanied by elevated serum carcinoembryonic antigen levels; (3) pulmonary lesions determined by imaging or biopsy; (4) exclusion of malignancy and infections; and (5) responsive to systemic corticosteroids. Allergic hyper-carcinoembryonic antigen syndrome suggests systemic corticosteroids should be introduced early when managing allergic patients with both eosinophilia and elevated serum carcinoembryonic antigen levels.

In machine learning (ML)-based hydrological forecasting, particularly in medium- and long-term prediction, judicious predictor selection is paramount, as it ultimately determines the forecast accuracy. This study pioneered an advanced predictor-screening method that synergizes the mutual information (MI) and random forest (RF) technologies through minimum-redundancy-maximum-relevance-recursive feature elimination-random forest (mRMR-RFE-RF) method, blending both filtering and wrapping techniques. This method was rigorously tested through a detailed case study in the Danjiangkou basin, where a comprehensive analysis of 1560 meteorological factors was conducted. Employing three sophisticated ML algorithms—RF, eXtreme Gradient Boosting (XGB), and Light Gradient Boosting (LGB)—we developed precipitation forecasting models. Furthermore, we performed an in-depth rationality analysis of high-frequency predictors. The findings from our study show that this novel hybrid screening strategy markedly outperformed conventional singular predictor-screening methods in enhancing the accuracy of precipitation forecasting when integrated into these forecasting models. Moreover, it assured the validity of the high-frequency forecast factors employed. Therefore, this innovative method not only elevates the accuracy of medium- and long-term precipitation forecasting but also contributes a novel perspective to the methodology of predictor selection in hydrological forecasting models.

Accurate medium- and long-term hydrological forecasting is crucial for sustainable water management, infrastructure planning, and ecosystem conservation. This study integrates visual geometry group convolution neural network algorithm (VGGNet)-driven precipitation similarity analysis with hydrological modeling to enhance streamflow forecasting accuracy. Traditional process-driven hydrological models, which rely on detailed physical mechanisms, often falter in data-scarce regions, whereas data-driven models, despite their simplicity, lack interpretability. By combining these approaches, we propose a novel methodology that leverages the image recognition capabilities of convolutional neural network, specifically VGGNet, to perform precipitation similarity analysis. This method transforms monthly precipitation data into daily forecasts, addressing the challenge of temporal downscaling. The Danjiangkou Basin in China serves as the study area, with historical precipitation and streamflow data from 1982 to 2015. The VGGNet model identifies historical months with similar precipitation patterns, and the Soil and Water Assessment Tool model is used to predict streamflow. Results demonstrate significant improvements in forecasting accuracy, with Pearson Correlation Coefficient of 0.89 and Nash-Sutcliffe Efficiency of 0.79. This integrated approach shows promise for advancing medium- and long-term hydrological forecasting techniques, providing a robust tool for effective water resource management.

The accurate prediction of climate patterns is crucial for effective environmental management and strategic planning, particularly in the face of increasing climate variability and extreme weather events. This study focuses on enhancing the predictive accuracy of global climate models by integrating a random forest algorithm with seasonal bias correction, which is aimed at forecasting changes in precipitation and temperature across various climate scenarios. Our approach significantly improves the precision of climate forecasts by using a comprehensive dataset that includes historical climate data and future projections under Representative Concentration Pathways. For precipitation, after implementing seasonal bias correction, the Correlation Coefficient improved from 0.826 to 0.860, and the Nash–Sutcliffe Efficiency increased from 0.633 to 0.735. In addition, the Mean Absolute Error and Root Mean Square Error decreased, thereby enhancing the model's reliability in predicting extreme precipitation events. Temperature forecasts also benefited from the Random Forest model, achieving a Correlation Coefficient of up to 0.987, indicating a strong predictive performance. These improvements highlight the potential of machine learning methods in refining climate models, thus providing more accurate tools for policymakers and planners to manage climate risks. Furthermore, the successful application of these advanced statistical techniques underscores the importance of continuous innovation in climate science, ensuring that climate projections remain relevant and reliable in informing global climate resilience and adaptation strategies.

The maintenance of biodiversity and ecological balance heavily relies on the diversity of insects. In order to investigate the impacts of elevation and human disturbance, as well as their interactions on insect diversity, we conducted an intensive survey of insects in the Hengduan Mountain Range, which is situated on the southeastern periphery of the Tibetan Plateau in China. A total of 50 line transects were established in this study to investigate the impact of elevation and human disturbance on insect diversity and distribution patterns. Designed insect surveys were conducted at various elevations and levels of human disturbance, and statistical methods such as generalized linear modeling and redundancy analysis were employed for data analysis. The results of this study indicated a negative correlation between insect diversity and elevation. Additionally, moderate disturbance was found to have a positive impact on insect diversity to some extent. The explanatory power of the model for the distribution of insect diversity could be improved if elevation and human disturbance were included as an interaction effect into the model, and there were differences in the effects of human disturbances on insect diversity at different elevation levels. The highest insect diversity was observed under low disturbance conditions below elevation of ~2200 m, whereas above this threshold, insect diversity was the highest under moderate disturbance compared to low disturbance. The response of different insect taxa to the interactions of elevation and human disturbance varied. The findings imply that when formulating strategies for managing insect diversity, it is crucial to thoroughly consider the interaction of environmental factors and disturbance response of individual insect taxa.

Rosemary (Rosmarinus officinalis L) is a medicinal and edible plant. Rosemary essential oil (REO) is the principal constituent of rosemary and possesses anti-inflammatory and antioxidant properties. In this study, we evaluated the cell viability and anti-inflammatory activity of REO through the MTT assay and LPS-induced NO production in mouse RAW264.7 cells, respectively. The optimal formulation for the preparation of REO- microemulsion (REO-ME) was determined employing reversed-phase emulsification in conjunction with pseudo-triphasic diagrams. Transcriptomics, combined with network pharmacology, was employed to identify key signaling pathways, and molecular docking analysis was performed to investigate the relationship between the active ingredients of REO-ME and the key targets. The results showed that REO-ME is an O/W type ME. In addition, further pharmacodynamic experiments showed that REO-ME inhibits the expression of inflammatory factors such as IL-6, IL-1β, and TNF-α by regulating the key targets in the IL-17 signaling pathway, thereby to alleviating UC.

ObjectiveThe aim of this study was to identify the molecular subtypes of breast cancer based on chromatin regulator-related genes.MethodsThe RNA sequencing data of The Cancer Genome Atlas–Breast Cancer cohort were obtained from the official website, while the single-cell data were downloaded from the Gene Expression Omnibus database (GSE176078). Validation was performed using the Molecular Taxonomy of Breast Cancer International Consortium dataset. Furthermore, the immune characteristics, tumor stemness, heterogeneity, and clinical characteristics of these molecular subtypes were analyzed. The correlation between chromatin regulators and chemotherapy resistance was examined in vitro using the quantitative real-time polymerase chain reaction (qRT-PCR) and Cell Counting Kit-8 (CCK8) assays.ResultsThis study identified three stable molecular subtypes with different prognostic and pathological features. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein–protein interaction analyses revealed that the differentially expressed genes were associated with disease processes, such as mitotic nuclear division, chromosome segregation, condensed chromosome, and specific chromosome region. The T stage and subtypes were correlated with the clinical features. Tumor heterogeneity (mutant-allele tumor heterogeneity, tumor mutational burden, purity, and homologous recombination deficiency) and tumor stemness (RNA expression-based stemness score, epigenetically regulated RNA expression-based stemness score, DNA methylation-based stemness score, and epigenetically regulated DNA methylation-based stemness score) significantly varied between the three subtypes. Furthermore, Western blotting, qRT-PCR, and CCK8 assays demonstrated that the expression of ASCL1 was positively correlated with chemotherapy resistance in breast cancer.ConclusionThis study identified the subtypes of breast cancer based on chromatin regulators and analyzed their clinical features, gene mutation status, immunophenotype, and drug sensitivity. The results of this study provide effective strategies for assessing clinical prognosis and developing personalized treatment strategies.

Abstract Background Metaplastic breast cancer(MBC) is a specific pathological type of invasive breast cancer. There are few studies related to MBC due to its rarity. This study aimed to analyse the differences in clinicopathological characteristics and prognosis between Metaplastic breast cancer and triple-negative invasive ductal carcinoma (TN-IDC). Methods We retrospectively compared the clinicopathological characteristics of patients diagnosed with MBC and TN-IDC at the Fourth Hospital of Hebei Medical University between 2011 and 2020 in a 1:2 ratio. The log-rank test was used to compare the two groups’ disease-free survival (DFS) and overall survival (OS). For MBCs, we performed univariate and multivariate analyses using the Cox proportional hazards model to determine the characteristics that impacted OS and DFS. Results A total of 81 patients with MBC and 162 patients with TN-IDC were included in this study. At initial diagnosis, MBC patients had larger tumour diameters(P = 0.03) and fewer positive lymph nodes (P = 0.04). Patients with MBC were more likely to have organ metastases after surgery (P = 0.03). Despite receiving the same treatment, MBC patients had worse DFS (HR = 1.66, 95%CI 0.90–3.08, P = 0.11) and OS (HR = 1.98, 95% CI 1.03–3.81, P = 0.04), and OS was statistically significant. Positive lymph nodes at initial diagnosis were associated with worse DFS (HR = 3.98, 95%CI 1.05–15.12, P = 0.04) and OS (HR = 3.70, 95%CI 1.03–13.34, P = 0.04) for patients with MBC. The efficacy of platinum-based agents is insensitive for MBC patients receiving chemotherapy. In addition, patients treated with preoperative chemotherapy had worse DFS compared to patients treated with postoperative chemotherapy (HR = 3.51, 95%CI 1.05–11.75, P = 0.04). Conclusions The clinicopathological characteristics and prognosis of MBC and TN-IDC differ in many ways. Further studies are required to determine suitable treatment guidelines for patients with MBC.

Abstract Background Previous studies have linked gut microbiota with cancer etiology, but the associations for specific gut microbiota are causal or owing to bias remain to be elucidated. Methods We performed a two‐sample Mendelian randomization (MR) analysis to assess the causal effect of gut microbiota on cancer risk. Five common cancers, including breast, endometrial, lung, ovarian, and prostate cancer as well as their subtypes (sample sizes ranging from 27,209 to 228,951) were included as the outcomes. Genetic information for gut microbiota was obtained from a genome‐wide association study (GWAS) comprising 18,340 participants. In univariable MR (UVMR) analysis, the inverse variance weighted (IVW) method was conducted as the primary method, with the robust adjusted profile scores, weighted median, and MR Egger used as supplementary methods for causal inference. Sensitivity analyses including the Cochran Q test, Egger intercept test, and leave‐one‐out analysis were performed to verify the robustness of the MR results. Multivariable MR (MVMR) was performed to evaluate the direct causal effects of gut microbiota on the risk of cancers. Results UVMR detected a higher abundance of genus Sellimonas predicted a higher risk of estrogen receptor‐positive breast cancer (OR = 1.09, 95% CI 1.05–1.14, p = 2.01 × 10−5), and a higher abundance of class Alphaproteobacteria was associated with a lower risk of prostate cancer (OR = 0.84, 95% CI 0.75–0.93, p = 1.11 × 10−3). Sensitivity analysis found little evidence of bias in the current study. MVMR further confirmed that genus Sellimonas exerted a direct effect on breast cancer, while the effect of class Alphaproteobacteria on prostate cancer was driven by the common risk factors of prostate cancer. Conclusion Our study implies the involvement of gut microbiota in cancer development, which provides a novel potential target for cancer screening and prevention, and might have an implication for future functional analysis.