[Clinical Multi-features Analysis of Cystic Lung Adenocarcinoma 
and Construction of Invasive Risk Prediction Model].

BACKGROUND: Cystic lung cancer, a special type of lung cancer, has been paid more and more attention. The most common pathological type of cystic lung cancer is adenocarcinoma. The invasiveness of cystic lung adenocarcinoma is vital for the selection of clinical treatment and prognosis. The aim of this study is to analyze the multiple clinical features of cystic lung adenocarcinoma, explore the independent risk factors of its invasiveness, and establish a risk prediction model. METHODS: A total of 129 cases of cystic lung adenocarcinoma admitted to the Department of Thoracic Surgery of the First Affiliated Hospital of Nanjing Medical University from January 2021 to July 2022 were retrospectively analyzed and divided into pre-invasive group [atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA)] and invasive group [invasive adenocarcinoma (IAC)] according to pathological findings. There were 47 cases in the pre-invasive group, including 19 males and 28 females, with an average age of (51.23±14.96) years. There were 82 cases in the invasive group, including 60 males and 22 females, with an average age of (61.27±11.74) years. Multiple clinical features of the two groups were collected, including baseline data, imaging data and tumor markers. Univariate analysis, LASSO regression and multivariate Logistic regression analysis were used to screen out the independent risk factors of the invasiveness of cystic lung adenocarcinoma, and the risk prediction model was established. RESULTS: In univariate analysis, age, gender, smoking history, history of emphysema, neuron-specific enolase (NSE), number of cystic airspaces, lesion diameter, cystic cavity diameter, nodule diameter, solid components diameter, cyst wall nodule, smoothness of cyst wall, shape of cystic airspace, lobulation, short burr sign, pleural retraction, vascular penetration and bronchial penetration were statistically different between the pre-invasive group and invasive groups (P<0.05). The above variables were processed by LASSO regression dimensionality reduction and screened as follows: age, gender, smoking history, NSE, number of cystic airspaces, lesion diameter, cystic cavity diameter, cyst wall nodule, smoothness of cyst wall and lobulation. Then the above variables were included in multivariate Logistic regression analysis. Cyst wall nodule (P=0.035) and lobulation (P=0.001) were found to be independent risk factors for the invasiveness of cystic lung adenocarcinoma (P<0.05). The prediction model was established as follows: P=e^x/(1+e^x), x=-7.927+1.476* cyst wall nodule+2.407* lobulation, and area under the curve (AUC) was 0.950. CONCLUSIONS: Cyst wall nodule and lobulation are independent risk factors for the invasiveness of cystic lung adenocarcinoma, which have certain guiding significance for the prediction of the invasiveness of cystic lung adenocarcinoma.

AM-MSFF: A Pest Recognition Network Based on Attention Mechanism and Multi-Scale Feature Fusion.

Traditional methods for pest recognition have certain limitations in addressing the challenges posed by diverse pest species, varying sizes, diverse morphologies, and complex field backgrounds, resulting in a lower recognition accuracy. To overcome these limitations, this paper proposes a novel pest recognition method based on attention mechanism and multi-scale feature fusion (AM-MSFF). By combining the advantages of attention mechanism and multi-scale feature fusion, this method significantly improves the accuracy of pest recognition. Firstly, we introduce the relation-aware global attention (RGA) module to adaptively adjust the feature weights of each position, thereby focusing more on the regions relevant to pests and reducing the background interference. Then, we propose the multi-scale feature fusion (MSFF) module to fuse feature maps from different scales, which better captures the subtle differences and the overall shape features in pest images. Moreover, we introduce generalized-mean pooling (GeMP) to more accurately extract feature information from pest images and better distinguish different pest categories. In terms of the loss function, this study proposes an improved focal loss (FL), known as balanced focal loss (BFL), as a replacement for cross-entropy loss. This improvement aims to address the common issue of class imbalance in pest datasets, thereby enhancing the recognition accuracy of pest identification models. To evaluate the performance of the AM-MSFF model, we conduct experiments on two publicly available pest datasets (IP102 and D0). Extensive experiments demonstrate that our proposed AM-MSFF outperforms most state-of-the-art methods. On the IP102 dataset, the accuracy reaches 72.64%, while on the D0 dataset, it reaches 99.05%.

Inflammation-based lung adenocarcinoma molecular subtype identification and construction of an inflammation-related signature with bulk and single-cell RNA-seq data.

The role of inflammation is increasingly understood to have a central influence on therapeutic outcomes and prognosis in lung adenocarcinoma (LUAD). However, the detailed molecular divisions involved in inflammatory responses are yet to be fully elucidated. Our study identified two main inflammation-oriented LUAD grades: the inflammation-low (INF-low) and the inflammation-high (INF-high) subtypes. Both presented with unique clinicopathological features, implications for prognosis, and distinctive tumor microenvironment profiles. Broadly, the INF-low grade, marked by its dominant immunosuppressive tumor microenvironment, was accompanied by less favorable prognostic outcomes and a heightened prevalence of oncogenic mutations. In contrast, the INF-high grade exhibited more optimistic clinical trajectories, underscored by its immune-active environment. In addition, our efforts led to the conceptualization and empirical validation of an inflammation-centric predictive model with considerable predictive potency. Our study paves the way for a refined inflammation-centric LUAD classification and fosters a deeper understanding of tumor microenvironment intricacies.

Metabolic perturbation of Streptomyces albulus by introducing NADP-dependent glyceraldehyde 3-phosphate dehydrogenase.

The available resources of Streptomyces represent a valuable repository of bioactive natural products that warrant exploration. Streptomyces albulus is primarily utilized in the industrial synthesis of ε-poly-L-lysine (ε-PL). In this study, the NADP-dependent glyceraldehyde 3-phosphate dehydrogenase (GapN) from Streptococcus mutans was heterologously expressed in S. albulus CICC11022, leading to elevated intracellular NADPH levels and reduced NADH and ATP concentrations. The resulting perturbation of S. albulus metabolism was comprehensively analyzed using transcriptomic and metabolomic methodologies. A decrease in production of ε-PL was observed. The expression of gapN significantly impacted on 23 gene clusters responsible for the biosynthesis of secondary metabolites. A comprehensive analysis revealed a total of 21 metabolites exhibiting elevated levels both intracellularly and extracellularly in the gapN expressing strain compared to those in the control strain. These findings underscore the potential of S. albulus to generate diverse bioactive natural products, thus offering valuable insights for the utilization of known Streptomyces resources through genetic manipulation.

[Comparison of four early warning scores in predicting the prognosis of critically ill patients in secondary hospitals].

OBJECTIVE: To explore the predictive value of acute physiology and chronic health evaluation II (APACHE II), sequential organ failure assessment (SOFA), quick sequential organ failure assessment (qSOFA) and modified early warning score (MEWS) in evaluating the prognosis of patients in intensive care unit (ICU) of secondary hospitals, and to provide guidance for clinical application. METHODS: The clinical data of adult critical patients admitted to the ICU of Wanzhou District First People's Hospital from October 2022 to April 2023 were retrospectively analyzed. According to the clinical outcome of ICU, the patients were divided into improvement group and death group. The general information, blood routine, heart, liver and kidney function indicators, coagulation indicators, blood gas analysis, APACHE II score, SOFA score, qSOFA score, MEWS score at the time of admission to the ICU, the number of cases of invasive mechanical ventilation (IMV) and continuous blood purification (CBP) were compared between the two groups. Univariate analysis was performed, and multivariate Logistic regression analysis was used to analyze the related factors of death. Receiver operator characteristic curve (ROC curve) was used to analyze the predictive value of the four scores in ICU patients. RESULTS: A total of 126 patients were included, of which 45 patients died in the ICU and 81 patients improved and transferred out. Univariate analysis of death-related critically ill patients showed that procalcitonin (PCT), serum creatinine (SCr), blood urea nitrogen (BUN), albumin (ALB), prothrombin time (PT), activated partial prothrombin time (APTT), D-dimer, pH value, HCO3-, blood lactic acid (Lac), number of patients treated with IMV and CBP, APACHE II score, SOFA score, qSOFA score and MEWS score were significantly different between the two groups (all P < 0.05). Multivariate Logistic regression analysis showed that the APACHE II score [odds ratio (OR) = 1.115, 95% confidence interval (95%CI) was 1.025-1.213, P = 0.011], SOFA score (OR = 1.204, 95%CI was 1.037-1.398, P = 0.015), MEWS score (OR = 1.464, 95%CI was 1.102-1.946, P = 0.009), and APTT (OR = 1.081, 95%CI was 1.015-1.152, P = 0.016) were independent risk factors affecting the mortality of critically ill patients in the ICU. ROC curve analysis showed that APACHE II, SOFA, qSOFA, and MEWS scores could predict the prognosis of critically ill ICU patients, among which SOFA score had the strongest predictive effect, and the area under the curve (AUC) was 0.808. There was a statistically significant difference in the time required for the four scores (F = 117.333, P < 0.001), among which the MEWS scoring required the shortest time [(1.03±0.39) minutes], and the APACHE II scoring required the longest time [(2.81±1.04) minutes]. CONCLUSIONS: APACHE II, SOFA, qSOFA, and MEWS scores can be used to assess the severity of critically ill patients and predict in-hospital mortality. The SOFA score is superior to other scores in predicting severity. The MEWS is preferred because its assessment time is shortest. Early warning score can help secondary hospitals to detect potentially critical patients early and provide help for clinical rapid urgent emergency decision-making.

AM3F-FlowNet: Attention-Based Multi-Scale Multi-Branch Flow Network.

Micro-expressions are the small, brief facial expression changes that humans momentarily show during emotional experiences, and their data annotation is complicated, which leads to the scarcity of micro-expression data. To extract salient and distinguishing features from a limited dataset, we propose an attention-based multi-scale, multi-modal, multi-branch flow network to thoroughly learn the motion information of micro-expressions by exploiting the attention mechanism and the complementary properties between different optical flow information. First, we extract optical flow information (horizontal optical flow, vertical optical flow, and optical strain) based on the onset and apex frames of micro-expression videos, and each branch learns one kind of optical flow information separately. Second, we propose a multi-scale fusion module to extract more prosperous and more stable feature expressions using spatial attention to focus on locally important information at each scale. Then, we design a multi-optical flow feature reweighting module to adaptively select features for each optical flow separately by channel attention. Finally, to better integrate the information of the three branches and to alleviate the problem of uneven distribution of micro-expression samples, we introduce a logarithmically adjusted prior knowledge weighting loss. This loss function weights the prediction scores of samples from different categories to mitigate the negative impact of category imbalance during the classification process. The effectiveness of the proposed model is demonstrated through extensive experiments and feature visualization on three benchmark datasets (CASMEII, SAMM, and SMIC), and its performance is comparable to that of state-of-the-art methods.

Isolation, structures, bioactivities, application and future prospective for polysaccharides from Tremella aurantialba: A review.

Since ancient times, Tremella aurantialba has been proposed to have medicinal and food benefits. Modern phytochemistry and pharmacological studies have demonstrated that polysaccharides, the main components from T. aurantialba appear to be an all-round talent resisting a variety of chronic inflammatory diseases and protecting against different types of tumors, diabetes and cardiovascular diseases. These health and pharmacological benefits have gained much attention from scholars around the world. Further, more and more methods for polysaccharides extraction, purification, structure identification have been proposed. Significantly, the bioactivity of fungus polysaccharides is affected by many factors such as extraction and purification conditions and chemical structure. This paper provides an overview of recent advances in the isolation, structural features and biological effects of polysaccharides derived from T. aurantialba, covers recent advances in the field and outlines future research and applications of these polysaccharides.

Evaluation of pharmacological activities and active components in Tremella aurantialba by instrumental and virtual analyses.

As a kind of medicinal and edible homologous fungus, there is a lack of data on the medicinal value of Tremella aurantialba. In this study, ultra-performance liquid chromatography-quadrupole-time of flight-mass spectrometry (UPLC-Q-TOF/MS) was used to screen the chemical components in T. aurantialba. Then, network pharmacology was used to reveal the potential biological activities, active compounds, and therapeutic targets of T. aurantialba. Finally, the potential binding sites of the active compounds of T. aurantialba and key targets were studied by molecular docking. Results showed that 135 chemical components in T. aurantialba, especially linoleic acid, and linolenic acid have significant biological activities in neuroprotective, anticancer, immune, hypoglycemic, and cardiovascular aspects. The existence of these bioactive natural products in T. aurantialba is consistent with the traditional use of T. aurantialba. Moreover, the five diseases have comorbidity molecular mechanisms and therapeutic targets. The molecular docking showed that linolenic acid, adenosine, and vitamin D2 had higher binding energy with RXRA, MAPK1, and JUN, respectively. This study is the first to systematically identify chemical components in T. aurantialba and successfully predict its bioactivity, key active compounds, and drug targets, providing a reliable novel strategy for future research on the bioactivity development and utilization of T. aurantialba.

Microfluidic Microwave Sensor Loaded with Star-Slotted Patch for Edible Oil Quality Inspection.

In this paper, we present a new microfluidic microwave sensor loaded with a star-slotted patch for detecting the quality of edible oil. The relative dielectric permittivity and the quality of edible oil will change after being heated at a high temperature. Therefore, the quality of edible oil can be detected by measuring the relative dielectric permittivity of edible oil. The sensor is used to determine the edible oil with different dielectric permittivity by measuring the resonance frequency offset of the input reflection coefficient, which operates at 2.68 GHz. This sensor is designed based on a resonant approach to provide the best sensing accuracy and is implemented using a substrate integrated waveguide structure combined with a pentagonal slot antenna operating at 2.3~2.9 GHz. It can detect greasy liquids with the real part of the complex permittivity ranging from two to three.

Benzo(a)pyrene and cardiovascular diseases: An overview of pre-clinical studies focused on the underlying molecular mechanism.

Benzo(a)pyrene (BaP) is a highly toxic and carcinogenic polycyclic aromatic hydrocarbon (PAH) whose toxicological effects in the vessel-wall cells have been recognized. Many lines of evidence suggest that tobacco smoking and foodborne BaP exposure play a pivotal role in the dysfunctions of vessel-wall cells, such as vascular endothelial cell and vascular smooth muscle cells, which contribute to the formation and worsening of cardiovascular diseases (CVDs). To clarify the underlying molecular mechanism of BaP-evoked CVDs, the present study mainly focused on both cellular and animal reports whose keywords include BaP and atherosclerosis, abdominal aortic aneurysm, hypertension, or myocardial injury. This review demonstrated the aryl hydrocarbon receptor (AhR) and its relative signal transduction pathway exert a dominant role in the oxidative stress, inflammation response, and genetic toxicity of vessel-wall cells. Furthermore, antagonists and synergists of BaP are also discussed to better understand its mechanism of action on toxic pathways.

TOP1α fine-tunes TOR-PLT2 to maintain root tip homeostasis in response to sugars.

Plant development is highly dependent on energy levels. TARGET OF RAPAMYCIN (TOR) activates the proximal root meristem to promote root development in response to photosynthesis-derived sugars during photomorphogenesis in Arabidopsis thaliana. However, the mechanisms of how root tip homeostasis is maintained to ensure proper root cap structure and gravitropism are unknown. PLETHORA (PLT) transcription factors are pivotal for the root apical meristem (RAM) identity by forming gradients, but how PLT gradients are established and maintained, and their roles in COL development are not well known. We demonstrate that endogenous sucrose induces TOPOISOMERASE1α (TOP1α) expression during the skotomorphogenesis-to-photomorphogenesis transition. TOP1α fine-tunes TOR expression in the root tip columella. TOR maintains columella stem cell identity correlating with reduced quiescent centre cell division in a WUSCHEL RELATED HOMEOBOX5-independent manner. Meanwhile, TOR promotes PLT2 expression and phosphorylates and stabilizes PLT2 to maintain its gradient consistent with TOR expression pattern. PLT2 controls cell division and amyloplast formation to regulate columella development and gravitropism. This elaborate mechanism helps maintain root tip homeostasis and gravitropism in response to energy changes during root development.

[Clinical Characteristics and Risk Factors Analysis for Visceral Pleural Invasion in 
Mixed Ground-glass Nodular Lung Adenocarcinoma].

BACKGROUND: Lung cancer is still the malignant tumor with the highest morbidity and mortality in China. Lung adenocarcinoma is the most common subtype, and the number of lung cancer presenting as mixed ground glass nodule (mGGN) in imaging is gradually increasing. Visceral pleural invasion (VPI) is an important factor affecting the prognosis of mGGN type lung adenocarcinoma. The aim of the study is to explore and analyze the risk factors for VPI in mGGN type lung adenocarcinoma. METHODS: From November 2016 to November 2019, 128 patients with mGGN lung adenocarcinoma underwent radical surgical resection in the First Affiliated Hospital of Nanjing Medical University. Their clinical data, including imaging, pathological and biological features, were collected and analyzed retrospectively. There were 40 males and 88 females, aged 60.3±9.3 years ranging from 30 to 81 years. Single factor Chi-square test and multivariate Logistic regression were used to analyze the risk factors of VPI in mGGN type lung adenocarcinoma. RESULTS: Among 128 mGGN patients who met the inclusion criteria, 57 cases were pathologically confirmed with pleural invasion. Between the VPI (+) and VPI (-) group (P<0.05), there were significant differences in gender, maximum diameter of solid component, consolidation tumor ratio (CTR), spicule sign, history of lung disease, family history of hypertension, relation of lesion to pleura (RLP), coursing relationship between bronchi and nodules. In multivariate Logistic regression analysis, RLP (OR=3.529, 95%CI: 1.430-8.713, P=0.006) and coursing relationship between bronchi and nodules (OR=3.993, 95%CI: 1.517-10.51, P=0.005) were found to be independent risk factors for VPI (P<0.05). CONCLUSIONS: The possibility of VPI in m GGN lung adenocarcinoma should be evaluated by combining these parameters in clinical diagnosis and treatment. As independent risk factors, RLP and coursing relationship between bronchi and nodules are instructive to identify VPI in mGGN type lung adenocarcinoma.

Intermittent fasting suppressed splenic CD205+ G-MDSC accumulation in a murine breast cancer model by attenuating cell trafficking and inducing apoptosis.

Immune-based interventions are the most promising approach for new cancer treatments to achieve long-term cancer-free survival. However, the expansion of myeloid-derived suppression cells (MDSCs) attenuates the therapeutic potential of immunotherapy. We recently showed that CD205+ granulocytic MDSCs (G-MDSCs), but not T cells, are sensitive to glucose deficiency. Intermittent fasting (IF) may inhibit the growth of malignant cells by reducing serum glucose levels, but little is known regarding the influence of IF on MDSC expansion. Herein, we observed that IF selectively inhibited splenic accumulation of CD205+ G-MDSCs in a 4T1 and 4T07 transplant murine breast cancer model. The efficiency of IF in suppressing tumor growth was comparable to that of docetaxel. Further examination revealed that CXCR4 expression was concentrated in CD205+ subsets of tumor-induced G-MDSCs. Downregulation of CXCR4 correlated with a reduction in CD205+ G-MDSC trafficking from bone marrow to the spleen under IF treatment. In addition, ex vivo culture assays showed that glucose deficiency and 2-deoxy-D-glucose (2DG) treatment selectively induced massive death of splenic CD205+ G-MDSCs. Interestingly, 2DG emulated the phenomena of IF selectively suppressing the accumulation of CD205+ G-MDSCs in the spleen, upregulating cleaved caspase 3 in the tumor, downregulating Ki67 in the lung, and retarding the growth of transplanted 4T1 and 4T07 murine breast tumors. These findings suggest that IF inhibited cell trafficking through the downregulation of CXCR4 and induced apoptosis by altering glucose metabolism; this, suppressed the accumulation of tumor-induced splenic CD205+ G-MDSCs and in turn enhanced antitumor immunity.

CD205+ polymorphonuclear myeloid-derived suppressor cells suppress antitumor immunity by overexpressing GLUT3.

Myeloid-derived suppressor cells (MDSCs) are responsible for antitumor immunodeficiency in tumor-bearing hosts. Primarily, MDSCs are classified into 2 groups: monocytic (M)-MDSCs and polymorphonuclear (PMN)-MDSCs. In most cancers, PMN-MDSCs (CD11b+ Ly6Clow Ly6G+ cells) represent the most abundant MDSC subpopulation. However, the functional and phenotypic heterogeneities of PMN-MDSC remain elusive, which delays clinical therapeutic targeting decisions. In the 4T1 murine tumor model, CD11b+ Ly6Glow PMN-MDSCs were sensitive to surgical and pharmacological interventions. By comprehensively analyzing 64 myeloid cell-related surface molecule expression profiles, cell density, nuclear morphology, and immunosuppressive activity, the PMN-MDSC population was further classified as CD11b+ Ly6Glow CD205+ and CD11b+ Ly6Ghigh TLR2+ subpopulations. The dichotomy of PMN-MDSCs based on CD205 and TLR2 is observed in 4T07 murine tumor models (but not in EMT6). Furthermore, CD11b+ Ly6Glow CD205+ cells massively accumulated at the spleen and liver of tumor-bearing mice, and their abundance correlated with in situ tumor burdens (with or without intervention). Moreover, we demonstrated that CD11b+ Ly6Glow CD205+ cells were sensitive to glucose deficiency and 2-deoxy-d-glucose (2DG) treatment. Glucose transporter 3 (GLUT3) knockdown by siRNA significantly triggered apoptosis and reduced glucose uptake in CD11b+ Ly6Glow CD205+ cells, demonstrating the dependence of CD205+ PMN-MDSCs survival on both glucose uptake and GLUT3 overexpression. As GLUT3 has been recognized as a target for the rescue of host antitumor immunity, our results further directed the PMN-MDSC subsets into the CD205+ GLUT3+ subpopulation as future targeting therapy.

A method for separation and purification of mouse splenocytes by density gradient centrifugation.

Spleen is an information-rich and easy-accessible peripheral lymphoid organ. It has complex cell composition because of the immunocytes maturity and settle down. Changes of the composition and function of these immunocytes are critical to body immune response. To understand the cell behaviors, specific cell subpopulations are required to be separated without heterogeneity. Density gradient centrifugation is one of the cell separation methods with high throughput. However, the greatest defect of this method is its low cell purity. In this study, the separation conditions of tumor-bearing mouse splenocytes were optimized by separation solutions with different density gradients. After separation, lymphocytes were located at the second layer with the proportion of 84.9%, monocytic-like myeloid-derived suppressor cells (Mo-MDSCs) were located at the fourth layer with the proportion of 54.2% and polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) were located at the sixth layer with the proportion of 85.5%. Cells in different layers were further determined by verifying the gene expression pattern of some chemokine receptors on cell surfaces. Furthermore, this method was also used to separate healthy mouse splenocytes. Therefore, this method will be highly useful to separate mouse splenocytes and has laid a foundation for further research on the changes and roles of immunocytes during the development of cancer.

Anti-migration and anti-invasion effects of 2-hydroxy-6-tridecylbenzoic acid is associated with the enhancement of CYP1B1 expression through activating the AMPK signaling pathway in triple-negative breast cancer cells.

2-hydroxy-6-tridecylbenzoic acid is alkylsalicylic acid monomer compound, abundantly existed in the ginkgo biloba extracts, however, the underlying mechanism of its anti-migration and anti-invasion effects in triple-negative breast cancer (TNBC) is not clear. Here, 2-hydroxy-6 -tridecylbenzoic acid inhibited MDA-MB-231 and 4 T-1 cells growth without toxicity to MCF-10A normal breast cells. Meanwhile, 2-hydroxy-6-tridecylbenzoic acid inhibited cells migration and invasion as well as EMT with the increase of E-cadherin expression accompanied by the decrease of N-cadherin, Vimentin, Snail, MMP-2 and MMP-9 expression. The inhibition was further demonstrated by the enhancement of cytochrome P450 (CYP) 1B1 expression through the activation of AMP activated protein kinase (AMPK) in MDA-MB-231 and 4 T-1 cells. Silencing of CYP1B1 and AMPK with siRNA blocked the inhibitory effects of migration and invasion, and reversed the EMT related genes. These findings may provide a novel mechanism of the 2-hydroxy-6-tridecylbenzoic acid as a molecular-targeted therapeutic drug for TNBC patients.

Antiproliferative effect of 2-Hydroxy-6-tridecylbenzoic acid from ginkgo biloba sarcotestas through the aryl hydrocarbon receptor pathway in triple-negative breast cancer cells.

This study aims to isolate the potential antiproliferative and cytotoxic compounds from ginkgo biloba sarcotestas (GBS) and investigates the underlying mechanism in human MDA-MB-231 and mouse 4T-1 triple-negative breast cancer cells. Our results showed that 2-Hydroxy-6-tridecylbenzoic acid was isolated by cytotoxicity-guided fractionation where different fractions were assessed using MTT assay against MDA-MB-231 and 4T-1 cells. Colony formation assay showed that 2-Hydroxy-6-tridecylbenzoic acid significantly inhibited cell proliferation. The inhibition was associated with the enhancement of cytochrome P450 (CYP) 1B1 expression in a dose- and time-dependent manner and no significant change of CYP1A1 expression by qPCR and Western blot assays in MDA-MB-231 and 4T-1 cells. The mechanism was further demonstrated by the activation of aryl hydrocarbon receptor (AhR) pathway with the upregulation of AhR, AhR nuclear translocator (ARNT) and AhR-dependent xenobiotic response elements (XRE) activity. These findings may have implications for development of anticancer agents containing 2-Hydroxy-6-tridecylbenzoic acid as functional additives.

Development of a high efficient promoter finding method based on transient transfection.

In metazoan genome, the mechanism of gene expression regulation between transcriptional regulatory elements and their target gene is spatiotemporal. Active promoters possess many specific chromosomal features, such as hypersensitive to DNaseI and enrichment of specific histone modifications. In this article, we proposed a novel method which possesses a high efficiency to find promoters in vitro. A promoter-trap library was constructed with totally 706 random mouse genomic DNA fragment clones, and 260 promoter-active fragments of the library were screened by transient transfection into 4T1 cells. To demonstrate the accuracy of this promoter finding method, 13 fragments with promoter activities were randomly selected for published DNase-seq and ChIP-seq data analysis, downstream transcripts prediction and expression confirmation. qRT-PCR results showed that six predicted transcription units were successfully amplified in different mouse tissues/cells or in reconstituted mouse mammary tumors. Our results indicate that this promoter finding method can successfully detect the promoter-active fragments and their downstream transcripts.

Exploration of the immune-related signature and immune infiltration analysis for breast ductal and lobular carcinoma.

BACKGROUND: In this study, we aimed to explore the tumour associated immune signature of breast cancer (BC) and conduct integrative analyses with immune infiltrates in BC. METHODS: We downloaded the transcriptome profiling and clinical data of BC from The Cancer Genome Atlas (TCGA) database. The list of immune-related signatures was from the Innate database. The limma package was utilized to conduct the normalization, and we screened the differential immune signatures in BC. A univariate Cox regression model and the LASSO method were used to find the hub prognostic immune genes. The TAIG risk model was calculated based on the multivariate Cox regression results, and a receiver operating characteristic (ROC) curve was generated to assess the predictive power of TAIG. Moreover, we also conducted a correlation analysis between TAIG and the clinical characteristics. Additionally, we utilized the METABRIC cohort as the validation data set. The TIMER database is a comprehensive resource for performing systematic analyses of immune infiltrates across various malignancies. We evaluated the associations of immune signatures with several immune cells based on TIMER. Furthermore, we used the CIBERSORT algorithm to determine the fractions of immune cells in each sample and compared the differential distributions of immune infiltrates between two TAIG groups using the Wilcoxon rank-sum test. RESULTS: A total of 1,178 samples were obtained from the TCGA-BRCA database, but only 1,045 breast tumour samples were matched with complete transcriptome expression data. Meanwhile, we collected a total of 1,094 BC patients from the METABRIC cohort. We found a list of 1,399 differential immune signatures associated with survival, and functional analysis revealed that these genes participated in cytokine-cytokine receptor interactions, Th1 and Th2 cell differentiation and the JAK-STAT signalling pathway. The TAIG risk model was established from the multivariate Cox analysis, and we observed that high TAIG levels correlated with poor survival outcomes based on Kaplan-Meier analysis. The Kruskal-Wallis test suggested that high TAIG levels correlated with high AJCC-TNM stages and advanced pathological stages (P<0.01). We validated the well robustness of TAIG in METABRIC cohort and 5-year AUC reached up to 0.829. Moreover, we further uncovered the associations of hub immune signatures with immune cells and calculated the immune cell fractions in specific tumour samples based on gene signature expression. Last, we used the Wilcoxon rank-sum test to compare the differential immune density in the two groups and found that several immune cells had a significantly lower infiltrating density in the high TAIG groups, including CD8+ T cells (P=0.031), memory resting CD4+ T cells (P=0.026), M0 macrophages (P=0.023), and M2 macrophages (P=0.048). CONCLUSIONS: In summary, we explored the immune signature of BC and constructed a TAIG risk model to predict prognosis. Moreover, we integrated the identified immune signature with tumour-infiltrating immune cells and found adverse associations between the TAIG levels and immune cell infiltrating density.