COL11A1 as an novel biomarker for breast cancer with machine learning and immunohistochemistry validation

Machine learning (ML) algorithms were used to identify a novel biological target for breast cancer and explored its relationship with the tumor microenvironment (TME) and patient prognosis. The edgR package identified hub genes associated with overall survival (OS) and prognosis, which were validated using public datasets. Of 149 up-regulated genes identified in tumor tissues, three ML algorithms identified COL11A1 as a hub gene. COL11A1was highly expressed in breast cancer samples and associated with a poor prognosis, and positively correlated with a stromal score (r=0.49, p<0.001) and the ESTIMATE score (r=0.29, p<0.001) in the TME. Furthermore, COL11A1 negatively correlated with B cells, CD4 and CD8 cells, but positively associated with cancer-associated fibroblasts. Forty-three related immune-regulation genes associated with COL11A1 were identified, and a five-gene immune regulation signature was built. Compared with clinical factors, this gene signature was an independent risk factor for prognosis (HR=2.591, 95%CI 1.831–3.668, p=7.7e-08). A nomogram combining the gene signature with clinical variables, showed better predictive performance (C-index=0.776). The model correction prediction curve showed little bias from the ideal curve. COL11A1 is a potential therapeutic target in breast cancer and may be involved in the tumor immune infiltration; its high expression is strongly associated with poor prognosis

Correlation between dietary patterns and cognitive function in older Chinese adults: A representative cross-sectional study

ObjectiveThe objective of this study was to investigate the relationship between dietary patterns and cognitive function in older adults (≥60 years old).MethodsFood intake was quantitatively assessed by the Food Frequency Questionnaire (FFQ), and cognitive function was assessed by the Chinese version of the Simple Mental State Examination Scale (MMSE). Four major dietary patterns were identified by the factor analysis (FA) method. The relationship between dietary patterns and cognitive function was evaluated by logistic regression.ResultsA total of 884 participants were included in the study. Four dietary patterns (vegetable and mushroom, oil and salt, seafood and alcohol, and oil tea dietary patterns) were extracted. In the total population, Model III results showed that the fourth quartile of dietary pattern factor scores for the vegetable and mushroom pattern was 0.399 and 7.056. The vegetable and mushroom dietary pattern may be a protective factor for cognitive function, with p-value = 0.033, OR (95% CI): 0.578 (0.348, 0.951) in Model III (adjusted for covariates: sex, ethnic, marital, agricultural activities, smoking, drinking, hypertension, diabetes, dyslipidemia, BMI, and dietary fiber). In the ethnic stratification analysis, the scores of dietary pattern factors of the vegetable and mushroom among the Yao participants were 0.333 and 5.064. The Vegetable and mushroom diet pattern may be a protective factor for cognitive function, p-value = 0.012, OR (95% CI): 0.415 (0.206, 0.815).ConclusionThe fourth quartile of the vegetable and mushroom dietary pattern scores showed dose-dependent and a strong correlation with cognitive function. Currently, increasing vegetable and mushroom intake may be one of the effective ways to prevent and mitigate cognitive decline. It is recommended to increase the dietary intake of vegetables and mushroom foods

Consistent low-energy reduction of the three-band model for copper oxides with O-O hopping to the effective t-J model

A full three-band model for the CuO$_{2}$ plane with inclusion of all essential interactions - Cu-O and O-O hopping, repulsion at the copper and oxygen and between them - is considered. A general procedure of the low-energy reduction of the primary Hamiltonian to the Hamiltonian of the generalized $t$-$t'$-$J$ model is developed. An important role of the direct O-O hopping is discussed. Parameters of the effective low-energy model (the hopping integral, the band position and the superexchange constant $J$ are calculated. An analysis of the obtained data shows that the experimental value of $J$ fixes the charge transfer energy $\Delta =(\epsilon_{p}-\epsilon_{d})$ in a narrow region of energies.Comment: 32 pp. (LATEX), two figures (PostScript) appende

MYCBP2 expression correlated with inflammatory cell infiltration and prognosis immunotherapy in thyroid cancer patients

IntroductionImmune checkpoint inhibitors (ICIs) have shown promising results for the treatment of multiple cancers. ICIs and related therapies may also be useful for the treatment of thyroid cancer (TC). In TC, Myc binding protein 2 (MYCBP2) is correlated with inflammatory cell infiltration and cancer prognosis. However, the relationship between MYCBP2 expression and ICI efficacy in TC patients is unclear.MethodsWe downloaded data from two TC cohorts, including transcriptomic data and clinical prognosis data. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to predict the efficacy of ICIs in TC patients. MCPcounter, xCell, and quanTIseq were used to calculate immune cell infiltration scores. Gene set enrichment analysis (GSEA) and single sample GSEA (ssGSEA) were used to evaluate signaling pathway scores. Immunohistochemical (IHC) analysis and clinical follow up was used to identify the MYCBP2 protein expression status in patients and associated with clinical outcome.ResultsA higher proportion of MYCBP2-high TC patients were predicted ICI responders than MYCBP2-low patients. MYCBP2-high patients also had significantly increased infiltration of CD8+ T cells, cytotoxic lymphocytes (CTLs), B cells, natural killer (NK) cells and dendritic cells (DC)s. Compared with MYCBP2-low patients, MYCBP2-high patients had higher expression of genes associated with B cells, CD8+ T cells, macrophages, plasmacytoid dendritic cells (pDCs), antigen processing and presentation, inflammatory stimulation, and interferon (IFN) responses. GSEA and ssGSEA also showed that MYCBP2-high patients had significantly increased activity of inflammatory factors and signaling pathways associated with immune responses.In addiation, Patients in our local cohort with high MYCBP2 expression always had a better prognosis and greater sensitivity to therapy while compared to patients with low MYCBP2 expression after six months clinic follow up.ConclusionsIn this study, we found that MYCBP2 may be a predictive biomarker for ICI efficacy in TC patients. High MYCBP2 expression was associated with significantly enriched immune cell infiltration. MYCBP2 may also be involved in the regulation of signaling pathways associated with anti-tumor immune responses or the production of inflammatory factors

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Deciphering the Oncogenic Role of VPS28 Modulated by miR-491-5p in Breast Cancer Cells Using In Silico and Functional Analysis

Vacuolar protein sorting-associated protein 28 (VPS28), one of the four cytosolic proteins comprising the endosomal sorting complex required for the transport I (ESCRT-I) component, has been reported to be linked to various cancers. However, less evidence is available regarding the involvement of VPS28 in breast cancer. To this end, this study focused on exploring the function of VPS28 in breast cancer cells using th

Direct identification and visualisation of real-world contaminating microplastics using Raman spectral mapping with multivariate curve resolution-alternating least squares

Microplastics (MPs) contamination is ubiquitous in environmental matrices worldwide. Moreover these pollutants can be ingested by organisms and transported to organs via the circulatory system. Although efficient methods for the analysis of MPs derived from environment matrices and organisms' tissue samples have been developed after special sample pre-treatment, there remains a need for an optimised approach allowing direct identification and visualisation these MPs in real environmental matrices and organismal samples. Herein, we firstly used a multivariate curve resolution-alternating least squares (MCR-ALS) analysis of Raman hyperspectral imaging data to direct identification and visualisation of MPs in a complex serum background. Four common MPs types including polyethylene (PE), polystyrene (PS), polypropylene (PP) and polyethylene terephthalate (PET) were identified and visualised either individually or in mixtures within spiked samples at an 8-μm spatial resolution. Moreover, Raman imaging based on MCR-ALS was successfully applied in fish faeces biological samples and environmental sand samples for in situ MPs identification directly without washing or removal of organic matter. The current results demonstrate Raman imaging based on MCR-ALS as a novel imaging approach for direct identification and visualisation of MPs, through extraction of MPs' chemical spectra within a complicated biological or environmental background whilst eliminating overlapping Raman bands and fluorescence interference. [Abstract copyright: Copyright © 2021 Elsevier B.V. All rights reserved.

Identification of benzoapyrene-induced cell cycle-associated alterations in MCF-7 cells using infrared spectroscopy with computational analysis

Chemical contaminants, such as benzoapyrene (BaP), may modulate transcriptional responses in cells via the activation of aryl hydrocarbon receptor (AhR) or through responses to DNA damage following adduct formation. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy can be employed in a non-destructive fashion to interrogate the biochemical signature of cells via generation of infrared (IR) spectra. By applying to generated spectral datasets subsequent computational approaches such as principal component analysis plus linear discriminant analysis (PCA-LDA), derived data reduction is achieved to facilitate the visualization of wavenumber-related alterations in target cells. Discriminating spectral variables might be associated with lipid or glycogen content, conformational protein changes and phosphorylation, and structural alterations in DNA/RNA. Using this approach, we investigated the dose-related effects of BaP in MCF-7 cells concentrated in S- or G{$_0$}/G{$_1$}-phase. Our findings identified that in PCA-LDA scores plots a clear segregation of IR spectra was evident, with the major spectral alterations associated with DNA/RNA, secondary protein structure and lipid. Dose-related effects were observed and even with exposures as low as 10{$^-$}{$^9$} M BaP, significant (P {$\leq$} 0.001) separation of BaP-treated vs. vehicle control cells was noted. ATR-FTIR spectroscopy with computational analysis is a novel approach to identify the effects of environmental contaminants in target cells

A Novel Anti-EGFR mAb Ame55 with Lower Toxicity and Better Efficacy than Cetuximab When Combined with Irinotecan

To improve efficacy and minimize toxicity of EGFR inhibition treatment, we developed Ame55, a novel anti-EGFR IgG1 with lower affinity to EGFR than cetuximab (C225) from a human phage library. Ame55 had lower bioactivity than cetuximab in vitro but similar antitumor efficacy as cetuximab in vivo. Moreover, Ame55 was more efficacious than cetuximab in a Lovo cell xenograft tumor model when combined with irinotecan (CPT-11). Ame55 concentrates in the mouse xenograft tumor and has less toxicity than cetuximab in cynomolgus monkeys in an overdose study