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      Establishment of a malignancy and benignancy prediction model of sub-centimeter pulmonary ground-glass nodules based on the inflammation-cancer transformation theory

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          Abstract

          Background

          In recent years, Chinese clinicians are frequently encountered by patients with multiple lung nodules and these intensity ground-glass nodules (GGNs) are usually small in size and some of them have no spicule sign. In addition, early lung cancer is diagnosed in large numbers of non-heavy smokers and individuals with no caner history. Obviously, the Mayo model is not applicable to these patients. The aim of the present study is to develop a new and more applicable model that can predict malignancy or benignancy of pulmonary GGNs based on the inflammation-cancer transformation theory.

          Materials and methods

          Included in this study were patients who underwent surgical resection or lung puncture biopsy of GGNs in Shanghai 10th People’s Hospital between January 1, 2018 and May 31, 2021 with the inclusion criterion of the maximum diameter of GGN < 1.0 cm. All the included patients had their pulmonary GGNs diagnosed by postoperative pathology. The patient data were analyzed to establish a prediction model and the predictive value of the model was verified.

          Results

          Altogether 100 GGN patients who met the inclusion criteria were included for analysis. Based on the results of logistic stepwise regression analysis, a mathematical predication equation was established to calculate the malignancy probability as follows: Malignancy probability rate (p) = ex/(1 + ex); p > 0.5 was considered as malignant and p ≤ 0.5 as benign, where x = 0.9650 + [0.1791 × T helper (Th) cell] + [0.2921 × mixed GGN (mGGN)] + (0.4909 × vascular convergence sign) + (0.1058 × chronic inflammation). According to this prediction model, the positive prediction rate was 73.3% and the negative prediction rate was 100% versus the positive prediction rate of 0% for the Mayo model.

          Conclusion

          By focusing on four major factors (chronic inflammation history, human Th cell, imaging vascular convergence sign and mGGNs), the present prediction model greatly improves the accuracy of malignancy or benignancy prediction of sub-centimeter pulmonary GGNs. This is a breakthrough innovation in this field.

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          Most cited references35

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          Inflammation and cancer.

          Recent data have expanded the concept that inflammation is a critical component of tumour progression. Many cancers arise from sites of infection, chronic irritation and inflammation. It is now becoming clear that the tumour microenvironment, which is largely orchestrated by inflammatory cells, is an indispensable participant in the neoplastic process, fostering proliferation, survival and migration. In addition, tumour cells have co-opted some of the signalling molecules of the innate immune system, such as selectins, chemokines and their receptors for invasion, migration and metastasis. These insights are fostering new anti-inflammatory therapeutic approaches to cancer development.
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            The Immune Response to Prevotella Bacteria in Chronic Inflammatory Disease.

            The microbiota plays a central role in human health and disease by shaping immune development, immune responses, metabolism, and protecting from invading pathogens. Technical advances that allow comprehensive characterization of microbial communities by genetic sequencing have sparked the hunt for disease modulating bacteria. Emerging studies in humans have linked increased abundance of Prevotella species at mucosal sites to localized and systemic disease, including periodontitis, bacterial vaginosis, rheumatoid arthritis, metabolic disorders, and low-grade systemic inflammation. Intriguingly, Prevotella abundance is reduced within the lung microbiota of asthma and COPD. Increased Prevotella abundance is associated with augmented Th17-mediated mucosal inflammation, which is in line with the marked capacity of Prevotella in driving Th17 immune responses in vitro. Studies indicate, that Prevotella predominantly activate TLR2 leading to production of Th17-polarizing cytokines by antigen presenting cells, including IL-23 and IL-1. Furthermore, Prevotella stimulate epithelial cells to produce IL-8, IL-6 and CCL20, which can promote mucosal Th17 immune responses and neutrophil recruitment. Prevotella-mediated mucosal inflammation leads to systemic dissemination of inflammatory mediators, bacteria, and bacterial products, which in turn may affect systemic disease outcomes. Studies in mice support a causal role of Prevotella as colonization experiments promote clinical and inflammatory features of human disease. When compared to strict commensal bacteria, Prevotella exhibit increased inflammatory properties as demonstrated by augmented release of inflammatory mediators from immune cells and various stromal cells. These findings indicate that some Prevotella strains may be clinically important pathobionts that can participate in human disease by promoting chronic inflammation. This article is protected by copyright. All rights reserved.
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              Depression and anxiety in relation to cancer incidence and mortality: a systematic review and meta-analysis of cohort studies

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                Author and article information

                Contributors
                Journal
                Front Med (Lausanne)
                Front Med (Lausanne)
                Front. Med.
                Frontiers in Medicine
                Frontiers Media S.A.
                2296-858X
                05 October 2022
                2022
                : 9
                : 1007589
                Affiliations
                [1] 1Department of Integrated Traditional Chinese and Western Medicine, Shanghai Tenth People’s Hospital, Tongji University School of Medicine , Shanghai, China
                [2] 2Liangcheng Xincun Community Health Services Center, Shanghai University of Traditional Chinese Medicine , Shanghai, China
                Author notes

                Edited by: Yi Liu, Shandong Provincial Hospital, China

                Reviewed by: Gunnar N. Hillerdal, Karolinska University Hospital, Sweden; Mariaenrica Tinè, University of Padua, Italy

                *Correspondence: Lihong Fan, fanlih@ 123456aliyun.com

                These authors share first authorship

                This article was submitted to Pulmonary Medicine, a section of the journal Frontiers in Medicine

                Article
                10.3389/fmed.2022.1007589
                9581285
                36275807
                0c618c11-d3ce-4585-8a47-4b149defa593
                Copyright © 2022 Shen, Wu, Xia, Cao, Wang, Li and Fan.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 01 August 2022
                : 20 September 2022
                Page count
                Figures: 1, Tables: 6, Equations: 0, References: 35, Pages: 7, Words: 4457
                Funding
                Funded by: Shanghai Municipal Health Commission, doi 10.13039/100017950;
                Categories
                Medicine
                Original Research

                prediction model,sub-centimeter,pulmonary ggns,mayo model,innovative

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