LungPoint导航联合吲哚菁绿荧光成像在Ⅰa期非小细胞肺癌淋巴结采样中的应用价值

目的:寻找一种准确定位Ⅰa期非小细胞肺癌患者(NSCLC)前哨淋巴结(SLN)的方法,验证SLN作为淋巴结取样样本的合理性。方法:采用前瞻性研究方法,参照入组标准纳入2021年1月至2023年12月在山东省公共卫生临床中心胸外科临床分期为Ⅰa期NSCLC住院患者50例,术前借助LungPoint导航气管镜下肿瘤周围注射示踪剂吲哚菁绿,通过荧光胸腔镜成像完成SLN定位,并对包括SLN在内的区域淋巴结行病理学检查,使用该方法对SLN的识别率、准确率与假阴性率等验证其作为淋巴结取样样本的合理性。结果:50例患者中,41例检测到SLN,识别率为82.0%(41/50),经病理检测发现3例共计9枚SLN有淋巴结转移(阳性),其中1例亦检出非前哨淋巴结(N-SLN)阳性2枚。9例患者未检测到SLN,清扫淋巴结54枚,未发现转移淋巴结,故SLN准确率为100.0%(41/41),假阴性率为0(0/3)。结论:借助LungPoint气管镜在肿瘤周围注射示踪剂吲哚菁绿,通过荧光胸腔镜成像探寻SLN技术具有较高的区域淋巴结转移预测性,有望成为指导Ⅰa期NSCLC系统性淋巴结采样的依据。

Effect of Climate Change on Lung Cancer

This research paper aims to draw a relationship between lung cancer and climate change. With the rise of climate change in the last few decades, many organizations and people are concerned about the future of the world. Climate change has many side effects, such as air pollution, which can increase the incidence and death rates of lung and bronchus cancer. This paper aims to draw the relationship between climate change factors and lung cancer incidence and mortality rates. The main finding of this analysis was that there is a positive relationship between lung cancer incidence, death rates, and climate change indicators. The findings from this study have the potential to inform targeted public health interventions and policies, emphasizing the need for proactive strategies in mitigating the health impacts of a changing climate. Section 2 of this paper is a literature review and focuses on the findings of other scholars in this field. Section 3 of this paper is Methods and Processes and will highlight the steps used to create the program and get the results. Section 4 of this paper is Results and Analysis, and will go over the results produced by the machine learning algorithm, and will present graphs and visualizations regarding the relationship of the dependent and independent variables. The final section, Section 5, is Limitations and Conclusion, in which we will discuss possible limitations to both my dataset and my model, and will conclude the paper by presenting a big-picture view of these problems in our society.

The Clinical Value of Accelerated Recovery Care in Pulmonary Rehabilitation of Perioperative Lung Cancer Patients

Aim: To study the clinical value of accelerated recovery care in pulmonary rehabilitation of perioperative lung cancer patients. Methods: 98 lung cancer patients undergoing surgery were admitted to our hospital from March 2020 to November 2021 and randomly divided into an observation group and an ACBT (Active Cycle of Breathing Technique) training group. Accelerated recovery care and routine care were respectively used in the perioperative period to compare the nursing effects of the two groups. Results: All perioperative indicators in the observation group were shorter than those in the ACBT training group. The pain scores at different time periods after surgery were lower in the observation group than in the ACBT training group (P 0.05). The improvement in the above indicators was higher in the observation group than in the ACBT training group after nursing care (P Conclusion: Accelerated recovery care during the perioperative period for lung cancer surgery patients showed significant effectiveness.

The Mechanism of Celastrol in the Treatment of Metastatic Lung Adenocarcinoma Revealed by Network Pharmacology and Molecular Docking

Background: Celastrol is an active ingredient extracted from Traditional Chinese Medicine (TCM), which can restrain the progression of lung cancer, whereas its underlying mechanism is unclear. In our study, the underlying mechanism of celastrol in the treatment of lung adenocarcinoma (LUAD) with metastasis was investigated by network pharmacology and molecular docking. Method: Potential targets of celastrol were collected from TCMSP, Batman-TCM and GeneCard database, and its potential targets were predicted using the STP platform and the TargetNet server. Metastasis marker genes (MGs) were obtained from the HCMDB. The genes correlated with LUAD were gathered from the GeneCard and OMIM database. And the common targets among celastrol potential targets, MGs and LUAD were analyzed. The protein-protein interaction (PPI) networks were obtained from the STRING database. SangerBox and the Xiantao bioinformatics tool were applied to visualize GO and KEGG analysis. Molecular docking tested the binding affinity between celastrol and core genes. Result: A total of 107 targets of celastrol against metastasis LUAD were obtained. The core targets were obtained from the PPI network, namely AKT1, JUN, MYC, STAT3, IL6, TNF, NFKB1, BCL2, IL1B, and HIF1A. GO and KEGG enrichment analysis indicated celastrol for the treatment of metastasis LUAD most refers to cellular response to chemical stress, DNA-binding transcription factor binding, transcription regulator complex and pathways in cancer. And some of these targets are associated with differential expressions and survival rates in LUAD. Moreover, Molecular docking shows celastrol can bind with BCL2 well by hydrogen bond and hydrophobic interaction. Conclusion: This finding roundly expounded the core genes and potential mechanisms of celastrol for the treatment of metastasis LUAD, offering the theoretical basis and antitumor mechanism of TCM in the treatment of lung cancer.

Research Progress of PTCH1 Gene in Lung Cancer

Background: The PTCH1 gene, also known as Patched 1, is located on the long arm of human chromosome 9 (9q22.3). It encodes the PTCH1 protein, which is a critical transmembrane receptor within the Hedgehog signaling pathway (Hh), playing a pivotal role in cellular communication and developmental processes. Recent studies have highlighted the significance of mutations in PTCH1 in the pathogenesis of lung cancer, positioning it as a crucial molecule for investigation in oncology. Purpose: This review aims to elucidate the role of the PTCH1 and the Hedgehog pathway in the initiation, progression, and potential treatment of lung cancer, thereby providing a theoretical foundation for personalized and precise therapeutic strategies. Method: To ensure a comprehensive review, this study systematically searched for literature related to the PTCH1, lung cancer, and the Hedgehog pathway across multiple databases including PubMed, Web of Science, and CNKI (China National Knowledge Infrastructure). The search strategy involved using specific keywords and advanced filtering options to include the most relevant and recent studies. Initial screening excluded irrelevant articles, followed by a detailed evaluation of the selected studies based on their scientific quality and relevance. Results: This review indicated that specific mutations in the PTCH1 gene are closely associated with the onset and progression of lung cancer. These mutations impede normal Hedgehog signaling, leading to unregulated cell proliferation and tumor growth. Targeting PTCH1, including vismodegib, have shown efficacy in clinical cases, particularly in SCCL with specific PTCH1 mutations, leading to complete remissions. Furthermore, the interaction between PTCH1 and microRNA-212 suggests potential therapeutic approaches by targeting miRNA to regulate PTCH1 expression. In addition, the investigation of traditional Chinese medicines such as Ginsenosides and Cordyceps sinensis extracts has shown their potential to modulate the Hedgehog pathway and reverse drug resistance. Conclusions: An in-depth understanding of the precise mechanisms by which PTCH1 mutations promote lung cancer could facilitate the development of targeted therapies. This study highlights the potential of PTCH1 as a biomarker for diagnosis and a target for precision medicine in lung cancer treatment, advocating for further research into its molecular pathways and therapeutic applications.

A Case Report of a Rare Sarcomatoid Poorly Differentiated Adenocarcinoma Harboring Concurrent Mutations in the ROS1, EGFR, ARID1A, and NFKBIA Genes in the Lung

ROS1 and EGFR are primary oncogenic drivers in non-small cell lung cancer (NSCLC) pathogenesis. However, EGFR mutations and ROS1 fusions are generally mutually exclusive in NSCLC, leading to a negligible probability of their co-occurrence. Consequently, clinical data and treatment strategies for their simultaneous presence are remarkably scarce. This report details the first recorded case of a sarcomatoid, poorly differentiated lung adenocarcinoma harboring both a ROS1 fusion and an EGFR mutation, alongside ARID1A and NFKBIA gene mutations. Moreover, this case study encompasses a review of instances featuring concurrent ROS1 and EGFR mutations. The identified genetic alterations in ROS1, EGFR, ARID1A, and NFKBIA are pivotal in the etiology of NSCLC. These mutations significantly influence disease progression and are essential for the development of personalized therapeutic approaches. Recognizing the unique genetic profiles in patients permits healthcare providers to devise customized treatment regimens that target these specific mutations, thereby enhancing patient outcomes in NSCLC.

The Value of γδ T Cells in Lung Infections and Advances in Diagnosis and Treatment

Lung infections are usually caused by pathogenic microorganisms and are a disease with high morbidity and mortality. In clinical practice, the use of broad-spectrum antibiotics has become increasingly common, but this has also led to the problem of antibiotic abuse and irrational use, which in turn has spawned the emergence of multidrug-resistant bacteria, making the treatment of lung infections more complex and difficult. In the human immune system, γδ T cells play a crucial role in defense against foreign pathogens and regulation of autoimmune responses. These cells act as a bridge between innate and adaptive immunity and can be rapidly activated in the early stages of infection to produce inflammatory factors and chemokines that attract other immune cells to the site of infection. Recent advances have shown that γδ T cells not only play a direct role in the innate immunity of pathogen infection, but are also involved in regulating the subsequent adaptive immune response. The aim of this review is to explore the mechanism of γδ T cells in lung infections and to summarize the current progress of clinical research, with the aim of providing new scientific basis and therapeutic strategies for the treatment of lung infections.

Life Review the Impact of Combined Watson Care Theory Intervention on Psychological Status and Quality of Life in Patients with Terminal Lung Cancer

Objective: To analyze the impact of combined Watson care theory intervention on the psychological state and quality of life in patients with terminal lung cancer. Methods: 72 patients with terminal lung cancer admitted from March 2021 to January 2024 were selected, which were divided into research group (life review combined with Watson care theory intervention) and control group (conventional intervention), with 36 cases each. Compare the nursing effect between the two groups. Results: The anxiety self-rating scale (SAS) and depression self-rating scale (SDS) scores were significantly lower than those of the control group, and the quality of life score was significantly higher than that of the control group (P < 0.05). Conclusion: Life review combined with Watson care theory intervention can improve the psychological state and improve the quality of life of patients with terminal lung cancer.

Progress of Immunotherapy Combined with Anti-Angiogenesis Therapy in Lung Cancer

Lung cancer is the most prevalent and fatal cancer in China and even around the world, and many patients are found in the late stage of lung cancer. For the treatment of advanced lung cancer, in addition to traditional chemotherapy modalities, many emerging treatments are increasingly significant, such as immunotherapy, anti-angiogenic therapy, and targeted therapy. An increasing number of studies have now shown that anti-angiogenic therapy improves the immune microenvironment by enhancing tumor immunity through normalization of tumor vessels. Immunization combined with anti-angiogenic therapy can exert synergistic effects and improve the prognosis of patients. This article summarizes the extent of benefit, current clinical study data, and future prospects of immunotherapy combined with anti-angiogenic agents in the treatment of advanced NSCLC.

Development and Application of Procedures for the Management of Skin Toxicity Related to Immune Checkpoint Inhibitors in Patients with Lung Cancer

Objective: To establish the procedures for the management of skin toxicity related to immune checkpoint inhibitors in patients with lung cancer and explore the effect of application. Methods: A total of 24 evidence-based evidences were collected from 7 aspects, including risk factors, baseline screening, ICIs monitoring, daily skin care, multidisciplinary management, symptom management and health education. A total of 157 lung cancer patients and 94 nurses from 8 wards of the Oncology department of our hospital from November 2022 to May 2023 were selected by convenience sampling. A total of 77 patients and 46 nurses from ward 1 - 4 were divided into the baseline group. There were 80 patients and 48 nurses in Ward 5 - 8 as the evidence-based practice group. In the baseline group, patients were treated with routine methods such as assessing skin symptoms, taking medication according to symptoms, guiding to keep skin clean and moist, eating a light diet, and avoiding scratching. The evidence-based practice group adopts an evidence-based continuous improvement model for nursing. The differences in the severity of symptoms of skin toxicity in the second cycle of medication and the knowledge and practice of self-care of skin toxicity were compared between the two groups before and after the use of the syndrome, as well as the differences in the implementation rate of review indicators, evidence-based ability and knowledge and practice of skin toxicity care before and after the use of the syndrome. Results: The incidence and severity of cutaneous toxicity were significantly lower after treatment than before treatment (P P < 0.05). Conclusion: The implementation of immune checkpoint inhibitor-related skin toxicity management procedures can effectively reduce the incidence and severity of skin toxicity symptoms, optimize the clinical pathway, and improve the quality of care.

The Investigation into Intrinsic Elements Influencing the Onset of Lung Cancer

Lung cancer is a highly heterogeneous malignancy with a complex pathogenesis, involving a series of endogenous alterations such as genetic mutations, epigenetic modifications, and oxidative stress. Recent advancements in lung cancer research, especially at the genomic and molecular biology levels, have continuously provided new potential targets and perspectives for the diagnosis and treatment of lung cancer. Therefore, this article summarizes the recent progress in the study of endogenous factors related to the pathogenesis of lung cancer, aiming to enhance the understanding of intrinsic factors in lung cancer and to organize ideas for subsequent related research.

Observation of the Effectiveness of Rapid Recovery Nursing on Lung Cancer Surgery Patients and Its Impact on Sleep Quality

Objective: To investigate the nursing effects of rapid recovery care measures on lung cancer surgery patients. Methods: 42 cases of lung cancer surgery patients were divided into control group and study group, with 21 cases in each group. The sleep quality and postoperative recovery indicators were compared between the two groups. Results: The study group showed better results than the control group in terms of PSQI scores, venting time, extubation time, time to getting out of bed, and duration of antibiotic use, with P Conclusion: Rapid recovery nursing has a positive impact on improving sleep quality and promoting postoperative recovery in lung cancer surgery patients.

Using Cross Entropy as a Performance Metric for Quantifying Uncertainty in DNN Image Classifiers: An Application to Classification of Lung Cancer on CT Images

Cross entropy is a measure in machine learning and deep learning that assesses the difference between predicted and actual probability distributions. In this study, we propose cross entropy as a performance evaluation metric for image classifier models and apply it to the CT image classification of lung cancer. A convolutional neural network is employed as the deep neural network (DNN) image classifier, with the residual network (ResNet) 50 chosen as the DNN archi-tecture. The image data used comprise a lung CT image set. Two classification models are built from datasets with varying amounts of data, and lung cancer is categorized into four classes using 10-fold cross-validation. Furthermore, we employ t-distributed stochastic neighbor embedding to visually explain the data distribution after classification. Experimental results demonstrate that cross en-tropy is a highly useful metric for evaluating the reliability of image classifier models. It is noted that for a more comprehensive evaluation of model perfor-mance, combining with other evaluation metrics is considered essential. .

Prediction of Lung Cancer Stage Using Tumor Gene Expression Data

Lung cancer remains a significant global health challenge and identifying lung cancer at an early stage is essential for enhancing patient outcomes. The study focuses on developing and optimizing gene expression-based models for classifying cancer types using machine learning techniques. By applying Log2 normalization to gene expression data and conducting Wilcoxon rank sum tests, the researchers employed various classifiers and Incremental Feature Selection (IFS) strategies. The study culminated in two optimized models using the XGBoost classifier, comprising 10 and 74 genes respectively. The 10-gene model, due to its simplicity, is proposed for easier clinical implementation, whereas the 74-gene model exhibited superior performance in terms of Specificity, AUC (Area Under the Curve), and Precision. These models were evaluated based on their sensitivity, AUC, and specificity, aiming to achieve high sensitivity and AUC while maintaining reasonable specificity.

Clinical Practice of Evidence-Based PDCA Cycle Management Model in Accelerated Recovery of Lung Cancer Patients

Objective: To explore the nursing effect of evidence-based PDCA cycle management mode in accelerated rehabilitation of patients undergoing thoracoscopic lung cancer radical surgery. Methods: 104 patients who underwent thoracoscopic lung cancer radical surgery in our hospital from June 2022 to February 2023 were randomly divided into control group and intervention group, with 52 cases in each group. The control group implemented evidence-based ERAS clinical pathway management, while the intervention group implemented evidence-based PDCA cycle quality management. The postoperative recovery of the two groups of patients was compared. Results: The postoperative recovery of the intervention group was significantly better than that of the control group. The first time to get out of bed, the first time to eat, the duration of chest drainage tube placement, and the length of hospital stay were significantly shorter than those of the control group. The incidence of postoperative chest complications and hospitalization costs were significantly lower than those of the control group, and patient satisfaction was significantly higher than that of the control group (P Conclusion: Evidence-based PDCA cycle quality management mode can effectively improve the implementation quality of accelerated rehabilitation nursing for patients undergoing thoracoscopic lung cancer radical surgery, and it is worthy of clinical promotion.

Pang Fuwan Uses Yao Medicine to Observe the Therapeutic Effects on the Physical and Mental Symptoms of Patients with Advanced Non-Small Cell Lung Cancer

Objective: Investigate the efficacy and safety of Yao Medicine in the treatment of advanced non-small-cell lung carcinoma, and explore the best therapeutic measure for clinical benefit. Methods: From July 2020 to July 2022, 84 patients with advanced non-small-cell lung carcinoma were selected and randomly divided into the Observation Group and control group, and the control group was treated with routine Western medicine, with 42 cases in each group. The activity of daily living (ADL) was assessed before and after treatment, meanwhile, the self-rating depression scale (SDS) and self-rating anxiety SAS (SAS) were used to assess the improvement of a bad mood, and quality of life SF-36 was used to assess the quality of life, to judge the efficacy and safety. Results: The effective rate of observation group was 91.67%. The effective rate of the control group was 76.19%. The effective rate of the observation group was significantly higher than that of the control group (P 0.05). There were no significant differences in the scores of SDS, SAS and quality of life between the two groups before treatment (P > 0.05), and after treatment, the scores of SDS, SAS and quality of life in the two groups were compared with those in the control group (P > 0.05), the scores of VAS, SDS and SAS decreased significantly, while ESCV, angle of straight leg elevation, ADL, physiological score, emotional score, social score and health status score increased significantly, the difference was statistically significant (P 0.05). Conclusion: Yao Medicine can improve the psychosomatic symptoms of patients with advanced non-small-cell lung carcinoma better, with better efficacy and higher safety.

Immunotherapy for Small Cell Lung Cancer

Small cell lung cancer (SCLC) is a poorly differentiated, highly malignant neuroendocrine tumor characterized by rapid growth, aggressiveness, and easy recurrence. It is usually found in late clinical stage and the opportunity for surgery is lost. Therefore, surgery is often not used in clinical treatment. Although it is sensitive to chemoradiotherapy, it has a high recurrence rate and lacks effective treatment methods at present. Following chemotherapy and radiotherapy, immunotherapy for small cell lung cancer has become the mainstream research direction. Immunotherapy is profoundly changing the approach to cancer treatment due to its tolerable safety profile, sustained treatment response due to the production of immune memory, and effectiveness in a broad patient population. Immunotherapy for small cell lung cancer is one of the effective treatment methods for small cell lung cancer, and relevant studies are not rare, but there are still shortcomings such as intolerance of side effects and inaccurate evaluation of treatment timing. This article reviews the history of immunotherapy, the mechanism of action of immunodrugs, and the current immunodrugs used in the first-line treatment of extensive small cell lung cancer.

Performance Comparison of Vision Transformer- and CNN-Based Image Classification Using Cross Entropy: A Preliminary Application to Lung Cancer Discrimination from CT Images

This study evaluates the performance and reliability of a vision transformer (ViT) compared to convolutional neural networks (CNNs) using the ResNet50 model in classifying lung cancer from CT images into four categories: lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), large cell carcinoma (LULC), and normal. Although CNNs have made significant advancements in medical imaging, their limited capacity to capture long-range dependencies has led to the exploration of ViTs, which leverage self-attention mechanisms for a more comprehensive global understanding of images. The study utilized a dataset of 748 lung CT images to train both models with standardized input sizes, assessing their performance through conventional metrics—accuracy, precision, recall, F1 score, specificity, and AUC—as well as cross entropy, a novel metric for evaluating prediction uncertainty. Both models achieved similar accuracy rates (95%), with ViT demonstrating a slight edge over ResNet50 in precision and F1 scores for specific classes. However, ResNet50 exhibited higher recall for LULC, indicating fewer missed cases. Cross entropy analysis showed that the ViT model had lower average uncertainty, particularly in the LUAD, Normal, and LUSC classes, compared to ResNet50. This finding suggests that ViT predictions are generally more reliable, though ResNet50 performed better for LULC. The study underscores that accuracy alone is insufficient for model comparison, as cross entropy offers deeper insights into the reliability and confidence of model predictions. The results highlight the importance of incorporating cross entropy alongside traditional metrics for a more comprehensive evaluation of deep learning models in medical image classification, providing a nuanced understanding of their performance and reliability. While the ViT outperformed the CNN-based ResNet50 in lung cancer classification based on cross-entropy values, the performance differences were minor and may not hold clinical significance. Therefore, it may be premature to consider replacing CNNs with ViTs in this specific application.

Comparison of efficacy of lung ultrasound and chest X-ray in diagnosing pulmonary edema and pleural effusion in ICU patients: A single centre, prospective, observational study

Background and Aims While chest X-ray (CXR) has been a conventional tool in intensive care units (ICUs) to identify lung pathologies, computed tomography (CT) scan remains the gold standard. Use of lung ultrasound (LUS) in resource-rich ICUs is still under investigation. The present study compares the utility of LUS to that of CXR in identifying pulmonary edema and pleural effusion in ICU patients. In addition, consolidation and pneumothorax were analyzed as secondary outcome measures. Material and Methods This is a prospective, single centric, observational study. Patients admitted in ICU were examined for lung pathologies, using LUS by a trained intensivist;and CXR done within 4 hours of each other. The final diagnosis was ascertained by an independent senior radiologist, based on the complete medical chart including clinical findings and the results of thoracic CT, if available. The results were compared and analyzed. Results Sensitivity, specificity and diagnostic accuracy of LUS was 95%, 94.4%, 94.67% for pleural effusion;and 98.33%, 97.78%, 98.00% for pulmonary edema respectively. Corresponding values with CXR were 48.33%, 76.67%, 65.33% for pleural effusion;and 36.67%, 82.22% and 64.00% for pulmonary edema respectively. Sensitivity, specificity and diagnostic accuracy of LUS was 91.30%, 96.85%, 96.00% for consolidation;and 100.00%, 79.02%, 80.00% for pneumothorax respectively. Corresponding values with CXR were 60.87%, 81.10%, 78.00% for consolidation;and 71.3%, 97.20%, 96.00% for pneumothorax respectively. Conclusion LUS has better diagnostic accuracy in diagnosis of pleural effusion and pulmonary edema when compared with CXR and is thus recommended as an effective alternative for diagnosis of these conditions in acute care settings. Our study recommends that a thoracic CT scan can be avoided in most of such cases.

Current Status of Clinical Application and Basic Research on Draba nemerosa Hebecarpa Jujube Lung-Diarrhoea Soup

The clinical application and basic research of Draba nemerosa Hebecarpa jujube diarrhoea lung soup focus on respiratory diseases and circulatory diseases, and its clinical application is more compared with the basic research, and Draba nemerosa Hebecarpa jujube diarrhoea lung soup is mostly used in the form of “Draba nemerosa Hebecarpa Hebecarpa jujube diarrhoea lung soup with additional subtractions or other formulas combining Draba nemerosa Hebecarpa Hebecarpa Hebecarpa jujube diarrhoea lung soup” in the clinical application. This article will focus on the main mechanisms of Draba nemerosa Hebecarpa jujube diarrhoea lung soup and its main components in the treatment of respiratory and circulatory diseases, and will give a review of the basic research on Draba nemerosa Hebecarpa Hebecarpa jujube diarrhoea lung soup as follows.