Multilevel Attention Unet Segmentation Algorithmfor Lung Cancer Based on CT Images

Lung cancer is a malady of the lungs that gravely jeopardizes human health.Therefore,early detection and treatment are paramount for the preservation of human life.Lung computed tomography(CT)image sequences can explicitly delineate the pathological condition of the lungs.To meet the imperative for accurate diagnosis by physicians,expeditious segmentation of the region harboring lung cancer is of utmost significance.We utilize computer-aided methods to emulate the diagnostic process in which physicians concentrate on lung cancer in a sequential manner,erect an interpretable model,and attain segmentation of lung cancer.The specific advancements can be encapsulated as follows:1)Concentration on the lung parenchyma region:Based on 16-bit CT image capturing and the luminance characteristics of lung cancer,we proffer an intercept histogram algorithm.2)Focus on the specific locus of lung malignancy:Utilizing the spatial interrelation of lung cancer,we propose a memory-based Unet architecture and incorporate skip connections.3)Data Imbalance:In accordance with the prevalent situation of an overabundance of negative samples and a paucity of positive samples,we scrutinize the existing loss function and suggest a mixed loss function.Experimental results with pre-existing publicly available datasets and assembled datasets demonstrate that the segmentation efficacy,measured as Area Overlap Measure(AOM)is superior to 0.81,which markedly ameliorates in comparison with conventional algorithms,thereby facilitating physicians in diagnosis.

Secondary metabolites of mulberry leaves exert anti-lung cancer activity through regulating the PD-L1/PD-1 signaling pathway

Lung cancer ranks the top of malignancies that cause cancer-related deaths worldwide.The leaves of Morus alba L are traditional Chinese medicine widely applied in respiratory diseases.Our previous work has demonstrated the anti-lung cancer effect of secondary metabolites of mulberry leaf,but their mechanism of action has still not fully elucidated.We synthesized Moracin N(MAN)-Probe conjugated with alkyne to label lung cancer cells and identified protein targets by chemical proteomic analysis.MAN and its probe exerted similar growth-inhibitory effect on human lung cancer cells.Chemical proteomic results showed that MAN targeted the programmed death ligand 1(PD-L1)checkpoint pathway and T cell receptor(TCR)signaling pathway,indicating its immune-regulatory function.Cell-free surface plasmon resonance(SPR)results showed the direct interaction of MAN with PD-L1 protein.Molecular docking analysis demonstrated that MAN bound to E158 residue of PD-L1 protein.MAN downregulated the expression levels of PD-L1 in a time-and dose-dependent manner and disrupted the PD-L1/programmed death 1(PD-1)binding,including other secondary metabolites of mulberry leaves Guangsangon E(GSE)and Chalcomoracin(CMR).Human peripheral blood mononuclear cells(PBMCs)co-cultured with MAN-treated A549 cells,resulting in the increase of CD8^(+)GZMB^(+)T cells and the decrease of CD8^(+)PD-1^(+)T cells.It suggested that MAN exerts anti-cancer effect through blocking the PD-L1/PD-1 signaling.In vivo,MAN combined with anti-PD-1 antibody significantly inhibited lung cancer development and metastasis,indicating their synergistic effect.Taken together,secondary metabolites of mulberry leaves target the PD-L1/PD-1 signaling,enhance T cell-mediated immunity and inhibit the tumorigenesis of lung cancer.Their modulatory effect on tumor microenvironment makes them able to enhance the therapeutic efficacy of immune checkpoint inhibitors in lung cancer.

Nursing effect of narrative nursing intervention on postoperative patients with severe lung cancer

BACKGROUND Lung cancer is a common disease with high mortality,and psychological support is very important in the diagnosis and treatment of postoperative patients with cancer pain.AIM To explore the application effect of the narrative nursing method in postoperative lung cancer patients in the intensive care unit.METHODS A total of 120 patients diagnosed with lung cancer and experiencing cancer-related pain were randomly allocated into two groups:an observation group and a control group,each consisting of 60 cases.The control group was given routine analgesic and psychological care,while the research group applied the five-step narrative nursing method based on routine care,comparing the visual analogue scale scores,sleep status,anxiety and depression status,and quality of life of the two groups of patients before and after the intervention.RESULTS The pain scores,anxiety scores,and depression scores of the study group were lower than those of the control group after the intervention using the narrative nursing method,and the difference was statistically significant(P<0.05).CONCLUSION Using narrative nursing methods to intervene in patients with lung cancer combined with cancerous pain can help patients to correctly recognize their disease,adjust their mentality,establish confidence,alleviate patients'subjective pain feelings,and improve their adverse emotions.

Imbalance of Circulating Follicular Regulatory and Follicular Helper T Cell Subpopulations Is Associated with Disease Progression and Serum CYFRA 21-1 Levels in Patients with Non-small Cell Lung Cancer

Objective This study aimed to investigate the changes of follicular helper T(TFH)and follicular regulatory T(TFR)cell subpopulations in patients with non-small cell lung cancer(NSCLC)and their significance.Methods Peripheral blood was collected from 58 NSCLC patients at different stages and 38 healthy controls.Flow cytometry was used to detect TFH cell subpopulation based on programmed death 1(PD-1)and inducible co-stimulator(ICOS),and TFR cell subpopulation based on cluster determinant 45RA(CD45RA)and forkhead box protein P3(FoxP3).The levels of interleukin-10(IL-10),interleukin-17a(IL-17a),interleukin-21(IL-21),and transforming growth factor-β(TGF-β)in the plasma were measured,and changes in circulating B cell subsets and plasma IgG levels were also analyzed.The correlation between serum cytokeratin fragment antigen 21-1(CYFRA 21-1)levels and TFH,TFR,or B cell subpopulations was further explored.Results The TFR/TFH ratio increased significantly in NSCLC patients.The CD45RA^(+)FoxP3^(int) TFR subsets were increased,with their proportions increasing in stages Ⅱ to Ⅲ and decreasing in stage IV.PD-1^(+)ICOS+TFH cells showed a downward trend with increasing stages.Plasma IL-21 and TGF-β concentrations were increased in NSCLC patients compared with healthy controls.Plasmablasts,plasma IgG levels,and CD45RA^(+)FoxP3^(int) TFR cells showed similar trends.TFH numbers and plasmablasts were positively correlated with CYFRA 21-1 in stages Ⅰ-Ⅲ and negatively correlated with CYFRA 21-1 in stage IV.Conclusion Circulating TFH and TFR cell subpopulations and plasmablasts dynamically change in different stages of NSCLC,which is associated with serum CYFRA 21-1 levels and reflects disease progression.

Enhanced recovery after surgery in elderly patients with non-small cell lung cancer who underwent video-assisted thoracic surgery

BACKGROUND This study was designed to investigate the clinical outcomes of enhanced recovery after surgery(ERAS)in the perioperative period in elderly patients with nonsmall cell lung cancer(NSCLC).AIM To investigate the potential enhancement of video-assisted thoracic surgery(VATS)in postoperative recovery in elderly patients with NSCLC.METHODS We retrospectively analysed the clinical data of 85 elderly NSCLC patients who underwent ERAS(the ERAS group)and 327 elderly NSCLC patients who received routine care(the control group)after VATS at the Department of Thoracic Surgery of Peking University Shenzhen Hospital between May 2015 and April 2017.After propensity score matching of baseline data,we analysed the postoperative stay,total hospital expenses,postoperative 48-h pain score,and postoperative complication rate for the 2 groups of patients who underwent lobectomy or sublobar resection.RESULTS After propensity score matching,ERAS significantly reduced the postoperative hospital stay(6.96±4.16 vs 8.48±4.18 d,P=0.001)and total hospital expenses(48875.27±18437.5 vs 55497.64±21168.63 CNY,P=0.014)and improved the satisfaction score(79.8±7.55 vs 77.35±7.72,P=0.029)relative to those for routine care.No significant between-group difference was observed in postoperative 48-h pain score(4.68±1.69 vs 5.28±2.1,P=0.090)or postoperative complication rate(21.2%vs 27.1%,P=0.371).Subgroup analysis showed that ERAS significantly reduced the postoperative hospital stay and total hospital expenses and increased the satisfaction score of patients who underwent lobectomy but not of patients who underwent sublobar resection.CONCLUSION ERAS effectively reduced the postoperative hospital stay and total hospital expenses and improved the satisfaction score in the perioperative period for elderly NSCLC patients who underwent lobectomy but not for patients who underwent sublobar resection.

Influence of initial check, information exchange, final accuracy check, reaction information nursing on the psychology of elderly with lung cancer

BACKGROUND As one of the fatal diseases with high incidence,lung cancer has seriously endangered public health and safety.Elderly patients usually have poor self-care and are more likely to show a series of psychological problems.AIM To investigate the effectiveness of the initial check,information exchange,final accuracy check,reaction(IIFAR)information care model on the mental health status of elderly patients with lung cancer.METHODS This study is a single-centre study.We randomly recruited 60 elderly patients with lung cancer who attended our hospital from January 2021 to January 2022.These elderly patients with lung cancer were randomly divided into two groups,with the control group taking the conventional propaganda and education and the observation group taking the IIFAR information care model based on the conventional care protocol.The differences in psychological distress,anxiety and depression,life quality,fatigue,and the locus of control in psychology were compared between these two groups,and the causes of psychological distress were analyzed.RESULTS After the intervention,Distress Thermometer,Hospital Anxiety and Depression Scale(HADS)for anxiety and the HADS for depression,Revised Piper’s Fatigue Scale,and Chance Health Locus of Control scores were lower in the observation group compared to the pre-intervention period in the same group and were significantly lower in the observation group compared to those of the control group(P<0.05).After the intervention,Quality of Life Questionnaire Core 30(QLQ-C30),Internal Health Locus of Control,and Powerful Others Health Locus of Control scores were significantly higher in the observation and the control groups compared to the pre-intervention period in their same group,and QLQ-C30 scores were significantly higher in the observation group compared to those of the control group(P<0.05).CONCLUSION The IIFAR information care model can help elderly patients with lung cancer by reducing their anxiety and depression,psychological distress,and fatigue,improving their tendencies on the locus of control in psychology,and enhancing their life qualities.

First-line immunotherapy for advanced non-small cell lung cancer:current progress and future prospects

Global Cancer Statistics 2022 reported the prevalence and high mortality rate of lung cancer.Notably,non-small cell lung cancer(NSCLC)accounts for the majority of the histologic types1.Precision therapy for lung cancer has progressed rapidly and immune checkpoint inhibitors(ICIs)have become a leading research topic.Indeed,ICI therapy has been shown to improve the prognosis of lung cancer patients.

Empowering Diagnosis: Cutting-Edge Segmentation and Classification in Lung Cancer Analysis

Lung cancer is a leading cause of global mortality rates.Early detection of pulmonary tumors can significantly enhance the survival rate of patients.Recently,various Computer-Aided Diagnostic(CAD)methods have been developed to enhance the detection of pulmonary nodules with high accuracy.Nevertheless,the existing method-ologies cannot obtain a high level of specificity and sensitivity.The present study introduces a novel model for Lung Cancer Segmentation and Classification(LCSC),which incorporates two improved architectures,namely the improved U-Net architecture and the improved AlexNet architecture.The LCSC model comprises two distinct stages.The first stage involves the utilization of an improved U-Net architecture to segment candidate nodules extracted from the lung lobes.Subsequently,an improved AlexNet architecture is employed to classify lung cancer.During the first stage,the proposed model demonstrates a dice accuracy of 0.855,a precision of 0.933,and a recall of 0.789 for the segmentation of candidate nodules.The suggested improved AlexNet architecture attains 97.06%accuracy,a true positive rate of 96.36%,a true negative rate of 97.77%,a positive predictive value of 97.74%,and a negative predictive value of 96.41%for classifying pulmonary cancer as either benign or malignant.The proposed LCSC model is tested and evaluated employing the publically available dataset furnished by the Lung Image Database Consortium and Image Database Resource Initiative(LIDC-IDRI).This proposed technique exhibits remarkable performance compared to the existing methods by using various evaluation parameters.

Increased Incidence of Severe Adverse Events in Non-Small Cell Lung Cancer Patients with Previous Tuberculosis Episode Treated with PD-1 Inhibitors

Lung cancer is the top cause of cancer deaths globally.Advances in immune checkpoint inhibitors(ICIs)have transformed cancer treatment,but their use in lung cancer has led to more side effects.This study examined if past pulmonary tuberculosis(TB)affects ICIs’effectiveness and safety in lung cancer treatment.We reviewed lung cancer patients treated with ICIs at Beijing Chest Hospital from January 2019 to August 2022.

Cancer-educated neutrophils promote lung cancer progression via PARP-1-ALOX5-mediated MMP-9 expression

Objective:Neutrophils are one of the most predominant infiltrating leukocytes in lung cancer tissues and are associated with lung cancer progression.How neutrophils promote lung cancer progression,however,has not been established.Methods:Kaplan–Meier plotter online analysis and tissue immunohistochemistry were used to determine the relationship between neutrophils and overall survival in lung cancer patients.The effect of neutrophils on lung cancer was determined using the Transwell migration assay,a proliferation assay,and a murine tumor model.Gene knockdown was used to determine poly ADPribose polymerase(PARP)-1 function in lung cancer-educated neutrophils.Western blot analysis and gelatin zymography were used to demonstrate the correlation between PARP-1 and matrix metallopeptidase 9(MMP-9).Immunoprecipitation coupled to mass spectrometry(IP/MS)was used to identify the proteins interacting with PARP-1.Co-immunoprecipitation(Co-IP)was used to confirm that PARP-1 interacts with arachidonate 5-lipooxygenase(ALOX5).Neutrophil PARP-1 blockage by AG14361 rescued neutrophil-promoted lung cancer progression.Results:An increased number of infiltrating neutrophils was negatively associated with overall survival in lung cancer patients(P<0.001).Neutrophil activation promoted lung cancer cell invasion,migration,and proliferation in vitro,and murine lung cancer growth in vivo.Mechanistically,PARP-1 was shown to be involved in lung cancer cell-induced neutrophil activation to increase MMP-9 expression through interacting and stabilizing ALOX5 by post-translational protein modification(PARylation).Blocking PARP-1 by gene knockdown or AG14361 significantly decreased ALOX5 expression and MMP-9 production,and eliminated neutrophil-mediated lung cancer cell invasion and in vivo tumor growth.Conclusion:We identified a novel mechanism by which PARP-1 mediates lung cancer cell-induced neutrophil activation and PARylates ALOX5 to regulate MMP-9 expression,which exacerbates lung cancer progression.

Metaheuristic-Driven Two-Stage Ensemble Deep Learning for Lung/Colon Cancer Classification

This study investigates the application of deep learning,ensemble learning,metaheuristic optimization,and image processing techniques for detecting lung and colon cancers,aiming to enhance treatment efficacy and improve survival rates.We introduce a metaheuristic-driven two-stage ensemble deep learning model for efficient lung/colon cancer classification.The diagnosis of lung and colon cancers is attempted using several unique indicators by different versions of deep Convolutional Neural Networks(CNNs)in feature extraction and model constructions,and utilizing the power of various Machine Learning(ML)algorithms for final classification.Specifically,we consider different scenarios consisting of two-class colon cancer,three-class lung cancer,and fiveclass combined lung/colon cancer to conduct feature extraction using four CNNs.These extracted features are then integrated to create a comprehensive feature set.In the next step,the optimization of the feature selection is conducted using a metaheuristic algorithm based on the Electric Eel Foraging Optimization(EEFO).This optimized feature subset is subsequently employed in various ML algorithms to determine the most effective ones through a rigorous evaluation process.The top-performing algorithms are refined using the High-Performance Filter(HPF)and integrated into an ensemble learning framework employing weighted averaging.Our findings indicate that the proposed ensemble learning model significantly surpasses existing methods in classification accuracy across all datasets,achieving accuracies of 99.85%for the two-class,98.70%for the three-class,and 98.96%for the five-class datasets.

Bronchoalveolar lavage fluid assessment facilitates precision medicine for lung cancer

Lung cancer is the most common and fatal malignant disease worldwide and has the highest mortality rate among tumor-related causes of death.Early diagnosis and precision medicine can significantly improve the survival rate and prognosis of lung cancer patients.At present,the clinical diagnosis of lung cancer is challenging due to a lack of effective non-invasive detection methods and biomarkers,and treatment is primarily hindered by drug resistance and high tumor heterogeneity.Liquid biopsy is a method for detecting circulating biomarkers in the blood and other body fluids containing genetic information from primary tumor tissues.Bronchoalveolar lavage fluid(BALF)is a potential liquid biopsy medium that is rich in a variety of bioactive substances and cell components.BALF contains information on the key characteristics of tumors,including the tumor subtype,gene mutation type,and tumor environment,thus BALF may be used as a diagnostic supplement to lung biopsy.In this review,the current research on BALF in the diagnosis,treatment,and prognosis of lung cancer is summarized.The advantages and disadvantages of different components of BALF,including cells,cell-free DNA,extracellular vesicles,and micro RNA are introduced.In particular,the great potential of extracellular vesicles in precision diagnosis and detection of drug-resistant for lung cancer is highlighted.In addition,the performance of liquid biopsies with different body fluid sources in lung cancer detection are compared to facilitate more selective studies involving BALF,thereby promoting the application of BALF for precision medicine in lung cancer patients in the future.

Primary biliary cholangitis presenting with granulomatous lung disease misdiagnosed as lung cancer:A case report

BACKGROUND There are few cases of pulmonary granulomatous changes secondary to primary biliary cirrhosis(PBC).No case of granulomatous lung disease secondary to PBC misdiagnosed as lung cancer had been reported.CASE SUMMARY A middle-aged woman presented with lung nodules and was misdiagnosed with lung cancer by positron emission tomography/computed tomography.She underwent left lobectomy,and the pathology of the nodules showed granulomatous inflammation,which was then treated with antibiotics.However,a new nodule appeared.Further investigation with lung biopsy and liver serology led to the diagnosis of PBC,and chest computed tomography indicated significant reduction in the pulmonary nodule by treatment with methylprednisolone and ursodeoxycholic acid.CONCLUSION Diagnosis of pulmonary nodules requires integrating various clinical data to avoid unnecessary pulmonary lobectomy.

Tongue image feature correlation analysis in benign lung nodules and lung cancer

Objective To analyze the differences in the correlation of tongue image indicators among patients with benign lung nodules and lung cancer.Methods From July 1;2020 to March 31;2022;clinical information of lung cancer patients and benign lung nodules patients was collected at the Oncology Department of Longhua Hos-pital Affiliated to Shanghai University of Traditional Chinese Medicine and the Physical Ex-amination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chi-nese Medicine;respectively.We obtained tongue images from patients with benign lung nod-ules and lung cancer using the TFDA-1 digital tongue diagnosis instrument;and analyzed these images with the TDAS V2.0 software.The extracted indicators included color space pa-rameters in the Lab system for both the tongue body(TB)and tongue coating(TC)(TB/TC-L;TB/TC-a;and TB/TC-b);textural parameters[TB/TC-contrast(CON);TB/TC-angular second moment(ASM);TB/TC-entropy(ENT);and TB/TC-MEAN];as well as TC parameters(perAll and perPart).The bivariate correlation of TB and TC features was analyzed using Pearson’s or Spearman’s correlation analysis;and the overall correlation was analyzed using canonical correlation analysis(CCA).Results Samples from 307 patients with benign lung nodules and 276 lung cancer patients were included after excluding outliers and extreme values.Simple correlation analysis indi-cated that the correlation of TB-L with TC-L;TB-b with TC-b;and TB-b with perAll in lung cancer group was higher than that in benign nodules group.Moreover;the correlation of TB-a with TC-a;TB-a with perAll;and the texture parameters of the TB(TB-CON;TB-ASM;TB-ENT;and TB-MEAN)with the texture parameters of the TC(TC-CON;TC-ASM;TC-ENT;and TC-MEAN)in benign nodules group was higher than lung cancer group.CCA further demon-strated a strong correlation between the TB and TC parameters in lung cancer group;with the first and second pairs of typical variables in benign nodules and lung cancer groups indicat-ing correlation coefficients of 0.918 and 0.817(P<0.05);and 0.940 and 0.822(P<0.05);re-spectively.Conclusion Benign lung nodules and lung cancer patients exhibited differences in correla-tion in the L;a;and b values of the TB and TC;as well as the perAll value of the TC;and the texture parameters(TB/TC-CON;TB/TC-ASM;TB/TC-ENT;and TB/TC-MEAN)between the TB and TC.Additionally;there were differences in the overall correlation of the TB and TC be-tween the two groups.Objective tongue diagnosis indicators can effectively assist in the diag-nosis of benign lung nodules and lung cancer;thereby providing a scientific basis for the ear-ly detection;diagnosis;and treatment of lung cancer.

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.

TonEBP expression is essential in the IL-1β–induced migration and invasion of human A549 lung cancer cells

Lung cancer has the highest mortality rate among all cancers,in part because it readily metastasizes.The tumor microenvironment,comprising blood vessels,fibroblasts,immune cells,and macrophages[including tumor-associated macrophages(TAMs)],is closely related to cancer cell growth,migration,and invasion.TAMs secrete several cytokines,including interleukin(IL)-1β,which participate in cancer migration and invasion.p21-activated kinase 1(PAK1),an important signaling molecule,induces cell migration and invasion in several carcinomas.Tonicityresponsive enhancer-binding protein(TonEBP)is also known to participate in cancer cell growth,migration,and invasion.However,the mechanisms by which it increases lung cancer migration remain unclear.Therefore,in this study,we aimed to elucidate the mechanisms by which IL-1βand TonEBP affect lung cancer cell migration and invasion.We found that A549 cocultured-MΦ-secreted IL-1βinduced A549 cell migration and invasion via the PAK1 pathway.TonEBP deficiency reduced A549 cell migration and invasion and increased responsiveness to IL-1β–induced migration and invasion.PAK1 phosphorylation,which was promoted by IL-1β,was reduced when TonEBP was depleted.These results suggest that TonEBP plays an important role in IL-1βinduction and invasiveness of A549 cells via the PAK1 pathway.These findings could be valuable in identifying potential targets for lung cancer treatment.

The role of cholesterol metabolism in lung cancer

Elevated serum cholesterol metabolism is associated with a reduced risk of lung cancer.Disrupted cholesterol metabolism is evident in both lung cancer patients and tumor cells.Inhibiting tumor cell cholesterol uptake or biosynthesis pathways,through the modulation of receptors and enzymes such as liver X receptor and sterolregulatory element binding protein 2,effectively restrains lung tumor growth.Similarly,promoting cholesterol excretion yields comparable effects.Cholesterol metabolites,including oxysterols and isoprenoids,play a crucial role in regulating cholesterol metabolism within tumor cells,consequently impacting cancer progression.In lung cancer patients,both the cholesterol levels in the tumor microenvironment and within tumor cells significantly influence cell growth,proliferation,and metastasis.The effects of cholesterol metabolism are further mediated by the reprogramming of immune cells such as T cells,B cells,macrophages,myeloid-derived suppressor cells,among others.Ongoing research is investigating drugs targeting cholesterol metabolism for clinical treatments.Statins,targeting the cholesterol biosynthesis pathway,are widely employed in lung cancer treatment,either as standalone agents or in combination with other drugs.Additionally,drugs focusing on cholesterol transportation have shown promise as effective therapies for lung cancer.In this review,we summarized current research regarding the rule of cholesterol metabolism and therapeutic advances in lung cancer.

Epidemiological and clinical characteristics of lung cancer in Saudi Arabia:a retrospective study in single oncology center

Background:Lung cancer(LC)is one of the most common neoplastic diseases and a leading cause of death in Saudi Arabia.Its incidence in Saudi Arabia has increased by more than 3%within two decades.Our study aimed to describe the epidemiological and genetic landscapes of LC in Al-Madinah city in Saudi Arabia.Methods:A retrospective analysis was conducted on the medical records of 65 patients diagnosed with lung cancer between 2015 and 2021 at a single medical oncology center in Al-Madinah city of Saudi Arabia.Results:The mean patients’age was 59.2 years,with 50(76.9%)males and 15(23.1%)females;37(57%)smokers,and 28(43%)non-smokers.The number of cases per year has increased gradually over six years from 2015(n=3)to 2020(n=13).The most prevalent histopathological diagnosis was non-small cell lung cancer(NSCLC)(n=58,89%)followed by small cell lung cancer(SCLC)(n=5,7.8%).NSCLC was frequently more common in smokers while squamous cell carcinoma was more frequent in non-smokers.Around 89%(n=58)of the cases were diagnosed in late stage IV and the most common metastatic sites were to pleura and lymph nodes(n=32,49.2%).Program Death Legend-1(PDL-1)was fairly expressed in 7/10(70%)patients.Epidermal Growth Factor Receptor(EGFR)was mutated in 5/17(29%)patients.Other mutations detected include Anaplastic Lymphoma Kinase(ALK)and phosphatidylinositol 3-kinase(PIK3C)mutations in two patients.Conclusions:Our study revealed that lung cancer is a significant burden in AlMadinah city of Saudi Arabia.If the risk factors are not controlled,the number of cases may increase considerably.Health education about the risk factors and cancer prevention helps in early lung cancer detection.

MicroRNAs modulation in lung cancer: exploring dual mechanisms and clinical prospects

The global incidence of lung cancer is marked by a considerably elevated mortality rate.MicroRNAs(miRNAs)exert pivotal influence in the intricate orchestration of gene regulation,and their dysregulation can precipitate dire consequences,notably cancer.Within this context,miRNAs encapsulated in exosomes manifest a diversified impact on the landscape of lung cancer,wherein their actions may either foster angiogenesis,cell proliferation,and metastasis,or counteract these processes.This comprehensive review article discerns potential targets for the prospective development of therapeutic agents tailored for lung cancer.Tumor-suppressive miRNAs,such as miR-204,miR-192,miR-30a,miR-34a,miR-34b,miR-203,and miR-212,exhibit heightened expression and demonstrate the capacity to inhibit cellular proliferation and invasiveness.Conversely,the deleterious effects of tumor-promoting miRNAs like miR-21,miR-106a,miR-155,miR-205,and miR-210 can be attenuated through the application of their respective inhibitors.Distinct miRNAs selectively target various oncogenes,including NUAK Family Kinase 1(NUAK1),Snail Family Transcriptional Repressor 1(Snai1),Astrocyte elevated gene-1(AEG-1),Vimentin,Proliferation and apoptosis adaptor protein 15(PEA-15/PED),Hypoxia-inducible factor 1-alpha(HIF1),as well as tumor suppressor genes such as phosphatase and tensin homolog(PTEN),Suppressor of cytokine signaling 1(SOCS1),Tumor protein P53 binding protein 1(TP53BP1),and PH Domain and Leucine Rich Repeat Protein Phosphatase 2(PHLP22).This investigative approach proves invaluable in elucidating the specific miRNAs implicated in the deregulation of crucial genes pivotal to the pathogenesis of cancer.

Enhancing Early Detection of Lung Cancer through Advanced Image Processing Techniques and Deep Learning Architectures for CT Scans

Lung cancer remains a major concern in modern oncology due to its high mortality rates and multifaceted origins,including hereditary factors and various clinical changes.It stands as the deadliest type of cancer and a significant cause of cancer-related deaths globally.Early diagnosis enables healthcare providers to administer appropriate treatment measures promptly and accurately,leading to improved prognosis and higher survival rates.The significant increase in both the incidence and mortality rates of lung cancer,particularly its ranking as the second most prevalent cancer among women worldwide,underscores the need for comprehensive research into efficient screening methods.Advances in diagnostic techniques,particularly the use of computed tomography(CT)scans,have revolutionized the identification of lung cancer.CT scans are renowned for their ability to provide high-resolution images and are particularly effective in detecting small,calcified areas,crucial for identifying earlystage lung cancer.Consequently,there is growing interest in enhancing computer-aided detection(CAD)systems.These algorithms assist radiologists by reducing false-positive interpretations and improving the accuracy of early cancer diagnosis.This study aims to enhance the effectiveness of CAD systems through various methods.Initially,the Contrast Limited Adaptive Histogram Equalization(CLAHE)algorithm is employed to preprocess CT scan images,thereby improving their visual quality.Further refinement is achieved by integrating different optimization strategies with the CLAHE method.The CutMix data augmentation technique is applied to boost the performance of the proposed model.A comparative analysis is conducted using deep learning architectures such as InceptionV3,ResNet101,Xception,and EfficientNet.The study evaluates the performance of these architectures in image classification tasks,both with and without the implementation of the CLAHE algorithm.The empirical findings of the study demonstrate a significant reduction in the false positive rate(FPR)and an overall enhancement in diagnostic accuracy.This research not only contributes to the field of medical imaging but also holds significant implications for the early detection and treatment of lung cancer,ultimately aiming to reduce its mortality rates.