[From the 7th TNM staging to the 8th in lung cancer]. / Akciger kanserinde 7. TNM evrelemesinden 8.'ye dogru.

The anatomic extent of disease, that is described by the TNM-classification remains the most important prognostic factor for lung cancer. Based on the changes in tumor characteristics, advances in diagnostic methods and treatment strategies, TNM-classifications are updated from time to time. The 7th TNM-classification was created on the basis of an international, large, and retrospective database. However due to retrospective data, there are still unanswered questions. Therefore "Prospective Lung Cancer Staging Project" is designed. In this project, in addition to the detailed evaluation of T, N, M descriptors; other factors, which were not considered to be relevant to lung cancer staging before, were also analyzed such as demographic data, histologic characteristics, certain biochemical and molecular prognostic and predictive factors. This project will be the basis of 8th TNM-classification for lung cancer. In this manuscript, we discuss the probable changes from the 7th TNM classification to the 8th.

Examining the effectiveness of artificial intelligence applications in asthma and COPD outpatient support in terms of patient health and public cost: SWOT analysis.

This research aimed to examine the effectiveness of artificial intelligence applications in asthma and chronic obstructive pulmonary disease (COPD) outpatient treatment support in terms of patient health and public costs. The data obtained in the research using semiotic analysis, content analysis and trend analysis methods were analyzed with strengths, weakness, opportunities, threats (SWOT) analysis. In this context, 18 studies related to asthma, COPD and artificial intelligence were evaluated. The strengths of artificial intelligence applications in asthma and COPD outpatient treatment stand out as early diagnosis, access to more patients and reduced costs. The points that stand out among the weaknesses are the acceptance and use of technology and vulnerabilities related to artificial intelligence. Opportunities arise in developing differential diagnoses of asthma and COPD and in examining prognoses for the diseases more effectively. Malicious use, commercial data leaks and data security issues stand out among the threats. Although artificial intelligence applications provide great convenience in the outpatient treatment process for asthma and COPD diseases, precautions must be taken on a global scale and with the participation of international organizations against weaknesses and threats. In addition, there is an urgent need for accreditation for the practices to be carried out in this regard.

Shared and unique transcriptomic signature genes and pathways among biopsy, peripheral blood mononuclear cells and bronchoalveolar lavage samples in IPF patients revealed using comparative meta-transcriptome analysis.

Introduction: Idiopathic pulmonary fibrosis (IPF) affects the tissue surrounding the alveoli and occurs when the lung tissue becomes thick and stiff for unknown reasons. Clinical findings are fairly well settled, but the molecular mechanisms of IPF are still poorly known. Materials and Methods: To further our understanding, we collected publicly available transcriptome dataset from IPF cohorts, grouped them according to sampling method [bronchoalveolar lavage (BAL), biopsy, blood], and performed comparative meta-transcriptome study to (I) unravel key pathways (II), set out differences in discovered genes, pathways, and functional annotation with respect to the sampling method, and (III) find biomarkers for early diagnosis. Result: The resulting lists are also compared with DisGeNet reported genes, earlier work, and Kyoto encyclopedia of genes and genomes (KEGG) pathways. Several pathways are shared among BAL and biopsy samples while blood samples point to alternative pathways, indicating the noise in information obtained from these samples. Conclusions: Common to all sampling methods, interleukin-10 pathway and extracellular signaling pathways are pointed as further targets.

Follow-up outcomes of chronic obstructive pulmonary disease patients who underwent dilatation and curettage with the Karakoca resector balloon: A 188-case series over 5 years.

We previously reported satisfactory results with the Karakoca resector balloon in 10 patients with stage IV chronic obstructive pulmonary disease (COPD) who did not respond to medical treatment. In this article, we present the outcomes of the Karakoca resector balloon dilatation and curettage technique in a larger case series (n = 188).A total of 188 COPD patients [mean age (SD): 69.2 (8.0) years; 46 females] classified as stage III to IV by the Global Initiative for Obstructive Lung Disease criteria underwent balloon desobstruction for segmental and subsegmental bronchi by therapeutic bronchoscopy. None of the patients could have achieved symptom relief even under high-dose inhaled bronchodilators and corticosteroids, oral corticosteroids, or oxygen and noninvasive mechanical ventilation therapy before the intervention. Forced expiratory volume in 1 s (FEV1) and oxygen saturation (SpO2) were measured, and modified Borg dyspnea scale (MBS) scores were determined before and 1 week and 1 month after the intervention.All patients were active smokers and 80% had concomitant chronic diseases. After the intervention, there was a notable reduction in the oxygen need of the patients. Comparison of lung function tests 1 week after the procedure with results before the procedure showed significant improvements in FEV1, MBS, and SpO2 levels (P < 0.001 for each), and the improvements were maintained for the entire postprocedural month (P < 0.001 for each). Except for 4 males, all patients were free of symptoms.These results confirmed our early observations that balloon dilatation and curettage is a safe and successful technique for medical treatment-resistant COPD.