Development of a multi-modal learning-based lymph node metastasis prediction model for lung cancer.

PURPOSE: This study proposed a three-dimensional (3D) multi-modal learning-based model for the automated prediction and classification of lymph node metastasis in patients with non-small cell lung cancer (NSCLC) using computed tomography (CT) images and clinical information. METHODS: We utilized clinical information and CT image data from 4239 patients with NSCLC across multiple institutions. Four deep learning algorithm-based multi-modal models were constructed and evaluated for lymph node classification. To further enhance classification performance, a soft-voting ensemble technique was applied to integrate the outcomes of multiple multi-modal models. RESULTS: A comparison of the classification performance revealed that the multi-modal model, which integrated CT images and clinical information, outperformed the single-modal models. Among the four multi-modal models, the Xception model demonstrated the highest classification performance, with an area under the curve (AUC) of 0.756 for the internal test dataset and 0.736 for the external validation dataset. The ensemble model (SEResNet50_DenseNet121_Xception) exhibited even better performance, with an AUC of 0.762 for the internal test dataset and 0.751 for the external validation dataset, surpassing the multi-modal model's performance. CONCLUSIONS: Integrating CT images and clinical information improved the performance of the lymph node metastasis prediction models in patients with NSCLC. The proposed 3D multi-modal lymph node prediction model can serve as an auxiliary tool for evaluating lymph node metastasis in patients with non-pretreated NSCLC, aiding in patient screening and treatment planning.

Deep Learning Model Using Stool Pictures for Predicting Endoscopic Mucosal Inflammation in Patients With Ulcerative Colitis.

INTRODUCTION: Stool characteristics may change depending on the endoscopic activity of ulcerative colitis (UC). We developed a deep learning model using stool photographs of patients with UC (DLSUC) to predict endoscopic mucosal inflammation. METHODS: This was a prospective multicenter study conducted in 6 tertiary referral hospitals. Patients scheduled to undergo endoscopy for mucosal inflammation monitoring were asked to take photographs of their stool using smartphones within 1 week before the day of endoscopy. DLSUC was developed using 2,161 stool pictures from 306 patients and tested on 1,047 stool images from 126 patients. The UC endoscopic index of severity was used to define endoscopic activity. The performance of DLSUC in endoscopic activity prediction was compared with that of fecal calprotectin (Fcal). RESULTS: The area under the receiver operating characteristic curve (AUC) of DLSUC for predicting endoscopic activity was 0.801 (95% confidence interval [CI] 0.717-0.873), which was not statistically different from the AUC of Fcal (0.837 [95% CI, 0.767-0.899, DeLong P = 0.458]). When rectal-sparing cases (23/126, 18.2%) were excluded, the AUC of DLSUC increased to 0.849 (95% CI, 0.760-0.919). The accuracy, sensitivity, and specificity of DLSUC in predicting endoscopic activity were 0.746, 0.662, and 0.877 in all patients and 0.845, 0.745, and 0.958 in patients without rectal sparing, respectively. Active patients classified by DLSUC were more likely to experience disease relapse during a median 8-month follow-up (log-rank test, P = 0.002). DISCUSSION: DLSUC demonstrated a good discriminating power similar to that of Fcal in predicting endoscopic activity with improved accuracy in patients without rectal sparing. This study implies that stool photographs are a useful monitoring tool for typical UC.

Advanced Bronchoscopic Diagnostic Techniques in Lung Cancer.

The increasing incidence of incidental pulmonary nodules necessitates effective biopsy techniques for accurate diagnosis and treatment planning. This paper reviews the widely used advanced bronchoscopic techniques, such as radial endobronchial ultrasound-guided transbronchial lung biopsy, electromagnetic navigation bronchoscopy, and the cutting-edge robotic-assisted bronchoscopy. In addition, the cryobiopsy technique, which can enhance diagnostic yield by combination with conventional biopsy tools, is described for application to peripheral pulmonary lesions and mediastinal lesions, respectively.

The Matrix Stiffness Coordinates the Cell Proliferation and PD-L1 Expression via YAP in Lung Adenocarcinoma.

The extracellular matrix (ECM) exerts physiological activity, facilitates cell-to-cell communication, promotes cell proliferation and metastasis, and provides mechanical support for tumor cells. The development of solid tumors is often associated with increased stiffness. A stiff ECM promotes mechanotransduction, and the predominant transcription factors implicated in this phenomenon are YAP/TAZ, ß-catenin, and NF-κB. In this study, we aimed to investigate whether YAP is a critical mediator linking matrix stiffness and PD-L1 in lung adenocarcinoma. We confirmed that YAP, PD-L1, and Ki-67, a marker of cell proliferation, increase as the matrix stiffness increases in vitro using the lung adenocarcinoma cell lines PC9 and HCC827 cells. The knockdown of YAP decreased the expression of PD-L1 and Ki-67, and conversely, the overexpression of YAP increased the expression of PD-L1 and K-67 in a stiff-matrix environment (20.0 kPa). Additionally, lung cancer cells were cultured in a 3D environment, which provides a more physiologically relevant setting, and compared to the results obtained from 2D culture. Similar to the findings in 2D culture, it was confirmed that YAP influenced the expression of PD-L1 and K-67 in the 3D culture experiment. Our results suggest that matrix stiffness controls PD-L1 expression via YAP activation, ultimately contributing to cell proliferation.

Prediction of lung cancer using novel biomarkers based on microbiome profiling of bronchoalveolar lavage fluid.

There is an unmet need for biomarkers for the diagnosis of lung cancer and decision criteria for lung biopsy. We comparatively investigated the lung microbiomes of patients with lung cancer and benign lung diseases. Patients who underwent bronchoscopy at Chungnam National University Hospital between June 2021 and June 2022 were enrolled. Bronchoalveolar lavage fluid (BALF) was collected from 24 patients each with lung cancer and benign lung diseases. The samples were analyzed using 16S rRNA-based metagenomic sequencing. We found that alpha diversity and the beta diversity distribution (P = 0.001) differed significantly between patients with benign lung diseases and those with lung cancer. Firmicutes was the most abundant phylum in patients with lung cancer (33.39% ± 17.439), whereas Bacteroidota was the most abundant phylum in patients with benign lung disease (31.132% ± 22.505), respectively. In differential abundance analysis, the most differentially abundant microbiota taxon was unclassified_SAR202_clade, belonging to the phylum Chloroflexi. The established prediction model distinguished patients with benign lung disease from those with lung cancer with a high accuracy (micro area under the curve [AUC] = 0.98 and macro AUC = 0.99). The BALF microbiome may be a novel biomarker for the detection of lung cancer.

Deep learning-radiomics integrated noninvasive detection of epidermal growth factor receptor mutations in non-small cell lung cancer patients.

This study focused on a novel strategy that combines deep learning and radiomics to predict epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer (NSCLC) using computed tomography (CT). A total of 1280 patients with NSCLC who underwent contrast-enhanced CT scans and EGFR mutation testing before treatment were selected for the final study. Regions of interest were segmented from the CT images to extract radiomics features and obtain tumor images. These tumor images were input into a convolutional neural network model to extract 512 image features, which were combined with radiographic features and clinical data to predict the EGFR mutation. The generalization performance of the model was evaluated using external institutional data. The internal and external datasets contained 324 and 130 EGFR mutants, respectively. Sex, height, weight, smoking history, and clinical stage were significantly different between the EGFR-mutant patient groups. The EGFR mutations were predicted by combining the radiomics and clinical features, and an external validation dataset yielded an area under the curve (AUC) value of 0.7038. The model utilized 1280 tumor images, radiomics features, and clinical characteristics as input data and exhibited an AUC of approximately 0.81 and 0.78 during the primary cohort and external validation, respectively. These results indicate the feasibility of integrating radiomics analysis with deep learning for predicting EGFR mutations. CT-image-based genetic testing is a simple EGFR mutation prediction method, which can improve the prognosis of NSCLC patients and help establish personalized treatment strategies.

Roles of Inflammatory Biomarkers in Exhaled Breath Condensates in Respiratory Clinical Fields.

BACKGROUND: Exhaled condensates contain inflammatory biomarkers; however, their roles in the clinical field have been under-investigated. METHODS: We prospectively enrolled subjects admitted to pulmonology clinics. We collected exhaled breath condensates (EBC) and analysed the levels of six and 12 biomarkers using conventional and multiplex enzyme-linked immunosorbent assay, respectively. RESULTS: Among the 123 subjects, healthy controls constituted the largest group (81 participants; 65.9%), followed by the preserved ratio impaired spirometry group (21 patients; 17.1%) and the chronic obstructive pulmonary disease (COPD) group (21 patients; 17.1%). In COPD patients, platelet derived growth factor-AA exhibited strong positive correlations with COPD assessment test (ρ=0.5926, p=0.0423) and COPD-specific version of St. George's Respiratory Questionnaire (SGRQ-C) score (total, ρ=0.6725, p=0.0166; activity, ρ=0.7176, p=0.0086; and impacts, ρ=0.6151, p=0.0333). Granzyme B showed strong positive correlations with SGRQ-C score (symptoms, ρ=0.6078, p=0.0360; and impacts, ρ=0.6007, p=0.0389). Interleukin 6 exhibited a strong positive correlation with SGRQ-C score (activity, ρ=0.4671, p=0.0378). The absolute serum eosinophil and basophil counts showed positive correlations with pro-collagen I alpha 1 (ρ=0.6735, p=0.0164 and ρ=0.6295, p=0.0283, respectively). In healthy subjects, forced expiratory volume in 1 second (FEV1)/forced vital capacity demonstrated significant correlation with CC chemokine ligand 3 (CCL3)/macrophage inflammatory protein 1 alpha (ρ=0.3897 and p=0.0068). FEV1 exhibited significant correlation with CCL11/eotaxin (ρ=0.4445 and p=0.0017). CONCLUSION: Inflammatory biomarkers in EBC might be useful to predict quality of life concerning respiratory symptoms and serologic markers. Further studies are needed.

Diagnostic Value of Transbronchial Lung Cryobiopsy Using an Ultrathin Cryoprobe and Guide Sheath for Peripheral Pulmonary Lesions.

BACKGROUND: The addition of cryobiopsy to conventional biopsy methods improves the diagnostic yield of peripheral pulmonary lesions. Moreover, cryobiopsy with a guide sheath (GS) provides additional diagnostic benefits. Semi-real-time biopsy can be repeatedly performed using conventional biopsy devices and a GS, and subsequent cryobiopsy can be easily performed at the same location. Recently, a disposable 1.1 mm-diameter ultrathin cryoprobe has been developed and can be used with a 1.95 mm GS in a 2.0 mm working channel. In this study, we evaluated the diagnostic performance of transbronchial lung cryobiopsy (TBLC) with the 1.1 mm cryoprobe and a GS in patients with peripheral pulmonary lesions. METHODS: We retrospectively reviewed the medical records of patients who underwent endobronchial ultrasound transbronchial lung biopsy with a guide sheath and TBLC from July 23, 2021 to April 30, 2022 at Chungnam National University Hospital. RESULTS: Of a consecutive series of 229 patients, 199 were included. The diagnostic yields of forceps biopsy and cryobiopsy were 65.3% (130/199) and 84.4% (168/199), respectively, and the total diagnostic yield was 91.5% (182/199) ( P <0.001 vs. forceps biopsy). Multivariate analysis showed that solid lesion morphology [adjusted odds ratio (OR) 3.659, P =0.002] was associated with a significantly greater diagnostic yield of cryobiopsy, whereas a lesion diameter >20 mm ( P =0.026; adjusted OR 3.816) and 'within' orientation ( P =0.004; adjusted OR 6.174) were associated with a significantly greater overall diagnostic yield. CONCLUSION: TBLC using an ultrathin cryoprobe and GS markedly improves the diagnostic yield.

Spontaneous regression of recurrent pulmonary large cell neuroendocrine carcinoma with alteration of PD-L1 expression after surgical resection: A case report.

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rare and aggressive subtype of non-small cell lung cancer with a poor prognosis. Spontaneous regression, that is, partial or complete disappearance of a malignancy without medical intervention, is extremely rare in LCNEC. Herein, we present a case of spontaneous complete regression in a 71-year-old male patient with recurrent LCNEC after surgical resection. The patient was diagnosed with stage IB LCNEC and underwent surgical resection. At 1-year follow-up, chest computed tomography revealed a recurrent lesion next to the stump site and enlargement of lymph nodes 4R and 7; recurrent LCNEC was confirmed. The patient declined chemoradiation therapy. One year after recurrence, the patient experienced severe multifocal necrotizing pneumonia and was treated with antibiotics, resulting in a gradual decrease in the size of the recurrent lesion. Five years after the initial diagnosis, positron emission tomography/computed tomography revealed no hypermetabolic lesions, indicating the spontaneous complete regression of LCNEC.

RNA-Seq-Based Molecular Classification Analyses in Colorectal Cancer and Synchronous Adenoma.

Colorectal cancers (CRC) are classified into consensus molecular subtypes (CMS) based on gene expression profiles. The revised classification system iCMS was proposed by considering intrinsic epithelial status, microsatellite instability (MSI), and fibrosis. This study aimed to provide molecular evidence for the adenoma-carcinoma sequence concept by examining CRC and synchronous adenomas using iCMS. Epithelial CMS cell proportion was estimated using CiberSortx, an in silico cell fractionation method that included CMS cell types among the reference cell types. A random forest (RF) model estimated the posterior probabilities of CMS classes, which were compared with the CiberSortx results. Gene expression profiles of the published iCMS signature panel were retrieved from our dataset and subjected to heatmap clustering for classification. Bulk RNA sequencing data were collected from 29 adenocarcinomas and 11 adenoma samples. CiberSortx showed all CRC contained either CMS2 or CMS3 as the major epithelial cancer cell type. The RF model classified approximately half of the CRC as CMS4, whereas CMS4 was hardly detected by CiberSortx. Because they were enriched with myofibroblasts as per the CiberSortx classification, we tentatively designated them as iCMS2-F/iCMS3-F. iCMS coupled with the application of an in silico cell fractionation method can provide the molecular dissection of CRC and adenoma.

A streamlined pipeline based on HmmUFOtu for microbial community profiling using 16S rRNA amplicon sequencing.

Microbial community profiling using 16S rRNA amplicon sequencing allows for taxonomic characterization of diverse microorganisms. While amplicon sequence variant (ASV) methods are increasingly favored for their fine-grained resolution of sequence variants, they often discard substantial portions of sequencing reads during quality control, particularly in datasets with large number samples. We present a streamlined pipeline that integrates FastP for read trimming, HmmUFOtu for operational taxonomic units (OTU) clustering, Vsearch for chimera checking, and Kraken2 for taxonomic assignment. To assess the pipeline's performance, we reprocessed two published stool datasets of normal Korean populations: one with 890 and the other with 1,462 independent samples. In the first dataset, HmmUFOtu retained 93.2% of over 104 million read pairs after quality trimming, discarding chimeric or unclassifiable reads, while DADA2, a commonly used ASV method, retained only 44.6% of the reads. Nonetheless, both methods yielded qualitatively similar ß-diversity plots. For the second dataset, HmmUFOtu retained 89.2% of read pairs, while DADA2 retained a mere 18.4% of the reads. HmmUFOtu, being a closed-reference clustering method, facilitates merging separately processed datasets, with shared OTUs between the two datasets exhibiting a correlation coefficient of 0.92 in total abundance (log scale). While the first two dimensions of the ß-diversity plot exhibited a cohesive mixture of the two datasets, the third dimension revealed the presence of a batch effect. Our comparative evaluation of ASV and OTU methods within this streamlined pipeline provides valuable insights into their performance when processing large-scale microbial 16S rRNA amplicon sequencing data. The strengths of HmmUFOtu and its potential for dataset merging are highlighted.

Enrichment of Activated Fibroblasts as a Potential Biomarker for a Non-Durable Response to Anti-Tumor Necrosis Factor Therapy in Patients with Crohn's Disease.

We investigated whether the response to anti-tumor necrosis factor (anti-TNF) treatment varied according to inflammatory tissue characteristics in Crohn's disease (CD). Bulk RNA sequencing (RNA-seq) data were obtained from inflamed and non-inflamed tissues from 170 patients with CD. The samples were clustered based on gene expression profiles using principal coordinate analysis (PCA). Cellular heterogeneity was inferred using CiberSortx, with bulk RNA-seq data. The PCA results displayed two clusters of CD-inflamed samples: one close to (Inflamed_1) and the other far away (Inflamed_2) from the non-inflamed samples. Inflamed_1 was rich in anti-TNF durable responders (DRs), and Inflamed_2 was enriched in non-durable responders (NDRs). The CiberSortx results showed that the cell fraction of activated fibroblasts was six times higher in Inflamed_2 than in Inflamed_1. Validation with public gene expression datasets (GSE16879) revealed that the activated fibroblasts were enriched in NDRs over Next, we used DRs by 1.9 times pre-treatment and 7.5 times after treatment. Fibroblast activation protein (FAP) was overexpressed in the Inflamed_2 and was also overexpressed in the NDRs in both the RISK and GSE16879 datasets. The activation of fibroblasts may play a role in resistance to anti-TNF therapy. Characterizing fibroblasts in inflamed tissues at diagnosis may help to identify patients who are likely to respond to anti-TNF therapy.

Aromatic nitrogen scanning by ipso-selective nitrene internalization.

Nitrogen scanning in aryl fragments is a valuable aspect of the drug discovery process, but current strategies require time-intensive, parallel, bottom-up synthesis of each pyridyl isomer because of a lack of direct carbon-to-nitrogen (C-to-N) replacement reactions. We report a site-directable aryl C-to-N replacement reaction allowing unified access to various pyridine isomers through a nitrene-internalization process. In a two-step, one-pot procedure, aryl azides are first photochemically converted to 3H-azepines, which then undergo an oxidatively triggered C2-selective cheletropic carbon extrusion through a spirocyclic azanorcaradiene intermediate to afford the pyridine products. Because the ipso carbon of the aryl nitrene is excised from the molecule, the reaction proceeds regioselectively without perturbation of the remainder of the substrate. Applications are demonstrated in the abbreviated synthesis of a pyridyl derivative of estrone, as well as in a prototypical nitrogen scan.

Metabolic-associated fatty liver disease is associated with colorectal adenomas in young and older Korean adults.

BACKGROUND AND AIMS: Given that the majority of colorectal cancers (CRCs) develop from high-risk adenomas, identifying risk factors for high-risk adenomas is important. The relationship between metabolic dysfunction-associated fatty liver disease (MAFLD) and the risk of colorectal adenoma in young adults remains unclear. We aimed to evaluate this relationship in adults <50 (younger) and ≥50 (older) years of age. METHODS: This cross-sectional study included 184 792 Korean adults (80% <50 years of age) who all underwent liver ultrasound and colonoscopy. Participants were grouped into those with and without MAFLD and classified by adenoma presence into no adenoma, low-risk adenoma, or high-risk adenoma (defined as ≥3 adenomas, any ≥10 mm, or adenoma with high-grade dysplasia/villous features). RESULTS: The prevalence of low- and high-risk adenomas among young and older adults was 9.6% and 0.8% and 22.3% and 4.8%, respectively. MAFLD was associated with an increased prevalence of low- and high-risk adenomas in young and older adults. Young adults with MAFLD had a 1.30 (95% CIs 1.26-1.35) and 1.40 (1.23-1.59) times higher prevalence of low- and high-risk adenomas, respectively, compared to those without MAFLD. These associations were consistent even in lean adults (BMI < 23 kg/m2 ) and those without a family history of CRC. CONCLUSIONS: MAFLD is associated with an increased prevalence of low- and high-risk adenomas in Korean adults, regardless of age or obesity status. Whether reducing metabolic risk factors, such as MAFLD, reduces the risk of precancerous lesions and ultimately reduces the risk of early-onset CRC requires further investigation.

Potential Oral Microbial Markers for Differential Diagnosis of Crohn's Disease and Ulcerative Colitis Using Machine Learning Models.

Although gut microbiome dysbiosis has been associated with inflammatory bowel disease (IBD), the relationship between the oral microbiota and IBD remains poorly understood. This study aimed to identify unique microbiome patterns in saliva from IBD patients and explore potential oral microbial markers for differentiating Crohn's disease (CD) and ulcerative colitis (UC). A prospective cohort study recruited IBD patients (UC: n = 175, CD: n = 127) and healthy controls (HC: n = 100) to analyze their oral microbiota using 16S rRNA gene sequencing. Machine learning models (sparse partial least squares discriminant analysis (sPLS-DA)) were trained with the sequencing data to classify CD and UC. Taxonomic classification resulted in 4041 phylotypes using Kraken2 and the SILVA reference database. After quality filtering, 398 samples (UC: n = 175, CD: n = 124, HC: n = 99) and 2711 phylotypes were included. Alpha diversity analysis revealed significantly reduced richness in the microbiome of IBD patients compared to healthy controls. The sPLS-DA model achieved high accuracy (mean accuracy: 0.908, and AUC: 0.966) in distinguishing IBD vs. HC, as well as good accuracy (0.846) and AUC (0.923) in differentiating CD vs. UC. These findings highlight distinct oral microbiome patterns in IBD and provide insights into potential diagnostic markers.

Serum 25-Hydroxyvitamin D Levels and Risk of Colorectal Cancer: An Age-Stratified Analysis.

BACKGROUND & AIMS: The role of circulating 25-hydroxyvitamin D (25(OH)D) in the prevention of early-onset colorectal cancer (CRC) in young adults aged <50 years is uncertain. We evaluated the age-stratified associations (<50 vs ≥50 years) between circulating 25(OH)D levels and the risk of CRC in a large sample of Korean adults. METHODS: Our cohort study included 236,382 participants (mean age, 38.0 [standard deviation, 9.0] years) who underwent a comprehensive health examination, including measurement of serum 25(OH)D levels. Serum 25(OH)D levels were categorized as <10, 10 to 20, and ≥20 ng/mL. CRC, along with the histologic subtype, site, and invasiveness, was ascertained through linkage with the national cancer registry. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for incident CRC according to the serum 25(OH)D status, with adjustment for potential confounders. RESULTS: During the 1,393,741 person-years of follow-up (median, 6.5 years; interquartile range, 4.5-7.5 years), 341 participants developed CRC (incidence rate, 19.2 per 105 person-years). Among young individuals aged <50 years, serum 25(OH)D levels were inversely associated with the risk of incident CRC with HRs (95% CIs) of 0.61 (0.43-0.86) and 0.41 (0.27-0.63) for 25(OH)D 10 to 19 ng/mL and ≥20 ng/mL, respectively, with respect to the reference (<10 ng/mL) (P for trend <.001, time-dependent model). Significant associations were evident for adenocarcinoma, colon cancer, and invasive cancers. For those aged ≥50 years, associations were similar, although slightly attenuated compared with younger individuals. CONCLUSIONS: Serum 25(OH)D levels may have beneficial associations with the risk of developing CRC for both early-onset and late-onset disease.

Cryobiopsy: A Breakthrough Strategy for Clinical Utilization of Lung Cancer Organoids.

One major challenge associated with lung cancer organoids (LCOs) is their predominant derivation from surgical specimens of patients with early-stage lung cancer. However, patients with advanced lung cancer, who are in need of chemotherapy, often cannot undergo surgery. Therefore, there is an urgent need to successfully generate LCOs from biopsy specimens. Conventional lung biopsy techniques, such as transthoracic needle biopsy and forceps biopsy, only yield small amounts of lung tissue, resulting in a low success rate for culturing LCOs from biopsy samples. Furthermore, potential complications, like bleeding and pneumothorax, make it difficult to obtain sufficient tissue. Another critical issue is the overgrowth of normal lung cells in later passages of LCO culture, and the optimal culture conditions for LCOs are yet to be determined. To address these limitations, we attempted to create LCOs from cryobiopsy specimens obtained from patients with lung cancer (n = 113). Overall, the initial success rate of establishing LCOs from cryobiopsy samples was 40.7% (n = 46). Transbronchial cryobiopsy enables the retrieval of significantly larger amounts of lung tissue than bronchoscopic forceps biopsy. Additionally, cryobiopsy can be employed for peripheral lesions, and it is aided via radial endobronchial ultrasonography. This study significantly improved the success rate of LCO culture and demonstrated that the LCOs retained characteristics that resembled the primary tumors. Single-cell RNA sequencing confirmed high cancer cell purity in early passages of LCOs derived from patients with advanced lung cancer. Furthermore, the three-dimensional structure and intracellular components of LCOs were characterized using three-dimensional holotomography. Finally, drug screening was performed using a specialized micropillar culture system with cryobiopsy-derived LCOs. LCOs derived from cryobiopsy specimens offer a promising solution to the critical limitations of conventional LCOs. Cryobiopsy can be applied to patients with lung cancer at all stages, including those with peripheral lesions, and can provide sufficient cells for LCO generation. Therefore, we anticipate that cryobiopsy will serve as a breakthrough strategy for the clinical application of LCOs in all stages of lung cancer.

Rheological Characteristics of Starch-Based Biodegradable Blends.

Thermoplastic starch was blended with commercially available biodegradable polyesters of poly(butylene adipate-co-terephthalate) (PBAT) and poly(lactic acid) (PLA) for its improved performance and processability. The morphology and elemental composition of these biodegradable polymer blends were observed by scanning electron microscopy and energy dispersive X-ray spectroscopy, respectively, while their thermal properties were analyzed using thermogravimetric analysis and differential thermal calorimetry. For rheological analysis, the steady shear and dynamic oscillation tests of three samples at various temperatures were investigated using a rotational rheometer. All three samples exhibited significant shear thinning at all measured temperatures, and their shear viscosity behavior was plotted using the Carreau model. The frequency sweep tests showed that the thermoplastic starch sample exhibited a solid state at all temperatures tested, whereas both starch/PBAT and starch/PBAT/PLA blend samples exhibited viscoelastic liquid behavior after the melting temperature such that their loss modulus at low frequencies was greater than the storage modulus, and inversion occurred at high frequencies (storage modulus > loss modulus).

The Influence of Sex on Characteristics and Outcomes of Coronavirus-19 Patients: A Retrospective Cohort Study.

BACKGROUND: The influence of sex on the clinical characteristics and prognosis of coronavirus disease (COVID-19) patients is variable. This study aimed to evaluate COVID-19 management based on sex differences. METHODS: We retrospectively reviewed COVID-19 patients who were admitted to the tertiary hospital between January 2020 and March 2021. Logistic regression analysis was used to evaluate the factors associated with in-hospital mortality. RESULTS: During the study period, 584 patients were admitted to our hospital. Among them, 305 patients (52.2%) were female, and 279 patients (47.8%) were male. Males were younger than females, and frailty scale was lower in males than in females. Fever was more common in males, and there was no difference in other initial symptoms. Among the underlying comorbidities, chronic obstructive disease was more common in males, and there were no significant differences in other comorbidities. Moreover, treatment, severity, and outcome did not significantly differ between the groups. The risk factors for in-hospital mortality were age, high white blood cell count, and c-reactive protein level. CONCLUSIONS: We found no definite sex differences in the clinical characteristics and outcomes of COVID-19 patients. However, a better understanding of sex-dependent differences in COVID-19 patients could help in understanding and treating patients.

The first case report of Paragonimus westermani infection diagnosed by transbronchial lung cryobiopsy.

We report a case of pulmonary paragonimiasis diagnosed by transbronchial lung cryobiopsy (TBLC). TBLC is likely to be a superior method to transbronchial forceps biopsy because TBLC can get larger specimens, resulting in a higher chance of containing the eggs. A male patient aged 57 years presented with hemoptysis and dyspnea on exertion. His initial chest computed tomography scans showed a cavitary nodule with a peripheral ground-glass appearance, leading to a prescription of an oral antibiotic, with an initial assumption of pneumonia. A follow-up chest computed tomography, however, revealed an appearance of a new nodule adjacent to the original nodule. TBLC and transbronchial forceps biopsy were done to rule out lung cancer and eventually, the eggs of Paragonimus westermani were found using TBLC. Praziquantel was prescribed, showing improvements in symptoms and chest X-ray findings. TBLC has more potential to be utilized as a diagnostic method than transbronchial forceps biopsy because it has a better chance to confirm pulmonary paragonimiasis, which can be initially suspected as pulmonary tuberculosis or lung cancer.