Recent and sustainable advances in phytoremediation of heavy metals from wastewater using aquatic plant species: Green approach.

A key component in a nation's economic progress is industrialization, however, hazardous heavy metals that are detrimental to living things are typically present in the wastewater produced from various industries. Therefore, before wastewater is released into the environment, it must be treated to reduce the concentrations of the various heavy metals to maximum acceptable levels. Even though several biological, physical, and chemical remediation techniques are found to be efficient for the removal of heavy metals from wastewater, these techniques are costly and create more toxic secondary pollutants. However, phytoremediation is inexpensive, environmentally friendly, and simple to be applied as a green technology for heavy metal detoxification in wastewater. The present study provides a thorough comprehensive review of the mechanisms of phytoremediation, with an emphasis on the possible utilization of plant species for the treatment of wastewater containing heavy metals. We have discussed the concept, its applications, advantages, challenges, and independent variables that determine how successful and efficient phytoremediation could be in the decontamination of heavy metals from wastewater. Additionally, we argue that the standards for choosing aquatic plant species for target heavy metal removal ought to be taken into account, as they influence various aspects of phytoremediation efficiency. Following the comprehensive and critical analysis of relevant literature, aquatic plant species are promising for sustainable remediation of heavy metals. However, several knowledge gaps identified from the review need to be taken into consideration and possibly addressed. Therefore, the review provides perspectives that indicate research needs and future directions on the application of plant species in heavy metal remediation.

EP4 receptor agonist CAY10598 upregulates ROS-dependent Hsp90 cleavage in colorectal cancer cells.

Prostaglandin E2 (PGE2) interacts with four specific G protein-coupled receptors, namely EP1, EP2, EP3, and EP4, playing a pivotal role in determining the fate of cells. Our previous findings highlighted that stimulating the EP4 receptor with its agonist, CAY10598, triggers apoptosis in colon cancer HCT116 cells via the production of reactive oxygen species (ROS). This process also reduces the phosphorylation of the oncogenic protein JAK2 and leads to its degradation in these cells. In this study, our goal was to explore the pathways through which CAY10598 leads to JAK2 degradation. We focused on Hsp90, a heat shock protein family member known for its role as a molecular chaperone maintaining the stability of several key proteins including EGFR, MET, Akt, and JAK2. Our results show that CAY10598 decreases the levels of client proteins of Hsp90 in HCT116 cells, an effect reversible by pretreatment with the ROS scavenger N-acetyl cysteine (NAC) or the proteasome inhibitor MG132, indicating that the degradation is likely driven by ROS. Furthermore, we observed that CAY10598 cleaves both α and ß isoforms of Hsp90, the process inhibited by NAC. Inhibition of EP4 with the antagonist GW627368x not only prevented the degradation of Hsp90 client proteins but also the cleavage of Hsp90 itself in CAY10598-treated HCT116 cells. Additionally, CAY10598 suppressed the growth of HCT116 cells implanted in mice. Our findings reveal that CAY10598 induces apoptosis in cancer cells by a novel mechanism involving the ROS-dependent cleavage of Hsp90, thereby inhibiting the function of crucial Hsp90 client proteins.

Microbiological confirmation of tuberculous pleurisy with medical thoracoscopy: targeted pleural washing and pleural biopsy.

Background: Due to the pauci-bacillary nature of tuberculous (TB) pleurisy, clinical diagnosis is common, but microbiological confirmation is necessary to determine drug resistance. This study aimed to investigate the diagnostic yield of medical thoracoscopy (MT) for microbiological confirmation of TB pleurisy. Methods: Medical records of patients diagnosed as TB pleurisy with microbiological or histologic evidence who underwent MT between May 2015 and July 2023 at Incheon St. Mary's Hospital were retrospectively reviewed. Sensitivities of microbiological results [acid-fast bacilli (AFB) culture or TB-polymerase chain reaction (PCR)] of pre-MT pleural fluid and those of targeted pleural washing fluid and pleural tissues obtained during MT were compared. Difference in sensitivity was verified with McNemar's test. Results: A total of 72 patients were enrolled. With pre-MT pleural fluid, sensitivities of AFB culture and TB PCR were 5.6% (4/72) and 1.4% (1/72), respectively. With targeted pleural washing fluid, sensitivities of AFB culture and TB-PCR were 23.6% (17/72) and 12.5% (9/72), respectively. With pleural tissues, sensitivities of AFB culture and TB-PCR were 18.1% (13/72) and 40.3% (29/72), respectively. MT showed an additional 27.8% [95% confidence interval (95% CI): 14.2-40.1%, P<0.001] of sensitivity gain in AFB culture and 40.3% (95% CI: 25.7-52.5%, P<0.001) of sensitivity gain in TB-PCR. With pleural washing, additional 19.4% (95% CI: 6.8-31.6%, P=0.001) of sensitivity gain in microbiological confirmation was identified, whereas additional 37.5% (95% CI: 22.6-50.2%, P<0.001) of sensitivity gain was identified with pleural biopsy. Conclusions: With MT, 44.4% of additional sensitivity gain in microbiological confirmation of TB pleurisy was identified. This underscores the role of MT in the diagnosis of TB pleurisy.

Implications of GLI spirometry reference equations in Northeast Asian patients with COPD.

BACKGROUND: Accurate spirometry interpretation is critical in the diagnosis and management of chronic obstructive pulmonary disease (COPD). With increasing efforts for a unified approach by the Global Lung Function Initiative (GLI), this study evaluated the application of race-specific 2012-GLI and race-neutral 2022-GLI reference equations compared to Choi's reference equations, which is derived and widely used in South Korea, for spirometry interpretation in Northeast Asian patients with COPD. RESEARCH QUESTION: What are the effects of applying race-specific 2012-GLI, race-neutral 2022-GLI, and Choi's reference equations on the diagnosis, severity grade, and clinical outcome associations of COPD STUDY DESIGN AND METHODS: Serial spirometry data from the Korea COPD Subgroup Study (KOCOSS) consisting of 3,477 patients were utilized for re-analyses using 2012-GLI, 2022-GLI, and Choi's reference equations. The COPD diagnosis and severity categorization, associations with disease manifestations and health outcomes, and longitudinal trajectories of lung function were determined. RESULTS: Although there was strong concordance in COPD diagnosis comparing 2012-GLI, and 2022-GLI reference equations to Choi's reference equations, a notable portion of patients were reclassified to milder disease severity (17.0% and 23.4% for 2012-GLI and 2022-GLI reference equations, respectively). Relationships between FEV1 percent-predicted values calculated using 2012-GLI, 2022-GLI, and Choi's equations with clinical outcomes including dyspnea severity, exercise capacity, health-related quality of life, and frequency of exacerbations remain consistently significant. Similar annual decline rates of FEV1 and FVC percent-predicted were observed among the reference equations used, except for slower annual decline rate of FEV1 in Choi's equation compared to 2022-GLI race-neutral equation. INTERPRETATION: Application of GLI reference equations for spirometry interpretation in Northeast Asian patients with COPD has potential implications on disease severity grade for clinical management and trial participation, and maintains consistent significant relationships with key disease outcomes.

Superficial Anaplastic Lymphoma Kinase-Rearranged Myxoid Spindle Cell Neoplasm in the Buttock: A Case Report.

Anaplastic lymphoma kinase (ALK) is detected in both normal and oncological developmental tissues. Among ALK-related tumors, superficial ALK-rearranged myxoid spindle cell neoplasm (SAMS) is a rare, soft tissue tumor characterized by the immunophenotypical co-expression of CD34 and S100. Here, we describe a patient with this rare tumor and outline its clinical and radiological characteristics. A 28-year-old woman with diabetes, hypertension, and panic disorder presented with discomfort caused by a rubbery mass on the left buttock that had persisted for 10 years. Computed tomography revealed a multilobulated hypodense mass with small internal enhancing foci, posing challenges for the exact diagnosis of the lesion. The entire lesion was excised with clear resection margins. An 8.0 × 6.0 cm, well-circumscribed tumor with a lobular growth pattern was observed in the deep subcutaneous tissue. Light microscopy revealed epithelioid, ovoid, and spindle-shaped cells with a reticular cordlike pattern. Immunohistochemistry results were positive for S100, CD34, and vimentin. Break-apart fluorescence in situ hybridization assay results for ALK were also positive. These findings were consistent with those of SAMS. This case suggests that SAMS should be considered when identifying large nonspecific masses during clinical and imaging evaluation.

Multiparametric Characterization of Focal Cortical Dysplasia Using 3D MR Fingerprinting.

OBJECTIVES: To develop a multiparametric machine-learning (ML) framework using high-resolution 3 dimensional (3D) magnetic resonance (MR) fingerprinting (MRF) data for quantitative characterization of focal cortical dysplasia (FCD). MATERIALS: We included 119 subjects, 33 patients with focal epilepsy and histopathologically confirmed FCD, 60 age- and gender-matched healthy controls (HCs), and 26 disease controls (DCs). Subjects underwent whole-brain 3 Tesla MRF acquisition, the reconstruction of which generated T1 and T2 relaxometry maps. A 3D region of interest was manually created for each lesion, and z-score normalization using HC data was performed. We conducted 2D classification with ensemble models using MRF T1 and T2 mean and standard deviation from gray matter and white matter for FCD versus controls. Subtype classification additionally incorporated entropy and uniformity of MRF metrics, as well as morphometric features from the morphometric analysis program (MAP). We translated 2D results to individual probabilities using the percentage of slices above an adaptive threshold. These probabilities and clinical variables were input into a support vector machine for individual-level classification. Fivefold cross-validation was performed and performance metrics were reported using receiver-operating-characteristic-curve analyses. RESULTS: FCD versus HC classification yielded mean sensitivity, specificity, and accuracy of 0.945, 0.980, and 0.962, respectively; FCD versus DC classification achieved 0.918, 0.965, and 0.939. In comparison, visual review of the clinical magnetic resonance imaging (MRI) detected 48% (16/33) of the lesions by official radiology report. In the subgroup where both clinical MRI and MAP were negative, the MRF-ML models correctly distinguished FCD patients from HCs and DCs in 98.3% of cross-validation trials for the magnetic resonance imaging negative group and MAP negative group. Type II versus non-type-II classification exhibited mean sensitivity, specificity, and accuracy of 0.835, 0.823, and 0.83, respectively; type IIa versus IIb classification showed 0.85, 0.9, and 0.87. In comparison, the transmantle sign was present in 58% (7/12) of the IIb cases. INTERPRETATION: The MRF-ML framework presented in this study demonstrated strong efficacy in noninvasively classifying FCD from normal cortex and distinguishing FCD subtypes. ANN NEUROL 2024.

It is high time to discard a cut-off of 0.70 in the diagnosis of COPD.

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) has traditionally been diagnosed based on the criterion of an FEV1/FVC <0.70. However, this definition has limitations as it may only detect patients with later-stage disease, when pathologic changes have become irreversible. Consequently, it potentially omits individuals with early-stage disease, in whom the pathologic changes could be delayed or reversed. AREAS COVERED: This narrative review summarizes recent evidence regarding early-stage COPD, which may not fulfill the spirometric criteria but nonetheless exhibits features of COPD or is at risk of future COPD progression. EXPERT OPINION: A comprehensive approach, including symptoms assessment, various physiologic tests, and radiologic features, is required to diagnose COPD. This approach is necessary to identify currently underdiagnosed patients and to halt disease progression in at- risk patients.

Predicting Asthma Exacerbation Risk in the Adult South Korean Population Using Integrated Health Data and Machine Learning Models.

Asthma is a chronic inflammatory airway disease with significant burden; exacerbations can severely affect quality of life and healthcare costs. Advances in big data analysis and artificial intelligence have made it easier to predict future exacerbations more accurately. This study used an integrated dataset of Korean National Health Insurance, meteorological, air pollution, and viral data from national public databases to develop a model to predict asthma exacerbations on a daily basis in South Korea. We merged these sources and applied random forest, AdaBoost, XGBoost, and LightGBM machine learning models to compare their performances at predicting future exacerbations. Of the models, XGBoost (AUROC of 0.68 and accuracy of 0.96) and LightGBM (AUROC of 0.67 and accuracy of 0.96) were the most promising. Common important variables were the number of visits and exacerbations per year, and medical resource utilization, including the prescription of asthma medications. Comorbid diabetes, hypertension, gastroesophageal reflux, arthritis, metabolic syndrome, osteoporosis, and ischemic heart disease were also associated with elevated exacerbation risk. The models examined in this study highlight the importance of previous exacerbations, use of medical resources, and comorbidities in the prediction of future exacerbations in patients with asthma.

Development of a novel scoring system for glaucoma risk based on demographic and laboratory factors using ChatGPT-4.

We developed a scoring system for assessing glaucoma risk using demographic and laboratory factors by employing a no-code approach (automated coding) using ChatGPT-4. Comprehensive health checkup data were collected from the Korea National Health and Nutrition Examination Survey. Using ChatGPT-4, logistic regression was conducted to predict glaucoma without coding or manual numerical processes, and the scoring system was developed based on the odds ratios (ORs). ChatGPT-4 also facilitated the no-code creation of an easy-to-use risk calculator for glaucoma. The ORs for the high-risk groups were calculated to measure performance. ChatGPT-4 automatically developed a scoring system based on demographic and laboratory factors, and successfully implemented a risk calculator tool. The predictive ability of the scoring system was comparable to that of traditional machine learning approaches. For high-risk groups with 1-2, 3-4, and 5 + points, the calculated ORs for glaucoma were 1.87, 2.72, and 15.36 in the validation set, respectively, compared with the group with 0 or fewer points. This study presented a novel no-code approach for developing a glaucoma risk assessment tool using ChatGPT-4, highlighting its potential for democratizing advanced predictive analytics, making them readily available for clinical use in glaucoma detection.

Risk Factors for Rapid Cognitive Decline in Amyloid-Negative Individuals Without Cognitive Impairment or With Early-Stage Cognitive Loss in Screening Tests.

PURPOSE: Although rapid cognitive decline (RCD) is an important unfavorable prognostic factor, not much is known about it, especially in amyloid-negative individuals. The purpose of this study was to investigate risk factors for RCD in amyloid-negative individuals. PATIENTS AND METHODS: We retrospectively enrolled 741 individuals who were either cognitively unimpaired or had early-stage cognitive ability loss and who underwent 18F-florbetaben (FBB) (n = 402) or 18F-flutemetamol (FMM) (n = 339) PET/CT. Based on visual and semiquantitative (SUV ratio [SUVR]-based) analysis, the following amyloid-negative groups were established: visual-negative FBB (n = 232), visual-negative FMM (n = 161), SUVR-negative FBB (n = 104), and SUVR-negative FMM (n = 101). Univariable and multivariable logistic regression analyses were performed for RCD using 5 SUVRs, 5 cortical thicknesses, and 5 neuropsychological domains and clinico-demographic factors. RESULTS: In the amyloid-negative groups, a decline in language function was commonly identified as a significant risk factor for RCD (P = 0.0044 in the visual-negative FBB group, P = 0.0487 in the visual-negative FMM group, P = 0.0031 in the SUVR-negative FBB group, and P = 0.0030 in the SUVR-negative FMM group). In addition, declines in frontal/executive function, frontal SUVR, and parietal SUVR; a longer duration of education; and mild cognitive decline in the amyloid-negative groups were also significant risk factors for RCD. CONCLUSIONS: Even in amyloid-negative individuals without cognitive impairment or with early-stage cognitive ability loss, those with decreased language and frontal/executive functions on neuropsychological testing are at risk of progression to RCD.

Multimodal Imaging Approach for Tumor Treatment Response Evaluation in the Era of Immunotherapy.

ABSTRACT: Immunotherapy is likely the most remarkable advancement in lung cancer treatment during the past decade. Although immunotherapy provides substantial benefits, their therapeutic responses differ from those of conventional chemotherapy and targeted therapy, and some patients present unique immunotherapy response patterns that cannot be judged under the current measurement standards. Therefore, the response monitoring of immunotherapy can be challenging, such as the differentiation between real response and pseudo-response. This review outlines the various tumor response patterns to immunotherapy and discusses methods for quantifying computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (PET) in the field of lung cancer. Emerging technologies in magnetic resonance imaging (MRI) and non-FDG PET tracers are also explored. With immunotherapy responses, the role for imaging is essential in both anatomical radiological responses (CT/MRI) and molecular changes (PET imaging). Multiple aspects must be considered when assessing treatment responses using CT and PET. Finally, we introduce multimodal approaches that integrate imaging and nonimaging data, and we discuss future directions for the assessment and prediction of lung cancer responses to immunotherapy.

18F-Fluorodeoxyglucose Positron Emission Tomography-Based Risk Score Model for Prediction of Five-Year Survival Outcome after Curative Resection of Non-Small-Cell Lung Cancer.

The aim of our retrospective study is to develop and assess an imaging-based model utilizing 18F-FDG PET parameters for predicting the five-year survival in non-small-cell lung cancer (NSCLC) patients after curative surgery. A total of 361 NSCLC patients who underwent curative surgery were assigned to the training set (n = 253) and the test set (n = 108). The LASSO regression model was used to construct a PET-based risk score for predicting five-year survival. A hybrid model that combined the PET-based risk score and clinical variables was developed using multivariate logistic regression analysis. The predictive performance was determined by the area under the curve (AUC). The individual features with the best predictive performances were co-occurrence_contrast (AUC = 0.675) and SUL peak (AUC = 0.671). The PET-based risk score was identified as an independent predictor after adjusting for clinical variables (OR 5.231, 95% CI 1.987-6.932; p = 0.009). The hybrid model, which integrated clinical variables, significantly outperformed the PET-based risk score alone in predictive accuracy (AUC = 0.771 vs. 0.696, p = 0.022), a finding that was consistent in the test set. The PET-based risk score, especially when integrated with clinical variables, demonstrates good predictive ability for five-year survival in NSCLC patients following curative surgery.

RECIST 1.1, mRECIST, and Choi criteria for evaluating treatment response and survival outcomes in hepatocellular carcinoma patients treated with atezolizumab plus bevacizumab.

OBJECTIVES: We aimed to compare the early responder rates, defined as complete or partial responders, using response evaluation criteria in solid tumors (RECIST) 1.1, modified RECIST (mRECIST), and Choi criteria in advanced HCC patients treated with atezolizumab-bevacizumab (atezo-bev), and to correlate them with progression-free survival (PFS) and overall survival (OS). METHODS: This retrospective study included advanced HCC patients treated with ≥ 3 cycles of atezo-bev. Two reviewers assessed responses using RECIST 1.1, mRECIST, and Choi criteria at 1st follow-up imaging. Kaplan-Meier curves with log-rank tests evaluated and compared PFS and OS. Cox proportional hazard models identified survival outcome predictors. Kappa statistics assessed inter-reader agreement. RESULTS: We evaluated 77 patients (65 men; mean age, 62.8 ± 12.3 years). Choi's criteria revealed the highest early responders rate (53.2%), exceeding mRECIST (32.5-33.8%) and RECIST 1.1 (24.7-26.0%), with an excellent agreement in all criteria (κ, 0.85-0.95). Across criteria, a consistent number of patients progressed (23-26) and was associated with significantly poor OS (ps ≤ 0.049). Responders by any criteria showed longer PFS (ps ≤ 0.009), and 1-year OS (ps ≤ 0.01). Choi criteria linked to significantly better OS without landmark (p = 0.003), with 1-year OS rates at 76.9% for responders vs 38.1% for non-responders. Cox analysis identified responders by Choi criteria as a significant OS predictor. CONCLUSION: Choi criteria identified more early responders than RECIST 1.1 and mRECIST, significantly correlating with improved OS. Choi criteria could be considered as a formal response assessment criterion for the emerging atezo-bev systemic treatment. CLINICAL RELEVANCE STATEMENT: For atezo-bev treatment of advanced HCC, more comprehensive response criteria, such as Choi criteria, could be effective in identifying early responders and predicting survival outcomes along with RECIST 1.1 and mRECIST. KEY POINTS: Choi criteria identified a higher rate of early responders compared to mRECIST and RECIST1.1 following atezo-bev treatment. Responders by all criteria had longer PFS and 1-year OS, and only those by Choi criteria experienced longer OS without landmark time. Choi criteria, with RECIST 1.1 and mRECIST, is an effective response assessment tool for atezo-bev treatment.

Clinical Utility of Tumor-Naïve Presurgical Circulating Tumor DNA Detection in Early-Stage NSCLC.

OBJECTIVES: The use of tumor-informed circulating tumor DNA (ctDNA) testing in patients with early-stage disease before surgery is limited, mainly owing to restricted tissue access and extended turnaround times. This study aimed to evaluate the clinical value of a tumor-naïve, methylation-based cell-free DNA assay in a large cohort of patients with resected NSCLC. METHOD: We analyzed presurgical plasma samples from 895 patients with EGFR and anaplastic lymphoma kinase-wild-type, clinical stage I or II NSCLC. The ctDNA status was evaluated for its prognostic significance in relation to tumor volume, metabolic activity, histologic diagnosis, histologic subtypes, and clinical-to-pathologic TNM upstaging. RESULTS: Presurgical ctDNA detection was observed in 55 of 414 patients (13%) with clinical stage I lung adenocarcinoma (LUAD) and was associated with poor recurrence-free survival (2-year recurrence-free survival 69% versus 91%; log-rank p < 0.001), approaching that of clinical stage II LUAD. Presurgical ctDNA detection was not prognostic in patients with clinical stage II LUAD or non-LUAD. Within LUAD, tumor volume and positron emission tomography avidity interacted to predict presurgical ctDNA detection. Moreover, presurgical ctDNA detection was predictive of the postsurgical discovery of International Association for the Study of Lung Cancer grade 3 tumors (p < 0.001) and pathologic TNM upstaging (p < 0.001). Notably, presurgical ctDNA detection strongly correlated with higher programmed death-ligand 1 expression in tumors (positive rates 28% versus 55%, p < 0.001), identifying a subgroup likely to benefit from anti-programmed death-ligand 1 therapies. CONCLUSION: These findings support the integration of ctDNA testing into routine diagnostic workflows in early-stage NSCLC without the need for tumor tissue profiling. Furthermore, it is clinically useful in identifying patients at high risk who might benefit from innovative treatments, including neoadjuvant immune checkpoint inhibitors.

An Extensive Study of the Influence of Key Flow Variables on Printed Line Quality Outcomes during Aerosol Jet Printing Using Coupled Three-Dimensional Numerical Models.

A three-dimensional (3D) numerical model was developed to explore the intricate aerodynamic mechanisms associated with aerosol jet printing (AJP). The proposed approach integrates computational fluid dynamics and discrete phase modeling, offering a comprehensive understanding of the deposition mechanisms of the AJP process. Initially, numerical solutions of the governing equations were obtained under the assumptions of compressible and laminar flows, facilitating an analysis of certain key flow variables, in this case, the sheath gas flow rate and carrier gas flow rate across the fluid domain. Subsequently, incorporating a Lagrangian discrete phase model allowed a detailed examination of the droplet behavior after nozzle ejection, considering the influence of the Saffman lift force. Finally, experiments were performed to elucidate the influence of key flow variables on the printed width. Generally, the measured printed line morphology and corresponding line electrical performance exhibited close conformity with the numerical model, demonstrating that the proposed numerical model is important for making well-informed decisions during process optimization.

Prognostic Significance of 18 F-FDG PET/CT Radiomics in Patients With Resectable Pancreatic Ductal Adenocarcinoma Undergoing Curative Surgery.

PURPOSE: This study aimed to investigate the prognostic significance of PET/CT radiomics to predict overall survival (OS) in patients with resectable pancreatic ductal adenocarcinoma (PDAC). METHODS: We enrolled 627 patients with resectable PDAC who underwent preoperative 18 F-FDG PET/CT and subsequent curative surgery. Radiomics analysis of the PET/CT images for the primary tumor was performed using the Chang-Gung Image Texture Analysis toolbox. Radiomics features were subjected to least absolute shrinkage and selection operator (LASSO) regression to select the most valuable imaging features of OS. The prognostic significance was evaluated by Cox proportional hazards regression analysis. Conventional PET parameters and LASSO score were assessed as predictive factors for OS by time-dependent receiver operating characteristic curve analysis. RESULTS: During a mean follow-up of 28.8 months, 378 patients (60.3%) died. In the multivariable Cox regression analysis, tumor differentiation, resection margin status, tumor stage, and LASSO score were independent prognostic factors for OS (HR, 1.753, 1.669, 2.655, and 2.946; all P < 0.001, respectively). The time-dependent receiver operating characteristic curve analysis showed that the LASSO score had better predictive performance for OS than conventional PET parameters. CONCLUSIONS: The LASSO score using the 18 F-FDG PET/CT radiomics of the primary tumor was the independent prognostic factor for predicting OS in patients with resectable PDAC and may be helpful in determining therapeutic and follow-up plans for these patients.

Enhancing Identification of High-Risk cN0 Lung Adenocarcinoma Patients Using MRI-Based Radiomic Features.

Purpose: To develop an MRI-based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space (STAS), and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography-CT (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, SUVmax (maximum standardized uptake value) on FDG PET/CT, and the mean ADC value on DWI, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The MR-eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p<0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p<0.001), worse 4-year disease free survival (p<0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC 0.860 and 0.907, respectively). Conclusion: Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

Clinical significance of chronic bronchitis in different racial groups.

BACKGROUNDS: Limited data are available on racial differences in the clinical features of chronic bronchitis (CB) patients with chronic obstructive pulmonary disease (COPD). In this study, we aimed to compare clinical features among CB patients of different races. We also analyzed the clinical significance of CB, defined classically and based on the COPD Assessment Test (CAT), to validate the CAT-based definition. METHODS: We analyzed patient data extracted from the Korean COPD Subgroup Study (KOCOSS) cohort (2012-2021) and US Genetic Epidemiology of COPD (COPDGene) study (2008-2011). We compared clinical characteristics among CB and non-CB patients of three different races using two CB definitions. RESULTS: In this study, 3,462 patients were non-Hispanic white (NHW), 1,018 were African American (AA), and 1,793 were Asian. The proportions of NHW, AA, and Asian patients with CB according to the classic definition were 27.4%, 20.9%, and 10.7%, compared with 25.2%, 30.9%, and 23.0% according to the CAT-based definition, respectively. The risk of CB prevalence was highest in NHW and lowest in Asian COPD patients. Among all races, CB patients were more likely to be current smokers, have worse respiratory symptoms and poorer health-related quality of life (HrQoL), and to have decreased lung function and exercise capacity. Most of these characteristics showed similar associations with the outcomes between the two definitions of CB. A binominal regression model revealed that CB patients of all races had an increased risk of future exacerbations according to both CB definitions, except for Asian patients with classically defined CB. CONCLUSIONS: The presence of CB was associated with worse respiratory symptoms, HrQoL, exercise capacity and lung function, and more exacerbations, regardless of race or CB definition. The CAT-based definition may be more useful for assessing the risk of future exacerbations in Asian COPD patients.

U-Shape Pillar Strip for 3D Cell-Lumped Organoid Model (3D-COM) Mimicking Lung Cancer Hypoxia Conditions in High-Throughput Screening (HTS).

Hypoxia is a representative tumor characteristic associated with malignant progression in clinical patients. Engineered in vitro models have led to significant advances in cancer research, allowing for the investigation of cells in physiological environments and the study of disease mechanisms and processes with enhanced relevance. In this study, we propose a U-shape pillar strip for a 3D cell-lumped organoid model (3D-COM) to study the effects of hypoxia on lung cancer in a high-throughput manner. We developed a U-pillar strip that facilitates the aggregation of PDCs mixed with an extracellular matrix to make the 3D-COM in 384-plate array form. The response to three hypoxia-activated prodrugs was higher in the 3D-COM than in the 2D culture model. The protein expression of hypoxia-inducible factor 1 alpha (HIF-1α) and HIF-2α, which are markers of hypoxia, was also higher in the 3D-COM than in the 2D culture. The results show that 3D-COM better recapitulated the hypoxic conditions of lung cancer tumors than the 2D culture. Therefore, the U-shape pillar strip for 3D-COM is a good tool to study the effects of hypoxia on lung cancer in a high-throughput manner, which can efficiently develop new drugs targeting hypoxic tumors.