Endobronchial Ultrasound Using Guide Sheath-Guided Transbronchial Lung Biopsy in Ground-Glass Opacity Pulmonary Lesions without Fluoroscopic Guidance.

Diagnosing ground-glass opacity (GGO) pulmonary lesions poses challenges. This study evaluates the utility of radial probe endobronchial ultrasound-guided transbronchial lung biopsy (RP-EBUS-TBLB) in diagnosing GGO pulmonary lesions. A total of 1651 RP-EBUS procedures were performed during the study period. This study analyzed 115 GGO lesions. The EBUS visualization yield was 80.1%. Of 115 lesions, 69 (60%) were successfully diagnosed. The average size of diagnosed lesions was significantly larger than that of undiagnosed lesions (21.9 ± 7.3 vs. 17.1 ± 6.6 mm, p < 0.001). Diagnostic yield varied by lesion size: 50.0% for lesions <20 mm, 65.1% for 20-30 mm lesions, and 85.7% for lesions >30 mm. The mixed blizzard sign on EBUS appeared in 60.6% of mixed GGO lesions, with no cases in pure GGO lesions. Multivariable analyses showed that lesion size (odds ratio [OR], 1.10; 95% confidence interval [CI], 1.00-1.16; p < 0.001) and mixed blizzard sign on EBUS (OR, 20.92; CI, 7.50-58.31; p < 0.001) were significantly associated with diagnostic success. Pneumothorax and hemoptysis occurred in 1.7% and 2.6% of patients, respectively. RP-EBUS-TBLB without fluoroscopic guidance is a viable diagnostic approach for GGO pulmonary lesions with acceptable complications.

Slowly Growing Pulmonary Glandular Papilloma with Air Bronchogram: A Case Report.

Pulmonary glandular papilloma is a rare benign neoplasm that has not been studied extensively. This neoplasm presents as a solid nodule, consolidation, or mass, with or without atelectasis, and assessing the correlation between these findings and the risk of malignancy is challenging. A 60-year-old woman presented a solitary pulmonary nodule on screening chest radiography and chest computed tomography (CT). During the subsequent 2-year follow-up, CT showed a progressive increase in nodule size and an air bronchogram, suggesting malignancy. The patient underwent a right upper lobectomy, and the final diagnosis was glandular papilloma. Teaching point: Pulmonary glandular papilloma with growth and an air bronchogram.

Central venous catheter tip colonization and associated bloodstream infection in patients with severe burns under routine catheter changing.

BACKGROUND: Although routine changing of central venous catheters (CVCs) is commonly performed in patients with severe burns, information on pathogen colonization of the CVC tip and associated bloodstream infections (BSIs) is limited in those patients. METHODS: The medical records of 214 patients with severe burns who underwent routine CVC changing at 7-day intervals and their results of 686 pairs of CVC tips and concurrent blood cultures were retrospectively reviewed to evaluate the CVC colonization rate and associated BSI pathogens. RESULTS: Of the 686 CVCs, 137 (20.0%) were colonized by pathogens, and 81 (59.1%) of them had BSIs caused by the same pathogen. Nonflame burn (P = .002), total body surface area burn ≥30% (P = .004), femoral catheterization (P = .001), CVC changing during pre-existing BSI (P < .001), and renal replacement therapy (P = .017) were associated with catheter-related BSI in the multivariate analysis. Most BSIs were caused by Gram-negative bacteria (most commonly Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa). CONCLUSIONS: The CVC colonization rate in patients with severe burns and routine CVC changing was not high. Lengthening the CVC duration might be attempted in patients at a lower risk of catheter-related BSI although further prospective studies are necessary.

Sixty-four-fold data reduction of chest radiographs using a super-resolution convolutional neural network.

OBJECTIVES: To develop and validate a super-resolution (SR) algorithm generating clinically feasible chest radiographs from 64-fold reduced data. METHODS: An SR convolutional neural network was trained to produce original-resolution images (output) from 64-fold reduced images (input) using 128 × 128 patches (n = 127 030). For validation, 112 radiographs-including those with pneumothorax (n = 17), nodules (n = 20), consolidations (n = 18), and ground-glass opacity (GGO; n = 16)-were collected. Three image sets were prepared: the original images and those reconstructed using SR and conventional linear interpolation (LI) using 64-fold reduced data. The mean-squared error (MSE) was calculated to measure similarity between the reconstructed and original images, and image noise was quantified. Three thoracic radiologists evaluated the quality of each image and decided whether any abnormalities were present. RESULTS: The SR-images were more similar to the original images than the LI-reconstructed images (MSE: 9269 ± 1015 vs. 9429 ± 1057; P = .02). The SR-images showed lower measured noise and scored better noise level by three radiologists than both original and LI-reconstructed images (Ps < .01). The radiologists' pooled sensitivity with the SR-reconstructed images was not significantly different compared with the original images for detecting pneumothorax (SR vs. original, 90.2% [46/51] vs. 96.1% [49/51]; P = .19), nodule (90.0% [54/60] vs. 85.0% [51/60]; P = .26), consolidation (100% [54/54] vs. 96.3% [52/54]; P = .50), and GGO (91.7% [44/48] vs. 95.8% [46/48]; P = .69). CONCLUSIONS: SR-reconstructed chest radiographs using 64-fold reduced data showed a lower noise level than the original images, with equivalent sensitivity for detecting major abnormalities. ADVANCES IN KNOWLEDGE: This is the first study applying super-resolution in data reduction of chest radiographs.

Pioneering predictions of AKI and AKIN severity in burn patients: a comprehensive CBC approach.

This study aims to evaluate the utility of complete blood count (CBC) markers, in conjunction with the acute kidney injury network (AKIN) criteria, for the early detection, severity assessment, and prediction of mortality outcomes of acute kidney injury (AKI) in burn patients. The research seeks to fill existing gaps in knowledge and validate the cost-effectiveness of using CBC as a routine diagnostic tool for better management of AKI. The study was conducted at Hangang Sacred Heart Hospital. We performed a large-scale retrospective analysis of 2758 adult patients admitted to the burn intensive care unit over a 12-year period. Among these patients, AKI occurred in 1554 patients (56.3%). Based on the AKIN stage classification, 794 patients (28.8%) were categorized as AKIN 1, 494 patients (17.9%) as AKIN 2, and 266 patients (9.6%) as AKIN 3. We defined several ratio markers, including the Neutrophil-to-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR), Monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), and various mean platelet volume (MPV) ratios. Our statistical analyses, conducted using the R programming language, revealed significant correlations between these markers and AKI severity. The AUC values for neutrophil count and WBC count were 0.790 and 0.793, respectively, followed by immature granulocyte count with an AUC of 0.727. For red blood cell (RBC)-related parameters, the AUC values for hematocrit (Hct), hemoglobin (Hb), and RBC count were 0.725, 0.713, and 0.713, respectively. Among the platelet-related parameters, only platelet distribution width (PDW) had an AUC of 0.677. Among the ratio markers, the NLR had the highest AUC at 0.772, followed by MPVNR and SII with AUC values of 0.700 and 0.680, respectively. The findings underscore the potential of CBC as an economical, routine test for AKI, thereby paving the way for enhanced patient outcomes. Our study suggests the utility of routine CBC tests, specifically WBC count and PLR, for predicting AKI and platelet, MPV, and NLR for mortality assessment in burn patients. These findings underscore the potential of easily accessible CBC tests in enhancing AKI management. However, further multicenter studies are needed for validation.

Big data insights into the diagnostic values of CBC parameters for sepsis and septic shock in burn patients: a retrospective study.

Sepsis and septic shock are prevalent and life-threatening complications in burn patients. Despite their severity, existing diagnostic methods are limited. This study aims to evaluate the efficacy of Complete Blood Count (CBC) and CBC ratio markers in diagnosing sepsis and septic shock, and in predicting mortality among burn patients. A cohort of 2757 burn patients was examined to ascertain the correlation between various CBC parameters, their ratios, and the incidence of sepsis and related mortality. Key markers analyzed included Red Cell Distribution Width (RDW), Mean Platelet Volume (MPV), Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), and Mean Platelet Volume-to-Platelet Ratio (MPVPR). Our findings indicate that 65.5% of the patients developed sepsis, and 24.3% succumbed to their conditions. The CBC parameters RDW, MPV, NLR, MPVPR, and MPV-to-Lymphocyte Ratio (MPVLR) were significantly associated with sepsis and mortality. These markers showed considerable temporal variation and yielded an Area Under the Curve (AUC) of over 0.65 in an unadjusted Generalized Estimating Equations (GEE) model. This study underscores the potential of RDW, MPV, NLR, MPVPR, and MPVLR as vital prognostic tools for diagnosing sepsis, septic shock, and predicting mortality in burn patients. Although based on a single-center dataset, our results contribute to the enhancement of sepsis management by facilitating earlier, more precise diagnosis and treatment strategies. Further multi-center research is necessary to confirm these findings and broaden their applicability, establishing a solid base for future explorations in this crucial field.

Usual Interstitial Pneumonia: Associations With Complications After Percutaneous Transthoracic Needle Lung Biopsy.

BACKGROUND. Changes in lung parenchyma elasticity in usual interstitial pneumonia (UIP) may increase the risk for complications after percutaneous transthoracic needle biopsy (PTNB) of the lung. OBJECTIVE. The purpose of this article was to investigate the association of UIP findings on CT with complications after PTNB, including pneumothorax, pneumothorax requiring chest tube insertion, and hemoptysis. METHODS. This retrospective single-center study included 4187 patients (mean age, 63.8 ± 11.9 [SD] years; 2513 men, 1674 women) who underwent PTNB between January 2010 and December 2015. Patients were categorized into a UIP group and non-UIP group by review of preprocedural CT. In the UIP group, procedural CT images were reviewed to assess for traversal of UIP findings by needle. Multivariable logistic regression analyses were performed to identify associations between the UIP group and needle traversal with postbiopsy complications, controlling for a range of patient, lesion, and procedural characteristics. RESULTS. The UIP and non-UIP groups included 148 and 4039 patients, respectively; in the UIP group, traversal of UIP findings by needle was observed in 53 patients and not observed in 95 patients. The UIP group, in comparison with the non-UIP group, had a higher frequency of pneumothorax (35.1% vs 17.9%, p < .001) and pneumothorax requiring chest tube placement (6.1% vs 1.5%, p = .001) and lower frequency of hemoptysis (2.0% vs 6.1%, p = .03). In multivariable analyses, the UIP group with traversal of UIP findings by needle, relative to the non-UIP group, showed independent associations with pneumothorax (OR, 5.25; 95% CI, 2.94-9.37; p < .001) and pneumothorax requiring chest tube placement (OR, 9.55; 95% CI, 3.74-24.38; p < .001). The UIP group without traversal of UIP findings by needle, relative to the non-UIP group, was not independently associated with pneumothorax (OR, 1.18; 95% CI, 0.71-1.97; p = .51) or pneumothorax requiring chest tube placement (OR, 1.08; 95% CI, 0.25-4.72; p = .92). The UIP group, with or without traversal of UIP findings by needle, was not independently associated with hemoptysis. No patient experienced air embolism or procedure-related death. CONCLUSION. Needle traversal of UIP findings is a risk factor for pneumothorax and pneumothorax requiring chest tube placement after PTNB. CLINICAL IMPACT. When performing PTNB in patients with UIP, radiologists should plan a needle trajectory that does not traverse UIP findings, when possible.

The clinical differentiation of blood culture-positive and -negative sepsis in burn patients: a retrospective cohort study.

Background: Sepsis is a potentially life-threatening condition that occurs when the body's response to infection leads to widespread inflammation and tissue damage. Negative cultures can make it difficult for clinicians to make a diagnosis and may raise questions about the validity of the definition of sepsis. In addition, the clinical distinctions between burn patients with blood culture-positive and -negative sepsis are also poorly understood. Therefore, this study aimed to examine the clinical differences between blood culture-positive and -negative sepsis in burn patients in order to improve the understanding of the pathophysiology and epidemiology of sepsis in this population. Methods: This study had a retrospective design, and the participants were adults aged ≥18 years. Patients diagnosed with sepsis were divided into two groups based on their blood culture results within 1 week of sepsis diagnosis. Results: We enrolled 1643 patients admitted to our institution's burn intensive care unit between January 2010 and December 2021. pH, platelet count, bicarbonate and haematocrit were significant in both the positive and negative groups. However, lymphocyte, red cell distribution width and blood urea nitrogen were significant only in the positive group, whereas lactate dehydrogenase was significant only in the negative group. Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumonia are common gram-negative bacterial species, and Staphylococcus aureus and Staphylococcus epidermidis are common gram-positive bacterial species seen in burn patients with positive blood cultures. Carbapenem resistance was found to be associated with an unfavourable prognosis in gram-negative bacteria, with the exception of P. aeruginosa. Conclusions: pH, platelet count, bicarbonate and haematocrit were routine biomarkers that demonstrated statistical significance in both groups. Lactate dehydrogenase was significant in the blood-negative group, while red cell distribution width, blood urea nitrogen and lymphocyte count were significant in the positive group. Furthermore, the most common causes of sepsis are gram-negative bacteria, including A. baumannii, K. pneumoniae and P. aeruginosa. Additionally, resistance to carbapenems is associated with unfavourable outcomes.

75% radiation dose reduction using deep learning reconstruction on low-dose chest CT.

OBJECTIVE: Few studies have explored the clinical feasibility of using deep-learning reconstruction to reduce the radiation dose of CT. We aimed to compare the image quality and lung nodule detectability between chest CT using a quarter of the low dose (QLD) reconstructed with vendor-agnostic deep-learning image reconstruction (DLIR) and conventional low-dose (LD) CT reconstructed with iterative reconstruction (IR). MATERIALS AND METHODS: We retrospectively collected 100 patients (median age, 61 years [IQR, 53-70 years]) who received LDCT using a dual-source scanner, where total radiation was split into a 1:3 ratio. QLD CT was generated using a quarter dose and reconstructed with DLIR (QLD-DLIR), while LDCT images were generated using a full dose and reconstructed with IR (LD-IR). Three thoracic radiologists reviewed subjective noise, spatial resolution, and overall image quality, and image noise was measured in five areas. The radiologists were also asked to detect all Lung-RADS category 3 or 4 nodules, and their performance was evaluated using area under the jackknife free-response receiver operating characteristic curve (AUFROC). RESULTS: The median effective dose was 0.16 (IQR, 0.14-0.18) mSv for QLD CT and 0.65 (IQR, 0.57-0.71) mSv for LDCT. The radiologists' evaluations showed no significant differences in subjective noise (QLD-DLIR vs. LD-IR, lung-window setting; 3.23 ± 0.19 vs. 3.27 ± 0.22; P = .11), spatial resolution (3.14 ± 0.28 vs. 3.16 ± 0.27; P = .12), and overall image quality (3.14 ± 0.21 vs. 3.17 ± 0.17; P = .15). QLD-DLIR demonstrated lower measured noise than LD-IR in most areas (P < .001 for all). No significant difference was found between QLD-DLIR and LD-IR for the sensitivity (76.4% vs. 72.2%; P = .35) or the AUFROCs (0.77 vs. 0.78; P = .68) in detecting Lung-RADS category 3 or 4 nodules. Under a noninferiority limit of -0.1, QLD-DLIR showed noninferior detection performance (95% CI for AUFROC difference, -0.04 to 0.06). CONCLUSION: QLD-DLIR images showed comparable image quality and noninferior nodule detectability relative to LD-IR images.

The Performance of a Deep Learning-Based Automatic Measurement Model for Measuring the Cardiothoracic Ratio on Chest Radiographs.

OBJECTIVE: Prior studies on models based on deep learning (DL) and measuring the cardiothoracic ratio (CTR) on chest radiographs have lacked rigorous agreement analyses with radiologists or reader tests. We validated the performance of a commercially available DL-based CTR measurement model with various thoracic pathologies, and performed agreement analyses with thoracic radiologists and reader tests using a probabilistic-based reference. MATERIALS AND METHODS: This study included 160 posteroanterior view chest radiographs (no lung or pleural abnormalities, pneumothorax, pleural effusion, consolidation, and n = 40 in each category) to externally test a DL-based CTR measurement model. To assess the agreement between the model and experts, intraclass or interclass correlation coefficients (ICCs) were compared between the model and two thoracic radiologists. In the reader tests with a probabilistic-based reference standard (Dawid-Skene consensus), we compared diagnostic measures-including sensitivity and negative predictive value (NPV)-for cardiomegaly between the model and five other radiologists using the non-inferiority test. RESULTS: For the 160 chest radiographs, the model measured a median CTR of 0.521 (interquartile range, 0.446-0.59) and a mean CTR of 0.522 ± 0.095. The ICC between the two thoracic radiologists and between the model and two thoracic radiologists was not significantly different (0.972 versus 0.959, p = 0.192), even across various pathologies (all p-values > 0.05). The model showed non-inferior diagnostic performance, including sensitivity (96.3% versus 97.8%) and NPV (95.6% versus 97.4%) (p < 0.001 in both), compared with the radiologists for all 160 chest radiographs. However, it showed inferior sensitivity in chest radiographs with consolidation (95.5% versus 99.9%; p = 0.082) and NPV in chest radiographs with pleural effusion (92.9% versus 94.6%; p = 0.079) and consolidation (94.1% versus 98.7%; p = 0.173). CONCLUSION: While the sensitivity and NPV of this model for diagnosing cardiomegaly in chest radiographs with consolidation or pleural effusion were not as high as those of the radiologists, it demonstrated good agreement with the thoracic radiologists in measuring the CTR across various pathologies.

Tracking longitudinal biomarkers in burn patients with sepsis and acute kidney injury: an unsupervised clustering approach.

BACKGROUND: Sepsis is a grave medical disorder characterized by a systemic inflammatory response to infection. Furthermore, it is a leading cause of morbidity and mortality, especially in hospitalized patients. Acute kidney injury (AKI) is a common complication of sepsis and is associated with increased morbidity and mortality. Patients with burns are particularly vulnerable to developing sepsis and AKI due to the extensive tissue damage and immune suppression resulting from burn injury. In this study, unsupervised clustering algorithms were used to track longitudinal biomarkers in patients with burns and assess their impact on mortality. METHODS: This retrospective study included adult patients with burns aged ≥ 18 years, who were admitted to the burn intensive care unit of Hallym University and Hangang Sacred Heart Hospital between July 2010 and December 2021. The patients were divided into two subgroups: those with sepsis (538 patients) and those without sepsis (826 patients). The longitudinal biomarkers were grouped into three clusters using the k-means clustering algorithm. Each cluster was assigned a letter from A to C according to its mortality rate. RESULTS: The odds ratio (OR) of pH was 9.992 in the positive group and 31.745 in the negative group in cluster C. The OR for lactate dehydrogenase (LD) was 3.704 in the positive group and 6.631 in the negative group in cluster C. The OR for creatinine was 2.784 in the positive group and 8.796 in the negative group in cluster C. The OR for blood urea nitrogen (BUN) in the negative group was 0.348, indicating a negative predictor of mortality. Regarding the application of Continuous Renal Replacement Therapy (CRRT) and ventilation, ventilation was significant in both groups. In contrast, CRRT application was not significant in the sepsis-positive group. Furthermore, it was not selected as a variable in the negative group. CONCLUSIONS: The pH, LD, and creatinine were significant in both groups, while lactate and platelets were significant in the sepsis-positive group. In addition, albumin, glucose, and BUN were significant in the sepsis-negative group. Continuous renal replacement therapy was not significant in either group. However, the use of a ventilator was associated with poor prognosis.

Evaluating clinical heterogeneity and predicting mortality in severely burned patients through unsupervised clustering and latent class analysis.

Burn injuries often result in a high level of clinical heterogeneity and poor prognosis in patients with severe burns. Clustering algorithms, which are unsupervised methods that can identify groups with similar trajectories in patients with heterogeneous diseases, can provide insights into the mechanisms of the disease pathogenesis. This study aimed to analyze routinely collected biomarkers to understand their mortality prediction power, identify the clinical meanings or subtypes, and inform treatment decisions to improve the outcomes of patients with burns. This retrospective cohort study included patients aged ≥ 18 years who were admitted between January 2010 and December 2021. The patients were divided into four subgroups based on the time period of their admission: week 1, 2, 3, and 4. The study revealed that 22 biomarkers were evaluated, and the red blood cell distribution width, bicarbonate level, pH, platelets, and lymphocytes were significantly associated with the mortality risk. Latent class analysis further demonstrated that the pH, platelets, lymphocytes, lactate, and albumin demonstrated the lowest levels in the cluster with the highest risk of mortality, with the lowest levels of pH and lactate being particularly noteworthy in week 1 of the study. During the week 2, the pH and lymphocyte levels were demonstrated to be significant predictors of the mortality risk, whereas the lymphocyte and platelet counts were meaningful predictors in week 3. During week 4, pH, platelet count, and albumin level were important predictors of mortality risk. Analysis of routinely collected biomarkers using clustering algorithms and latent class analysis can provide valuable insights into the heterogeneity of burn injuries and improve the ability to predict disease progression and mortality. Our findings suggest that lactate levels are a better indicator of cellular hypoxia in the early stages of burn shock, whereas platelet and lymphocyte levels are more indicative of infections such as sepsis. Albumin levels are considered a better indicator of reduced nutritional loss with decrease in unhealed burn wounds; however, the pH levels reflect the overall condition of the patient throughout the study period. These findings can be used to inform treatment decisions and improve the outcomes of burn patients.

Distal Ventriculoperitoneal Shunt Catheter Migration into the Pulmonary Vasculature and Cardiac Chamber: A Case Report.

Ventriculoperitoneal shunting is the most common neurosurgical procedure for treatment of hydrocephalus. Shunt-related complications are relatively common and associated with a high rate of shunt revision. However, migration of the distal ventriculoperitoneal shunt, especially into the cardiac and intravascular regions, has rarely been reported. Awareness of this rare but potentially hazardous complication is important owing to its significant morbidity, which can be prevented by prompt management. Here, we introduce a case of a 23-year-old male with migration of the distal shunt catheter through the left internal jugular vein into the cardiac chamber and both pulmonary arteries, which occurred 2 months after receiving ventriculoperitoneal shunting. Furthermore, we discuss the possible mechanisms and management of this condition.

The genetic structure and demographic history of Zabelia tyaihyonii, endemic to Korean limestone karst forests, based on genome-wide SNP markers.

Similar to the global phenomenon, many plant species endemic to Korean limestone karst forests are at risk of extinction due to human intervention. Zabelia tyaihyonii is a familiar shrub, called "Hardy abelia" and "Fragrant abelia" growing in the karst forests of Korea, where it is one of the most threatened species. We investigated the genetic structure and demographic history of Z. tyaihyonii, which allow us to develop appropriate conservation and management strategies. The genetic structure was evaluated using a total of 187 samples from 14 populations, covering the entire distribution of Z. tyaihyonii in South Korea. We utilized 254 and 1753 SNP loci obtained via MIG-seq (Multiplexed ISSR Genotyping by sequencing) for structure and demographic analyses, respectively. The population demographic modeling was performed with site frequency spectrum. To gain further historical insights, we also employed ENM (Ecological Niche Modeling). We found two distinct clusters (CLI and CLII) of ancient origin (ca. 490 ka). Despite CLII experiencing a more severe bottleneck, both clusters showed similar levels of genetic diversity, indicating mutual historical gene flow. Their historical distribution range seems to have changed very little. We proposed a historical distribution scenario for Z. tyaihyonii, taking into account its intrinsic factors, and emphasized a more complex response to Quaternary climate change beyond simple allopatric speciation models. These findings provide valuable insights for conservation and management strategies for Z. tyaihyonii.

Nontuberculous Mycobacterial Infection Mimicking Lung Cancer in A Patient with Usual Interstitial Pneumonia Pattern Interstitial Lung Disease: A Case Report.

BACKGROUND: It has been reported that structure damage in the parenchymal lung disease such as idiopathic pulmonary fibrosis (IPF) is associated with high susceptibility to nontuberculous mycobacterial (NTM) infection. Radiologic features of NTM lung disease in destructive lung parenchyma can be atypical, which can cause confusion with other diseases including malignancy. Prompt and accurate identification of newly developed lesions in the follow-up computed tomography (CT) of IPF patients is challenging but crucial. CASE REPORT: We reported a case of an NTM infection in a patient with IPF, manifested as a mass-like consolidation with cavitation on chest CT, mimicking lung cancer. CONCLUSION: Being aware of the unusual radiologic features of NTM lung disease in IPF patients can be useful in the differential diagnosis of newly detected lesions.

Phytochemical profiling of Symplocos tanakana Nakai and S. sawafutagi Nagam. leaf and identification of their antioxidant and anti-diabetic potential.

Symplocos sp. contains various phytochemicals and is used as a folk remedy for treatment of diseases such as enteritis, malaria, and leprosy. In this study, we discovered that 70% ethanol extracts of Symplocos sawafutagi Nagam. and S. tanakana Nakai leaves have antioxidant and anti-diabetic effects. The components in the extracts were profiled using high-performance liquid chromatography coupled to electrospray ionization and quadrupole time-of-flight mass spectrometry; quercetin-3-O-(6''-O-galloyl)-ß-d-galactopyranoside (6) and tellimagrandin II (7) were the main phenolic compounds. They acted as strong antioxidants with excellent radical scavenging activity and as inhibitors of non-enzymatic advanced glycation end-products (AGEs) formation. Mass fragmentation analysis demonstrated that compounds 6 and 7 could form mono- or di-methylglyoxal adducts via reaction with methylglyoxal, which is a reactive carbonyl intermediate and an important precursor of AGEs. In addition, compound 7 effectively inhibited the binding between AGE2 and receptor for AGEs as well as the activity of α-glucosidase. Enzyme kinetic study revealed that compound 7 acts as a competitive inhibitor of α-glucosidase, through interaction with the active site of the enzyme. Therefore, compounds 6 and 7, the major constituents of S. sawafutagi and S. tanakana leaves, are promising for developing drugs for preventing or treating diseases caused by aging and excessive sugar consumption.

Identification of Active Pulmonary Tuberculosis Among Patients With Positive Interferon-Gamma Release Assay Results: Value of a Deep Learning-based Computer-aided Detection System in Different Scenarios of Implementation.

PURPOSE: To evaluate the accuracy of a deep learning-based computer-aided detection (CAD) system in identifying active pulmonary tuberculosis on chest radiographs (CRs) of patients with positive interferon-gamma release assay (IGRA) results in different scenarios of clinical implementation. MATERIALS AND METHODS: We collected the CRs of consecutive patients with positive IGRA results. Findings of active pulmonary tuberculosis on CRs were independently evaluated by the CAD and a thoracic radiologist, followed by interpretation using the CAD. Sensitivity and specificity were evaluated in different scenarios: (a) radiologists' interpretation, (b) radiologists' CAD-assisted interpretation, and (c) CAD-based prescreening (radiologists' interpretation for positive CAD results only). We conducted a reader test to compare the accuracy of the CAD with those of 5 radiologists. RESULTS: Among 1780 patients (men, 53.8%; median age, 56 y), 44 (2.5%) were diagnosed with active pulmonary tuberculosis. The CAD-assisted interpretation exhibited a higher sensitivity (81.8% vs. 72.7%; P =0.046) but lower specificity than the radiologists' interpretation (84.1% vs. 85.7%; P <0.001). The CAD-based prescreening exhibited a higher specificity than the radiologists' interpretation (88.8% vs. 85.7%; P <0.001) at the same sensitivity, with a workload reduction of 85.2% (1780 to 263). In the reader test, the CAD exhibited a higher sensitivity than radiologists (72.7% vs. 59.5%; P =0.005) at the same specificity (88.0%), and CAD-assisted interpretation significantly improved the sensitivity of radiologists' interpretation (72.3%; P <0.001). CONCLUSIONS: For identifying active pulmonary tuberculosis among patients with positive IGRA results, deep learning-based CAD can enhance the sensitivity of interpretation. CAD-based prescreening may reduce the radiologists' workload at an improved specificity.

Genetic and demographic signatures accompanying the evolution of the selfing syndrome in Daphne kiusiana, an evergreen shrub.

BACKGROUND AND AIMS: The evolution of mating systems from outcrossing to self-fertilization is a common transition in flowering plants. This shift is often associated with the 'selfing syndrome', which is characterized by less visible flowers with functional changes to control outcrossing. In most cases, the evolutionary history and demographic dynamics underlying the evolution of the selfing syndrome remain poorly understood. METHODS: Here, we characterize differences in the demographic genetic consequences and associated floral-specific traits between two distinct geographical groups of a wild shrub, Daphne kiusiana, endemic to East Asia; plants in the eastern region (southeastern Korea and Kyushu, Japan) exhibit smaller and fewer flowers compared to those of plants in the western region (southwestern Korea). Genetic analyses were conducted using nuclear microsatellites and chloroplast DNA (multiplexed phylogenetic marker sequencing) datasets. KEY RESULTS: A high selfing rate with significantly increased homozygosity characterized the eastern lineage, associated with lower levels of visibility and herkogamy in the floral traits. The two lineages harboured independent phylogeographical histories. In contrast to the western lineage, the eastern lineage showed a gradual reduction in the effective population size with no signs of a severe bottleneck despite its extreme range contraction during the last glacial period. CONCLUSIONS: Our results suggest that the selfing-associated morphological changes in D. kiusiana are of relatively old origin (at least 100 000 years ago) and were driven by directional selection for efficient self-pollination. We provide evidence that the evolution of the selfing syndrome in D. kiusiana is not strongly associated with a severe population bottleneck.

The complete chloroplast genome of Porella gracillima Mitt. (Porellaceae) and phylogenetic relationships to other bryophytes.

Porella gracillima Mitt. (Jungermanniidae, Porellaceae), a bryophyte is widespread in temperate Asia and North America. In Korea, P. gracillima is mainly observed in shaded and dried rocks or tree trunks on mountains. Here, we determined the complete chloroplast (cp) genome sequence of P. gracillima to provide useful genetic information in the phylogenetic relationship, phylogeographic history, and conservation of the species. The complete cp genome of P. gracillima was assembled using NGS Illumina HiSeqX platform. The cp genome was 121,867 bp in length (GC contents, 33.7%) and showed a typical quadripartite structure, consisting of a large single copy (LSC) of 83,406 bp, a small single copy (SSC) of 19,692 bp, and two inverted repeats (IRs) of 9,385 bp. Phylogenetic analysis shows that Porellaceae was a sister group of Radulaceae, which agrees with the findings of the previous phylogenetic studies. Our cp genome data of P. gracillima may contribute to a better understanding of the evolution of the Porella in Porellaceae and will help to infer its molecular identification, thereby providing a guideline for conservation.

Artificial intelligence system for identification of false-negative interpretations in chest radiographs.

OBJECTIVES: To investigate the efficacy of an artificial intelligence (AI) system for the identification of false negatives in chest radiographs that were interpreted as normal by radiologists. METHODS: We consecutively collected chest radiographs that were read as normal during 1 month (March 2020) in a single institution. A commercialized AI system was retrospectively applied to these radiographs. Radiographs with abnormal AI results were then re-interpreted by the radiologist who initially read the radiograph ("AI as the advisor" scenario). The reference standards for the true presence of relevant abnormalities in radiographs were defined by majority voting of three thoracic radiologists. The efficacy of the AI system was evaluated by detection yield (proportion of true-positive identification among the entire examination) and false-referral rate (FRR, proportion of false-positive identification among all examinations). Decision curve analyses were performed to evaluate the net benefits of applying the AI system. RESULTS: A total of 4208 radiographs from 3778 patients (M:F = 1542:2236; median age, 56 years) were included. The AI system identified initially overlooked relevant abnormalities with a detection yield and an FRR of 2.4% and 14.0%, respectively. In the "AI as the advisor" scenario, radiologists detected initially overlooked relevant abnormalities with a detection yield and FRR of 1.2% and 0.97%, respectively. In a decision curve analysis, AI as an advisor scenario exhibited a positive net benefit when the cost-to-benefit ratio was below 1:0.8. CONCLUSION: An AI system could identify relevant abnormalities overlooked by radiologists and could enable radiologists to correct their false-negative interpretations by providing feedback to radiologists. KEY POINTS: • In consecutive chest radiographs with normal interpretations, an artificial intelligence system could identify relevant abnormalities that were initially overlooked by radiologists. • The artificial intelligence system could enable radiologists to correct their initial false-negative interpretations by providing feedback to radiologists when overlooked abnormalities were present.