Quantification of Resection Margin following Sublobar Resection in Lung Cancer Patients through Pre- and Post-Operative CT Image Comparison: Utilizing a CT-Based 3D Reconstruction Algorithm.

Sublobar resection has emerged as a standard treatment option for early-stage peripheral non-small cell lung cancer. Achieving an adequate resection margin is crucial to prevent local tumor recurrence. However, gross measurement of the resection margin may lack accuracy due to the elasticity of lung tissue and interobserver variability. Therefore, this study aimed to develop an objective measurement method, the CT-based 3D reconstruction algorithm, to quantify the resection margin following sublobar resection in lung cancer patients through pre- and post-operative CT image comparison. An automated subvascular matching technique was first developed to ensure accuracy and reproducibility in the matching process. Following the extraction of matched feature points, another key technique involves calculating the displacement field within the image. This is particularly important for mapping discontinuous deformation fields around the surgical resection area. A transformation based on thin-plate spline is used for medical image registration. Upon completing the final step of image registration, the distance at the resection margin was measured. After developing the CT-based 3D reconstruction algorithm, we included 12 cases for resection margin distance measurement, comprising 4 right middle lobectomies, 6 segmentectomies, and 2 wedge resections. The outcomes obtained with our method revealed that the target registration error for all cases was less than 2.5 mm. Our method demonstrated the feasibility of measuring the resection margin following sublobar resection in lung cancer patients through pre- and post-operative CT image comparison. Further validation with a multicenter, large cohort, and analysis of clinical outcome correlation is necessary in future studies.

Deep Learning Analysis for Predicting Tumor Spread through Air Space in Early-Stage Lung Adenocarcinoma Pathology Images.

The presence of spread through air spaces (STASs) in early-stage lung adenocarcinoma is a significant prognostic factor associated with disease recurrence and poor outcomes. Although current STAS detection methods rely on pathological examinations, the advent of artificial intelligence (AI) offers opportunities for automated histopathological image analysis. This study developed a deep learning (DL) model for STAS prediction and investigated the correlation between the prediction results and patient outcomes. To develop the DL-based STAS prediction model, 1053 digital pathology whole-slide images (WSIs) from the competition dataset were enrolled in the training set, and 227 WSIs from the National Taiwan University Hospital were enrolled for external validation. A YOLOv5-based framework comprising preprocessing, candidate detection, false-positive reduction, and patient-based prediction was proposed for STAS prediction. The model achieved an area under the curve (AUC) of 0.83 in predicting STAS presence, with 72% accuracy, 81% sensitivity, and 63% specificity. Additionally, the DL model demonstrated a prognostic value in disease-free survival compared to that of pathological evaluation. These findings suggest that DL-based STAS prediction could serve as an adjunctive screening tool and facilitate clinical decision-making in patients with early-stage lung adenocarcinoma.

CT-Based Deep-Learning Model for Spread-Through-Air-Spaces Prediction in Ground Glass-Predominant Lung Adenocarcinoma.

BACKGROUND: Sublobar resection is strongly associated with poor prognosis in early-stage lung adenocarcinoma, with the presence of tumor spread through air spaces (STAS). Thus, preoperative prediction of STAS is important for surgical planning. This study aimed to develop a STAS deep-learning (STAS-DL) prediction model in lung adenocarcinoma with tumor smaller than 3 cm and a consolidation-to-tumor (C/T) ratio less than 0.5. METHODS: The study retrospectively enrolled of 581 patients from two institutions between 2015 and 2019. The STAS-DL model was developed to extract the feature of solid components through solid components gated (SCG) for predicting STAS. The STAS-DL model was assessed with external validation in the testing sets and compared with the deep-learning model without SCG (STAS-DLwoSCG), the radiomics-based model, the C/T ratio, and five thoracic surgeons. The performance of the models was evaluated using area under the curve (AUC), accuracy and standardized net benefit of the decision curve analysis. RESULTS: The study evaluated 458 patients (institute 1) in the training set and 123 patients (institute 2) in the testing set. The proposed STAS-DL yielded the best performance compared with the other methods in the testing set, with an AUC of 0.82 and an accuracy of 74%, outperformed the STAS-DLwoSCG with an accuracy of 70%, and was superior to the physicians with an AUC of 0.68. Moreover, STAS-DL achieved the highest standardized net benefit compared with the other methods. CONCLUSION: The proposed STAS-DL model has great potential for the preoperative prediction of STAS and may support decision-making for surgical planning in early-stage, ground glass-predominant lung adenocarcinoma.

Micro-scale urbanization-based risk factors for dengue epidemics.

Dengue is one of the world's most rapidly spreading mosquito-borne viral diseases. As it is found mostly in urban and semi-urban areas, urbanization and associated human activities that affect the environment and larval habitats could become risk factors (e.g., lane width, conditions of street ditches) for the spread of dengue. However, there are currently no systematic studies of micro-scale urbanization-based risk factors for the spread of dengue epidemics. We describe the study area, two micro-scale environmental risk factors associated with urbanization, and meteorological data. Since the observations involve spatial and temporal correlations, we also use some statistical methods for the analysis of spatial and spatial-temporal data for the relationship between urbanization and dengue. In this study, we analyzed data from Kaohsiung, a densely populated city in southern Taiwan, and found a positive correlation between environmental risk factors associated with urbanization (ditches positive for mosquito larvae and closely packed streets termed "dengue lanes") and clustering effects in dengue cases. The statistical analysis also revealed that the occurrence of positive ditches was significantly associated with that of dengue lanes in the study area. The relationship between climate variables and positive ditches was also analyzed in this paper, indicating a relationship between dengue and both rainfall and temperature, with temperature having a greater effect. Overall, this work is immediately relevant and applicable for policymakers in government, who will need to reduce these favorable habitats for vector-born disease spreaders and implement regulations for new urban constructions to thus reduce dengue spread in future outbreaks.

Stably suspended SiO2-supported CdS photocatalyst for a promising organic pollutant degradation in the absence of mechanical stirring.

Even with solar-activatable photocatalyst, incommensurable energy input for stirring is still required to overcome the transport limitations in powder-photocatalysis. To counter this, a novel concept of auto-suspending photocatalyst based on SiO2/CdS was proposed to enable promising photo-activity even under stirring-free condition. Functionally-speaking, CdS would act as photoreaction-driver while SiO2 endows sufficient buoyance for suspension-stabilization during stirring-free photocatalysis. In photoreactions degrading methylene blue for theoretical demonstration, SiO2/CdS_0.3 promises only 4.57% activity reduction in non-stirred photoreaction, enabling 15.26% of methylene blue decolorization comparing to 15.99% of stirred-photoreaction under visible light irradiation. This could be ascribed to the slow settling tendency of SiO2/CdS_0.3, evading severe light-shielding under stacked condition. Also, its rightly-exposed SiO2 surface permits 'adsorb-and-degrade' mechanism, thereby overcoming the sluggish surface transport across thick boundary layer. Contrarily, photocatalyst with quintuple CdS content (SiO2/CdS_1.5) exhibits largest activity reduction (31.47%), reasoned by its quick-settling tendency. Overall, current study provides new perspectives to photocatalysis-community. The success elimination of mechanical stirring from photocatalysis promises significant energy-saving (19.1-136 kW/m3), thus consenting better practicality for solar energy-harvesting and environmental protection.

Symmetry-Breaking p-Block Antimony Single Atoms Trigger N-Bridged Titanium Sites for Electrocatalytic Nitrogen Reduction with High Efficiency.

The electrochemical nitrogen reduction reaction (eNRR) under mild conditions emerges as a promising approach to produce ammonia (NH3) compared to the typical Haber-Bosch process. Herein, we design an asymmetrically coordinated p-block antimony single-atom catalyst immobilized on nitrogen-doped Ti3C2Tx (Sb SA/N-Ti3C2Tx) for eNRR, which exhibits ultrahigh NH3 yield (108.3 µg h-1 mgcat-1) and excellent Faradaic efficiency (41.2%) at -0.3 V vs RHE. Complementary in situ spectroscopies with theoretical calculations reveal that the nitrogen-bridged two titanium atoms triggered by an adjacent asymmetrical Sb-N1C2 moiety act as the active sites for facilitating the protonation of the rate-determining step from *N2 to *N2H and the kinetic conversion of key intermediates during eNRR. Moreover, the introduction of Sb-N1C2 promotes the formation of oxygen vacancies to expose more titanium sites. This work presents a strategy for single-atom-decorated ultrathin two-dimensional materials with the aim of simultaneously enhancing NH3 yield and Faradaic efficiency for electrocatalytic nitrogen reduction.

Patients with Non-Alcoholic Fatty Liver Disease and Alcohol Dehydrogenase 1B/Aldehyde Dehydrogenase 2 Mutant Gene Have Higher Values of Serum Alanine Transaminase.

Patients with non-alcoholic fatty liver disease (NAFLD) share similar pathophysiologies to those of patients with alcohol liver disease. Alcoholic metabolic enzyme-related genes (alcohol dehydrogenase 1B (ADH1B) and aldehyde dehydrogenase 2 (ALDH2)) may be associated with pathophysiology in NAFLD patients. In this study, the association between ADH1B/ALDH2 gene polymorphism and serum metabolic factors, body statures, and hepatic steatosis/fibrosis status was evaluated in patients with NAFLD. Using biochemistry data, abdominal ultrasonography, fibrosis evaluation (Kpa), and steatosis evaluation (CAP), ADH1B gene SNP rs1229984 and ALDH2 gene SNP rs671 polymorphism were analyzed in sixty-six patients from 1 January 2022 to 31 December 2022. The percentage of the mutant type (GA + AA) was 87.9% (58/66) in the ADH1B allele and 45.5% (30/66) in the ALDH2 allele. Patients with the mutant-type ADH1B/ALDH2 allele had higher values of alanine aminotransferase (ALT) than the wild type (ß = 0.273, p = 0.04). No association was observed between body mass index, serum metabolic factors (sugar and lipid profile), CAP, kPa, and ADH1B/ALDH2. A high proportion of the mutant-type ADH1B allele (87.9%) and ALDH2 allele (45.5%) was observed in patients with NAFLD. No association was observed between ADH1B/ALDH2 allele, BMI, and hepatic steatosis/fibrosis. Patients with the mutant-type ADH1B/ALDH2 allele had higher values of ALT than those with the wild type.

Controllable Crystallization of Two-Dimensional Bi Nanocrystals with Morphology-Boosted CO2 Electroreduction in Wide pH Environments.

Two-dimensional low-melting-point (LMP) metal nanocrystals are attracting increasing attention with broad and irreplaceable applications due to their unique surface and topological structures. However, the chemical synthesis, especially the fine control over the nucleation (reduction) and growth (crystallization), of such LMP metal nanocrystals remains elusive as limited by the challenges of low standard redox potential, low melting point, poor crystalline symmetry, etc. Here, a controllable reduction-melting-crystallization (RMC) protocol to synthesize free-standing and surfactant-free bismuth nanocrystals with tunable dimensions, morphologies, and surface structures is presented. Especially, ultrathin bismuth nanosheets with flat or jagged surfaces/edges can be prepared with high selectivity. The jagged bismuth nanosheets, with abundant surface steps and defects, exhibit boosted electrocatalytic CO2 reduction performances in acidic, neutral, and alkaline aqueous solutions, achieving the maximum selectivity of near unity at the current density of 210 mA cm-2 for formate evolution under ambient conditions. This work creates the RMC pathway for the synthesis of free-standing two-dimensional LMP metal nanomaterials and may find broader applicability in more interdisciplinary applications.

Boosting CO2 Electroreduction on Bismuth Nanoplates with a Three-Dimensional Nitrogen-Doped Graphene Aerogel Matrix.

Electrochemical CO2 reduction reaction (CO2RR), which uses renewable electricity to produce high-value-added chemicals, offers an alternative clean path to the carbon cycle. However, bismuth-based catalysts show great potential for the conversion of CO2 and water to formate, but their overall efficiency is still hampered by the weak CO2 adsorption, low electrical conductivity, and slow mass transfer of CO2 molecules. Herein, we report that a rationally modulated nitrogen-doped graphene aerogel matrix (NGA) can significantly enhance the CO2RR performance of bismuth nanoplates (BiNPs) by both modulating the electronic structure of bismuth and regulating the interface for chemical reaction and mass transfer environments. In particular, the NGA prepared by reducing graphene oxide (GO) with hydrazine hydrate (denoted as NGAhdrz) exhibits significantly enhanced strong metal-support interaction (SMSI), increased specific surface area, strengthened CO2 adsorption, and modulated wettability. As a result, the Bi/NGAhdrz exhibits significantly boosted CO2RR properties, with a Faradaic efficiency (FE) of 96.4% at a current density of 51.4 mA cm-2 for formate evolution at a potential of -1.0 V versus reversible hydrogen electrode (vs RHE) in aqueous solution under ambient conditions.

Quantization of extraoral free flap monitoring for venous congestion with deep learning integrated iOS applications on smartphones: a diagnostic study.

BACKGROUND: Free flap monitoring is essential for postmicrosurgical management and outcomes but traditionally relies on human observers; the process is subjective and qualitative and imposes a heavy burden on staffing. To scientifically monitor and quantify the condition of free flaps in a clinical scenario, we developed and validated a successful clinical transitional deep learning (DL) model integrated application. MATERIAL AND METHODS: Patients from a single microsurgical intensive care unit between 1 April 2021 and 31 March 2022, were retrospectively analyzed for DL model development, validation, clinical transition, and quantification of free flap monitoring. An iOS application that predicted the probability of flap congestion based on computer vision was developed. The application calculated probability distribution that indicates the flap congestion risks. Accuracy, discrimination, and calibration tests were assessed for model performance evaluations. RESULTS: From a total of 1761 photographs of 642 patients, 122 patients were included during the clinical application period. Development (photographs =328), external validation (photographs =512), and clinical application (photographs =921) cohorts were assigned to corresponding time periods. The performance measurements of the DL model indicate a 92.2% training and a 92.3% validation accuracy. The discrimination (area under the receiver operating characteristic curve) was 0.99 (95% CI: 0.98-1.0) during internal validation and 0.98 (95% CI: 0.97-0.99) under external validation. Among clinical application periods, the application demonstrates 95.3% accuracy, 95.2% sensitivity, and 95.3% specificity. The probabilities of flap congestion were significantly higher in the congested group than in the normal group (78.3 (17.1)% versus 13.2 (18.1)%; 0.8%; 95% CI, P <0.001). CONCLUSION: The DL integrated smartphone application can accurately reflect and quantify flap condition; it is a convenient, accurate, and economical device that can improve patient safety and management and assist in monitoring flap physiology.

Ultrathin Dendritic Pd-Ag Nanoplates for Efficient and Durable Electrocatalytic Reduction of CO2 to Formate.

CO2 reduction reactions (CO2 RR) powered by renewable electricity can directly convert CO2 to hydrocarbons and fix the sustainable but intermittent energy (e. g., sunlight, wind, etc.) in stable and portable chemical fuels. Advanced catalysts boosting CO2 RR with high activity, selectivity, and durability at low overpotentials are of great importance but still elusive. Here, we report that the ultrathin Pd-Ag dendritic nanoplates (PdAg DNPs) exhibited boosted activity, selectivity, and stability for producing formate from CO2 at a very low overpotential in aqueous solutions under ambient conditions. As a result, the PdAg DNPs exhibited a Faradaic efficiency (FE) for formate of 91% and a cathodic energy efficiency (EE) of ∼90% at the potential of -0.2 V versus reversible hydrogen electrode (vs. RHE), showing significantly enhanced durability as compared with pure Pd catalysts. Our strategy represents a rational catalyst design by engineering the surface geometrical and electronic structures of metal nanocrystals and may find more applicability in future electrocatalysis.

Rs9679162 genotype predicts prognosis of real-world advanced hepatocellular carcinoma treated by sorafenib.

BACKGROUND: Sorafenib and lenvatinib are tyrosine kinase inhibitors widely used in the targeted therapy to treat advanced hepatocellular carcinoma (aHCC). The GALNT14-rs9679162 genotype is a predictor of therapeutic outcome in multiple gastrointestinal cancers. OBJECTIVE: To investigate the predictive role of the GALNT14-rs9679162 genotype in aHCC treated with sorafenib or lenvatinib. METHODS: Totally 350 real-world patients with aHCC received sorafenib or lenvatinib were enrolled for GALNT14-rs9679162 genotyping and outcome analysis. Kaplan-Meier and Cox regression analysis were conducted to evaluate therapeutic outcomes. Cell-based assays were performed to determine the underlying mechanism. RESULTS: Kaplan-Meier and Cox regression analysis showed that the "GG" genotype was not associated with overall survival (OS) when all patients were included. However, it was associated with shorter OS in specific clinical subgroups, including anti-hepatitis C virus antibody-positive (n= 108; P= 0.005) and hepatitis B surface antigen-negative (n= 117; P= 0.002) patients. Intriguingly, hepatitis B virus X protein trans-suppressed the GALNT14 promoter, thereby reducing the elevated expression of GALNT14 in hepatoma cells, which partially contributed to the inability of the GALNT14-rs9679162 genotypes to predict the outcome of hepatitis B-related HCC. Finally, by analyzing the outcomes of 52 patients with aHCC treated with lenvatinib, patients with the "GG" genotype were associated with a favorable/shorter time-to-response (P= 0.013). CONCLUSIONS: The GALNT14-rs9679162 "GG" genotype predicted shorter OS in patients with HBsAg-negative aHCC treated with sorafenib, but predicted a favorable response in all patients with aHCC treated with lenvatinib.

Waist-to-height ratio for the prediction of gallstone disease among different obesity indicators.

Background: Factors of metabolic syndrome such as obesity are well-known risk factors for gallstone disease (GSD). There are different indicators of obesity, including weight, body mass index, waist circumference, and waist-to-height ratio. The predictive ability of different obesity indicators for GSD remains unclear. Objective: To explore the most efficient predictor of GSD among the different anthropometric indicators of obesity. Methods: This population-based cross-sectional study included 2263 participants who completed a questionnaire detailing their demographics, medical history, and lifestyle between 2014 and 2017 in Taiwan. Blood samples were collected and physical examinations, including anthropometric measurements, were performed. Gallstone disease was ascertained using ultrasonography. Multivariate analyses were performed to identify independent risk factors for GSD. Results: The overall prevalence of GSD was 8.8%. According to the multivariate analysis, individuals with a waist-to-height ratio ≥0.5 (odds ratio|odds ratios (OR) = 1.65, 95% confidence interval (CI) = 1.10-2.48, p = 0.017) had an increased risk of GSD. Diabetes was the main risk factor for GSD in men (OR = 2.06, 95% CI = 1.17-3.65, p = 0.013). Among women, waist-to-height ratio >0.5 (OR = 1.76, 95% CI = 1.03-3.02, p = 0.040) and current hormone drug use (OR = 2.73, 95% CI = 1.09-6.84, p = 0.033) were significant risk factors for gallstones. Conclusion: GSD was independently associated with central obesity and exogenous hormone intake in women. Among the anthropometric indicators used to assess central obesity, waist-to-height ratio was the most accurate predictor of GSD.

A Single Nucleotide Polymorphism rs1010816 Predicts Sorafenib Therapeutic Outcomes in Advanced Hepatocellular Carcinoma.

Sorafenib is currently a targeted agent widely used in the treatment of advanced hepatocellular carcinoma (aHCC). However, to date there is still a lack of a reliable marker capable of predicting sorafenib therapeutic responses. Here, we conducted a genome-wide association study (GWAS) to identify candidate single-nucleotide polymorphism outcome predictors in aHCC patients. A total of 74 real-world sorafenib-treated aHCC patients were enrolled for GWAS and outcome analysis. GWAS showed that rs1010816 (p = 2.2 × 10-7) was associated with sorafenib therapeutic response in aHCC patients. Kaplan-Meier analysis indicated that the "TT" genotype was significantly associated with a favorable therapeutic response but not significantly associated with overall survival (OS). Univariate followed by multivariate Cox proportional hazard analysis showed that ascites, main portal vein thrombosis, lower platelet count, lower total sorafenib doses, higher PALBI score in model A and higher ALBI grade in model B were significantly associated with a shorter OS. Subgroup analysis showed that only in alcoholic aHCC patients treated by sorafenib, rs1010816 "TT" genotype was significantly associated with longer OS (p = 0.021). Sorafenib had a favorable therapeutic outcome in alcoholic aHCC patients carrying rs1010816 "TT" genotype.

Design, Implementation, and Assessment Approaches Within an Advanced Human Immunodeficiency Virus (HIV) Elective Course.

Introduction: An estimated 38 million people are living with human immunodeficiency virus (HIV) worldwide. Pharmacists are well positioned to provide care to patients with HIV, but gaps in HIV education among pharmacists exist. Recognizing the need to educate and prepare future pharmacists, a 2-credit advanced HIV elective course was created for Doctor of Pharmacy students at Washington State University College of Pharmacy and Pharmaceutical Sciences in the United States, and Masters of Clinical Pharmacy students from University of Western Cape School of Pharmacy in South Africa. Methods: Course topics included diagnosis and treatment of HIV in children and adults, management of common comorbidities, pre-exposure prophylaxis, pharmacogenetic applications, and antiretroviral drug-drug interactions. Course effectiveness was evaluated using student examination results. Student perceptions were evaluated using pre- and post-course self-assessments involving abilities, confidence, and attitudes toward caring for people living with HIV. Results: Student pharmacists demonstrated competency in HIV knowledge, demonstrated skills in application to clinical-based scenarios, and reported significantly improved confidence and abilities as well as positive changes in attitudes toward people with HIV. Conclusion: This course contributed to student learning across different student cohorts in an institutional program in the United States including successful execution of distance learning and clinical application for students at a program in South Africa.

Improving performance of cell imprinted PDMS by integrating boronate affinity and local post-imprinting modification for selective capture of circulating tumor cells from cancer patients.

Efficient capture of circulating tumor cells (CTCs) from cancer patients is an important technique that may promote early diagnosis and prognosis monitoring of cancer. However, the existing systems have certain disadvantages, such as poor selectivity, low capture efficiency, consumption of antibodies, and difficulty in release of CTCs for downstream analysis. Herein, we fabricated an innovative PEGylated boronate affinity cell imprinted polydimethylsiloxane (PBACIP) for highly efficient capture of CTCs from cancer patients. The antibody-free PBACIP possessed hierarchical structure of imprinted cavities, which were inlaid with boronic acid modified SiO2 nanoparticles (SiO2@BA), so it could specifically capture target CTCs from biological samples due to the synergistic effect of boronate affinity and cell imprinting. Furthermore, PEGylation was accurately completed in the non-imprinted region by the template cells occupying the imprinted cavity, which not only retained the microstructure of original imprinted cavities, but also endowed PBACIP with hydrophilicity. The artificial PBACIP could efficiently capture human breast-cancer cells from biological sample. When 5 to 500 SKBR3 cells were spiked in 1 mL mice lysed blood, the capture efficiency reached 86.7 ± 11.5% to 96.2 ± 2.3%. Most importantly, the PBACIP was successfully used to capture CTCs from blood of breast cancer patients, and the captured CTCs were released for subsequent gene mutation analysis. The PBACIP can efficiently capture and release CTCs for downstream analysis, which provides a universal strategy toward individualized anti-tumor comprehensive treatments and has great potential in the future cell-based clinical applications.

The association between serum folate and gestational diabetes mellitus: a large retrospective cohort study in Chinese population.

OBJECTIVE: To investigate the association between folate levels and the risk of gestational diabetes mellitus (GDM) risk during the whole pregnancy. DESIGN: In this retrospective cohort study of pregnant women, serum folate levels were measured before 24 gestational weeks (GW). GDM was diagnosed between 24th and 28th GW based on the criteria of the International Association of Diabetes and Pregnancy Study Groups. General linear models were performed to examine the association of serum folate with plasma glucose (i.e. linear regressions) and risk of GDM (i.e. log-binomial regressions) after controlling for confounders. Restricted cubic spline regression was conducted to test the dosage-response relationship between serum folate and the risk of GDM. SETTING: A sigle, urban hospital in Shanghai, China. PARTICIPANTS: A total of 42 478 women who received antenatal care from April 2013 to March 2017 were included. RESULTS: Consistent positive associations were observed between serum folate and plasma glucose levels (fasting, 1-h, 2-h). The adjusted relative risks (RR) and 95 % CI of GDM across serum folate quartiles were 1·00 (reference), 1·15 (95 % CI (1·04, 1·26)), 1·40 (95 % CI (1·27, 1·54)) and 1·54 (95 % CI (1·40, 1·69)), respectively (P-for-trend < 0·001). The positive association between serum folate and GDM remained when stratified by vitamin B12 (adequate v. deficient groups) and the GW of serum folate measurement (≤13 GW v. >13 GWs). CONCLUSIONS: The findings of this study may provide important evidence for the public health and clinical guidelines of pregnancy folate supplementation in terms of GDM prevention.

[Protective effect and mechanism of Maiwei Yangfei Decoction on pulmonary fibrosis mice based on Nrf2 regulation of oxidative stress].

This study explored the effect and mechanism of Maiwei Yangfei Decoction(MWYF) on pulmonary fibrosis(PF) mice. MWYF was prepared, and its main components were detected by ultra-high-performance liquid chromatography-triple quadrupole tandem mass spectrometry(UPLC-MS/MS). Male C57BL/6J mice were randomly divided into a control group, a model group, a pirfenidone(PFD) group, and low-, medium-, and high-dose MWYF groups, with 10 mice in each group. The PF model was induced in mice except for those in the control group by intratracheal instillation of bleomycin(BLM), and model mice were treated with saline or MWYF or PFD by gavage the next day. The water consumption, food intake, hair, and activity of mice were observed daily. The pathological changes in lung tissues were observed by hematoxylin-eosin(HE) staining, Masson staining, and CT scanning. The level of hydroxyproline(HYP) in lung tissues was detected by alkaline hydrolysis. Immunohistochemistry was used to observe the expression of collagen type Ⅲ(COL3) and fibronectin. The mRNA expression levels of α-smooth muscle actin(α-SMA), type Ⅰ collagen α1(COL1α1), COL3, and vimentin were detected by reverse transcription real-time fluorescence quantitative polymerase chain reaction(RT-qPCR). Superoxide dismutase(SOD) and malondialdehyde(MDA) kits were used to detect oxidative stress indicators in lung tissues and serum. The nuclear translocation of nuclear factor E2-related factor 2(Nrf2) protein was detected by immunofluorescence. The protein and mRNA expression levels of Nrf2, catalase(CAT), and heme oxygenase 1(HO-1) in lung tissues were detected by Western blot and RT-qPCR. Twelve chemical components were detected by UPLC-MS/MS. Animal experiments showed that MWYF could improve alveolar inflammation, collagen deposition, and fibrosis in PF mice, increase body weight of mice, and down-regulate the expression of fibrosis indexes such as HYP, α-SMA, COL1α1, COL3, fibronectin, and vimentin in lung tissues. In addition, MWYF could potentiate the activity of SOD in lung tissues and serum of PF mice, up-regulate the expression level of Nrf2, and promote its transfer to the nucleus, up-regulate the levels of downstream antioxidant target genes CAT and HO-1, and then reduce the accumulation of lipid metabolite MDA. In summary, MWYF can significantly improve the pathological damage and fibrosis of lung tissues in PF mice, and its mechanism may be related to the activation of the Nrf2 pathway to regulate oxidative stress.

CT-Based Radiomic Analysis for Preoperative Prediction of Tumor Invasiveness in Lung Adenocarcinoma Presenting as Pure Ground-Glass Nodule.

It remains a challenge to preoperatively forecast whether lung pure ground-glass nodules (pGGNs) have invasive components. We aimed to construct a radiomic model using tumor characteristics to predict the histologic subtype associated with pGGNs. We retrospectively reviewed clinicopathologic features of pGGNs resected in 338 patients with lung adenocarcinoma between 2011-2016 at a single institution. A radiomic prediction model based on forward sequential selection and logistic regression was constructed to differentiate adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA) from invasive adenocarcinoma. The study cohort included 133 (39.4%), 128 (37.9%), and 77 (22.8%) patients with AIS, MIA, and invasive adenocarcinoma (acinar 55.8%, lepidic 33.8%, papillary 10.4%), respectively. The majority (83.7%) underwent sublobar resection. There were no nodal metastases or tumor recurrence during a mean follow-up period of 78 months. Three radiomic features-cluster shade, homogeneity, and run-length variance-were identified as predictors of histologic subtype and were selected to construct a prediction model to classify the AIS/MIA and invasive adenocarcinoma groups. The model achieved accuracy, sensitivity, specificity, and AUC of 70.6%, 75.0%, 70.0%, and 0.7676, respectively. Applying the developed radiomic feature model to predict the histologic subtypes of pGGNs observed on CT scans can help clinically in the treatment selection process.