Deep learning model for pleural effusion detection via active learning and pseudo-labeling: a multisite study.

BACKGROUND: The study aimed to develop and validate a deep learning-based Computer Aided Triage (CADt) algorithm for detecting pleural effusion in chest radiographs using an active learning (AL) framework. This is aimed at addressing the critical need for a clinical grade algorithm that can timely diagnose pleural effusion, which affects approximately 1.5 million people annually in the United States. METHODS: In this multisite study, 10,599 chest radiographs from 2006 to 2018 were retrospectively collected from an institution in Taiwan to train the deep learning algorithm. The AL framework utilized significantly reduced the need for expert annotations. For external validation, the algorithm was tested on a multisite dataset of 600 chest radiographs from 22 clinical sites in the United States and Taiwan, which were annotated by three U.S. board-certified radiologists. RESULTS: The CADt algorithm demonstrated high effectiveness in identifying pleural effusion, achieving a sensitivity of 0.95 (95% CI: [0.92, 0.97]) and a specificity of 0.97 (95% CI: [0.95, 0.99]). The area under the receiver operating characteristic curve (AUC) was 0.97 (95% DeLong's CI: [0.95, 0.99]). Subgroup analyses showed that the algorithm maintained robust performance across various demographics and clinical settings. CONCLUSION: This study presents a novel approach in developing clinical grade CADt solutions for the diagnosis of pleural effusion. The AL-based CADt algorithm not only achieved high accuracy in detecting pleural effusion but also significantly reduced the workload required for clinical experts in annotating medical data. This method enhances the feasibility of employing advanced technological solutions for prompt and accurate diagnosis in medical settings.

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.

Machine Learning Model with Computed Tomography Radiomics and Clinicobiochemical Characteristics Predict the Subtypes of Patients with Primary Aldosteronism.

RATIONALE AND OBJECTIVES: Adrenal venous sampling (AVS) is the primary method for differentiating between primary aldosterone (PA) subtypes. The aim of study is to develop prediction models for subtyping of patients with PA using computed tomography (CT) radiomics and clinicobiochemical characteristics associated with PA. MATERIALS AND METHODS: This study retrospectively enrolled 158 patients with PA who underwent AVS between January 2014 and March 2021. Neural network machine learning models were developed using a two-stage analysis of triple-phase abdominal CT and clinicobiochemical characteristics. In the first stage, the models were constructed to classify unilateral or bilateral PA; in the second stage, they were designed to determine the predominant side in patients with unilateral PA. The final proposed model combined the best-performing models from both stages. The model's performance was evaluated using repeated stratified five-fold cross-validation. We employed paired t-tests to compare its performance with the conventional imaging evaluations made by radiologists, which categorize patients as either having bilateral PA or unilateral PA on one side. RESULTS: In the first stage, the integrated model that combines CT radiomic and clinicobiochemical characteristics exhibited the highest performance, surpassing both the radiomic-alone and clinicobiochemical-alone models. It achieved an accuracy and F1 score of 80.6% ± 3.0% and 74.8% ± 5.2% (area under the receiver operating curve [AUC] = 0.778 ± 0.050). In the second stage, the accuracy and F1 score of the radiomic-based model were 88% ± 4.9% and 81.9% ± 6.2% (AUC=0.831 ± 0.087). The proposed model achieved an accuracy and F1 score of 77.5% ± 3.9% and 70.5% ± 7.1% (AUC=0.771 ± 0.046) in subtype diagnosis and lateralization, surpassing the accuracy and F1 score achieved by radiologists' evaluation (p < .05). CONCLUSION: The proposed machine learning model can predict the subtypes and lateralization of PA. It yields superior results compared to conventional imaging evaluation and has potential to supplement the diagnostic process in PA.

Uteroplacental insufficiency decreases leptin expression and impairs lung development in growth-restricted newborn rats.

BACKGROUND: The study aimed to analyze the effect of uteroplacental insufficiency (UPI) on leptin expression and lung development of intrauterine growth restriction (IUGR) rats. METHODS: On day 17 of pregnancy, time-dated Sprague-Dawley rats were randomly divided into either an IUGR group or a control group. Uteroplacental insufficiency surgery (IUGR) and sham surgery (control) were conducted. Offspring rats were spontaneously delivered on day 22 of pregnancy. On postnatal days 0 and 7, rats' pups were selected at random from the control and IUGR groups. Blood was withdrawn from the heart to determine leptin levels. The right lung was obtained for leptin and leptin receptor levels, immunohistochemistry, proliferating cell nuclear antigen (PCNA), western blot, and metabolomic analyses. RESULTS: UPI-induced IUGR decreased leptin expression and impaired lung development, causing decreased surface area and volume in offspring. This results in lower body weight, decreased serum leptin levels, lung leptin and leptin receptor levels, alveolar space, PCNA, and increased alveolar wall volume fraction in IUGR offspring rats. The IUGR group found significant relationships between serum leptin, radial alveolar count, von Willebrand Factor, and metabolites. CONCLUSION: Leptin may contribute to UPI-induced lung development during the postnatal period, suggesting supplementation as a potential treatment. IMPACT: The neonatal rats with intrauterine growth restriction (IUGR) caused by uteroplacental insufficiency (UPI) showed decreased leptin expression and impaired lung development. UPI-induced IUGR significantly decreased surface area and volume in lung offspring. This is a novel study that investigates leptin expression and lung development in neonatal rats with IUGR caused by UPI. If our findings translate to IUGR infants, leptin may contribute to UPI-induced lung development during the postnatal period, suggesting supplementation as a potential treatment.

Intrauterine growth restriction alters kidney metabolism at the end of nephrogenesis.

BACKGROUND: This study investigated the effect of uteroplacental insufficiency (UPI) on renal development by detecting metabolic alterations in the kidneys of rats with intrauterine growth restriction (IUGR). METHODS: On gestational day 17, pregnant Sprague Dawley rats were selected and allocated randomly to either the IUGR group or the control group. The IUGR group received a protocol involving the closure of bilateral uterine vessels, while the control group underwent a sham surgery. The rat pups were delivered on gestational day 22 by natural means. Pups were randomly recruited from both the control and IUGR groups on the seventh day after birth. The kidneys were surgically removed to conduct Western blot and metabolomic analyses. RESULTS: IUGR was produced by UPI, as evidenced by the significantly lower body weights of the pups with IUGR compared to the control pups on postnatal day 7. UPI significantly increased the levels of cleaved caspase-3 (p < 0.05) and BAX/Bcl-2 (p < 0.01) in the pups with IUGR. Ten metabolites exhibited statistically significant differences between the groups (q < 0.05). Metabolic pathway enrichment analysis demonstrated statistically significant variations between the groups in the metabolism related to fructose and mannose, amino and nucleotide sugars, and inositol phosphate. CONCLUSIONS: UPI alters kidney metabolism in growth-restricted newborn rats and induces renal apoptosis. The results of our study have the potential to provide new insights into biomarkers and metabolic pathways that are involved in the kidney changes generated by IUGR.

Automated marker-free longitudinal infrared breast image registration by GA-PSO.

The automated marker-free longitudinal Infrared (IR) breast image registration overcomes several challenges like no anatomic fiducial markers on the body surface, blurry boundaries, heat pattern variation by environmental and physiological factors, nonrigid deformation, etc, has the ability of quantitative pixel-wise analysis with the heat energy and patterns change in a time course study. To achieve the goal, scale-invariant feature transform, Harris corner, and Hessian matrix were employed to generate the feature points as anatomic fiducial markers, and hybrid genetic algorithm and particle swarm optimization minimizing the matching errors was used to find the appropriate corresponding pairs between the 1st IR image and thenth IR image. Moreover, the mechanism of the IR spectrogram hardware system has a high level of reproducibility. The performance of the proposed longitudinal image registration system was evaluated by the simulated experiments and the clinical trial. In the simulated experiments, the mean difference of our system is 1.64 mm, which increases 57.58% accuracy than manual determination and makes a 17.4% improvement than the previous study. In the clinical trial, 80 patients were captured several times of IR breast images during chemotherapy. Most of them were well aligned in the spatiotemporal domain. In the few cases with evident heat pattern dissipation and spatial deviation, it still provided a reliable comparison of vascular variation. Therefore, the proposed system is accurate and robust, which could be considered as a reliable tool for longitudinal approaches to breast cancer diagnosis.

Intranasal administration of Lactobacillus johnsonii attenuates hyperoxia-induced lung injury by modulating gut microbiota in neonatal mice.

BACKGROUND: Supplemental oxygen impairs lung development in newborn infants with respiratory distress. Lactobacillus johnsonii supplementation attenuates respiratory viral infection in mice and exhibits anti-inflammatory effects. This study investigated the protective effects of intranasal administration of L. johnsonii on lung development in hyperoxia-exposed neonatal mice. METHODS: Neonatal C57BL/6N mice were reared in either room air (RA) or hyperoxia condition (85% O2). From postnatal days 0 to 6, they were administered intranasal 10 µL L. johnsonii at a dose of 1 × 105 colony-forming units. Control mice received an equal volume of normal saline (NS). We evaluated the following four study groups: RA + NS, RA + probiotic, O2 + NS, and O2 + probiotic. On postnatal day 7, lung and intestinal microbiota were sampled from the left lung and lower gastrointestinal tract, respectively. The right lung of each mouse was harvested for Western blot, cytokine, and histology analyses. RESULTS: The O2 + NS group exhibited significantly lower body weight and vascular density and significantly higher mean linear intercept (MLI) and lung cytokine levels compared with the RA + NS and RA + probiotic groups. At the genus level of the gut microbiota, the O2 + NS group exhibited significantly higher Staphylococcus and Enterobacter abundance and significantly lower Lactobacillus abundance compared with the RA + NS and RA + probiotic groups. Intranasal L. johnsonii treatment increased the vascular density, decreased the MLI and cytokine levels, and restored the gut microbiota in hyperoxia-exposed neonatal mice. CONCLUSIONS: Intranasal administration of L. johnsonii protects against hyperoxia-induced lung injury and modulates the gut microbiota.

Molecular Mechanisms of Hyperoxia-Induced Neonatal Intestinal Injury.

Oxygen therapy is important for newborns. However, hyperoxia can cause intestinal inflammation and injury. Hyperoxia-induced oxidative stress is mediated by multiple molecular factors and leads to intestinal damage. Histological changes include ileal mucosal thickness, intestinal barrier damage, and fewer Paneth cells, goblet cells, and villi, effects which decrease the protection from pathogens and increase the risk of necrotizing enterocolitis (NEC). It also causes vascular changes with microbiota influence. Hyperoxia-induced intestinal injuries are influenced by several molecular factors, including excessive nitric oxide, the nuclear factor-κB (NF-κB) pathway, reactive oxygen species, toll-like receptor-4, CXC motif ligand-1, and interleukin-6. Nuclear factor erythroid 2-related factor 2 (Nrf2) pathways and some antioxidant cytokines or molecules including interleukin-17D, n-acetylcysteine, arginyl-glutamine, deoxyribonucleic acid, cathelicidin, and health microbiota play a role in preventing cell apoptosis and tissue inflammation from oxidative stress. NF-κB and Nrf2 pathways are essential to maintain the balance of oxidative stress and antioxidants and prevent cell apoptosis and tissue inflammation. Intestinal inflammation can lead to intestinal damage and death of the intestinal tissue, such as in NEC. This review focuses on histologic changes and molecular pathways of hyperoxia-induced intestinal injuries to establish a framework for potential interventions.

Alteration in branching morphogenesis via YAP/TAZ in fibroblasts of fetal lungs in an LPS-induced inflammation model.

BACKGROUND: Chorioamnionitis is a common cause of preterm birth and leads to serious complications in newborns. The objective of this study was to investigate the role of the Hippo signaling pathway in lung branching morphogenesis under a lipopolysaccharide (LPS)-induced inflammation model. MATERIALS AND METHODS: IMR-90 cells and ex vivo fetal lungs were treated with 0, 10, 30, or 50 µg/ml LPS for 24 and 72 h. Supernatant levels of lactate dehydrogenase (LDH), interleukin (IL)-6, IL-8, Chemokine (C-X-C motif) ligand 1(CXCL1), branching and the surface area ratio, Yes-associated protein (YAP), transcription coactivator with PDZ-binding motif (TAZ), fibroblast growth factor 10 (FGF10), fibroblast growth factor receptor II (FGFR2), SRY-box transcription factor 2 (SOX2), SOX9, and sirtuin 1 (SIRT1) levels were examined. Differentially expressed genes in fetal lungs after LPS treatment were identified by RNA-sequencing. RESULTS: LPS at 50 µg/ml increased IL-6 and IL-8 in IMR-90 cells and increased IL-6, CXCL1 and LDH in fetal lungs. The branching ratio significantly increased by LPS at 30 µg/ml compared to the control but the increased level had decreased by 50 µg/ml LPS exposure. Exposure to 50 µg/ml LPS increased phosphorylated (p)-YAP, p-YAP/YAP, and p-TAZ/TAZ in IMR-90 cells, whereas 50 µg/ml LPS decreased FGF10 and SOX2. Consistently, p-YAP/YAP and p-TAZ/TAZ were increased in fibronectin+ cells of fetal lungs. Moreover, results of RNA-sequencing in fetal lungs showed that SMAD, FGF, IκB phosphorylation, tissue remodeling and homeostasis was involved in branching morphogenesis following exposure to 50 µg/ml LPS. The p-SIRT1/SIRT1 ratio increased in IMR-90 cells by LPS treatment. CONCLUSIONS: This study showed that regulation of the Hippo pathway in fibroblasts of fetal lungs was involved in branching morphogenesis under an inflammatory disease such as chorioamnionitis.

Polar map-free 3D deep learning algorithm to predict obstructive coronary artery disease with myocardial perfusion CZT-SPECT.

PURPOSE: Deep learning (DL) models have been shown to outperform total perfusion deficit (TPD) quantification in predicting obstructive coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, previously published methods have depended on polar maps, required manual correction, and normal database. In this study, we propose a polar map-free 3D DL algorithm to predict obstructive disease. METHODS: We included 1861 subjects who underwent MPI using cadmium-zinc-telluride camera and subsequent coronary angiography. The subjects were divided into parameterization and external validation groups. We implemented a fully automatic algorithm to segment myocardium, perform registration, and apply normalization. We further flattened the image based on spherical coordinate system transformation. The proposed model consisted of a component to predict patent arteries and a component to predict disease in each vessel. The model was cross-validated in the parameterization group, and then further tested using the external validation group. The performance was assessed by area under receiver operating characteristic curves (AUCs) and compared with TPD. RESULTS: Our algorithm preprocessed all images accurately as confirmed by visual inspection. In patient-based analysis, the AUC of the proposed model was significantly higher than that for stress-TPD (0.84 vs 0.76, p < 0.01). In vessel-based analysis, the proposed model also outperformed regional stress-TPD (AUC = 0.80 vs 0.72, p < 0.01). The addition of quantitative images did not improve the performance. CONCLUSIONS: Our proposed polar map-free 3D DL algorithm to predict obstructive CAD from MPI outperformed TPD and did not require manual correction or a normal database.

Effects of uteroplacental insufficiency on cardiac development in growth-restricted newborn rats.

Fetal growth restriction (FGR) is associated with reduced cardiac function in neonates. Uteroplacental insufficiency (UPI) is the most common cause of FGR. The mechanisms underlying these alterations remain unknown. We hypothesized that UPI would influence cardiac development in offspring rats. Through this study, we evaluated the effects of UPI during pregnancy on heart histology and pulmonary hypertension in growth-restricted newborn rats. On gestation Day 18, either UPI was induced through bilateral uterine vessel ligation (FGR group) or sham surgery (control group) was performed. The right middle lobe of the lung and the heart were harvested for histological and immunohistochemical evaluation on postnatal days 0 and 7. The FGR group exhibited significantly lower body weight, hypertrophy and degeneration of cardiomyocytes, increased intercellular spaces between the cardiomyocytes and collagen deposition, and decreased glycogen deposition and HNK-1 expression compared with the control group on postnatal days 0 and 7. These results suggest that neonates with FGR may have inadequate myocardial reserves, which may cause subsequent cardiovascular compromise in future life. Further studies are required to evaluate the hemodynamic changes in these growth-restricted neonates.

Diesel exhaust particles inhibit lung branching morphogenesis via the YAP/TAZ pathway.

Prenatal exposure to air pollution may associated with inhibition of lung development in the child, however the possible mechanism is unclear. We investigated the effects of traffic-related diesel exhaust particle (DEP) exposure on fetal lung branching morphogenesis and elucidate the possible mechanism. Ex vivo fetal lungs collected from ICR mice at an age of 11.5 embryonic (E) days were exposed to DEPs at 0 (control), 10, and 50 µg/mL and branching morphogenesis was measured for 3 days. Normal IMR-90 human fetal lung fibroblast cells were exposed to DEPs at 0 (control), 10, and 50 µg/mL for 24 h. We observed that DEP exposure significantly inhibited lung branching morphogenesis with reduced lung branching ratios and surface areas on day 3. RNA sequencing (RNA-Seq) showed that DEP increased the inflammatory response and impaired lung development-related gene expressions. DEPs significantly decreased Yes-associated protein (YAP), phosphorylated (p)-YAP, transcriptional coactivator with a PDZ-binding motif (TAZ), and p-TAZ in IMR-90 cells at 10 and 50 µg/mL. Treatment of fetal lungs with the YAP inhibitor, PFI-2, also demonstrated restricted lung branching development similar to that of DEP exposure, with a significantly decreased lung branching ratio on day 3. DEP exposure significantly decreased the lung branching modulators fibroblast growth factor receptor 2 (FGFR2), sex-determining region Y-box 2 (SOX2), and SOX9 in IMR-90 cells at 10 and 50 µg/mL. Fetal lung immunofluorescence staining showed that DEP decreased SOX2 expression in fibronectin+ fibroblasts. DEP exposure decreased the cellular senescence regulator, p-sirtuin 1 (SIRT1)/SIRT1 in IMR-90 cells, with RNA-Seq showing impaired telomere maintenance. DEP exposure impaired fetal lung growth during the pseudoglandular stage through dysregulating the Hippo signaling pathway, causing fibroblast lung branching restriction and early senescence. Prenatal exposure to traffic-related air pollution has adverse effects on fetal lung development.

Cathelicidin Attenuates Hyperoxia-Induced Lung Injury by Inhibiting Ferroptosis in Newborn Rats.

High oxygen concentrations are often required to treat newborn infants with respiratory distress but have adverse effects, such as increased oxidative stress and ferroptosis and impaired alveolarization. Cathelicidins are a family of antimicrobial peptides that exhibit antioxidant activity, and they can reduce hyperoxia-induced oxidative stress. This study evaluated the effects of cathelicidin treatment on lung ferroptosis and alveolarization in hyperoxia-exposed newborn rats. Sprague Dawley rat pups were either reared in room air (RA) or hyperoxia (85% O2) and then randomly given cathelicidin (8 mg/kg) in 0.05 mL of normal saline (NS), or NS was administered intraperitoneally on postnatal days from 1-6. The four groups obtained were as follows: RA + NS, RA + cathelicidin, O2 + NS, and O2 + cathelicidin. On postnatal day 7, lungs were harvested for histological, biochemical, and Western blot analyses. The rats nurtured in hyperoxia and treated with NS exhibited significantly lower body weight and cathelicidin expression, higher Fe2+, malondialdehyde, iron deposition, mitochondrial damage (TOMM20), and interleukin-1ß (IL-1ß), and significantly lower glutathione, glutathione peroxidase 4, and radial alveolar count (RAC) compared to the rats kept in RA and treated with NS or cathelicidin. Cathelicidin treatment mitigated hyperoxia-induced lung injury, as demonstrated by higher RAC and lower TOMM20 and IL-1ß levels. The attenuation of lung injury was accompanied by decreased ferroptosis. These findings indicated that cathelicidin mitigated hyperoxia-induced lung injury in the rats, most likely by inhibiting ferroptosis.

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.

Automated 3D segmentation of the aorta and pulmonary artery for predicting outcomes after thoracoscopic lobectomy in lung cancer patients.

Background: Preoperative two-dimensional manual measurement of pulmonary artery diameter in a single-cut axial view computed tomography (CT) image is a commonly used non-invasive prediction method for pulmonary hypertension. However, the accuracy may be unreliable. Thus, this study aimed to evaluate the correlation of short-term surgical outcomes and pulmonary artery/aorta (PA/Ao) diameter ratio measured by automated three-dimensional (3D) segmentation in lung cancer patients who underwent thoracoscopic lobectomy. Materials and methods: We included 383 consecutive lung cancer patients with thin-slice CT images who underwent lobectomy at a single institute between January 1, 2011 and December 31, 2019. Automated 3D segmentation models were used for 3D vascular reconstruction and measurement of the average diameters of Ao and PA. Propensity-score matching incorporating age, Charlson comorbidity index, and lobectomy performed by uniportal VATS was used to compare clinical outcomes in patients with PA/Ao ratio ≥1 and those <1. Results: Our segmentation method measured 29 (7.57%) patients with a PA/Ao ratio ≥1. After propensity-score matching, a higher overall postoperative complication classified by the Clavien-Dindo classification (p = 0.016) were noted in patients with 3D PA/Ao diameter ratio ≥1 than those of <1. By multivariate logistic regression, patients with a 3D PA/Ao ratio ≥ 1 (p = 0.013) and tumor diameter > 3 cm (p = 0.002) both significantly predict the incidence of postoperative complications. Conclusions: Pulmonary artery/aorta diameter ratio ≥ 1 measured by automated 3D segmentation may predict postoperative complications in lung cancer patients who underwent lobectomy.

Uteroplacental Insufficiency Causes Microbiota Disruption and Lung Development Impairment in Growth-Restricted Newborn Rats.

Preclinical studies have demonstrated that intrauterine growth retardation (IUGR) is associated with reduced lung development during the neonatal period and infancy. Uteroplacental insufficiency (UPI), affecting approximately 10% of human pregnancies, is the most common cause of IUGR. This study investigated the effects of UPI on lung development and the intestinal microbiota and correlations in newborn rats with IUGR, using bilateral uterine artery ligation to induce UPI. Maternal fecal samples were collected on postnatal day 0. On postnatal days 0 and 7, lung and intestinal microbiota samples were collected from the left lung and the lower gastrointestinal tract. The right lung was harvested for histological assessment and Western blot analysis. Results showed that UPI through bilateral uterine artery ligation did not alter the maternal gut microbiota. IUGR impaired lung development and angiogenesis in newborn rats. Moreover, on postnatal day 0, the presence of Acinetobacter and Delftia in the lungs and Acinetobacter and Nevskia in the gastrointestinal tract was negatively correlated with lung development. Bacteroides in the lungs and Rodentibacter and Romboutsia in the gastrointestinal tract were negatively correlated with lung development on day 7. UPI may have regulated lung development and angiogenesis through the modulation of the newborn rats' intestinal and lung microbiota.

Effects of uteroplacental insufficiency on growth-restricted rats with altered lung development: A metabolomic analysis.

Background: Intrauterine growth restriction (IUGR) is among the most challenging problems in antenatal care. Several factors implicated in the pathophysiology of IUGR have been identified. We aimed to investigate the effect of UPI on lung development by identifying metabolic changes during the first seven days of postnatal life. Materials and methods: On gestation day 17, four time-dated pregnant Sprague Dawley rats were randomized to a IUGR group or a control group, which underwent an IUGR protocol comprising bilateral uterine vessel ligation and sham surgery, respectively. On gestation day 22, 39 control and 26 IUGR pups were naturally delivered. The rat pups were randomly selected from the control and IUGR group on postnatal day 7. The pups' lungs were excised for histological, Western blot, and metabolomic analyses. Liquid chromatography mass spectrometry was performed for metabolomic analyses. Results: UPI induced IUGR, as evidenced by the IUGR rat pups having a significantly lower average body weight than the control rat pups on postnatal day 7. The control rats exhibited healthy endothelial cell healthy and vascular development, and the IUGR rats had a significantly lower average radial alveolar count than the control rats. The mean birth weight of the 26 IUGR rats (5.89 ± 0.74 g) was significantly lower than that of the 39 control rats (6.36 ± 0.55 g; p < 0.01). UPI decreased the levels of platelet-derived growth factor-A (PDGF-A) and PDGF-B in the IUGR newborn rats. One-way analysis of variance revealed 345 features in the pathway, 14 of which were significant. Regarding major differential metabolites, 10 of the 65 metabolites examined differed significantly between the groups (p < 0.05). Metabolite pathway enrichment analysis revealed significant between-group differences in the metabolism of glutathione, arginine-proline, thiamine, taurine-hypotaurine, pantothenate, alanine-aspartate-glutamate, cysteine-methionine, glycine-serine-threonine, glycerophospholipid, and purine as well as in the biosynthesis of aminoacyl-tRNA, pantothenate, and CoA. Conclusions: UPI alters lung development and metabolomics in growth-restricted newborn rats. Our findings may elucidate new metabolic mechanisms underlying IUGR-induced altered lung development and serve as a reference for the development of prevention and treatment strategies for IUGR-induced altered lung development.

Kidney Injuries and Evolution of Chronic Kidney Diseases Due to Neonatal Hyperoxia Exposure Based on Animal Studies.

Preterm birth interrupts the development and maturation of the kidneys during the critical growth period. The kidneys can also exhibit structural defects and functional impairment due to hyperoxia, as demonstrated by various animal studies. Furthermore, hyperoxia during nephrogenesis impairs renal tubular development and induces glomerular and tubular injuries, which manifest as renal corpuscle enlargement, renal tubular necrosis, interstitial inflammation, and kidney fibrosis. Preterm birth along with hyperoxia exposure induces a pathological predisposition to chronic kidney disease. Hyperoxia-induced kidney injuries are influenced by several molecular factors, including hypoxia-inducible factor-1α and interleukin-6/Smad2/transforming growth factor-ß, and Wnt/ß-catenin signaling pathways; these are key to cell proliferation, tissue inflammation, and cell membrane repair. Hyperoxia-induced oxidative stress is characterized by the attenuation or the induction of multiple molecular factors associated with kidney damage. This review focuses on the molecular pathways involved in the pathogenesis of hyperoxia-induced kidney injuries to establish a framework for potential interventions.