Green space in the living environment has been linked to the development of allergic diseases. However, evidence regarding early-onset allergy in toddlers was limited, and the critical exposure window remained unclear. We aimed to investigate associations between residential greenness with allergic diseases in early life.This prospective birth cohort study included 522 mother-child pairs in Guangzhou, China. We quantified prenatal, postnatal, and early-life (i.e., the first 1000 days of life) residential greenness, estimated from remote satellite data using normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and tree cover. We identified physician-diagnosed allergic diseases (eczema, atopic dermatitis, urticaria, allergic rhinitis, allergic conjunctivitis, food allergy, and asthma) based on medical records at age 2 years. Generalized linear regression was conducted to examine the associations of greenness with allergic outcomes.The ranges of residential NDVI and EVI values in 500-m buffer during early life were 0.06-0.70 and 0.03-0.46, respectively. We found a 0.1 unit increase of NDVI in 500-m buffer throughout early life was associated with higher odds of any allergic diseases (prenatal: OR [odds ratio], 1.25; 95%CI, 1.02-1.53; postnatal: OR, 1.24; 95%CI, 1.02-1.52; early-life: OR, 1.25, 95%CI: 1.02-1.53) and higher odds of eczema (prenatal: OR, 1.28; 95%CI, 1.04-1.59; postnatal: OR, 1.24; 95%CI, 1.01-1.54; early-life: OR, 1.26, 95%CI: 1.02-1.56). The results were consistent when using EVI as a proxy for greenness. We only observed that prenatal exposure to the highest tertile of NDVI-500 was adversely associated with any allergic diseases (OR, 1.63; 95%CI, 1.03-2.58) and eczema (OR, 1.70; 95%CI: 1.04-2.78) compared with the lowest tertile.This study identified detrimental associations of residential greenness with allergic diseases especially eczema among toddlers, and pregnancy appears to be the critical exposure window. Our findings highlighted the importance of urban planning to develop friendly-green neighborhood to improve maternal and child health. 

The associations between residential greenness and allergic diseases in Chinese toddlers: A birth cohort study.

Prediction of Microvascular Invasion in Solitary AFP-Negative Hepatocellular Carcinoma ≤ 5 cm Using a Combination of Imaging Features and Quantitative Dual-Layer Spectral-Detector CT Parameters.

Abstract Objectives In this study, we developed a radiomic signature for the classification of benign lipid-poor adenomas, which may potentially help clinicians limit the number of unnecessary investigations in clinical practice. Indeterminate adrenal lesions of benign and malignant nature may exhibit different values of key radiomics features. Methods Patients who had available histopathology reports and a non-contrast-enhanced CT scan were included in the study. Radiomics feature extraction was done after the adrenal lesions were contoured. The primary feature selection and prediction performance scores were calculated using the least absolute shrinkage and selection operator (LASSO). To eliminate redundancy, the best-performing features were further examined using the Pearson correlation coefficient, and new predictive models were created. Results This investigation covered 50 lesions in 48 patients. After LASSO-based radiomics feature selection, the test dataset’s 30 iterations of logistic regression models produced an average performance of 0.72. The model with the best performance, made up of 13 radiomics features, had an AUC of 0.99 in the training phase and 1.00 in the test phase. The number of features was lowered to 5 after performing Pearson’s correlation to prevent overfitting. The final radiomic signature trained a number of machine learning classifiers, with an average AUC of 0.93. Conclusions Including more radiomics features in the identification of adenomas may improve the accuracy of NECT and reduce the need for additional imaging procedures and clinical workup, according to this and other recent radiomics studies that have clear points of contact with current clinical practice. Clinical relevance statement The study developed a radiomic signature using unenhanced CT scans for classifying lipid-poor adenomas, potentially reducing unnecessary investigations that scored a final accuracy of 93%. Key Points • Radiomics has potential for differentiating lipid-poor adenomas and avoiding unnecessary further investigations. • Quadratic mean, strength, maximum 3D diameter, volume density, and area density are promising predictors for adenomas. • Radiomics models reach high performance with average AUC of 0.95 in the training phase and 0.72 in the test phase. 

Radiomics in the characterization of lipid-poor adrenal adenomas at unenhanced CT: time to look beyond usual density metrics.

Background Animal experiments and clinical trials have revealed a potential relationship between sleep disorders and asthma. However, the associations between these factors remain unclear. Material and methods We searched PubMed, Embase, Web of Science and Cochrane Library databases for eligible studies published before 30 December 2022. Studies investigating the association between sleep disorders (insomnia, poor sleep quality and insufficient sleep time) and asthma were selected. Sleep disorders were assessed using questionnaires, interviews, or medical records. Asthma was diagnosed based on medical history and drug use. The Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality checklist were employed for quality assessment. We used OR with 95% CI as the effect measures and forest plots to display the results. Heterogeneity was evaluated using I2 statistics and subgroup analyses were performed for bias analysis. Publication bias was evaluated using the funnel plots and Egger’s test. Results Twenty-three studies were included in the primary analysis, which suggested a positive association between sleep disorders and asthma (OR: 1.38, 95% CI 1.10 to 1.74). Subgroup analyses were conducted according to the study design, age, family history of asthma and type of sleep disorders. We did not find any association between sleep disorders and asthma in children aged ˂12 years (OR: 1.13, 95% CI 0.97 to 1.32). The association was insignificant in studies where the family history of asthma was adjusted for (OR: 1.16, 95% CI 0.94 to 1.42). Funnel plot and Egger’s test indicated a significant publication bias. Conclusion Sleep disorders are associated with an increased prevalence and incidence of asthma. However, the quality of the evidence was low because of potential biases. PROSPERO registration number CRD42023391989.

Association of sleep disorders with asthma: a meta-analysis

Clinical application study on miR-98-5p as a prognostic biomarker in hepatocellular carcinoma.

Preoperative MRI features for characterization of vessels encapsulating tumor clusters and microvascular invasion in hepatocellular carcinoma

Background It is difficult for radiologists to differentiate adrenal lipid-poor adenomas from non-adenomas; nevertheless, this differentiation is important as the clinical interventions required are different for adrenal lipid-poor adenomas and non-adenomas. Purpose To develop an unenhanced computed tomography (CT)-based radiomics model for identifying adrenal lipid-poor adenomas to assist in clinical decision-making. Materials and methods Patients with adrenal lesions who underwent CT between January 2015 and August 2021 were retrospectively recruited from two independent institutions. Patients from institution 1 were randomly divided into training and test sets, while those from institution 2 were used as the external validation set. The unenhanced attenuation and tumor diameter were measured to build a conventional model. Radiomics features were extracted from unenhanced CT images, and selected features were used to build a radiomics model. A nomogram model combining the conventional and radiomic features was also constructed. All the models were developed in the training set and validated in the test and external validation sets. The diagnostic performance of the models for identifying adrenal lipid-poor adenomas was compared. Results A total of 292 patients with 141 adrenal lipid-poor adenomas and 151 non-adenomas were analyzed. Patients with adrenal lipid-poor adenomas tend to have lower unenhanced attenuation and smoother image textures. In the training set, the areas under the curve of the conventional, radiomic, and nomogram models were 0.94, 0.93, and 0.96, respectively. There was no difference in diagnostic performance between the conventional and nomogram models in all datasets (all p < 0.05). Conclusions Our unenhanced CT-based nomogram model could effectively distinguish adrenal lipid-poor adenomas. The diagnostic power of conventional unenhanced CT imaging features may be underestimated, and further exploration is worthy.

/pdf/can-radiomics-provide-additional-diagnostic-value-for-hu90eg47.pdf

Can Radiomics Provide Additional Diagnostic Value for Identifying Adrenal Lipid-Poor Adenomas From Non-Adenomas on Unenhanced CT?

Background: Previous studies have linked allergic symptoms to sleep in children, but the associations might be different when considering different types of allergic symptoms or sleep outcomes. Moreover, the combined effects of multiple allergic symptoms remain unclear in early life. This study aimed to investigate the associations between multiple allergic symptoms and sleep outcomes in early life. Methods: We included 673 toddlers aged 2 years from a birth cohort in Guangzhou, China. We identified allergic symptoms (skin, eyes and nose, gastrointestinal tract, mouth and lips, and wheeze) within 2 years via standard questionnaires. Sleep outcomes including sleep duration and quality over the past month were assessed based on the Chinese version of the Brief Infant Sleep Questionnaire. Associations between allergic symptoms and sleep outcomes were examined using multivariable linear regression and logistic regression. Results: Compared to children without allergic symptoms, children with allergic nasal and ocular symptoms had higher odds of frequent nighttime awakenings (OR = 1.41; 95% CI: 1.03, 1.93) and irregular sleep (OR = 1.45, 95% CI: 1.05, 2.00); children with allergic gastrointestinal symptoms slept 0.28 h less during nighttime (95% CI: −0.48, −0.07) and 0.25 h less per day (95% CI: −0.43, −0.08), and had 59% higher odds of irregular sleep (95% CI: 1.24, 2.04). We also found significant association of multiple allergic symptoms with shortened nighttime sleep duration and increased irregular sleep. Whereas, allergic skin, mouth and lips, and wheeze symptoms were not significantly associated with sleep outcomes. Conclusion: Allergic symptoms within 2 years of age were adversely associated with sleep outcomes, which highlight the importance of early screening of allergic symptoms in toddlers in order to improve their sleep outcomes.

/pdf/association-of-allergic-symptoms-in-the-first-2-years-of-1148g4gb.pdf

Association of Allergic Symptoms in the First 2 Years of Life With Sleep Outcomes Among Chinese Toddlers

Purpose This study aimed to develop a repeatable MRI-based machine learning model to differentiate between low-grade gliomas (LGGs) and glioblastoma (GBM) and provide more clinical information to improve treatment decision-making. Methods Preoperative MRIs of gliomas from The Cancer Imaging Archive (TCIA)–GBM/LGG database were selected. The tumor on contrast-enhanced MRI was segmented. Quantitative image features were extracted from the segmentations. A random forest classification algorithm was used to establish a model in the training set. In the test phase, a random forest model was tested using an external test set. Three radiologists reviewed the images for the external test set. The area under the receiver operating characteristic curve (AUC) was calculated. The AUCs of the radiomics model and radiologists were compared. Results The random forest model was fitted using a training set consisting of 142 patients [mean age, 52 years ± 16 (standard deviation); 78 men] comprising 88 cases of GBM. The external test set included 25 patients (14 with GBM). Random forest analysis yielded an AUC of 1.00 [95% confidence interval (CI): 0.86–1.00]. The AUCs for the three readers were 0.92 (95% CI 0.74–0.99), 0.70 (95% CI 0.49–0.87), and 0.59 (95% CI 0.38–0.78). Statistical differences were only found between AUC and Reader 1 (1.00 vs. 0.92, respectively; p = 0.16). Conclusion An MRI radiomics-based random forest model was proven useful in differentiating GBM from LGG and showed better diagnostic performance than that of two inexperienced radiologists.

/pdf/preoperative-contrast-enhanced-mri-in-differentiating-gk2mcvba.pdf

Preoperative Contrast-Enhanced MRI in Differentiating Glioblastoma From Low-Grade Gliomas in The Cancer Imaging Archive Database: A Proof-of-Concept Study

Emphysematous pyelonephritis (EPN) is a potentially life-threatening disease caused by a gas-producing necrotizing bacterial infection that involves the renal parenchyma, collecting system, and/or perinephric tissue. EPN is often complicated by a previous diagnosis of diabetes mellitus, and venous air bubbles are an uncommon complication of it. We describe a 52-year-old woman who was admitted in coma, with a history of vomiting, and was found to have EPN with air bubbles in the uterine veins. We discuss the presentation, diagnosis, and pathogenesis of this uncommon but clinically significant event, and briefly review other case reports of venous gas or thrombosis caused by EPN.We report the case of a 52-year-old woman with past history of type 2 diabetes mellitus, presenting with loss of consciousness after vomiting for half a day. Abdominal computed tomography scan revealed unilateral EPN with air bubbles in the uterine veins. The blood, pus, and urine cultures were positive for extended-spectrum beta-lactamase-producing Escherichia coli. The patient's condition improved well after conservative management comprising supportive measures, broad-spectrum antibiotics, percutaneous drainage therapy, and an open operation.Venous air bubbles are rare but fatal complication of EPN. Early diagnosis and treatment are critical to ensure good results. 

/pdf/venous-gas-caused-by-emphysematous-pyelonephritis-a-case-1o5remwq.pdf

Venous gas caused by emphysematous pyelonephritis: a case report and review of literature

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