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Background Bisphenol A (BPA) is a plasticizer with high production and ubiquitous usage in polycarbonate plastics and epoxy resins. The association between prenatal or postnatal exposure to BPA and childhood wheeze/asthma has not been well established. Our study aimed to provide further justification for the current studies. Methods Studies were searched from PubMed, Web of Science, Scopus and Embase from inception until Sep 15, 2020. Meta-analysis was performed to calculate pooled adjusted odds ratios (aOR). The methodological quality of included studies was assessed by using the Newcastle Ottawa Scale (NOS). Results Of 2,814 screened articles, 9 studies with 3,885 participants were included in the final analysis. When all studies were pooled, postnatal exposure to BPA was associated with a higher risk of childhood asthma (aOR =1.43; 95% CI: 1.28-1.59) or childhood wheeze (aOR =1.38; 95% CI: 1.18-1.62). Prenatal exposure to BPA had a small but significant increased risk of childhood asthma (aOR =1.17; 95% CI: 1.01-1.34). An increased risk of childhood wheeze was related to prenatal exposure to BPA at 16 weeks' gestation (aOR =1.29; 95% CI: 1.07-1.55), but not at 26 weeks' gestation (aOR =1.07; 95% CI: 0.88-1.29) nor at random-time gestation (aOR =1.02; 95% CI: 0.89-1.16). Conclusions Prenatal and postnatal exposure to BPA was related to an increased risk of childhood asthma. However, only postnatal and early gestational exposure (at 16 weeks) to BPA could induce the risk of childhood wheeze, but not late gestational exposure (at 26 weeks).

The effect of unilateral and bilateral bone-filling mesh containers (BFC) on osteoporotic vertebral compression fracture (OVCF) was analyzed by the finite element method. The CT scan data of the T12-L2 vertebral body were obtained from a healthy female volunteer with no history of lumbar spine injury or obvious abnormality of vertebral body morphology. The normal finite element model of the T12-L2 vertebral body and the finite element model of osteoporosis were established, and the models were validated. The L1 in the normal model of the vertebral body was used to simulate the vertebral compression fracture, after which the unilateral and bilateral BFC were simulated to establish models representing the two surgical approaches. We analyzed changes in the deformation and von Mises stress in vertebral bodies and intervertebral discs in the two models under seven working conditions (axial direction, anteflexion, rear protraction, left-side bending, right-side bending, left rotation, and right rotation) and found that the unilateral and bilateral approaches are biomechanically comparable, with no statistical difference between the two overall models.

Objective: To establish and verify the validity of a three-dimensional finite element model of the thoracolumbal segments T12-L2; the stress distribution of the model was analyzed, providing a theoretical basis for finite element analysis of thoracolumbal segment fracture as well as a surgical model. Methods: A healthy female volunteer with no history of lumbar spine injury was selected to obtain CT scan data of the T12-L2 vertebral bodies. Mimics 3D reconstruction software was used to generate the T12-L2 3D model, and surface mesh and body mesh were generated by smoothing treatment and mesh division. The normal finite element model of the T12-L2 vertebral bodies and the finite element model of osteoporosis were established with Ansys finite element software. Under a loading force of 500 N vertically downward and a load of 7.5 N•m bending moment, seven operating conditions were simulated to analyze the displacement and stress distribution of each vertebral body and intervertebral disc, and to verify the effectiveness of the model. Results: There were 31,901 nodes and 64,244 elements in the thoracolumbar T12-L2 three-dimensional finite element model. These results were similar to the conclusions found in a review of the domestic and global literature, and the finite element model was validated. Conclusions: The results of this experiment can provide a practical reference for clinical work and help to establish a three-dimensional finite element model of the thoracolumbar junction.

Background Lung nodules are a diagnostic challenge. Current clinical management of lung nodule patients is inefficient and therefore causes patient misclassification, which increases healthcare expenses. However, a precise and robust lung nodule classifier to minimize discomfort for patients and healthcare costs is still lacking. The aim of the present protocol is to evaluate the effectiveness of using a liquid biopsy classifier to diagnose nodules compared to physician estimates and whether the classifier can reduce the number of unnecessary biopsies in benign cases. Methods A prospective cohort of 10,560 patients enrolled at 23 clinical centers in China with non-calcified pulmonary nodules, ranging from 0.5 to 3 cm in diameter, indicated by LDCT or CT will be included. After signed consent forms, the participants' pulmonary nodules will be assessed using three evaluation tools: (I) physician cancer probability estimates (II) validated lung nodule risk models, including Mayo Clinic and Veteran's Affairs models (III) ctDNA methylation classifier previously established. Each patient will undergo LDCT/CT follow-ups for 2 to 3 years and their information and one blood sample will be collected at baseline, 3, 6, 12, 24 and 36 months. The primary study outcomes will be the diagnostic accuracy of the methylation classifier in the cohort. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) will be used to compare the diagnostic value of each testing tool in differentiating benign and malignant pulmonary nodules. Discussion We are conducting an observational study to explore the accuracy of using a ctDNA methylation classifier for incidental lung nodules diagnosis. Trial registration Clinicaltrials.gov NCT03651986.

Objective As a result of the pandemic of COVID‐19, the public have been experiencing psychological distress. However, the prevalence of psychological distress during the COVID‐19 pandemic remains unknown. Our objective was to evaluate the prevalence of psychological distress during COVID‐19 outbreak and their risk factors, especially their internal paths and causality. Methods A nationwide cross‐sectional survey of the prevalence of mental disorders was conducted. We used Hospital Anxiety and Depression Scale (HADS) to estimate the prevalence of anxiety and depression. The internal paths and the causality of the psychological health were analyzed using a structural equation modeling (SEM) approach. Results A total of 24,789 respondents completed the survey. We found that the overall prevalence of anxiety, depression, combination of anxiety, and depression were 51.6% (95% CI: 51.0–52.2), 47.5% (95% CI: 46.9–48.1), and 24.5% (95% CI: 24.0–25.0), respectively. The risk of psychological disorders in men was higher than that in women. The status of psychological health was different across different age groups, education levels, occupations, and income levels. The SEM analysis revealed that inadequate material supplies, low income, low education, lack of knowledge or confidence of the epidemic, and lack of exercise are major risk factors for psychological distress. Conclusions The evidence from this survey poses serious challenges related to the high prevalence of psychological distress, but also offers strategies to deal with the mental health problems caused by the COVID‐19 pandemic., In national cross‐sectional survey with largest participants in china, we pose serious challenges related to the high prevalence of psychological distress, find out major risk factors for them, and then offer evidence‐based strategies to deal with the mental health problems caused by the COVID‐19 pandemic. Our research also provides evidences for other countries suffering from the COVID‐19 to take public health interventions to relieve the public psychological pressure.

UNSTRUCTURED Dear Editor, Per your instruction, I have submitted a formal request to withdraw our manuscript 18108 on June 11th with an explanation for the withdraw and a scan of the signed letter. The same letter has been uploaded to your online system as well. I am sending this withdraw letter again due to the “request for a revised manuscript” email get to us again! Feel free to contact me should you have any question. But, please help DO NOT send any further junk mail to 40+ co-authors. It is really bad that we have submitted the withdraw petition several times with an explanation, but the system is still sending emails to all authorships. Best regards, Jian-Bing Fan (the corresponding author)