Experimental test and mechanism analysis of soil crust erosion resistance of rammed earth Great Wall in rainy season.

Rammed earth is a kind of cleaning material, widely used in all kinds of buildings in the world. The Great Wall of ancient China is a typical world cultural site built from rammed earth. The rammed earth Great Wall of Shanhaiguan is close to Bohai Bay, which has suffered from long-term erosion by rain, causing a series of problems such as soil loss, collapse and gully flushing. The protection materials of the rammed earth site have always puzzled scholars. However, during the rainy season, it was found that some of the walls at Xiaowan Gouge and Nantuzhuang Gouge in the Shanhaiguan Great Wall had unwashed traces, the soil surface of the walls was intact, and the anti-erosion ability of the walls was significantly higher than that of other places. In order to explore the reasons for its strong anti-erosion ability in the natural state of rammed earth wall, guide the protection of rammed earth Great Wall, and carry out different experimental tests to explore its anti-erosion reasons and internal mechanisms. Firstly, the characteristics of rammed soil were understood through the composition test of rammed soil, and the indoor and outdoor erosion test was carried out to determine that the anti-erosion reason was the protection of gray-green soil crust. The property and composition of soil crust were determined through the immersion test and genome sequencing. Finally, the protection mechanism of soil crust was analyzed by scanning electron microscopy.

Analysis of influencing factors of asymptomatic arrhythmia in college students / 中国学校卫生

Objective@#To research the prevalence and influencing factors of asymptomatic arrhythmia among college students, and provide scientific basis for heart rate control and health management of asymptomatic arrhythmia among college students.@*Methods@#Using cluster sampling method, 3 012 college students who studied in the First Clinical Medical College of Henan University of Traditional Chinese Medicine and the Second Clinical Medical College of Henan University of Traditional Chinese Medicine were selected as the research objects from September to November 2022. After entering school in autumn (September in 2022), all college students were investigated by questionnaire, and the general data and living habits of asymptomatic arrhythmia college students and normal college students were compared. Logistic regression was used to analyze the influencing factors of asymptomatic arrhythmia among college students.@*Results@#A total of 62 patients with asymptomatic arrhythmia were found. The detection rates of the patients with body mass index(BMI)≥24.0 kg/m 2 , systolic blood pressure(SBP)≥120 mmHg, diastolic blood pressure(DBP)≥80 mmHg, family history of cardiovascular disease, smoking, drinking, exercising less than three times a week, heavy study pressure, irregular work and rest, depression tendency and anxiety tendency were 5.58%, 4.49%, 5.63%, 6.18%, 4.26%, 4.50%, 3.72%, 4.29%, 4.28%, 9.15%,9.03%, which were significantly higher than those of patients with BMI<24.0 kg/m 2, SBP＜120 mmHg, DBP<80 mmHg, no family history of cardiovascular disease, no smoking, no drinking, exercise more than three times a week, little study pressure, regular work and rest, no depression tendency and no anxiety tendency (1.20%, 1.37%, 1.35%, 1.53%, 1.55 %, 1.59%, 1.27%, 1.52%, 1.38%, 1.71%,1.71%), and the differences were statistically significant ( χ 2=45.33, 25.20, 37.74, 32.24, 16.69, 17.25, 19.57, 17.83, 22.36, 37.23,39.42, P <0.01). Logistic regression analysis showed that the higher of BMI,SBP and DBP, family history of cardiovascular disease, smoking, drinking, times of exercise, heavy study pressure, irregular work and rest, depression tendency and anxiety tendency were positively correlated with asymptomatic arrhythmia of college students ( P <0.05).@*Conclusions@#The higher of BMI and blood pressure, family history of cardiovascular diseases, bad living habits and psychological status are related to asymptomatic arrhythmia in college students. It is of great significance to control weight and blood pressure reasonably and maintain good living habits and mental state for preventing and improving asymptomatic arrhythmia.

Network pharmacology-based research on the effect of Radix Astragali on osteosarcoma and the underlying mechanism.

To explore the anti-tumor effects of Radix Astragali on osteosarcoma and its mechanism. We analyzed the PPI network of Radix Astragali's potential targets for treating osteosarcoma and got the hub targets. We used KM curves to screen hub targets that could prolong sarcoma patients' survival time. We performed GO and KEGG enrichment analysis of Radix Astragali's potential targets and predicted Radix Astragali's molecular mechanism and function in treating osteosarcoma. The binding process between the hub targets, which could prolong sarcoma patients' survival time, and Radix Astragali was simulated through molecular docking. PPI network analysis of potential therapeutic targets discriminated 25 hub targets. The KM curves of the hub targets showed there were 13 hub targets that were effective in improving the 5-year survival rate of sarcoma patients. GO and KEGG enrichment demonstrated that Radix Astragali regulates multiple signaling pathways of osteosarcoma. Molecular docking results indicated that Radix Astragali could bind freely to the hub target, which could prolong the sarcoma patient's survival time. Radix Astragali act on osteosarcoma by regulating a signaling network formed by hub targets connecting multiple signaling pathways. Radix Astragali has the potential to become a drug for treating osteosarcoma and prolonging the sarcoma patient's survival time.

A web-based nomogram to predict overall survival for postresection leiomyosarcoma patients with lung metastasis.

To investigate the overall survival of post-resection leiomyosarcoma (LMS) patients with lung metastasis, data of post-resection LMS patients with lung metastasis between 2010 and 2016 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The clinical characteristics and survival data for post-resection LMS patients with lung metastasis at Tianjin Medical University Cancer Hospital & Institute (TJMUCH) between October 2010 and July 2018 were collected. Patients derived from the SEER database and TJMUCH were divided into training and validation cohorts, respectively. Univariate and multivariate Cox regression analyses were performed and a nomogram was established. The area under the curve (AUC) and the calibration curve were used to evaluate the nomogram. A web-based nomogram was developed based on the established nomogram. Eventually, 226 patients from the SEER database who were diagnosed with LMS and underwent primary lesion resection combined with lung metastasis were enrolled in the training cohort, and 17 patients from TJMUCH were enrolled in the validation cohort. Sex, race, grade, tumor size, chemotherapy, and bone metastasis were correlated with overall survival in patients with LMS. The C-index were 0.65 and 0.75 in the SEER and Chinese set, respectively. Furthermore, the applicable AUC values of the ROC curve in the SEER cohort to predict the 1-, 3-, 5- years survival rate were 0.646, 0.682, and 0.689, respectively. The corresponding AUC values in the Chinese cohort were 0.970, 0.913, and 0.881, respectively. The calibration curve showed that the nomogram performed well in predicting the overall survival in post-resection LMS patients with lung metastasis. A web-based nomogram (https://weijunqiang.shinyapps.io/survival_lms_lungmet/) was established. The web-based nomogram (https://weijunqiang.shinyapps.io/survival_lms_lungmet/) is an accurate and personalized tool for predicting the overall survival of post-resection LMS with lung metastasis.

Web-based nomogram to predict postresection risk of distant metastasis in patients with leiomyosarcoma: retrospective analysis of the SEER database and a Chinese cohort.

OBJECTIVES: This study investigated risk factors and constructed an online tool to predict distant metastasis (DM) risk in patients with leiomyosarcoma (LMS) after surgical resection. METHODS: Data regarding patients with LMS who underwent surgical resection between 2010 and 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Data were collected regarding patients with LMS who underwent surgical resection at Tianjin Medical University Cancer Hospital and Institute (TJMUCH) between October 2010 and July 2018. Patients were randomly divided into training and validation sets. Logistic regression analyses were performed; a nomogram was established. The area under the curve (AUC) and calibration curve were used to evaluate the nomogram, which served as the basis for a web-based nomogram. RESULTS: This study included 4461 and 76 patients from the SEER database and TJMUCH, respectively. Age, ethnicity, grade, T stage, N stage, radiotherapy, and chemotherapy were associated with DM incidence. C-index values were 0.815 and 0.782 in the SEER and Chinese datasets, respectively; corresponding AUC values were 0.814 and 0.773, respectively. A web-based nomogram (https://weijunqiang-leimyosarcoma-seer.shinyapps.io/dynnomapp/) was established. CONCLUSIONS: Our web-based nomogram is an accurate and user-friendly tool to predict DM risk in patients with LMS; it can aid clinical decision-making.

Network pharmacology-based research on the effect of angelicin on osteosarcoma and the underlying mechanism.

To explore the antitumor effects of angelicin on osteosarcoma and the underlying mechanism. We aimed to elucidate the mechanism by network pharmacology, molecular docking, and in vitro experiments. We analyzed a PPI network of potential angelicin targets in the treatment of osteosarcoma and identified hub targets. We systematically performed GO and KEGG enrichment analyses of the potential targets of angelicin, and we predicted it function in osteosarcoma treatment and the underlying molecular mechanism. Through molecular docking, the interactions between hub targets and angelicin were simulated, and then, the hub targets of angelicin were identified. Based on these results, we validated the effects of angelicin on osteosarcoma cells by conducting in vitro experiments. The PPI network analysis of potential therapeutic targets identified four apoptosis-related hub targets, namely, BCL-2, Casp9, BAX and BIRC 2. GO and KEGG enrichment analyses demonstrated that angelicin regulates osteosarcoma cell apoptosis. Molecular docking results indicated that angelicin can freely bind to the hub targets listed above. In vitro experiments showed that angelicin promoted osteosarcoma cell apoptosis in a dose-dependent manner and inhibited osteosarcoma cell migration and proliferation in a time- and dose-dependent manner. The RT-PCR results showed that angelicin simultaneously promoted the mRNA expression of Bcl-2 and Casp9 and inhibited the mRNA expression of BAX and BIRC 2. Angelicin promotes osteosarcoma cell apoptosis and inhibits osteosarcoma cell proliferation and migration by activating a signaling network that is composed of hub targets that link multiple signaling pathways. Angelicin could become an alternative drug for the treatment of osteosarcoma.

Multi-dimensional safety risk assessment on coal mines under the profitability dilemma.

China is a major coal producer, with huge differences in coal production and safety situations between the South and the North. Taking province A as an example, its coal enterprises have low output, poor efficiency, backward equipment, and low-quality personnel. The output accounts for 0.08% of the country, and the number of deaths accounts for 2.2% of the country, the safety situation of coal enterprises in province A is severe. In order to study the safety risk situation of coal mines under difficult conditions, this paper screens 98 factor indexes including multiple subjects such as enterprise managers, front-line workers, government supervisors, external environment, work quality, stress factors, economic factors, and other dimensions. For different data, the indicator weights were calculated using triangular fuzzy number, entropy weight method, CRITIC method, and three rough set methods in a total of six methods. The comprehensive weights of the indicators were obtained using the proposed new comprehensive weight method. The current situation of safety work of four coal mining enterprises and three levels of government supervision departments was evaluated, and the evaluation results were compared with other existing data to verify the reliability of the evaluation system. The horizontal comparison of the evaluation results indicates the main problems of each subject; the longitudinal comparison points out the problems that need to be solved with the assistance of higher-level enterprises and the central government, and corresponding suggestions for coal mining enterprises and government departments are put forward to reduce the safety risks of troubled coal mining enterprises.

Research: Construction and validation of elbow function prediction model after supracondylar humerus fracture in children.

This article's objectives are to develop a model to predict children's recovery of elbow function following supracondylar fracture, analyze the risk factors affecting those children's elbow function after surgery, and propose a individualized treatment strategy for elbow function in various children. We retrospectively analyzed clinical data from 410 children with supracondylar humerus fracture. A modeling set and a validation set of kids in the included studies were arbitrarily split into 2 groups on a 7:3 basis. To identify statistically significant risk factors, univariate logistic regression analysis was used. Then, multivariate logistic regression was used with the risk factors, and the best logistic regression model was chosen based on sensitivity and accuracy to create a nomogram; A total of 410 children were included in the study according to the inclusion criteria. Among them, there were 248 males and 162 females, and the fracture type: 147 cases of type IIb and 263 cases of type III. There were no significant changes in the afflicted limb's lateral difference, surgical method, onset season, and number of K-wires, according to univariate logistic regression analysis. Age (P < .001), weight (P < .001), height (P < .001), preoperative elbow soft tissue injury (OR = 1.724, 95% CI: 1.040-2.859, P = .035), sex (OR = 2.220, 95% CI: 1.299-3.794, P = .004), fracture classification (Gartland IIb) (OR = 0.252, 95% CI: 0.149-0.426, P < .001), no nerve injury before surgery (OR = 0.304, 95% CI: 0.155-0.596, P = .001), prying technique (OR = 0.464, 95% CI: 0.234-0.920, P = .028), postoperative daily light time > 2 hours (OR = 0.488, 95% CI: 0.249-0.955, P = .036) has a significant difference in univariate analysis; Multivariate regression analysis yielded independent risk factors: fracture classification; No nerve injury before surgery; The daily light duration after surgery was > 2 hours; soft tissue injury; Age, postoperative cast fixation time. The establishment of predictive model is of significance for pediatric orthopedic clinicians in the daily diagnosis and treatment of supracondylar humerus fracture.

Network pharmacology and molecular docking reveal the mechanism of Angelica dahurica against Osteosarcoma.

Osteosarcoma (OS) is a malignant bone tumor of mesenchymal origin. Angelica dahurica is a typical traditional Chinese herb. Angelica dahurica is used in the treatment of a variety of tumors. However, the studies of Angelica dahurica for OS have not been reported. To investigate Angelica dahurica's potential mechanism of action in the treatment of OS, we used network pharmacology and molecular docking methods in this study. Of which the network pharmacology includes the collection of active ingredients of Angelica dahurica, the collection of predicted targets of Angelica dahurica and predicted targets of OS, the analysis of therapeutic targets of Angelica dahurica, gene ontology (GO) enrichment, and Kyoto encyclopedia of genes and genomes (KEGG) enrichment. The Venn plot performance showed that there were 225 predicted targets of Angelica dahurica for the treatment of OS. The therapeutic targets enrichment analysis results showed that Angelica dahurica treated OS through multiple targets and pathways. Angelica dahurica could affect OS's proliferation, apoptosis, migration, infiltration, and angiogenesis through a signaling network formed by pivotal genes crosstalking numerous signaling pathways. In addition, molecular docking results showed that sen-byakangelicol, beta-sitosterol, and Prangenin, have a relatively high potential to become a treatment for patients with OS and improve 5-year survival in OS patients. We used network pharmacology and molecular docking methods to predict the active ingredients and significant targets of Angelica dahurica for the treatment of OS and, to a certain extent, elucidated the potential molecular mechanism of Angelica dahurica in the treatment of OS. This study provided a theoretical basis for Angelica dahurica in the treatment of OS.

A novel inflammatory signature for evaluating immune microenvironment status in soft tissue sarcoma.

Background: Tumorigenesis and progression are intimately associated with inflammation. However, the inflammatory landscape in soft tissue sarcoma (STS) and its clinical consequences are yet unknown, and more investigation is needed. Methods: RNA-seq expression data for STS and corresponding normal tissues were downloaded from The Cancer Genome Atlas database and the Genotype-Tissue Expression Portal. Differential and prognostic analyses were performed based on known inflammatory response genes from Gene Set Enrichment Analysis (GSEA). We utilized LASSO-Cox analysis to determine hub genes and built an inflammatory score (INFscore) and risk stratification model. Furthermore, a nomogram, including the risk stratification model, was established to predict the prognosis. We further elucidated the characteristics among different risk STS patients by GSEA, gene set variation analysis, and detailed immune infiltration analysis. Finally, the INFscore and risk stratification model in predicting prognosis and depicting immune microenvironment status were verified by pan-cancer analysis. Results: Five hub genes (HAS2, IL1R1, NMI, SERPINE1, and TACR1) were identified and were used to develop the INFscore. The risk stratification model distinguished the immune microenvironment status and evaluated the efficacy of immunotherapy and chemotherapy in STS. The novel nomogram had good efficacy in predicting the prognosis of STS patients. Finally, a pan-cancer investigation verified the association of INFscore with prognosis and immunity. Conclusions: According to the present study, the risk stratification model can be used to evaluate STS prognosis, tumor microenvironment status, immunotherapy, and chemotherapy efficacy. The novel nomogram has an excellent predictive value. Thus, the INFscore and risk stratification model has potential value in assessing the prognosis and immune status of multiple malignancies.

The new horizon of biomarker in melanoma patients: A study based on autophagy-related long non-coding RNA.

ABSTRACT: Autophagy-related long non-coding RNAs (arlncRNAs) play a crucial role in the pathogenesis and development of the tumor. However, there is a lack of systematic analysis of arlncRNAs in melanoma patients.Melanoma data for analysis were obtained from The Cancer Genome Atlas (TCGA) database. By establishing a co-expression network of autophagy-related mRNAs-lncRNAs, we identified arlncRNAs in melanoma patients. We evaluated the prognostic value of arlncRNAs by univariate and multivariate Cox analysis and constructed an arlncRNAs risk model. Patients were divided into high- and low-risk groups based on the arlncRNAs risk score. This model was evaluated by Kaplan-Meier (K-M) analysis, univariate-multivariate Cox regression analysis, and receiver operating characteristic (ROC) curve analysis. Characteristics of autophagy genes and co-expressive tendency were analyzed by principal component analysis and Gene Set Enrichment Analysis (GSEA) functional annotation.Nine arlncRNAs (USP30-AS1, LINC00665, PCED1B-AS1, LINC00324, LINC01871, ZEB1-AS1, LINC01527, AC018553.1, and HLA-DQB1-AS1) were identified to be related to the prognosis of melanoma patients. Otherwise, the 9 arlncRNAs constituted an arlncRNAs prognostic risk model. K-M analysis and ROC curve analysis showed that the arlncRNAs risk model has good discrimination. Univariate and multivariate Cox regression analysis showed that arlncRNAs risk model was an independent prognostic factor in melanoma patients. Principal component analysis and GSEA functional annotation showed different autophagy and carcinogenic status in the high- and low-risk groups.This novel arlncRNAs risk model plays an essential role in predicting of the prognosis of melanoma patients. The model reveals new prognosis-related biomarkers for autophagy, promotes precision medicine, and provides a lurking target for melanoma's autophagy-related treatment.

Development, validation, and visualization of a web-based nomogram for predicting the incidence of leiomyosarcoma patients with distant metastasis.

BACKGROUND: Leiomyosarcoma (LMS) is one of the most common soft tissue sarcomas. LMS is prone to distant metastasis (DM), and patients with DM have a poor prognosis. AIM: In this study, we investigated the risk factors of DM in LMS patients and the prognostic factors of LMS patients with DM. METHODS AND RESULTS: LMS patients diagnosed between 2010 and 2016 were extracted from the Surveillance, Epidemiology, and End Result (SEER) database. Patients were randomly divided into the training set and validation set. Univariate and multivariate logistic regression analyses were performed, and a nomogram was established. The area under the curve (AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram. Based on the nomogram, a web-based nomogram is established. The univariate and multivariate Cox regression analyses were used to assess the prognostic risk factors of LMS patients with DM. Eventually, 2184 patients diagnosed with LMS were enrolled, randomly divided into the training set (n = 1532, 70.14%) and validation set (n = 652, 29.86%). Race, primary site, grade, T stage, and tumor size were correlated with DM incidence in LMS patients. The AUC of the nomogram is 0.715 in training and 0.713 in the validation set. The calibration curve and DCA results showed that the nomogram performed well in predicting the DM risk. A web-based nomogram was established to predict DM's risk in LMS patients (https://wenn23.shinyapps.io/riskoflmsdm/). Epithelioid LMS, in uterus, older age, giant tumor, multiple organ metastasis, without surgery, and chemotherapy had a poor prognosis. CONCLUSIONS: The established web-based nomogram (https://wenn23.shinyapps.io/riskoflmsdm/) is an accurate and personalized tool to predict the risks of LMS developing DM. Advanced age, larger tumor, multiple organ metastasis, epithelioid type, uterine LMS, no surgery, and no chemotherapy were associated with poor prognosis in LMS patients with DM.

Specification and guideline for technical aspects and scanning parameter settings of neonatal lung ultrasound examination.

Lung ultrasound (LUS) is now widely used in the diagnosis and monitor of neonatal lung diseases. Nevertheless, in the published literatures, the LUS images may display a significant variation in technical execution, while scanning parameters may influence diagnostic accuracy. The inter- and intra-observer reliabilities of ultrasound exam have been extensively studied in general and in LUS. As expected, the reliability declines in the hands of novices when they perform the point-of-care ultrasound (POC US). Consequently, having appropriate guidelines regarding to technical aspects of neonatal LUS exam is very important especially because diagnosis is mainly based on interpretation of artifacts produced by the pleural line and the lungs. The present work aimed to create an instrument operation specification and parameter setting guidelines for neonatal LUS. Technical aspects and scanning parameter settings that allow for standardization in obtaining LUS images include (1) select a high-end equipment with high-frequency linear array transducer (12-14 MHz). (2) Choose preset suitable for lung examination or small organs. (3) Keep the probe perpendicular to the ribs or parallel to the intercostal space. (4) Set the scanning depth at 4-5 cm. (5) Set 1-2 focal zones and adjust them close to the pleural line. (6) Use fundamental frequency with speckle reduction 2-3 or similar techniques. (7) Turn off spatial compounding imaging. (8) Adjust the time-gain compensation to get uniform image from the near-to far-field.

Construction, validation and, visualization of a web-based nomogram to identify the best candidates for primary tumor resection in advanced cutaneous melanoma patients.

Background: Existing studies have shown whether primary site resection (PSR) in cutaneous melanoma (CM) patients with stage IV is controversial. Our study aimed to identify the clinical characteristics of CM patients with stage IV who benefited from PSR on a population-based study. Methods: We retrospectively reviewed stage IV CM patients in the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015. Patients were divided into surgical and non-surgical groups according to whether PSR was performed or not. According to the median cancer-specific survival (CSS) time of the non-surgery group, the surgical group was divided into the surgery-benefit group and the non-surgery-benefit group. Multivariate cox regression analysis was used to explore independent CSS prognostic factors in the surgical group. Then, based on the independent prognostic factors of the surgical group, we established a web-based nomogram based on logistics regression. Results: A total of 574 stage IV CM patients were included in our study, and 491 (85.60%) patients were included in the surgical group. The clinical characteristics (benefit group and non-benefit group) included age, M stage, lesion location, and ulceration status. These independent prognostic factors were includeed to construct a web-based nomogram. Conclusions: We constructed a web-based nomogram. This model was suitable for identifying the best candidates suitable for PSR in stage IV CM patients.

Network pharmacology, molecular docking and bioinformatics reveal the mechanism of Tripterygii Wilfordii against Osteosarcoma.

Osteosarcoma (OS) is a malignant bone tumor of mesenchymal origin. Tripterygii Wilfordii (TW) is a traditional Chinese medicine widely used for its anti-inflammatory and immunomodulatory effects. Various components of TW have been shown to have antitumor effects, however, no systematic study has been conducted to prove the anti-OS effects of TW. This study aimed to investigate the effects of TW on OS and its mechanism based on network pharmacology and molecular docking. The web pharmacology section includes the gathering of the active components of TW, the collection of predicted targets of TW and OS-related targets, the analysis of therapeutic targets of TW, the enrichment of gene ontology (GO), and the enrichment of Kyoto Encyclopedia of Genes and Genomes (KEGG). The Veen diagram showed 451 targets for OS treatment in TW. The therapeutic target enrichment analysis results showed that TW treated OS via multiple targets and pathways. TW can affect OS proliferation, apoptosis, migration, infiltration, and angiogenesis through a signaling network formed by hub genes that cascade through numerous signaling pathways. In addition, molecular docking results showed that triptolide, kaempferol, and 5,8-Dihydroxy-7-(4-hydroxy-5-methyl-coumarin-3)-coumarin have relatively high potential to become drugs for patients with OS and improve the 5-year survival rate of patients with OS. Network pharmacology and molecular docking suggest that TW affects the biological behavior of OS through multiple pathways involving multiple targets, such as proliferation, apoptosis, migration, and infiltration. Upregulation of the cellular tumor antigen p53 (TP53) gene and downregulation of peroxisome proliferator-activated receptor gamma (PPARG) and signal transducer and activator of transcription 1-alpha/beta (STAT1) genes can prolong the survival time of patients with OS. Triptolide, kaempferol, and 5,8-Dihydroxy-7-(4-hydroxy-5 methyl-coumarin-3)-coumarin have a relatively high potential to become a treatment for patients with OS and improve 5-year survival of OS patients.

A predictive web-based nomogram for the early death of patients with lung adenocarcinoma and bone metastasis: a population-based study.

OBJECTIVE: To identify risk factors and develop predictive web-based nomograms for the early death of patients with bone metastasis of lung adenocarcinoma (LUAD). METHODS: Patients in the Surveillance, Epidemiology, and End Results database diagnosed with bone metastasis of LUAD between 2010 and 2016 were included and randomly divided into training and validation sets. Early death-related risk factors (survival time ≤7 months) were evaluated by logistic regression. Two predictive nomograms were established and validated by calibration curves, receiver operating characteristic curves, and decision curve analysis. RESULTS: A total of 9189 patients (56.59%) died from all causes within 7 months of being diagnosed, including 8585 patients (56.67%) who died from cancer-specific causes. Age >65 years, sex (men), T stage (T3 and T4), N stage (N2 and N3), brain metastasis, and liver metastasis were risk factors for all-cause and cancer-specific early death. The area under the curves of the nomograms for all-cause and cancer-specific early death prediction were 0.754 and 0.753 (training set) and 0.747 and 0.754 (validation set), respectively. Further analysis showed that the two nomograms performed well. CONCLUSIONS: Our two web-based nomograms for all-cause and cancer-specific early death provide valuable tools for predicting early death in these patients.

Construction, validation and, visualization of a web-based nomogram for predicting the overall survival and cancer-specific survival of leiomyosarcoma patients with lung metastasis.

BACKGROUND: This study sought to assess the prognostic factors for leiomyosarcoma (LMS) patients with lung metastasis and construct web-based nomograms to predict overall survival (OS) and cancer-specific survival (CSS). METHOD: Patients diagnosed with LMS combined with lung metastasis between 2010 and 2016 were identified in the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly divided into a training set and a testing set. The X-tile analysis provides the best age and tumor size cut-off point, and changes continuous variables into categorical variables. The independent prognostic factors were determined by Cox regression analysis, and 2 nomograms were established. Receiver operating characteristic curves and calibration curves were used to evaluate the nomograms. Based on the nomograms, 2 web-based nomograms were established. RESULTS: Two hundred and twenty-eight cases were included in the OS nomogram construction, and were randomly divided into a training set (n=160) and a validation set (n=68). Age, T stage, bone metastasis, surgery, chemotherapy, marital status, tumor size, and tumor site were found to be correlated with OS. One hundred and eighty-three cases were enrolled in the CSS nomogram construction, and randomly divided into a training set (n=129) and a validation set (n=54). Age, bone metastasis, surgery, chemotherapy, tumor size, and tumor site were found to be correlated with CSS. Two nomograms were established to predict OS and CSS. In the training set, the areas under the curve of the nomogram for predicting 1-, 2-, and 3-year OS were 0.783, 0.830, and 0.832, respectively, and those for predicting 1-, 2-, and 3-year CSS were 0.889, 0.777, and 0.884, respectively. Two web-based nomograms were established to predict OS (https://wenn23.shinyapps.io/lmslmosapp/), and CSS (https://wenn23.shinyapps.io/lmslmcssapp/). CONCLUSION: The developed web-based nomogram is a useful tool for accurately analyzing the prognosis of LMS patients with lung metastasis, and could help clinical doctors to make personalized clinical decisions.

International Expert Consensus and Recommendations for Neonatal Pneumothorax Ultrasound Diagnosis and Ultrasound-guided Thoracentesis Procedure.

Pneumothorax (PTX) represents accumulation of the air in the pleural space. A large or tension pneumothorax can collapse the lung and cause hemodynamic compromise, a life-threatening disorder. Traditionally, neonatal pneumothorax diagnosis has been based on clinical images, auscultation, transillumination, and chest X-ray findings. This approach may potentially lead to a delay in both diagnosis and treatment. The use of lung US in diagnosis of PTX together with US-guided thoracentesis results in earlier and more precise management. The recommendations presented in this publication are aimed at improving the application of lung US in guiding neonatal PTX diagnosis and management.

Protocol and Guidelines for Point-of-Care Lung Ultrasound in Diagnosing Neonatal Pulmonary Diseases Based on International Expert Consensus.

Ultrasound is a safe bedside imaging tool that obviates the use of ionizing radiation diagnostic procedures. Due to its convenience, the lung ultrasound has received increasing attention from neonatal physicians. Nevertheless, clear reference standards and guideline limits are needed for accurate application of this diagnostic modality. This document aims to summarize expert opinions and to provide precise guidance to help facilitate the use of the lung ultrasound in the diagnosis of neonatal lung diseases.

An improved biopsy technique for rabbits with VX2 bone tumors.

The present study aimed to investigate the efficacy of an improved biopsy method for reducing local exudation and metastasis. After resecting the VX2 tumor in cancer-bearing VX2 rabbits, a tumor cell suspension was prepared. Tumor cells were transplanted into the tibias of 20 rabbits in order to establish a bone tumor model. These adult rabbits underwent a puncture procedure after 2 weeks. All the left tibias were punctured using the improved biopsy method (the experimental group), where bolt closures were implanted into puncture holes through the metallic casing following biopsy. All the right tibias were punctured using a traditional biopsy technique (the control group). Color Doppler ultrasonography was used to assess the exudation of each puncture hole after 1 h. After 7 days, a pathological study was performed on the soft tissue near each puncture hole. The success rate of the bone model was 100% for the 20 rabbits. The exudation rate in the experimental group was lower than that in the control group (25 vs. 80%, respectively; χ2=12.13; P<0.05). The tumor-spreading rate in the experimental group was lower than that in the control group (35 vs. 85%, respectively; χ2=10.41; P<0.05). Overall, it was shown that the improved biopsy method can prevent local bleeding and tumor metastasis.