Left atrial shortening fraction to predict fetal cardiac abnormalities and dysfunction in gestational diabetes mellitus.

Objective: To evaluate the diagnostic efficiency of left atrial shortening fraction (LASF) in the detection of fetal cardiac abnormalities and dysfunction in patients with gestational diabetes mellitus (GDM). Methods: In this study, we enrolled 256 pregnant women and divided them into GDM group (n = 156) and control group (n = 100). Fetal echocardiography was performed at 24-28 weeks of gestation to measure the LASF and interventricular septum (IVS) thickness. Based on IVS thickness, the GDM group was subdivided into the septal hypertrophy group (GDM I, n = 62) and non-septal hypertrophy group (GDM II, n = 94). LASF and IVS thickness were compared between the GDM and control groups and between GDM I and GDM II groups. Receiver operating characteristic (ROC) analysis was performed to determine the diagnostic accuracy of LASF in predicting septal hypertrophy. Results: The GDM group had a larger IVS thickness (P < 0.05) but a lower LASF level (P < 0.001) than those of the control group. GDM I group had significantly lower LASF level than that in the GDM II group (P < 0.001). At 38.41% as the cutoff value, the LASF can predict septal hypertrophy with diagnostic sensitivity and specificity of 96.7% and 65.2%, respectively. Conclusion: Fetal GDM are more likely to induce septal hypertrophy and ventricular dysfunction. LASF is a good indicator of septal hypertrophy or early diastolic dysfunction without septal hypertrophy.

The LncRNA MIR503HG/miR-224-5p/TUSC3 Signaling Cascade Suppresses Gastric Cancer Development via Modulating ATF6 Branch of Unfolded Protein Response.

BACKGROUND: Unfolded protein response (UPR)-mediated tumor-promoting functions have been identified in multiple cancers, and this study focused on investigating the role and molecular mechanisms of UPR in modulating gastric cancer (GC) pathogenesis. METHODS: The bioinformatics analysis was performed to examine the expression status of cancer associated genes in patients with stomach adenocarcinoma (STAD) and predict the targeting sites of miR-224-5p with LncRNA MIR503HG and TUSC3. Genes expressions were quantified by Real-Time qPCR, Western Blot and immunohistochemistry (IHC). Cell proliferation, viability, apoptosis and mobility were evaluated by MTT assay, trypan blue staining assay, flow cytometer and transwell assay, respectively. The binding sites were validated by dual-luciferase reporter gene system assay. RESULTS: LncRNA MIR503HG and TUSC3 were downregulated, but miR-224-5p was upregulated in GC tissues and cells, in contrast with their normal counterparts. Further gain- and loss-of-function experiments validated that the malignant phenotypes in GC cells, including cell proliferation, invasion, epithelial-mesenchymal transition (EMT) and tumorigenesis, were negatively regulated by LncRNA MIR503HG. Mechanistically, LncRNA MIR503HG upregulated TUSC3 in GC cells through sponging miR-224-5p, resulting in the repression of GC progression. Finally, we validated that knock-down of ATF6, but not other two branches of UPR (PERK1 and IRE1), partially rescued cell proliferation and EMT in the GC cells with LncRNA MIR503HG overexpression. CONCLUSIONS: Targeting the LncRNA MIR503HG/miR-224-5p/TUSC3 signaling cascade suppressed ATF6-mediated UPR, resulting in the blockage of GC development.

Undifferentiated intimal sarcoma of the pulmonary artery: A case report.

BACKGROUND: Since 1923, only a few hundred cases of pulmonary arterial sarcoma (PAS) have been reported. It is easy for PAS to be misdiagnosed as pulmonary thromboembolism, which makes treatment difficult. The median survival time without surgical treatment for PAS is only 1.5-3 mo. Echocardiography is widely used in screening for pulmonary artery space-occupying lesions in patients with chest pain, dyspnea, and cough; furthermore, it is typically considered the first imaging examination for patients with PAS. CASE SUMMARY: In May 2017, a 39-year-old male patient experienced chest pain with no particular obvious cause. At that time, the cause was thought to be pulmonary embolism. In July 2017, positron emission tomography-computed tomography revealed space-occupying lesions in the right lung and multiple metastases in both lungs. The lesions of the right lung were biopsied, and pathology revealed undifferentiated sarcoma. Chemotherapy had been performed since July 2017 in another hospital. In December 2019, the patient was admitted to our hospital for the sake of CyberKnife treatment. Echocardiography suggested: (1) A right ventricular outflow tract (RVOT) solid mass of the main pulmonary artery; and (2) mild pulmonary valve regurgitation. Ultrasonography showed the absence of a thrombus in the deep veins of either lower limb. CONCLUSION: PAS is a single, central space-occupying lesion involving the RVOT and pulmonary valve. Echocardiography of PAS has its own characteristics.

A mixed logit model with mean-variance heterogeneity to investigate factors of crash occurrence.

This study thoroughly investigated factors affecting crash occurrence using detailed data of crash, traffic condition and freeway geometries. To fully account for heterogeneity induced by unobserved characteristics of crash factors, a mixed logit model with mean-variance heterogeneity was estimated as an alternative to the commonly used mixed logit model and the fixed parameters logit model. Results indicate that the mixed logit model with mean-variance heterogeneity could improve the goodness-of-fit and was more flexible in accounting for unobserved heterogeneity compared with its counterparts. Additionally, by allowing means and variances of random parameters to be estimable functions of explanatory variables, the safety effect of interactions among multiple factors was concluded, for example: (1) sharp curves resulted in an increasing risk of crash and the rate of increase was positively correlated with the distance travelled by vehicles along a steep downgrade; (2) the adverse safety effect of steep downgrade increased with the distance covered by vehicles, especially for segments with high proportion of heavy trucks; (3) downhill segments with steep slopes were particularly dangerous. Findings from this study are expected to provide an insightful knowledge to the mechanism of crash occurrence and should be beneficial to design and manage safer freeways.

Unfolded protein response in colorectal cancer.

Colorectal cancer (CRC) is a gastrointestinal malignancy originating from either the colon or the rectum. A growing number of researches prove that the unfolded protein response (UPR) is closely related to the occurrence and progression of colorectal cancer. The UPR has three canonical endoplasmic reticulum (ER) transmembrane protein sensors: inositol requiring kinase 1 (IRE1), pancreatic ER eIF2α kinase (PERK), and activating transcription factor 6 (ATF6). Each of the three pathways is closely associated with CRC development. The three pathways are relatively independent as well as interrelated. Under ER stress, the activated UPR boosts the protein folding capacity to maximize cell adaptation and survival, whereas sustained or excessive ER triggers cell apoptosis conversely. The UPR involves different stages of CRC pathogenesis, promotes or hinders the progression of CRC, and will pave the way for novel therapeutic and diagnostic approaches. Meanwhile, the correlation between different signal branches in UPR and the switch between the adaptation and apoptosis pathways still need to be further investigated in the future.

Assessing the explanatory and predictive performance of a random parameters count model with heterogeneity in means and variances.

Random parameters model has been demonstrated to be an effective method to account for unobserved heterogeneity that commonly exists in highway crash data. However, the predefined single distribution for each random parameter may limit how the unobserved heterogeneity is captured. A more flexible approach is to develop a random parameters model with heterogeneity in means and variances by allowing the mean and variance of potential each random parameter to be an estimable function of explanatory variables. This burgeoning technique for modelling unobserved heterogeneity has been increasingly applied to various safety evaluation scenarios recently. However, the predictive performance of this emerging method, which determines the practicability of the model for a specific circumstance, has never been investigated as far as our knowledge. In addition, the explanatory power by including heterogeneous means and variances of random parameters need to be further investigated to confirm the potential merits of this method in crash data analysis. In this paper, a random parameters negative binomial with heterogeneity in means and variances (RPNBHMV) model, a standard random parameters negative binomial (RPNB) model and a traditional fixed parameters negative binomial (NB) model were estimated using the same dataset. The explanatory and predictive performance of the three models were thoroughly evaluated and compared. Results showed that: 1) the RPNB model fitted the data significantly better than the NB model, and the RPNBHMV model further improved the statistical fit of the RPNB model but the improvement was slight; 2) more insights into interactions of safety factors were inferred from the RPNBHMV model, which demonstrates the explanatory benefit of this model; 3) the RPNBHMV and RPNB models had both advantages (e.g., produced overall better prediction accuracy) and disadvantages (e.g., provided reduced prediction accuracy across the range of explanatory variables) when applied to in-sample observations (i.e., observations used to estimate the model); 4) the RPNBHMV and RPNB models might be less precise than the NB model when applied to out-of-sample observations. These findings indicate that the RPNBHMV model offers more insights and may be used for explanatory safety analysis for sites where reliable data can be collected. However, the simple NB model is more reliable - at least with the dataset used in this study - than its random parameters model counterparts for other sites where the data are unavailable or unreliable, which is a common safety evaluation scenario in practice.

A correlated random parameters tobit model to analyze the safety effects and temporal instability of factors affecting crash rates.

Numerous studies have previously used a variety of count-data models to investigate factors that affect the number of crashes over a certain period of time on roadway segments. Unlike past studies which deal with crash frequency, this study views the crash rates directly as a continuous variable left-censored at zero and explores the application of an alternate approach based on tobit regression. To thoroughly investigate the factors affecting freeway crash rates and the potentially temporal instability in the effects of crash factors involving traffic volume, freeway geometries and pavement conditions, a classic uncorrelated random parameters tobit (URPT) model and a correlated random parameters tobit (CRPT) model were estimated, along with a conventional fixed parameters tobit (FPT) model. The analysis revealed a large number of safety factors, including several appealing and interesting factors rarely studied in the past, such as the safety effects of climbing lanes and distance along composite descending grade. The results also showed that the CRPT model was not only able to reflect the heterogeneous effects of various factors, but also able to estimate the underlying interactions among unobserved characteristics, and therefore provide better statistical fit and offer more insights into factors contributing to freeway crashes than its model counterparts. Additionally, the results showed significant temporal instability in CRPT models across the studied time periods indicating that crash factors (including unobserved characteristics and the underlying interactions among them) and their effects on crash rates varied over time, and more attentions should be paid when interpreting crash data-analysis findings and making safety policies. The modeling technique in this study demonstrates the potential of CRPT model as an effective approach to gain new insights into safety factors, particularly when the heterogeneous effects of factors on safety are interactive. Additionally, findings from this study are also expected to assist in developing more effective countermeasures by better understanding the safety effects of factors associated with freeway design characteristics and pavement conditions.

Association of mutation patterns in GyrA and ParC genes with quinolone resistance levels in lactic acid bacteria.

The quinolone resistance of 19 lactic acid bacterial strains belonging to the genera Enterococcus and Lactobacillus isolated from the natural fermented koumiss and yoghurt were investigated. The objective of this study was to determine the quinolone resistance levels and to explore the association of the resistance with the mutation patterns in gyrA and parC genes, as is currently recommended by the Food and Agriculture Organization/World Health Organization Joint Expert Committee in Guidelines for Evaluation of Probiotics in Food for probiotic lactic acid bacteria drug resistance in 2001. The Oxford Cup method and double-tube dilution method were used to determine the quinolone resistance levels of the isolated strains. Generally, all of the 19 strains showed resistance towards norfloxacin and ciprofloxacin when the Oxford cup method was used, whereas the incidence was lower (to norfloxacin 89.5% and to ciprofloxacin 68.4%) when minimum inhibitory concentration breakpoints (CLSI M100-S23) were tested. Furthermore, gene sequencing was conducted on gyrA and parC of topoisomerase II of these isolated strains. The genetic basis for quinolone resistance may be closely related to mutations in gyrA genes as there were 10 mutation sites in amino-acid sequences encoded by gyrA genes in 10 quinolone resistance strains and 14 mutation sites in Enterococcus durans HZ28, whereas no typical mutations were detected in parC genes.