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CO2 laserlight vaporization to treat vaginal intraepithelial neoplasia: success along with predictive elements regarding repeat.
e be influenced by the choice of the SF-6Dv2 over the SF-6D.
To classify COVID-19, COVID-19-like and non-COVID-19 interstitial pneumonia using lung CT radiomic features.

CT data of 115 patients with respiratory symptoms suspected for COVID-19 disease were retrospectively analyzed. Based on the results of nasopharyngeal swab, patients were divided into two main groups, COVID-19 positive (C +) and COVID-19 negative (C-), respectively. C- patients, however, presented with interstitial lung involvement. A subgroup of C-, COVID-19-like (CL), were considered as highly suggestive of COVID pneumonia at CT. Radiomic features were extracted from the whole lungs. A dual machine learning (ML) model approach was used. The first one excluded CL patients from the training set, eventually included on the test set. The second model included the CL patients also in the training set.

The first model classified C + and C- pneumonias with AUC of 0.83. CL median response (0.80) was more similar to C + (0.92) compared to C- (0.17). Radiomic footprints of CL were similar to the C + ones (possibly false negative swab test). The second model, however, merging C + with CL patients in the training set, showed a slight decrease in classification performance (AUC = 0.81).

Whole lung ML models based on radiomics can classify C + and C- interstitial pneumonia. This may help in the correct management of patients with clinical and radiological stigmata of COVID-19, however presenting with a negative swab test. CL pneumonia was similar to C + pneumonia, albeit with slightly different radiomic footprints.
Whole lung ML models based on radiomics can classify C + and C- interstitial pneumonia. This may help in the correct management of patients with clinical and radiological stigmata of COVID-19, however presenting with a negative swab test. CL pneumonia was similar to C + pneumonia, albeit with slightly different radiomic footprints.
The purpose of this paper is to present and validate a new semi-automated 3D surface mesh segmentation approach that optimizes the laborious individual human vertebrae separation in the spinal virtual surgical planning workflow and make a direct accuracy and segmentation time comparison with current standard segmentation method.

The proposed semi-automatic method uses the 3D bone surface derived from CT image data for seed point-based 3D mesh partitioning. The accuracy of the proposed method was evaluated on a representative patient dataset. In addition, the influence of the number of used seed points was studied. The investigators analyzed whether there was a reduction in segmentation time when compared to manual segmentation. check details Surface-to-surface accuracy measurements were applied to assess the concordance with the manual segmentation.

The results demonstrated a statically significant reduction in segmentation time, while maintaining a high accuracy compared to the manual segmentation. A considerably smaller error was found when increasing the number of seed points. Anatomical regions that include articulating areas tend to show the highest errors, while the posterior laminar surface yielded an almost negligible error.

A novel seed point initiated surface based segmentation method for the laborious individual human vertebrae separation was presented. This proof-of-principle study demonstrated the accuracy of the proposed method on a clinical CT image dataset and its feasibility for spinal virtual surgical planning applications.
A novel seed point initiated surface based segmentation method for the laborious individual human vertebrae separation was presented. This proof-of-principle study demonstrated the accuracy of the proposed method on a clinical CT image dataset and its feasibility for spinal virtual surgical planning applications.The white shrimp Penaeus (Litopenaeus) vannamei is the most economically important crustacean species cultivated in the Western Hemisphere. This crustacean shifts its metabolism to survive under extreme environmental conditions such as hypoxia, although for a limited time. Glucose-6-phosphatase (G6Pase) is a key enzyme contributing to maintain blood glucose homeostasis through gluconeogenesis and glycogenolysis. To our knowledge, there are no current detailed studies about cDNA or gene sequences of G6Pase from any crustacean reported. Herein we report the shrimp P. (L.) vannamei cDNA and gene sequences. The gene contains seven exons interrupted by six introns. The deduced amino acid sequence has 35% identity to other homolog proteins, with the catalytic amino acids conserved and phylogenetically close to the corresponding invertebrate homologs. Protein molecular modeling predicted eight transmembrane helices with the catalytic site oriented towards the lumen of the endoplasmic reticulum. G6Pase expression under normoxic conditions was evaluated in hepatopancreas, gills, and muscle and the highest transcript abundance was detected in hepatopancreas. In response to different times of hypoxia, G6Pase mRNA expression did not change in hepatopancreas and became undetectable in muscle; however, in gills, its expression increased after 3 h and 24 h of oxygen limitation, indicating its essential role to maintain glycemic control in these conditions.Preeclampsia (PE) is a pregnancy complication that is characterized by high blood pressure and is associated with high maternal and fetal morbidities. At a mechanistic level, PE is characterized by reduced invasion ability of trophoblasts. Collagen triple helix repeat containing-1 (CTHRC1) is a well-known tumor-promoting factor in several malignant tumors, but its role in trophoblasts remains unknown. In this study, we characterized the expression of CTHRC1 in placenta tissue samples from PE pregnancies and from normal pregnancies. We used the trophoblasts cell lines HTR-8/SVneo and JEG-3 to investigate the role of CTHRC1 in cell migration, invasion and proliferation. Western blot, PCR and TOP/FOP luciferase activity assays were used to investigate the molecular mechanisms underlying these cell behaviors. Placenta tissue samples obtained from pregnant women with PE expressed lower levels of CTHRC1 than those of placenta tissues from women with normal pregnancies. Down-regulation of CTHRC1 impaired cell proliferation, migration and invasion of trophoblasts, while CTHRC1 overexpression promoted nuclear translocation of β-catenin, a result that was further confirmed by TOP/FOP luciferase activity assay.
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