The effect of skill level on darts throwers’ use of different mental skills

Background: In recent years sports psychologists, coaches and athletes have paid a greater focus of attention to mental wellbeing and psychological skills. The purpose of this study was to investigate which psychological skills are important to two levels of skills among Darts players, namely; elite and beginner. Method: The sample consisted of 24 elite and 24 beginner Darts throwers. In order to gain insight into Darts throwing, beginner Darts players attended a national-championship-simulated competition. Both elite and beginner players also completed the Ottawa Mental Skill Questionnaire. Results: Independent t-test results showed that there was a significant difference just in basic psychiatric skills between the beginner and elite Darts throwers (p0.05). Conclusion: Results revealed differences between elite and beginner Darts players in foundation mental skills and commitment and mental practice subscales. Furthermore, results showed that for the commitment skill, elite and beginner Darts throwers were at the highest and lowest level respectively

Utility of commonly used commercial human chorionic gonadotropin immunoassays in the diagnosis and management of trophoblastic diseases.

A multi-centre study involving worldwide collaboration highlighted the between-method variation in hCG quantification and estimation and the resultant potential misdiagnosis of GTD

Improving on whole-brain radiotherapy in patients with large brain metastases: a planning study to support the AROMA clinical trial

PURPOSE: To develop a novel dose-escalated volumetric modulated arc therapy (VMAT) strategy for patients with single or multiple large brain metastases which can deliver a higher dose to individual lesions for better local control (LC), and to compare dosimetry between whole brain radiotherapy (WBRT), hippocampal-sparing whole brain radiotherapy (HS-WBRT) and different VMAT-based focal radiotherapy approaches. METHODS AND MATERIALS: We identified 20 patients with one to ten brain metastases and at least one lesion larger than 15 cm3 who had received WBRT as part of routine care. For each patient, we designed and evaluated five radiotherapy treatment plans, including WBRT, HS-WBRT and three VMAT dosing models. A dose of 20 Gy in 5 fractions was prescribed to the whole brain or target volumes depending on the plan, with higher doses to smaller lesions and dose-escalated inner planning target volumes (DE-iPTV) in VMAT plans, respectively. Treatment plans were evaluated using the efficiency index, mean dose and D0.1cc to the target volumes and organs at risk. RESULTS: Compared with WBRT, VMAT plans achieved a significantly more efficient dose distribution in brain lesions, especially with our DE-iPTV model, while minimising the dose to the normal brain and other organs at risks (OARs) (p < 0.05). CONCLUSIONS: VMAT plans obtained higher doses to brain metastases and minimised doses to OARs. Dose-escalated VMAT for larger lesions allows higher radiotherapy doses to be delivered to larger lesions while maintaining safe doses to OARs

Land subsidence susceptibility mapping in South Korea using machine learning algorithms

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. In this study, land subsidence susceptibility was assessed for a study area in South Korea by using four machine learning models including Bayesian Logistic Regression (BLR), Support Vector Machine (SVM), Logistic Model Tree (LMT) and Alternate Decision Tree (ADTree). Eight conditioning factors were distinguished as the most important affecting factors on land subsidence of Jeong-am area, including slope angle, distance to drift, drift density, geology, distance to lineament, lineament density, land use and rock-mass rating (RMR) were applied to modelling. About 24 previously occurred land subsidence were surveyed and used as training dataset (70% of data) and validation dataset (30% of data) in the modelling process. Each studied model generated a land subsidence susceptibility map (LSSM). The maps were verified using several appropriate tools including statistical indices, the area under the receiver operating characteristic (AUROC) and success rate (SR) and prediction rate (PR) curves. The results of this study indicated that the BLR model produced LSSM with higher acceptable accuracy and reliability compared to the other applied models, even though the other models also had reasonable results

Clinical utility of chromogranin A and octreotide in large cell neuro endocrine carcinoma of the uterine corpus

Primary neuroendocrine tumors of the female genital tract have been described in the cervix, ovaries and uterus. Large cell neuroendocrine carcinoma (LCNC) of the uterine corpus is the least common and appears to behave the most aggressively. We report a rare case of a large cell neuroendocrine tumor of the endometrium. These tumors are not well characterized, unlike neuroendocrine tumors of the uterine cervix. Consequently, the optimal management remains still unclear. The treatment of our case consisted of surgery, radiotherapy, chemotherapy, and octreotide. Despite the aggressive treatment, the patient died of disease progression 12 months after the initial diagnosis. We discuss the diagnosis, prognosis, and treatment options for LCNC of the genital tract, and potential future therapeutics

Deep learning-based quantification of temporalis muscle has prognostic value in patients with glioblastoma

Background Glioblastoma is the commonest malignant brain tumour. Sarcopenia is associated with worse cancer survival, but manually quantifying muscle on imaging is time-consuming. We present a deep learning-based system for quantification of temporalis muscle, a surrogate for skeletal muscle mass, and assess its prognostic value in glioblastoma. Methods A neural network for temporalis segmentation was trained with 366 MRI head images from 132 patients from 4 different glioblastoma data sets and used to quantify muscle cross-sectional area (CSA). Association between temporalis CSA and survival was determined in 96 glioblastoma patients from internal and external data sets. Results The model achieved high segmentation accuracy (Dice coefficient 0.893). Median age was 55 and 58 years and 75.6 and 64.7% were males in the in-house and TCGA-GBM data sets, respectively. CSA was an independently significant predictor for survival in both the in-house and TCGA-GBM data sets (HR 0.464, 95% CI 0.218–0.988, p = 0.046; HR 0.466, 95% CI 0.235–0.925, p = 0.029, respectively). Conclusions Temporalis CSA is a prognostic marker in patients with glioblastoma, rapidly and accurately assessable with deep learning. We are the first to show that a head/neck muscle-derived sarcopenia metric generated using deep learning is associated with oncological outcomes and one of the first to show deep learning-based muscle quantification has prognostic value in cancer

The semen microbiome and its relationship with local immunology and viral load in HIV infection

Semen is a major vector for HIV transmission, but the semen HIV RNA viral load (VL) only correlates moderately with the blood VL. Viral shedding can be enhanced by genital infections and associated inflammation, but it can also occur in the absence of classical pathogens. Thus, we hypothesized that a dysregulated semen microbiome correlates with local HIV shedding. We analyzed semen samples from 49 men who have sex with men (MSM), including 22 HIV-uninfected and 27 HIV-infected men, at baseline and after starting antiretroviral therapy (ART) using 16S rRNA gene-based pyrosequencing and quantitative PCR. We studied the relationship of semen bacteria with HIV infection, semen cytokine levels, and semen VL by linear regression, non-metric multidimensional scaling, and goodness-of-fit test. Streptococcus, Corynebacterium, and Staphylococcus were common semen bacteria, irrespective of HIV status. While Ureaplasma was the more abundant Mollicutes in HIV-uninfected men, Mycoplasma dominated after HIV infection. HIV infection was associated with decreased semen microbiome diversity and richness, which were restored after six months of ART. In HIV-infected men, semen bacterial load correlated with seven pro-inflammatory semen cytokines, including IL-6 (p = 0.024), TNF-α (p = 0.009), and IL-1b (p = 0.002). IL-1b in particular was associated with semen VL (r(2)  = 0.18, p = 0.02). Semen bacterial load was also directly linked to the semen HIV VL (r(2) = 0.15, p = 0.02). HIV infection reshapes the relationship between semen bacteria and pro-inflammatory cytokines, and both are linked to semen VL, which supports a role of the semen microbiome in HIV sexual transmission

The semen microbiome and its relationship with local immunology and viral load in HIV infection

Semen is a major vector for HIV transmission, but the semen HIV RNA viral load (VL) only correlates moderately with the blood VL. Viral shedding can be enhanced by genital infections and associated inflammation, but it can also occur in the absence of classical pathogens. Thus, we hypothesized that a dysregulated semen microbiome correlates with local HIV shedding. We analyzed semen samples from 49 men who have sex with men (MSM), including 22 HIV-uninfected and 27 HIV-infected men, at baseline and after starting antiretroviral therapy (ART) using 16S rRNA gene-based pyrosequencing and quantitative PCR. We studied the relationship of semen bacteria with HIV infection, semen cytokine levels, and semen VL by linear regression, non-metric multidimensional scaling, and goodness-of-fit test. Streptococcus, Corynebacterium, and Staphylococcus were common semen bacteria, irrespective of HIV status. While Ureaplasma was the more abundant Mollicutes in HIV-uninfected men, Mycoplasma dominated after HIV infection. HIV infection was associated with decreased semen microbiome diversity and richness, which were restored after six months of ART. In HIV-infected men, semen bacterial load correlated with seven pro-inflammatory semen cytokines, including IL-6 (p = 0.024), TNF-α (p = 0.009), and IL-1b (p = 0.002). IL-1b in particular was associated with semen VL (r2 = 0.18, p = 0.02). Semen bacterial load was also directly linked to the semen HIV VL (r2 = 0.15, p = 0.02). HIV infection reshapes the relationship between semen bacteria and pro-inflammatory cytokines, and both are linked to semen VL, which supports a role of the semen microbiome in HIV sexual transmission