Risk of female athlete triad development in Japanese collegiate athletes is related to sport type and competitive level

Introduction: Menstrual dysfunction, musculoskeletal injury, and poor nutrition combine to form the female athlete triad (FAT), which results in serious health consequences for affected athletes. To this point, the risk factors of this phenomenon have not been fully explored in Japanese female college athletes. Additionally, the effect of competitive level on FAT risk factors has also not been reported. Therefore, we aimed to examine FAT risk factors in Japanese female athletes of various sports as well as examine the impact of competitive level on FAT.Methods: A Japanese-language survey was completed by 531 athletes and 20 nonathletes at two Japanese universities and answers with regard to menstrual status, musculoskeletal injury, nutrition, and other variables were analyzed based on classification of the sports into nine distinct groups based on activity type. Sport intensity, training volume, and competitive levels were used to further classify each sport. One-way ANOVA and the Bonferroni post hoc test using SPSS were carried out to analyze significance for relationships between sport intensity and FAT risk factors. Additionally, the relationship between competitive level and FAT risk factors was analyzed by ANOVA and Bonferroni post hoc tests.Results: Sport intensity was positively correlated with a delay in menarche as well as dysmenorrhea and poor nutrition while musculoskeletal injury was correlated with repetitive, high-training volume sports. Lower competitive levels increased dysmenorrhea but did not impact injury status or nutrition.Conclusion: Sport intensity and training volume, but not competitive level, are the critical factors affecting FAT risk in Japanese female college athletes

Fibroblast growth factor 19 expression correlates with tumor progression and poorer prognosis of hepatocellular carcinoma

<p>Abstract</p> <p>Background</p> <p>Although fibroblast growth factor 19 (FGF19) can promote liver carcinogenesis in mice, its involvement in human hepatocellular carcinoma (HCC) has not been well investigated. FGF19, a member of the FGF family, has unique specificity for its receptor FGFR4. This study aimed to clarify the involvement of FGF19 in the development of HCC.</p> <p>Methods</p> <p>We investigated human FGF19 and FGFR4 expression in 40 hepatocellular carcinoma specimens using quantitative real-time reverse transcription polymerase chain reaction (RT-PCR) analysis and immunohistochemistry. Moreover, we examined the expression and the distribution of FGF19 and FGFR4 in 5 hepatocellular carcinoma cell lines (HepG2, HuH7, HLE, HLF, and JHH7) using RT-PCR and immunohistochemistry. To test the role of the FGF19/FGFR4 system in tumor progression, we used recombinant FGF19 protein and small interfering RNA (siRNA) of <it>FGF19 </it>and <it>FGFR4 </it>to regulate their concentrations.</p> <p>Results</p> <p>We found that FGF19 was significantly overexpressed in HCCs as compared with corresponding noncancerous liver tissue (<it>P </it>< 0.05). Univariate and multivariate analyses revealed that the tumor <it>FGF19 </it>mRNA expression was an independent prognostic factor for overall and disease-free survival. Moreover, we found that the FGF19 recombinant protein could increase the proliferation (<it>P </it>< 0.01, <it>n </it>= 12) and invasion (<it>P </it>< 0.01, <it>n </it>= 6) capabilities of human hepatocellular carcinoma cell lines and inhibited their apoptosis (<it>P </it>< 0.01, <it>n </it>= 12). Inversely, decreasing <it>FGF19 </it>and <it>FGFR4 </it>expression by siRNA significantly inhibited proliferation and increased apoptosis in JHH7 cells (<it>P </it>< 0.01, <it>n </it>= 12). The postoperative serum FGF19 levels in HCC patients was significantly lower than the preoperative levels (<it>P </it>< 0.01, <it>n </it>= 29).</p> <p>Conclusions</p> <p>FGF19 is critically involved in the development of HCCs. Targeting FGF19 inhibition is an attractive potential therapeutic strategy for HCC.</p

Diets of Steller sea lions off the coast of Hokkaido, Japan: An inter-decadal and geographic comparison

Inter-decadal and geographic variations in the diets of Steller sea lion, Eumetopias jubatus, were examined based on the contents of 408 stomachs collected from coastal areas around Hokkaido Island during the periods 1994-1998 and 2005-2012. The most important prey species in the 1990s were gadid fishes (walleye pollock [Gadus chalcogrammus], Pacific cod [Gadus microcephalus] and saffron cod [Eleginus gracilis]). The frequency of occurrence and gravimetric contribution of gadids decreased in the 2000s latter period at three study sites (Rausu, Shakotan and Rebun) and were replaced by Okhotsk Atka mackerel (Pleurogrammus azonus) and smooth lumpsucker (Aptocyclus ventricosus). However, analysis based on gravimetric composition indicated that the dietary diversity of prey showed only a slight inter-decadal difference, reflecting the wide diversity of prey ingested during both study periods. These results indicate that Steller sea lions along the Hokkaido coast are opportunistic feeders that utilize a wide variety of prey, and appear to feed mainly upon prey that is easily obtained

New mosquito repellency bioassay for evaluation of repellents and pyrethroids using an attractive blood-feeding device

Background: With the increasing threat of the worldwide spread of mosquito-borne infectious diseases, consumer interest in anti-mosquito textiles that protect against mosquito bites is also increasing. Accordingly, repellent- or insecticide-treated textiles are gaining popularity. The standardization of commercial textile products is, therefore, indispensable for an authentic and objective evaluation of these products. Here we report a textile testing method using an artificial blood-feeding system that does not involve human volunteers or live animals, which aligns with the policy of protecting human and animal welfare.Methods: The attractive blood-feeding device (ABFD) was designed using the Hemotek® membrane feeding system. The repellency of DEET, icaridin and permethrin was assayed using unfed female adults of Aedes albopictus (Skuse) under two different test conditions, namely choice and no-choice tests. The choice test consisted of two feeding units, one chemically treated and untreated, that were installed on the ABFD; mosquitoes attracted to and resting on the feeding units were counted and the overall blood-feeding rates recorded. The no-choice test consisted of two feeding units treated with the same chemical that were installed on the ABFD; mosquitoes attracted to and resting on the feeding units were counted and the blood-feeding rates were recorded. A control test was conducted using two feeding units, both sides of which were untreated.Results: In the choice test, high repellency (> 95% inhibition of resting on the treated surface) of 1% DEET and 2% icaridin was observed, whereas 2% permethrin was not an effective repellent. Also, high blood-feeding inhibition (> 95%) was observed for 2% DEET and 2% icaridin. In the no-choice test, high repellency was observed for 1% DEET and 2% icaridin, whereas the repellency of 2% permethrin was low. Also, high blood-feeding inhibition was observed for 2% DEET, 4% icaridin and 2% permethrin.Conclusions: The accuracy and reproducibility of the developed method demonstrate that the ABFD may be widely used for fundamental experiments in the field of mosquito physiology, for the development of new repellent chemicals and in evaluation studies of mosquito repellent products, such as anti-mosquito textiles. The further development of the membrane and feeding unit systems will enable a more practical evaluation of mosquito repellents and blood-feeding inhibitors, such as pyrethroids

Gene Transfer of Heme Oxygenase-1 Using an Adeno-Associated Virus Serotype 6 Vector Prolongs Cardiac Allograft Survival

Introduction. Allograft survival can be prolonged by overexpression of cytoprotective genes such as heme oxygenase-1 (HO-1). Modifications in vector design and delivery have provided new opportunities to safely and effectively administer HO-1 into the heart prior to transplantation to improve long-term graft outcome. Methods. HO-1 was delivered to the donor heart using an adeno-associated virus vector (AAV) with a pseudotype 6 capsid and vascular endothelial growth factor (VEGF) to enhance myocardial tropism and microvascular permeability. Survival of mouse cardiac allografts, fully or partially mismatched at the MHC, was determined with and without cyclosporine A. Intragraft cytokine gene expression was examined by PCR. Results. The use of AAV6 to deliver HO-1 to the donor heart, combined with immunosuppression, prolonged allograft survival by 55.3% when donor and recipient were completely mismatched at the MHC and by 94.6% if partially mismatched. The combination of gene therapy and immunosuppression was more beneficial than treatment with either AAV6-HO-1 or CsA alone. IL-17a, b, e and f were induced in the heart at rejection. Conclusions. Pretreatment of cardiac allografts with AAV6-HO-1 plus cyclosporine A prolonged graft survival. HO-1 gene therapy represents a beneficial adjunct to immunosuppressive therapy in cardiac transplantation

Classification of the Epileptic Seizure Onset Zone Based on Partial Annotation.

Epilepsy is a chronic disorder caused by excessive electrical discharges. Currently, clinical experts identify the seizure onset zone (SOZ) channel through visual judgment based on long-time intracranial electroencephalogram (iEEG), which is a very time-consuming, difficult and experience-based task. Therefore, there is a need for high-accuracy diagnostic aids to reduce the workload of clinical experts. In this article, we propose a method in which, the iEEG is split into the 20-s segment and for each patient, we ask clinical experts to label a part of the data, which is used to train a model and classify the remaining iEEG data. In recent years, machine learning methods have been successfully applied to solve some medical problems. Filtering, entropy and short-time Fourier transform (STFT) are used for extracting features. We compare them to wavelet transform (WT), empirical mode decomposition (EMD) and other traditional methods with the aim of obtaining the best possible discriminating features. Finally, we look for their medical interpretation, which is important for clinical experts. We achieve high-performance results for SOZ and non-SOZ data classification by using the labeled iEEG data and support vector machine (SVM), fully connected neural network (FCNN) and convolutional neural network (CNN) as classification models. In addition, we introduce the positive unlabeled (PU) learning to further reduce the workload of clinical experts. By using PU learning, we can learn a binary classifier with a small amount of labeled data and a large amount of unlabeled data. This can greatly reduce the amount and difficulty of annotation work by clinical experts. All together, we show that using 105 minutes of labeled data we achieve a classification result of 91.46% on average for multiple patients

Classification of the Epileptic Seizure Onset Zone Based on Partial Annotation.

Epilepsy is a chronic disorder caused by excessive electrical discharges. Currently, clinical experts identify the seizure onset zone (SOZ) channel through visual judgment based on long-time intracranial electroencephalogram (iEEG), which is a very time-consuming, difficult and experience-based task. Therefore, there is a need for high-accuracy diagnostic aids to reduce the workload of clinical experts. In this article, we propose a method in which, the iEEG is split into the 20-s segment and for each patient, we ask clinical experts to label a part of the data, which is used to train a model and classify the remaining iEEG data. In recent years, machine learning methods have been successfully applied to solve some medical problems. Filtering, entropy and short-time Fourier transform (STFT) are used for extracting features. We compare them to wavelet transform (WT), empirical mode decomposition (EMD) and other traditional methods with the aim of obtaining the best possible discriminating features. Finally, we look for their medical interpretation, which is important for clinical experts. We achieve high-performance results for SOZ and non-SOZ data classification by using the labeled iEEG data and support vector machine (SVM), fully connected neural network (FCNN) and convolutional neural network (CNN) as classification models. In addition, we introduce the positive unlabeled (PU) learning to further reduce the workload of clinical experts. By using PU learning, we can learn a binary classifier with a small amount of labeled data and a large amount of unlabeled data. This can greatly reduce the amount and difficulty of annotation work by clinical experts. All together, we show that using 105 minutes of labeled data we achieve a classification result of 91.46% on average for multiple patients

Mycophenolic Acid and Its Derivatives as Potential Chemotherapeutic Agents Targeting Inosine Monophosphate Dehydrogenase in Trypanosoma congolense

This study aimed to evaluate the trypanocidal activity of mycophenolic acid (MPA) and its derivatives for Trypanosoma congolense. The proliferation of T. congolense was completely inhibited by adding <1 μM MPA and its derivatives. In addition, the IMP dehydrogenase in T. congolense was molecularly characterized as the target of these compounds. The results suggest that MPA and its derivatives have the potential to be new candidates as novel trypanocidal drugs