Systematic review of prognostic models in traumatic brain injury

BACKGROUND: Traumatic brain injury (TBI) is a leading cause of death and disability world-wide. The ability to accurately predict patient outcome after TBI has an important role in clinical practice and research. Prognostic models are statistical models that combine two or more items of patient data to predict clinical outcome. They may improve predictions in TBI patients. Multiple prognostic models for TBI have accumulated for decades but none of them is widely used in clinical practice. The objective of this systematic review is to critically assess existing prognostic models for TBI METHODS: Studies that combine at least two variables to predict any outcome in patients with TBI were searched in PUBMED and EMBASE. Two reviewers independently examined titles, abstracts and assessed whether each met the pre-defined inclusion criteria. RESULTS: A total of 53 reports including 102 models were identified. Almost half (47%) were derived from adult patients. Three quarters of the models included less than 500 patients. Most of the models (93%) were from high income countries populations. Logistic regression was the most common analytical strategy to derived models (47%). In relation to the quality of the derivation models (n:66), only 15% reported less than 10% pf loss to follow-up, 68% did not justify the rationale to include the predictors, 11% conducted an external validation and only 19% of the logistic models presented the results in a clinically user-friendly way CONCLUSION: Prognostic models are frequently published but they are developed from small samples of patients, their methodological quality is poor and they are rarely validated on external populations. Furthermore, they are not clinically practical as they are not presented to physicians in a user-friendly way. Finally because only a few are developed using populations from low and middle income countries, where most of trauma occurs, the generalizability to these setting is limited

Bone Marrow Transplantation Restores Follicular Maturation and Steroid Hormones Production in a Mouse Model for Primary Ovarian Failure

Recent studies suggest that bone marrow stem cells (BMSCs) are promising grafts to treat a variety of diseases, including reproductive dysfunction. Primary ovarian failure is characterized by amenorrhea and infertility in a normal karyotype female, with an elevated serum level of follicle-stimulating hormone (FSH) and a decrease level of estrogen caused by a mutation in FSH receptor (FSHR) gene. Currently, there is no effective treatment for this condition. The phenotype of FSHR (−/−) mouse, FORKO (follitropin receptor knockout), is a suitable model to study ovarian failure in humans. Female FORKO mice have elevated FSH, decreased estrogen levels, are sterile because of the absence of folliculogenesis, and display thin uteri and small nonfunctional ovaries. In this study, we determined the effects of BMSC transplantation on reproductive physiology in this animal model. Twenty four hours post BMSC transplantation, treated animals showed detectable estroidogeneic changes in daily vaginal smear. Significant increase in total body weight and reproductive organs was observed in treated animals. Hemotoxylin and eosin (H&E) evaluation of the ovaries demonstrated significant increase in both the maturation and the total number of the follicles in treated animals. The FSH dropped to 40–50% and estrogen increased 4–5.5 times in the serum of treated animals compared to controls. The FSHR mRNA was detected in the ovaries of treated animals. Our results show that intravenously injected BMSCs were able to reach the ovaries of FORKO mice, differentiate and express FHSR gene, make FSHR responsive to FSH, resume estrogen hormone production, and restore folliculogenesis

P3HT-Based Solar Cells: Structural Properties and Photovoltaic Performance

Each year we are bombarded with B.Sc. and Ph.D. applications from students that want to improve the world. They have learned that their future depends on changing the type of fuel we use and that solar energy is our future. The hope and energy of these young people will transform future energy technologies, but it will not happen quickly. Organic photovoltaic devices are easy to sketch, but the materials, processing steps, and ways of measuring the properties of the materials are very complicated. It is not trivial to make a systematic measurement that will change the way other research groups think or practice. In approaching this chapter, we thought about what a new researcher would need to know about organic photovoltaic devices and materials in order to have a good start in the subject. Then, we simplified that to focus on what a new researcher would need to know about poly-3-hexylthiophene:phenyl-C61-butyric acid methyl ester blends (P3HT: PCBM) to make research progress with these materials. This chapter is by no means authoritative or a compendium of all things on P3HT:PCBM. We have selected to explain how the sample fabrication techniques lead to control of morphology and structural features and how these morphological features have specific optical and electronic consequences for organic photovoltaic device applications