Depresión perimenopáusica: una revisión

A partir de la adolescencia, las mujeres presentan un riesgo 1,5 a 3 veces mayor que los hombres de padecer un trastorno depresivo. Este riesgo aumenta en el periodo de transición hacia la menopausia o perimenopausia, cuando la vulnerabilidad depresiva se hace especialmente intensa. Se han postulado mecanismos hormonales, psicológicos y socioculturales para entender la etiopatogenia de estos cuadros. El tratamiento de la depresión en la perimenopausia viene determinado por la gravedad clínica e incluye antidepresivos, psicoterapia y, en ocasiones, terapia hormonal sustitutiva mediante estrógenos. La depresión perimenopáusica constituye un problema infradiagnosticado e infratratado, que genera un alto nivel de sufrimiento y que merece una mayor atención por parte de los clínicos y el sistema sanitario

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Depresión perimenopáusica: una revisión

A partir de la adolescencia, las mujeres presentan un riesgo 1,5 a 3 veces mayor que los hombres de padecer un trastorno depresivo. Este riesgo aumenta en el periodo de transición hacia la menopausia o perimenopausia, cuando la vulnerabilidad depresiva se hace especialmente intensa. Se han postulado mecanismos hormonales, psicológicos y socioculturales para entender la etiopatogenia de estos cuadros. El tratamiento de la depresión en la perimenopausia viene determinado por la gravedad clínica e incluye antidepresivos, psicoterapia y, en ocasiones, terapia hormonal sustitutiva mediante estrógenos. La depresión perimenopáusica constituye un problema infradiagnosticado e infratratado, que genera un alto nivel de sufrimiento y que merece una mayor atención por parte de los clínicos y el sistema sanitario

Virtual reality training in neurosurgery: Review of current status and future applications

Background : Over years, surgical training is changing and years of tradition are being challenged by legal and ethical concerns for patient safety, work hour restrictions, and the cost of operating room time. Surgical simulation and skill training offer an opportunity to teach and practice advanced techniques before attempting them on patients. Simulation training can be as straightforward as using real instruments and video equipment to manipulate simulated "tissue" in a box trainer. More advanced virtual reality (VR) simulators are now available and ready for widespread use. Early systems have demonstrated their effectiveness and discriminative ability. Newer systems enable the development of comprehensive curricula and full procedural simulations. Methods : A PubMed review of the literature was performed for the MESH words "Virtual reality", "Augmented Reality", "Simulation", "Training," and "Neurosurgery". Relevant articles were retrieved and reviewed. A review of the literature was performed for the history, current status of VR simulation in neurosurgery. Results : Surgical organizations are calling for methods to ensure the maintenance of skills, advance surgical training, and credential surgeons as technically competent. The number of published literature discussing the application of VR simulation in neurosurgery training has evolved over the last decade from data visualization, including stereoscopic evaluation to more complex augmented reality models. With the revolution of computational analysis abilities, fully immersive VR models are currently available in neurosurgery training. Ventriculostomy catheters insertion, endoscopic and endovascular simulations are used in neurosurgical residency training centers across the world. Recent studies have shown the coloration of proficiency with those simulators and levels of experience in the real world. Conclusion : Fully immersive technology is starting to be applied to the practice of neurosurgery. In the near future, detailed VR neurosurgical modules will evolve to be an essential part of the curriculum of the training of neurosurgeons

Dr. Laurence Weinstein Editor in Chief

From the “Practitioner’s Corner Musings of a Serial Entrepreneur—Reconciling Theory with Practic