Reading the Second Code: Mapping Epigenomes to Understand Plant Growth, Development, and Adaptation to the Environment

We have entered a new era in agricultural and biomedical science made possible by remarkable advances in DNA sequencing technologies. The complete sequence of an individual's set of chromosomes (collectively, its genome) provides a primary genetic code for what makes that individual unique, just as the contents of every personal computer reflect the unique attributes of its owner. But a second code, composed of "epigenetic" layers of information, affects the accessibility of the stored information and the execution of specific tasks. Nature's second code is enigmatic and must be deciphered if we are to fully understand and optimize the genetic potential of crop plants. The goal of the Epigenomics of Plants International Consortium is to crack this second code, and ultimately master its control, to help catalyze a new green revolution

Malignant pleural mesothelioma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up.

Biological, physical and clinical aspects of cancer treatment with ionising radiatio

Factors Associated with D-Dimer Levels in HIV-Infected Individuals

Matti A Ristola on työryhmän jäsen.Peer reviewe

The FIGO ovulatory disorders classification system.

peer reviewedOvulatory disorders are common causes of amenorrhea, abnormal uterine bleeding, and infertility, and are frequent manifestations of polycystic ovary syndrome (PCOS). There are many potential causes and contributors to ovulatory dysfunction that challenge clinicians, trainees, educators, and those who perform basic, translational, clinical, and epidemiological research. Similarly, therapeutic approaches to ovulatory dysfunction potentially involve a spectrum of lifestyle, psychological, medical, and procedural interventions. Collaborative research, effective education, and consistent clinical care remain challenged by the absence of a consensus comprehensive system for classification of these disorders. The existing and complex system, attributed to WHO, was developed more than three decades ago and did not consider more than 30 years of research into these disorders in addition to technical advances in imaging and endocrinology. This manuscript describes the development of a new classification of ovulatory disorders performed under the aegis of the International Federation of Gynecology and Obstetrics (FIGO) and conducted using a rigorously applied Delphi process. The stakeholder organizations and individuals who participated in this process comprised specialty journals, experts at large, national, specialty obstetrical and gynecological societies, and informed lay representatives. After two face-to-face meetings and five Delphi rounds, the result is a three-level multi-tiered system. The system is applied after a preliminary assessment identifies the presence of an ovulatory disorder. The primary level of the system is based on an anatomic model (Hypothalamus, Pituitary, Ovary) that is completed with a separate category for PCOS. This core component of the system is easily remembered using the acronym HyPO-P. Each anatomic category is stratified in the second layer of the system to provide granularity for investigators, clinicians, and trainees using the "GAIN-FIT-PIE" mnemonic (Genetic, Autoimmune, Iatrogenic, Neoplasm; Functional, Infectious and Inflammatory, Trauma and Vascular; Physiological, Idiopathic, Endocrine). The tertiary level allows for specific diagnostic entities. It is anticipated that, if widely adopted, this system will facilitate education, clinical care, and the design and interpretation of research in a fashion that better informs progress in this field. Integral to the deployment of this system is a periodic process of reevaluation and appropriate revision, reflecting an improved understanding of this collection of disorders

Seasonal Variation and Sources of NO(x) of Beibu Gulf

The concentration of NO(x) of Beibu Gulf was analyzed on four voyages in four seasons respectively between 2006 and 2007. We also studied its distribution characters as well as sources in different seasons. The results showed that the concentration of NO(x) of Beibu Gulf was ranging from under detection limit to 0.77 mg/m(3). The annual average concentration is 0.017 mg/m(3), which was lower than other reported gulfs of China. The general trend was inshore > offshore. The higher areas were Qiongzhou Bay estuary and coastal of western Hainan Island. Besides, it was relatively higher in the southern Hainan Island. It was lower in coastal of Guangxi Province and the middle of the gulf. The seasonal variation of NO(x) of Beibu Gulf combined this order: winter > autumn > spring > summer. The concentration of winter and autumn was much higher than the other two seasons. Based on these above results, it was inferred that NO(x) of Beibu Gulf was mainly controlled by continental air which was transported to ocean by wind. The next important source was emission from ships while natural emission was minor

Neurosurgeons and the fight with COVID-19: a position statement from the EANS Individual Membership Committee

Scientific Assessment and Innovation in Neurosurgical Treatment Strategie

A Case for the Use of Artificial Intelligence in Glaucoma Assessment

We hypothesize that artificial intelligence (AI) applied to relevant clinical testing in glaucoma has the potential to enhance the ability to detect glaucoma. This premise was discussed at the recent Collaborative Community on Ophthalmic Imaging meeting, “The Future of Artificial Intelligence–Enabled Ophthalmic Image Interpretation: Accelerating Innovation and Implementation Pathways,” held virtually September 3–4, 2020. The Collaborative Community on Ophthalmic Imaging (CCOI) is an independent self-governing consortium of stakeholders with broad international representation from academic institutions, government agencies, and the private sector whose mission is to act as a forum for the purpose of helping speed innovation in healthcare technology. It was 1 of the first 2 such organizations officially designated by the Food and Drug Administration in September 2019 in response to their announcement of the collaborative community program as a strategic priority for 2018–2020. Further information on the CCOI can be found online at their website (https://www.cc-oi.org/about). Artificial intelligence for glaucoma diagnosis would have high utility globally, because access to care is limited in many parts of the world and half of all people with glaucoma are unaware of their illness. The application of AI technology to glaucoma diagnosis has the potential to broadly increase access to care worldwide, in essence flattening the Earth by providing expert-level evaluation to individuals even in the most remote regions of the planet