The radial arrangement of the human chromosome 7 in the lymphocyte cell nucleus is associated with chromosomal band gene density

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ Springer-Verlag 2008.In the nuclei of human lymphocytes, chromosome territories are distributed according to the average gene density of each chromosome. However, chromosomes are very heterogeneous in size and base composition, and can contain both very gene-dense and very gene-poor regions. Thus, a precise analysis of chromosome organisation in the nuclei should consider also the distribution of DNA belonging to the chromosomal bands in each chromosome. To improve our understanding of the chromatin organisation, we localised chromosome 7 DNA regions, endowed with different gene densities, in the nuclei of human lymphocytes. Our results showed that this chromosome in cell nuclei is arranged radially with the gene-dense/GC-richest regions exposed towards the nuclear interior and the gene-poorest/GC-poorest ones located at the nuclear periphery. Moreover, we found that chromatin fibres from the 7p22.3 and the 7q22.1 bands are not confined to the territory of the bulk of this chromosome, protruding towards the inner part of the nucleus. Overall, our work demonstrates the radial arrangement of the territory of chromosome 7 in the lymphocyte nucleus and confirms that human genes occupy specific radial positions, presumably to enhance intra- and inter-chromosomal interaction among loci displaying a similar expression pattern, and/or similar replication timing

Emergency Department and Out-of-Hospital Emergency System (112\u2014AREU 118) integrated response to Coronavirus Disease 2019 in a Northern Italy centre

Since December 2019, the world has been facing the life-threatening disease, named Coronavirus disease-19 (COVID-19), recognized as a pandemic by the World Health Organization. The response of the Emergency Medicine network, integrating \u201cout-of-hospital\u201d and \u201chospital\u201d activation, is crucial whenever the health system has to face a medical emergency, being caused by natural or human-derived disasters as well as by a rapidly spreading epidemic outbreak. We here report the Pavia Emergency Medicine network response to the COVID-19 outbreak. The \u201cout-of-hospital\u201d response was analysed in terms of calls, rescues and missions, whereas the \u201chospital\u201d response was detailed as number of admitted patients and subsequent hospitalisation or discharge. The data in the first 5 weeks of the Covid-19 outbreak (February 21\u2013March 26, 2020) were compared with a reference time window referring to the previous 5 weeks (January 17\u2013February 20, 2020) and with the corresponding historical average data from the previous 5 years (February 21\u2013March 26). Since February 21, 2020, a sudden and sustained increase in the calls to the AREU 112 system was noted (+ 440%). After 5 weeks, the number of calls and missions was still higher as compared to both the reference pre-Covid-19 period (+ 48% and + 10%, respectively) and the historical control (+ 53% and + 22%, respectively). Owing to the overflow from the neighbouring hospitals, which rapidly became overwhelmed and had to temporarily close patient access, the population served by the Pavia system more than doubled (from 547.251 to 1.135.977 inhabitants, + 108%). To minimize the possibility of intra-hospital spreading of the infection, a separate \u201cEmergency Department\u2014Infective Disease\u201d was created, which evaluated 1241 patients with suspected infection (38% of total ED admissions). Out of these 1241 patients, 58.0% (n = 720) were admitted in general wards (n = 629) or intensive care unit (n = 91). To allow this massive number of admissions, the hospital reshaped many general ward Units, which became Covid-19 Units (up to 270 beds) and increased the intensive care unit beds from 32 to 60. In the setting of a long-standing continuing emergency like the present Covid-19 outbreak, the integration, interaction and team work of the \u201cout-of-hospital\u201d and \u201cin-hospital\u201d systems have a pivotal role. The present study reports how the rapid and coordinated reorganization of both might help in facing such a disaster. AREU-112 and the Emergency Department should be ready to finely tune their usual cooperation to respond to a sudden and overwhelming increase in the healthcare needs brought about by a pandemia like the current one. This lesson should shape and reinforce the future

Survivorship Data in Prostate Cancer: Where Are We and Where Do We Need To Be?

Cancer survivorship was recently identified as a prostate cancer (PCa) research priority by PIONEER, a European network of excellence for big data in PCa. Despite being a research priority, cancer survivorship lacks a clear and agreed definition, and there is a distinct paucity of patient-reported outcome (PRO) data available on the subject. Data collection on cancer survivorship depends on the availability and implementation of (validated) routinely collected patient-reported outcome measures (PROMs). There have been recent advances in the availability of such PROMs. For instance, the European Organisation for Research and Treatment of Cancer Quality of Life Group (EORTC QLG) is developing survivorship questionnaires. This provides an excellent first step in improving the data available on cancer survivorship. However, we propose that an agreed, standardised definition of (prostate) cancer survivorship must first be established. Only then can real-world data on survivorship be collected to strengthen our knowledge base. With more men than ever surviving PCa, this type of research is imperative to ensure that the quality of life of these men is considered as much as their quantity of life. Patient summary: As there are more prostate cancer survivors than ever before, research into cancer survivorship is crucial. We highlight the importance of such research and provide recommendations on how to carry it out. The first step should be establishing agreement on a standardised definition of survivorship. From this, patient-reported outcome measures can then be used to collect important survivorship data