The CRZ1 transcription factor in plant fungi: regulation mechanism and impact on pathogenesis.

Calcium (Ca2+) is a universal signaling molecule that is tightly regulated, and a fleeting elevation in cytosolic concentration triggers a signal cascade within the cell, which is crucial for several processes such as growth, tolerance to stress conditions, and virulence in fungi. The link between calcium and calcium-dependent gene regulation in cells relies on the transcription factor Calcineurin-Responsive Zinc finger 1 (CRZ1). The direct regulation of approximately 300 genes in different stress pathways makes it a hot topic in host-pathogen interactions. Notably, CRZ1 can modulate several pathways and orchestrate cellular responses to different types of environmental insults such as osmotic stress, oxidative stress, and membrane disruptors. It is our belief that CRZ1 provides the means for tightly modulating and synchronizing several pathways allowing pathogenic fungi to install into the apoplast and eventually penetrate plant cells (i.e., ROS, antimicrobials, and quick pH variation). This review discusses the structure, function, regulation of CRZ1 in fungal physiology and its role in plant pathogen virulence.

Hepatitis C Virus Positive Patients on the Waiting List for Liver Transplantation: Turnover and Characteristics of the Population on the Eve of the Therapeutic Revolution With Direct-Acting Antivirals.

INTRODUCTION: Antivirals direct acting (DAA) for hepatitis C virus (HCV) have brought a revolution in the field of transplantation. It is likely to think that in the future patients on the waiting list for liver transplantation (LT) will no longer be registered for HCV-related cirrhosis but for liver disease from other causes. On the eve of this change, we show a snapshot of the Italian waiting list for LT. METHODS: From October 1, 2012 to September 30, 2013, we estimated the total number of patients on the liver waiting list as intention to treat (ITT), the number of incident cases, and the delistings, particularly in the HCV positive (HCV+) population. Gender, median age, etiology and prognosis of liver disease, presence of hepatocellular carcinoma (HCC), reason for delisting, mean waiting time for LT, and rate of death on waiting list were evaluated. RESULTS: In the time period, there were 517 new patients who were HCV+ (median age, 53 years): 255 (49.3%) mono-infected with HCV, 236 (45.7%) co-infected with HCV and hepatitis B virus (HBV), 11 (2.1%) co-infected with HCV and human immunodeficiency virus (HIV), and 15 (2.9%) co-infected with HCV, HBV, and HIV. The median model for end-stage liver disease (MELD) score at listing was 17 and HCC was present in 206 (39.8%) cases. HCV+ patients delisted were 442 (61.9%), 355 (80.3%) for LT. The mean waiting time to transplantation was 1.9 months; the percentage of death was 7.6%. CONCLUSIONS: This snapshot of the waiting list for LT in the year before the advent of DAA drugs will allow us to assess whether and how they will change the waiting list for LT when we start to look at the impact of new therapies on the waiting list.

Optimizing the Use of Available Lungs.

BACKGROUND: Organ transplantation, the treatment of choice in organ failure, is penalized by the lack of organs. Because the increase in the number of donors is not proportional throughout the different age groups, there is no increase in lung transplantations. The aim of this work was to analyze the use of available lungs and evaluate strategies that may help increase transplantations. METHODS: We analyzed the activity of lung transplantation in 2015, divided into various allocation programs. We also examined the surplus organs, in particular, their origin, their destination, their offer's outcome, the characteristics of the donor and the proposed organ, and the reasons for rejection. RESULTS: In 2015, 112 lung transplantations were performed: 66 (68.9%) with regional organs, 46 (41.1%) with extraregional organs; 21 (45.6%) of these were allocated as emergencies/return, and 25 (54.4%) as surplus (19 in the North macroarea, 6 in the South macroarea). The number of surplus lungs was 148: 67 from the North macroarea, 71 from the South macroarea, and 10 from abroad. No organ procured in the North macroarea was transplanted in the South macroarea, whereas 6 lungs coming from the South macroarea were transplanted in the North. CONCLUSIONS: The acceptance criteria are not the same in different transplant centers and they include not only clinical parameters, but also ischemia time and composition of the waiting list at the time of the offer, quality and accessibility of the intensive care units where the donor is located, and organizational reasons. Offering organs which can not be transplanted within the region to other centers, without clinical foreclosures is a system that increases transplant activities by maximizing the available resources.

Liver Allocation in Urgent MELD Score ≥30: The Italian Experience.

INTRODUCTION: Patients with an urgent MELD score ≥30 are managed by the Italian Operative National Transplant Center on the basis of a division of Italy into 2 main areas, the northern macro area (NMA) and the southern macro area (SMA). The object of this study was to evaluate the possibility and the need to transform the MELD score ≥30 macro area-based program into a nationwide one. PATIENTS AND METHODS: When a region reports the presence of a patient with a MELD score ≥30, the same macro area-compatible donors, in the absence of urgent national and 1B status, are offered primarily to this recipient. RESULTS: From August 2014 to August 2015, 132 requests for patients with urgent MELD score ≥30, 98 from the NMA and 34 from the SMA, were handled. The average waiting list in the NMA was significantly different from that of the SMA (2.74 ± 2.29 vs 4.5 ± 3.98, P < .05). A total of 73.7% of the received requests (n = 97) were satisfied: the NMA met 80.4% of the requests (n = 77), whereas the SMA met 55.5% (n = 20). A total of 35 requests (26.5%), 21 from the NMA (60%) and 14 (40%) from the SMA, were not met. The average waiting time of these recipients for a liver was significantly different between the NMA and the SMA (3.14 ± 3.21 vs 5.78 ± 4.59; P < .05). CONCLUSIONS: The MELD score is a priority allocation, and the longer the waiting time to transplantation for these recipients, the more their mortality increases. Given the differences in waiting times between the NMA and SMA, we should start thinking about transforming the macro area program into a national one.