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Variables sampled by eddy-covariance (EC) systems are not temporally aligned because, to avoid possible wind flow distortions, sensors are not perfectly co-located. If not properly treated, such a temporal mis-alignment constitutes a source of systematic error in the derived EC fluxes. In most of EC data processing pipelines, the time lag is detected by assessing the cross-covariance function between the vertical wind speed and the atmospheric concentration of the scalar of interest. In particular, the optimal time lag is detected in correspondence of the lag that maximizes (in absolute terms) the cross-covariance function between raw, high-frequency, time series. Such a procedure is effective when the cross-covariance function exhibits a distinct and pronounced peak, a condition occurring under second-order stationary conditions and when the signal-to-noise ratio is moderate/high. In other circumstances, the cross-covariance function can be characterized by multiple local minima or maxima of similar magnitude, making the detection of the optimal time lag problematic. This often occurs for trace gases or during dormant/senescence periods when fluxes are of small magnitude.This work introduces a new procedure being computationally efficient and completely data-driven where time lag is detected by assessing the statistical significance of the cross-correlation estimates between raw EC data subject to a preliminary (linear) transformation known as prewhitening. Prewhitening avoids the risk of nonsense (or spurious) correlations, making it more realistic and informative the assessment of the cross-correlation function, and then the detection of the optimal time lag.The procedure consists of the following steps: i) removal of the serial correlation from at least one of the two series involved in the cross-correlation function using an autoregressive integrated moving average (ARIMA) model; ii) filtering of the other time series using an ARIMA model with the same parameters estimated in the previous step; iii) evaluation of the cross-correlation function between the transformed variables (i.e. between the model residuals). The effectiveness of the procedure is evaluated for the detection of time lag affecting CO2, H2O, N2O and CH4 variables. Results indicate that applying the proposed approach and using sonic temperature instead of vertical wind speed greatly facilitates the detection of the optimal time lag, even in the case of low magnitude fluxes.

While the vaccination campaign against COVID-19 is having its positive impact, we retrospectively analyze the causal impact of some decisions made by the Italian government on the second outbreak of the SARS-CoV-2 pandemic in Italy, when no vaccine was available. First, we analyze the causal impact of reopenings after the first lockdown in 2020. In addition, we also analyze the impact of reopening schools in September 2020. Our results provide an unprecedented opportunity to evaluate the causal relationship between the relaxation of restrictions and the transmission in the community of a highly contagious respiratory virus that causes severe illness in the absence of prophylactic vaccination programs. We present a purely data-analytic approach based on a Bayesian methodology and discuss possible interpretations of the results obtained and implications for policy makers.

The eddy covariance is a micrometeorological technique which allows for the estimation of the net fluxes of gases and energy between the atmosphere and an ecosystem. To estimate the net balance, the required input data are high frequency measurements (e.g. 10 or 20 Hz) of wind speed and gas concentration or amount of energy, plus lower frequency measurements (e.g. 1s to 30min ) of some meteorological variables and gas concentration vertical gradients below the measuring point. From these measurements, through a set of processing algorithms and corrections, continuous time series of fluxes are obtained which can be used to, e.g., estimate the net ecosystem exchange, as input/validation for modelling purposes, or for eco-physiological analyses. Although the fundamental processing steps and corrections are well established, there is still a discrete margin of subjectivity in the choice of specific operations and corrections which leads to different results even starting from the same set of measured data. The ICOS Ecosystem infrastructure consists of a network of eddy covariance stations equipped with high-level standardized instrumentation, whose data are processed centrally by means of a fully standardized and documented processing pipeline. This allows to obtain robust and consistent datasets, along with sets of metadata (e.g. instruments characteristics and location) and ancillary variables (e.g. meteorological and biometric) that help their interpretation and ensure their traceability and reproducibility. The description of the full processing pipeline is the aim of this contribution. All the data and metadata produced by the ICOS Ecosystem Thematic Centre (ETC) are freely available through the ICOS Carbon Portal as well as the processing codes are available in the ICOS ETC GitHub repository.

The article is a review of the conference The Origins of the Italian Republic: The 2nd June and Its Stories, held on 6-7 October 2021, in Rimini. The conference was the occasion to analyze and to discuss historical issues, educational projects and Public history strategies, aimed to study and disclose the meaning of the origins of the Italian Republic.

The paper analyses the history behind the monument to Vittorio Bottego in Parma, built in 1907 ten years after the death of the parmisan explorer. The essay focuses on the political narratives and the significance of this monument – an Italian colonialist symbol – from the Italian liberal age till today, passing through the Fascist period.

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET). ISSN:0168-1923 ISSN:1873-2240

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-flled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the frst time in this paper. In addition, 206 of these sites are for the frst time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible., European Union (EU), United States Department of Energy (DOE)

Purpose To investigate the prevalence, incidence and characteristics of bacterial infections and their impact on outcome in critically ill patients infected with COVID-19. Methods We conducted a prospective observational study in eight Italian ICUs from February to May 2020; data were collected through an interactive electronic database. Kaplan–Meier analysis (limit product method) was used to identify the occurrence of infections and risk of acquisition. Results During the study period 248 patients were recruited in the eight participating ICUs. Ninety (36.3%) patients developed at least one episode of secondary infection. An ICU length of stay between 7 and 14 days was characterized by a higher occurrence of infectious complications, with ventilator-associated pneumonia being the most frequent. At least one course of antibiotic therapy was given to 161 (64.9%) patients. Overall ICU and hospital mortality were 33.9% and 42.9%, respectively. Patients developing bacteremia had a higher risk of ICU mortality [45.9% vs. 31.6%, odds ratio 1.8 (95% CI 0.9–3.7), p = 0.069] and hospital mortality [56.8% vs. 40.3%, odds ratio 1.9 (95% CI 1.1–3.9), p = 0.04]. Conclusion In critically ill patients infected with COVID-19 the incidence of bacterial infections is high and associated with worse outcomes. Regular microbiological surveillance and strict infection control measures are mandated. Supplementary Information The online version contains supplementary material available at 10.1007/s15010-021-01661-2.

L’articolo descrive il progetto Parma in tempo di guerra 1940-1945, realizzato da Istituto storico della Resistenza e dell’eta contemporanea di Parma - Isrec Parma. Il progetto prevede la realizzazione di quattro portali web che raccontano – attraverso mappe, immagini, documenti e schede – i molteplici aspetti della Seconda guerra mondiale, adottando la prospettiva del Parmense. Il primo atto e Prigionieri nei campi alleati: un portale sui militari del Parmense detenuti dagli Alleati.

Background The investigation of transcriptome profiles using short reads in non-model organisms, which lack of well-annotated genomes, is limited by partial gene reconstruction and isoform detection. In contrast, long-reads sequencing techniques revealed their potential to generate complete transcript assemblies even when a reference genome is lacking. Cynara cardunculus var. altilis (DC) (cultivated cardoon) is a perennial hardy crop adapted to dry environments with many industrial and nutraceutical applications due to the richness of secondary metabolites mostly produced in flower heads. The investigation of this species benefited from the recent release of a draft genome, but the transcriptome profile during the capitula formation still remains unexplored. In the present study we show a transcriptome analysis of vegetative and inflorescence organs of cultivated cardoon through a novel hybrid RNA-seq assembly approach utilizing both long and short RNA-seq reads. Results The inclusion of a single Nanopore flow-cell output in a hybrid sequencing approach determined an increase of 15% complete assembled genes and 18% transcript isoforms respect to short reads alone. Among 25,463 assembled unigenes, we identified 578 new genes and updated 13,039 gene models, 11,169 of which were alternatively spliced isoforms. During capitulum development, 3424 genes were differentially expressed and approximately two-thirds were identified as transcription factors including bHLH, MYB, NAC, C2H2 and MADS-box which were highly expressed especially after capitulum opening. We also show the expression dynamics of key genes involved in the production of valuable secondary metabolites of which capitulum is rich such as phenylpropanoids, flavonoids and sesquiterpene lactones. Most of their biosynthetic genes were strongly transcribed in the flower heads with alternative isoforms exhibiting differentially expression levels across the tissues. Conclusions This novel hybrid sequencing approach allowed to improve the transcriptome assembly, to update more than half of annotated genes and to identify many novel genes and different alternatively spliced isoforms. This study provides new insights on the flowering cycle in an Asteraceae plant, a valuable resource for plant biology and breeding in Cynara and an effective method for improving gene annotation.

Appropriate weaning is of crucial importance for critically ill patients requiring respiratory support. However, a remarkable proportion of them are difficult to wean. Levosimendan is a positive inotropic agent characterized by vasodilatory properties, which is used for the treatment of acute decompensated heart failure or in patients needing inotropic treatment, including cardiogenic shock, septic shock, pulmonary hypertension and right ventricular dysfunction, needed for hemodynamic support in patients with diuretic resistance, and weaning either from ventilator or from extracorporeal membrane oxygenation. This position paper will discuss the use of levosimendan in facilitating weaning from cardiorespiratory support in critically ill patients, according to available evidence and the personal experience of a group of Italian Experts.

Whenever a community of practice starts developing an IT solution for its use case(s) it has to face the issue of carefully selecting "the platform" to use. Such a platform should match the requirements and the overall settings resulting from the specific application context (including legacy technologies and solutions to be integrated and reused, costs of adoption and operation, easiness in acquiring skills and competencies). There is no one-size-fits-all solution that is suitable for all application context, and this is particularly true for scientific communities and their cases because of the wide heterogeneity characterising them. However, there is a large consensus that solutions from scratch are inefficient and services that facilitate the development and maintenance of scientific community-specific solutions do exist. This chapter describes how a set of diverse communities of practice efficiently developed their science demonstrators (on analysing and producing user-defined atmosphere data products, greenhouse gases fluxes, particle formation, mosquito diseases) by leveraging the services offered by the D4Science infrastructure. It shows that the D4Science design decisions aiming at streamlining implementations are effective. The chapter discusses the added value injected in the science demonstrators and resulting from the reuse of D4Science services, especially regarding Open Science practices and overall quality of service.

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.

Modern eddy covariance (EC) systems collect high-frequency data (10–20 Hz) via digital outputs of instruments. This is an important evolution with respect to the traditional and widely used mixed analog/digital systems, as fully digital systems help overcome the traditional limitations of transmission reliability, data quality, and completeness of the datasets.However, fully digital acquisition introduces a new problem for guaranteeing data synchronicity when the clocks of the involved devices themselves cannot be synchronized, which is often the case with instruments providing data via serial or Ethernet connectivity in a streaming mode. In this paper, we suggest that, when assembling EC systems in-house, aspects related to timing issues need to be carefully considered to avoid significant flux biases.By means of a simulation study, we found that, in most cases, random timing errors can safely be neglected, as they do not impact fluxes significantly. At the same time, systematic timing errors potentially arising in asynchronous systems can effectively act as filters leading to significant flux underestimations, as large as 10 %, by means of attenuation of high-frequency flux contributions. We characterized the transfer function of such filters as a function of the error magnitude and found cutoff frequencies as low as 1 Hz, implying that synchronization errors can dominate high-frequency attenuations in open- and enclosed-path EC systems. In most cases, such timing errors neither be detected nor characterized a posteriori. Therefore, it is important to test the ability of traditional and prospective EC data logging systems to assure the required synchronicity and propose a procedure to implement such a test relying on readily available equipment.

The eddy-covariance (EC) technique is considered the most direct and reliable method to calculate flux exchanges of the main greenhouse gases over natural ecosystems and agricultural fields. The resulting measurements are extremely important to characterize ecosystem exchanges of carbon, water, energy and other trace gases, and are widely used to validate or constrain parameter of land surface models via data assimilation techniques. For this purpose, the availability of both complete half-hourly flux time series and its associated uncertainty is mandatory. However, uncertainty estimation for EC data is challenging because the standard procedures based on repeated sampling are not suitable for this kind of measurements, and the presence of missing data makes it difficult to build any sensible time series model with time-varying second-order moments that can provide estimates of total random uncertainty. To overcome such limitations, this paper describes a new method in the context of the strategy based on the model residual approach proposed by Richardson et al. (Agric For Meteorol 148(1): 38–50, 2008). The proposed approach consists in (1) estimating the conditional mean process as representative of the true signal underlying observed data and (2) estimating the conditional variance process as representative of the total random uncertainty affecting EC data. The conditional mean process is estimated through the multiple imputation algorithm recently proposed by Vitale et al. (J Environ Inform https://doi.org/10.3808/jei.201800391 , 2018). The conditional variance process is estimated through the stochastic volatility model introduced by Beltratti and Morana (Econ Notes 30(2): 205–234, 2001). This strategy is applied to ten sites that are part of FLUXNET2015 dataset, selected in such a way to cover various ecosystem types under different climatic regimes around the world. The estimated uncertainty is compared with estimates by other well-established methods, and it is demonstrated that the scaling relationship between uncertainty and flux magnitude is preserved. Additionally, the proposed strategy allows obtaining a complete half-hourly time series of uncertainty estimates, which are expected to be useful for many users of EC flux data.

The agreement of Leaf Area Index (LAI) assessments from three indirect methods, i.e. the LAI–2200 Plant Canopy Analyzer, the SS1 SunScan Canopy Analysis System and Digital Hemispherical Photography (DHP) was evaluated for four canopy types, i.e. a short rotation coppice plantation (SRC) with poplar, a Scots pine stand, a Pedunculate oak stand and a maize field. In the SRC and in the maize field, the indirect measurements were compared with direct measurements (litter fall and harvesting). In the low LAI range (0 to 2) the discrepancies of the SS1 were partly explained by the inability to properly account for clumping and the uncertainty of the ellipsoidal leaf angle distribution parameter. The higher values for SS1 in the medium (2 to 6) to high (6 to 8) ranges might be explained by gap fraction saturation for LAI–2200 and DHP above certain values. Wood area index –understood as the woody light-blocking elements from the canopy with respect to diameter growth– accounted for overestimation by all indirect methods when compared to direct methods in the SRC. The inter-comparison of the three indirect methods in the four canopy types showed a general agreement for all methods in the medium LAI range (2 to 6). LAI–2200 and DHP revealed the best agreement among the indirect methods along the entire range of LAI (0 to 8) in all canopy types. SS1 showed some discrepancies with the LAI–2200 and DHP at low (0 to 2) and high ranges of LAI (6 to 8).

The aorta is the largest artery in the body. It arises from the left ventricle, ascends for a short distance in the thorax, then forms an arch, and finally descends through the chest and through the abdomen, where it ends by dividing into two arteries called the common iliac arteries. Echocardiography is useful for every aortic disease that involves size, shape, and atherosclerotic degeneration of the thoracic aorta. With transesophageal echocardiography we can easily visualize and study the aortic root and the proximal ascending aorta, and transesophageal echocardiography can resolve the technical limitation of transthoracic echocardiography in the examination of the thoracic aorta.

One of the most significant indicators for assessing the quality of university careers is the dropout rate between the first and second year. Both literature on the subjects and the results that emerged from numerous specific investigations into the dropouts of the university system, showed the crucial importance of this junction between the first and the second year. Reasons for dropping out can be quite varied, ranging from incorrect and/or insufficient prospective student orientation, the willingness or need to find a job as quickly as possible, to a lack of awareness of not being able to cope with a particular course of study rather than another. In this paper we focus specifically on the problem of dropouts in Italy, addressing it from a dual point of view. At an aggregate level, the analysis deals with dropout rates in Italy between the first and second year, in order to identify the main trends and dynamics at the national level. Subsequently, we analyze individual-level data from the University of Bari Aldo Moro, aiming to identify the most important contributing factors. This individual-level approach has emerged over recent years, and is generally known as ‘Educational Data Mining’, focused on the development of ad hoc methods that can be used to discover regularities and new information within databases from contexts related to education. Using supervised classification methods, we are able to identify retrospectively the profile of students who are most likely to dropout.

Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO2, CH4, N2O, H2O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.

The eddy covariance is a powerful technique to estimate the surface-atmosphere exchange of different scalars at the ecosystem scale. The EC method is central to the ecosystem component of the Integrated Carbon Observation System, a monitoring network for greenhouse gases across the European Continent. The data processing sequence applied to the collected raw data is complex, and multiple robust options for the different steps are often available. For Integrated Carbon Observation System and similar networks, the standardisation of methods is essential to avoid methodological biases and improve comparability of the results. We introduce here the steps of the processing chain applied to the eddy covariance data of Integrated Carbon Observation System stations for the estimation of final CO2, water and energy fluxes, including the calculation of their uncertainties. The selected methods are discussed against valid alternative options in terms of suitability and respective drawbacks and advantages. The main challenge is to warrant standardised processing for all stations in spite of the large differences in e.g. ecosystem traits and site conditions. The main achievement of the Integrated Carbon Observation System eddy covariance data processing is making CO2 and energy flux results as comparable and reliable as possible, given the current micrometeorological understanding and the generally accepted state-of-the-art processing methods.

Modern Eddy Covariance (EC) systems collect high-frequency data (10–20 Hz) via instruments’ digital outputs. While this helps overcome the limits of traditional mixed analog/digital systems, it also introduces the new problem of guaranteeing data synchronicity when the clocks of the involved devices cannot themselves be synchronized, which is often the case with instruments providing data via serial or Ethernet connectivity. By means of a simulation study, we found that in most cases random timing errors can safely be neglected, as they do not impact fluxes to a large extent. On the contrary, realistic systematic timing errors potentially arising in asynchronous systems can lead to flux underestimations as large as 10 %, by means of attenuation of high-frequency flux contributions. We characterize the transfer function of such filters as a function of the error amount and find cut-off frequencies as low as 1 Hz, which means that synchronization errors can dominate high-frequency attenuations in open- and enclosed-path EC systems. In most cases, such timing errors cannot be detected nor quantified a posteriori. Therefore, we suggest testing the ability of prospect EC data logging systems to assure required synchronicity and propose a procedure to implement such a test, which relies on readily available equipment.

Aims To evaluate the accuracy, consumable cost and time around testing (TAT) of a next-generation sequencing (NGS) assay, the Ion Torrent AmpliSeq Colon and Lung Cancer Panel, as an alternative to Sanger sequencing to genotype KRAS, NRAS and BRAF in colorectal cancer patients. Methods The Ion Torrent panel was first verified on cell lines and on control samples and then prospectively applied to routine specimens (n=114), with Sanger sequencing as reference. Results The Ion Torrent panel detected mutant alleles at the 5% level on cell lines and correctly classified all control tissues. The Ion Torrent assay was successfully carried out on most (95.6%) routine diagnostic samples. Of these, 12 (11%) harboured mutations in the BRAF gene and 47 (43%) in either of the two RAS genes, in two cases with a low abundance of RAS mutant allele which was missed by Sanger sequencing. The mean TAT, from sample receipt to reporting, was 10.4 (Sanger) and 13.0 (Ion Torrent) working days. The consumable cost for genotyping KRAS, NRAS and BRAF was €196 (Sanger) and €187 (Ion Torrent). Conclusions Ion Torrent AmpliSeq Colon and Lung Cancer Panel sequencing is as robust as Sanger sequencing in routine diagnostics to select patients for anti-epidermal growth factor receptor (EGFR) therapy for metastatic colorectal cancer.

Scanlon and Sahu (Water Resour Res 44(10): W10418, 2008) proposed an interesting method to estimate assimilation, respiration, evaporation and transpiration directly using high-frequency eddy-covariance measurements. In this note we critically revise this method and, in particular, using the Descartes' rule of sign, we show that one branch of solutions can be directly neglected reducing the analytical complexity of the procedure. We also discuss the stability of the results of the method with respect to the input parameters, especially to the water-use efficiency.

Background Whether intracoronary plasma adiponectin levels may vary in the presence of coronary artery disease and change after coronary revascularization is unexplored. Aim We evaluated plasma adiponectin levels in peripheral vein and coronary circulation before and after coronary artery bypass graft (CABG) in patients with CAD and without CAD (no CAD). Methods We examined 12 patients with CAD who required CABG and 10 patients with non-CAD who underwent cardiac surgery for valve replacement. Peripheral plasma adiponectin and intracoronary adiponectin levels were measured in left coronary artery (LCA) and great cardiac vein (GCV) during coronary angiography at baseline, 24 h and 7 days after cardiac surgery. Results Peripheral and GCV and LCA plasma adiponectin levels were significantly lower in CAD than non-CAD patients (6±3 vs 12±5, p p p p p p Conclusions Our study shows that intracoronary plasma adiponectin is lower in CAD than in no CAD subjects, but rapidly and significantly increases after CABG.

The calcium sensitizer levosimendan has anti-ischaemic effects mediated via the opening of sarcolemmal and mitochondrial ATP-sensitive potassium channels. These properties suggest potential application in clinical situations where cardioprotection would be beneficial, such as cardiac surgery. We thus decided to investigate whether pharmacological pre-treatment with levosimendan reduces intensive care unit (ICU) length of stay in patients undergoing elective myocardial revascularization under cardiopulmonary bypass.One hundred and six patients undergoing elective coronary artery bypass grafting were randomly assigned in a double-blind manner to receive levosimendan or placebo. Levosimendan (24 microg kg(-1)) or placebo was administered as a slow i.v. bolus over a 10 min period before the initiation of bypass.Tracheal intubation time and the length of ICU stay were significantly reduced in the levosimendan group (P0.01). The number of patients needing inotropic support for12 h was significantly higher in the control group (18.0% vs 3.8%; P=0.021). Compared with control patients, levosimendan-treated patients had lower postoperative troponin I concentrations (P0.0001) and a higher cardiac power index (P0.0001).Pre-treatment with levosimendan in patients undergoing surgical myocardial revascularization resulted in less myocardial injury, a reduction in tracheal intubation time, less requirement for inotropic support, and a shorter length of ICU stay.

Objective: The aim of this study was to assess safety and effectiveness of recombinant activated factor VII (rFVIIa) in patients with refractory bleeding undergoing acute aortic dissection surgery with deep hypothermic circulatory arrest. Design: Propensity score-matched analysis. Setting: University hospital. Patients: Twenty-three cardiac surgery patients receiving rF-VIIa compared with 23 matched controls. Interventions: An intravenous bolus of rFVIIa (70 mu g/kg) was administered at the end of a complete transfusion protocol. Five patients received rFVIIa in the operating room, and 18 patients received rFVIIa in the intensive care unit. Four of the intensive care unit patients required a second dose. Measurements and Main Results: Blood loss and transfusion requirements were significantly reduced in the period after rFVIIa administration. A highly significant reduction in hourly blood loss was found at -1 hr vs. 0 hrs and 0 hrs vs. 1 hr (-194 and -77.5 mL, respectively; both adjusted p < .001). In addition, significant improvements of international normalized ratio (p < .001), partial thromboplastin time (p < .001), platelet count (p < .001), fibrinogen (p < .001), and antithrombin (p < .001) were detected after rFVIIa administration. The two groups did not differ regarding adverse events. Conclusions: rFVIIa was successfully used as an additional therapy both during and after acute aortic dissection surgery with deep hypothermic circulatory arrest, when bleeding was refractory to conventional methods. Randomized studies are necessary to confirm the safety and efficacy of rFVIIa in this setting.

Background The calcium sensitizer levosimendan protects against myocardial ischaemia and reperfusion injury in animal models. Methods The present pilot study investigated whether a short infusion before coronary artery bypass grafting (CABG) would protect the myocardium and improve postoperative haemodynamics. Twenty-four patients with stable angina undergoing elective CABG surgery were randomized to receive either placebo or levosimendan (24 µg kg−1) infused i.v. over a 10 min period just before placing the patient on cardiopulmonary bypass. Results Perioperative haemodynamic variables, concentrations of cardiac troponin I over the 48 h postoperative period, and clinical outcomes were assessed. There were no adverse effects related to levosimendan. Compared with control patients, levosimendan-treated patients had lower postoperative troponin I concentrations (P Conclusion Patients receiving a short infusion of levosimendan before CABG showed evidence of less myocardial damage, suggestive of a preconditioning effect. Larger outcome studies are thus indicated to confirm benefit.

Sepsis and other critical illnesses produce a biphasic inflammatory, immune, hormonal, and metabolic response. The acute phase is marked by an abrupt rise in the secretion of so-called stress hormones with an associated increase in mitochondrial and metabolic activity. The combination of severe inflammation and secondary changes in endocrine profile diminish energy production, metabolic rate, and normal cellular processes, leading to multiple organ dysfunction. This perceived failure of organs might instead be a potentially protective mechanism, because reduced cellular metabolism could increase the chances of survival of cells, and thus organs, in the face of an overwhelming insult. We propose that, first, multiple organ failure induced by critical illness is primarily a functional, rather than structural, abnormality. Indeed, it may not be failure as such, but a potentially protective, reactive mechanism. Second, the decline in organ function is triggered by a decrease in mitochondrial activity and oxidative phosphorylation, leading to reduced cellular metabolism. Third, this effect on mitochondria might be the consequence of acute-phase changes in hormones and inflammatory mediators.

Objective The aim was to investigate perioperative factors associated with the development of post-traumatic stress disorder (PTSD) in patients who underwent cardiac surgery. Design Prospective observational study. Setting Single academic center. Participants One hundred twenty-eight consecutive patients scheduled for elective cardiac surgery with cardiopulmonary bypass. Interventions Patients were interviewed within the surgical unit 1 to 3 days before cardiac surgery. Measurements and Main Results Six months after surgery, participants were mailed the modified version of the Posttraumatic Stress Symptom Inventory 10. Of the 71 patients who completed the questionnaire and mailed it back at follow-up, 14 (19.7%) received a diagnosis of PTSD. Seven of 13 female patients who were not treated with β-blockers received a diagnosis of PTSD compared with 0 of 12 who were treated with β-blockers (p = 0.005, Fisher exact test). In a general linear model, including sex and β-blocker treatment as predictors, the Posttraumatic Stress Symptom Inventory 10 score was significantly predicted by β-blockade (F = 4.74, p = 0.033), with a significant interaction between sex and β-blockade (F = 9.72, p = 0.003). Conclusions These findings suggest that the use of β-blockers might be protective against the development of PTSD in women after cardiac surgery.

It has been extensively demonstrated that an elevated heart rate is a modifiable, independent risk factor for cardiovascular events. A high heart rate increases myocardial oxygen consumption and reduces diastolic perfusion time. It can also increase ventricular diastolic pressures and induce ventricular arrhythmias. Critical care patients are prone to develop a stress induced cardiac impairment and consequently an increase in sympathetic tone. This in turn increases heart rate. In this setting, however, heart rate lowering might be difficult because the effects of inotropic drugs could be hindered by heart rate reducing drugs like beta-blockers. Ivabradine is a new selective antagonist of funny channels. It lowers heart rate, reducing the diastolic depolarization slope. Moreover, ivabradine is not active on sympathetic pathways, thus avoiding any interference with inotropic amines. We reviewed the literature available regarding heart rate control in critical care patients, focusing our interest on the use of ivabradine to assess the potential benefits of the drug in this particular setting.

This work describes the results obtained by the statistical downscaling technique for the assessment of changes in precipitation (P), potential evaporation (PE). In turn P and PE are used for computing two indexes of water availability, namely the index of water deficit (WDI) and the aridity index (AI). The analysis is carried out for the Capitanata plain (South-East of Italy) and the A2 scenario of the IPCC Assessment Report 4 (AR4). The large-scale temperature at the 1000hPa level and sea level pressure fields are used as predictors. The local precipitation and potential evaporation time series are used as predictands. The statistical downscaling technique used is based on Canonical Correlation Analysis. A validation procedure of the model is performed and the same technique is used for climatic projections of P, PE and consequently WDI and AI. Climate analysis and projections at this local space scale is an important issue not only for current water management and planning, but also for improving the irrigation efficiency considering future climate change scenarios. © L. Palatella et al., 2012.

This note reports an updated analysis of global climate change and its relationship with Carbon Dioxide (CO2) emissions: advanced methods rooted in econometrics are applied to bivariate climatic time series. We found a strong evidence for the absence of Granger causality from CO2 emissions to global surface temperature: we can conclude that our findings point out that the hypothesis of anthropogenically-induced climate change still need a conclusive confirmation using the most appropriate methods for data analysis.

This study aims to evaluate the potential effects of the climatic variations on the reference evapotranspiration (ET0) and, consequently, on the crop water requirements in the Apulian Tavoliere, one of the largest irrigated districts of Southern Italy. To reach this purpose, both climatic parameters (air temperature and rainfall) and estimated water requirements of ‘processing’ tomato (among the most representative irrigated crops in the district since the mid-1970s and, therefore, chosen as a study-case) were analyzed in order to find out if a time trend exists or does not. The analysis covered the period from 1957 to 2008. The analysis showed that the rainfall amounts decreased (−3.4 mm per year in the analyzed period), while air temperature increased (0.18 °C and 0.25−°C per decade for minimum and maximum, respectively). As a consequence of the climatic variation during the considered period, a growth trend of the ET0 (1.4 mm per year) and water deficit (3.2 mm per year) took place. As a consequence, the water amounts for irrigating the same crop in the considered period were growing. This increased consumption is in agreement with the perception of the farmers of the district but never documented. Through the FAO AquaCrop model, the tomato irrigation water requirements have been simulated during the considered period. The trend analysis of the seasonal evapotranspiration values simulated in 52 years confirmed the increase in tomato water requirements (0.7 mm per year).

The impacts of the climate change for agriculture is an ambitious and unresolved topic due to the complexity of the natural phenomena. The high variability of the Mediterranean basin does not allow us to generalize with enough certainty the results obtained from other researches and other locations. Therefore, a site specific analysis in Capitanata plain was conducted. The aim is to provide a detailed picture of recent change in climate regime in one of the most important agricultural area of South Italy. Climate analysis was carried out and several indices of extreme events were studied on the basis of temperature and precipitation observations registered at experimental station ‘Podere 124’ (CRA-SCA). The period under study is 1979-2008. Increasing trends were identified for the summer season with an intensification of the number of heat waves.