Model evaluation and ensemble modelling of surface-level ozone in Europe and North America in the context of AQMEII

More than ten state-of-the-art regional air quality models have been applied as part of the Air Quality Model Evaluation International Initiative (AQMEII). These models were run by twenty independent groups in Europe and North America. Standardised modelling outputs over a full year (2006) from each group have been shared on the web-distributed ENSEMBLE system, which allows for statistical and ensemble analyses to be performed by each group. The estimated ground-level ozone mixing ratios from the models are collectively examined in an ensemble fashion and evaluated against a large set of observations from both continents. The scale of the exercise is unprecedented and offers a unique opportunity to investigate methodologies for generating skilful ensembles of regional air quality models outputs. Despite the remarkable progress of ensemble air quality modelling over the past decade, there are still outstanding questions regarding this technique. Among them, what is the best and most beneficial way to build an ensemble of members? And how should the optimum size of the ensemble be determined in order to capture data variability as well as keeping the error low? These questions are addressed here by looking at optimal ensemble size and quality of the members. The analysis carried out is based on systematic minimization of the model error and is important for performing diagnostic/probabilistic model evaluation. It is shown that the most commonly used multi-model approach, namely the average over all available members, can be outperformed by subsets of members optimally selected in terms of bias, error, and correlation. More importantly, this result does not strictly depend on the skill of the individual members, but may require the inclusion of low-ranking skill-score members. A clustering methodology is applied to discern among members and to build a skilful ensemble based on model association and data clustering, which makes no use of priori knowledge of model skill. Results show that, while the methodology needs further refinement, by optimally selecting the cluster distance and association criteria, this approach can be useful for model applications beyond those strictly related to model evaluation, such as air quality forecasting. (C) 2012 Elsevier Ltd. All rights reserved.Peer reviewe

Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data

© 2016. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. Ioannis Kioutsioukis, et al, ‘Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data’, Atmospheric Chemistry and Physics, Vol 16(24): 15629-15652, published 20 December 2016, the version of record is available at doi:10.5194/acp-16-15629-2016 Published by Copernicus Publications on behalf of the European Geosciences Union.Simulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism). Multi-model ensembles can improve the forecast skill, provided that certain mathematical conditions are fulfilled. In this work, four ensemble methods were applied to two different datasets, and their performance was compared for ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM10). Apart from the unconditional ensemble average, the approach behind the other three methods relies on adding optimum weights to members or constraining the ensemble to those members that meet certain conditions in time or frequency domain. The two different datasets were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). The methods are evaluated against ground level observations collected from the EMEP (European Monitoring and Evaluation Programme) and AirBase databases. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill over the single models and the ensemble mean. Verification statistics show that the deterministic models simulate better O3 than NO2 and PM10, linked to different levels of complexity in the represented processes. The unconditional ensemble mean achieves higher skill compared to each station's best deterministic model at no more than 60 % of the sites, indicating a combination of members with unbalanced skill difference and error dependence for the rest. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way. The skill improvements were higher for O3 and lower for PM10, associated with the extent of potential changes in the joint distribution of accuracy and diversity in the ensembles. The skill enhancement was superior using the weighting scheme, but the training period required to acquire representative weights was longer compared to the sub-selecting schemes. Further development of the method is discussed in the conclusion.Peer reviewedFinal Published versio

Mitochondrial Localization of ABC Transporter ABCG2 and Its Function in 5-Aminolevulinic Acid-Mediated Protoporphyrin IX Accumulation

Accumulation of protoporphyrin IX (PpIX) in malignant cells is the basis of 5-aminolevulinic acid (ALA)-mediated photodynamic therapy. We studied the expression of proteins that possibly affect ALA-mediated PpIX accumulation, namely oligopeptide transporter-1 and -2, ferrochelatase and ATP-binding cassette transporter G2 (ABCG2), in several tumor cell lines. Among these proteins, only ABCG2 correlated negatively with ALA-mediated PpIX accumulation. Both a subcellular fractionation study and confocal laser microscopic analysis revealed that ABCG2 was distributed not only in the plasma membrane but also intracellular organelles, including mitochondria. In addition, mitochondrial ABCG2 regulated the content of ALA-mediated PpIX in mitochondria, and Ko143, a specific inhibitor of ABCG2, enhanced mitochondrial PpIX accumulation. To clarify the possible roles of mitochondrial ABCG2, we characterized stably transfected-HEK (ST-HEK) cells overexpressing ABCG2. In these ST-HEK cells, functionally active ABCG2 was detected in mitochondria, and treatment with Ko143 increased ALA-mediated mitochondrial PpIX accumulation. Moreover, the mitochondria isolated from ST-HEK cells exported doxorubicin probably through ABCG2, because the export of doxorubicin was inhibited by Ko143. The susceptibility of ABCG2 distributed in mitochondria to proteinase K, endoglycosidase H and peptide-N-glycosidase F suggested that ABCG2 in mitochondrial fraction is modified by N-glycans and trafficked through the endoplasmic reticulum and Golgi apparatus and finally localizes within the mitochondria. Thus, it was found that ABCG2 distributed in mitochondria is a functional transporter and that the mitochondrial ABCG2 regulates ALA-mediated PpIX level through PpIX export from mitochondria to the cytosol

Detection and characterisation of multi-drug resistance protein 1 (MRP-1) in human mitochondria

BACKGROUND: Overexpression of plasma membrane multi-drug resistance protein 1 (MRP-1) can lead to multidrug resistance. In this study, we describe for the first time the expression of mitochondrial MRP-1 in untreated human normal and cancer cells and tissues. METHODS: MRP-1 expression and subcellular localisation in normal and cancer cells and tissues was examined by differential centrifugation and western blotting, and immunofluorescence microscopy. Viable mitochondria were isolated and MRP-1 efflux activity measured using the calcein-AM functional assay. MRP-1 expression was increased using retroviral infection and specific overexpression confirmed by RNA array. Cell viability was determined by trypan blue exclusion and annexin V-propidium iodide labelling of cells. RESULTS: MRP-1 was detected in the mitochondria of cancer and normal cells and tissues. The efflux activity of mitochondrial MRP-1 was more efficient (55-64%) than that of plasma membrane MRP-1 (11-22%; P<0.001). Induced MRP-1 expression resulted in a preferential increase in mitochondrial MRP-1, suggesting selective targeting to this organelle. Treatment with a non-lethal concentration of doxorubicin (0.85 nM, 8 h) increased mitochondrial and plasma membrane MRP-1, increasing resistance to MRP-1 substrates. For the first time, we have identified MRP-1 with efflux activity in human mitochondria. CONCLUSION: Mitochondrial MRP-1 may be an exciting new therapeutic target where historically MRP-1 inhibitor strategies have limited clinical success

Inflammatory Indices and CA 125: A New Approach to Distinguish Ovarian Carcinoma and Borderline Tumors in Suspicious Ovarian Neoplasms from a Retrospective Observational Multicentric Study

Background and Objectives: This study aimed to evaluate the diagnostic potential of systemic inflammatory indices such as Systemic Inflammation Response Index (SIRI) and Systemic Inflammatory Response (SIR). These were assessed in combination with CA 125 to distinguish ovarian carcinoma (OC) from borderline ovarian tumors (BOT) in patients with suspicious adnexal masses. Materials and Methods: A retrospective multicenter observational study including patients undergoing surgery for suspected ovarian neoplasms was conducted. Inclusion criteria required preoperative blood sampling for inflammatory markers and CA 125. SIR-125 and SIRI-125 were developed by combining SIR and SIRI with CA 125 levels. Diagnostic performance was assessed using ROC curve analysis and linear regression models. Results: A total of 63 patients (42 BOT, 21 OC) were analyzed. OC patients exhibited significantly higher SIR-125 and SIRI-125 values (p &lt; 0.001). ROC analysis demonstrated good diagnostic accuracy, with AUCs of 0.83 (SIR-125) and 0.82 (SIRI-125). SIR-125 showed higher specificity (0.83), while SIRI-125 had superior sensitivity (0.86). Conclusions: SIR-125 and SIRI-125 enhance diagnostic differentiation between OC and BOT, providing a simple, cost-effective preoperative tool. Future prospective studies are needed to validate these findings in broader patient populations

Provenancing Archaeological Wool Textiles from Medieval Northern Europe by Light Stable Isotope Analysis (δ13C, δ15N, δ2H)

We investigate the origin of archaeological wool textiles preserved by anoxic waterlogging from seven medieval archaeological deposits in north-western Europe (c. 700-1600 AD), using geospatial patterning in carbon (δ13C), nitrogen (δ15N) and non-exchangeable hydrogen (δ2H) composition of modern and ancient sheep proteins. δ13C, δ15N and δ2H values from archaeological wool keratin (n = 83) and bone collagen (n = 59) from four sites were interpreted with reference to the composition of modern sheep wool from the same regions. The isotopic composition of wool and bone collagen samples clustered strongly by settlement; inter-regional relationships were largely parallel in modern and ancient samples, though landscape change was also significant. Degradation in archaeological wool samples, examined by elemental and amino acid composition, was greater in samples from Iceland (Reykholt) than in samples from north-east England (York, Newcastle) or northern Germany (Hessens). A nominal assignment approach was used to classify textiles into local/non-local at each site, based on maximal estimates of isotopic variability in modern sheep wool. Light element stable isotope analysis provided new insights into the origins of wool textiles, and demonstrates that isotopic provenancing of keratin preserved in anoxic waterlogged contexts is feasible. We also demonstrate the utility of δ2H analysis to understand the location of origin of archaeological protein samples

Deep sea tests of a prototype of the KM3NeT digital optical module

The first prototype of a photo-detection unit of the future KM3NeT neutrino telescope has been deployed in the deepwaters of the Mediterranean Sea. This digital optical module has a novel design with a very large photocathode area segmented by the use of 31 three inch photomultiplier tubes. It has been integrated in the ANTARES detector for in-situ testing and validation. This paper reports on the first months of data taking and rate measurements. The analysis results highlight the capabilities of the new module design in terms of background suppression and signal recognition. The directionality of the optical module enables the recognition of multiple Cherenkov photons from the same (40)Kdecay and the localisation of bioluminescent activity in the neighbourhood. The single unit can cleanly identify atmospheric muons and provide sensitivity to the muon arrival directions

Clinical outcome of kidney transplantation in HIV-infected recipients: a retrospective study

Kidney transplantation is a safe and effective option for HIV-positive (HIV+) patients. We conducted a retrospective study on HIV+ kidney transplant recipients who underwent transplantation from March 2008 to September 2016.Inclusion criteria for transplantation were CD4þ T-cell count 200 per mm3 and undetectable HIV load. The current study reports the outcome of 19 HIV+ recipients, mostly of Caucasian origin (79%) with a median age of 50 years (interquartile range [IQR], 42–52), who were followed up for a median period of 2.4 years (IQR, 1.2–4.6) after transplantation. Compared with HIV-negative (HIV-) controls, HIV+ recipients had similar one- and three-year graft and patient survival, but significantly lower five-year patient survival (P¼0.03). The differences in graft outcome became less evident with the analysis of death-censored graft survival rates. Cumulative incidence of allograft rejection at one year was 32.9%. Rates of infections were not particularly elevated and HIV replication remained well controlled in all but one patient. A high prevalence of metabolic and endocrine complications (68%) was reported after transplantation. Further studies are needed to evaluate long-term outcomes of HIV+ recipients who underwent kidney transplantation

Ovarian microbiota and ovarian cancer: An overview and update meta-analysis

Background and aim: Ovarian cancer (OC) remains the most lethal gynecological malignancy, al-though advancements in treatment strategies. Emerging data suggested the potential role of ovarian micro-biota in ovarian cancer pathogenesis. The objective of this review and meta-analysis is to analyze available literature to investigate this correlation. Methods: According to the recommendations in the Preferred Re-porting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, the Pubmed database and the Embase database were searched in February 2024. No limitation of the countries was considered. Results: Twenty-seven studies met the inclusion criteria. Five thousand and fourteen ovarian carcinoma cases were included of which 1659 (33.1%) showed dysbiosis. The fixed-effect model and the random-effect model showed no significant correlation between ovarian cancer patients and dysbiosis (p&lt;0.001 and p&lt;0.001 with 95% Confidence Interval 0.21-0.35 and effect size 0.28, respectively). The heterogeneity between studies was high with an I2 of 95.76% (p&lt;0.001). Conclusions: Our meta-analysis suggests no significant difference in dysbiosis prevalence between OC patients and controls. Considering the substantial heterogeneity found, more studies with control groups and precise methodologies are needed to further evaluate the potential role of the ovarian microbiota in the OC. (www.actabiomedica.it)