Decision support methods in diabetic patient management by insulin administration neural network vs. induction methods for knowledge classification

Diabetes mellitus is now recognised as a major worldwide public health problem. At present, about 100 million people are registered as diabetic patients. Many clinical, social and economic problems occur as a consequence of insulin-dependent diabetes. Treatment attempts to prevent or delay complications by applying ‘optimal’ glycaemic control. Therefore, there is a continuous need for effective monitoring of the patient. Given the popularity of decision tree learning algorithms as well as neural networks for knowledge classification which is further used for decision support, this paper examines their relative merits by applying one algorithm from each family on a medical problem; that of recommending a particular diabetes regime. For the purposes of this study, OC1 a descendant of Quinlan’s ID3 algorithm was chosen as decision tree learning algorithm and a generating shrinking algorithm for learning arbitrary classifications as a neural network algorithm. These systems were trained on 646 cases derived from two countries in Europe and were tested on 100 cases which were different from the original 646 cases

Preliminary results of high resolution paleoceanography and paleoclimatology during sapropel S1 deposition (South Limnos Basin, North Aegean Sea).

Οι παλαιοπεριβαλλοντικές συνθήκες κατά τη διάρκεια απόθεσης του σαπροπηλού S1 στο Βόρειο Αιγαίο (πυρήνας βαρύτητας Μ-4, μήκους 2,53 m, λεκάνης νότιας Λήμνου) προσδιορίζονται με βάση την ποσοτική ανάλυση μικροπαλαιοντολογικών (βενθονικά και πλαγκτονικά τρηματοφόρα) και γεωχημικών (OC, δ13Corg) δεικτών. Χαρακτηριστικό του πυρήνα Μ-4 είναι η μεγάλη εμφάνιση του S1 που φτάνει το πάχος των 96 cm. Η μελέτη κατέδειξε ότι, το κατώτερο σαπροπηλικό στρώμα S1a αποτέθηκε σε θερμότερες συνθήκες, εντονότερης δυσοξίας, σε σχέση με το ανώτερο σαπροπηλικό στρώμα S1b.. Αύξηση της παραγωγικότητας και καλύτερη διατήρηση του οργανικού υλικού πιστοποιήθηκαν στο κατώτερο τμήμα του S1. Η διακοπή των σαπροπηλικών συνθηκών στα 8,0 Ka BP που χαρακτηρίζεται κυρίως από την αύξηση της σχετικής συχνότητας των συμφυρματοπαγών μορφών των βενθονικών τρηματοφόρων υποστηρίζει συνθήκες υψηλής οξυγόνωσης του πυθμένα και εισροή γλυκών υδάτων.The paleoenviromental conditions during the depositional interval of sapropel S1 in the northeastern Aegean (gravity core M-4, length 2.53 m; south Limnos basin) are studied based on quantitative micropaleontological (benthic and planktonic foraminifera) and geochemical (OC, δ13Corg) analyses. Special feature of core M-4 is the thickness of S1 layer (96 cm). Our study points that sapropelic layer S1a has been deposited in more dysoxic and warmer conditions in respect to S1b. Both primary productivity and preservation of organic material are more intense during the lower part of S1. An interruption of the sapropelic conditions at 8.0 Ka BP which is mainly characterized by the increase of agglutinated foraminiferal forms confirms both higher oxygen bottom conditions and freshwater input

Rapid Detection of Carbapenem Resistance in Acinetobacter baumannii Using Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry

Rapid detection of carbapenem-resistant Acinetobacter baumannii strains is critical and will benefit patient care by optimizing antibiotic therapies and preventing outbreaks. Herein we describe the development and successful application of a mass spectrometry profile generated by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) that utilized the imipenem antibiotic for the detection of carbapenem resistance in a large series of A. baumannii clinical isolates from France and Algeria. A total of 106 A. baumannii strains including 63 well-characterized carbapenemase-producing and 43 non-carbapenemase-producing strains, as well as 43 control strains (7 carbapenem-resistant and 36 carbapenem-sensitive strains) were studied. After an incubation of bacteria with imipenem for up to 4 h, the mixture was centrifuged and the supernatant analyzed by MALDI-TOF MS. The presence and absence of peaks representing imipenem and its natural metabolite was analyzed. The result was interpreted as positive for carbapenemase production if the specific peak for imipenem at 300.0 m/z disappeared during the incubation time and if the peak of the natural metabolite at 254.0 m/z increased as measured by the area under the curves leading to a ratio between the peak for imipenem and its metabolite being <0.5. This assay, which was applied to the large series of A. baumannii clinical isolates, showed a sensitivity of 100.0% and a specificity of 100.0%. Our study is the first to demonstrate that this quick and simple assay can be used as a routine tool as a point-of-care method for the identification of A. baumannii carbapenemase-producers in an effort to prevent outbreaks and the spread of uncontrollable superbugs

Physical forcing and physical/biochemical variability of the Mediterranean Sea: a review of unresolved issues and directions for future research

This paper is the outcome of a workshop held in Rome in November 2011 on the occasion of the 25th anniversary of the POEM (Physical Oceanography of the Eastern Mediterranean) program. In the workshop discussions, a number of unresolved issues were identified for the physical and biogeochemical properties of the Mediterranean Sea as a whole, i.e., comprising the Western and Eastern sub-basins. Over the successive two years, the related ideas were discussed among the group of scientists who participated in the workshop and who have contributed to the writing of this paper. Three major topics were identified, each of them being the object of a section divided into a number of different sub-sections, each addressing a specific physical, chemical or biological issue: 1. Assessment of basin-wide physical/biochemical properties, of their variability and interactions. 2. Relative importance of external forcing functions (wind stress, heat/moisture fluxes, forcing through straits) vs. internal variability. 3. Shelf/deep sea interactions and exchanges of physical/biogeochemical properties and how they affect the sub-basin circulation and property distribution. Furthermore, a number of unresolved scientific/methodological issues were also identified and are reported in each sub-section after a short discussion of the present knowledge. They represent the collegial consensus of the scientists contributing to the paper. Naturally, the unresolved issues presented here constitute the choice of the authors and therefore they may not be exhaustive and/or complete. The overall goal is to stimulate a broader interdisciplinary discussion among the scientists of the Mediterranean oceanographic community, leading to enhanced collaborative efforts and exciting future discoveries

Towards sustainability in cold chains: Development of a quality, energy and environmental assessment tool (QEEAT)

Quantification of the impact of refrigeration technologies in terms of the quality of refrigerated food, energy usage, and environmental impact is essential to assess cold chain sustainability. In this paper, we present a software tool QEEAT (Quality, Energy and Environmental Assessment Tool) for evaluating refrigeration technologies. As a starting point, a reference product was chosen for the different main food categories in the European cold chain. Software code to predict the products temperature, based on validated heat and mass transfer models, were written in Matlab (The Mathworks Inc., Natick, USA). Also, based on validated kinetic models for the different quality indicators of the reference products, (including fruit, meat, fish, vegetables and dairy products) a software code was written to calculate the quality and safety evolutions of the food product, using the predicted product temperature as input. Finally, software code to calculate the energy usage and Total Equivalent Warming Impact (TEWI) value of different refrigeration technologies was also written in Matlab. All three software codes were integrated, and a graphical user interface was developed. Using the QEEAT, a user can tailor a cold chain scenario by adding cold chain blocks (different steps of a cold chain) and simulating the quality evolution, energy use and emission throughout the chain. Also, the user can modify properties of a cold chain block, by selecting different technologies, or changing set point values. Defaults are provided for input values, and are based on the current practice, and obtained by extensive literature studies and consultation with different experts of the cold chain. Furthermore, the user can build and simulate several chains simultaneously, allowing him/her to compare different chains with respect to quality, energy and emission

Longitudinal Analysis of the Temporal Evolution of Acinetobacter baumannii Strains in Ohio, USA, by Using Rapid Automated Typing Methods

Genotyping methods are essential to understand the transmission dynamics of Acinetobacter baumannii. We examined the representative genotypes of A. baumannii at different time periods in select locations in Ohio, using two rapid automated typing methods: PCR coupled with electrospray ionization mass spectrometry (PCR/ESI-MS), a form of multi-locus sequence typing (MLST), and repetitive-sequence-based-PCR (rep-PCR). Our analysis included 122 isolates from 4 referral hospital systems, in 2 urban areas of Ohio. These isolates were associated with outbreaks at 3 different time periods (1996, 2000 and 2005–2007). Type assignments of PCR/ESI-MS and rep-PCR were compared to each other and to worldwide (WW) clone types. The discriminatory power of each method was determined using the Simpson's index of diversity (DI). We observed that PCR/ESI-MS sequence type (ST) 14, corresponding to WW clone 3, predominated in 1996, whereas ST 12 and 14 co-existed in the intermediate period (2000) and ST 10 and 12, belonging to WW clone 2, predominated more recently in 2007. The shift from WW clone 3 to WW clone 2 was accompanied by an increase in carbapenem resistance. The DI was approximately 0.74 for PCR/ESI-MS, 0.88 for rep-PCR and 0.90 for the combination of both typing methods. We conclude that combining rapid automated typing methods such as PCR/ESI-MS and rep-PCR serves to optimally characterize the regional molecular epidemiology of A. baumannii. Our data also sheds light on the changing sequence types in an 11 year period in Northeast Ohio

Variability and Trends in Physical and Biogeochemical Parameters of the Mediterranean Sea during a Cruise with RV MARIA S. MERIAN in March 2018

The last few decades have seen dramatic changes in the hydrography and biogeochemistry of the Mediterranean Sea. The complex bathymetry and highly variable spatial and temporal scales of atmospheric forcing, convective and ventilation processes contribute to generate complex and unsteady circulation patterns and significant variability in biogeochemical systems. Part of the variability of this system can be influenced by anthropogenic contributions. Consequently, it is necessary to document details and to understand trends in place to better relate the observed processes and to possibly predict the consequences of these changes. In this context we report data from an oceanographic cruise in the Mediterranean Sea on the German research vessel Maria S. Merian (MSM72) in March 2018. The main objective of the cruise was to contribute to the understanding of long-term changes and trends in physical and biogeochemical parameters, such as the anthropogenic carbon uptake and to further assess the hydrographical situation after the major climatological shifts in the eastern and western part of the basin, known as the Eastern and Western Mediterranean Transients. During the cruise, multidisciplinary measurements were conducted on a predominantly zonal section throughout the Mediterranean Sea, contributing to the Med-SHIP and GO-SHIP long-term repeat cruise section that is conducted at regular intervals in the Mediterranean Sea to observe changes and impacts on physical and biogeochemical variables. The data can be accessed at https://doi.org/10.1594/PANGAEA.905902 (Hainbucher et al., 2019), https://doi.org/10.1594/PANGAEA.913512 (Hainbucher, 2020a) https://doi.org/10.1594/PANGAEA.913608, (Hainbucher, 2020b) https://doi.org/10.1594/PANGAEA.913505, (Hainbucher, 2020c) https://doi.org/10.1594/PANGAEA.905887 (Tanhua et al., 2019) and https://doi.org/10.25921/z7en-hn85 (Tanhua et al, 2020)

Discerning natural and anthropogenic organic matter inputs to salt marsh sediments of Ria Formosa lagoon (South Portugal)

Sedimentary organic matter (OM) origin and molecular composition provide useful information to understand carbon cycling in coastal wetlands. Core sediments from threors' Contributionse transects along Ria Formosa lagoon intertidal zone were analysed using analytical pyrolysis (Py-GC/MS) to determine composition, distribution and origin of sedimentary OM. The distribution of alkyl compounds (alkanes, alkanoic acids and alkan-2-ones), polycyclic aromatic hydrocarbons (PAHs), lignin-derived methoxyphenols, linear alkylbenzenes (LABs), steranes and hopanes indicated OM inputs to the intertidal environment from natural-autochthonous and allochthonous-as well as anthropogenic. Several n-alkane geochemical indices used to assess the distribution of main OM sources (terrestrial and marine) in the sediments indicate that algal and aquatic macrophyte derived OM inputs dominated over terrigenous plant sources. The lignin-derived methoxyphenol assemblage, dominated by vinylguaiacol and vinylsyringol derivatives in all sediments, points to large OM contribution from higher plants. The spatial distributions of PAHs (polyaromatic hydrocarbons) showed that most pollution sources were mixed sources including both pyrogenic and petrogenic. Low carbon preference indexes (CPI > 1) for n-alkanes, the presence of UCM (unresolved complex mixture) and the distribution of hopanes (C-29-C-36) and steranes (C-27-C-29) suggested localized petroleum-derived hydrocarbon inputs to the core sediments. Series of LABs were found in most sediment samples also pointing to domestic sewage anthropogenic contributions to the sediment OM.EU Erasmus Mundus Joint Doctorate fellowship (FUECA, University of Cadiz, Spain)EUEuropean Commission [FP7-ENV-2011, 282845, FP7-534 ENV-2012, 308392]MINECO project INTERCARBON [CGL2016-78937-R]info:eu-repo/semantics/publishedVersio

Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study

Background: Bayesian networks (BNs) are machine-learning-based computational models that visualize causal relationships and provide insight into the processes underlying disease progression, closely resembling clinical decision-making. Preoperative identification of patients at risk for lymph node metastasis (LNM) is challenging in endometrial cancer, and although several biomarkers are related to LNM, none of them are incorporated in clinical practice. The aim of this study was to develop and externally validate a preoperative BN to predict LNM and outcome in endometrial cancer patients.Methods and findings: Within the European Network for Individualized Treatment of Endometrial Cancer (ENI-TEC), we performed a retrospective multicenter cohort study including 763 patients, median age 65 years (interquartile range [IQR] 58-71), surgically treated for endometrial cancer between February 1995 and August 2013 at one of the 10 participating European hospitals. A BN was developed using score-based machine learning in addition to expert knowledge. Our main outcome measures were LNM and 5-year disease-specific survival (DSS). Preoperative clinical, histopathological, and molecular biomarkers were included in the network. External validation was performed using 2 prospective study cohorts: the Molecular Markers in Treatment in Endometrial Cancer (MoMaTEC) study cohort, including 446 Norwegian patients, median age 64 years (IQR 59-74), treated between May 2001 and 2010; and the PIpelle Prospective ENDOmetrial carcinoma (PIPENDO) study cohort, including 384 Dutch patients, median age 66 years (IQR 60-73), treated between September 2011 and December 2013. A BN called ENDORISK (preoperative risk stratification in endometrial cancer) was developed including the following predictors: preoperative tumor grade; immunohistochemical expression of estrogen receptor (ER), progesterone receptor (PR), p53, and L1 cell adhesion molecule (L1CAM); cancer antigen 125 serum level; thrombocyte count; imaging results on lymphadenopathy; and cervical cytology. In the MoMaTEC cohort, the area under the curve (AUC) was 0.82 (95% confidence interval [CI] 0.76-0.88) for LNM and 0.82 (95% CI 0.77-0.87) for 5-year DSS. In the PIPENDO cohort, the AUC for 5-year DSS was 0.84 (95% CI 0.78-0.90). The network was well-calibrated. In the MoMaTEC cohort, 249 patients (55.8%) were classified with Conclusions: In this study, we illustrated how BNs can be used for individualizing clinical decision-making in oncology by incorporating easily accessible and multimodal biomarkers. The network shows the complex interactions underlying the carcinogenetic process of endometrial cancer by its graphical representation. A prospective feasibility study will be needed prior to implementation in the clinic.</div