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Background: Studies on the effects of sociodemographic factors on health in aging now include the use of statistical models and machine learning. The aim of this study was to evaluate the determinants of health in aging using machine learning methods and to compare the accuracy with traditional methods. Material/Methods: The health status of 6,209 adults, age 80 years (n=1,357) were measured using an established health metric (0–100) that incorporated physical function and activities of daily living (ADL). Data from the English Longitudinal Study of Ageing (ELSA) included socio-economic and sociodemographic characteristics and history of falls. Health-trend and personal-fitted variables were generated as predictors of health metrics using three machine learning methods, random forest (RF), deep learning (DL) and the linear model (LM), with calculation of the percentage increase in mean square error (%IncMSE) as a measure of the importance of a given predictive variable, when the variable was removed from the model. Results: Health-trend, physical activity, and personal-fitted variables were the main predictors of health, with the%incMSE of 85.76%, 63.40%, and 46.71%, respectively. Age, employment status, alcohol consumption, and household income had the%incMSE of 20.40%, 20.10%, 16.94%, and 13.61%, respectively. Performance of the RF method was similar to the traditional LM (p=0.7), but RF significantly outperformed DL (p=0.006). Conclusions: Machine learning methods can be used to evaluate multidimensional longitudinal health data and may provide accurate results with fewer requirements when compared with traditional statistical modeling., The ATHLOS project has received funding from the European Union Horizon 2020 Research and Innovation Program under grant agreement No. 635316 (EU HORIZON2020-PHC-635316)

Background: Utilization of neoadjuvant chemotherapy for the treatment of muscle invasive bladder cancer in everyday practice differs from that of clinical trials. We describe the patterns of referral for “neoadjuvant chemotherapy”, treatment and outcomes in a multi-disciplinary tumor board. Methods: This was an observational study. Patients referred for neoadjuvant chemotherapy received 4 cycles of dose-dense gemcitabine/cisplatin and were then assessed for definitive local therapy. Patients had a minimum follow-up of 2 years. Primary objective was a 3-year disease-free survival rate. Results: Forty-six patients (clinical stages II: 28, IIIA: 9, IIIB: 4, IVA: 3, missing: 2) were included. Following chemotherapy, 30 underwent radical cystectomy, 8 radiotherapy and 8 no further therapy. Pathological downstaging was observed in 14 (46.6%) of the 30 patients who underwent radical cystectomy; clinical TNM staging was correlated with disease-free survival in the whole population, while clinical and pathological stages, as well as pathological downstaging, were correlated with disease-free survival in patients undergoing radical cystectomy. Three-year disease-free survival rates for the whole cohort and for patients undergoing radical cystectomy were 67.3% (95% confidence interval [CI]: 51–79.2) and 65.2 (95% CI: 44.9–79.6), respectively. Conclusion: Real-world muscle invasive bladder cancer patients who receive neoadjuvant chemotherapy are characterized by more advanced diseases and less frequent radical surgery than those included in clinical trials. Nevertheless, outcomes were comparable and, therefore, offering patients with stage II–IVA muscle invasive bladder cancer neoadjuvant chemotherapy after assessment by multidisciplinary tumor boards should be strongly encouraged. © 2021 Dellis et al.

Sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB) are the most frequent bariatric surgery procedures worldwide. In this prospective study, we examined the association of a genetic risk score (GRS) with loss of excess weight after bariatric surgery. A total of forty-seven morbidly obese Greek patients who underwent SG (81%) or RYGB were recruited, followed up for 2 years and genotyped. Weight loss after surgery was reported as the percentage of excess weight that was lost (%EWL) at 12 and 24 months after surgery. A GRS was constructed based on previously BMI- and WHR-related single nucleotide polymorphisms (SNPs) that were found significantly correlated with weight loss after bariatric surgery in our population. The level of post-surgery %EWL after 12 and 24 months was estimated through two multiple linear regression models that considered the effects of relevant genetic risk variants. The first proposed model suggested that the predictor variables of GRS, age, and BMI had a significant effect on %EWL12m. GRS was significantly associated with %EWL12m, indicating a 4.618% decrease of %EWL12m per score unit. The second model indicated a positive correlation between %EWL24m and %EWL12m, suggesting that while post-surgery weight loss increased during the first 12 months, an increase was expected in the next 12 months as well. GRS was also significantly associated with %EWL24m, indicating approximately 3% decrease of %EWL24m per score unit. GRS can be used in the future together with other preoperative parameters in order to predict the outcome of bariatric surgery.

Waldenström macroglobulinaemia is an indolent B-cell lymphoma with clearly defined criteria for diagnosis, initiation of therapy, and response, which was established by consensus panels at previous International Workshops for Waldenström Macroglobulinaemia (IWWM). The treatment options for Waldenström macroglobulinaemia continued to be researched after the publication of the eighth IWWM consensus recommendations in 2016, and at the tenth IWWM in New York, USA (October, 2018) an international consensus panel was formed to update treatment recommendations. Participants were selected as members of the consensus panel based on their expertise on Waldenström macroglobulinaemia. The initial live discussion took place during the tenth IWWM meeting and two separate teleconferences were held in June, 2019, and January, 2020, to refine recommendations. No external or financial support was received for the elaboration of these recommendations. According to these updated consensus recommendations, alkylating drugs (bendamustine, cyclophosphamide) and proteasome inhibitors (bortezomib, carfilzomib, ixazomib), both in combination with rituximab, as well as BTK inhibitors (ibrutinib), alone or in combination with rituximab, are preferred first-line therapy options for symptomatic patients with Waldenström macroglobulinaemia. In previously treated patients with Waldenström macroglobulinaemia who had an initial durable response, reuse of a previous regimen or another primary therapy regimen are acceptable options. Novel BTK inhibitors (acalabrutinib, zanubrutinib, tirabrutinib) and the BCL2 antagonist venetoclax appear safe and active, and represent emerging options for the treatment of Waldenström macroglobulinaemia. The choice of therapy should be guided by the patient's clinical profile, genomic features, and drug availability. © 2020 Elsevier Ltd

In the light of the COVID-19 pandemic, the International Workshop on Waldenström Macroglobulinemia (IWWM) Treatment Recommendations Panel felt the need to provide a consensus statement for the management of Waldenström Macroglobulinemia (WM) patients during this challenging time. We followed the current recommendations by the American Society of Hematology, which have been modified accordingly to fit the specific realities associated with the management of WM. In this Consensus Statement, the Panel addresses questions related to treatment initiation, preferred therapies, minimizing visit to clinics and infusions centers, supportive care and guidance for WM patients in clinical trials. Finally, we also provide information on timing and appropriateness of testing and management of COVID-19 infected patients, as well as ways to get physicians and patients involved in registry studies that could help others. Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the European Hematology Association. This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Sharing, reusing and reproducing data, software and other digital objects forms the cornerstone of open science practices. Such practices are guided by the Findable, Accessible, Interoperable and Reusable (FAIR) principles. Implementing FAIR principles is not always straightforward, especially in the context of Bioinformatics training. If we are to meet worldwide demand for such training, adhering to the FAIR principles is vital not only for data and software, but also for training materials (any digital object used in a training context, such as slide presentations, exercises, datasets). To facilitate this process, and break the principles down into practical steps, the ELIXIR Training Platform community has put together ten simple rules for making training materials FAIR. Above all is the need to plan to share your training materials online from the outset. Amongst the remaining rules is the importance of describing materials properly, assigning unique identifiers, registering them online, defining access criteria, and using interoperable formats. The full set of ten rules is presented here.

In this paper, an efficient hardware relay is presented that is implemented based on syntactic pattern recognition techniques. The proposed system is capable of detecting faults existing at power system waveforms in $$\upmu $$ s, after reading each peak of the examined signal, aiming to reduce or even to totally prevent safety problems and economic losses. In order syntactic pattern recognition methods to be utilized as a recognition tool of waveforms at transmission lines, the tasks of selecting appropriate primitive patterns, determining the linguistic representation and forming a suitable grammar, should be developed. In this study, attribute grammars have been selected to model the examined signals due to their power to describe syntactic and semantic knowledge. The hardware implementation of the suggested relay, that stands on Earley’s parsing algorithm, is developed using Verilog hardware description language, downloaded on a Virtex 7 XILINX FPGA board and evaluated through real waveforms and data received from IPTO. The obtained results have shown that the presented system could be an efficient alternative tool in the field of transmission lines’ fault detection.

RNA sequencing has become the standard technique for high resolution genome-wide monitoring of gene expression. As such, it often comprises the first step towards understanding complex molecular mechanisms driving various phenotypes, spanning organ development to disease genesis, monitoring and progression. An advantage of RNA sequencing is its ability to capture complex transcriptomic events such as alternative splicing which results in alternate isoform abundance. At the same time, this advantage remains algorithmically and computationally challenging, especially with the emergence of even higher resolution technologies such as single-cell RNA sequencing. Although several algorithms have been proposed for the effective detection of differential isoform expression from RNA-Seq data, no widely accepted golden standards have been established. This fact is further compounded by the significant differences in the output of different algorithms when applied on the same data. In addition, many of the proposed algorithms remain scarce and poorly maintained. Driven by these challenges, we developed a novel integrative approach that effectively combines the most widely used algorithms for differential transcript and isoform analysis using state-of-the-art machine learning techniques. We demonstrate its usability by applying it on simulated data based on several organisms, and using several performance metrics; we conclude that our strategy outperforms the application of the individual algorithms. Finally, our approach is implemented as an R Shiny application, with the underlying data analysis pipelines also available as docker containers.

Flow measurements in industrial ducts and stacks are combined with pollutant or greenhouse gas concentrations to deduce mass emissions. These are then used to populate pollutant emission inventories and are traded under emissions trading schemes. Reference methods for flow are described in ISO 10780 and more recently in EN ISO 16911-1. This paper discusses the key differences between the two standards. We consider sources of error in flow measurement and discuss how each standard addresses them. We find that EN ISO 16911-1 introduces a series of improvements that when combined provide critical uncertainty gains that support compliance with the EU’s Emissions Trading System (EU ETS). All these areas are either not addressed or only partially dealt with in ISO 10780. More specifically, EN ISO 16911-1, (a) specifies a wider range of reference techniques enabling the optimal one to be used for different flue gas environments. (b) Provides a method to correct for cyclonic flow effects. (c) Addresses measurement assembly misalignment and specifies tolerance values for it and (d) provides wall effect correction factors. Most importantly, it has been validated through laboratory and field work. However, the quality control specified in EN ISO 16911-1 is more suitable for measurements to support EU ETS requirements and at times can be too onerous for pollutant mass emission reporting that will usually have less stringent uncertainty requirements.

A parallelized version of a multispecies dynamic flux balance analysis (msdFBA) algorithm is implemented and applied to the AGORA collection of genome-scale metabolic reconstructions for 818 members of the human gut microbiome. The msdFBA method assumes the well stirred interaction mode of all organisms to exchange external metabolites. In each msdFBA simulation, the biomasses the gut microbiome composition of one of 149 patients from NIH Human Microbiome Project is used for initialization in combination with one of 11 different diets used as substrates as defined in the Virtual Metabolic Human database. The union of all species in the patient data comprises 255 different microbes. The patients are either healthy or suffer from inflammatory bowel disease (IBD). The msdFBA simulation is performed for 50 time steps. For all combinations of patients and time steps, the euclidean distance between the vector of the biomasses of the 255 patient species and the evolving vector of biomasses for the same species is calculated, providing the information about the biomass distance to each patient during each simulation. To quantify the overall influence of a diet for all patients, a diet score is defined as the sum of the reciprocal distances to the closest patient at the last time step, in case the closest patient is diseased, subtracted from the respective sum for the case that the closest patient is healthy. With this score, the known beneficial influences both of a high fiber and a gluten free diet for IBD is verified. Noteworthy is the utility of a Mediterranean diet in this context, having similar distance patterns. The proposed method provides an universal platform for the in-silico analysis of different environmental influences like diets for different microbiotas defined by metagenomic quantifications from individual patients and has the potential to generate additional dietary recommendations for the management of various other diseases.

Background: Hereditary amyloidosis refers to a wide spectrum of rare diseases with different causative mutations in the genes of various proteins including transthyretin, apolipoprotein AI and AII, gelsolin, lysozyme, cystatin C, fibrinogen Aα-chain, β2-microglobulin, apolipoprotein CII and CIII. Case presentation: Among hereditary amyloidosis subtypes, we describe here a specific case of Apolipoprotein AI amyloidosis (AApoAI), where the diagnosis began from an almost asymptomatic hepatomegaly followed by the development of primary hypogonadism. Baseline laboratory tests showed increased liver enzymes, while imaging tests revealed a suspected infiltrative liver disease. Patient underwent into liver biopsy and histological examination detected the presence of periodic acid-Schiff (−) and Congo-red (+) amorphous eosinophilic material within normal liver tissue. In the typing of amyloid by immunoelectron microscopy, the liver appeared heavily infiltrated by anti-apoAI (+) amyloid fibrils. Gene sequencing and mutational analysis revealed a single-base mutation at position c.251 T > C resulting in an amino acid substitution from leucine to proline in the mature ApoAI protein. This amino acid change led to lower cleavage and ApoAI deposition into the involved organs. Few years later, our patient remaining without treatment, came with symptoms consistent with primary hypogonadism but testicular involvement with ApoAI deposits could not be proven since the patient refused testicular biopsy. Based on this case, we recap the diagnostic challenges, the clinical manifestations, and the potential treatment options for this indolent hereditary amyloidosis subtype. Conclusions: This case-report enlarges the clinical picture of ApoAI-driven disease and its complex genetic background and in parallel suggests for a more systematic approach in any case with strong suspicion of hereditary amyloidosis. © 2019 The Author(s).

Objects: Invasive pulmonary mold infection usually has devastating outcomes. Timely differentiation between invasive pulmonary aspergillosis (IPA) from pulmonary mucormycosis (PM) is critical for treatment decision-making. However, information on IPA and PM differentiation is limited. Methods: We conducted a retrospective, multicenter, observational study, with proven and probable IPA and PM patients from January 2004 to December 2017. Demographics, clinical manifestations, image reports, histopathological findings, and outcomes were analyzed. Results: A total of 46 IPA (33 proven and 13 probable) and 19 PM (18 proven and one probable) cases were analyzed. The majority of tissues (81% in IPA and 61% in PM) were obtained using bronchoscopy. Prior influenza infection was a predisposing factor for IPA, and abscess formation in CT scan was associated with PM (p = 0.0491, p = 0.0454, respectively). The positive culture rate for PM was lower than that for IPA (37% vs. 67%, p = 0.0294). The galactomannan (GM) level from serum and bronchoalveolar lavage (BAL) fluid was significantly higher in IPA than in PM (3.3 ± 0.5 vs. 0.8 ± 0.6, p = 0.0361; 4.0 ± 0.6 vs. 0.59 ± 0.1, p = 0.0473, respectively). The overall mortality rate was 65%, which was similar among IPA and PM groups. Systemic steroid exposure and high Acute Physiology and Chronic Health Evaluation II (APACHE II) scores on admission were independently correlated to mortality in IPA (p = 0.027, p = 0.026, respectively). However, there was no predictor for mortality found in PM patients. Conclusions: Influenza infection, abscess formation in CT scan, and GM level may help physicians to differentiate IPA and PM. Bronchoscopy-guided biopsy and lavage specimen provide timely and definite diagnosis. The prognosis of IPA is associated with systemic steroid exposure and higher APACHE II scores on admission. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.

Background The use of Cardiovascular Disease (CVD) risk estimation scores in primary prevention has long been established. However, their performance still remains a matter of concern. The aim of this study was to explore the potential of using ML methodologies on CVD prediction, especially compared to established risk tool, the HellenicSCORE. Methods Data from the ATTICA prospective study (n = 2020 adults), enrolled during 2001–02 and followed-up in 2011–12 were used. Three different machine-learning classifiers (k-NN, random forest, and decision tree) were trained and evaluated against 10-year CVD incidence, in comparison with the HellenicSCORE tool (a calibration of the ESC SCORE). Training datasets, consisting from 16 variables to only 5 variables, were chosen, with or without bootstrapping, in an attempt to achieve the best overall performance for the machine learning classifiers. Results Depending on the classifier and the training dataset the outcome varied in efficiency but was comparable between the two methodological approaches. In particular, the HellenicSCORE showed accuracy 85%, specificity 20%, sensitivity 97%, positive predictive value 87%, and negative predictive value 58%, whereas for the machine learning methodologies, accuracy ranged from 65 to 84%, specificity from 46 to 56%, sensitivity from 67 to 89%, positive predictive value from 89 to 91%, and negative predictive value from 24 to 45%; random forest gave the best results, while the k-NN gave the poorest results. Conclusions The alternative approach of machine learning classification produced results comparable to that of risk prediction scores and, thus, it can be used as a method of CVD prediction, taking into consideration the advantages that machine learning methodologies may offer.

Using logic gates is the traditional way of designing logic circuits. However, in many cases, the use of modules is advantageous as the module is considered a uniform structure composed of multiple gates. In this paper, a nonlinear approach is proposed for designing logic circuits for use as modules multiplexers (MUXs) or Reed–Muller universal blocks (RMs). The experimental results show that the method gives better results compared to other methods available in the literature. The main advantages of the method are that it guarantees minimality and it can also handle Boolean functions for incompletely specified functions. The method is general enough and can be used for any kind of modules.

Statistical methods are usually applied in examining diet–disease associations, whereas factor analysis is commonly used for dietary pattern recognition. Recently, machine learning (ML) has been also proposed as an alternative technique in health classification. In this work, the predictive accuracy of statistical v. ML methodologies as regards the association of dietary patterns on CVD risk was tested. During 2001–2002, 3042 men and women (45 (sd 14) years) were enrolled in the ATTICA study. In 2011–2012, the 10-year CVD follow-up was performed among 2020 participants. Item Response Theory was applied to create a metric of combined 10-year cardiometabolic risk, the ‘Cardiometabolic Health Score’, that incorporated incidence of CVD, diabetes, hypertension and hypercholesterolaemia. Factor analysis was performed to extract dietary patterns, on the basis of either foods or nutrients consumed; linear regression analysis was used to assess their association with the cardiometabolic score. Two ML techniques (k-nearest-neighbor’s algorithm and random-forests decision tree) were applied to evaluate participants’ health based on dietary information. Factor analysis revealed five and three factors from foods and nutrients, respectively, explaining 54 and 65 % of the total variation in intake. Nutrient and food pattern regression models showed similar accuracy in correctly classifying an individual according to the cardiometabolic risk (R2=9·6 % and R2=8·3 %, respectively). ML techniques were superior compared with linear regression in correct classification of the individuals according to the Health Score (accuracy approximately 38 v. 6 %, respectively), whereas the two ML methods showed equal classification ability. Conclusively, ML methods could be a valuable tool in the field of nutritional epidemiology, leading to more accurate disease-risk evaluation.

Infections are a major cause of death in patients with multiple myeloma. A post hoc analysis of the phase 3 FIRST trial was conducted to characterize treatment-emergent (TE) infections and study risk factors for TE grade ≥ 3 infection. The number of TE infections/month was highest during the first 4 months of treatment (defined as early infection). Of 1613 treated patients, 340 (21.1%) experienced TE grade ≥ 3 infections in the first 18 months and 56.2% of these patients experienced their first grade ≥ 3 infection in the first 4 months. Risk of early infection was similar regardless of treatment. Based on the analyses of data in 1378 patients through multivariate logistic regression, a predictive model of first TE grade ≥ 3 infection in the first 4 months retained Eastern Cooperative Oncology Group performance status and serum β 2 -microglobulin, lactate dehydrogenase, and hemoglobin levels to define high- and low-risk groups showing significantly different rates of infection (24.0% vs. 7.0%, respectively; P < 0.0001). The predictive model was validated with data from three clinical trials. This predictive model of early TE grade ≥ 3 infection may be applied in the clinical setting to guide infection monitoring and strategies for infection prevention. © 2018 The Author(s).

The introduction of novel agents in the management of multiple myeloma and related plasma cell dyscrasias has changed our treatment approaches and subsequently the outcome of patients. Due to current advances, the European Myeloma Network updated the diagnostic and therapeutic recommendations for patients with Waldenström’s macroglobulinemia (WM), AL-amyloidosis, monoclonal immunoglobulin deposition disease (MIDD), POEMS syndrome, and primary plasma cell leukemia. For patients with WM, the combination of rituximab with chemotherapy remains the treatment cornerstone, while the Bruton-tyrosine kinase inhibitor ibrutinib has been introduced and approved for relapsed/refractory disease. The management of light chain amyloidosis depends on the presence and severity of heart disfunction. If present, intensification with an autologous stem cell transplantation (ASCT) is not recommended. Further aggregation of misfolded light chains could be prevented by doxycycline or monoclonal antibodies targeting amyloid deposits. Initial treatment generally consists of melphalan/dexamethasone or bortezomib-based regimens. For relapsing patients, one can consider proteasome inhibitors, immunomodulatory agents, melphalan or daratumumab. Because intact or light-chain immunoglobulins are also the culprits for MIDD, the small monoclonal plasma cells' clones should be treated and generally respond well to bortezomib-based treatment. POEMS syndrome is a well-defined clinical entity that can present as solitary bone lesions or disseminated disease. Radiation therapy is used for patients with localized disease and result in long-lasting response. Systemic treatment should be proposed to patients with disseminated disease, but regimens that can worsen a pre-existing polyneuropathy should be avoided. PPCL is located at the other end of the spectrum of plasma cell disorders and is associated with an aggressive disease course and poor prognosis. It requires an imminent, multi-phase and novel agents-based therapy, including induction, ASCT, consolidation and maintenance, with short treatment-free intervals. Patients not eligible for transplant procedures require personalized, intensive therapeutic approach. Allogeneic stem cell transplantation can be used in selected patients. © 2018, Springer Nature Limited.

Several studies support an important role of angiogenesis in breast cancer growth and metastasis. The main objectives of the study were to investigate the immunohistochemical expression of vascular endothelial growth factor (VEGF) family ligands (VEGF-A and VEGF-C) and receptors (VEGFR1, VEGFR2 and VEGFR3) in breast cancer and their associations with clinicopathological parameters, cancer subtypes/subgroups and patient outcome. Formalin-fixed paraffin-embedded tumor tissue samples were collected from early-stage breast cancer patients treated with anthracycline-based chemotherapy within a randomized trial. Immunohistochemistry was performed on serial 2.5 μm thick tissue sections from tissue microarray blocks. High VEGF-A, VEGF-C, VEGFR1, VEGFR2 and VEGFR3 protein expression was observed in 11.8% (N = 87), 80.8% (N = 585), 28.1% (N = 202), 64.6% (N = 359) and 71.8% (N = 517) of the cases, respectively. Significant associations were observed among all proteins (all p-values

Growth differentiation factor-15 (GDF-15) improves prognostication in patients with cardiovascular disorders in addition to conventional cardiac markers (N-terminal pro B-type natriuretic peptide [NT-proBNP], troponins [Tns]) and has shown prognostic value in patients with renal diseases. In patients with light chain (AL) amyloidosis, cardiac involvement is the major determinant of prognosis, and cardiac markers define prognosis, whereas biomarkers of renal involvement stratify renal risk. We explored the prognostic importance of serum level of GDF-15 in patients with AL amyloidosis in 2 independent cohorts. The prognostic value of GDF-15 level was initially evaluated in a cohort of 107 consecutive previously untreated patients with AL amyloidosis from Athens, Greece, and was then validated in a second cohort of 202 consecutive previously untreated patients from Pavia, Italy. High GDF-15 level was associated with a higher risk of early death and poor overall survival independently of NT-proBNP and high-sensitivity TnT (hsTnT) or hsTnI levels. At the 6-month landmark, reduction of GDF-15 level ‡25% was associated with improved outcome. GDF-15 level ‡4000 pg/mL was associated with a high risk of progression to dialysis, independently of renal risk defined by estimated glomerular filtration rate and proteinuria, in both cohorts; failure to reduce GDF-15 below this level was associated with increased risk at either the 3- or 6-month landmark, independently of the established renal response or progression criteria. In conclusion, GDF-15 has prognostic implications for different outcomes in patients with AL and adds prognostic information independent of that provided by cardiac and renal risk biomarkers. (Blood. 2018;131(14):1568-1575) © 2018 by The American Society of Hematology

The Internet of Things constitutes a prominent field, integrating smart devices and people into complex systems that may vary in scale. To ensure the constant availability and performance of provided services, alternative distributed architectures should be explored, promoting system scalability. To this end, alternative architectures for the IoT are proposed. Commonly an intermediate layer consisting of aggregators, controlling sensors and actuators and providing a service interface to IoT applications, is incorporated in such architectures. To promote scalability of IoT systems, aggrerators should to operate as autonomous entities. For an aggregator to become autonomous, self-management policies should be enforced. In the paper, we discuss autonomous aggregator software, running on multi-core IoT systems to efficiently implement such policies. A demonstrator for smart buildings, developed as a proof of concept for the proposed concepts, is also presented.

In newly diagnosed multiple myeloma (MM), patients ineligible for front-line autologous stem cell transplantation (ASCT), melphalan and prednisone (MP) with thalidomide (MPT) or bortezomib (VMP) are standard first-line therapeutic options. Despite new treatment regimens incorporating bortezomib or lenalidomide, MM remains incurable. The FIRST study demonstrated significant improvement in progression-free survival (PFS) and overall survival (OS) for the combination of lenalidomide and low-dose dexamethasone (Rd) until progression vs. MPT in transplant-ineligible ndMM patients. However, to date no head-to-head randomized controlled trials (RCTs) have compared Rd or MPT versus VMP. We conducted a network meta-analysis using RCTs identified through a systematic literature review to evaluate the relative efficacy of Rd versus other regimens on survival endpoints in previously untreated MM patients ineligible for ASCT. In this analysis, Rd was associated with a significant PFS and survival advantage versus other first-line treatments (VMP, MPT, MP), challenging the role of alkylators in this setting. © 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Monoclonal immunoglobulin deposition disease (MIDD) is characterized by non-organized immunoglobulin-fragments along renal basement membranes with subsequent organ deterioration. Treatment is directed against the immunoglobulin-producing clone. We treated 18 MIDD patients with bortezomib-based regimens (12 received bortezomib-dexamethasone, 6 bortezomib-dexamethasone with cyclophosphamide). Eleven (61%) patients achieved a hematologic response, but only 6 (33.3%) reached to a complete (CR) or very good partial response (VGPR). Regarding renal outcomes 77.8 and 55.6% had ≥30 and ≥50% reduction of proteinuria, respectively, but 33.3% ended up in end-stage renal disease (ESRD). Among patients with CR or VGPR, median eGFR improvement was 7.7 ml/min/1.73 m2 and none progressed to ESRD, but no significant renal recovery was observed in patients achieving a partial response or less, with 50% progressing to dialysis. Pretreatment eGFR seems to influence renal prognosis. Bortezomib-based treatment is considered an effective approach in MIDD and reaching to a deep hematologic response (≥VGPR) conditionally controls further renal declining. © 2016 Informa UK Limited, trading as Taylor & Francis Group.

Background: Invasive fungal tracheobronchitis (IFT) is a severe form of pulmonary fungal infection that is not limited to immunocompromised patients. Although respiratory failure is a crucial predictor of death, information regarding IFT in critically ill patients is limited. Methods: In this retrospective, multicenter, observational study, we enrolled adults diagnosed as having IFT who had been admitted to the intensive care unit between January 2007 and December 2015. Their demographics, clinical imaging data, bronchoscopic and histopathological findings, and outcomes were recorded. Results: This study included 31 patients who had been diagnosed as having IFT, comprising 24 men and 7 women with a mean age of 64.7 ± 13.7 years. All patients developed respiratory failure and received mechanical ventilation before diagnosis. Eighteen (58.1%) patients had diabetes mellitus, and 12 (38.7%) had chronic lung disease. Four (12.9%) patients had hematologic disease, and none of the patients had neutropenia. Twenty-five (80.6%) patients were diagnosed as having proven IFT, and the remaining patients had probable IFT. Aspergillus spp. (61.3%) were the most common pathogenic species, followed by Mucorales (25.8%) and Candida spp. (6.5%). The diagnoses in six (19.4%) patients were confirmed only through bronchial biopsy and histopathological examination, whereas their cultures of bronchoalveolar lavage fluid were negative for fungi. The overall in-hospital mortality rate was 93.5%. Conclusions: IFT in critically ill patients results in a high mortality rate. Diabetes mellitus is the most prevalent underlying disease, followed by chronic lung disease. In addition to Aspergillus spp., Mucorales is another crucial pathogenic species. Bronchial lesion biopsy is the key diagnostic strategy. © 2017, The Author(s).

The landscape of local and systemic therapy of renal cell carcinoma (RCC) is rapidly changing. The increase in the incidental finding of small renal tumors has increased the application of nephron-sparing procedures, while ten novel agents targeting the vascular endothelial growth factor (VEGF) or the mammalian target of rapamycin pathways, or inhibiting the interaction of the programmed death 1 receptor with its ligand, have been approved since 2006 and have dramatically improved the prognosis of metastatic RCC (mRCC). These rapid developments have resulted in continuous changes in the respective Clinical Practice Guidelines/Expert Recommendations.We conducted a systematic review of the existing guidelines inMEDLINE according to the Preferred Reporting Items for Systematic Review and Meta-Analyses statement, aiming to identify areas of agreement and discrepancy among them and to evaluate the underlying reasons for such discrepancies. Data synthesis identified selection criteria for nonsurgical approaches in renal masses; the role of modern laparoscopic techniques in the context of partial nephrectomy; selection criteria for cytoreductive nephrectomy and metastasectomy in mRCC; systemic therapy of metastatic non-clear-cell renal cancers; and optimal sequence of available agents in mRCC relapsed after anti-VEGF therapy as the major areas of uncertainty. Agreement or uncertainty was not always correlated with the availability of data from phase III randomized controlled trials. Our review suggests that the combination of systematic review and critical evaluation can define practices of wide applicability and areas for future research by identifying areas of agreement and uncertainty among existing guidelines. © AlphaMed Press 2017.

As the internet of things (IoT) becomes more popular, supporting systems and their components become more complex and largely heterogeneous. This paper discusses on a system of systems (SoS) architecture for IoT systems composed by autonomous components. The proposed architecture focuses on a middleware transforming sensor services to REST services, for the development of mixed-criticality applications. The middleware consisting of autonomous aggregation software running on commodity multi-core devices, such as Raspberry Pi. Self-management policies applied are discussed in the paper. The analysis of a smart building system, developed as a use case, provides solid evidence that such an architecture is realistic and can lead to highly competitive systems.

The Future Internet era dictates the deployment of high complexity systems having a variety of properties such as adaptivity, self-configuration and self-optimization. This paper discusses on the design and deployment of a context-aware management architecture, for mixed-criticality applications. The architecture of an autonomous smart building system is described, focusing on diverse requirement satisfaction, including response time, energy efficiency and users' needs. The main objective of the architecture is to investigate the relationships between context awareness characteristics and mixed-criticality aspects, and to identify ways to exploit the one in favor of the other. The analysis provides solid evidence that such an architecture is realistic and can lead to highly competitive systems.

In this paper a parallel algorithm for branch and bound applications is proposed. The algorithm is a general purpose one and it can be used to parallelize effortlessly any sequential branch and bound style algorithm, that is written in a certain format. It is a distributed dynamic scheduling algorithm, i.e. each node schedules the load of its cores, it can be used with different programming platforms and architectures and is a hybrid algorithm (OpenMP, MPI). To prove its validity and efficiency the proposed algorithm has been implemented and tested with numerous examples in this paper that are described in detail. A speed-up of about 9 has been achieved for the tested examples, for a cluster of three nodes with four cores each.

Relapsed urothelial cancer represents an unmet medical need. Vinflunine is a third-generation antimicrotubuline inhibitor and is currently the only approved drug for secondline treatment across the European Union. We conducted a retrospective analysis assessing the efficacy and safety of vinflunine in 71 Greek patients with relapsed urothelial cancer who were treated between 2005 and 2014. An overall 84% of our patients received vinflunine as second-line treatment, 77% had a performance status of Eastern Cooperative Oncology Group scale 0 or 1, and 30% had liver metastasis at the time of vinflunine administration. A median of four cycles of vinflunine were administered (range 1-16). The most common reported adverse events were constipation, fatigue, and anemia. Median progression-free survival was 6.2 months (95% confidence interval: 4.4-8.8) and overall survival was 11.9 months (95% confidence interval: 7.4-21). Two patients (3%) achieved a complete remission, seven a partial remission (10%), and 22 (31%) had stable disease according to an intention-to-treat analysis. Hemoglobin level less than 10 g/dl and Eastern Cooperative Oncology Group performance status greater than 1 were independent adverse prognostic factors. Stratification according to the Bellmunt risk model was also associated with progression-free survival and overall survival in our population. Vinflunine appears to be a safe and effective treatment modality for relapsed urothelial cancer. More effective therapies and more accurate prognostic algorithms should be sought. © 2015 Wolters Kluwer Health, Inc. All rights reserved.