DNA methyltransferase expression (DNMT1, DNMT3a and DNMT3b) as a potential biomarker for anti-VEGF diabetic macular edema response

PURPOSE

DNA methylation is involved in Diabetic Retinopathy progression showing a metabolic memory mechanism. However, the association of DNA methyltransferase with diabetic macular edema is still unknown. We aimed to describe the differences in DNA methyltransferase gene expression in patients with different diabetic macular edema responses.

METHODS

A total of 27 diabetic patients, aged 59-90 years, were prospectively enrolled in this cross-sectional study. The participants were classified into control group (CG, n = 11), diabetic macular edema responders (rDME, n = 9) and non-responder diabetic macular edema (nrDME, n = 7) after anti-vascular endothelial growth factor (anti-VEGF) treatment. Only cases with a complete ophthalmological examination, digital 133° color fundus, and SD-OCT assessments were used. After RNA extraction and first-strand cDNA synthesis, quantitative real-time PCR was performed with specific primers on the CFX Connect™ Real-Time PCR Detection System to assess differential transcriptional expression patterns.

RESULTS

The DNMT1 gene showed a positive correlation (r = 0.617; p = 0.043) with Best Corrected Visual Acuity (BCVA) in CG, a positive correlation (r = 0.917; p = 0.010) with HbA1c in nrDME and a negative correlation (r = -0.659; p = 0.049) with GCL-IPL thickness in rDME. DNMT3A gene showed a positive correlation (r = -0.890; p = 0.001) with Sub-foveal Choroidal thickness in rDME whereas DNMT3b gene showed a negative correlation (r = -0.815; p = 0.007) with HbA1c and RNFL (r = -0.664; p = 0.026) in CG.

CONCLUSIONS

Patients with similar metabolic profile risk factors showed associated DNA methyltransferase transcriptional expression patterns differences fitting with the anti-VEGF diabetic macular edema response. Further studies are needed to clarify if these results (1) reflect disease evolution, (2) translate the therapeutic impact, (3) or can help to predict the therapeutic resistance profile.

An interpretable machine learning approach to estimate the influence of inflammation biomarkers on cardiovascular risk assessment

BACKGROUND AND OBJECTIVE

Cardiovascular disease has a huge impact on health care services, originating unsustainable costs at clinical, social, and economic levels. In this context, patients' risk stratification tools are central to support clinical decisions contributing to the implementation of effective preventive health care. Although useful, these tools present some limitations, in particular, some lack of performance as well as the impossibility to consider new risk factors potentially important in the prognosis of severe cardiac events. Moreover, the actual use of these tools in the daily practice requires the physicians' trust. The main goal of this work addresses these two issues: (i) evaluate the importance of inflammation biomarkers when combined with a risk assessment tool; (ii) incorporation of personalization and interpretability as key elements of that assessment.

METHODS

Firstly, machine learning based models were created to assess the potential of the inflammation biomarkers applied in secondary prevention, namely in the prediction of the six month risk of death/myocardial infarction. Then, an approach based on three main phases was created: (i) set of interpretable rules supported by clinical evidence; (ii) selection based on a machine learning classifier able to identify for a given patient the most suitable subset of rules; (iii) an ensemble scheme combining the previous subset of rules in the estimation of the patient cardiovascular risk. All the results were statistically validated (t-test, Wilcoxon-signed rank test) according to a previous verification of data normality (Shapiro-Wilk).

RESULTS

The proposed methodology was applied to a real acute coronary syndrome patients dataset (N = 1544) from the Cardiology Unit of Coimbra Hospital and Universitary centre. The first assessment was based on the GRACE tool and a Random Forest classifier, the incorporation of inflammation biomarkers achieved SE=0.83; SP=0.84 whereas the original GRACE risk factors reached SE=0.75; SP=0.85. In the second phase, the proposed approach with inflammation biomarkers achieved SE=0.763 and SP=0.778.

CONCLUSIONS

This approach confirms the potential of combining inflammation markers with the GRACE score, increasing SE and SP, when compared with the original GRACE. Additionally, it assures interpretability and personalization, which are critical issues to allow its application in the daily clinical practice.

Early Extracorporeal CPR for Refractory Out-of-Hospital Cardiac Arrest

BACKGROUND

Extracorporeal cardiopulmonary resuscitation (CPR) restores perfusion and oxygenation in a patient who does not have spontaneous circulation. The evidence with regard to the effect of extracorporeal CPR on survival with a favorable neurologic outcome in refractory out-of-hospital cardiac arrest is inconclusive.

METHODS

In this multicenter, randomized, controlled trial conducted in the Netherlands, we assigned patients with an out-of-hospital cardiac arrest to receive extracorporeal CPR or conventional CPR (standard advanced cardiac life support). Eligible patients were between 18 and 70 years of age, had received bystander CPR, had an initial ventricular arrhythmia, and did not have a return of spontaneous circulation within 15 minutes after CPR had been initiated. The primary outcome was survival with a favorable neurologic outcome, defined as a Cerebral Performance Category score of 1 or 2 (range, 1 to 5, with higher scores indicating more severe disability) at 30 days. Analyses were performed on an intention-to-treat basis.

RESULTS

Of the 160 patients who underwent randomization, 70 were assigned to receive extracorporeal CPR and 64 to receive conventional CPR; 26 patients who did not meet the inclusion criteria at hospital admission were excluded. At 30 days, 14 patients (20%) in the extracorporeal-CPR group were alive with a favorable neurologic outcome, as compared with 10 patients (16%) in the conventional-CPR group (odds ratio, 1.4; 95% confidence interval, 0.5 to 3.5; P = 0.52). The number of serious adverse events per patient was similar in the two groups.

CONCLUSIONS

In patients with refractory out-of-hospital cardiac arrest, extracorporeal CPR and conventional CPR had similar effects on survival with a favorable neurologic outcome. (Funded by the Netherlands Organization for Health Research and Development and Maquet Cardiopulmonary [Getinge]; INCEPTION ClinicalTrials.gov number, NCT03101787.).

Challenges, facilitators and barriers to the adoption and use of a web-based national IRD registry: lessons learned from the IRD-PT registry

Rare disease registries increase research accessibility for patients, while providing clinicians/investigators with a coherent data ecosystem necessary to boost research and patient care. The IRD-PT registry is a national, web-based, interoperable registry for inherited retinal degenerations (IRDs) designed to generate scientific knowledge and collect high-quality data on the epidemiology, genomic landscape and natural history of IRDs in Portugal. In two years, the number of enrolled patients almost doubled (537 to 1060). Still, the registry has a lower-than-expected adoption rate, with only 4 centers across Portugal actively enrolling patients. This highlights a strong need to understand factors that may be hindering the registry’s nationwide adoption. The purpose of this manuscript is to analyze challenges, facilitators and barriers to the adoption and use of the IRD-PT registry, and to discuss avenues for improvement, focusing on keeping the registry sustainable in the long run. We believe that this exercise may help other rare disease registries to improve user adherence and engagement, ultimately contributing to develop more sustainable and successful registries in the field.

A Fundamental Study on Compression Properties and Strain Rate Sensitivity of Spray-Dried Amorphous Solid Dispersions

Amorphous solid dispersions (ASDs) are a proven method of improving the solubility and bioavailability of poorly soluble compounds. Immediate release tablets are frequently used as final dosage form for ASDs. Increasing tableting process throughput during clinical development requires using larger, faster tablet presses which subject materials to higher strain rate. Many pharmaceutical materials show strain rate sensitivity, i.e., yield pressure sensitivity to compression speed. Currently, there is only scattered information available in scientific literature on how ASDs behave under different tablet compression speeds. The purpose of this study was to examine spray-dried ASDs' sensitivity to strain rate under compression in a comprehensive study. We also investigated the drivers for such a strain sensitive behavior. A set of sample spray-dried powders, selected for their range of properties, were compressed using a simulated Korsch XL100 profile at 3 and 30 RPM and V-profile at 0.1 and 300 mm/s on a Phoenix compaction simulator. The sample set included samples with varying API content (0-50% w/w), stabilizing polymer (HPMC, HPMC-AS, PVP-VA), particle size, and bulk densities, produced on spray driers from lab to commercial scale. We identified that all ASD samples showed plastic flow and deformation behavior and form robust compacts at slow compression speeds. At high speed, tablet defects occurred. The strain rate sensitivity observed in this study was comparable or slightly superior to that observed for microcrystalline cellulose, known to be a mildly strain rate-sensitive material. We showed that compression speed is a critical process parameter for ASD-containing tablets.

The quest for GRACE 3.0: improving our beloved risk score with machine learning

Background

Although widely recommended for risk assessment of patients with acute coronary syndrome (ACS), the Global Registry of Acute Coronary Events (GRACE) score famously lacks discriminative power. On the other hand, in-hospital serum hemoglobin levels (HG) have been shown to simultaneously forecast both thrombotic and hemorrhagic hazards.

Purpose

To ascertain the extent to which the incorporation of HG in the GRACE score is able to increase its predictive ability.

Methods

Retrospective single-center study encompassing ACS patients consecutively admitted to a Cardiac Intensive Care Unit. Inclusion criteria comprised the acquaintance of GRACE score, HG and vital status on a 6-month follow-up, which served as the outcome. 3 discriminative models were first created: (standard) GRACE score (model 1); GRACE score plus HG, by means of logistic regression (model 2); GRACE score plus HG, by means of multilayer perceptron (a class of feedforward artificial neural network) (model 3). Hereafter, if models 2 and/or 3 were to be found significantly more discriminative than model 1, a correction factor would be calculated, also allowing for the conception of the most predictive model possible (model 4). The discriminative ability was estimated by both the area under the receiver-operating characteristic curve (AUC), and the dyad sensitivity/specificity.

Results

Between April 2009 and December 2016, 1468 patients met study inclusion criteria. Mean age was 68.0±13.2 years and 29.8% were female, while 36.9% presented with ST-segment elevation myocardial infarction. Mean GRACE score was 145.5±47.0 and mean HG was 13.5±2.0. All-cause mortality reached 10.5%, at 6 months. Predictive power for models 1, 2 and 3 may be quantified as follows: AUC 0.6998, sensitivity 77.7% and specificity 62.5%; AUC 0.7818, sensitivity 36.3% and specificity 92.2%; AUC 0.7851, sensitivity 47.7% and specificity 88.5%, respectively. Both models 2 and 3 exhibited more discriminative ability than model 1 (p<0.001), due to their higher specificity. As such, a correction factor was computed (y = −7.8556x + 86.4117) and model 4 was created, displaying a sensitivity of 65.9% and a specificity of 76.5%.

Conclusion

HG single-handedly provides incremental predictive value – namely more specificity – to the GRACE score. In particular, the latter seems to overestimate ACS patients' risk if HG is normal or close to normal.

Funding Acknowledgement

Type of funding sources: None.

Guidelines for the Management of Center-Involving Diabetic Macular Edema: Treatment Options and Patient Monitorization

Diabetic macular edema (DME) is the main cause of visual impairment associated with diabetic retinopathy (DR) and macular laser, during approximately three decades, and was the single treatment option. More recently, intravitreous injections of anti-angiogenics and corticosteroids modified the treatment paradigm associated with significant vision improvements. Nevertheless, not all patients respond satisfactorily to anti-VEGF or corticosteroid injections, so an adequate treatment choice and a prompt switch in therapeutic class is recommended. Several algorithms and guidelines have been proposed for treating center involving DME to improve patients’ vision and quality of life. However, in Portugal, such guidelines are lacking. The present review aimed to provide guidelines for the treatment options and patient monitorization in the management of center-involving DME. We recommend anti-vascular endothelial growth factor (VEGF) as first-line therapy after a clinical evaluation accompanied by a rigorous metabolic control. Depending on the response obtained after 3–6 monthly intravitreal injections we suggest switching outside the class in case of a non-responder, maintaining the anti-VEGF-therapy in responders to anti-angiogenics. The treatment regimen for Dexamethasone intravitreal implant (DEXii) should be pro-re-nata with bi-monthly or quarterly monitoring visits (with a scheduled visit at 6–8 weeks after DEXii for intraocular pressure control). If a patient does not respond to DEXii, switch again to anti-VEGF therapy, combine therapies, or re-evaluate patients diagnose. There is a resilient need to understand the disease, its treatments, regimens available, and convenience for all involved to propose an adequate algorithm for the treatment of diabetic retinopathy (DR) and DME in an individualized regimen. Further understanding of the contributing factors to the development and progression of DR should bring new drug discoveries for more effective and better-tolerated treatments.

Emotional prosody perception in presbycusis patients after auditory rehabilitation

OBJECTIVE

Perception of emotion plays a major role in social interaction. Studies have shown that hearing loss and aging degrade emotional recognition. The main aim of the present study was to evaluate the benefit of first-time hearing aids (HA) for emotional prosody perception in presbycusis patients. Secondary objectives comprised comparison with normal-hearing subjects, and assessment of the impact of demographic and audiologic factors.

METHODS

To assess HA impact, 29 subjects with presbycusis were included. They were tested without HA and 1 month after starting to use HA. A test with emotional hearing stimuli (Montreal Affective Voice test: MAV) was performed at various intensities (50, 65 and 80dB SPL). Patients' experience was evaluated on the Profile of Emotional Competence questionnaire, before and after HA fitting. Results were compared with those of 29 normal-hearing subjects.

RESULTS

Auditory rehabilitation did not significantly improve MAV results (P>0.005), or subjective questionnaire results (P>0.005). Scores remained lower than those of normal-hearing subjects (P<0.001). MAV results, before and after HA, showed significant correlation with pure-tone average (r=-0.88, P<0.001) and age (r=0.44, P=0.018). The older the presbycusis patient and the more severe the hearing loss, the greater the difficulty in recognising emotional prosody.

CONCLUSION

Despite hearing rehabilitation, presbycusis patients' results remained poorer than in normal-hearing subjects.

Non Type-1 Brugada pattern, diagnostic yield of 5 ECG criteria in a young adult cohort

Introduction

Distinguishing between non-Type 1 Brugada pattern (non-T1BrP) and an athlete's ECG remains challenging and may have important prognostic implications. We aimed to study prevalence and the diagnostic yield of experts and non-experts for the electrocardiographic non-T1BrP criteria in the young adults from the Sudden Cardiac Death-Screening Of risk factorS (SCD-SOS) cohort.

Methods

We performed a cross-sectional study in which we reviewed 14662 ECGs of SCD-SOS survey participants and selected 2494 that presented a rSr'-pattern in V1-V2. Among these, 98 were classified by experts in hereditary arrhythmic syndromes for the presence of non-T1BrP and by non-experts who performed manual measurements of the diagnostic criteria based on triangle formed by r'-wave. We estimated intra and interobserver concordance for each criterion, and used logistic regression and receiver operating characteristics (ROC) analysis and C-statistics for diagnostic accuracy and definition of the most appropriate cut-off values.

Results

We detected a rSr'-pattern in V1-V2 in 17% of the individuals and found that it was associated with higher PQ and QTc intervals, male gender and lower BMI. The manual measurements of non-T1BrP criteria were reproducible: we had high intraobserver concordance coefficients (CC) ranging from 0.90 to 0.94 (except for d(B) that had 0.66), but interobserver CC were lower (0.45–0.68). The measurements performed were highly correlated with non-T1BrP diagnosis and the criteria with higher discriminatory capacity were the distance d(B) (AUC 0.77; 95% CI0.69–0.84) and the degree of ST-ascent (AUC 0.79; 95% CI 0.72–0.86). The cut-offs defined by other authors had very low sensitivity (8–12%), despite high specificity (98%), so we defined new cut-offs: d(A) ≥2mm, d(B) ≥1.25mm, d(B)/h ≥0.38, β-angle ≥19° and ST-ascent ≥1mm. The addition of the degree of ST-ascent to a model with these 4 parameters presented an increase in C-statistics from 0.77 (95% CI: 0.68–0.86) to 0.83 (95% CI: 0.75–0.91) for the diagnosis of non-T1BrP by an expert in Sudden Arrhythmic Death and Channelopathies.

Conclusion

A rSr'-pattern in precordial leads V1-V2 is a frequent finding and the detection of non-T1BrP by using the aforementioned 5 measurements is reproducible and accurate. In this study, we describe new cut-off values that may help untrained clinicians to identify young individuals who should be referred for provocative drug testing for Brugada Syndrome.

Accuracy of non-T1 BrP criteria

Funding Acknowledgement

Type of funding source: None

Design, development and deployment of a web-based interoperable registry for inherited retinal dystrophies in Portugal: the IRD-PT

Background

The development of multicenter patient registries promotes the generation of scientific knowledge by using real-world data. A country-wide, web-based registry for inherited retinal dystrophies (IRDs) empowers patients and community organizations, while supporting formal partnerships research. We aim to describe the design, development and deployment of a country-wide, with investigators and stakeholders in the global aim to develop high-value, high-utility web-based, user-friendly and interoperable registry for IRDs—the IRD-PT.

Results

The IRD-PT is a clinical/genetic research registry included in the retina.pt platform (https://www.retina.com.pt), which was developed by the Portuguese Retina Study Group. The retina.pt platform collects data on individuals diagnosed with retinal diseases, from several sites across Portugal, with over 1800 participants and over 30,000 consultations to date. The IRD-PT module interacts with the retina.pt core system which provides a range of basic functions for patient data management, while the IRD-PT module allows data capture for the specific purpose of IRDs. All IRDs are coded accordingly to the International Statistical Classification of Diseases and Related Health Problems (ICD) 9, ICD 10, ICD 11, and Orphanet Rare Disease Ontology (ORPHA codes) to make the IRD-PT interoperable with other IRD registries across the world. Furthermore, the genes are coded according to the Ontology of Genes and Genomes and Online Mendelian Inheritance in Man, whereas signs and symptoms are coded according to the Human Phenotype Ontology. The IRD-PT module pre-launched at Centro Hospitalar e Universitário de Coimbra, the largest reference center for IRDs in Portugal. As of April 1st 2020, finalized data from 537 participants were available for this preliminary analysis.

Conclusions

In the specific field of rare diseases, the use of registries increases research accessibility for individuals, while providing clinicians/investigators with a coherent data ecosystem necessary to boost research. Appropriate design and implementation of patient registries enables rapid decision making and ongoing data mining, ultimately leading to improved patient outcomes. We have described here the principles behind the design, development and deployment of a web-based, user-friendly and interoperable software tool aimed to generate important knowledge and collecting high-quality data on the epidemiology, genomic landscape and natural history of IRDs in Portugal.

Continuous wave milipulse yellow laser treatment for perifoveal exudative vascular anomalous complex-like lesion: A case report

INTRODUCTION

Perifoveal exudative vascular anomalous complex (PEVAC) is an underdiagnosed macular entity. A striking feature of this entity is the unresponsiveness to anti-VEGF treatment. Continuous wave milipulse yellow laser 577 nm (CWMYL-577) has a high absorption peak for oxyhaemoglobin, which allows for low power density use.

PURPOSE

To report a case of a PEVAC-like lesion unresponsive to anti-VEGF and corticosteroids, successfully treated with a single session of minimally invasive focal laser, using CWMYL-577.

METHODS

A diabetic patient with a symptomatic PEVAC-like lesion in the right eye, presented with decreased vision (20/100) and cystoid edema that had persisted for the last 18 months, despite multiple intraocular injections of anti-VEGF and long acting corticosteroids. Three spots of low power density CWMYL-577 (100 mW, 25 ms and 100 µm, using lens with no amplification factor) over the lesion were successfully performed in one laser session. One month and three months after the laser procedure, a gradual decrease of edema and lipid exudates was observed and at a 6-month follow-up, the retina had recovered its normal anatomy with visual acuity of 20/20 that have persisted for 4 years after treatment.

CONCLUSIONS

Minimal invasive focal laser using the CWMYL-577 can be considered an effective therapeutic strategy for symptomatic nonresponding PEVAC-like lesion in patients with DM without DR.

Simultaneous Synthesis and Nitrogen Doping of Free-Standing Graphene Applying Microwave Plasma

An experimental and theoretical investigation on microwave plasma-based synthesis of free-standing N-graphene, i.e., nitrogen-doped graphene, was further extended using ethanol and nitrogen gas as precursors. The in situ assembly of N-graphene is a single-step method, based on the introduction of N-containing precursor together with carbon precursor in the reactive microwave plasma environment at atmospheric pressure conditions. A previously developed theoretical model was updated to account for the new reactor geometry and the nitrogen precursor employed. The theoretical predictions of the model are in good agreement with all experimental data and assist in deeper understanding of the complicated physical and chemical process in microwave plasma. Optical Emission Spectroscopy was used to detect the emission of plasma-generated ‘‘building units’’ and to determine the gas temperature. The outlet gas was analyzed by Fourier-Transform Infrared Spectroscopy to detect the generated gaseous by-products. The synthesized N-graphene was characterized by Scanning Electron Microscopy, Raman, and X-ray photoelectron spectroscopies.

Prognostic and predictive value of the Immunoscore in stage III colon cancer patients treated with oxaliplatin in the prospective IDEA France PRODIGE-GERCOR cohort study

BACKGROUND

The Immunoscore (IS), which prognostically classifies stage I-III colon cancer (CC) patients, was evaluated in the International Duration Evaluation of Adjuvant Therapy (IDEA) France cohort study investigating 3 versus 6 months of oxaliplatin-based adjuvant chemotherapy in stage III CC patients.

PATIENTS AND METHODS

Densities of CD3+ and CD8+ T cells in the tumor and invasive margin were determined by immunohistochemistry, quantified by digital pathology, and converted to IS. Mismatch repair status was determined by immunohistochemistry or by pentaplex PCR. Prediction of disease-free survival (DFS) by IS was analyzed by a multivariable Cox regression model in each study arm. Harrell's C-statistics were used to investigate the IS performance.

RESULTS

Samples of 1322 patients were available. IS Low, Intermediate (Int), and High were observed in 43.6%, 47.0%, and 9.4% of patients, respectively. IS Low identified patients at higher risk of relapse or death compared with Int + High [hazard ratio (HR) = 1.54; 95% confidence interval (CI) 1.24-1.93, P = 0.0001]. The 3-year DFS was 66.80% (95% CI 62.23-70.94) for IS Low and 77.14% (95% CI 73.50-80.35) for IS Int + High. In multivariable analysis, IS remained significantly independently associated with DFS (P = 0.003) when adjusted for sex, histological grade, T/N stage, and microsatellite instability. For mFOLFOX6-treated patients (91.6% of the cohort), a statistical significant interaction was observed for the predictive value of IS for treatment duration (3 versus 6 months) in terms of DFS (P = 0.057). IS Int + High significantly predicted benefit of 6 months of treatment (HR = 0.53; 95% CI 0.37-0.75; P = 0.0004), including clinically low- and high-risk stage III CC (all P < 0.001). Conversely, patients with IS Low (46.4%) did not significantly benefit from the 6-month mFOLFOX6 versus the 3-month mFOLFOX6.

CONCLUSIONS

The prognostic value of IS for DFS was confirmed in patients with stage III CC treated with oxaliplatin-based chemotherapy. Its predictive value for DFS benefit of longer duration of mFOLFOX6 adjuvant treatment was found in IS Int + High. These results will be validated in an external independent cohort. CLINICALTRIALS.

GOV REGISTRATION

NCT03422601; EudraCT Number: 2009-010384-16.

Latent states extraction through Kalman Filter for the prediction of heart failure decompensation events

Cardiac function deterioration of heart failure patients is frequently manifested by the occurrence of decompensation events. One relevant step to adequately prevent cardiovascular status degradation is to predict decompensation episodes in order to allow preventive medical interventions.In this paper we introduce a methodology with the goal of finding onsets of worsening progressions from multiple physiological parameters which may have predictive value in decompensation events. The best performance was obtained for the model composed by only two features using a telemonitoring dataset (myHeart) with 41 patients. Results were achieved by applying leave-one-subject-out validation and correspond to a geometric mean of 83.67%. The obtained performance suggests that the methodology has the potential to be used in decision support solutions and assist in the prevention of this public health burden.

Microwave plasma-based direct synthesis of free-standing N-graphene

Scheme of ethanol/ammonia plasma driven decomposition pathways considering injection of the nitrogen precursor in “hot” and “mild” plasma zone.

A Clinical Interpretable Approach Applied to Cardiovascular Risk Assessment

The effectiveness of predictive models in supporting the Clinical Decision is closely related with their clinical interpretability, i.e.the model should provide clear information on how to reach a specific classification/decision. In fact, the development of interpretable and accurate predictive models assumes a key importance as these tools can be very useful in Clinical Decision Support Systems (CDSS). The development of those models may comprise two main perspectives; existent clinical knowledge (clinical expert knowledge, clinical guidelines, current models, etc.) as well as data driven approaches able to extract (new) knowledge from recent clinical datasets. This work focuses in knowledge extraction from recent datasets (data driven) based on computational intelligence techniques. The main hypothesis that supports this work is that individuals with similar characteristics present a similar risk prof ile. Thus, this work addresses the development of stratification models able to learn distinct groups (or classes) of subjects assessing the similarity between characterizing variables. In particular, in the current study a data-driven supervised cluster approach is proposed aiming the derivation of meaningful rules directly from the dataset. The validation was performed based on the largest Portuguese coronary artery disease patient's dataset, provided by the Portuguese Society of Cardiology and comprising 13902 acute coronary syndrome patients. The goal was to assess the risk of death 30 days after admission. The models' performance was assessed through the sensitivity, specificity and geometric mean values. The obtained results show the potential of this approach, as they represent an acceptable performance (GM= 72%) while the clinical interpretability of the model is assured through the derived rules. Despite the achieved results, there are several research directions to be followed in order to enhance this work.

Complementary role of cardiac computed tomography angiography in the diagnosis of prosthetic aortic valve endocarditis and septic coronary embolism - a case report

A 73-year old man presented with a posterolateral ST-elevated myocardial infarction 9 months after biological aortic valve replacement for aortic valve stenosis. Invasive coronary angiography showed a filling defect across the left main coronary artery bifurcation extending into the left anterior descending artery and the ramus circumflex. Transthoracic echocardiography revealed a thickened prosthesis leaflet with signs of slight stenosis. Cardiac computed tomography angiography showed a mass on the left coronary cusp of the valve prosthesis, suggestive for vegetation or thrombus. The scan also revealed central luminal filling defects, indicative for thrombus or septic emboli. Blood cultures proved positive for Propionibacterium acnes, therefore the patient was treated for prosthetic valve endocarditis. Computed tomography angiography offers high diagnostic accuracy for detecting infective endocarditis and renders complementary information about valvular anatomy, coronary artery disease and the extension of infections.

Using mimicry of body movements by a virtual agent to increase synchronization behavior and rapport in individuals with schizophrenia

Synchronization of behavior such as gestures or postures is assumed to serve crucial functions in social interaction but has been poorly studied to date in schizophrenia. Using a virtual collaborative environment (VCS), we tested 1) whether synchronization of behavior, i.e., the spontaneous initiation of gestures that are congruent with those of an interaction partner, was impaired in individuals with schizophrenia compared with healthy participants; 2) whether mimicry of the patients' body movements by the virtual interaction partner was associated with increased behavioral synchronization and rapport. 19 patients and 19 matched controls interacted with a virtual agent who either mimicked their head and torso movements with a delay varying randomly between 0.5 s and 4 s or did not mimic, and rated feelings of rapport toward the virtual agent after each condition. Both groups exhibited a higher and similar synchronization behavior of the virtual agent forearm movements when they were in the Mimicry condition rather than in the No-mimicry condition. In addition, both groups felt more comfortable with a mimicking virtual agent rather than a virtual agent not mimicking them suggesting that mimicry is able to increase rapport in individuals with schizophrenia. Our results suggest that schizophrenia cannot be considered anymore as a disorder of imitation, particularly as regards behavioral synchronization processes in social interaction contexts.

Risk Prediction of Heart Failure Decompensation Events in Multiparametric Feature Spaces

Cardiac function deterioration of heart failure patients is frequently manifested by the occurrence of decompensation events. One relevant step to adequately prevent cardiovascular status degradation is to predict decompensation episodes in order to allow preventive medical interventions. In this paper we introduce a methodology with the goal of finding relevant feature spaces from multiple physiological parameters which may have predictive value in decompensation events. The best performance was obtained for the feature space comprising the following features: mean weight, standard deviation of the blood pressure and mean of extra-thoracic impedance in a time window of 20 days. Results were achieved by applying leave-one-out validation and correspond to a geometric mean of 88.32%. The obtained performance suggests that the methodology has the potential to be used in decision support solutions and assist in the prevention of this public health burden.

Large-scale synthesis of free-standing N-doped graphene using microwave plasma

Direct assembling of N-graphene, i.e. nitrogen doped graphene, in a controllable manner was achieved using microwave plasmas at atmospheric pressure conditions. The synthesis is accomplished via a single step using ethanol and ammonia as carbon and nitrogen precursors. Tailoring of the high-energy density plasma environment results in a selective synthesis of N-graphene (~0.4% doping level) in a narrow range of externally controlled operational conditions, i.e. precursor and background gas fluxes, plasma reactor design and microwave power. Applying infrared (IR) and ultraviolet (UV) irradiation to the flow of free-standing sheets in the post-plasma zone carries out changes in the percentage of sp², the N doping type and the oxygen functionalities. X-ray photoelectron spectroscopy (XPS) revealed the relative extension of the graphene sheets π-system and the type of nitrogen chemical functions present in the lattice structure. Scanning Electron microscopy (SEM), Transmission Electron microscopy (TEM) and Raman spectroscopy were applied to determine morphological and structural characteristics of the sheets. Optical emission and FT-IR spectroscopy were applied for characterization of the high-energy density plasma environment and outlet gas stream. Electrochemical measurements were also performed to elucidate the electrochemical behavior of NG for supercapacitor applications.

Physiologically motivated detection of Atrial Fibrillation

Atrial Fibrillation (AF) is the most common arrhythmia and it is estimated to affect 33.5 million people worldwide. AF is associated with an increased risk of mortality and morbidity, such as heart failure and stroke and affects mostly older persons and persons with other conditions (e.g. heart failure and coronary artery disease). In order to prevent such life threatening and life quality reducing conditions it is essential to provide better algorithms, capable of being integrated in low-cost personalized health systems. This paper presents a new algorithm for AF detection, which is based on the analysis of the three physiological characteristics of AF: 1) Irregularity of heart rate and; 2) Absence of P-waves and 3) Presence of fibrillatory waves. Based on these characteristics several features were extracted from 12-lead electrocardiograms (ECG) and selected according to their discrimination ability. The classification between AF and non-AF episodes was performed using a Support Vector Machine (SVM) classification model. Our results show that the identification of the fibrillatory patterns, using the proposed features, extracted from the analysis of 12-lead ECG improves the performance of the algorithm to a sensitivity of 88.5% and specificity 92.9%, when compared to our previous single-channel approach, in the same database.

Intravenous Immunoglobulin and Rituximab in HLA Highly Sensitized Kidney Transplant Recipients

INTRODUCTION

HLA-sensitized patients are penalized both in the access to kidney transplantation (KT) and, once transplanted, in the incidence of rejections and long-term allograft survival despite aggressive induction and maintenance therapy.

METHODS

This study retrospectively evaluates the impact of combining T- and B-cell-depleting agents and intravenous immunoglobulin for induction therapy in 45 highly sensitized KT patients (anti-panel reactive antibodies >60%, positive flow cytometry crossmatch or donor specific antibodies at the time of transplantation). The outcome data included the occurrence of biopsy-proven acute rejection, new-onset proteinuria, development of leukopenia, incidence of poliomavirus infection (BK or JC virus), fungal or bacterial infection after KT, de novo neoplasia, graft function, graft loss, or death with functioning KT.

RESULTS

The average panel reactive antibody was 62.5%; 41 patients (91.1%) had ≥3 HLA mismatches with the donor and 91.1% of patients had class I or II anti-HLA antibodies. Fourteen patients (31.1%) presented pre-KT donor-specific antibodies and 6 patients (13.3%) had a positive flow cytometry cross-match at the time of transplantation. The incidence of acute rejection in the first 6 months was 24.4% and the cumulative incidence was 37.8%. Two patients were diagnosed with leukopenia in the first 6 months after KT. Two patients (4.5%) had cytomegalovirus disease, 17 patients (37.8%) were diagnosed with bacterial infections. Cutaneous neoplasms were identified in 5 patients (11.1%) and solid tumors in 4 (8.9%). The death-censored graft survival was 100% in the first 6 months and 93.5% at the last evaluation. Patient survival in the same periods was 97.8% and 93.3%, respectively.

CONCLUSIONS

Induction immunosuppressive therapy with intravenous immunoglobulin and rituximab is effective; outcomes demonstrate an excellent patient and allograft survival and allograft function over the follow-up period.

Detection of wheezes using their signature in the spectrogram space and musical features

In this work thirty features were tested in order to identify the best feature set for the robust detection of wheezes. The features include the detection of the wheezes signature in the spectrogram space (WS-SS) and twenty-nine musical features usually used in the context of Music Information Retrieval. The method proposed to detect the signature of wheezes imposes a temporal Gaussian regularization and a reduction of the false positives based on the (geodesic) morphological opening by reconstruction operator. Our dataset contains wheezes, crackles and normal breath sounds. Four selection algorithms were used to rank the features. The performance of the features was asserted having into account the Matthews correlation coefficient (MCC). All the selection algorithms ranked the WS-SS feature as the most important. A significant boost in performance was obtained by using around ten features. This improvement was independent of the selection algorithm. The use of more than ten features only allows for a small increase of the MCC value.

Microwave plasma enabled synthesis of free standing carbon nanostructures at atmospheric pressure conditions

Schematic representation of the physico-chemical processes involved in the formation of carbon nanostructures in the microwave plasma environment.

Detection of explosive cough events in audio recordings by internal sound analysis

We present a new method for the discrimination of explosive cough events, which is based on a combination of spectral content descriptors and pitch-related features. After the removal of near-silent segments, a vector of event boundaries is obtained and a proposed set of 9 features is extracted for each event. Two data sets, recorded using electronic stethoscopes and comprising a total of 46 healthy subjects and 13 patients, were employed to evaluate the method. The proposed feature set is compared to three other sets of descriptors: a baseline, a combination of both sets, and an automatic selection of the best 10 features from both sets. The combined feature set yields good results on the cross-validated database, attaining a sensitivity of 92.3±2.3% and a specificity of 84.7±3.3%. Besides, this feature set seems to generalize well when it is trained on a small data set of patients, with a variety of respiratory and cardiovascular diseases, and tested on a bigger data set of mostly healthy subjects: a sensitivity of 93.4% and a specificity of 83.4% are achieved in those conditions. These results demonstrate that complementing the proposed feature set with a baseline set is a promising approach.

Artifact detection in accelerometer signals acquired from the carotid

Manual pulse palpation is the common procedure to assess pulse in unconscious patients. This is an error prone procedure during cardiopulmonary resuscitation and therefore automatic pulse detection techniques are being investigated. Accelerometry is an interesting sensing modality for this type of applications. However, accelerometers are highly prone to movement artifacts. Hence, one challenge in designing a solution using accelerometers is to handle motion artifacts properly. In this paper we investigate computationally simple features and classifier to capture movement artifacts in accelerometer signals acquired from the carotid. In particular, based on data obtained from health subjects we show that it is possible to use simple features to achieve an artifact detection sensitivity and specificity higher than 90%.

Pattern discovery and similarity assessment for robust heart sound segmentation

Heart Sound Segmentation plays a fundamental role in pathology detection in Phonocardiogram (PCG) signals. This matter of study has been widely studied in the past decades, however the majority of algorithms' results correspond only to small databases, composed by only quality signals or signals specific to one acquisition system. In this work we proposed a robust segmentation algorithm integrated with clinical information, based on a pattern recognition approach for segmentation of the fundamental heart sounds, which is validated in several databases from different countries and with different acquisition instrumentations. The database comprises a total of 3153 recordings from 764 patients with a variety of pathological conditions. The general results were 95% and 96% of sensitivity and positive predictivity, respectively. Based on the results the algorithm is able to perform with accuracy maintaining generalization capabilities.

Pattern discovery and similarity assessment for robust Heart Sound Segmentation

Heart Sound Segmentation plays a fundamental role in pathology detection in Phonocardiogram (PCG) signals. This matter of study has been widely studied in the past decades, however the majority of algorithms' results correspond only to small databases, composed by only quality signals or signals specific to one acquisition system. In this work we proposed a robust segmentation algorithm integrated with clinical information, based on a pattern recognition approach for segmentation of the fundamental heart sounds, which is validated in several databases from different countries and with different acquisition instrumentations. The database comprises a total of 3153 recordings from 764 patients with a variety of pathological conditions. The general results were 95% and 96% of sensitivity and positive predictivity, respectively. Based on the results the algorithm is able to perform with accuracy maintaining generalization capabilities.

Narrative meaning making and integration: Toward a better understanding of the way falling ill influences quality of life

Falling seriously ill is often experienced as a life event that causes conflict with people’s personal goals and expectations in life and evokes existential questions. This article presents a new humanities approach to the way people make meaning of such events and how this influences their quality of life. Incorporating theories on contingency, narrative identity, and quality of life, we developed a theoretical model entailing the concepts life event, worldview, ultimate life goals, experience of contingency, narrative meaning making, narrative integration, and quality of life. We formulate testable hypotheses and describe the self-report questionnaire that was developed based on the model.

Towards large-scale in free-standing graphene and N-graphene sheets

One of the greatest challenges in the commercialization of graphene and derivatives is production of high quality material in bulk quantities at low price and in a reproducible manner. The very limited control, or even lack of, over the synthesis process is one of the main problems of conventional approaches. Herein, we present a microwave plasma-enabled scalable route for continuous, large-scale fabrication of free-standing graphene and nitrogen doped graphene sheets. The method's crucial advantage relies on harnessing unique plasma mechanisms to control the material and energy fluxes of the main building units at the atomic scale. By tailoring the high energy density plasma environment and complementarily applying in situ IR and soft UV radiation, a controllable selective synthesis of high quality graphene sheets at 2 mg/min yield with prescribed structural qualities was achieved. Raman spectroscopy, scanning electron microscopy, high resolution transmission electron microscopy, X-ray photoelectron spectroscopy and Near Edge X-ray-absorption fine-structure spectroscopy were used to probe the morphological, chemical and microstructural features of the produced material. The method described here is scalable and show a potential for controllable, large-scale fabrication of other graphene derivatives and promotes microwave plasmas as a competitive, green, and cost-effective alternative to presently used chemical methods.

Detection of crackle events using a multi-feature approach

The automatic detection of adventitious lung sounds is a valuable tool to monitor respiratory diseases like chronic obstructive pulmonary disease. Crackles are adventitious and explosive respiratory sounds that are usually associated with the inflammation or infection of the small bronchi, bronchioles and alveoli. In this study a multi-feature approach is proposed for the detection of events, in the frame space, that contain one or more crackles. The performance of thirty-five features was tested. These features include thirty-one features usually used in the context of Music Information Retrieval, a wavelet based feature as well as the Teager energy and the entropy. The classification was done using a logistic regression classifier. Data from seventeen patients with manifestations of adventitious sounds and three healthy volunteers were used to evaluate the performance of the proposed method. The dataset includes crackles, wheezes and normal lung sounds. The optimal detection parameters, such as the number of features, were chosen based on a grid search. The performance of the detection was studied taking into account the sensitivity and the positive predictive value. For the conditions tested, the best results were obtained for the frame size equal to 128 ms and twenty-seven features.

An interpretable data-driven approach for rules construction: Application to cardiovascular risk assessment

The development of models able to produce an understandable decision by the clinicians is of great importance to support their decision. Therefore, the research of methodologies able to extract useful knowledge from existing datasets, as well as to integrate this knowledge into the current clinical evidence, is a key aspect in the enhancement of the clinical decision. This work focuses on the development of interpretable models to assess the patient's condition based on supervised clustering theories, enabling the discovery of a set of features that best represents that condition. At the same time, the technique is supported on a structure that enables the formulation of simple and interpretable rules. Despite its general applicability, the proposed methodology is applied to coronary artery disease (CAD), particularly, in the risk of death assessment (30 days after the admission) of patients that have been admitted to the emergency unit. The validation is performed using a real dataset with Acute Coronary Syndromes, provided by the Portuguese Society of Cardiology. While the methodology produces simple and interpretable rules, the performance achieves an improvement of 7% in relation to geometric mean, when compared with GRACE model (commonly used in Portugal).

A non-exercise based V02max prediction using FRIEND dataset with a neural network

The main goal of this work is the development of models, based on computational intelligence techniques, in particular neural networks, to predict the maximum oxygen consumption value. While the maximum oxygen consumption is a direct mark of the cardiorespiratory fitness, several studies have also confirmed it also as a powerful predictor of risk for adverse outcomes, such as hypertension, obesity, and diabetes. Therefore, the existence of simpler and accurate models, establishing an alternative to standard cardiopulmonary exercise tests, with the potential to be employed in the stratification of the general population in daily clinical practice, would be of major importance. In the current study, different models were implemented and compared: 1) the traditional Wasserman/Hansen equation; 2) linear regression and; 3) non-linear neural networks. Their performance was evaluated based on the "FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base" [1] being, in the present study, a subset of 12262 individuals employed. The accuracy of the models was performed through the computation of sensitivity and specificity values. The results show the superiority of neural networks in the prediction of maximum oxygen consumption.

Can PPG be used for HRV analysis?

Heart rate variability (HRV) represents one of the most promising markers of the autonomic nervous system (ANS) regulation. However, it requires the acquisition of the ECG signal in order to reliably detect the RR intervals, which is not always easily and comfortably available in personal health applications. Additionally, due to progress in single spot optical sensors, photoplethysmography (PPG) is an interesting alternative for heartbeat interval measurements, since it is a more convenient and a less intrusive measurement technique. Driven by the technological advances in such sensors, wrist-worn devices are becoming a commodity, and the interest in the assessment of HRV indexes from the PPG analysis (pulse rate variability - PRV) is rising. In this study, we investigate the hypothesis of using PRV features as surrogates for HRV indexes, in three different contexts: healthy subjects at rest, healthy subjects after physical exercise and subjects with cardiovascular diseases (CVD). Additionally, we also evaluate which are the characteristic points better suited for PRV analysis in these contexts, i.e. the PPG waveform characteristic points leading to the PRV features that present the best estimates of HRV (correlation and error analysis). The achieved results suggest that the PRV can be often used as an alternative for HRV analysis in healthy subjects, with significant correlations above 82%, for both time and frequency features. Contrarily, in the post-exercise and CVD subjects, time and (most importantly) frequency domain features shall be used with caution (mean correlations ranging from 68% to 88%).

Evaluation of lung ventilation distribution in chronic obstructive pulmonary disease patients using the global inhomogeneity index

The global inhomogeneity (GI) index is a electrical impedance tomography (EIT) parameter that quantifies the tidal volume distribution within the lung. In this work the global inhomogeneity index was computed for twenty subjects in order to evaluate his potential use in the detection and follow up of chronic obstructive pulmonary disease (COPD) patients. EIT data of 17 subjects were acquired: 14 patients with the main diagnoses of COPD and 3 healthy subjects which served as a control group. Two or three datasets of around 30 seconds were acquired at 33 scans/s and analysed for each subject. After reconstruction, a tidal EIT image was computed for each breathing cycle and a GI index calculated from it. Results have shown significant differences in GI values between the two groups (0.745 ± 0.007 for COPD and 0.668 ± 0.006 for lung-healthy subject, p <; 0.005). The GI values obtained for each subject have shown small variance between them, which is a good indication of stability. The results suggested that the GI may be useful for the identification and follow up of ventilation problems in patients with COPD.

The use of low-dose metronomic chemotherapy in dogs-insight into a modern cancer field

The era of chemotherapy, which started in the middle of the last century, has been ruled by the routine use of dose-intense protocols, based on the "maximum-tolerated dose" concept. By promoting a balance between patient's quality of life and the goal of rapidly killing as many tumour cells as possible, these protocols still play a prominent role in veterinary oncology. However, with the opening of a new millennium, metronomic chemotherapy (MC) started to be considered a possible alternative to traditional dose-intense chemotherapy. Characterized by a long-term daily administration of lower doses of cytotoxic drugs, this new modality stands out for its unique combination of effects, namely on neovascularization, immune response and tumour dormancy. This article reviews the rationale for treatment with MC, its mechanism of action and the main studies conducted in veterinary medicine, and discusses the key challenges yet to be solved.

A Nonrandomized, Open-Label, Multicenter, Phase 4 Pilot Study on the Effect and Safety of ILUVIEN® in Chronic Diabetic Macular Edema Patients Considered Insufficiently Responsive to Available Therapies (RESPOND)

PURPOSE

The aim of this study was to assess the effectiveness and safety of ILUVIEN® in patients with chronic diabetic macular edema (DME) who were insufficiently responsive to prior therapies.

METHODS

This is a prospective, nonrandomized, multicenter, open-label, phase 4 pilot study assessing the effectiveness and safety of ILUVIEN® involving 12 patients insufficiently responsive to available therapies. Assessments were performed at screening, baseline, week 1, and months 1, 3, 6, 9, and 12. Demographics, medical/ophthalmic history, prior laser, anti-VEGF, and steroid treatments, and lab tests were recorded at screening. A complete ophthalmic examination and SD-OCT were performed at screening and at all follow-up visits.

RESULTS

The patients showed improvements in best-corrected visual acuity (+3.7 letters), with greater improvement among pseudophakic patients (+6.8 letters) compared with phakic patients (-2.5 letters) 12 months after ILUVIEN®. The mean central subfield thickness decrease from baseline to month 12 was statistically significant, with a rapid reduction in the first week. Regarding safety, only 2 patients showed an intraocular pressure (IOP) increase over 25 mm Hg during the study, and the rise in IOP was well managed with eye drops only.

CONCLUSIONS

This prospective and pilot study suggests that ILUVIEN® is safe and may be considered effective for chronic DME patients insufficiently responsive to other available therapies as it showed a rapid and sustained improvement of macular edema obtained after treatment with ILUVIEN®.

Protocol Design Challenges in the Detection of Awareness in Aware Subjects Using EEG Signals

Recent studies have evidenced serious difficulties in detecting covert awareness with electroencephalography-based techniques both in unresponsive patients and in healthy control subjects. This work reproduces the protocol design in two recent mental imagery studies with a larger group comprising 20 healthy volunteers. The main goal is assessing if modifications in the signal extraction techniques, training-testing/cross-validation routines, and hypotheses evoked in the statistical analysis, can provide solutions to the serious difficulties documented in the literature. The lack of robustness in the results advises for further search of alternative protocols more suitable for machine learning classification and of better performing signal treatment techniques. Specific recommendations are made using the findings in this work.

Evaluation of Pax5 expression and comparison with BLA.36 and CD79αcy in feline non-Hodgkin lymphoma

Paired box gene 5 (Pax5) is a widely used B-cell marker for human and canine non-Hodgkin's lymphoma (nHL); however, in the literature there is only one case report using Pax5 in a cat B-cell lymphoma. The purposes of this study were to investigate the expression and detection of B-cell specific activator protein (BSAP) using a monoclonal anti-Pax5 antibody in feline nHL (FnHL) tissue samples to evaluate its diagnostic relevance as a B-cell marker. A total of 45 FnHL samples in 45 cats were evaluated. B-cell lymphoma was the most common immunophenotype (51.1%) for all the samples and T-cell the most common immunophenotype (64.3%) for the gastrointestinal (GI) form. Pax5 stained 82.6% of all B-cell lymphomas and no expression was found in any of the T-cell lymphomas. Anti-Pax5 antibody staining in FnHL is similar to that reported in human and canine counterparts and may offer an excellent B-cell marker in cats.