Search

Uromodulin is a kidney-specific glycoprotein which is exclusively produced by the epithelial cells lining the thick ascending limb and early distal convoluted tubule. It is currently recognized as a multifaceted player in kidney physiology and disease, with discrete roles for intracellular, urinary, interstitial and serum uromodulin. Among these, uromodulin modulates renal sodium handling through the regulation of tubular sodium transporters that reabsorb sodium and are targeted by diuretics, such as the loop diuretic–sensitive Na+-K+-2Cl− cotransporter type 2 (NKCC2) and the thiazide-sensitive Na+/Cl− cotransporter (NCC). Given these roles, the contribution of uromodulin to sodium-sensitive hypertension has been proposed. However, recent studies in humans suggest a more complex interaction between dietary sodium intake, uromodulin and blood pressure. This review presents an updated overview of the uromodulin's biology and its various roles, and focuses on the interaction between uromodulin and sodium-sensitive hypertension. [ABSTRACT FROM AUTHOR]

The change in heating and cooling needs of Greece in the near future due to the climate change is assessed in the present study. Global and regional climate models and two different representative concentration pathways (RCPs) are used to simulate the expected change in temperature. A widely used methodology of computation of heating degree days (HDDs) and cooling degree days (CDDs) is employed with a base temperature of 18 °C. In agreement with the expected temperature rise in the near future, an HDD decrease and CDD increase under both RCPs is also expected. The changes under RCP8.5 are stronger compared to those under RCP4.5. Differences related to topography are noted. The HDD decrease is stronger than CDD increase but the relative increase in CDDs is higher than the relative increase in HDDs. The highest absolute decreases in HDDs are expected for February and March while the highest absolute increases in CDDs are expected during the three summer months. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that was first identified in December 2019 and emerged into an ongoing global pandemic. Both the pandemic itself and the associated public restrictive measures of social mobility established with different intensity over different periods in various countries have significantly affected the everyday activities and lifestyles of people all over the world. The impact of lockdown and quarantine measures on hypertension incidence and blood pressure (BP) control is an important topic that requires further investigation. The aim of this review is: a) to present the current evidence regarding the actual effects of public restrictive measures on BP levels and control, originating primarily from studies investigating the impact of public restrictive measures on BP control with the use of various BP phenotypes; b) to summarize the possible pandemic-related effects of factors known to affect BP levels, including both traditional (e.g. dietary habits including alcohol and sodium intake, body weight, smoking and physical activity) and non-traditional (e.g. sleep patterns, air pollution, environmental noise, delayed diagnosis and medication adherence) ones. [ABSTRACT FROM AUTHOR]

Objectives Micro–computed tomography (micro-CT) is a novel, nondestructive, slide-free digital imaging modality that enables the acquisition of high-resolution, volumetric images of intact surgical tissue specimens. The aim of this systematic mapping review is to provide a comprehensive overview of the available literature on clinical applications of micro-CT tissue imaging and to assess its relevance and readiness for pathology practice. Methods A computerized literature search was performed in the PubMed, Scopus, Web of Science, and CENTRAL databases. To gain insight into regulatory and financial considerations for performing and examining micro-CT imaging procedures in a clinical setting, additional searches were performed in medical device databases. Results Our search identified 141 scientific articles published between 2000 and 2021 that described clinical applications of micro-CT tissue imaging. The number of relevant publications is progressively increasing, with the specialties of pulmonology, cardiology, otolaryngology, and oncology being most commonly concerned. The included studies were mostly performed in pathology departments. Current micro-CT devices have already been cleared for clinical use, and a Current Procedural Terminology (CPT) code exists for reimbursement of micro-CT imaging procedures. Conclusions Micro-CT tissue imaging enables accurate volumetric measurements and evaluations of entire surgical specimens at microscopic resolution across a wide range of clinical applications. [ABSTRACT FROM AUTHOR]

Atherosclerotic renovascular disease (ARVD) represents the most common type of renal artery stenosis. In the last decade, a few large trials failed to demonstrate the superiority of standard medical therapy plus percutaneous transluminal renal angioplasty (PTRA) compared with medical therapy alone in lowering blood pressure levels or preventing adverse renal and cardiovascular outcomes in patients with ARVD. However, this issue remains controversial and an ongoing debate focusses on the benefits that selected patients could experience from renal revascularization procedures. In this regard, several pieces of observational data show that PTRA is associated with future cardiorenal benefits in patients presenting with high-risk ARVD phenotypes. Such evidence resulted in a progressive shift in relevant recommendations, with most recent not-graded suggestions supporting that revascularization should be offered in these high-risk subjects. Existing evidence clearly calls for a properly designed randomized controlled trial with selected patients presenting high-risk ARVD phenotypes, in order to confirm the superiority of PTRA versus non-invasive management in this patient group and objectively guide everyday clinical practice. [ABSTRACT FROM AUTHOR]

Background: Immunotherapy of gastrointestinal cancers is challenging; however, several lines of evidence suggest that adoptive transfer of stimulated or modified immune cells support not only protective role of immune cells in tumor microenvironment, but actively participate in the elimination of cancer cells.Methods: In vivo studies employing cancer cell-derived allograft murine models of gastrointestinal cancers were performed. The effects of T helper (Th) 2 cells on gastrointestinal cancers growth and tumor microenvironment composition using adoptive transfer of Th2 cells, interleukin (IL)-5 treatment, and immunofluorescence, multiplex and real-time PCR were explored.Results: Here, we show that Th2 cells play an essential role in the inhibition of colon and pancreas cancers progression. In murine models of gastrointestinal tumors using adoptive transfer of Th2 cells, we identify that Th2 cells are responsible for generation of apoptotic factors and affect macrophage as well as eosinophil recruitment into tumors where they produce cytotoxic factors. Moreover, we found that Th2 cells lead to IL-5 hypersecretion, which links the anti-tumorigenic function of Th2 cells and eosinophils. Importantly, we noted that recombinant IL-5 administration is also related with inhibition of gastrointestinal tumor growth. Finally, using an in vitro approach, we documented that both Th2 cells and eosinophils are directly responsible for gastrointestinal cancer cell killing.Conclusions: These data demonstrate the significance of Th2 cells, eosinophils and IL-5 in the inhibition of gastrointestinal tumor growth, and pointed toward tumor microenvironment reprogramming as a Th2 cell-mediated anti-tumorigenic mechanism of action. [ABSTRACT FROM AUTHOR]

Background: Increased arterial stiffness is suggested to be involved in the pathogenesis of intradialytic‐hypertension (IDH). Ambulatory pulse‐wave‐velocity (PWV) is an independent predictor for all‐cause‐mortality in haemodialysis and its prognostic power is better than office PWV. This is the first study examining ambulatory central blood pressure (BP) and arterial stiffness parameters in patients with and without IDH. Methods: This study examined 45 patients with IDH (SBP rise ≥10 mmHg from pre‐ to post‐dialysis and post‐dialysis SBP ≥150 mmHg) in comparison with 197 patients without IDH. All participants underwent 48‐h ABPM with Mobil‐O‐Graph‐NG; parameters of central haemodynamics, wave reflection and PWV were estimated. Results: Age, dialysis vintage and interdialytic weight gain did not differ between‐groups. IDH patients had higher 48‐h cSBP (131.7 ± 16.2 vs. 119.2 ± 15.2 mmHg, p < 0.001), 48‐h cDBP (86.7 ± 12.7 vs. 79.6 ± 11.5 mmHg, p < 0.001) and 48‐h cPP (45.5 ± 10.4 vs. 39.8 ± 10.0 mmHg, p = 0.001) compared to patients without IDH. Similarly, during day‐ and nighttime periods, cSBP/cDBP and cPP levels were higher in IDH‐patients compared to non‐IDH. Forty‐eight‐hour augmentation pressure and index, but not AIx(75) were higher in IDH patients; 48‐h PWV (10.0 ± 2.0 vs. 9.2 ± 2.1 m/s, p = 0.017) was significantly higher in patients with IDH. The two study groups displayed different trajectories in central BP and PWV over the course of the recording; IDH patients had steadily high values of the above variables during the 2 days of the interdialytic‐interval, whereas non‐IDH patients showed a gradual elevation, with significant increases from the 1st to 2nd 24 h. Conclusions: IDH patients have significantly higher levels of ambulatory central BP and arterial stiffness parameters and a different course over the 48‐h period compared with non‐IDH patients. Increased arterial stiffness could be a prominent factor associated with the high burden of cardiovascular disease in this population. [ABSTRACT FROM AUTHOR]

Background: Diabetes mellitus (DM) and coronary artery disease (CAD) constitute inter-related clinical entities. Biomarker profiling emerges as a promising tool for the early diagnosis and risk stratification of either DM or CAD. However, studies assessing the predictive capacity of novel metabolomics biomarkers in coexistent CAD and DM are scarce. Methods: This post-hoc analysis of the CorLipid trial (NCT04580173) included 316 patients with CAD and comorbid DM who underwent emergency or elective coronary angiography due to acute or chronic coronary syndrome. Cox regression analyses were performed to identify metabolomic predictors of the primary outcome, which was defined as the composite of major adverse cardiovascular or cerebrovascular events (MACCE: cardiovascular death, myocardial infarction, stroke, major bleeding), repeat unplanned revascularizations and cardiovascular hospitalizations. Linear regression analyses were also performed to detect significant predictors of CAD complexity, as assessed by the SYNTAX score. Results: After a median 2-year follow up period (IQR = 0.7 years), the primary outcome occurred in 69 (21.8%) of patients. Acylcarnitine ratio C4/C18:2, apolipoprotein (apo) B, history of heart failure (HF), age > 65 years and presence of acute coronary syndrome were independent predictors of the primary outcome in diabetic patients with CAD (aHR = 1.89 [1.09, 3.29]; 1.02 [1.01, 1.04]; 1.28 [1.01, 1.41]; 1.04 [1.01, 1.05]; and 1.12 [1.05–1.21], respectively). Higher levels of ceramide ratio C24:1/C24:0, acylcarnitine ratio C4/C18:2, age > 65 and peripheral artery disease were independent predictors of higher CAD complexity (adjusted β = 7.36 [5.74, 20.47]; 3.02 [0.09 to 6.06]; 3.02 [0.09, 6.06], respectively), while higher levels of apoA1 were independent predictors of lower complexity (adjusted β= − 0.65 [− 1.31, − 0.02]). Conclusions: In patients with comorbid DM and CAD, novel metabolomic biomarkers and metabolomics-based prediction models could be recruited to predict clinical outcomes and assess the complexity of CAD, thereby enabling the integration of personalized medicine into routine clinical practice. These associations should be interpreted taking into account the observational nature of this study, and thus, larger trials are needed to confirm its results and validate them in different and larger diabetic populations. [ABSTRACT FROM AUTHOR]

Background: The role of non-invasive ventilation (NIV) in severe COVID-19 remains a matter of debate. Therefore, the utilization and outcome of NIV in COVID-19 in an unbiased cohort was determined. Aim: The aim was to provide a detailed account of hospitalized COVID-19 patients requiring non-invasive ventilation during their hospital stay. Furthermore, differences of patients treated with NIV between the first and second wave are explored. Methods: Confirmed COVID-19 cases of claims data of the Local Health Care Funds with non-invasive and/or invasive mechanical ventilation (MV) in the spring and autumn pandemic period in 2020 were comparable analysed. Results: Nationwide cohort of 17.023 cases (median/IQR age 71/61–80 years, 64% male) 7235 (42.5%) patients primarily received IMV without NIV, 4469 (26.3%) patients received NIV without subsequent intubation, and 3472 (20.4%) patients had NIV failure (NIV-F), defined by subsequent endotracheal intubation. The proportion of patients who received invasive MV decreased from 75% to 37% during the second period. Accordingly, the proportion of patients with NIV exclusively increased from 9% to 30%, and those failing NIV increased from 9% to 23%. Median length of hospital stay decreased from 26 to 21 days, and duration of MV decreased from 11.9 to 7.3 days. The NIV failure rate decreased from 49% to 43%. Overall mortality increased from 51% versus 54%. Mortality was 44% with NIV-only, 54% with IMV and 66% with NIV-F with mortality rates steadily increasing from 62% in early NIV-F (day 1) to 72% in late NIV-F (>4 days). Conclusions: Utilization of NIV rapidly increased during the autumn period, which was associated with a reduced duration of MV, but not with overall mortality. High NIV-F rates are associated with increased mortality, particularly in late NIV-F. [ABSTRACT FROM AUTHOR]

Granulocyte colony-stimulating factor (G-CSF) is produced at high levels in several cancers and is directly linked with metastasis in gastrointestinal (GI) cancers. In order to further understand the alteration of molecular compositions and biochemical features triggered by G-CSF treatment at molecular and cell levels, we sought to investigate the long term treatment of G-CSF on colon and breast cancer cells measured by label-free, non-invasive single-cell Raman microspectroscopy. Raman spectrum captures the molecule-specific spectral signatures ("fingerprints") of different biomolecules presented on cells. In this work, mouse breast cancer line 4T1 and mouse colon cancer line CT26 were treated with G-CSF for 7 weeks and subsequently analyzed by machine learning based Raman spectroscopy and gene/cytokine expression. The principal component analysis (PCA) identified the Raman bands that most significantly changed between the control and G-CSF treated cells. Notably, here we proposed the concept of aggressiveness score, which can be derived from the posterior probability of linear discriminant analysis (LDA), for quantitative spectral analysis of tumorigenic cells. The aggressiveness score was effectively applied to analyze and differentiate the overall cell biochemical changes of G-CSF-treated two model cancer cells. All these tumorigenic progressions suggested by Raman analysis were confirmed by pro-tumorigenic cytokine and gene analysis. A high correlation between gene expression data and Raman spectra highlights that the machine learning based non-invasive Raman spectroscopy offers emerging and powerful tools to better understand the regulation mechanism of cytokines in the tumor microenvironment that could lead to the discovery of new targets for cancer therapy. [ABSTRACT FROM AUTHOR]

We report new nanocomposites with poly(benzoxazine-co-epoxy) matrix reinforced with 1 wt% graphene. Curabox 24-111, a benzoxazine resin was copolymerised with Epilok 60-566, a mixture of epoxy resins. Copolymerisation was also carried out in the presence of different graphene powders, namely, Nanene-001 and Nanene-002, used as single fillers and as mixture (relative weight ratio 70:30 or 30:70). DSC results showed the addition of either single filler caused a delay in polymerisation and an increase in the exothermic peak temperature of the curing reaction with a related reduction in ΔH Total. compared to the neat copolymer. Copolymerisation showed a 38% reduction and 24% increase in tensile modulus (E) compared to the neat polybenzoxazine and epoxy polymer, with a respective 18% and 30% reduction in tensile strength (TS). Nanocomposites with 0.7wt% Nanene-002 + 0.3 wt% Nanene-001 showed the highest increase of 35% in TS, a 1.6% reduction in E and 36% increase in elongation at break (EB) compared to the neat copolymer matrix. Samples with 1 wt% Nanene-001 showed the largest reduction of 21% in E, a 27% increase in TS and a 45% increase in EB. Additionally, TGA thermographs showed a 22°C increase in the onset of degradation (300°C–322°C) improving the materials thermal stability. [ABSTRACT FROM AUTHOR]

Visual sensing of the environment is crucial for flying an unmanned aerial vehicle (UAV) and is a centerpiece of many related applications. The ability to run computer vision and machine learning algorithms onboard an unmanned aerial system (UAS) is becoming more of a necessity in an effort to alleviate the communication burden of high-resolution video streaming, to provide flying aids, such as obstacle avoidance and automated landing, and to create autonomous machines. Thus, there is a growing interest on the part of many researchers in developing and validating solutions that are suitable for deployment on a UAV system by following the general trend of edge processing and airborne computing, which transforms UAVs from moving sensors into intelligent nodes that are capable of local processing. In this paper, we present, in a rigorous way, the design and implementation of a 12.85 kg UAV system equipped with the necessary computational power and sensors to serve as a testbed for image processing and machine learning applications, explain the rationale behind our decisions, highlight selected implementation details, and showcase the usefulness of our system by providing an example of how a sample computer vision application can be deployed on our platform. [ABSTRACT FROM AUTHOR]

This work studies the effects of graphene nanoplatelets (GNPs) and hexagonal boron nitride (hBN) on the thermal and mechanical properties of polydimethylsiloxane (PDMS) matrix for use as thermal interface materials (TIMs). Solution mixing of 10 wt% GNPs and 40 wt% hBN with PDMS produced TIMs with through-plane thermal conductivity (TC) of 1.24 W m−1 K−1 showing a 519% increase relative to the neat matrix. A synergistic effect between GNPs and hBN was particularly demonstrated when in samples with 48 wt% total filler content, 8 wt% hBN was replaced by GNPs, and the TC was increased by 33%. The elongation at break of the hBN (40 wt%)/GNP (8 wt%) samples reached 151%, representing a 160% increase when compared to samples with only 40 wt% hBN. Moreover, the shore hardness of samples containing 40 wt% hBN was 68 A, and the introduction of 8 wt% GNPs caused a decrease to 38 A. DSC measurements on samples filled with hBN and GNPs showed a reduction up to 65% in Ultimate Heat of Curing, which was attributed to the presence of graphene flakes interfering with the curing of the matrix. Graphene was found to be an efficient filler in tuning the thermal and mechanical properties of TIMs. [ABSTRACT FROM AUTHOR]

Background: Stress induced hyperglycemia (SIH) is common among patients with ST-elevation myocardial infarction (STEMI), even in patients without diabetes mellitus. However, evidence regarding its role on the angiographic outcomes and the prognosis of patients presenting with STEMI is scarce. Methods: This study included 309 consecutively enrolled STEMI patients undergoing primary percutaneous coronary intervention (pPCI). Patients were diagnosed with SIH if blood glucose on admission was > 140 mg/dl. Also, patients had to fast for at least 8 hours before blood sampling. The objective was to assess whether SIH was associated with major adverse cardiovascular and cerebrovascular (MACCE) events and explore its relationship with angiographic predictors of worse prognosis such as poor initial TIMI flow, intracoronary thrombus burden, distal embolization, and presence of residual thrombus after pPCI. Results: SIH in diabetic and non-diabetic patients was associated with a higher incidence of LTB (aOR = 2.171, 95% CI 1.27–3.71), distal embolization (aOR = 2.71, 95% CI 1.51–4.86), and pre-procedural TIMI flow grade = 0 (aOR = 2.69, 95% CI 1.43–5.04) after adjusting for relevant clinical variables. Importantly, during a median follow-up of 1.7 years STEMI patients with SIH with or without diabetes experienced increased occurrence of MACCE both in univariate (HR = 1.92, 95% CI 1.19–3.01) and multivariate analysis (aHR = 1.802, 95% CI 1.01–3.21). Conclusions: SIH in STEMI patients with or without diabetes was independently associated with increased MACCE. This could be attributed to the fact that SIH was strongly correlated with poor pre-procedural TIMI flow, LTB, and distal embolization. Large clinical trials need to validate SIH as an independent predictor of adverse angiographic and clinical outcomes to provide optimal individualized care for patients with STEMI. [ABSTRACT FROM AUTHOR]

• In total, 11 studies were reviewed for the prevalence of atrial cardiomyopathy markers in ESUS patients. • Electrocardiographic and echocardiographic markers of atrial cardiomyopathy, as well as anatomical characteristics of the left atrium appendage differed in ESUS and non-cardioembolic stroke patients in most studies. • We highlight the need to establish a universal definition for atrial cardiomyopathy based on specific biomarkers. Emerging evidence suggests the potential role of atrial cardiomyopathy (AC) as a direct thromboembolic determinant in embolic stroke of undetermined source (ESUS). We aimed to quantify the prevalence of potential AC markers among ESUS, non-cardioembolic (NCE) and cardioembolic (CE) stroke patients. PubMed and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched for publications from inception to October 2021, with duplicate data extraction and risk of bias assessment. The Newcastle-Ottawa assessment scale was used to evaluate study quality. Among 398 screened studies, 11 observational studies with 2009 ESUS patients (mean age 66.5 years) fulfilled the inclusion criteria. Of electrocardiographic markers, increased P-wave terminal force in lead V1 was more prevalent in ESUS vs NCE (OR=2.26, 95%CI: 1.40–3.66). Of imaging markers, left atrial volume index (LAVI) and left atrial diameter (LAd) were higher in ESUS vs NCE (OR=1.04, 95%CI: 1.02–1.06 and OR=3.41, 95%CI: 1.35–8.61 respectively). Non-chicken wing morphology of the left atrial appendage was more frequent in ESUS compared to NCE patients in the majority of studies. Of serum biomarkers, the prevalence of NT-proBNP >250 pg/ml did not differ among ESUS vs NCE (OR=0.73, 95%CI: 0.39 -1.35). Electrocardiographic, echocardiographic markers and advanced imaging modalities able to assess the morphologic characteristics of left atrial appendage and left atrial function may be important tools to discriminate AC among ESUS vs NCE stroke patients. Prospective studies exploring the association of potential AC markers with ESUS occurrence are warranted to validate their clinical utility. [Display omitted] [ABSTRACT FROM AUTHOR]

In this study, atmospheric dynamical processes, which govern the intensification of wildfire activity and the associated increase in low-level ozone concentrations, were studied using images, advanced products and vertical profiles derived from satellite observations. The analyses confirm that the influence of deep stratospheric intrusions, identified in the satellite water vapor imagery, on a fire-risk area contributes to the increase in fire activity. The depth of dry stratospheric intrusions, the associated synoptic evolution and the enhanced low-level ozone concentrations caused by vertical transport of stratospheric air and/or related to biomass burning emissions were analyzed using satellite measurements from SEVIRI, IASI and CrIS instruments, complemented with surface observations near the wildfires' locations. It is shown that the spatial and vertical resolutions of these soundings provide a way of identifying areas of enhanced ozone downwind of wildfires. Influences of the upper-troposphere dynamics and the wind field evolution as factors of uncertainty and complexity in studying the ozone production from wildfire emissions are considered. The combination of satellite soundings and satellite estimations of fire radiative energy and WV imagery may contribute to better understand the ozone enhancement associated with stratospheric intrusion and wildfire emissions. [ABSTRACT FROM AUTHOR]

Background: This systematic review explores the effects of landiolol administration in individuals presenting with supraventricular tachyarrhythmia (SVT) and concurrent left ventricular dysfunction, without being septic or in a peri-operative period. Methods: We systematically searched PubMed, Cochrane, Web of Science, and Scopus databases, retrieving a total of 15 eligible studies according to prespecified eligibility criteria. Results: Patients treated with landiolol experienced a substantial reduction in heart rate (HR) (mean HR reduction: 42 bpm, 95% confidence intervals (CIs): 37–47, I2 = 82%) and were more likely to achieve the target HR compared to those receiving alternative antiarrhythmic therapy (pooled odds ratio (OR): 5.37, 95% CIs: 2.87–10.05, I2 = 0%). Adverse events, primarily hypotension, occurred in 14.7% of patients receiving landiolol, but no significant difference was observed between the landiolol and alternative antiarrhythmic receiving groups (pooled OR: 1.02, 95% CI: 0.57–1.83, I2 = 0%). No significant difference was observed between the two groups concerning sinus rhythm restoration (pooled OR: 0.97, 95% CI: 0.25–3.78, I2 = 0%) and drug discontinuation due to adverse events (pooled OR: 5.09, 95% CI: 0.6–43.38, I2 = 0%). Conclusion: While further research is warranted, this systematic review highlights the potential benefits of landiolol administration in the management of SVTs in the context of left ventricular dysfunction. [ABSTRACT FROM AUTHOR]

Heart failure (HF) remains a major cause of morbidity and mortality worldwide. Recently, significant advances have been made in its treatment; however, diuretics remain the cornerstone in managing congestion in HF. Although diuretic resistance poses a significant challenge in the management of HF and is associated with poor outcomes, only limited alternative pharmaceutical options are available in clinical practice. The objective of this narrative review is to provide a comprehensive analysis of the current evidence on the effects of sodium-glucose co-transporter-2 (SGLT-2) inhibitors on diuretic resistance in HF patients. The primary emphasis is placed on clinical data that assess the impact of SGLT-2 inhibitors on fluid balance, symptom improvement, and clinical outcomes and secondarily on safety profile and potential adverse effects associated with SGLT-2 inhibitor use in acute decompensated HF. The current evidence on the efficacy of SGLT-2 on diuretic resistance remains controversial. Findings from observational and randomized studies are quite heterogenous; however, they converge on the notion that although SGLT-2 inhibitors show promise for mitigating diuretic resistance in HF, their diuretic effect may not be potent enough to be widely used to relieve objective signs of congestion in patients with HF. Importantly, the introduction of SGLT-2 inhibitors in HF treatment appears to be generally well tolerated, with manageable adverse effects. Further research is needed to investigate the underlying mechanisms and the possible beneficial impact of SGLT-2 inhibitors on diuretic resistance in HF. [ABSTRACT FROM AUTHOR]

Background: Acute myocardial infarction (AMI) remains a major cause of death worldwide. Survivors of AMI are particularly at high risk for additional cardiovascular events. Consequently, a comprehensive approach to secondary prevention is necessary to mitigate the occurrence of downstream complications. This may be achieved through a multiparametric tailored risk stratification by incorporating clinical, laboratory and echocardiographic parameters. Methods: The "CLEAR-AMI Study" (ClinicalTrials.gov Identifier: NCT05791916) is a non-interventional, prospective study including consecutive patients with AMI without a known history of coronary artery disease. All patients satisfying these inclusion criteria are enrolled in the present study. The rationale of this study is to refine risk stratification by using clinical, laboratory and novel echocardiographic biomarkers. All the patients undergo a comprehensive transthoracic echocardiographic assessment, including strain and myocardial work analysis of the left and right heart chambers, within 48 h of admission after coronary angiography. Their laboratory profile focusing on systemic inflammation is captured during the first 24 h upon admission, and their demographic characteristics, past medical history, and therapeutic management are recorded. The angioplasty details are documented, the non-culprit coronary lesions are archived, and the SYNTAX score is employed to evaluate the complexity of coronary artery disease. A 24-month follow-up period will be recorded for all patients recruited. Conclusion: The "CLEAR-AMI" study is an ongoing prospective registry endeavoring to refine risk assessment in patients with AMI without a known history of coronary artery disease, by incorporating echocardiographic parameters, biochemical indices, and clinical and coronary characteristics in the acute phase of AMI. [ABSTRACT FROM AUTHOR]

This work introduces the design, architecture, implementation, and testing of a low-cost and machine-learning-enabled device to be worn on the wrist. The suggested wearable device has been developed for use during emergency incidents of large passenger ship evacuations, and enables the real-time monitoring of the passengers' physiological state, and stress detection. Based on a properly preprocessed PPG signal, the device provides essential biometric data (pulse rate and oxygen saturation level) and an efficient unimodal machine learning pipeline. The stress detecting machine learning pipeline is based on ultra-short-term pulse rate variability, and has been successfully integrated into the microcontroller of the developed embedded device. As a result, the presented smart wristband is able to provide real-time stress detection. The stress detection system has been trained with the use of the publicly available WESAD dataset, and its performance has been tested through a two-stage process. Initially, evaluation of the lightweight machine learning pipeline on a previously unseen subset of the WESAD dataset was performed, reaching an accuracy score equal to 91%. Subsequently, external validation was conducted, through a dedicated laboratory study of 15 volunteers subjected to well-acknowledged cognitive stressors while wearing the smart wristband, which yielded an accuracy score equal to 76%. [ABSTRACT FROM AUTHOR]

The implementation of smart networks has made great progress due to the development of the Internet of Things (IoT). LoRa is one of the most prominent technologies in the Internet of Things industry, primarily due to its ability to achieve long-distance transmission while consuming less power. In this work, we modeled different environments and assessed the performances of networks by observing the effects of various factors and network parameters. The path loss model, the deployment area size, the transmission power, the spreading factor, the number of nodes and gateways, and the antenna gain have a significant effect on the main performance metrics such as the energy consumption and the data extraction rate of a LoRa network. In order to examine these parameters, we performed simulations in OMNeT++ using the open source framework FLoRa. The scenarios which were investigated in this work include the simulation of rural and urban environments and a parking area model. The results indicate that the optimization of the key parameters could have a huge impact on the deployment of smart networks. [ABSTRACT FROM AUTHOR]

Aim: Maternal pregestational diabetes mellitus (PGDM), type 1 or type 2, has been established as a potential risk factor for congenital heart disease (CHD). At the same time, the correlation between gestational diabetes mellitus (GDM) and increased risk of CHD has not been yet fully elucidated. The objective of this systematic review and meta-analysis (PROSPERO number: CRD42020182390) was to analyze the existing evidence on PGDM and to attempt to fill, to the best of our ability, the remaining knowledge gap in the association of GDM with CHD. Materials and methods: Two authors have independently searched the Pubmed/Medline, Scopus, Cochrane, Web of Science, and Theses Global databases with keywords and Boolean operators. The search yielded 9333 relevant articles, which were later screened for eligibility. Original peer-reviewed (case-control or cohort) studies were included if they were published in English between 1997 and 2020. Thirteen studies on mothers with PGDM and seven studies on mothers with GDM were finally included in our meta-analysis to investigate the association of maternal diabetes with the risk of delivering a child with CHD. The selected studies were all assessed for their methodological quality using the Newcastle–Ottawa scale. Associations with p < .05 were considered statistically significant. Results: Our meta-analysis (I² > 75%, total population: n = 12,461,586) of 79,476 women with PGDM and 160,893 with GDM produced an odds ratio of 3.48 (2.36–4.61) and 1.55 (1.48–1.61), respectively. Additionally, we did not find any noticeable difference in the risk for CHD among diabetic women living in the USA and Europe. Nevertheless, it still needs to be clarified, whether or not the gestational diabetic population includes undiagnosed women with preexisting diabetes, which might account for the increased risk of delivering a child with CHD in women classified as suffering from GDM. Conclusion: While both GDM and PGDM seem to significantly increase the risk of CHD in comparison with the general population, PDGM appears to have a greater association with CHD, being correlated with a 3.5-fold increase in the risk of malformation. Preconceptional and gestational diabetes care are, therefore, essential to mitigate the adverse effect of hyperglycemia on fetal heart formation during pregnancy. [ABSTRACT FROM AUTHOR]

The cell-free massive multiple-input multiple-output (CFmMIMO) aims to provide uniform quality of service (QoS) for all users, and can be used in small-area scenarios such as indoor industrial networks. This paper studies the CFmMIMO system for indoor industrial scenarios. Firstly, an access point (AP) grouping based hierarchical network topology is proposed. Based on this, we propose an effective AP selection method. To reduce pilot contamination, a pilot assignment scheme based on inspection robot (IR) location is proposed. Considering the high reliability requirement of industrial data transmission, the power control and backhaul combining are jointly optimized to maximize the minimum signal to interference plus noise ratio (SINR). The scalability of the proposed CFmMIMO system is analyzed, and a scalable power control method is proposed. The simulations demonstrate the effectiveness of the AP selection method, pilot assignment scheme, and the joint optimization algorithm for power control and backhaul combining. Moreover, the impact of network scale and network load on system performance is evaluated and analyzed in the simulations. [ABSTRACT FROM AUTHOR]

The study describes a homogenisation technique of developing a Polyether ether ketone (PEEK) and calcium hydroxyapatite (cHAp) composite with periodic pattern lattice structures. The continuum depiction of the discrete structures was evaluated to retain the PEEK cellulose composite properties of the lattice cell applied to dental implants. Design approaches were considered, using different software modelling to optimise the orthotropic lattice PEEK material by establishing an optimal variable cell lattice density distribution in the geometric model of a dental implant. A homogenising model was studied based on the lattice optimisation that resulted from the previous stage and considered different volume fractions, pore size, and variable density for different lattice cells for dental implants. Their adequate elastic fatigues were obtained by the unit cell's fast design-based model homogenisation method, and bioactivity cell tests took place in a culture medium. It was evident from the results obtained that the homogenisation increased the stiffness of the bracket by using the same cubic lattice cell, and the fundamental frequency obtained with lattice optimisation to higher results after implants. This result can easily be applied by using these lattice structures and PEEK composite in dental implants for medical industries and institutions as a lightweight and better biocompatible materials compared to metals. [Display omitted] • Designing and printing of variable macro-lattice structures of PEEK composite using FDM. • Measure the compressive deformation behaviour of macro-lattice structures for dental implants. • FEA helped us understand the behaviours of lattice structures of PEEK/cHAP in different ratios. • Varying lattice designs of gyroid and BCCO can influence both strength and failure Implants. [ABSTRACT FROM AUTHOR]

The prognostic value of health status metrics in patients with adult congenital heart disease (ACHD) and atrial arrhythmias is unclear. In this retrospective cohort study of an ongoing national, multicenter registry (PROTECT-AR, NCT03854149), ACHD patients with atrial arrhythmias on apixaban are included. At baseline, health metrics were assessed using the physical component summary (PCS), the mental component summary (MCS) of the Short-Form-36 (SF-36) Health Survey, and the modified European Heart Rhythm Association (mEHRA) score. Patients were divided into groups according to their SF-36 PCS and MCS scores, using the normalized population mean of 50 on the PCS and MCS as a threshold. The primary outcome was the composite of mortality from any cause, major thromboembolic events, major/clinically relevant non-major bleedings, or hospitalizations. Multivariable Cox-regression analyses using clinically relevant parameters (age greater than 60 years, anatomic complexity, ejection fraction of the systemic ventricle, and CHA₂DS₂-VASc and HAS-BLED scores) were performed to examine the association of health metrics with the composite outcome. Over a median follow-up period of 20 months, the composite outcome occurred in 50 of 158 (32%) patients. The risk of the outcome was significantly higher in patients with SF-36 PCS ≤ 50 compared with those with PCS > 50 (adjusted hazard ratio (aHR), 1.98; 95% confidence interval [CI], 1.02–3.84; p = 0.04) after adjusting for possible confounders. The SF-36 MCS ≤ 50 was not associated with the outcome. The mEHRA score was incrementally associated with a higher risk of the composite outcome (aHR = 1.44 per 1 unit increase in score; 95% CI, 1.03–2.00; p = 0.03) in multivariable analysis. In ACHD patients with atrial arrhythmias, the SF-36 PCS ≤ 50 and mEHRA scores predicted an increased risk of adverse events. [ABSTRACT FROM AUTHOR]

Extracorporeal membrane oxygenation (ECMO) is increasingly being used for patients with severe respiratory failure and has received particular attention during the coronavirus disease 2019 (COVID-19) pandemic. Evidence from two key randomized controlled trials, a subsequent post hoc Bayesian analysis, and meta-analyses support the interpretation of a benefit of ECMO in combination with ultra-lung-protective ventilation for select patients with very severe forms of acute respiratory distress syndrome (ARDS). During the pandemic, new evidence has emerged helping to better define the role of ECMO for patients with COVID-19. Results from large cohorts suggest outcomes during the first wave of the pandemic were similar to those in non-COVID-19 cohorts. As the pandemic continued, mortality of patients supported with ECMO has increased. However, the precise reasons for this observation are unclear. Known risk factors for mortality in COVID-19 and non-COVID-19 patients are higher patient age, concomitant extra-pulmonary organ failures or malignancies, prolonged mechanical ventilation before ECMO, less experienced treatment teams and lower ECMO caseloads in the treating center. ECMO is a high resource-dependent support option; therefore, it should be used judiciously, and its availability may need to be constrained when resources are scarce. More evidence from high-quality research is required to better define the role and limitations of ECMO in patients with severe COVID-19. [ABSTRACT FROM AUTHOR]

The fifth generation (5G) of telecommunications networks is currently commercially deployed. One of their core enabling technologies is cellular Massive Multiple-Input-Multiple-Output (M-MIMO) systems. However, future wireless networks are expected to serve a very large number of devices and the current MIMO networks are not scalable, highlighting the need for novel solutions. At this moment, Cell-free Massive MIMO (CF M-MIMO) technology seems to be the most promising idea in this direction. Despite their appealing characteristics, CF M-MIMO systems face their own challenges, such as power allocation and channel estimation. Deep Learning (DL) has been successfully employed to a wide range of problems in many different research areas, including wireless communications. In this paper, a review of the state-of-the-art DL methods applied to CF M-MIMO communications systems is provided. In addition, the basic characteristics of Cell-free networks are introduced, along with the presentation of the most commonly used DL models. Finally, future research directions are highlighted. [ABSTRACT FROM AUTHOR]

Differentiable programming has recently received much interest as a paradigm that facilitates taking gradients of computer programs. While the corresponding flexible gradient-based optimization approaches so far have been used predominantly for deep learning or enriching the latter with modeling components, we want to demonstrate that they can also be useful for statistical modeling per se, for example, for quick prototyping when classical maximum likelihood approaches are challenging or not feasible. In an application from a COVID-19 setting, we use differentiable programming to quickly build and optimize a flexible prediction model adapted to the data quality challenges at hand. Specifically, we develop a regression model, inspired by delay differential equations, that can bridge temporal gaps of observations in the central German registry of COVID-19 intensive care cases for predicting future demand. With this exemplary modeling challenge, we illustrate how differentiable programming can enable simple gradient-based optimization of the model by automatic differentiation. This allowed us to quickly prototype a model under time pressure that outperforms simpler benchmark models. We thus exemplify the potential of differentiable programming also outside deep learning applications to provide more options for flexible applied statistical modeling. [ABSTRACT FROM AUTHOR]

Adults with congenital heart disease (ACHD) and atrial arrhythmias (AA) face an increased risk of thromboembolic events. Limited data exist on the use of non-vitamin K oral anticoagulants for thromboprophylaxis in ACHD. We aimed to assess the effectiveness and safety of apixaban in ACHD patients with AA. PROTECT-AR (NCT03854149) was a prospective, multicenter, observational study conducted from 2019 to 2023. ACHD patients with atrial fibrillation, atrial flutter, or intra-atrial re-entrant tachycardia on routine apixaban treatment were included. The historical control group consisted of patients previously on vitamin K antagonist (VKA), who were analyzed prior to their transition to apixaban. The primary effectiveness endpoint was the composite of stroke or thromboembolism. The primary safety endpoint was major bleeding. The study enrolled 218 ACHD patients with AA on apixaban, of which 73 were previous VKA users. The analysis covered 527 patient-years of prospective exposure to apixaban and 169 patient-years of retrospective exposure to VKA. The annualized rate of stroke or thromboembolism was 0.6% in the apixaban group and 1.8% in the VKA group (absolute difference − 1.2%; upper limit of one-sided 95% confidence interval [CI] 0.9%, lower than the predefined non-inferiority margin of +1.8%, P non-inferiority < 0.001). The annualized rate of major bleeding was 1.5% in the apixaban group and 2.4% in the VKA group (hazard ratio 0.64; 95% CI 0.19–2.10, P = 0.48). In ACHD patients with AA, routine apixaban use exhibited a non-inferior rate of stroke or thromboembolism compared to historical VKA use, alongside a similar rate of major bleeding. • Apixaban was associated with low rates of thromboembolism and major bleeding. • Long-term safety and effectiveness of apixaban were comparable to VKA. • Apixaban was linked to reduced non-major bleeding and improved QoL compared to VKA. ACHD, adults with congenital heart disease; CI, confidence interval, VKA, vitamin K antagonist. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: Polycystic ovary syndrome (PCOS) is closely related to various adverse cardiovascular manifestations and increased cardiovascular risk. However, atrial fibrillation (AF) development and atrial conduction abnormalities have not been thoroughly studied in patients with PCOS. Methods: This meta-analysis (CRD42021261375) was conducted in accordance with the PRISMA guidelines. Our aim was to investigate associations between PCOS and disorders in atrial conduction parameters linked with an increased risk for AF occurrence. Results: Five cohort studies with aggregate data on 406 adult women (229 with PCOS and 177 age-matched without PCOS) were included in this analysis. Our results showed a significantly increased mean difference in P-wave maximum duration (+7.63 ± 7.07 msec; p < 0.01) and P-wave dispersion (+11.42 ± 5.22 msec; p = 0.03) of patients with PCOS compared to healthy women. The mean difference in P-wave minimum duration (−2.22 ± 2.68 msec; p = 0.11) did not reach the statistical threshold between the compared groups. Echocardiographic measurements of atrial electromechanical delay (AED) also indicated a statistically significant mean difference in favour of the PCOS group in all assessed parameters, except for atrial electromechanical coupling (PA) in the tricuspid annulus. Particularly, PCOS was associated with increased lateral PA, septal PA, inter- and intra-AED durations (mean difference: +17.31 ± 9.02 msec; p < 0.01, +11.63 ± 7.42 msec; p < 0.01, +15.31 ± 9.18 msec; p < 0.01, +9.31 ± 6.85 msec; p < 0.01, respectively). Conclusions: PCOS is strongly associated with alterations in several electrocardiographic and echocardiographic parameters indicating abnormal atrial conduction. Therefore, PCOS could be considered as a causal or triggering factor of AF. Larger studies are needed to confirm these results and investigate direct associations between PCOS and AF. [ABSTRACT FROM AUTHOR]

We investigate the optimal signal detection problem in large-scale multiple-input multiple-output (MIMO) system with the generalized spatial modulation (GSM) scheme, which can be formulated as a closest lattice point search (CLPS). To identify invalid signals, an efficient pruning strategy is needed while searching on the GSM decision tree. However, the existing algorithms have exponential complexity, whereas they are infeasible in large-scale GSM-MIMO systems. In order to tackle this problem, we propose a memory-efficient pruning strategy by leveraging the combinatorial nature of the GSM signal structure. Thus, the required memory size is squared to the number of transmit antennas. We further propose an efficient memory-bounded maximum likelihood (ML) search (EM-MLS) algorithm by jointly employing the proposed pruning strategy and the memory-bounded best-first algorithm. Theoretical and simulation results show that our proposed algorithm can achieve the optimal bit error rate (BER) performance, while its memory size can be bounded. Moreover, the expected time complexity decreases exponentially with increasing the signal-to-noise ratio (SNR) as well as the system’s excess degree of freedom, and it often converges to squared time under practical scenarios. [ABSTRACT FROM AUTHOR]

Meta-surfaces intend to improve the performance of future wireless networks significantly by controlling the wireless propagation and shaping the radio waves according to the generalized Snell's law. A recent application of meta-surfaces are reconfigurable intelligent surfaces that are mainly proposed for the reflection and steering of the impinging signal. In this article, we introduce randomly reconfigurable surfaces (RRSs) aiming to diffuse the incoming wave and characterize the performance of an RRS-assisted communication network. To facilitate the performance analysis of an RRS-assisted network, first, we present novel closed-form expressions for the probability density function, the cumulative distribution function, the moments, and the characteristic function of the amplitude of the distribution of the sum of double-Nakagami- $m$ random vectors, whose amplitudes follow the double-Nakagami- $m$ distribution, and phases following the circular uniform distribution. We also consider a special case of this distribution, namely the distribution of the sum of Rayleigh-Nakagami-m random vectors. Then, we exploit the obtained expressions to investigate the RRS-assisted composite channel, assuming that the two links undergo Nakagami- $m$ fading. Specifically, closed-form expressions for the outage probability, the average received signal-to-noise ratio, the ergodic capacity, the bit error probability, the amount of fading, and the channel quality estimation index are provided to evaluate the performance of the considered system. Finally, these metrics are also derived for the practical special case where one of the two links undergoes Rayleigh fading, implying that this link is non-line-of-sight. [ABSTRACT FROM AUTHOR]

The manufacturing landscape is ever-changing, and one of the most significant driving forces is the emergence of additive manufacturing (AM), which enables cost-effective and small-scale production towards sustainability. To better align AM with manufacturing in suitable applications, this study proposes a business model in terms of the cost pattern and scaling production supported by three key concepts: standardisation, localisation and collaboration. The ambiguity of the cost calculation is one of the key factors slowing down AM progress, and a lack of a cost pattern affects decision-making when applying AM to appropriate applications. The business model in this study is focused on applying the data collected from previous research, the collection-recycling-manufacturing (CRM) model, to discover the implications of AM processes on the road to sustainable manufacturing. The novel business model envisions the nature of AM characteristics and their linkages to cost patterns, so AM applications can be integrated into a cost-effective process. This study contributes qualitative analysis to the cost patterns' integration. Through this integration, the business model mediates the gap between technologies and applications via the formulas of cost patterns, so AM can perform its appropriate role in the industry mainstream. The cost modelling proposed in this study derives generic formulas via the unit cost of tooling, moulding, machine, materials, design, miscellaneous cost and the batch size. The business model applies the "divide-and-conquer" concept, convergence effect and data analysis to support quantitative analysis. The model can calculate the total cost per unit, and its accuracy is close to 100%. Through the novelty of this model, AM and conventional manufacturing (CM) cost benchmarking and decision support functions are enabled to aid in stakeholder decision-making. Eventually, appropriate AM technologies and processes can synchronise with localisation, standardisation and collaboration and, ultimately, the impact of AM towards sustainable manufacturing. [ABSTRACT FROM AUTHOR]

This paper investigates the optimal signal detection problem with a particular interest in large-scale multiple-input multiple-output (MIMO) systems. The problem is NP-hard and can be solved optimally by searching the shortest path on the decision tree. Unfortunately, the existing optimal search algorithms often involve prohibitively high complexities, which indicates that they are infeasible in large-scale MIMO systems. To address this issue, we propose a general heuristic search algorithm, namely, hyper-accelerated tree search (HATS) algorithm. The proposed algorithm employs a deep neural network (DNN) to estimate the optimal heuristic, and then use the estimated heuristic to speed up the underlying memory-bounded search algorithm. This idea is inspired by the fact that the underlying heuristic search algorithm reaches the optimal efficiency with the optimal heuristic function. Simulation results show that the proposed algorithm reaches almost the optimal bit error rate (BER) performance in large-scale systems, while the memory size can be bounded. In the meanwhile, it visits nearly the fewest tree nodes. This indicates that the proposed algorithm reaches almost the optimal efficiency in practical scenarios, and thereby it is applicable for large-scale systems. Besides, the code for this paper is available at https://github.com/skypitcher/hats. [ABSTRACT FROM AUTHOR]

Materials recycling and additive manufacturing (AM) present challenges and great opportunities in plastic industries. The rapid developments in AM are transforming the manufacturing industry. Reducing CO 2 emissions, saving cost, and escaping from landfill are the decisive factors in this transformation. In this study, to mitigate any risk caused by production speed and scaling and accelerate shift towards a more localized recycling and manufacturing of plastic parts and components, a collection-recycling-manufacturing (CRM) model is built to envision the evaluation of process flow as well as process integration. The novelty of the CRM model enables optimization between recycling facilities and transportation distance calculation. It further strengthens a seamless integration between recycling and AM processes and envisions the areas that need enhancements. The study reveals that AM creates opportunities such as prototyping, customizing, transportation cost reduction, and creation of jobs in rural areas, which may stop unnecessary immigration; and, most importantly, reducing CO 2 emissions and plastic waste despite challenges such as skills requirement and disadvantages in speed and scale production. With a combination of recycling and AM, sustainable manufacturing can be achieved effectively, although several conditions must be met and obstacles must be overcome. A few innovations are further proposed in this study to streamline the transformation and to support the "cradle-to-cradle" approach towards "zero waste" for a sustainable future. [ABSTRACT FROM AUTHOR]

Nowadays, the transformations of cities into smart cities is a crucial factor in improving the living conditions of the inhabitants as well as addressing emergency situations under the concept of public safety and property loss. In this context, many sensing systems have been designed and developed that provide fire detection and gas leakage alerts. On the other hand, new technologies such edge computing have gained significant attention in recent years. Moreover, the development of recent intelligent applications in IoT aims to integrate several types of systems with automated next-generation emergency calls in case of a serious accident. Currently, there is a lack of studies that combine all the aforementioned technologies. The proposed smart building sensor system, SB112, combines a small-size multisensor-based (temperature, humidity, smoke, flame, CO, LPG, and CNG) scheme with an open-source edge computing framework and automated Next Generation (NG) 112 emergency call functionality. It involves crucial actors such as IoT devices, a Public Safety Answering Point (PSAP), the middleware of a smart city platform, and relevant operators in an end-to-end manner for real-world scenarios. To verify the utility and functionality of the proposed system, a representative end-to-end experiment was performed, publishing raw measurements from sensors as well as a fire alert in real time and with low latency (average latency of 32 ms) to the middleware of a smart city platform. Once the fire was detected, a fully automatic NG112 emergency call to a PSAP was performed. The proposed methodology highlights the potential of the SΒ112 system for exploitation by decision-makers or city authorities. [ABSTRACT FROM AUTHOR]

Atrial fibrillation (AF) and diabetes mellitus (DM) constitute two major closely inter-related chronic cardiovascular disorders whose concurrent prevalence rates are steadily increasing. Although, the pathogenic mechanisms behind the AF and DM comorbidity are still vague, it is now clear that DM precipitates AF occurrence. DM also affects the clinical course of established AF; it is associated with significant increase in the incidence of stroke, AF recurrence, and cardiovascular mortality. The impact of DM on AF management and prognosis has been adequately investigated. However, evidence on the relative impact of glycemic control using glycated hemoglobin levels is scarce. This review assesses up-to-date literature on the association between DM and AF. It also highlights the usefulness of glycated hemoglobin measurement for the prediction of AF and AF-related adverse events. Additionally, this review evaluates current anti-hyperglycemic treatment in the context of AF, and discusses AF-related decision-making in comorbid DM. Finally, it quotes significant remaining questions and sets some future strategies with the potential to effectively deal with this prevalent comorbidity. [ABSTRACT FROM AUTHOR]

Recent studies support that acylcarnitines exert a significant role in cardiovascular disease development and progression. The aim of this metabolomics-based study was to investigate the association of serum acylcarnitine levels with coronary artery disease (CAD) severity, as assessed via SYNTAX Score. Within the context of the prospective CorLipid trial (NCT04580173), the levels of 13 circulating acylcarnitines were accurately determined through a newly developed HILIC-MS/MS method in 958 patients undergoing coronary angiography in the AHEPA University Hospital of Thessaloniki, Greece. Patients presenting with acute coronary syndrome had significantly lower median acylcarnitine C8, C10, C16, C18:1 and C18:2 values, compared to patients with chronic coronary syndrome (p = 0.012, 0.007, 0.018, 0.011 and <0.001, respectively). Among CAD subgroups, median C5 levels were significantly decreased in unstable angina compared to STEMI (p = 0.026), while median C10, C16, C18:1 and C18:2 levels were higher in stable angina compared to STEMI (p = 0.019 p = 0.012, p = 0.013 and p < 0.001, respectively). Moreover, median C2, C3, C4 and C8 levels were significantly elevated in patients with diabetes mellitus (p < 0.001, <0.001, 0.029 and 0.011, respectively). Moreover, short-chain acylcarnitine C2, C4, C5 and C6 levels were elevated in patients with heavier calcification and lower left ventricular ejection fraction (LVEF) % (all p-values less than 0.05). With regard to CAD severity, median C4 and C5 levels were elevated and C16 and C18:2 levels were reduced in the high CAD complexity group with SYNTAX Score > 22 (p = 0.002, 0.024, 0.044 and 0.012, respectively), indicating a potential prognostic capability of those metabolites and of the ratio C4/C18:2 for the prediction of CAD severity. In conclusion, serum acylcarnitines could serve as clinically useful biomarkers leading to a more individualized management of patients with CAD, once further clinically oriented metabolomics-based studies provide similar evidence. [ABSTRACT FROM AUTHOR]

The 2021 fire season in Greece was the worst of the past 13 years, resulting in more than 130,000 ha of burnt area, with about 70% consumed by five wildfires that ignited and spread in early August. Common to these wildfires was the occurrence of violent pyroconvection. This work presents a meteorological analysis of this outbreak of extreme pyroconvective wildfires. Our analysis shows that dry and warm antecedent weather preconditioned fuels in the fire-affected areas, creating a fire environment that alone could effectively support intense wildfire activity. Analysis of surface conditions revealed that the ignition and the most active spread of all wildfires coincided with the most adverse fire weather since the beginning of the fire season. Further, the atmospheric environment was conducive to violent pyroconvection, as atmospheric instability gradually increased amid the breakdown of an upper-air ridge ahead of an approaching long-wave trough. In summary, we highlight that the severity and extent of the 2021 Greek wildfires were not surprising considering the fire weather potential for the period when they ignited. Continuous monitoring of the large- and local-scale conditions that promote extreme fire behavior is imperative for improving Greece's capacity for managing extreme wildfires. [ABSTRACT FROM AUTHOR]

Purpose: The question of whether cancer patients with severe respiratory failure benefit from veno-venous extracorporeal membrane oxygenation (vv-ECMO) remains unanswered. We, therefore, analyzed clinical characteristics and outcomes of a large cohort of cancer patients treated with vv-ECMO with the aim to identify prognostic factors. Methods: 297 cancer patients from 19 German and Austrian hospitals who underwent vv-ECMO between 2009 and 2019 were retrospectively analyzed. A multivariable cox proportional hazards analysis for overall survival was performed. In addition, a propensity score-matched analysis and a latent class analysis were conducted. Results: Patients had a median age of 56 (IQR 44–65) years and 214 (72%) were males. 159 (54%) had a solid tumor and 138 (47%) a hematologic malignancy. The 60-day overall survival rate was 26.8% (95% CI 22.1–32.4%). Low platelet count (HR 0.997, 95% CI 0.996–0.999; p = 0.0001 per 1000 platelets/µl), elevated lactate levels (HR 1.048, 95% CI 1.012–1.084; p = 0.0077), and disease status (progressive disease [HR 1.871, 95% CI 1.081–3.238; p = 0.0253], newly diagnosed [HR 1.571, 95% CI 1.044–2.364; p = 0.0304]) were independent adverse prognostic factors for overall survival. A propensity score-matched analysis with patients who did not receive ECMO treatment showed no significant survival advantage for treatment with ECMO. Conclusion: The overall survival of cancer patients who require vv-ECMO is poor. This study shows that the value of vv-ECMO in cancer patients with respiratory failure is still unclear and further research is needed. The risk factors identified in the present analysis may help to better select patients who may benefit from vv-ECMO. [ABSTRACT FROM AUTHOR]

Gender equality is a demand in all societies and is a key goal of all of us, as well as the integration of people with disabilities and especially women. This article reports on the prevailing situation of women with disabilities in society, how to deal with them and how to eliminate their exclusion and accept them as equal citizens in society. [ABSTRACT FROM AUTHOR]

Background: Oxygen (O2) is a drug with specific biochemical and physiological properties, a range of effective doses and may have side effects. In 2015, 14% of over 55,000 hospital patients in the UK were using oxygen. 42% of patients received this supplemental oxygen without a valid prescription. Health care professionals are frequently uncertain about the relevance of hypoxemia and have low awareness about the risks of hyperoxemia. Numerous randomized controlled trials about targets of oxygen therapy have been published in recent years. A national guideline is urgently needed. Methods: A national S3 guideline was developed and published within the Program for National Disease Management Guidelines (AWMF) with participation of 10 medical associations. A literature search was performed until February 1, 2021, to answer 10 key questions. The Oxford Centre for Evidence-Based Medicine (CEBM) System ("The Oxford 2011 Levels of Evidence") was used to classify types of studies in terms of validity. Grading of Recommendations, Assessment, Development and Evaluation (GRADE) was used for assessing the quality of evidence and for grading guideline recommendation, and a formal consensus-building process was performed. Results: The guideline includes 34 evidence-based recommendations about indications, prescription, monitoring and discontinuation of oxygen therapy in acute care. The main indication for O2 therapy is hypoxemia. In acute care both hypoxemia and hyperoxemia should be avoided. Hyperoxemia also seems to be associated with increased mortality, especially in patients with hypercapnia. The guideline provides recommended target oxygen saturation for acute medicine without differentiating between diagnoses. Target ranges for oxygen saturation are based depending on ventilation status risk for hypercapnia. The guideline provides an overview of available oxygen delivery systems and includes recommendations for their selection based on patient safety and comfort. Conclusion: This is the first national guideline on the use of oxygen in acute care. It addresses health care professionals using oxygen in acute out-of-hospital and in-hospital settings. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a secure mobile edge computing (MEC) network in the presence of multiple eavesdroppers, where multiple users can offload parts of their tasks to the computational access point (CAP). The multiple eavesdroppers may overhear the confidential task offloading, which leads to information leakage. In order to address this issue, we present the minimization problem of the secrecy outage probability (SOP), by jointly taking into account the constraints from the latency and energy consumption. With the aim to improve the system secrecy performance, we then introduce three user selection criteria to choose the best user among multiple ones. Specifically, criterion I maximizes the locally computational capacity, while criterion II and III maximize the secrecy capacity and data rate of main links, respectively. For these criteria, we further analyze the system secrecy performance by deriving analytical and asymptotic expressions for the SOP, from which we can conclude important insights for the system design. Finally, simulation and analytical results are provided to verify the proposed analysis. The results show that the three criteria can efficiently safeguard the MEC networks, compared to the traditional local computing and fully offloading, especially with a large value of user number. [ABSTRACT FROM AUTHOR]

Gender equality is a fundamental human right and is essential for the existence of peaceful societies, with human resources that are fully utilized and sustainable development. Emotional Intelligence is not gender biased and it is an integral key to successful personal and working life. In (Drigas & Papoutsi, 2021) there was an attempt to construct a reliable and valid measurement instrument of emotional intelligence with 81 items, based on the theoretical ninelayer pyramid model of emotional intelligence. The sample was consisted of 520 teachers (129 males and 391 females) from primary and secondary school grade and the data was collected with the Nine Layer Pyramid Model Questionnaire for Emotional Intelligence. Among other results we examined gender differences in emotional intelligence. The results revealed some differences between the two genders on emotional intelligence with women scoring higher on overall emotional intelligence. This article also provides an overview of the prevailing emotional intelligence status of both sexes as it emerges through research, beliefs about emotions between women and men, and suggestions for avoiding stereotypes and proper interventions for raising emotional both men and women. Finally, a reference is made to technology in its various forms, including Information and Communication Technology (ICT), which is also associated with emotional intelligence and has great potential to empower women worldwide and promote gender equality. [ABSTRACT FROM AUTHOR]