Performance of the 2019 ESC/EASD guideline strategy for the screening of silent coronary artery disease in patients with diabetes.

BACKGROUND: The 2019 guidelines for cardiovascular risk stratification by the European Society of Cardiology and European Association for the Study of Diabetes (ESC-EASD) suggested screening for silent coronary disease in very high risk patients with severe target organ damage (TOD) (i.e. peripheral occlusive arterial disease or severe nephropathy) or high coronary artery calcium (CAC) score. This study aimed to test the validity of this strategy. METHODS: In this retrospective study, we included 385 asymptomatic patients with diabetes and no history of coronary disease but with TOD or ≥ 3 risk factors in addition to diabetes. CAC score was measured using computed tomography scan and a stress myocardial scintigraphy was performed to detect silent myocardial ischemia (SMI), with subsequent coronary angiography in those with SMI. Various strategies to select patients to be screened for SMI were tested. RESULTS: CAC score was ≥ 100 Agatston units (AU) in 175 patients (45.5%). SMI was present in 39 patients (10.1%) and among the 30 patients who underwent angiography, 15 had coronary stenoses and 12 had a revascularization procedure. The most effective strategy consisted in performing myocardial scintigraphy in the 146 patients with severe TOD and, among the 239 other patients without severe TOD, in those with CAC ≥ 100 AU: this strategy provided 82% sensitivity for SMI diagnosis, and identified all the patients with stenoses. CONCLUSION: The ESC-EASD guidelines suggesting SMI screening in asymptomatic patients with very high risk assessed by severe TOD or high CAC score appears effective and could identify all the patients with stenoses eligible for revascularization.

Perfluorocarbon Nanoemulsions with Fluorous Chlorin-Type Photosensitizers for Antitumor Photodynamic Therapy in Hypoxia.

The efficacy of photodynamic therapy (PDT) strictly depends on the availability of molecular oxygen to trigger the light-induced generation of reactive species. Fluorocarbons have an increased ability to dissolve oxygen and are attractive tools for gas delivery. We synthesized three fluorous derivatives of chlorin with peripheral polyfluoroalkyl substituents. These compounds were used as precursors for preparing nanoemulsions with perfluorodecalin as an oxygen depot. Therefore, our formulations contained hydrophobic photosensitizers capable of absorbing monochromatic light in the long wavelength region and the oxygen carrier. These modifications did not alter the photosensitizing characteristics of chlorin such as the generation of singlet oxygen, the major cytocidal species in PDT. Emulsions readily entered HCT116 colon carcinoma cells and accumulated largely in mitochondria. Illumination of cells loaded with emulsions rapidly caused peroxidation of lipids and the loss of the plasma membrane integrity (photonecrosis). Most importantly, in PDT settings, emulsions potently sensitized cells cultured under prolonged (8 weeks) hypoxia as well as cells after oxygen depletion with sodium sulfite (acute hypoxia). The photodamaging potency of emulsions in hypoxia was significantly more pronounced compared to emulsion-free counterparts. Considering a negligible dark cytotoxicity, our materials emerge as efficient and biocompatible instruments for PDT-assisted eradication of hypoxic cells.

A review of progress and an advanced method for shock advice algorithms in automated external defibrillators.

Shock advice algorithm plays a vital role in the detection of sudden cardiac arrests on electrocardiogram signals and hence, brings about survival improvement by delivering prompt defibrillation. The last decade has witnessed a surge of research efforts in racing for efficient shock advice algorithms, in this context. On one hand, it has been reported that the classification performance of traditional threshold-based methods has not complied with the American Heart Association recommendations. On the other hand, the rise of machine learning and deep learning-based counterparts is paving the new ways for the development of intelligent shock advice algorithms. In this paper, we firstly provide a comprehensive survey on the development of shock advice algorithms for rhythm analysis in automated external defibrillators. Shock advice algorithms are categorized into three groups based on the classification methods in which the detection performance is significantly improved by the use of machine learning and/or deep learning techniques instead of threshold-based approaches. Indeed, in threshold-based shock advice algorithms, a parameter is calculated as a threshold to distinguish shockable rhythms from non-shockable ones. In contrast, machine learning-based methods combine multiple parameters of conventional threshold-based approaches as a set of features to recognize sudden cardiac arrest. Noticeably, those features are possibly extracted from stand-alone ECGs, alternative signals using various decomposition techniques, or fully augmented ECG segments. Moreover, these signals can be also used directly as the input channels of deep learning-based shock advice algorithm designs. Then, we propose an advanced shock advice algorithm using a support vector machine classifier and a feature set extracted from a fully augmented ECG segment with its shockable and non-shockable signals. The relatively high detection performance of the proposed shock advice algorithm implies a potential application for the automated external defibrillator in the practical clinic environment. Finally, we outline several interesting yet challenging research problems for further investigation.

Epicardial adipose tissue volume and coronary calcification among people living with diabetes: a cross-sectional study.

BACKGROUND: Epicardial adipose tissue (EAT) has anatomic and functional proximity to the heart and is considered a novel diagnostic marker and therapeutic target in cardiometabolic diseases. The aim of this study was to evaluate whether EAT volume was associated with coronary artery calcification (CAC) in people living with diabetes, independently of confounding factors. METHODS: We included all consecutive patients with diabetes whose EAT volume and CAC score were measured using computed tomography between January 1, 2019 and September 30, 2020 in the Department of Diabetology-Endocrinology-Nutrition at Avicenne Hospital, France. Determinants of EAT volume and a CAC score ≥ 100 Agatston units (AU) were evaluated. RESULTS: The study population comprised 409 patients (218 men). Mean (± standard deviation) age was 57 ± 12 years, and 318, 56 and 35 had type 2 (T2D), type 1 (T1D), or another type of diabetes, respectively. Mean body mass index (BMI) was 29 ± 6 kg/m2, mean AET volume 93 ± 38 cm3. EAT volume was positively correlated with age, BMI, pack-year smoking history and triglyceridaemia, but negatively correlated with HDL-cholesterol level. Furthermore, it was lower in people with retinopathy, but higher in men, in Caucasian people, in patients on antihypertensive and lipid-lowering medication, in people with nephropathy, and finally in individuals with a CAC ≥ 100 AU (CAC < 100 vs CAC ≥ 100: 89 ± 35 vs 109 ± 41 cm3, respectively, p < 0.05). In addition to EAT volume, other determinants of CAC ≥ 100 AU (n = 89, 22%) were age, T2D, ethnicity, antihypertensive and lipid-lowering medication, cumulative tobacco consumption, retinopathy, macular edema and macrovascular disease. Multivariable analysis considering all these determinants as well as gender and BMI showed that EAT volume was independently associated with CAC ≥ 100 AU (per 10 cm3 increase: OR 1.11 [1.02-1.20]). CONCLUSIONS: EAT volume was independently associated with CAC. As it may play a role in coronary atherosclerosis in patients with diabetes, reducing EAT volume through physical exercise, improved diet and pharmaceutical interventions may improve future cardiovascular risk outcomes in this population.

Epicardial adipose tissue volume and myocardial ischemia in asymptomatic people living with diabetes: a cross-sectional study.

BACKGROUND: Epicardial adipose tissue (EAT) is considered a novel diagnostic marker for cardiometabolic disease. This study aimed to evaluate whether EAT volume was associated with stress-induced myocardial ischemia in asymptomatic people living with diabetes-independently of confounding factors-and whether it could predict this condition. METHODS: We included asymptomatic patients with diabetes and no coronary history, who had undergone both a stress a myocardial scintigraphy to diagnose myocardial ischemia, and a computed tomography to measure their coronary artery calcium (CAC) score. EAT volume was retrospectively measured from computed tomography imaging. Determinants of EAT volume and asymptomatic myocardial ischemia were evaluated. RESULTS: The study population comprised 274 individuals, including 153 men. Mean (± standard deviation) age was 62 ± 9 years, and 243, 23 and 8 had type 2, type 1, or another type of diabetes, respectively. Mean body mass index was 30 ± 6 kg/m2, and mean EAT volume 96 ± 36 cm3. Myocardial ischemia was detected in 32 patients (11.7%). EAT volume was positively correlated with age, body mass index and triglyceridemia, but negatively correlated with HbA1c, HDL- and LDL-cholesterol levels. Furthermore, EAT volume was lower in people with retinopathy, but higher in men, in current smokers, in patients with nephropathy, those with a CAC score > 100 Agatston units, and finally in individuals with myocardial ischemia (110 ± 37 cm3 vs 94 ± 37 cm3 in those without myocardial ischemia, p < 0.05). The association between EAT volume and myocardial ischemia remained significant after adjustment for gender, diabetes duration, peripheral macrovascular disease and CAC score. We also found that area under the ROC curve analysis showed that EAT volume (AROC: 0.771 [95% confidence interval 0.683-0.858]) did not provide improved discrimination of myocardial ischemia over the following classic factors: gender, diabetes duration, peripheral macrovascular disease, retinopathy, nephropathy, smoking, atherogenic dyslipidemia, and CAC score (AROC 0.773 [0.683-0.862]). CONCLUSIONS: EAT may play a role in coronary atherosclerosis and coronary circulation in patients with diabetes. However, considering EAT volume is not a better marker for discriminating the risk of asymptomatic myocardial ischemia than classic clinical data.

Association of serum adiponectin and leptin levels with renal function in kidney transplant recipients with or without new-onset diabetes after transplantation.

PURPOSE: To evaluate serum adiponectin and leptin concentration in new-onset diabetes after transplantation (NODAT) and non-NODAT patients and association with renal function in kidney transplant recipients (KTRs). PATIENTS AND METHODS: A study of 314 consecutive adults KTRs divided into four groups: 236 individuals without NODAT who had renal insufficiency (RI; n = 56) or normal renal function (n = 180) and 78 patients with NODAT who had RI (n = 17) or normal renal function (n = 61). NODAT was diagnosed based on venous fasting blood glucose or HbA1c with the criteria of the American Diabetes Association. Renal insufficiency was defined according to KDOQI 2002 guidelines. RESULTS: In the NODAT group, the median level of serum adiponectin was lower than that of non-NODAT one (30 µg/ml vs 37.15 µg/ml, p < 0.001); in contrast, the median leptin concentration was higher (4.27 ng/ml vs 4.05 ng/ml, p = 0.024). In the RI group, both median serum adiponectin and leptin levels were higher than those of non-RI one (Adiponectin: 40.01 µg/ml vs 33.7 µg/ml; Leptin: 4.51 ng/ml vs 3.91 ng/ml, p < 0.001 both). We found that BMI was related to both adiponectin and leptin levels in both NODAT, non-NODAT, and all subject groups, based on univariate and multivariate linear regression analysis. CONCLUSION: New-onset diabetes after transplantation, BMI, and renal insufficiency were affected to the serum level of adiponectin and leptin in KTRs.

Serum osteoprotegerin level in hemodialysis patients using low-flux reused dialyzer in relation to atherosclerosis.

AIMS: To assess the relation of high serum OPG level and carotid atherosclerosis in maintenance hemodialysis (MHD) patients using low-flux reused dialyzer. MATERIALS AND METHODS: We examined 209 MHD patients with and without carotid atherosclerosis (83 patients and 126 patients) to establish the relation between OPG and atherosclerosis. RESULTS: The proportion of carotid atherosclerosis was 39.7%. The median serum OPG level was 45.3 pmol/L. Serum OPG had a good predicting value for atherosclerosis in MHD patients using low-flux reused dialyzer (AUC = 0.934, p < 0.001, cutoff value = 43.35 pmol/L, Se = 81.3%, Sp = 90.9%). CONCLUSIONS: In this study, serum OPG had a good predicting value for atherosclerosis in MHD patients using low-flux reused dialyzer.

NLOS Identification in WLANs Using Deep LSTM with CNN Features.

Identifying channel states as line-of-sight or non-line-of-sight helps to optimize location-based services in wireless communications. The received signal strength identification and channel state information are used to estimate channel conditions for orthogonal frequency division multiplexing systems in indoor wireless local area networks. This paper proposes a joint convolutional neural network and recurrent neural network architecture to classify channel conditions. Convolutional neural networks extract the feature from frequency-domain characteristics of channel state information data and recurrent neural networks extract the feature from time-varying characteristics of received signal strength identification and channel state information between packet transmissions. The performance of the proposed methods is verified under indoor propagation environments. Experimental results show that the proposed method has a 2% improvement in classification performance over the conventional recurrent neural network model.

An Evidence-Based Algorithm for Early Prognosis of Severe Dengue in the Outpatient Setting.

Background: Early prediction of severe dengue could significantly assist patient triage and case management. Methods: We prospectively investigated 7563 children with ≤3 days of fever recruited in the outpatient departments of 6 hospitals in southern Vietnam between 2010 and 2013. The primary endpoint of interest was severe dengue (2009 World Health Organization Guidelines), and predefined risk variables were collected at the time of enrollment to enable prognostic model development. Results: The analysis population comprised 7544 patients, of whom 2060 (27.3%) had laboratory-confirmed dengue; nested among these were 117 (1.5%) severe cases. In the multivariate logistic model, a history of vomiting, lower platelet count, elevated aspartate aminotransferase (AST) level, positivity in the nonstructural protein 1 (NS1) rapid test, and viremia magnitude were all independently associated with severe dengue. The final prognostic model (Early Severe Dengue Identifier [ESDI]) included history of vomiting, platelet count, AST level. and NS1 rapid test status. Conclusions: The ESDI had acceptable performance features (area under the curve = 0.95, sensitivity 87% (95% confidence interval [CI], 80%-92%), specificity 88% (95% CI, 87%-89%), positive predictive value 10% (95% CI, 9%-12%), and negative predictive value of 99% (95% CI, 98%-100%) in the population of all 7563 enrolled children. A score chart, for routine clinical use, was derived from the prognostic model and could improve triage and management of children presenting with fever in dengue-endemic areas.

Atherogenic dyslipidemia and risk of silent coronary artery disease in asymptomatic patients with type 2 diabetes: a cross-sectional study.

BACKGROUND: To investigate whether atherogenic dyslipidemia, a dyslipidemic profile combining elevated triglycerides and low high-density lipoprotein (HDL) cholesterol, is predictive of risk of silent myocardial ischemia (SMI) or angiographic coronary artery disease (CAD) in asymptomatic patients with type 2 diabetes. METHODS: Cohort study in 1080 asymptomatic patients with type 2 diabetes with a normal resting electrocardiogram, at least one additional cardiovascular risk factor and low density lipoprotein (LDL) cholesterol <3.35 mmol/L. Patients initially underwent screening for SMI by stress myocardial scintigraphy. Patients with SMI underwent coronary angiography. RESULTS: Overall, 60 (5.5 %) patients had atherogenic dyslipidemia (triglycerides ≥2.26 mmol/L and HDL cholesterol ≤0.88 mmol/L). In multivariate analyses taking into account the parameters associated in univariate analyses with SMI and then CAD, atherogenic dyslipidemia was associated with SMI (odds ratio 1.8[1.0-3.3]), as were male gender (OR 2.1[1.5-2.9]), BMI (OR 0.97[0.94-0.997]), retinopathy (OR 1.4[1.1-1.9]), peripheral occlusive arterial disease (POAD: OR 2.5[1.6-3.8]) and mean blood pressure (OR 1.01[1.00-1.03]); atherogenic dyslipidemia was associated with CAD (OR 4.0[1.7-9.2]), as were male gender (OR 3.0[1.6-5.6]), BMI (OR 0.94[0.90-0.995]), retinopathy (OR 1.7[1.0-2.9], POAD (OR 4.0[2.1-7.4]) and mean blood pressure (OR 1.03[1.01-1.05]). In the subgroup of 584 patients with LDL cholesterol <2.6 mmol/L, atherogenic dyslipidemia was also associated with CAD (OR 3.6[1.5-9.0]). CONCLUSIONS: Atherogenic dyslipidemia was associated with an increased risk of SMI and silent CAD in patients with type 2 diabetes and LDL cholesterol levels <3.35 mmol/L. Specific management of atherogenic dyslipidemia might help reducing the high residual burden of cardiovascular disease.

Noninvasive study of coronary microcirculation response to a cold pressor test.

BACKGROUND: The aims of this study were to noninvasively (i) assess the coronary microcirculation changes in response to a cold pressor test (CPT) in control subjects, nondiabetic obese patients and patients with type 2 diabetes and (ii) investigate the response of the coronary microcirculation in patients with diabetes according to the presence or the absence of silent myocardial ischaemia (SMI), asymptomatic coronary stenosis (CS) and left ventricle hypertrophy (LVH). METHODS: The mean left anterior descending coronary flow velocity (mCFV) was measured using transthoracic Doppler before and after a CPT in 16 control subjects, 11 obese and 66 asymptomatic diabetic patients with a high cardiovascular risk. Patients with diabetes were screened for SMI using stress myocardial scintigraphy and/or echocardiography. A coronary angiography was performed in those with SMI. RESULTS: At baseline, pressure-rate product (PRP) was correlated with mCFV (r = 0.23; P < 0.05) and left ventricle mass (r = 0.26; P < 0.05) in the whole population. Changes in PRP and mCFV during CPT were correlated with controls (r = 0.58, P < 0.05), obese (r = 0.75, P < 0.01) and diabetic patients without CS (r = 0.56, P < 0.0001) or without LVH (r = 0.63, P < 0.05) but not in diabetic patients with CS or with LVH. In patients with diabetes, SMI was associated with mCFV changes, independent of other parameters (P < 0.05). CONCLUSION: Transthoracic coronary Doppler allows noninvasive study of changes in the coronary microcirculation during CPT. In asymptomatic patients with type 2 diabetes, this method showed that SMI was associated with mCFV changes during CPT and the presence of CS or LVH was associated with a mismatch between coronary microcirculation and myocardial oxygen demand.

Flow-mediated-paradoxical vasoconstriction is independently associated with asymptomatic myocardial ischemia and coronary artery disease in type 2 diabetic patients.

BACKGROUND: To investigate whether flow-mediated dilation (FMD) impairment, which precedes overt atherosclerosis, is associated with silent myocardial ischemia (SMI) and asymptomatic coronary artery disease (CAD) in type 2 diabetes. METHODS: Forearm FMD was measured by ultrasonography in 25 healthy control, 30 non-diabetic overweight or obese patients and 118 asymptomatic type 2 diabetic patients with a high cardiovascular risk profile. SMI (abnormal stress myocardial scintiscan and/or stress dobutamine echocardiogram) and CAD (coronary angiography in the patients with SMI) were assessed in the diabetic cohort. RESULTS: FMD was lower in diabetic patients (median 0.61% (upper limits of first and third quartiles -1.22;3.2)) than in healthy controls (3.95% (1.43;5.25), p < 0.01) and overweight/obese patients (4.25% (1.74;5.56), p < 0.01). SMI was present in 60 diabetic patients, including 21 subjects with CAD. FMD was lower in patients with SMI than in those without (0.12% (-2.3;1.58) vs 1.64% (0;3.69), p < 0.01), with a higher prevalence of paradoxical vasoconstriction (50.0% vs 29.3%, p < 0.05). FMD was also lower in patients with than without CAD (-1.22% (-2.5;1) vs 1.13% (-0.4;3.28), p < 0.01; paradoxical vasoconstriction 61.9% vs 34.4%, p < 0.05). Logistic regression analyses considering the parameters predicting SMI or CAD in univariate analyses with a p value <0.10 showed that paradoxical vasoconstriction (odds ratio 2.7 [95% confidence interval 1.2-5.9], p < 0.05) and nephropathy (OR 2.6 [1.2-5.7], p < 0.05) were independently associated with SMI; and only paradoxical vasoconstriction (OR 3.1 [1.2-8.2], p < 0.05) with CAD. The negative predictive value of paradoxical vasoconstriction to detect CAD was 88.7%. CONCLUSIONS: In diabetic patients, FMD was independently associated with SMI and asymptomatic CAD. TRIAL REGISTRATION: Trial registration number NCT00685984.

Effect of azithromycin on enhancement of methane production from waste activated sludge.

In the methane production from waste activated sludge (WAS), complex bacterial interactions in WAS have been known as a major contribution to methane production. Therefore, the influence of bacterial community changes toward methane production from WAS was investigated by an application of antibiotics as a simple means for it. In this study, azithromycin (Azm) as an antibiotic was mainly used to observe the effect on microbial changes that influence methane production from WAS. The results showed that at the end of fermentation, Azm enhanced methane production about twofold compared to control. Azm fostered the growth of acid-producing bacterial communities, which synthesized more precursors for methane formation. DGGE result showed that the hydrolysis as well as acetogenesis stage was improved by the dominant of B1, B2 and B3 strains, which are Clostridium species. In the presence of Azm, the total population of archaeal group was increased, resulting in higher methane productivity achievement.

High Ferritin and Low Total Iron-Binding Capacity in Plasma Predict All-Cause Mortality During the First 3 Years of Hemodialysis in Patients with End-Stage Chronic Kidney Disease.

Aim: To determine all-cause mortality rate and the predictive value of plasma ferritin and total iron-binding capacity (TIBC) concentrations for mortality during the first 3 years of hemodialysis in patients with end-stage chronic renal disease (ESRD). Methods: We conducted a study on 174 ESRD patients (estimated Glomerular Filtration Rate < 15 mL/min/1.73m2). The plasma TIBC level was quantified by the ELISA method in all patients at the time before hemodialysis. Based on TIBC concentration, patients were divided equally into 2 groups. Each group had 87 patients. Patients were initiated on hemodialysis, and patients who died from any cause during the first 3 years of hemodialysis were recorded. Results: The all-cause mortality rate of ESRD patients in the first 3 years of maintenance hemodialysis was 22.9%. Plasma high hs-CRP, high ferritin, and low TIBC concentrations were independent factors associated with all-cause mortality in the patients. Plasma ferritin (cut-off value = 454.2 ng/L) and TIBC (cut-off value = 39.84 µmol/L) were predictors of all-cause mortality, AUC is: 0.772; 0.723, p < 0.001. Conclusion: Plasma ferritin and TIBC were good predictors of all-cause mortality in ESRD patients during the first 3 years of hemodialysis.

Thiadiazole-, selenadiazole- and triazole-fused anthraquinones as G-quadruplex targeting anticancer compounds.

G-quadruplex (G4) ligands attract considerable attention as potential anticancer therapeutics. In this study we proposed an original scheme for synthesis of azole-fused anthraquinones and prepared a series of G4 ligands carrying amino- or guanidinoalkylamino side chains. The heterocyclic core and structure of the terminal groups strongly affect on binding to G4-forming oligonucleotides, cellular accumulation and antitumor potency of compounds. In particular, thiadiazole- and selenadiazole- but not triazole-based ligands inhibit the proliferation of tumor cells (e.g. K562 leukemia) and stabilize primarily telomeric and c-MYC G4s. Anthraselenadiazole derivative 11a showed a good affinity to c-MYC G4 in vitro and down-regulated expression of c-MYC oncogene in cellular conditions. Further studies revealed that anthraselenadiazole 11a provoked cell cycle arrest and apoptosis in a dose- and time-dependent manner inhibiting K562 cells growth. Taken together, this work gives a valuable example that the closely related heterocycles may cause a significant difference in biological properties of G4 ligands.

Diagnosis of sudden cardiac arrest using principal component analysis in automated external defibrillators.

Sudden cardiac arrest (SCA) consisting of ventricular fibrillation and ventricular tachycardia considered as shockable rhythms is a life-threatening heart disease, which is treated efficiently by the automated external defibrillator (AED). This work proposes a novel design of the SAA, which includes a k-nearest neighbors model and a subset of 8 features extracted from the ECG segments, for the SCA diagnosis on the electrocardiogram (ECG) signal. These features are addressed as the most productive subset among 31 input features based on the evaluation of the feature correlation. The recursive feature elimination algorithm combined with the Boosting model and wise-patient fivefold cross-validation method is adopted for the calculation of the average feature importance, which shows the degree of feature correlation, to construct various input feature subsets. Moreover, component feature combinations known as the representatives of the input feature subsets with an enormous level of correlation and independence are transformed from the input subsets by the principal component analysis method. The wise-patient fivefold cross-validation procedure is used for the evaluation of these component feature combinations on the validation set. The proposed SAA is certainly efficient for SCA detection with a small number of the extracted feature and relatively high diagnosis performance such as accuracy of 99.52%, sensitivity of 97.69%, and specificity of 99.91%.

Clinical relevance of coronary risk classification and reclassification with coronary artery calcium score in asymptomatic people living with diabetes. An observational study.

AIMS: To explore (i) in what proportion and direction coronary artery calcium (CAC) score reclassifies coronary risk in asymptomatic diabetic patients at high a priori coronary risk, and (ii) whether screening for asymptomatic myocardial ischemia / coronary stenosis only in patients at very high coronary risk - whether a priori or combined with those reclassified at very high risk according to their CAC score - has good sensitivity to detect these conditions. METHODS: We retrospectively selected 377 asymptomatic primary prevention diabetic patients at high or very high a priori coronary risk according to national guidelines. All had their CAC score measured and underwent stress myocardial scintigraphy to detect myocardial ischemia. Those identified with ischemia then had a coronary angiography to identify coronary stenoses. RESULTS: Of the selected patients, 242 and 135 patients had a high and very high a priori coronary risk, respectively. After taking into account their CAC score, the former were reclassified into three risk categories: moderate (n = 159, 66%), high (n = 38) and very high (45 patients) risk. Myocardial ischemia was identified in 35 patients and coronary stenoses in 14 of the latter. Had a stress scintigraphy been performed only in the 135 patients at very high risk a priori, 18 patients would have been detected with ischemia (sensitivity 51%), and 9 with coronary stenoses (sensitivity 64%). Had a scintigraphy also been performed on the 45 patients at very high risk after CAC-reclassification, an additional 7 and 5 patients with ischemia and coronary stenoses, respectively, would have been identified. CONCLUSION: Following national guidelines, 66% of our population of asymptomatic diabetic persons at high a priori coronary risk were reclassified into the moderate risk category, translating into less stringent goals for risk factor control. Eighteen percent were reclassified into the very high-risk category, leading to 100% detection sensitivity for patients with ischemia and coronary stenoses.

Oligohexamethylene Guanidine Derivative as a Means to Prevent Biological Fouling of a Polymer-Based Composite Optical Oxygen Sensor.

The use of biocidal agents is a common practice for protection against biofouling in biomass-rich environments. In this paper, oligohexamethyleneguanidine (OHMG) polymer, known for its biocidal properties, was further modified with para-aminosalicylic acid (PAS) to enhance its properties against microorganisms coated with a lipid membrane. The structure of the product was confirmed by 1H NMR, 13C NMR, and FTIR spectroscopy. The values of the minimum inhibitory concentration (MIC) against Mycobacterium smegmatis ATCC 607 and Pseudomonas chlororaphis 449 were found to be 1.40 and 1.05 µg/mL, respectively. The synthesized substance was used as an additive to the polymer matrix of the composite optical oxygen sensor material. A series of samples with different contents of OHMG-PAS was prepared using a co-dissolution method implying the fabrication of a coating from a solution containing both polymers. It turned out that the mutual influence of the components significantly affects the distribution of the indicator in the matrix, surface morphology, and contact angle. The optimal polymer content turned out to be wt.3%, at which point the water contact angle reaches almost 122°, and the fouling rate decreases by almost five times, which is confirmed by both the respiratory MTT assay and confocal microscopy with staining. This opens up prospects for creating stable and biofouling-resistant sensor elements for use in air tanks or seawater.

Learning meaningful latent space representations for patient risk stratification: Model development and validation for dengue and other acute febrile illness.

Background: Increased data availability has prompted the creation of clinical decision support systems. These systems utilise clinical information to enhance health care provision, both to predict the likelihood of specific clinical outcomes or evaluate the risk of further complications. However, their adoption remains low due to concerns regarding the quality of recommendations, and a lack of clarity on how results are best obtained and presented. Methods: We used autoencoders capable of reducing the dimensionality of complex datasets in order to produce a 2D representation denoted as latent space to support understanding of complex clinical data. In this output, meaningful representations of individual patient profiles are spatially mapped in an unsupervised manner according to their input clinical parameters. This technique was then applied to a large real-world clinical dataset of over 12,000 patients with an illness compatible with dengue infection in Ho Chi Minh City, Vietnam between 1999 and 2021. Dengue is a systemic viral disease which exerts significant health and economic burden worldwide, and up to 5% of hospitalised patients develop life-threatening complications. Results: The latent space produced by the selected autoencoder aligns with established clinical characteristics exhibited by patients with dengue infection, as well as features of disease progression. Similar clinical phenotypes are represented close to each other in the latent space and clustered according to outcomes broadly described by the World Health Organisation dengue guidelines. Balancing distance metrics and density metrics produced results covering most of the latent space, and improved visualisation whilst preserving utility, with similar patients grouped closer together. In this case, this balance is achieved by using the sigmoid activation function and one hidden layer with three neurons, in addition to the latent dimension layer, which produces the output (Pearson, 0.840; Spearman, 0.830; Procrustes, 0.301; GMM 0.321). Conclusion: This study demonstrates that when adequately configured, autoencoders can produce two-dimensional representations of a complex dataset that conserve the distance relationship between points. The output visualisation groups patients with clinically relevant features closely together and inherently supports user interpretability. Work is underway to incorporate these findings into an electronic clinical decision support system to guide individual patient management.

Analysis of ESAFORM 2021 cup drawing benchmark of an Al alloy, critical factors for accuracy and efficiency of FE simulations.

This article details the ESAFORM Benchmark 2021. The deep drawing cup of a 1 mm thick, AA 6016-T4 sheet with a strong cube texture was simulated by 11 teams relying on phenomenological or crystal plasticity approaches, using commercial or self-developed Finite Element (FE) codes, with solid, continuum or classical shell elements and different contact models. The material characterization (tensile tests, biaxial tensile tests, monotonic and reverse shear tests, EBSD measurements) and the cup forming steps were performed with care (redundancy of measurements). The Benchmark organizers identified some constitutive laws but each team could perform its own identification. The methodology to reach material data is systematically described as well as the final data set. The ability of the constitutive law and of the FE model to predict Lankford and yield stress in different directions is verified. Then, the simulation results such as the earing (number and average height and amplitude), the punch force evolution and thickness in the cup wall are evaluated and analysed. The CPU time, the manpower for each step as well as the required tests versus the final prediction accuracy of more than 20 FE simulations are commented. The article aims to guide students and engineers in their choice of a constitutive law (yield locus, hardening law or plasticity approach) and data set used in the identification, without neglecting the other FE features, such as software, explicit or implicit strategy, element type and contact model.