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The current care model of type 2 diabetes (T2D) and its complications appears to be "asynchronous" with patient care divided by specialty. This model is associated with low use of guideline-directed medical therapies.The use of integrated care models has been well described in the management of patients with T2D; this usually includes an endocrinologist coupled with a nutritionist and nurse. However, physician-based care models are largely "asynchronous," whereby the patient requires multiple different siloed specialties to manage their health care. To date, there has been limited exploration of synchronous care delivery, i.e., whereby multi-comorbid patients with T2D are seen simultaneously by health care providers from endocrinology, cardiology, and nephrology to optimize use of guideline-directed medical therapies (GDMT). Given the rising complexity of patients with T2D, further research is needed on the role of synchronous health care delivery in optimizing the use of GDMT and improving patient outcomes.

A network health monitoring system focuses on the quantification of the network's health by taking into account various security flaws, leaks, and vulnerabilities. A plethora of propriety tools and patents are available for network health quantification. However, there is a paucity of available research and literature in this field. Thus, in this study, we present an architectural design of a network health monitoring system. The design focuses on the quantification of the network health of each end-user as well as the entire network. The network health score for each end-user is quantified by identifying (1) illicit egress-ingress traffic, (2) anomalous fingerprints, and (3) system-network vulnerabilities based on the NVD-CVSS (National Vulnerability Database, Common Vulnerability Severity Score) standards. An overall network-health score is produced, along with a prevention and recovery mechanism that is triggered upon the detection of an anomaly. The proposed system is implemented in a local area network and has demonstrated to protect the network against various threats successfully. The study is concluded by comparing the proposed tool with the popular propriety tools available in the field. The results outline that the proposed system garners features of open-source tools and enriches them by introducing a state-of-the-art architecture coupled with multiple novel features like exhaustive identification of vulnerability and detection of network aberrations using timers.

Worsening heart failure (WHF) is defined as persistent or worsening symptoms of heart failure that require an escalation in intravenous therapy or initiation of mechanical and ventilatory support during hospitalization. We assessed a simplified version of WHF called diuretic failure (DF), defined as an escalation of loop diuretic dosing after 48 h, and assessed its effects on mortality and rehospitalizations at 60-days.We conducted a multicenter retrospective study between December 1, 2017 and January 1, 2020. We identified 1389 patients of which 6.4% experienced DF.There was a significant relationship between DF and cumulative rates of 60-day mortality and 60-day rehospitalizations (p = 0.0002 and p = 0.0214). After multivariate adjustment, DF was associated with longer hospital stay (p 0.0001), increased rate of 60-day mortality (p = 0.026), 60-day rehospitalizations (p = 0.036), and a composite outcome of 60-day mortality and 60-day cardiac rehospitalizations (p = 0.018).DF has a strong relationship with adverse heart failure outcomes suggesting it is a simple yet robust prognostic indicator which can be used in real time to identify high-risk patients during hospitalization and beyond.

With recent advances in the pharmacological management of type 2 diabetes mellitus (T2DM), there is a growing need to understand which patients optimally benefit from these novel therapies. Various clinical clustering methodologies have emerged that utilise data-agnostic strategies to categorise patients that have similar clinical characteristics and outcomes; broadly, this characterisation is termed phenotyping. In patients with T2DM, we aimed to describe patient characteristics from phenotype studies, their cardiovascular risk profiles and the impact of antihyperglycemic treatment. Numerous phenotypic studies have been undertaken that have utilised a combination of clinical, biochemical, imaging and genetic variables. Each of these has produced phenotypes that display a spectrum of cardiovascular risk. Studies that aimed to describe pathophysiological phenotypes generally identified five phenotypes: autoimmune phenotype, insulin-related phenotypes (including permutations of insulin deficiency and resistance), obesity phenotype, ageing phenotype, and a sex-related phenotype. Studies examining risk profiles have demonstrated that across such phenotypes there is a spectrum of risk for diabetic complications. Few studies have examined treatment effects across these phenotypes, and thus provide little insights towards making phenotype-guided treatment decisions Clustering analyses in patients with T2DM have identified distinct phenotypes with unique risk profiles. Further studies are needed that harness the use of clinical, biochemical, imaging and genetic data to explore therapeutic heterogeneity and response to antihyperglycemic treatment across the spectrum of patient phenotypes.

We propose a mesoscopic Brownian magneto heat pump made of a single charged Brownian particle that is steered by an external magnetic field. The particle is subjected to two thermal noises from two different heat sources. When confined, the particle performs gyrating motion around a potential energy minimum. We show that such a magneto-gyrator can be operated as both a heat engine and a refrigerator. The maximum power delivered by the engine and the performance of the refrigerator, namely the rate of heat transferred per unit external work, can be tuned and optimised by the applied magnetic field. Further tunability of the key properties of the engine, such as the direction of gyration and the torque exerted by the engine on the confining potential, is obtained by varying the strength and direction of the applied magnetic field. In principle, our predictions can be tested by experiments with colloidal particles and complex plasmas.

Women, older patients and non-White ethnic groups experience a substantial proportion of acute coronary syndromes (ACS), although they have been historically underrepresented in ACS randomized clinical trials (RCTs). To assess the influence of sex, age and race on major adverse cardiovascular events (MACE) and on heart failure events, we studied patients with type 2 diabetes in a large post-ACS trial (EXAMINE). Differences in baseline characteristics and the respective composite endpoint of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke (MACE) and cardiovascular death or heart failure hospitalization (HF events) were evaluated by subgroups in a cohort of post-ACS patients with diabetes, using unadjusted and adjusted Cox regression modelling. The EXAMINE trial enrolled 5380 patients with 35% aged > 65, 32% female and 27% non-White. The risk of MACE was higher in non-White compared to White patients after adjustment for potential confounding (HR = 1.35; 95% CI 1.04–1.75), but there were no significant differences by sex and age (HR = 1.03; 95% CI 0.87–1.22 for women; HR = 1.14; 95% CI 0.96–1.35 for patients ≥ 65 years). The risk of HF events was higher in non-White patients (HR = 1.56; 95% CI 1.13–2.14), and in patients aged > 65 (HR = 1.33; 95% CI 1.07–1.66) and nominally so in women (HR = 1.23; 95% CI 0.99–1.52). The additive risk of each demographic factor (women, older age and non-White race) was greater for HF events in comparison with MACE. Moreover, non-White elderly patients consistently had poorer prognosis regardless of sex. Older adults, women and non-White patients with diabetes who are post-ACS are often underrepresented in RCTs. The risk for HF events was higher in older and non-White patients, with a trend towards significance in women, whereas only non-White patients (and not women and older patients) were at higher risk for MACE. Future trials should enrich enrollment of these persons at risk.

Ceramic to metal joining has its potential applications in microelectronics packaging, metal–ceramic seals, vacuum tubes, sapphire metal windows, etc. But there are many limitations in joining this duo of materials that range from their structures, nature of bonding, physical properties to a complex phenomenon like wetting, spreading and adhesion. The current review discusses these critical issues from the aspects of thermodynamics, the role, and type of active elements, Ag–Cu–Ti brazing filler system and the reliability factors like residual stress, coefficient of thermal expansion, material reliability, pores and unbonded regions on the surface which affect the mechanical reliability of the joint.

Active fingerprinting is an effective penetration testing technique to know about vulnerability of hosts against security threats and network as a whole. Sometimes firewalls may block fingerprinting packets, hence making the probes infeasible. Measured Round Trip Time (RTTm) is a benign number that can be obtained from communication based on legitimate non malicious packets. In this paper, RTTm has been used along with other timers namely Smoothened Round-trip Time (SRTT), Round-trip Time Variance (RTTVar), Retransmission Time Out (RTO) and Scantime for pattern recognition and association analysis with the aid of cross-correlations. Experimental relationship among these timers are derived to back-up existing theoretical knowledge. A novel method to estimate IP-ID Sequence classes and network-traffic intensity based on these timers has been proposed. Results show that the model can be used to accurately derive (about 100% accuracy) active fingerprinting components IP-ID sequences and link traffic estimation. Analytical results obtained by this study can help in designing high-performance realistic networks and dynamic congestion control techniques.

In the field of array signal processing, direction of arrival (DOA) estimation is a prime area of research. DOA estimation and adaptive beamforming (ABF) are the main issues in smart antennas, which dynamically find the direction of desired and interfering users and finds the optimum weights for beamforming. There are numerous spectral and eigen structure algorithms for estimating the direction of narrow band sources. However, in a complex multipath channel environment, received signals from different directions are fully or partially correlated, which prevents the applications of high resolution techniques to estimate the direction of incoming signals. Maximum likelihood (ML) is an efficient technique for DOA estimation in a low signal to noise ratio (SNR) and coherent channel environment. In this paper, we use particle swarm optimization (PSO) for estimating ML solution by optimizing complex non linear multimodal function over a high dimensional space in linear arrays. PSO-ML estimator has been compared with conventional DOA estimation techniques in uncorrelated, partially correlated and coherent channel environment. The performance of PSO-ML estimator and conventional algorithms are analyzed in varying partially correlated channel environment. The simulation results demonstrate that PSO based estimator gives superior statistical performance.

The optimal treatment approach to patients with coronary artery disease (CAD), including those with type 2 diabetes mellitus (T2DM), has been extensively evaluated. Several trials of stable ischemic heart disease including patients with T2DM have demonstrated that medical management is comparable to revascularization in terms of mortality and rates of major adverse cardiovascular events (MACE). There has been a growing appreciation for optimal medical therapy's (OMT) role in improving clinical outcomes. It is vital to target T2DM patients to prevent or delay MACE events through advanced OMT, ultimately delaying if not avoiding the need for revascularization. There has been significant evolution in the development of pharmacologic management of T2DM patients. Sodium-glucose co-transporter-2 (SGLT2) inhibitors are a new pharmacologic therapy with tremendous potential to alter clinical practice and influence practice guidelines. SGLT2-inhibitors have great potential in reducing MACE in patients with T2DM and CAD. Empagliflozin should be considered as a part of OMT among these patients. If results similar to the EMPA-REG OUTCOMES trial are replicated in other trials, the use of these pharmacologic agents as a part of OMT may narrow the gap between revascularization and OMT alone in patients with T2DM and multi-vessel disease. Future studies on the role of SLGT-2 inhibitors with regard to heart failure outcomes are needed to elucidate the mechanisms and clinical effects in this vulnerable population.

Cardiac troponin T (cTnT) is considered a clinical standard for its high specificity and sensitivity when diagnosing acute myocardial infarction; however, most studies on the electrical sensors of cardiac troponin biomarkers have focused on cTnI rather than cTnT. This study presents label-free, low-cost, transparent, and flexible aptamer-based immunosensors for the electrical detection of cTnT using reduced graphene oxide (rGO) sheets. GO was first deposited by AC dielectrophoresis between two predefined source and drain electrodes on a 3-aminopropyltriethoxylsilane-modified polyethylene terephthalate substrate. The GO was then reduced using hydrazine vapour without damaging the substrate, resulting in uniform, controlled, and stable deposition of rGO sheets, and demonstrating more stability than those directly deposited by dielectrophoresis. Amine-modified single-strand DNA aptamers against cTnT were immobilized onto the rGO channels. The relative resistance change of this sensor owing to the attachment of cTnT was quantified as the cTnT concentration decreased from 10 ng/mL to 1 pg/mL in phosphate buffered saline (PBS) and 10-fold diluted human serum in PBS, with the limits of detection being 1.2 pg/mL and 1.7 pg/mL, respectively, which is sufficiently sensitive for clinical applications. High-yield and rapid fabrication of the present rGO sensors will have significant influences on scaled-up fabrication of graphene-based sensors.

A laboratory-scale anoxic-oxic sequential reactor system was seeded with acclimatized mixed microbial consortium for the treatment of common effluent treatment plant (CETP) wastewater having 7000-7400 mg L(-1) of COD and 3000-3400 mg L(-1) of BOD. Initially, CETP wastewater was treated under anoxic reactor at 5000 mg L(-1) of MLSS concentrations, 5.26 ± 0.27 kg COD m(-3) day(-1) of organic loading rate (OLR) and 36 h of hydraulic retention time (HRT). Further, the effluent of anoxic reactor was treated in oxic reactor with an OLR of 6.6 ± 0.31 kg COD m(-3) day(-1) and 18 h HRT. Maximum color and COD removal were found to be 72 and 85 % at total HRT of 2.25 days under anoxic-oxic sequential reactor at 37 °C and pH 7.0. The UV-VIS, FTIR, NMR and GCMS studies showed that majority of peaks observed in untreated wastewater were either shifted or disappeared after sequential treatment. Phytotoxicity study with the seeds of Vigna radiata and Triticum aestivum showed more sensitivity toward the CETP wastewater, while the products obtained after sequential treatment does not have any inhibitory effects. The results demonstrated that the anoxic-oxic reactor fed with bacterial consortium VN11 could bring about efficient bioremediation of industrial wastewaters.

The purpose of this review is to summarize the new guidelines from the American Society of Echocardiography (ASE) and the European Association of Cardiovascular Imaging (EACVI) for the diagnosis and grading of diastolic dysfunction (DD), with commentary on the rationale behind the use of the recommended individual parameters. Previous guidelines for assessment of diastolic function have been criticized for being too complex with modest diagnostic performance and inter-observer variability. The new ASE/EACVI diastology guidelines aim to simplify the diagnosis and gradation of DD by using a limited set of echocardiographic variables. The robustness of these recommendations has been subsequently validated in several trials. Understanding the physiological principles that govern changes in echocardiographic parameters during normal and abnormal diastolic function is critical for the appropriate application of these recommendations.

We conducted this study to determine the preferences of anesthesia residents training in Canada for fellowship training, research, and future practice location and to identify the factors that influence those preferences. Using a cross-sectional study design, a survey was sent to all anesthesia residents enrolled at an accredited Canadian anesthesiology residency program (N = 629). Data were collected on demographics and preferences for fellowship training, research, and future practice location. A multivariable logistic regression model was used to determine significant associations. Two hundred forty-four residents (39%) responded to the survey. Seventy percent of residents intended to pursue fellowship training. The top three fellowships they favoured were regional anesthesia, intensive care, and cardiac anesthesia. Male sex was positively associated with the decision to pursue fellowship training, whereas having an additional graduate degree was negatively associated with this choice. Among those pursuing fellowship training, the most influential factors were personal interest, enhancing employability, and an interest in an academic career. Fifty-seven percent of residents preferred to work at an academic hospital. Thirty-four percent of residents intended to incorporate research into their future practice, and personal interest, employability, and colleagues were most influential in their decision. Research activity and publishing in residency were associated with the desire to pursue future research initiatives. The majority of anesthesia residents training in Canada choose to pursue fellowship training and work at an academic hospital. Approximately one-third of residents have an interest in incorporating research into their future careers.

Fibric acid derivatives like fenofibric acid (FA) decrease hepatic production of very low-density lipoprotein (VLDL)-associated triglycerides (TG). Hepatic VLDL production can be estimated from VLDL-associated cholesterol (VLDL-C). We assessed if the degree of TG reduction observed with FA, statins, or their combination is associated with baseline VLDL-C. Overall, 2,715 patients with mixed dyslipidemia in three randomized, controlled studies were assigned to one of six treatment strategies: FA, low-dose statin (LDS), FA + LDS, moderate-dose statin (MDS), FA + MDS, and high-dose statin (HDS). Patients were dichotomized into low- or high-baseline VLDL-C groups. Pooled data were used to compare the degree of TG reduction in patients with low- vs. high-baseline VLDL-C for each treatment arm, using unpaired, two-sided t test. Additionally, the association between baseline VLDL-C level and percentage TG reduction from baseline was evaluated by linear regression. Diagnostic performance of baseline VLDL-C levels in predicting 5, 10, 15, and 20% TG reduction was assessed by receiver operating characteristics (ROC) analysis. In all treatment groups, following 12 weeks of therapy, a significantly greater percent change from baseline in TG was observed in the high-baseline VLDL-C group as compared with the low-baseline VLDL-C group. Linear regression analysis indicated that approximately 6 to 13% of the decrease in TG could be explained by baseline VLDL-C. ROC-derived cut points for baseline VLDL-C were obtained for 5, 10, 15, and 20% TG reduction. Baseline VLDL-C levels are associated with the degree of TG lowering using FA, statins, or their combination, thereof.

Whether quantitative, two-dimensional, and three-dimensional plaque measurements by intravascular ultrasound with radiofrequency backscatter (IVUS/VH) are different between intermediate lesions with or without major adverse cardiovascular events (MACE) is unknown. IVUS/VH-derived parameters were compared in 60 patients with an intermediate coronary lesion (40–70 %) between lesions that did or did not result in MACE over 12 months. IVUS/VH measurements were done at the site of the minimal lumen area (MLA) and on a per-plaque basis, defined by 40 % plaque burden. Pre-specified, adjudicated MACE events occurred in 5 of 60 patients (8.3 %). MACE lesions had larger plaque burden (65 % vs. 53 %, p = 0.004), less dense calcium (6.6 % vs. 14.7 %, p = 0.05), and more non-calcified plaque, mostly fibrofatty kind (17.6 % vs. 10 %, p = 0.02). Intermediate coronary lesions associated with MACE at 12 months have more plaque, less dense calcium, and more non-calcified plaque, particularly fibrofatty tissue by IVUS/VH.

Gels formed by semiflexible filaments such as most biopolymers exhibit non-linear behavior in their response to shear deformation, e.g., with a pronounced strain stiffening and negative normal stress. These negative normal stresses suggest that networks would collapse axially when subject to shear stress. This coupling of axial and shear deformations can have particularly important consequences for extracellular matrices and collagenous tissues. Although measurements of uniaxial moduli have been made on biopolymer gels, these have not directly been related to the shear response. Here, we report measurements and simulations of axial and shear stresses exerted by a range of hydrogels subjected to simultaneous uniaxial and shear strains. These studies show that, in contrast to volume-conserving linearly elastic hydrogels, the Young’s moduli of networks formed by the biopolymers are not proportional to their shear moduli and both shear and uniaxial moduli are strongly affected by even modest degrees of uniaxial strain.

Subclinical atherosclerosis can be quantified by coronary artery calcium (CAC) scoring. Due to its high specificity for atherosclerosis, CAC is an excellent phenotypic tool for the evaluation of emerging risk markers. Lipoprotein(a) [Lp(a)] is atherogenic due to the presence of apoB and may be thrombogenic through its apo(a) component. Lp(a) has been linked to cardiovascular events in Caucasians; however, its link to atherosclerosis in various ethnicities remains unclear. We evaluated the ability of Lp(a) mass to predict subclinical atherosclerosis in Southeast Asians and Caucasians, as measured by CAC. Traditional lipid measurements, Lp(a) measurements, and CAC by 64-slice multidetector computed tomography was performed in 103 consecutive patients in the USA and in 104 consecutive patients in Jakarta, Indonesia. Proportion of positive CAC and median CAC in Southeast Asians and in Caucasians was 61.5% and 63.1%, and 23.5 (interquartile range, 0–270) and 13 (interquartile range, 0–388), respectively. Significantly higher proportion of Southeast Asians had elevated Lp(a) levels, compared to Caucasians (51.0% vs. 29.2%; p = 0.005). In Southeast Asians, Lp(a) remained an independent predictor of CAC with an odds ratio of 4.97 (95% confidence interval, 1.56–15.88; p