Physicians’ misperceived cardiovascular risk and therapeutic inertia as determinants of low LDL-cholesterol targets achievement in diabetes

Background: Greater efforts are needed to overcome the worldwide reported low achievement of LDL-c targets. This survey aimed to dissect whether and how the physician-based evaluation of patients with diabetes is associated with the achievement of LDL-c targets. Methods: This cross-sectional self-reported survey interviewed physicians working in 67 outpatient services in Italy, collecting records on 2844 patients with diabetes. Each physician reported a median of 47 records (IQR 42–49) and, for each of them, the physician specified its perceived cardiovascular risk, LDL-c targets, and the suggested refinement in lipid-lowering-treatment (LLT). These physician-based evaluations were then compared to recommendations from EAS/EASD guidelines. Results: Collected records were mostly from patients with type 2 diabetes (94%), at very-high (72%) or high-cardiovascular risk (27%). Physician-based assessments of cardiovascular risk and of LDL-c targets, as compared to guidelines recommendation, were misclassified in 34.7% of the records. The misperceived assessment was significantly higher among females and those on primary prevention and was associated with 67% lower odds of achieving guidelines-recommended LDL-c targets (OR 0.33, p < 0.0001). Peripheral artery disease, target organ damage and LLT-initiated by primary-care-physicians were all factors associated with therapeutic-inertia (i.e., lower than expected probability of receiving high-intensity LLT). Physician-suggested LLT refinement was inadequate in 24% of overall records and increased to 38% among subjects on primary prevention and with misclassified cardiovascular risk. Conclusions: This survey highlights the need to improve the physicians’ misperceived cardiovascular risk and therapeutic inertia in patients with diabetes to successfully implement guidelines recommendations into everyday clinical practice

Efficacy and durability of multifactorial intervention on mortality and MACEs:a randomized clinical trial in type-2 diabetic kidney disease

Background: Multiple modifiable risk factors for late complications in patients with diabetic kidney disease (DKD), including hyperglycemia, hypertension and dyslipidemia, increase the risk of a poor outcome. DKD is associated with a very high cardiovascular risk, which requires simultaneous treatment of these risk factors by implementing an intensified multifactorial treatment approach. However, the efficacy of a multifactorial intervention on major fatal/non-fatal cardiovascular events (MACEs) in DKD patients has been poorly investigated. Methods: Nephropathy in Diabetes type 2 (NID-2) study is a multicentre, cluster-randomized, open-label clinical trial enrolling 395 DKD patients with albuminuria, diabetic retinopathy (DR) and negative history of CV events in 14 Italian diabetology clinics. Centres were randomly assigned to either Standard-of-Care (SoC) (n = 188) or multifactorial intensive therapy (MT, n = 207) of main cardiovascular risk factors (blood pressure 40/50 mg/dL for men/women and < 175 mg/dL, respectively). Primary endpoint was MACEs occurrence by end of follow-up phase. Secondary endpoints included single components of primary endpoint and all-cause death. Results: At the end of intervention period (median 3.84 and 3.40 years in MT and SoC group, respectively), targets achievement was significantly higher in MT. During 13.0 years (IQR 12.4–13.3) of follow-up, 262 MACEs were recorded (116 in MT vs. 146 in SoC). The adjusted Cox shared-frailty model demonstrated 53% lower risk of MACEs in MT arm (adjusted HR 0.47, 95%CI 0.30–0.74, P = 0.001). Similarly, all-cause death risk was 47% lower (adjusted HR 0.53, 95%CI 0.29–0.93, P = 0.027). Conclusion: MT induces a remarkable benefit on the risk of MACEs and mortality in high-risk DKD patients. Clinical Trial Registration ClinicalTrials.gov number, NCT00535925. https://clinicaltrials.gov/ct2/show/NCT0053592

Frequency of left ventricular hypertrophy in non-valvular atrial fibrillation

Left ventricular hypertrophy (LVH) is significantly related to adverse clinical outcomes in patients at high risk of cardiovascular events. In patients with atrial fibrillation (AF), data on LVH, that is, prevalence and determinants, are inconsistent mainly because of different definitions and heterogeneity of study populations. We determined echocardiographic-based LVH prevalence and clinical factors independently associated with its development in a prospective cohort of patients with non-valvular (NV) AF. From the "Atrial Fibrillation Registry for Ankle-brachial Index Prevalence Assessment: Collaborative Italian Study" (ARAPACIS) population, 1,184 patients with NVAF (mean age 72 \ub1 11 years; 56% men) with complete data to define LVH were selected. ARAPACIS is a multicenter, observational, prospective, longitudinal on-going study designed to estimate prevalence of peripheral artery disease in patients with NVAF. We found a high prevalence of LVH (52%) in patients with NVAF. Compared to those without LVH, patients with AF with LVH were older and had a higher prevalence of hypertension, diabetes, and previous myocardial infarction (MI). A higher prevalence of ankle-brachial index 640.90 was seen in patients with LVH (22 vs 17%, p = 0.0392). Patients with LVH were at significantly higher thromboembolic risk, with CHA2DS2-VASc 652 seen in 93% of LVH and in 73% of patients without LVH (p &lt;0.05). Women with LVH had a higher prevalence of concentric hypertrophy than men (46% vs 29%, p = 0.0003). Logistic regression analysis demonstrated that female gender (odds ratio [OR] 2.80, p &lt;0.0001), age (OR 1.03 per year, p &lt;0.001), hypertension (OR 2.30, p &lt;0.001), diabetes (OR 1.62, p = 0.004), and previous MI (OR 1.96, p = 0.001) were independently associated with LVH. In conclusion, patients with NVAF have a high prevalence of LVH, which is related to female gender, older age, hypertension, and previous MI. These patients are at high thromboembolic risk and deserve a holistic approach to cardiovascular prevention

Spreading of powders in powder bed additive manufacturing: An experimental approach

Powder bed additive manufacturing allows for the production of fully customizable parts and is of great interest for industrial applications. However, the repeatability of the parts and the uniformity of the mechanical properties are still an issue. More specifically, the physical mechanism of the spreading process of the powders, which significantly affects the characteristics of the final part, is not completely understood. In powder bed fusion technologies, the spreading is performed by a device, typically a roller or a blade, that collects the powders from the feedstock and successively deposits them in a layer of several dozens of microns that is then processed with a laser beam. In this work, an experimental approach is developed and employed to study the powder spreading process and analyze in detail the motion of the powders from the accumulation zone to the deposition stage. The presented experiments are carried out on a home-made device that reproduces the spreading process and enables the measurement of the characteristics of the powder bed. Furthermore, the correlation with the process parameters, e.g., the speed of the spreading device, is also investigated. These results can be used to obtain useful insights on the optimal window for the process parameters

Discrete element method analysis of the spreading mechanism and its influence on powder bed characteristics in additive manufacturing

Laser powder bed fusion additive manufacturing is among the most used industrial processes, allowing for the production of customizable and geometrically complex parts at relatively low cost. Although different aspects of the powder spreading process have been investigated, questions remain on the process repeatability on the actual beam–powder bed interaction. Given the influence of the formed bed on the quality of the final part, understanding the spreading mechanism is crucial for process optimization. In this work, a Discrete Element Method (DEM) model of the spreading process is adopted to investigate the spreading process and underline the physical phenomena occurring. With parameters validated through ad hoc experiments, two spreading velocities, accounting for two different flow regimes, are simulated. The powder distribution in both the accumulation and deposition zone is investigated. Attention is placed on how density, effective layer thickness, and particle size distribution vary throughout the powder bed. The physical mechanism leading to the observed characteristics is discussed, effectively defining the window for the process parameters

Powder Bed Spreading in Additive Manufacturing: Numerical Simulations and Experimental Study

Powder bed based additive manufacturing technologies allow for the production of more complex parts with overall better characteristics and are therefore of high industrial interest. However, due to an incomplete understanding of the multi-physic processes involved there are still some issues to be addressed. More specifically, in this work we will focus on the powder spreading stage. In powder bed-based technologies a thin layer of powder is deposited by a recoating device and is then processed by an energy source to obtain a layer of the final part. We use a numerical model based on the Discrete Element Method to reproduce the spreading process and propose an experimental analysis procedure to obtain data suitable for the validation of such numerical model. The experiments are carried out on a purposely designed device and both computations and experiment are referred to a single layer deposition. Being able to validate the numerical results can give way to a more confident use of DEM based models for the optimization of the spreading process and therefore improve the quality of printed parts

Conformational stability of ageritin, a metal binding ribotoxin-like protein of fungal origin

Ageritin is a ribotoxin-like protein of biotechnological interest, belonging to a family of ribonucleases from edible mushrooms. Its enzymatic activity is explicated through the hydrolysis of a single phosphodiester bond, located in the sarcin/ricin loop of ribosomes. Unlike other ribotoxins, ageritin activity requires divalent cations (Zn2+). Here we investigated the conformational stability of ageritin in the pH range 4.0–7.4, using calorimetric and spectroscopic techniques. We observed a high protein thermal stability at all pHs with a denaturation temperature of 78 °C. At pH 5.0 we calculated a value of 36 kJ mol−1 for the unfolding Gibbs energy at 25 °C. We also analysed the thermodynamic and catalytic behaviour of S-pyridylethylated form, obtained by alkylating the single Cys18 residue, which is predicted to bind Zn2+. We show that this form possesses the same activity and structure of ageritin, but lower stability. In fact, the corresponding values of 52 °C and 14 kJ mol−1 were found. Conservation of activity is consistent with the location of alkylation site on the opposite site of the catalytic site cleft. Inasmuch as Cys18 is part of a structurally stabilizing zinc-binding site, disrupted by cysteine alkylation, our results point to an important role of metal ions in ageritin stability

Toxicity and membrane perturbation properties of the ribotoxin-like protein Ageritin

Ageritin is the prototype of a new ribotoxin-like protein family, which has been recently identified also in basidiomycetes. The protein exhibits specific RNase activity through the cleavage of a single phosphodiester bond located at sarcin/ricin loop of the large rRNA, thus inhibiting protein biosynthesis at early stages. Conversely to other ribotoxins, its activity requires the presence of divalent cations. In the present study, we report the activity of Ageritin on both prokaryotic and eukaryotic cells showing that the protein has a prominent effect on cancer cells viability and no effects on eukaryotic and bacterial cells. In order to rationalize these findings, the ability of the protein to interact with various liposomes mimicking normal, cancer and bacterial cell membranes was explored. The collected results indicate that Ageritin can interact with DPPC/DPPS/Chol vesicles, used as a model of cancer cell membranes, and with DPPC/DPPG vesicles, used as a model of bacterial cell membranes, suggesting a selective interaction with anionic lipids. However, a different perturbation of the two model membranes, mediated by cholesterol redistribution, was observed and this might be at the basis of Ageritin selective toxicity towards cancer cells