Clinical Determinants and Prognosis of Left Ventricular Reverse Remodelling in Non-Ischemic Dilated Cardiomyopathy

Aims: Non-ischaemic dilated cardiomyopathy (NIDCM) is characterized by left ventricular (LV) chamber enlargement and systolic dysfunction in the absence of coronary artery disease. Left ventricular reverse remodelling (LVRR) is the ability of a dilated ventricle to restore its normal size, shape and function. We sought to determine the frequency, clinical predictors and prognostic implications of LVRR, in a cohort of heart failure (HF) patients with NIDCM. Methods: We conducted a multicentre observational, retrospective cohort study of patients with NIDCM, with prospective serial echocardiography evaluations. LVRR was defined as an increase of ≥15% in left ventricular ejection fraction (LVEF) or as a LVEF increase ≥ 10% plus reduction of LV end-systolic diameter index ≥ 20%. We used multivariable logistic regression analyses to identify the baseline clinical predictors of LVRR and evaluate the prognostic impact of LVRR. Results: LVRR was achieved in 42.5% of 527 patients with NIDCM during the first year of follow-up (median LVEF 49%, median change +22%), Alcoholic aetiology, HF duration, baseline LVEF and the absence of LBBB (plus NT-proBNP levels when in the model), were the strongest predictors of LVRR. During a median follow-up of 47 months, 134 patients died (25.4%) and 7 patients (1.3%) received a heart transplant. Patients with LVRR presented better outcomes, regardless of other clinical conditions. Conclusions: In patients with NIDCM, LVRR was frequent and was associated with improved prognosis. Major clinical predictors of LVRR were alcoholic cardiomyopathy, absence of LBBB, shorter HF duration, and lower baseline LVEF and NT-proBNP levels. Our study advocates for clinical phenotyping of non-ischaemic dilated cardiomyopathy and intense gold-standard treatment optimization of patients according to current guidelines and recommendations in specialized HF units.

Properties and functions of TP/PD-ECGF — enzyme and angiogenic factor in norm and in neoplastic pathology

Thymidine phosphorylase is a protein which may has a dual action: it is a rate-limiting enzyme in thymidine metabolism and it is similar to the platelet – derived endothelial cell growth factor (PD/ECGF). The enzyme catalyzes the reversible reaction of phosphorolytic cleavage of thymidine to thymine and deoxyribose-1-phosphate. It has been found that TP has higher activity in tumor tissues. Also it is involved in a proliferative process in a wide variety of chronic inflammatory diseases. Increased expression of PD/ECGF in many tumors is associated with aggressive disease and/or poor prognosis. Its known that high TP activity is related to malignant angiogenesis and invasion. On the other hand, TP inhibits a hypoxia induced apoptotic pathway and enhances expression of various inflammatory cytokines and interferons. This apparent role of enzyme in tumor progression has prompted investigation a large number of TP inhibitors for applicability in chemotherapy backbone regimens. The enzymatic activity of PD/ECGF is being able to generate 5-fluorouracile from capecitabine and other precursors. Thus TP is identified as a prime target for developing novel anticancer therapies. The serum TP level in cancer patients provides useful prognostic information regarding both responses to chemotherapy and length of survival and should be used in planning appropriate therapy. TP could be suggested that control of individual enzyme activity in blood serum may be used as informative tool for monitoring of patients and treatment optimization.

Combination treatment optimization using a pan-cancer pathway model

The design of efficient combination therapies is a difficult key challenge in the treatment of complex diseases such as cancers. The large heterogeneity of cancers and the large number of available drugs renders exhaustive in vivo or even in vitro investigation of possible treatments impractical. In recent years, sophisticated mechanistic, ordinary differential equation-based pathways models that can predict treatment responses at a molecular level have been developed. However, surprisingly little effort has been put into leveraging these models to find novel therapies. In this paper we use for the first time, to our knowledge, a large-scale state-of-the-art pan-cancer signaling pathway model to identify candidates for novel combination therapies to treat individual cancer cell lines from various tissues (e.g., minimizing proliferation while keeping dosage low to avoid adverse side effects) and populations of heterogeneous cancer cell lines (e.g., minimizing the maximum or average proliferation across the cell lines while keeping dosage low). We also show how our method can be used to optimize the drug combinations used in sequential treatment plans—that is, optimized sequences of potentially different drug combinations—providing additional benefits. In order to solve the treatment optimization problems, we combine the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm with a significantly more scalable sampling scheme for truncated Gaussian distributions, based on a Hamiltonian Monte-Carlo method. These optimization techniques are independent of the signaling pathway model, and can thus be adapted to find treatment candidates for other complex diseases than cancers as well, as long as a suitable predictive model is available.

Structure and Magnetic Properties of Thermodynamically Predicted Rapidly Quenched Fe85-xCuxB15 Alloys

In this work, based on the thermodynamic prediction, the comprehensive studies of the influence of Cu for Fe substitution on the crystal structure and magnetic properties of the rapidly quenched Fe85B15 alloy in the ribbon form are performed. Using thermodynamic calculations, the parabolic shape dependence of the ΔGamoprh with a minimum value at 0.6% of Cu was predicted. The ΔGamoprh from the Cu content dependence shape is also asymmetric, and, for Cu = 0% and Cu = 1.5%, the same ΔGamoprh value is observed. The heat treatment optimization process of all alloys showed that the least lossy (with a minimum value of core power losses) is the nanocomposite state of nanocrystals immersed in an amorphous matrix obtained by annealing in the temperature range of 300–330 °C for 20 min. The minimum value of core power losses P10/50 (core power losses at 1T@50Hz) of optimally annealed Fe85-xCuxB15 x = 0,0.6,1.2% alloys come from completely different crystallization states of nanocomposite materials, but it strongly correlates with Cu content and, thus, a number of nucleation sites. The TEM observations showed that, for the Cu-free alloy, the least lossy crystal structure is related to 2–3 nm short-ordered clusters; for the Cu = 0.6% alloy, only the limited value of several α-Fe nanograins are found, while for the Cu-rich alloy with Cu = 1.2%, the average diameter of nanograins is about 26 nm, and they are randomly distributed in the amorphous matrix. The only high number of nucleation sites in the Cu = 1.2% alloy allows for a sufficient level of grains’ coarsening of the α-Fe phase that strongly enhances the ferromagnetic exchange between the α-Fe nanocrystals, which is clearly seen with the increasing value of saturation induction up to 1.7T. The air-annealing process tested on studied alloys for optimal annealing conditions proves the possibility of its use for this type of material.

Modelling and Simulation of Phase Formations in Martensitic Stainless Steels

Modelling and simulation of solidification processes and solid-state phase transformation have become key instruments in the field of alloy development and heat treatment optimization. Apart from equilibrium-controlled processes, also diffusion-based effects need to be considered. This contribution presents some typical approaches at the example of martensitic stainless steels. Important aspects affecting the production and properties of these steels, such as alloying limits with nitrogen, the formation of ledeburitic structures, or the retained austenite content after heat treatment, can be predicted with reasonable accuracy.

Impact of Maximizing Css/MIC Ratio on Efficacy of Continuous Infusion Meropenem Against Documented Gram-Negative Infections in Critically Ill Patients and Population Pharmacokinetic/Pharmacodynamic Analysis to Support Treatment Optimization

Introduction: optimal treatment of Gram-negative infections in critically ill patients is challenged by changing pathophysiological conditions, reduced antimicrobial susceptibility and limited therapeutic options. The aim of this study was to assess the impact of maximizing Css/MIC ratio on efficacy of continuous infusion (CI) meropenem in treating documented Gram-negative infections in critically ill patients and to perform a population pharmacokinetic/pharmacodynamic analysis to support treatment optimization.Materials and Methods: Classification and regression tree (CART) analysis was used to identify whether a cutoff of steady-state meropenem concentration (Css)-to-minimum inhibitory concentration (MIC) (Css/MIC) ratio correlated with favorable clinical outcome. A non-parametric approach with Pmetrics was used for pharmacokinetic analysis and covariate evaluation. The probability of target attainment (PTA) of the identified Css/MIC ratio was calculated by means of Monte Carlo simulations. Cumulative fraction of response (CFRs) were calculated against common Enterobacterales, P. aeruginosa and A. baumannii as well.Results: a total of 74 patients with 183 meropenem Css were included. CART analysis identified a Css/MIC ratio ≥4.63 as cutoff value significantly associated with favorable clinical outcomes. Multivariate regression analysis confirmed the association [OR (95%CI): 20.440 (2.063–202.522); p < 0.01]. Creatinine clearance (CLCR) was the only covariate associated with meropenem clearance. Monte Carlo simulations showed that, across different classes of renal function, dosages of meropenem ranging between 0.5 and 2 g q6h over 6 h (namely by CI) may grant PTAs of Css/MIC ratios ≥4.63 against susceptible pathogens with an MIC up to the EUCAST clinical breakpoint of 2 mg/L. The CFRs achievable with these dosages were very high (>90%) against Enterobacterales across all the classes of renal function and against P. aeruginosa among patients with CLCR < 30 ml/min/1.73 m2, and quite lower against A. baumannii.Discussion: our findings suggest that Css/MIC ratio ≥4.63 may be considered the pharmacodynamic target useful at maximizing the efficacy of CI meropenem in the treatment of Gram-negative infections in critically ill patients. Dosages ranging between 0.5 g q6h and 2 g q6h by CI may maximize the probability of favorable clinical outcome against meropenem-susceptible Gram-negative pathogens among critically ill patients having different degrees of renal function.