Chimeric Antigen Receptor T-Cell Therapy: What We Expect Soon

The treatment landscape for hematologic malignancies has changed since the recent approval of highly effective chimeric antigen receptor T-cell therapies (CAR-T). Moreover, more than 600 active trials are currently ongoing. However, early enthusiasm should be tempered since several issues are still unsolved and represent the challenges for the coming years. The lack of initial responses and early relapse are some hurdles to be tackled. Moreover, new strategies are needed to increase the safety profile or shorten the manufacturing process during CAR-T cells therapy production. Nowadays, most clinically evaluated CAR-T cells products are derived from autologous immune cells. The use of allogeneic CAR-T cells products generated using cells from healthy donors has the potential to change the scenario and overcome many of these limitations. In addition, CAR-T cells carry a high price tag, and there is an urgent need to understand how to pay for these therapies as many of today’s current payment systems do not feature the functionality to address the reimbursement gap. Finally, the clinical experience with CAR-T cells for solid tumors has been less encouraging, and development in this setting is desirable.     

On computing the 2‐diameter ‐constrained K ‐reliability of networks

This article considers a communication network modeled by a graph and a distinguished set of terminal nodes . We assume that the nodes never fail, but the edges fail randomly and independently with known probabilities. The classical K ‐reliability problem computes the probability that the subnetwork is composed only by the surviving edges in such a way that all terminals communicate with each other. The d ‐diameter ‐constrained K ‐reliability generalization also imposes the constraint that each pair of terminals must be the extremes of a surviving path of approximately d length. It allows modeling communication network situations in which limits exist on the acceptable delay times or on the amount of hops that packets can undergo. Both problems have been shown to be NP ‐hard, yet the complexity of certain subproblems remains undetermined. In particular, when , it was an open question whether the instances with were solvable in polynomial time. In this paper, we prove that when and is a fixed parameter (i.e. not an input) the problem turns out to be polynomial in the number of nodes of the network (in fact linear). We also introduce an algorithm to compute these cases in such time and also provide two numerical examples.     

Full complexity analysis of the diameter‐constrained reliability

Let be a simple graph with nodes and links, a subset of “terminals,” a vector , and a positive integer d, called “diameter.” We assume that nodes are perfect but links fail stochastically and independently, with probabilities . The “diameter‐constrained reliability” (DCR) is the probability that the terminals of the resulting subgraph remain connected by paths composed of d links, or less. This number is denoted by . The general DCR computation belongs to the class of ‐hard problems, since it subsumes the problem of computing the probability that a random graph is connected. The contributions of this paper are twofold. First, a full analysis of the computational complexity of DCR subproblems is presented in terms of the number of terminal nodes and the diameter d. Second, we extend the class of graphs that accept efficient DCR computation. In this class, we include graphs with bounded co‐rank, graphs with bounded genus, planar graphs, and, in particular, Monma graphs, which are relevant to robust network design.     

Analysis and Classification of Human Driving Behaviour in an Urban Environment*

Intelligent vehicle systems have introduced the need for designers to consider user preferences so as to make several kinds of driving features as driver friendly as possible. This requirement raises the problem of how to suitably analyse human performance so they can be implemented in automatic driving tasks. The framework of the present work is an adaptive cruise control with stop and go features for use in an urban setting. In such a context, one of the main requirements is to be able to tune the control strategy to the driver’s style. In order to do this, a number of different drivers were studied through the statistical analysis of their behaviour while driving. The aim of this analysis is to decide whether it is possible to determine a driver’s behaviour, what signals are suitable for this task and which parameters can be used to describe a driver’s style. An assignment procedure is then introduced in order to classify a driver’s behaviour within the stop and go task being considered. Finally, the findings were analysed subjectively and compared with a statistically objective one.     

A multidisciplinary approach for Model Predictive Control Education: A Lego Mindstorms NXT-based framework

This work introduces an educational framework based on the Lego Mindstorms NXT robotic platform used to outline both the theoretical and practical aspects of the Model Predictive Control (MPC) theory. The framework has been developed in the widely used MatLab/Simulink environment. A two-wheeled inverted pendulum is considered as hands-on experimental scenario. For such a system, starting from its mathematical modeling, an established design methodology is presented aiming to outline step-by-step the predictive controller implementation on a low power architecture. This methodology stress the design of a non-linear MPC controller on a low power embedded system, pruning the designer to deal with hard real time constraints without impacting the overall design requirements. The effectiveness of this multidisciplinary approach is shown through this presentation and demonstrated with experimental results.     

Set membership inversion and robust control from data of nonlinear systems

A set membership method for right inversion of nonlinear systems from data is proposed in the paper. Both the cases where the system to invert is known or unknown and therefore identified from data are addressed. The method does not require the invertibility of the regression function describing the system and ensures tight bounds on the inversion error. In the case of unknown system, the method allows the derivation of a robust right‐inverse, guaranteeing the inversion error bound for all the systems belonging to the uncertainty set which can be defined from the available prior and experimental information. Based on such a set membership inversion, two methods for robust control of nonlinear systems from data are introduced: nonlinear feed‐forward control (NFFC) and nonlinear internal model control (NIMC). Both the design methods ensure robust stability and bounded tracking errors for all the systems belonging to the involved uncertainty set. Two applicative examples of robust control from data are presented: NFFC control of semi‐active suspension systems and NIMC control of vehicle lateral dynamics.Copyright © 2013 John Wiley & Sons, Ltd.     

Sodium bicarbonate for early lactation cows fed corn silage or hay crop silage-based diets

To compare the effects of NaHCO3 in diets based on different forage sources, 16 Holstein cows, in a split-plot design, were assigned at 2 d postpartum to a total mixed diet of either 30% hay crop silage: 70% concentrate or 40% corn silage: 60% concentrate (dry basis) that contained 0 or 1.25% NaHCO3. Over the first 6 wk postpartum, NaHCO3 increased milk fat percentage in cows fed the corn silage-based diet. During wk 2 through 6 postpartum, NaHCO3 increased milk yield with the hay crop silage-based diet and tended to decrease milk yield with the corn silage-based diet. Sodium bicarbonate increased digestion of NDF with both forages and increased excretion of urinary nitrogen with the corn silage-based diet. Responses to NaHCO3 by cows in early lactation may depend on the nature of the dietary forage component.     

Gut Microbiota and Sex Hormones: Crosstalking Players in Cardiometabolic and Cardiovascular Disease

The available evidence indicates a close connection between gut microbiota (GM) disturbance and increased risk of cardiometabolic (CM) disorders and cardiovascular (CV) disease. One major objective of this narrative review is to discuss the key contribution of dietary regimen in determining the GM biodiversity and the implications of GM dysbiosis for the overall health of the CV system. In particular, emerging molecular pathways are presented, linking microbiota-derived signals to the local activation of the immune system as the driver of a systemic proinflammatory state and permissive condition for the onset and progression of CM and CV disease. We further outline how the cross-talk between sex hormones and GM impacts disease susceptibility, thereby offering a mechanistic insight into sexual dimorphism observed in CVD. A better understanding of these relationships could help unravel novel disease targets and pave the way to the development of innovative, low-risk therapeutic strategies based on diet interventions, GM manipulation, and sex hormone analogues.     

强烈淬火:改善了硬度和残余应力

通过数值模拟和试验研究结果确定使用强烈淬火方法在表面形成最佳压应力,根据这些结果,提出了改善零件的热处理和设备的一些建议.除了探讨最大表面压应力的形成外,对使用可控淬透性钢的优点也进行了讨论.