Important advancements in the treatment of non-small cell lung cancer (NSCLC) have been achieved over the past two decades, increasing our understanding of the disease biology and mechanisms of ...tumour progression, and advancing early detection and multimodal care. The use of small molecule tyrosine kinase inhibitors and immunotherapy has led to unprecedented survival benefits in selected patients. However, the overall cure and survival rates for NSCLC remain low, particularly in metastatic disease. Therefore, continued research into new drugs and combination therapies is required to expand the clinical benefit to a broader patient population and to improve outcomes in NSCLC.
Worldwide, lung cancer is the most common cause of cancer-related deaths. Molecular targeted therapies and immunotherapies for non-small-cell lung cancer (NSCLC) have improved outcomes markedly over ...the past two decades. However, the vast majority of advanced NSCLCs become resistant to current treatments and eventually progress. In this Perspective, we discuss some of the recent breakthrough therapies developed for NSCLC, focusing on immunotherapies and targeted therapies. We highlight our current understanding of mechanisms of resistance and the importance of incorporating genomic analyses into clinical studies to decipher these further. We underscore the future role of neoadjuvant and maintenance combination therapy approaches to potentially cure early disease. A major challenge to successful development of rational combination therapies will be the application of robust predictive biomarkers for clear-cut patient stratification, and we provide our views on clinical research areas that could influence how NSCLC will be managed over the coming decade.
Gaze—where one looks, how long, and when—plays an essential part in human social behavior. While many aspects of social gaze have been reviewed, there is no comprehensive review or theoretical ...framework that describes how gaze to faces supports face-to-face interaction. In this review, I address the following questions: (1) When does gaze need to be allocated to a particular region of a face in order to provide the relevant information for successful interaction; (2) How do humans look at other people, and faces in particular, regardless of whether gaze needs to be directed at a particular region to acquire the relevant visual information; (3) How does gaze support the regulation of interaction? The work reviewed spans psychophysical research, observational research, and eye-tracking research in both lab-based and interactive contexts. Based on the literature overview, I sketch a framework for future research based on dynamic systems theory. The framework holds that gaze should be investigated in relation to sub-states of the interaction, encompassing sub-states of the interactors, the content of the interaction as well as the interactive context. The relevant sub-states for understanding gaze in interaction vary over different timescales from microgenesis to ontogenesis and phylogenesis. The framework has important implications for vision science, psychopathology, developmental science, and social robotics.
Recently, various algorithms for data-driven simulation and control have been proposed based on the Willems' fundamental lemma. However, when collected data are noisy, these methods lead to ...ill-conditioned data-driven model structures. In this article, we present a maximum likelihood framework to obtain an optimal data-driven model, the signal matrix model, in the presence of output noise. Data compression and noise-level estimation schemes are also proposed to apply the algorithm efficiently to large datasets and unknown noise-level scenarios. Two approaches in system identification and receding horizon control are developed based on the derived optimal estimator. The first one identifies a finite impulse response model. This approach improves the least-squares estimator with less restrictive assumptions. The second one applies the signal matrix model as the predictor in predictive control. The control performance is shown to be better than existing data-driven predictive control algorithms, especially under high noise levels. Both approaches demonstrate that the derived estimator provides a promising framework to apply data-driven algorithms to noisy data.
The treatment landscape of driver-negative non-small-cell lung cancer (NSCLC) is rapidly evolving. Immune-checkpoint inhibitors, specifically those targeting PD-1 or PD-L1, have demonstrated durable ...efficacy in a subset of patients with NSCLC, and these agents have become the cornerstone of first-line therapy. Approved immunotherapeutic strategies for treatment-naive patients now include monotherapy, immunotherapy-exclusive regimens or chemotherapy-immunotherapy combinations. Decision making in this space is complex given the absence of head-to-head prospective comparisons, although a thorough analysis of long-term efficacy and safety data from pivotal clinical trials can provide insight into the optimal management of each subset of patients. Indeed, histological subtype and the extent of tumour cell PD-L1 expression are paramount to regimen selection, although other clinicopathological factors and patient preferences might also be relevant in certain scenarios. Finally, several emerging biomarkers and novel therapeutic strategies are currently under investigation, and these might further refine the current treatment paradigm. In this Review, we discuss the current treatment landscape and detail our approach to first-line immunotherapy regimen selection for patients with advanced-stage, driver-negative NSCLC.
The past decade has been transformative for lung cancer patients, physicians, and scientists. The discovery of EGFR mutations that confer sensitivity to tyrosine kinase inhibitors in lung ...adenocarcinomas in 2004 heralded the beginning of the era of precision medicine for lung cancer. Indeed, it precipitated concerted efforts by many investigators to define molecular subgroups of lung cancer, characterize the genomic landscape of lung cancer subtypes, identify novel therapeutic targets, and define mechanisms of sensitivity and resistance to targeted therapies. The fruits of these efforts are visible every day now in lung cancer clinics: Patients receive molecular testing to determine whether their tumor harbors an actionable mutation, new and improved targeted therapies that can overcome resistance to first-generation drugs are in clinical trials, and drugs targeting the immune system are showing activity in patients. This extraordinary promise is tempered by the sobering fact that even the newest treatments for metastatic disease are rarely curative and are effective only in a small fraction of all patients. Ongoing and future efforts to find new vulnerabilities of lung cancers, unravel the complexity of drug resistance, increase the efficacy of immunotherapies, and perform biomarker-driven clinical trials are necessary to improve outcomes for patients with lung cancer.
This paper reports the final results of the predictive building control project OptiControl-II that encompassed seven months of model predictive control (MPC) of a fully occupied Swiss office ...building. First, this paper provides a comprehensive literature review of experimental building MPC studies. Second, we describe the chosen control setup and modeling, the main experimental results, as well as simulation-based comparisons of MPC to industry-standard control using the EnergyPlus simulation software. Third, the costs and benefits of building MPC for cases similar to the investigated building are analyzed. In the experiments, MPC controlled the building reliably and achieved a good comfort level. The simulations suggested a significantly improved control performance in terms of energy and comfort compared with the previously installed industry-standard control strategy. However, for similar buildings and with the tools currently available, the required initial investment is likely too high to justify the deployment in everyday building projects on the basis of operating cost savings alone. Nevertheless, development investments in an MPC building automation framework and a tool for modeling building thermal dynamics together with the increasing importance of demand response and rising energy prices may push the technology into the net benefit range.
Subspace identification techniques have gained widespread acceptance as a method of obtaining a low-order model from data. These are based on using the singular-value decomposition as a means of ...estimating the underlying system order and extracting a basis for the extended observability space. In the presence of noise rank determination becomes difficult and the low rank estimates lose the structure required for exact realizability. Furthermore the noise corrupts the singular values in a manner that is inconsistent with physical noise processes. These problems are addressed by an optimization based approach using a nuclear norm minimization objective. By using Hankel matrices as the underlying data structure exact realizability of the low rank system models is maintained. Noise in the data enters the formulation linearly, allowing for the inclusion of more realistic noise weightings. A cumulative spectral weight is presented and shown to be useful in estimating models from data corrupted via noise. A numerical example illustrates the characteristics of the problem.
Immune-checkpoint inhibitors (ICI), particularly inhibitors of the PD-1 axis, have altered the management of non-small cell lung cancer (NSCLC) over the last 10 years. First demonstrated to improve ...outcomes in second-line or later therapy of advanced disease, ICIs were shown to improve overall survival compared with chemotherapy in first-line therapy for patients whose tumors express PD-L1 on at least 50% of cells. More recently, combining ICIs with chemotherapy has been shown to improve survival in patients with both squamous and nonsquamous NSCLC, regardless of PD-L1 expression. However, PD-L1 and, more recently, tumor mutational burden have not proven to be straightforward indicative biomarkers. We describe the advances to date in utilizing these biomarkers, as well as novel markers of tumor inflammation, to ascertain which patients are most likely to benefit from ICIs. Ongoing translational work promises to improve the proportion of patients who benefit from these agents.
Ventral CA1 neurons store social memory Okuyama, Teruhiro; Kitamura, Takashi; Roy, Dheeraj S. ...
Science (American Association for the Advancement of Science),
09/2016, Letnik:
353, Številka:
6307
Journal Article
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Odprti dostop
The medial temporal lobe, including the hippocampus, has been implicated in social memory. However, it remains unknown which parts of these brain regions and their circuits hold social memory. Here, ...we show that ventral hippocampal CA1 (vCA1) neurons of a mouse and their projections to nucleus accumbens (NAc) shell play a necessary and sufficient role in social memory. Both the proportion of activated vCA1 cells and the strength and stability of the responding cells are greater in response to a familiar mouse than to a previously unencountered mouse. Optogenetic reactivation of vCA1 neurons that respond to the familiar mouse enabled memory retrieval and the association of these neurons with unconditioned stimuli. Thus, vCA1 neurons and their NAc shell projections are a component of the storage site of social memory.
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