Treatment Guidance for Patients With Lung Cancer During the Coronavirus 2019 Pandemic

The global coronavirus disease 2019 pandemic continues to escalate at a rapid pace inundating medical facilities and creating substantial challenges globally. The risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in patients with cancer seems to be higher, especially as they are more likely to present with an immunocompromised condition, either from cancer itself or from the treatments they receive. A major consideration in the delivery of cancer care during the pandemic is to balance the risk of patient exposure and infection with the need to provide effective cancer treatment. Many aspects of the SARS-CoV-2 infection currently remain poorly characterized and even less is known about the course of infection in the context of a patient with cancer. As SARS-CoV-2 is highly contagious, the risk of infection directly affects the cancer patient being treated, other cancer patients in close proximity, and health care providers. Infection at any level for patients or providers can cause considerable disruption to even the most effective treatment plans. Lung cancer patients, especially those with reduced lung function and cardiopulmonary comorbidities are more likely to have increased risk and mortality from coronavirus disease 2019 as one of its common manifestations is as an acute respiratory illness. The purpose of this manuscript is to present a practical multidisciplinary and international overview to assist in treatment for lung cancer patients during this pandemic, with the caveat that evidence is lacking in many areas. It is expected that firmer recommendations can be developed as more evidence becomes available

Adsorption of 2-chlorophenol on Cu2O(111)–CuCUS: A first-principles density functional study

First-principles density functional theory and a periodic-slab model have been utilized to investigate the adsorption of a 2-chlorophenol molecule on a CuO(1 1 1) surface with a vacant Cu surface site, namely Cu2O(1 1 1)-CuCUS. Several vertical and flat orientations have been studied. All of these molecular configurations interact very weakly with the Cu2O(1 1 1)-CuCUS surface, an observation which also holds for clean copper surfaces and the Cu2O(1 1 0):CuO surface. Hydroxyl-bond dissociation assisted by the surface was found to be endoergic by 0.42-1.72 eV, depending predominantly on the position of the isolated H on the surface. In addition, the corresponding adsorbed 2-chlorophenoxy moiety was found to be more stable than a vacuum 2-chlorophenoxy radical by about 0.76 eV. Despite these predicted endoergicities, however, we would predict the formation of 2-chlorophenoxy radicals from gaseous 2-chlorophenol over the copper (I) oxide Cu2O(1 1 1)-CuCUS surface to be a feasible and important process in the formation of PCDD/Fs in the post-flame region where gas-phase routes are negligible

Facial Electromyography-based Adaptive Virtual Reality Gaming for Cognitive Training.

Cognitive training has shown promising results for delivering improvements in human cognition related to attention, problem solving, reading comprehension and information retrieval. However, two frequently cited problems in cognitive training literature are a lack of user engagement with the training programme, and a failure of developed skills to generalise to daily life. This paper introduces a new cognitive training (CT) paradigm designed to address these two limitations by combining the benefits of gamification, virtual reality (VR), and affective adaptation in the development of an engaging, ecologically valid, CT task. Additionally, it incorporates facial electromyography (EMG) as a means of determining user affect while engaged in the CT task. This information is then utilised to dynamically adjust the game’s difficulty in real-time as users play, with the aim of leading them into a state of flow. Affect recognition rates of 64.1% and 76.2%, for valence and arousal respectively, were achieved by classifying a DWT-Haar approximation of the input signal using kNN. The affect-aware VR cognitive training intervention was then evaluated with a control group of older adults. The results obtained substantiate the notion that adaptation techniques can lead to greater feelings of competence and a more appropriate challenge of the user’s skills

Identification and validation of expressed HLA-binding breast cancer neoepitopes for potential use in individualized cancer therapy

Background Therapeutic regimens designed to augment the immunological response of a patient with breast cancer (BC) to tumor tissue are critically informed by tumor mutational burden and the antigenicity of expressed neoepitopes. Herein we describe a neoepitope and cognate neoepitope-reactive T-cell identification and validation program that supports the development of next-generation immunotherapies. Methods Using GPS Cancer, NantOmics research, and The Cancer Genome Atlas databases, we developed a novel bioinformatic-based approach which assesses mutational load, neoepitope expression, human leukocyte antigen (HLA)-binding prediction, and in vitro confirmation of T-cell recognition to preferentially identify targetable neoepitopes. This program was validated by application to a BC cell line and confirmed using tumor biopsies from two patients with BC enrolled in the Tumor-Infiltrating Lymphocytes and Genomics (TILGen) study. Results The antigenicity and HLA-A2 restriction of the BC cell line predicted neoepitopes were determined by reactivity of T cells from HLA-A2-expressing healthy donors. For the TILGen subjects, tumor-infiltrating lymphocytes (TILs) recognized the predicted neoepitopes both as peptides and on retroviral expression in HLA-matched Epstein-Barr virus-lymphoblastoid cell line and BC cell line MCF-7 cells; PCR clonotyping revealed the presence of T cells in the periphery with T-cell receptors for the predicted neoepitopes. These high-avidity immune responses were polyclonal, mutation-specific and restricted to either HLA class I or II. Interestingly, we observed the persistence and expansion of polyclonal T-cell responses following neoadjuvant chemotherapy. Conclusions We demonstrate our neoepitope prediction program allows for the successful identification of neoepitopes targeted by TILs in patients with BC, providing a means to identify tumor-specific immunogenic targets for individualized treatment, including vaccines or adoptively transferred cellular therapies.Immunobiology of allogeneic stem cell transplantation and immunotherapy of hematological disease

Joint effect of obesity and TNFA variability on asthma: two international cohort studies

Obesity is a risk factor for asthma. Adipose tissue expresses pro-inflammatory molecules including tumour necrosis factor (TNF), and levels of TNF are also related to polymorphisms in the TNF-a (TNFA) gene. The current authors examined the joint effect of obesity and TNFA variability on asthma in adults by combining two population-based studies. The European Community Respiratory Health Survey and the Swiss Cohort Study on Air Pollution and Lung and Heart Disease in Adults used comparable protocols, questionnaires and measures of lung function and atopy. DNA samples from 9,167 participants were genotyped for TNFA -308 and lymphotoxin-a (LTA) +252 gene variants. Obesity and TNFA were associated with asthma when mutually adjusting for their independent effects (odds ratio (OR) for obesity 2.4, 95% confidence interval (CI) 1.7–3.2; OR for TNFA -308 polymorphism 1.3, 95% CI 1.1–1.6). The association of obesity with asthma was stronger for subjects carrying the G/A and A/A TNFA -308 genotypes compared with the more common G/G genotype, particularly among nonatopics (OR for G/A and A/A genotypes 6.1, 95% CI 2.5–14.4; OR for G/G genotype 1.7, 95% CI 0.8–3.3). The present findings provide, for the first time, evidence for a complex pattern of interaction between obesity, a pro-inflammatory genetic factor and asthma

The twin hypotheses

The Brain Code (BC) relies on several essential concepts that are found across a range of physiological and behavioral functions. The Fundamental Code Unit (FCU) assumes an abstract code unit to allow for a higher order of abstractions that informs information exchanges at the cellular and genetic levels, together the two hypotheses provide a foundation for a system level understanding and potentially cyphering of the Brain Code [1–3]. This paper discusses an organizing principle for an abstract framework tested in a limited scope experimental approach as a means to show an empirical example of cognitive measurement as well as a framework for a Cortical Computation methodology. Four important concepts of the BC and FCU are discussed. First, the principle of activation based on Guyton thresholds. This is seen in the well-known and widely documented action potential threshold in neurons, where once a certain threshold is reached, the neuron will fire, reflecting the transmission of information. The concept of thresholds is also valid in Weber minimum detectable difference in our sensing, which applies to our hearing, seeing and touching. Not only the intensity, but also the temporal pattern is affected by this [4]. This brings insight to the second important component, which is duration. The combination of both threshold crossing and duration may define the selection mechanisms, depending on both external and intrinsic factors. However, ranges exist within which tuning can take place. Within reason it can be stated that no functional implication will occur beyond this range. Transfer of information and processing itself relies on energy and can be described in waveforms, which is the third concept. The human sensing system acts as transducer between the different forms of energy, the fourth principle. The aim of the brain code approach is to incorporate these four principles in an explanatory, descriptive and predictive model. The model will take into account fundamental physiological knowledge and aims to reject assumptions that are not yet fully established. In order to fill in the gaps with regards to the missing information, modules consisting of the previous described four principles are explored. This abstraction should provide a reasonable placeholder, as it is based on governing principles in nature. The model is testable and allows for updating as more data becomes available. It aims to replace methods that rely on structural levels to abstraction of functions, or approaches that are evidence-based, but across many noisy-elements and assumptions that outcomes might not reflect behavior at the organism level. </p