Search

Background: VeriStrat is a blood-based proteomic test with predictive and prognostic significance in second-line treatments for non-small cell lung cancer (NSCLC). This trial was designed to investigate the role of VeriStrat in first-line treatment of advanced NSCLC with standard chemotherapy. Here we present the results for 76 non-squamous patients treated with a combination of carboplatin or cisplatin with pemetrexed.Methods: The test-assigned classifications of VeriStrat Good or VeriStrat Poor to samples collected at baseline. The primary end point was progression-free survival (PFS); secondary end points included overall survival (OS) and objective response. Exploratory analyses of end points separately in carboplatin/pemetrexed and cisplatin/pemetrexed subgroups were also conducted.Results: Patients classified as VeriStrat Good had longer PFS and OS than VeriStrat Poor: 6.5 vs 1.6 months and 10.8 vs 3.4 months, respectively; the corresponding hazard ratios (HRs) were 0.36 (P<0.0001) and 0.26 (P<0.0001); they were also more likely to achieve objective response. Prognostic significance of VeriStrat was confirmed in multivariate analysis. Significant differences in OS and PFS between Veristrat classifications were also found when treatment subgroups were analysed separately.Conclusions: The trial demonstrated clinical utility of VeriStrat as a prognostic test for standard first-line chemotherapy of non-squamous advanced NSCLC. [ABSTRACT FROM AUTHOR]

Temperature is a fundamental physical constraint regulating key aspects of microbial life. Protein binding, membrane fluidity, central dogma processes, and metabolism are all tightly controlled by temperature, such that growth rate profiles across taxa and environments follow the same general curve. An open question in microbial ecology is how the effects of temperature on individual traits scale up to determine community structure and function at planetary scales. Here, we review recent theoretical and experimental efforts to connect physiological responses to the outcome of species interactions, the assembly of microbial communities, and their function as temperature changes. We identify open questions in the field and define a roadmap for future studies., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Rules of thumb are behavioral algorithms that approximate optimal behavior while lowering cognitive and sensory costs. One way to reduce these costs is by simplifying the representation of the environment: While the theoretically optimal behavior may depend on many environmental variables, a rule of thumb may use a smaller set of variables that performs reasonably well. Experimental proof of this simplification requires an exhaustive mapping of all relevant combinations of several environmental parameters, which we performed for Caenorhabditis elegans foraging by covering systematically combinations of food density (across 4 orders of magnitude) and food type (across 12 bacterial strains). We found that worms' response is dominated by a single environmental variable: food density measured as number of bacteria per unit surface. They disregard other factors such as biomass content or bacterial strain. We also measured experimentally the impact on fitness of each type of food, determining that the rule is near-optimal and therefore constitutes a rule of thumb that leverages the most informative environmental variable. These results set the stage for further investigations into the underlying genetic and neural mechanisms governing this simplification process, and into its role in the evolution of decision-making strategies., (© 2023. Springer Nature Limited.)

Earth's life-sustaining oceans harbor diverse bacterial communities that display varying composition across time and space. While particular patterns of variation have been linked to a range of factors, unifying rules are lacking, preventing the prediction of future changes. Here, analyzing the distribution of fast- and slow-growing bacteria in ocean datasets spanning seasons, latitude, and depth, we show that higher seawater temperatures universally favor slower-growing taxa, in agreement with theoretical predictions of how temperature-dependent growth rates differentially modulate the impact of mortality on species abundances. Changes in bacterial community structure promoted by temperature are independent of variations in nutrients along spatial and temporal gradients. Our results help explain why slow growers dominate at the ocean surface, during summer, and near the tropics and provide a framework to understand how bacterial communities will change in a warmer world.

The relationship between the number of available nutrients and community diversity is a central question in ecological research that remains unanswered. Here we studied the assembly of hundreds of soil-derived microbial communities on a wide range of well-defined resource environments, from single carbon sources to combinations of up to 16. We found that, while single resources supported multispecies communities varying from 8 to 40 taxa, mean community richness increased only one-by-one with additional resources. Cross-feeding could reconcile these seemingly contrasting observations, with the metabolic network seeded by the supplied resources explaining the changes in richness due to both the identity and the number of resources, as well as the distribution of taxa across different communities. By using a consumer-resource model incorporating the inferred cross-feeding network, we provide further theoretical support to our observations and a framework to link the type and number of environmental resources to microbial community diversity., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Foraging animals have to locate food sources that are usually patchily distributed and subject to competition. Deciding when to leave a food patch is challenging and requires the animal to integrate information about food availability with cues signaling the presence of other individuals (e.g., pheromones). To study how social information transmitted via pheromones can aid foraging decisions, we investigated the behavioral responses of the model animal Caenorhabditis elegans to food depletion and pheromone accumulation in food patches. We experimentally show that animals consuming a food patch leave it at different times and that the leaving time affects the animal preference for its pheromones. In particular, worms leaving early are attracted to their pheromones, while worms leaving later are repelled by them. We further demonstrate that the inversion from attraction to repulsion depends on associative learning and, by implementing a simple model, we highlight that it is an adaptive solution to optimize food intake during foraging., Competing Interests: MD, AP, FS, JG No competing interests declared, (© 2021, Dal Bello et al.)

Timely identification of COVID-19 patients at high risk of mortality can significantly improve patient management and resource allocation within hospitals. This study seeks to develop and validate a data-driven personalized mortality risk calculator for hospitalized COVID-19 patients. De-identified data was obtained for 3,927 COVID-19 positive patients from six independent centers, comprising 33 different hospitals. Demographic, clinical, and laboratory variables were collected at hospital admission. The COVID-19 Mortality Risk (CMR) tool was developed using the XGBoost algorithm to predict mortality. Its discrimination performance was subsequently evaluated on three validation cohorts. The derivation cohort of 3,062 patients has an observed mortality rate of 26.84%. Increased age, decreased oxygen saturation (≤ 93%), elevated levels of C-reactive protein (≥ 130 mg/L), blood urea nitrogen (≥ 18 mg/dL), and blood creatinine (≥ 1.2 mg/dL) were identified as primary risk factors, validating clinical findings. The model obtains out-of-sample AUCs of 0.90 (95% CI, 0.87-0.94) on the derivation cohort. In the validation cohorts, the model obtains AUCs of 0.92 (95% CI, 0.88-0.95) on Seville patients, 0.87 (95% CI, 0.84-0.91) on Hellenic COVID-19 Study Group patients, and 0.81 (95% CI, 0.76-0.85) on Hartford Hospital patients. The CMR tool is available as an online application at covidanalytics.io/mortality&#95;calculator and is currently in clinical use. The CMR model leverages machine learning to generate accurate mortality predictions using commonly available clinical features. This is the first risk score trained and validated on a cohort of COVID-19 patients from Europe and the United States., Competing Interests: KN, MS, BS are employed by Hartford HealthCare. ON is employed by Benefits Science Technologies. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

: The treatment of advanced non-small cell lung cancer (NSCLC) has been revolutionized by immune checkpoint inhibitors (ICIs). The identification of prognostic and predictive factors in ICIs-treated patients is presently challenging. Circulating tumor cells (CTCs) and cell-free DNA (cfDNA) were evaluated in 89 previously treated NSCLC patients receiving nivolumab. Blood samples were collected before therapy and at the first and second radiological response assessments. CTCs were isolated by a filtration-based method. cfDNA was extracted from plasma and estimated by quantitative PCR. Patients with baseline CTC number and cfDNA below their median values (2 and 836.5 ng from 3 mL of blood and plasma, respectively) survived significantly longer than those with higher values (p = 0.05 and p = 0.04, respectively). The two biomarkers were then used separately and jointly as time-dependent covariates in a regression model confirming their prognostic role. Additionally, a four-fold risk of death for the subgroup presenting both circulating biomarkers above the median values was observed ( p < 0.001). No significant differences were found between circulating biomarkers and best response. However, progressing patients with concomitant lower CTCs and cfDNA performed clinically well ( p = 0.007), suggesting that jointed CTCs and cfDNA might help discriminate a low-risk population which might benefit from continuing ICIs beyond progression., Competing Interests: C.G. received honoraria from AstraZeneca, Boehringer-Ingelheim, Bristol-Myers-Squibb. G.R. received honoraria as medical writer from Amgen and Roche. E.R. received honoraria from Bristol-Myers Squibb. F.G. has consulting/advisory relationship with and received honoraria from Bristol-Myers Squibb, Merck Sharp & Dohme, and Pierre Fabre and has consulting/advisory relationship with AstraZeneca and Roche. The other authors indicated no financial relationship.

Microbial cooperation pervades ecological scales, from single-species populations to host-associated microbiomes. Understanding the mechanisms promoting the stability of cooperation against potential threats by cheaters is a major question that only recently has been approached experimentally. Synthetic biology has helped to uncover some of these basic mechanisms, which were to some extent anticipated by theoretical predictions. Moreover, synthetic cooperation is a promising lead towards the engineering of novel functions and enhanced productivity of microbial communities. Here, we review recent progress on engineered cooperation in microbial ecosystems. We focus on bottom-up approaches that help to better understand cooperation at the population level, progressively addressing the challenges of tackling higher degrees of complexity: spatial structure, multispecies communities, and host-associated microbiomes. We envisage cooperation as a key ingredient in engineering complex microbial ecosystems.

Research on regime shifts has focused primarily on how changes in the intensity and duration of press disturbances precipitate natural systems into undesirable, alternative states. By contrast, the role of recurrent pulse perturbations, such as extreme climatic events, has been largely neglected, hindering our understanding of how historical processes regulate the onset of a regime shift. We performed field manipulations to evaluate whether combinations of extreme events of temperature and sediment deposition that differed in their degree of temporal clustering generated alternative states in rocky intertidal epilithic microphytobenthos (biofilms) on rocky shores. The likelihood of biofilms to shift from a vegetated to a bare state depended on the degree of temporal clustering of events, with biofilm biomass showing both states under a regime of non-clustered (60 d apart) perturbations while collapsing in the clustered (15 d apart) scenario. Our results indicate that time since the last perturbation can be an important predictor of collapse in systems exhibiting alternative states and that consideration of historical effects in studies of regime shifts may largely improve our understanding of ecosystem dynamics under climate change., (© 2018 by the Ecological Society of America.)

Understanding how increasing human domination of the biosphere affects life on earth is a critical research challenge. This task is facilitated by the increasing availability of open-source data repositories, which allow ecologists to address scientific questions at unprecedented spatial and temporal scales. Large datasets are mostly observational, so they may have limited ability to uncover causal relations among variables. Experiments are better suited at attributing causation, but they are often limited in scope. We propose hybrid datasets, resulting from the integration of observational with experimental data, as an approach to leverage the scope and ability to attribute causality in ecological studies. We show how the analysis of hybrid datasets with emerging techniques in time series analysis (Convergent Cross-mapping) and macroecology (Joint Species Distribution Models) can generate novel insights into causal effects of abiotic and biotic processes that would be difficult to achieve otherwise. We illustrate these principles with two case studies in marine ecosystems and discuss the potential to generalize across environments, species and ecological processes. If used wisely, the analysis of hybrid datasets may become the standard approach for research goals that seek causal explanations for large-scale ecological phenomena., (© 2018 by the Ecological Society of America.)

Understanding how historical processes modulate the response of ecosystems to perturbations is becoming increasingly important. In contrast to the growing interest in projecting biodiversity and ecosystem functioning under future climate scenarios, how legacy effects originating from historical conditions drive change in ecosystems remains largely unexplored. Using experiments in combination with stochastic antecedent modelling, we evaluated how extreme warming, sediment deposition and grazing events modulated the ecological memory of rocky intertidal epilithic microphytobenthos (EMPB). We found memory effects in the non-clustered scenario of disturbance (60 days apart), where EMPB biomass fluctuated in time, but not under clustered disturbances (15 days apart), where EMPB biomass was consistently low. A massive grazing event impacted on EMPB biomass in a second run of the experiment, also muting ecological memory. Our results provide empirical support to the theoretical expectation that stochastic fluctuations promote ecological memory, but also show that contingencies may lead to memory loss., (© 2017 John Wiley & Sons Ltd.)

Introduction: Vinflunine belongs to the class of vinca alkaloids and acts by disrupting the microtubule dynamics during cell cycle; this agent is currently available for previously treated advanced transitional cell carcinoma in Europe. The aim of this invited review is to evaluate the potential role of vinflunine for the treatment of non-small cell lung cancer (NSCLC). Areas covered: The potential role of vinflunine in NSCLC is discussed on the basis of the available data, including full papers and meeting abstracts. Relevant preclinical studies describing the pharmacological properties of vinflunine are also included. The review also summarizes clinical studies, including phase I trials involving NSCLC among other tumors as well as phase II/III trials specifically addressing this malignancy. Additionally, the safety profile and the current regulatory status of vinflunine is discussed. Expert opinion: Vinflunine is active as single agent and as part of platinum-based combinations in NSCLC. It results non-inferior to docetaxel in a randomized phase III trial including previously treated NSCLC patients; additionally, its safety profile is generally considered manageable. Ultimately, further studies are needed to confirm the role of vinflunine in NSCLC, in consideration of the evolving evidence regarding targeted therapies and immune check-point inhibitors.

Introduction: The evaluation by a "Psychiatric Board" of workers in certified sickness absence is a complex practice, and its results have significant effects from a work and health standpoint., Objectives: To evaluate the inter-rater reliability in the psychiatric board and the association between self-reported measurement and the board judgment., Materials and Method: information was obtained from 68 school teachers on sick leaves through self-reported scales (Zung and Conde Self-rating Scale for Depression; Maslach Burnout Inventory; Effort-reward Imbalance Questionnaire; and Self Reported Present Health State Scale). Blind clinical psychiatric evaluation regarding the former information was carried out. Two independent scores of the Global Assessment Scale; Clinical Global Impression; Brief Psychiatric Rating Scale and Reliability Scale were obtained., Results: The results support the reliability of the instruments and that they can provide important information to the Psychiatric Board.