38 Spatial immune profiling of human glioblastoma tissue reveals the presence of aggregated lymphoid niches in the tumor microenvironment

BackgroundGlioblastomas (GBM) account for 60% of adult primary brain tumors. With few advances in therapeutics, median overall survival remains 15-months post-diagnosis. Immunotherapies may provide therapeutic benefit in GBM patients; however, no predictive immune features currently inform therapeutic stratification in GBM. We have shown that, independently of known prognosticators, radiographic tumor contact with the lateral ventricle (C-GBM) correlates with 7-months worse survival prognosis compared to patients with ventricle non-contacting GBM (NC-GBM). This study sought to characterize the GBM immune microenvironment and identify targetable mechanisms of immunosuppression correlating with worse outcomes in C-GBM.MethodsTwelve patients presented with pathologically confirmed primary, IDH wildtype C-GBM and thirteen with NC-GBM. Multiplex immunohistochemistry (mxIHC) was performed on formalin-fixed paraffin embedded (FFPE) tissue for each patient interrogating 8 predictive immune markers (CD3, CD4, CD8, FOXP3, CD68, IBA1, PD-1, and PD-L1). Machine learning tools characterized tumor-infiltrating immune populations and identified biomarkers correlating with C-GBM and patient survival. K-means clustering identified immunological neighborhoods within the tissue and a log odds ratio was used to quantify the likelihood of cell-cell interactions in the tissue.ResultsC-GBM tumors were enriched in monocyte-derived macrophages (MDM) compared to NC-GBM (19 ± 8% vs. 6 ± 2%; p<0.001) and depleted in lymphocytes (2.9 ± 1% vs. 7.6 ± 2%; p<0.001) and tissue-resident microglia (1.8 ± 0.3% vs. 7 ± 3%; p<0.001). Further, T cells in C-GBM co-expressed the checkpoint receptors PD-1, suggesting T cell exhaustion in the C-GBM tumor microenvironment. K-means clustering identified 10 immunological niches prevalent in GBM tissue. Macrophage-tumor niches were most common niche in the tissue accounting for 17.93% of all niches, followed by T cell-microglia-tumor niches (17.72%). Conversely, tumor-tumor niches were the least prevalent, accounting for only 2.51% of niches. Within niches, T cell-T cell interactions occurred more frequently than expected by random chance (log odds ratio = 0.90) whereas T cell-macrophage interactions occurred less frequently than expected by random chance (log odds ratio = -1.61). Pathological assessment of the tissue confirmed the presence of lymphoid aggregates in regions of myeloid exclusion in the tissue.ConclusionsThese findings suggest that factors within the periventricular space may influence antitumor immunity within GBM, and have identified clinically targetable immune biomarkers in glioblastoma. The prevalence of T cell niches in GBM tumors suggests the establishment tertiary lymphoid aggregates may be targetable to improve patient outcomes. Lastly, radiologic assessment of lateral ventricle contact by standard-of-care MRI may guide clinical trial design for immunotherapies in neuro-oncology.AcknowledgementsThis study was funded by NIH/NCI grant K00 CA212447 and supported by the Translational Pathology Shared Resource at Vanderbilt University (P30 CA068485).Ethics ApprovalPrimary glioblastoma tumors obtained in accordance with the Declaration of Helsinki and with institutional IRB approval (#131870) along with patient written informed consent.

Generalized Deep Learning EEG Models for Cross-Participant and Cross-Task Detection of the Vigilance Decrement in Sustained Attention Tasks

Tasks which require sustained attention over a lengthy period of time have been a focal point of cognitive fatigue research for decades, with these tasks including air traffic control, watchkeeping, baggage inspection, and many others. Recent research into physiological markers of mental fatigue indicate that markers exist which extend across all individuals and all types of vigilance tasks. This suggests that it would be possible to build an EEG model which detects these markers and the subsequent vigilance decrement in any task (i.e., a task-generic model) and in any person (i.e., a cross-participant model). However, thus far, no task-generic EEG cross-participant model has been built or tested. In this research, we explored creation and application of a task-generic EEG cross-participant model for detection of the vigilance decrement in an unseen task and unseen individuals. We utilized three different models to investigate this capability: a multi-layer perceptron neural network (MLPNN) which employed spectral features extracted from the five traditional EEG frequency bands, a temporal convolutional network (TCN), and a TCN autoencoder (TCN-AE), with these two TCN models being time-domain based, i.e., using raw EEG time-series voltage values. The MLPNN and TCN models both achieved accuracy greater than random chance (50%), with the MLPNN performing best with a 7-fold CV balanced accuracy of 64% (95% CI: 0.59, 0.69) and validation accuracies greater than random chance for 9 of the 14 participants. This finding demonstrates that it is possible to classify a vigilance decrement using EEG, even with EEG from an unseen individual and unseen task.

Formulation and resolutions of the red sky paradox

Most stars in the Universe are red dwarfs. They outnumber stars like our Sun by a factor of 5 and outlive them by another factor of 20 (population-weighted mean). When combined with recent observations uncovering an abundance of temperate, rocky planets around these diminutive stars, we are faced with an apparent logical contradiction—Why do we not see a red dwarf in our sky? To address this “red sky paradox,” we formulate a Bayesian probability function concerning the odds of finding oneself around an F/G/K-spectral type (Sun-like) star. If the development of intelligent life from prebiotic chemistry is a universally rapid and ensured process, the temporal advantage of red dwarfs dissolves, softening the red sky paradox, but exacerbating the classic Fermi paradox. Otherwise, we find that humanity appears to be a 1-in-100 outlier. While this could be random chance (resolution I), we outline three other nonmutually exclusive resolutions (II to IV) that broadly act as filters to attenuate the suitability of red dwarfs for complex life. Future observations may be able to provide support for some of these. Notably, if surveys reveal a paucity of temperate rocky planets around the smallest (and most numerous) red dwarfs, then this would support resolution II. As another example, if future characterization efforts were to find that red dwarf worlds have limited windows for complex life due to stellar evolution, this would support resolution III. Solving this paradox would reveal guidance for the targeting of future remote life sensing experiments and the limits of life in the cosmos.

Evidence of air quality data misreporting in China: An impulse indicator saturation model comparison of local government-reported and U.S. embassy-reported PM2.5 concentrations (2015–2017)

This paper analyzes hourly PM2.5 measurements from government-controlled and U.S. embassy-controlled monitoring stations in five Chinese cities between January 2015 and June 2017. We compare the two datasets with an impulse indicator saturation technique that identifies hours when the relation between Chinese and U.S. reported data diverges in a statistically significant fashion. These temporary divergences, or impulses, are 1) More frequent than expected by random chance; 2) More positive than expected by random chance; and 3) More likely to occur during hours when air pollution concentrations are high. In other words, relative to U.S.-controlled monitoring stations, government-controlled stations systematically under-report pollution levels when local air quality is poor. These results contrast with the findings of other recent studies, which argue that Chinese air quality data misreporting ended after a series of policy reforms beginning in 2012. Our findings provide evidence that local government misreporting did not end after 2012, but instead continued in a different manner. These results suggest that Chinese air quality data, while still useful, should not be taken entirely at face value.

Insightful behaviour in arthropods?

Arthropod behaviour is usually explained through ‘hard-wired’ motor routines and learning abilities that have been favoured by natural selection. We describe observations in which two arthropods solved rare and perhaps completely novel problems, and consider four possible explanations for their behaviours: (i) the behaviour was a pre-programmed motor routine evolved to solve this particular problem, or evolved for other functions but pre-programmed to be recruited for this function under certain conditions; (ii) it was learned previously; (iii) it resulted by chance; or (iv) it was the result of insightful behaviour. Pre-programmed solutions can be favoured by natural selection if they provide solutions to common or crucial problems. Given the apparent rarity of the problems that these animals solved, the solutions they employed are unlikely to represent innate behaviour. Learning and random chance seem unlikely, although we cannot rule them out completely. Possibly these animals employed some degree of insight.

Swineherds and Hogs on Ice: Leadership Impacts for State Chief Judges

Chief judges stand as visible leaders of their courts. Analyses of the Supreme Court focus on the role of the chief justice as an institution-builder seeking out public-facing consensus to protect Court legitimacy. Studying the powers of chief judges and political leadership in general is difficult. Analyzing all 50 states over 16 years we find no evidence that the identity of chief judges explains consensus behavior any better than random chance. This is true even among the subset of chief judges with additional institutional powers like opinion assignment. We show that court structures explain consensus, while leader features do not. Being chief judge correlates with an elevated likelihood of being in the majority, particularly in cases decided by one vote. These results add to our understanding of leadership on courts and imply that the office of chief judge at the state level is more symbolic than uniquely powerful.

A comprehensive analysis of the phylogenetic signal in ramp sequences in 211 vertebrates

Ramp sequences increase translational speed and accuracy when rare, slowly-translated codons are found at the beginnings of genes. Here, the results of the first analysis of ramp sequences in a phylogenetic construct are presented. Ramp sequences were compared from 247 vertebrates (114 Mammalian and 133 non-mammalian), where the presence and absence of ramp sequences was analyzed as a binary character in a parsimony and maximum likelihood framework. Additionally, ramp sequences were mapped to the Open Tree of Life synthetic tree to determine the number of parallelisms and reversals that occurred, and those results were compared to random permutations. Parsimony and maximum likelihood analyses of the presence and absence of ramp sequences recovered phylogenies that are highly congruent with established phylogenies. Additionally, 81% of vertebrate mammalian ramps and 81.2% of other vertebrate ramps had less parallelisms and reversals than the mean from 1000 randomly permuted trees. A chi-square analysis of completely orthologous ramp sequences resulted in a p-value < 0.001 as compared to random chance. Ramp sequences recover comparable phylogenies as other phylogenomic methods. Although not all ramp sequences appear to have a phylogenetic signal, more ramp sequences track speciation than expected by random chance. Therefore, ramp sequences may be used in conjunction with other phylogenomic approaches if many orthologs are taken into account. However, phylogenomic methods utilizing few orthologs should be cautious in incorporating ramp sequences because individual ramp sequences may provide conflicting signals.

Risk, chance and danger in Classical Greek writing on battle

This article highlights two aspects of the language used in Classical Greek literary sources to discuss pitched battle. First, the sources regularly use unqualified forms of the verb kinduneuein, “to take a risk,” when they mean fighting a battle. They do so especially in contexts of deliberation about the need to fight. Second, they often describe the outcome of major engagements in terms of luck, fate, and random chance, at the explicit expense of human agency. Taken together, these aspects of writing on war suggest that pitched battle was seen as an inherently risky course of action with unacceptably unpredictable results, which was therefore best avoided. Several examples show that the decision to fight was indeed evaluated in such terms. This practice casts further doubt on the traditional view that Greek armies engaged in pitched battles as a matter of principle.