Spatial and molecular profiling of the classic Hodgkin lymphoma microenvironment reveals an immunosuppressive mononuclear phagocyte network

Although a lymph node infiltrated by classic Hodgkin lymphoma is mostly composed of non-neoplastic immune cells, the malignant Hodgkin Reed-Sternberg cells (HRSC) successfully suppress an anti-tumor immune response, to create a cancer-permissive microenvironment. Accordingly, unleashing the dormant immune cells, for example by checkpoint inhibition, has been a central focus of recent therapeutic advances for this disease. Here, we profiled the global immune cell composition of normal and diseased lymph nodes by single-cell RNA sequencing, as a basis for interrogating the immediate vicinity of HRSC, first regionally and then at cellular resolution. Our analyses revealed specific immune cells and functional states associated with HRSC. Most prominently, we discovered a non-random spatial association of immunoregulatory mononuclear phagocytes positioned around HRSC, which express the immune checkpoints PD-L1, TIM-3, and the tryptophan-catabolizing protein IDO1. These findings provide a basis for rational targeting and activation of the anti-tumor immune response in classic Hodgkin lymphoma.

Extreme drought triggers transition to an alternative soil microbial state

Soil microbial communities play a pivotal role in regulating ecosystem functioning but they are increasingly threatened by human-driven perturbations, including climate extremes, which are predicted to increase in frequency and intensity with climate change. It has been demonstrated that soil microbial communities are sensitive to climate extremes, such as drought, and that effects can be long-lasting. However, considerable uncertainties remain concerning the response of soil microbial communities to increases in the intensity and frequency of climate extremes, and their potential to trigger transitions to alternative, and potentially deleterious, taxonomic and functional states. Here we demonstrate that extreme, frequent drought induces a shift to an alternative soil microbial state characterised by strongly altered bacterial and fungal community structure of reduced complexity and functionality. Moreover, we found that this drought-induced alternative microbial state persisted after returning soil to its previous moisture status. However, bacterial communities were able to adapt by increasing their growth capacity, despite being of reduced diversity. Abrupt transitions to alternative states are well documented in aquatic and terrestrial plant communities in response to human-induced perturbations, including climate extremes. Our results provide experimental evidence that such transitions also occur in soil microbial communities in response to extreme drought with potentially deleterious consequences for soil health.

Correlation of EEG Envelopes is the Best Method for Identifying Mental Diseases, Functional States, Individual and Intergroup Differences

The principal errors of spectral and coherent analysis are discussed,and the mathematics of these methods is not related to EEG nature. In this regard, in 2011, the new method was developed for evaluating EEG synchronyby the correlation of envelopes, which has a direct and fundamental physiological meaning. The basics of this method and the methodology of subsequent multilateral statistical analysis are considered. The effective use of the method for identifying individual and intergroup differences in the norm and several types of schizophrenia, depressive diseases, five stages of sleep, and similar functional states are presented.

Brain-wide neural co-activations in resting human

Spontaneous neural activity in human as assessed with resting-state functional magnetic resonance imaging (fMRI) exhibits brain-wide coordinated patterns in the frequency of <0.1Hz. However, fast brain-wide networks at the timescales of neuronal events (milliseconds to sub-seconds) and their spatial, spectral, and propagational characteristics remain unclear due to the temporal constraints of hemodynamic signals. With milli-second resolution and whole-head coverage, scalp-based electroencephalography (EEG) provides a unique window into brain-wide networks with neuronal-timescale dynamics, shedding light on the organizing principles of brain function. Using state-of-the-art signal processing techniques, we reconstructed cortical neural tomography from resting-state EEG and extracted component-based co-activation patterns (cCAPs). These cCAPs revealed brain-wide intrinsic networks and their dynamics, indicating the configuration/reconfiguration of resting human brains into recurring and propagating functional states, which are featured with the prominent spatial phenomena of global patterns and anti-state pairs of co-(de)activations. Rich oscillational structures across a wide frequency band (i.e., 0.6Hz, 5Hz, and 10Hz) were embedded in the dynamics of these functional states. We further identified a superstructure that regulated between-state propagations and governed a significant aspect of brain-wide network dynamics. These findings demonstrated how resting-state EEG data can be functionally decomposed using cCAPs to reveal rich structures of brain-wide human neural activations.

Decoding accelerometry for classification and prediction of critically ill patients with severe brain injury

Our goal is to explore quantitative motor features in critically ill patients with severe brain injury (SBI). We hypothesized that computational decoding of these features would yield information on underlying neurological states and outcomes. Using wearable microsensors placed on all extremities, we recorded a median 24.1 (IQR: 22.8–25.1) hours of high-frequency accelerometry data per patient from a prospective cohort (n = 69) admitted to the ICU with SBI. Models were trained using time-, frequency-, and wavelet-domain features and levels of responsiveness and outcome as labels. The two primary tasks were detection of levels of responsiveness, assessed by motor sub-score of the Glasgow Coma Scale (GCSm), and prediction of functional outcome at discharge, measured with the Glasgow Outcome Scale–Extended (GOSE). Detection models achieved significant (AUC: 0.70 [95% CI: 0.53–0.85]) and consistent (observation windows: 12 min–9 h) discrimination of SBI patients capable of purposeful movement (GCSm > 4). Prediction models accurately discriminated patients of upper moderate disability or better (GOSE > 5) with 2–6 h of observation (AUC: 0.82 [95% CI: 0.75–0.90]). Results suggest that time series analysis of motor activity yields clinically relevant insights on underlying functional states and short-term outcomes in patients with SBI.

Structures of prokaryotic ubiquitin-like protein Pup in complex with depupylase Dop reveal the mechanism of catalytic phosphate formation

Pupylation is the post-translational modification of lysine side chains with prokaryotic ubiquitin-like protein (Pup) that targets proteins for proteasomal degradation in mycobacteria and other members of Actinobacteria. Pup ligase PafA and depupylase Dop are the two enzymes acting in this pathway. Although they share close structural and sequence homology indicative of a common evolutionary origin, they catalyze opposing reactions. Here, we report a series of high-resolution crystal structures of Dop in different functional states along the reaction pathway, including Pup-bound states in distinct conformations. In combination with biochemical analysis, the structures explain the role of the C-terminal residue of Pup in ATP hydrolysis, the process that generates the catalytic phosphate in the active site, and suggest a role for the Dop-loop as an allosteric sensor for Pup-binding and ATP cleavage.

Gating by Memory: a Theory of Learning in the Cerebellum

This paper presents a model of learning by the cerebellar circuit. In the traditional and dominant learning model, training teaches finely graded parallel fibre synaptic weights which modify transmission to Purkinje cells and to interneurons that inhibit Purkinje cells. Following training, input in a learned pattern drives a training-modified response. The function is that the naive response to input rates is displaced by a learned one, trained under external supervision. In the proposed model, there is no weight-controlled graduated balance of excitation and inhibition of Purkinje cells. Instead, the balance has two functional states—a switch—at synaptic, whole cell and microzone level. The paper is in two parts. The first is a detailed physiological argument for the synaptic learning function. The second uses the function in a computational simulation of pattern memory. Against expectation, this generates a predictable outcome from input chaos (real-world variables). Training always forces synaptic weights away from the middle and towards the limits of the range, causing them to polarise, so that transmission is either robust or blocked. All conditions teach the same outcome, such that all learned patterns receive the same, rather than a bespoke, effect on transmission. In this model, the function of learning is gating—that is, to select patterns that trigger output merely, and not to modify output. The outcome is memory-operated gate activation which operates a two-state balance of weight-controlled transmission. Group activity of parallel fibres also simultaneously contains a second code contained in collective rates, which varies independently of the pattern code. A two-state response to the pattern code allows faithful, and graduated, control of Purkinje cell firing by the rate code, at gated times.

Heme Oxygenase-1 Predicts Risk Stratification and Immunotherapy Efficacy in Lower Grade Gliomas

Background: Gliomas are the most common tumors in human brains with unpleasing outcomes. Heme oxygenase-1 (HMOX1, HO-1) was a potential target for human cancers. However, their relationship remains incompletely discussed.Methods: We employed a total of 952 lower grade glioma (LGG) patients from TCGA and CGGA databases, and 29 samples in our hospital for subsequent analyses. Expression, mutational, survival, and immune profiles of HMOX1 were comprehensively evaluated. We constructed a risk signature using the LASSO Cox regression model, and further generated a nomogram model to predict survival of LGG patients. Single-cell transcriptomic sequencing data were also employed to investigated the role of HMOX1 in cancer cells.Results: We found that HMOX1 was overexpressed and was related to poorer survival in gliomas. HMOX1-related genes (HRGs) were involved in immune-related pathways. Patients in the high-risk group exhibited significantly poorer overall survival. The risk score was positively correlated with the abundance of resting memory CD4+ T cells, M1, M2 macrophages, and activated dendritic cells. Additionally, immunotherapy showed potent efficacy in low-risk group. And patients with lower HMOX1 expression were predicted to have better response to immunotherapies, suggesting that immunotherapies combined with HMOX1 inhibition may execute good responses. Moreover, significant correlations were found between HMOX1 expression and single-cell functional states including angiogenesis, hypoxia, and metastasis. Finally, we constructed a nomogram which could predict 1-, 3-, and 5-year survival in LGG patients.Conclusion:HMOX1 is involved in immune infiltration and predicts poor survival in patients with lower grade glioma. Importantly, HMOX1 were related to oncological functional states including angiogenesis, hypoxia, and metastasis. A nomogram integrated with the risk signature was obtained to robustly predict glioma patient outcomes, with the potential to guide clinical decision-making.

An intrinsic temporal order of c-Jun N-terminal phosphorylation regulates its activity by orchestrating co-factor recruitment

Protein phosphorylation is a major regulatory mechanism of cellular signalling. The c-Jun proto-oncoprotein is phosphorylated at four residues within its transactivation domain (TAD) by the JNK family kinases, but the functional significance of c-Jun multisite phosphorylation has remained elusive. Here we show that c-Jun phosphorylation by JNK exhibits a defined temporal kinetics, with serine63 and serine73 being phosphorylated more rapidly than threonine91 and threonine93. We identified the positioning of the phosphorylation sites relative to the kinase docking motif, and their primary sequence, as the main factors controlling phosphorylation kinetics. Functional analysis revealed three c-Jun phosphorylation states: unphosphorylated c-Jun recruits the Mbd3 repressor, serine63/73 doubly-phosphorylated c-Jun binds to the Tcf4 co-activator, whereas the fully phosphorylated form disfavours Tcf4 binding attenuating JNK signalling. Thus, c-Jun phosphorylation encodes multiple functional states that drive a complex signalling response from a single JNK input.