Relationship between high-frequency activity in the cortical sensory and the motor hand areas, and their regional myelin content BackgroundThe human primary sensory (S1) and primary motor (M1) hand areas feature high-frequency neuronal responses. Electrical nerve stimulation evokes high-frequency oscillations (HFO) at around 650 Hz in the contralateral S1. Likewise, transcranial magnetic stimulation (TMS) of M1 can evoke a series of descending volleys in the corticospinal pathway that can be detected non-invasively with a paired-pulse TMS protocol, called short interval intracortical facilitation (SICF). SICF features several peaks of facilitation of motor evoked potentials in contralateral hand muscles, which are separated by inter-peak intervals resembling HFO rhythmicity.

HypothesisIn this study, we tested the hypothesis that the individual expressions of HFO and SICF are tightly related to each other and to the regional myelin content in the sensorimotor cortex.

MethodsIn 24 healthy volunteers, we recorded HFO and SICF, and, in a subgroup of 20 participants, we mapped the cortical myelin content using the ratio between the T1- and T2-weighted MRI signal as read-out.

ResultsThe individual frequencies and magnitudes of HFO and SICF curves were tightly correlated: the intervals between the first and second peak of cortical HFO and SICF showed a positive linear relationship (r= 0.703, p< 0.001), while their amplitudes were inversely related (r= -0.613, p= 0.001). The rhythmicity, but not the magnitude of the high-frequency responses, was related to the cortical myelin content: the higher the cortical myelin content, the shorter the inter-peak intervals of HFO and SICF.

ConclusionThe results confirm a tight functional relationship between high-frequency responses in S1 (i.e., HFO) and M1 (i.e., as measured with SICF). They also establish a link between the degree of regional cortical myelination and the expression of high-frequency responses in the human sensorimotor cortex, giving further the opportunity to infer their generators.
Dynamic selective auditory attention detection using RNN and reinforcement learning The cocktail party phenomenon describes the ability of the human brain to focus auditory attention on a particular stimulus while ignoring other acoustic events. Selective auditory attention detection (SAAD) is an important issue in the development of brain-computer interface systems and cocktail party processors. This paper proposes a new dynamic attention detection system to process the temporal evolution of the input signal. The proposed dynamic SAAD is modeled as a sequential decision-making problem, which is solved by recurrent neural network (RNN) and reinforcement learning methods of Q-learning and deep Q-learning. Among different dynamic learning approaches, the evaluation results show that the deep Q-learning approach with RNN as agent provides the highest classification accuracy (94.2%) with the least detection delay. The proposed SAAD system is advantageous, in the sense that the detection of attention is performed dynamically for the sequential inputs. Also, the system has the potential to be used in scenarios, where the attention of the listener might be switched in time in the presence of various acoustic events.
NOMA: a high-throughput microchip for robust, sequential measurements of secretions from the same single-cells Despite recent advances in single-cell analysis technologies, lacking simple methods to keep the live single-cells traceable for longitudinal detection reliably poses a significant obstacle in single-cell secretion analysis. Here we reported the high-density NOMA (narrow-opening microwell array) microchip that realized the retention of[&ge;] 97% of trapped single cells in dedicated spatial locations during repetitive detection procedures, verified with both adherent and suspension cells by two researchers independently. We applied it in monitoring single-cell protein secretions sequentially from the same single cells, and we found the digital protein secretion patterns dominate the protein secretion. We also demonstrated the microchip for longitudinally tracking IL-8 and the CD81+EV secretions from the same single-cells over days, which revealed the presence of "super secretors" within the cell population be more persistent to secrete protein or extracellular vesicle for an extended period. The NOMA platform reported here is simple, robust, and easy to operate for tracking sequential measurements from the same single cells, representing a novel and informative tool to inspire new observations in biomedical research.

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org.highwire.dtl.DTLVardef@aa69c7org.highwire.dtl.DTLVardef@6bc79org.highwire.dtl.DTLVardef@3fcbbforg.highwire.dtl.DTLVardef@597f4b_HPS_FORMAT_FIGEXP  M_FIG C_FIG Determinants of Murine Skin Microbiota Composition in Homeostasis and Wound Healing Animal microbiota have complex interactions with hosts and environment that determines its composition. Yet the ability of hosts to determine their microbiota composition is less well studied. In this study, to investigate the role host genetics in determining skin microbiota, we used 30 different mouse strains from the recombinant inbred panel, the Collaborative Cross. Murine skin microbiota composition was strongly dependent on murine strain with > 50% of the variation explained by murine strain. In particular, a quantitative trait locus on chromosome 4 associates both with Staphylococcus abundance and principal-component multi-trait analyses. Additionally, excisional wound associated changes in microbiota composition were not uniform across mouse strains and were host-specific, the genetic background accounting for about 40% of the variation in microbiota. Genetic background also had the highest effect on the healing speed of wounds accounting for over 50% of the variation while mouse age and microbiota composition change accounted only for 20% and 5% of the healing speed despite reaching statistical significance. In conclusion, host genetics has a significant impact on the skin microbiota composition during both homeostasis and wound healing. These findings have long reaching implications in our understanding of associations between microbiota dysbiosis and disease. Predicting the re-distribution of antibiotic molecules caused byinter-species interactions in microbial communities Microbes associate in nature forming complex communities, but they are often studied in purified form. Here I show that differences in antibiotic sensitivity between co-existing bacterial species can modify the diffusion of antibiotic molecules, and alter the drug efficacy measured in conventional in vitro assays. I developed a model, validated experimentally using an artificial two-species community, showing antibiotic molecules re-distribute evenly across all species if they have similar drug sensitivity. The result is lower drug efficacy with respect to conventional in vitro assays. However, when species have different sensitivities, the re-distribution of antibiotic is uneven and most sensitive species accumulate more drug. The result is increased drug efficacy against these species. Despite this discrepancy with conventional laboratory assays, my data suggests the changes in drug efficacy are predictable and provides insight into how communities can affect the diffusion of other molecules in the environment. Citation needed? Wikipedia and the COVID-19 pandemic BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. Predicting gene regulatory networks from multi-omics to link genetic risk variants and neuroimmunology to Alzheimers disease phenotypes BackgroundGenome-wide association studies have found many genetic risk variants associated with Alzheimers disease (AD). However, how these risk variants affect deeper phenotypes such as disease progression and immune response remains elusive. Also, our understanding of cellular and molecular mechanisms from disease risk variants to various phenotypes is still limited. To address these problems, we performed an integrative multi-omics analysis of genotype, transcriptomics, and epigenomics for revealing gene regulatory mechanisms from disease variants to AD phenotypes.

MethodFirst, given the population gene expression data of a cohort, we construct and cluster its gene co-expression network to identify gene co-expression modules for various AD phenotypes. Next, we predict transcription factors (TFs) regulating co-expressed genes and AD risk SNPs that interrupt TF binding sites on regulatory elements. Finally, we construct a gene regulatory network (GRN) linking SNPs, interrupted TFs, and regulatory elements to target genes and gene modules for each phenotype in the cohort. This network thus provides systematic insights into gene regulatory mechanisms from risk variants to AD phenotypes.

ResultsOur analysis predicted GRNs in three major AD-relevant regions: Hippocampus, Dorsolateral Prefrontal Cortex (DLPFC), Lateral Temporal Lobe (LTL). Comparative analyses revealed cross-region-conserved and region-specific GRNs, in which many immunological genes are present. For instance, SNPs rs13404184 and rs61068452 disrupt SPI1 binding and regulation of AD gene INPP5D in the Hippocampus and LTL. However, SNP rs117863556 interrupts bindings of REST to regulate GAB2 in DLPFC only. Driven by emerging neuroinflammation in AD, we used Covid-19 as a proxy to identify possible regulatory mechanisms for neuroimmunology in AD. To this end, we looked at the GRN subnetworks relating to genes from shared AD-Covid pathways. From those subnetworks, our machine learning analysis prioritized the AD-Covid genes for predicting Covid-19 severity. Decision Curve Analysis also validated our AD-Covid genes outperform known Covid-19 genes for classifying severe Covid-19 patients. This suggests AD-Covid genes along with linked SNPs can be potential novel biomarkers for neuroimmunology in AD. Finally, our results are open-source available as a comprehensive functional genomic map for AD, providing a deeper mechanistic understanding of the interplay among multi-omics, brain regions, gene functions like neuroimmunology, and phenotypes. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Venomics and antivenomics of Indian spectacled cobra (Naja naja) from the Western Ghats Venom proteome profiling of Naja naja from the Western Ghats region in Kerala was achieved through SDS-PAGE and RP-HPLC followed by Q-TOF LC-MS/MS analysis, incorporating PEAKS and Novor assisted de novo sequencing methodologies. A total of 115 proteins distributed across 17 different enzymatic and non-enzymatic venom protein families were identified through conventional and 39 peptides through homology-driven proteomics approaches. Fourteen peptides derived through de novo complements the Mascot data indicating the importance of homology-driven approaches in improving protein sequence information. Among the protein families identified, glutathione peroxidase and endonuclease were reported for the first time in the Indian cobra venom. Immunological cross-reactivity assessed using Indian polyvalent antivenoms suggested that VINS showed better EC50 (2.48 g/mL) value than that of PSAV (6.04 g/mL) and Virchow (6.03 g/mL) antivenoms. Western blotting experiments indicated that all the antivenoms elicited poor binding specificities, especially towards low molecular mass proteins. Second-generation antivenomics studies revealed that VINS antivenom was less efficient to detect many low molecular mass proteins such as three-finger toxins and Kunitz-type serine protease Inhibitors. Taken together, the present study enabled a large-scale characterization of the venom proteome of Naja naja from the Western Ghats and emphasized the need for developing more efficient antivenoms.

HighlightsO_LIProteomics of cobra venom resulted in the identification of 115 proteins representing 17 snake venom protein families.
C_LIO_LIDe novo approaches exclusively yielded 39 peptides harbouring multiple amino acid mutations.
C_LIO_LIGlutathione peroxidase and endonuclease were identified for the first time in Indian cobra venom.
C_LIO_LIIndian polyvalent antivenoms showed varying cross-reactivity towards cobra venom.
C_LIO_LIVINS antivenom was less efficient to detect many low molecular mass proteins (< 20 kDa).
C_LI Secretory cells are the primary source of pIgR in small airways BackgroundLoss of secretory immunoglobulin A (SIgA) is common in COPD small airways and likely contributes to disease progression. We hypothesized loss of SIgA results from reduced expression of pIgR, a chaperone protein needed for SIgA transcytosis, in the COPD small airway epithelium.

MethodspIgR-expressing cells were defined and quantified at single-cell resolution in human airways using RNA in-situ hybridization, immunostaining, and single-cell RNA sequencing. Complementary studies in mice utilized immunostaining, primary murine tracheal epithelial cell (MTEC) culture, and transgenic mice with secretory or ciliated cell-specific knockout of pIgR. SIgA degradation by human neutrophil elastase or secreted bacterial proteases from non-typeable Haemophilus influenzae (NTHi) was evaluated in vitro.

ResultsWe found that secretory cells are the predominant cell type responsible for pIgR expression in human and murine airways. Loss of SIgA in small airways was not associated with a reduction in secretory cells but rather a reduction in pIgR protein expression despite intact PIGR mRNA expression. Neutrophil elastase and NTHi-secreted proteases are both capable of degrading SIgA in vitro and may also contribute to a deficient SIgA immunobarrier in COPD.

InterpretationLoss of the SIgA immunobarrier in small airways of patients severe COPD is complex and likely results from both pIgR-dependent defects in IgA transcytosis and SIgA degradation.

Key MessagesWhat is the key question? Localized SIgA deficiency in small airways is an established driver of COPD pathogenesis, but the mechanism of loss remains unclear. We hypothesized loss of SIgA is due to reduced numbers of pIgR-expressing cells in SIgA-deficient small airways.

What is the bottom line? pIgR is primarily expressed by secretory cells in human and murine airways. Although numbers of secretory cells are similar between SIgA-deficient and SIgA-replete airways in COPD, there is reduced expression of pIgR protein, but not mRNA, in SIgA-deficient airways. Additionally, host and bacterial proteases degrade SIgA in vitro, suggesting loss of SIgA may relate to both impaired transcytosis and increased degradation.

Why read on? This study highlights the complexity of SIgA immunobarrier maintenance and suggests that strategies aimed at restoring the SIgA immunobarrier will need to account for both impaired transcytosis and degradation by host and/or bacterial proteases. Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes IntroductionIncreasingly, logistic regression methods for genetic association studies of binary phenotypes must be able to accommodate data sparsity, which arises from unbalanced case-control ratios and/or rare genetic variants. Sparseness leads to maximum likelihood estimators (MLEs) of log-OR parameters that are biased away from their null value of zero and tests with inflated type 1 errors. Different penalized-likelihood methods have been developed to mitigate sparse-data bias. We study penalized logistic regression using a class of log-F priors indexed by a shrinkage parameter m to shrink the biased MLE towards zero.

MethodsWe propose a two-step approach to the analysis of a genetic association study: first, a set of variants that show evidence of association with the trait is used to estimate m; and second, the estimated m is used for log-F -penalized logistic regression analyses of all variants using data augmentation with standard software. Our estimate of m is the maximizer of a marginal likelihood obtained by integrating the latent log-ORs out of the joint distribution of the parameters and observed data. We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation.

ResultsWe evaluate the statistical properties of our proposed two-step method and compared its performance to other shrinkage methods by a simulation study. Our simulation studies suggest that the proposed log-F -penalized approach has lower bias and mean squared error than other methods considered. We also illustrate the approach on data from a study of genetic associations with "super senior" cases and middle aged controls.

Discussion/ConclusionWe have proposed a method for single rare variant analysis with binary phenotypes by logistic regression penalized by log-F priors. Our method has the advantage of being easily extended to correct for confounding due to population structure and genetic relatedness through a data augmentation approach. Nuclear alpha-synuclein is present in the human brain and is modified in dementia with Lewy bodies Dementia with Lewy bodies is pathologically defined by the cytoplasmic accumulation of alpha-synuclein within neuronal cells in the brain. Alpha-synuclein is predominately pre-synaptic, but has been reported present in various subcellular compartments in cell and animal models. In particular, nuclear alpha-synuclein is evident in-vitro and in disease models and has been associated with altered DNA integrity, gene transcription, nuclear homeostasis. However, owing to various factors, the presence of alpha-synuclein in the nuclei of human brain cells remains controversial, as does its role in synucleinopathies.

Here, we close this gap and provide a unique demonstration confirming the presence of nuclear alpha-synuclein in post-mortem brain tissue obtained from cases of dementia with Lewy bodies as well as from controls via immunohistochemistry, immunoblot, and label-free mass-spectrometry.

Discrete intra-nuclear alpha-synuclein puncta reactive against phosphorylated serine 129-alpha-synuclein and pan-alpha-synuclein antibodies were observed in cortical neurons and non-neuronal cells in fixed brain sections and in isolated nuclear preparations from Dementia with Lewy bodies cases and matched controls. Subsequent biochemical analysis of subcellular fractionated tissue confirmed alpha-synuclein as present in a nuclear fraction at levels ~ 10-fold lower than in the cytoplasm. Critically, however, an increase in monomeric nuclear alpha-synuclein phosphorylated as serine 129 was observed in cases of dementia with Lewy bodies alongside higher molecular weight pan- and phosphorylation reactive alpha-synuclein species, consistent with the formation of intranuclear phosphorylated alpha-synuclein oligomers. Furthermore, the presence of nuclear alpha-synuclein was confirmed via label free mass spectrometry, as 6 unique alpha-synuclein derived peptide sequences were identified in nuclear fractions (71.4% sequence coverage).

Collectively, our data confirm the presence of nuclear alpha-synuclein in human brain tissue and describe nuclear pathology associated with dementia with Lewy bodies. These findings address a major controversy in the synucleinopathy field by confirming the presence of nuclear alpha-synuclein in autoptic human brain tissue and, for the first time, identify that alpha-synuclein is aggregated into novel and potentially pathological assemblies in the nucleus as part of the disease process associated with dementia with Lewy bodies and thus may contribute to the disease phenotype. Embryo development in Carica papaya Linn. Papaya (Carica papaya Linn.) is a tropical plant whose draft genome has been sequenced. Papaya produces large fruits rich in vitamins A and C and is an important cash crop in developing countries. Nonetheless, little is known about how the female gametophyte develops, how it is fertilized and how it develops into a mature seed containing an embryo and an endosperm. The Papaya female gametophyte displays a Polygonum-type architecture consisting of two synergid cells, an egg cell, a central cell, and three antipodal cells. Reports are available of the presumed existence of varieties in which cross fertilization is bypassed and autonomous development of embryos occurs (e.g., apomixis). In this study, we analyzed the development of female gametophytes in a commercial Hawaiian parental line and in the presumed apomictic Costa Rican line L1. Samples were collected before and after anthesis to compare the overall structure, size and transcriptional patterns of several genes that may be involved in egg and endosperm cell fate and proliferation. These genes were the putative papaya homologs of ARGONAUTE9 (AGO9), MEDEA (MEA), RETINOBLASTOMA RELATED-1 (RBR1), and SLOW WALKER-1 (SWA1). Our results suggest that its feasibly to identify structural features of Polygonum-type development, and that in bagged female flowers of line L1 we might have observed autonomous development of embryo-like structures. Possible downregulation of papaya homologs for AGO9, MEA, RBR1 and SWA1 was observed in embryo sacs from line L1 before and after anthesis, which may suggest a link between suspected apomixis and transcriptional downregulation of genes for RNA-directed DNA methylation, histone remodelers, and rRNA processing. Most notably, the large size of the papaya embryo sac suggests that it could be a cytological alternative to Arabidopsis thaliana for study. Significant variation in embryo sac size was observed between the varieties under study, suggesting wide differences in the genetic regulation of anatomical features. Understanding the Spin Crossover Dynamical Effects of the Dioxygen Binding and Activation on HOD Enzyme For the cofactor-free 1-H-3-hydroxy-4-oxoquinaldine-2,4-dioxygenase (HOD), the dioxygen (O2) dependent steps are rate-limiting along with a spin state crossover to the singlet spin state. Here, the primary triplet O2 molecule activation on the 2-methyl-3-hydroxy-4(1H)-quinolone (MHQ) is investigated, and the catalytic role of the intersystem crossing effects is highlighted by directly comparing results from the Born-Oppenheimer dynamics and non-adiabatic surface hopping dynamics. This work confirms non-adiabatic dynamical effects are essential to modulate the O2 activation on the substrate MHQ. The time scale of the equilibration and conversion from triplet to singlet state should be in the range of a few hundreds of femtoseconds. We hope this work provides us a fresh look at the underlying physics of dioxygen activation reactions involving more than one spin state. Simulation of foraging behavior using a decision-making agent with Bayesian and inverse Bayesian inference: Temporal correlations and power laws in displacement patterns It has been stated that in human migratory behavior, the step length series may have temporal correlation and that there is some relationship between this time dependency and the fact that the frequency distribution of step length follows a power-law distribution. Furthermore, the frequency of occurrence of the step length in some large marine organisms has been found to switch between power-law and exponential distributions, depending on the difficulty of prey acquisition. However, to date it has not been clarified how the aforementioned three phenomena arise: the positive correlation created in the step length series, the relation between the positive correlation of the step length series and the form of an individuals step length distribution, and the switching between power-law and exponential distributions depending on the abundance of prey. This study simulated foraging behavior using the Bayesian decision-making agent simultaneously performing both knowledge learning and knowledge-based inference to analyze how the aforementioned three phenomena arise. In the agent with learning and inference, past experiences were stored as hypotheses (knowledge) and they were used in current foraging behavior; at the same time, the hypothesis continued to be updated based on new experiences. The simulation results show that the agent with both learning and inference has a mechanism that simultaneously causes all the phenomena. Sablefish (Anoplopoma fimbria Pallas, 1814) plasma biochemistry and hematology reference intervals including blood cell morphology Plasma biochemistry and hematology reference intervals are integral health assessment tools in all medical fields, including aquatic animal health. As sablefish (Anoplopoma fimbria) are becoming aquaculturally and economically more important, this manuscript provides essential reference intervals (RI) for their plasma biochemistry and hematology along with reference photomicrographs of blood cells in healthy, fasted sablefish. Blood cell morphology can differ between fish species. In addition, blood cell counts and blood chemistry can vary between fish species, demographics, water conditions, seasons, diets, and culture systems, which precludes the use of RIs from other fish species. For this study, blood was collected for plasma biochemistry and hematology analysis between June 20 and July 18, 2019, from healthy, yearling sablefish, hatched and reared in captivity on a commercial diet. Overnight fast of 16-18 hours did not sufficiently reduce lipids in the blood, which led to visible lipemia and frequent rupture of blood cells during analysis. Therefore, sablefish should be fasted for 24 to 36 hours before blood is collected to reduce hematology artifacts or possible reagent interference in plasma biochemistry analysis. Lymphocytes were the most dominant leukocytes (98%), while eosinophils were rare, and basophils were not detected in sablefish. Neutrophils were very large cells with Dohle bodies. In mammals and avian species, Dohle bodies are usually signs of toxic change from inflammation, but no such association was found in these fish. In conclusion, lipemia can interfere with sablefish blood analysis, and available removal methods should be evaluated as fasting for up to 36 h might not always be feasible. Also, more studies are required to establish RI for different developmental stages and rearing conditions. The relative speed of the glucorticoid stress response varies independently of scope and is predicted by environmental variability and longevity across birds. The acute glucocorticoid response is a key mediator of the coordinated vertebrate response to unpredictable challenges. Rapid glucocorticoid increases initiate changes that allow animals to cope with stressors. The scope of the glucocorticoid response -- defined here as the absolute increase in glucocorticoids -- is associated with individual differences in performance and varies across species with environment and life history. In addition to varying in scope, responses can differ enormously in speed; however, relatively little is known about whether speed and absolute glucocorticoid levels covary, how selection shapes speed, or what aspects of speed are important. We used corticosterone samples collected at 5 time points from 1,750 individuals of 60 species of birds to ask i) how the speed and scope of the glucocorticoid response covary and ii) whether variation in absolute or relative speed is predicted by environmental context or life history. As predicted by a recent model, faster absolute glucocorticoid responses were strongly associated with a larger scope. Despite this covariation, the relative speed of the glucocorticoid response (standardized within species) varied independently of absolute scope, suggesting that selection could operate on both features independently. Species with faster relative glucocorticoid responses lived in locations with more variable temperature and had shorter lifespans. Our results suggest that rapid changes associated with the speed of the glucocorticoid response, such as those occurring through non-genomic receptors, might be an important determinant of coping ability and we emphasize the need for studies designed to measure speed independently of absolute glucocorticoid levels. A MALDI-TOF assay identifies nilotinib as an inhibitor of inflammation in acute myeloid leukaemia Inflammatory responses are important in cancer, particularly in the context of monocyte-rich aggressive myeloid neoplasm. We developed a label-free cellular phenotypic drug discovery assay to identify anti-inflammatory drugs in human monocytes derived from acute myeloid leukaemia (AML), by tracking several biological features ionizing from only 2,500 cells using matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry. A proof-of-concept screen showed that the BCR-ABL inhibitor nilotinib, but not the structurally similar imatinib, blocks inflammatory responses. In order to identify the cellular (off-)targets of nilotinib, we performed thermal proteome profiling (TPP). Unlike imatinib, nilotinib and other later generation BCR-ABL inhibitors inhibit the p38-MK2/3 signalling axis which suppressed the expression of inflammatory cytokines, cell adhesion and innate immunity markers in activated human monocytes derived from AML. Thus, our study provides a tool for the discovery of new anti-inflammatory drugs, which could contribute to the treatment of inflammation in myeloid neoplasms and other diseases.

Key PointsLabel-free cell-based assay identifies new anti-inflammatory drugs using MALDI-TOF MS. Nilotinib reduces inflammation by inhibition of MAPK14-MK2/3 signalling axis in AML. TSC22D4 interacts with Akt1 in response to metabolic and stress signals Transforming Growth Factor {beta} 1 Stimulated Clone 22 D4 (TSC22D4) is an intrinsically disordered protein that regulates cellular and physiological processes such as cell proliferation, cellular senescence as well as hepatic glucose and lipid metabolism. The molecular mechanism of TSC22D4 action in these cellular and metabolic functions, however, remains largely elusive. Here, we identified TSC22D4 as a novel protein kinase B/Akt1 interacting protein, a critical mediator of insulin/PI3K signaling pathway implicated in diverse set of diseases including type 2 diabetes, obesity and cancer. TSC22D4 interacts with Akt1 not constitutively but rather in a regulatory manner. While glucose and insulin stimulation of cells or refeeding of mice impair the hepatic TSC22D4-Akt1 interaction, inhibition of mitochondria and oxidative stress, promote it; indicating that extra- and intra-cellular cues play a key role in controlling TSC22D4-Akt1 interaction. Our results also demonstrate that together with its dimerization domain, i.e. the TSC box, TSC22D4 requires its intrinsically disordered region (D2 domain) to interact with Akt1. To understand regulation of TSC22D4 function further, we employed tandem mass spectrometry and identified 15 novel phosphorylation sites on TSC22D4. Similar to TSC22D4-Akt1 interaction, TSC22D4 phosphorylation also responds to environmental signals such as starvation, mitochondrial inhibition and oxidative stress. Interestingly, 6 out of the 15 novel phosphorylation sites lie within the TSC22D4 D2 domain, which is required for TSC22D4-Akt1 interaction. Characterization of the regulation and function of these novel phosphorylation sites, in the future, will shed light on our understanding of the role of TSC22D4-Akt1 interaction in both cell biological and physiological functions. Overall, our findings postulate a model whereby TSC22D4 acts as an environmental sensor and interacts with Akt1 to regulate cell proliferation, cellular senescence as well as maintain metabolic homeostasis. PlotMI: interpretation of pairwise dependencies and positional preferences learned by deep learning models from sequence data Deep learning models have recently gained success in various tasks related to understanding information coded in biological sequences. Although offering state-of-the art predictive performance, the predictions made by deep learning models can be difficult to understand. In virtually all biological research, the understanding of how a predictive model works is as, or even more important as the raw predictive performance. Thus interpretation of deep learning models is an emerging hot topic especially in context of biological research. Here we describe PlotMI, a mutual information based model interpretation tool that can intuitively visualize positional preferences and pairwise dependencies learned by any machine learning model trained on sequence data such as DNA, RNA or amino acid sequence. PlotMI can also be used to compare dependencies present in training data to the dependencies learned by the model and to compare dependencies learned by different types of models that are trained to perform the same task. PlotMI is freely available at https://github.com/hartonen/plotMI. Parallel introgression, not recurrent emergence, explains apparent elevational ecotypes of polyploid Himalayan snowtrout The recurrence of similar evolutionary patterns within different habitats often reflects parallel selective pressures acting upon either standing or independently occurring genetic variation to produce a convergence of phenotypes. This interpretation (i.e. parallel divergences within adjacent streams) has been hypothesized for drainage-specific morphological  ecotypes observed in polyploid snowtrout (Cyprinidae: Schizothorax). However, parallel patterns of differential introgression during secondary contact is a viable alternative hypothesis. Here, we utilized ddRADseq (N=35,319 de-novo and N=10,884 transcriptome-aligned SNPs), as derived from Nepali/Bhutanese samples (N=48 each), to test these competing hypotheses. We first employed genome-wide allelic depths to derive appropriate ploidy models, then a Bayesian approach to yield genotypes statistically consistent under the inferred expectations. Elevational  ecotypes were consistent in geometric-morphometric space, but with phylogenetic relationships at the drainage-level, sustaining an hypothesis of independent emergence. However, partitioned analyses of phylogeny and admixture identified subsets of loci under selection that retained genealogical concordance with morphology, suggesting instead that apparent patterns of morphological/phylogenetic discordance are driven by widespread genomic homogenization. Here, admixture occurring in secondary contact effectively  masks previous isolation. Our results underscore two salient factors:1) Morphological adaptations are retained despite hybridization; and 2) The degree of admixture varies across tributaries, presumably concomitant with underlying environmental or anthropogenic factors. Synthetic periphyton as a model system to understand species dynamics in complex microbial freshwater communities Phototrophic biofilms, also known as periphyton, are microbial freshwater communities that drive crucial ecological processes in streams and lakes. Gaining a deep mechanistic understanding of the biological processes occurring in natural periphyton remains challenging due to the high complexity and variability of such communities. To address this challenge, we rationally developed a workflow to construct a synthetic community by co-culturing 26 phototrophic species (i.e., diatoms, green algae and cyanobacteria) that were inoculated in a successional sequence to create a periphytic biofilm on glass slides. We show that this community is diverse, stable and highly reproducible in terms of microbial composition, function and 3D spatial structure of the biofilm. We also demonstrate the ability to monitor microbial dynamics at the single species level during periphyton development and how their abundances are impacted by stressors such as increased temperature and a herbicide, singly and in combination. Overall, such a synthetic periphyton, grown under controlled conditions, can be used as a model system for theory testing through targeted manipulation. Where there's smoke, there's fuel: dynamic vegetation data improve predictions of wildfire hazard in the Great Basin Wildfires are a growing management concern in western US rangelands, where invasive annual grasses have altered fire regimes and contributed to an increased incidence of catastrophic large wildfires. Fire activity in arid, non-forested ecosystems is thought to be largely controlled by interannual variation in fuel amount, which in turn is controlled by antecedent weather. Thus, long-range forecasting of fire activity in rangelands should be feasible given annual estimates of fuel quantity. Using a 32 yr time series of spatial data, we employed machine learning algorithms to predict the relative probability of large (>405 ha) wildfire in the Great Basin based on fine-scale annual and 16-day estimates of cover and production of vegetation functional groups, weather, and multitemporal scale drought indices. We evaluated the predictive utility of these models with a leave-one-year-out cross-validation, building spatial hindcasts of fire probability for each year that we compared against actual footprints of large wildfires. Herbaceous aboveground biomass production, bare ground cover, and long-term drought indices were the most important predictors of burning. Across 32 fire seasons, 88% of the area burned in large wildfires coincided with the upper 3 deciles of predicted fire probabilities. At the scale of the Great Basin, several metrics of fire activity were moderately to strongly correlated with average fire probability, including total area burned in large wildfires, number of large wildfires, and maximum fire size. Our findings show that recent years of exceptional fire activity in the Great Basin were predictable based on antecedent weather-driven growth of fine fuels and reveal a significant increasing trend in fire probability over the last three decades driven by widespread changes in fine fuel characteristics. VIP plasma levels associate with survival in severe COVID-19 patients, correlating with protective effects in SARS-CoV-2-infected cells. Infection by SARS-CoV-2 may elicit uncontrolled and damaging inflammatory responses. Thus, it is critical to identify compounds able to inhibit virus replication and thwart the inflammatory reaction. Here, we show that the plasma levels of the immunoregulatory neuropeptide VIP are elevated in patients with severe COVID-19, correlating with reduced inflammatory mediators and with survival on those patients. In vitro, VIP and PACAP, highly similar neuropeptides, decreased the SARS-CoV-2 genome replication in human monocytes and viral production in lung epithelial cells, also reducing cell death. Both neuropeptides inhibited the production of proinflammatory mediators in lung epithelial cells and in monocytes. VIP and PACAP prevented in monocytes the SARS-CoV-2-induced activation of NF-kB and SREBP1 and SREBP2, transcriptions factors involved in proinflammatory reactions and lipid metabolism, respectively. They also promoted CREB activation, a transcription factor with antiapoptotic activity and negative regulator of NF-kB. Specific inhibition of NF-kB and SREBP1/2 reproduced the anti-inflammatory, antiviral and cell death protection effects of VIP and PACAP. Our results support further clinical investigations of these neuropeptides against COVID-19. Remarked Suppression of Aβ42 Protomer-protomer Dissociation Reaction via Pentamer Dimerization Multimeric protein complexes are molecular apparatuses to regulate biological systems and often determine their fate. Among proteins forming such molecular assemblies, amyloid proteins have drawn attention over a half-century since amyloid fibril formation of these proteins is supposed to be a common pathogenic cause for neurodegenerative diseases. This process is triggered by the accumulation of fibril-like aggregates, while the microscopic mechanisms are mostly elusive due to technical limitation of experimental methodologies in individually observing each of diverse aggregate species in the aqueous solution. We then addressed this problem by employing atomistic molecular dynamics simulations for the paradigmatic amyloid protein, amyloid-{beta} (1-42) (A{beta}42). Seven different dimeric forms of oligomeric A{beta}42 fibril-like aggregate in aqueous solution, ranging from tetramer to decamer, were considered. We found additive effects of the size of these fibril-like aggregates on their thermodynamic stability and have clarified kinetic suppression of protomer-protomer dissociation reactions at and beyond the point of pentamer dimer formation. This observation was obtained from the specific combination of the A{beta}42 protomer structure and the physicochemical condition that we here examined, while it is worthwhile to recall that several amyloid fibrils take dimeric forms of their protomers. We could thus conclude that the stable formation of fibril-like protomer dimer should be involved in a turning point where rapid growth of amyloid fibrils is triggered. Stepwise progression of beta-selection during T cell development as revealed by histone deacetylation inhibition During T cell development, the first step in creating a unique T Cell Receptor (TCR) is the genetic recombination of the TCR{beta} chain. The quality of the newly recombined TCR{beta} is assessed at the {beta}-selection checkpoint. Most cells fail this checkpoint and die, but the coordination of the complex events that control fate at the {beta}-selection checkpoint is not yet understood. We shed new light on fate determination during {beta}-selection using a selective inhibitor of histone deacetylase 6, ACY1215. ACY1215 disrupted the {beta}-selection checkpoint. Characterising the basis for this disruption revealed a new, pivotal stage in {beta}-selection, bookended by upregulation of the TCR co-receptors, CD28 and CD2 respectively. Within this  DN3bPre stage, CD5 and Lef1 are upregulated to reflect pre-TCR signalling and their expression correlates with proliferation. During this phase, ACY1215-mediated disruption of the organisation of the {beta}-selection immunological synapse is associated with a breakdown in connectivity of expression of pre-TCR, CD5 and Lef1. Subsequent deregulation of pre-TCR-induced proliferation leads to bypass of the {beta}-selection checkpoint and subsequent failure to progress. We propose that the progressive expression of CD28, CD5 and Lef1, then CD2 reports and modulates the pre-TCR signal to orchestrate passage through the {beta}-selection checkpoint. These findings suggest a refined model of {beta}-selection in which a coordinated increase in expression of pre-TCR, CD28, CD5 and Lef1 provides for escalating TCR signalling strength, and culminates in the expression of CD2 to enable exit from the {beta}-selection checkpoint.