title: Alpha-Frag: a deep neural network for fragment presence prediction improves peptide identification by data independent acquisition mass spectrometry

abstract:
Identification of peptides in mass spectrometry-based proteomics typically relies on spectra matches. As MS/MS spectra record presence and intensity of fragment ions, the match should take both fragment presence similarity and intensity similarity into consideration. Fragment presence similarity can be calculated with the help of fragment presence prediction such as theoretical enumeration of all possible fragment ions or selecting non-zero intensity ions from the result of fragment intensity prediction, but neither of these two methods is accurate enough. In this work, we developed a deep neural network based model, Alpha-Frag, to predict precisely the fragment ions that should be present for a given peptide. Alpha-Frag modelled fragment presence prediction as a multi-label classification task and trained with ProteomeTools dataset. In terms of intersection over union (IoU), Alpha-Frag achieved an average of >0.7 and outperformed the benchmarks across the validation datasets. Furthermore, fragment presence similarity was calculated based on presence prediction and incorporated into the peptide statistical validation tools as an additional score to improve peptide identifications. Our preliminary experiments show that this score led to a maximum increase of 26.8% (FDR 0.1%) and 21.6% (FDR 1%) for the DDA and the DIA identification, respectively.

Significance StatementA better prediction of fragmentation for peptides in mass spectrometry (MS) is beneficial to the peptide identification. As the MS/MS spectra record two-dimensional information of fragment ions derived from precursors, mass-to-charge ratio (m/z) and their corresponding intensities, besides the fragment intensity prediction, it is necessary to study the presence prediction. Although the presence prediction can be realized by enumerating all the possible fragmentation patterns of a peptide with equal probability or by selecting non-zero intensity fragment ions from the result of fragment intensity prediction, neither of these two methods is accurate enough. In this study, deep learning is leveraged to precisely predict the fragment ions of a given peptide. Based on the fragment presence prediction, fragment presence similarity between experimental spectra and predicted spectra can be calculated which is proved to promote the peptide detections both for DDA and for DIA data.

category: bioinformatics


title: Alpha-Frag: a deep neural network for fragment presence prediction improves peptide identification


title: bayesynergy: flexible Bayesian modelling of synergistic interaction effects in in-vitro drug combination experiments

abstract: The effect of cancer therapies is often tested pre-clinically via in-vitro experiments, where the post-treatment viability of the cancer cell population is measured through assays estimating the number of viable cells. In this way, large libraries of compounds can be tested, comparing the efficacy of each treatment. Drug interaction studies focus on the quantification of the additional effect encountered when two drugs are combined, as opposed to using the treatments separately. In the bayesynergy R package, we implement a probabilistic approach for the description of the drug combination experiment, where the observed dose response curve is modelled as a sum of the expected response under a zero-interaction model and an additional interaction effect (synergistic or antagonistic). The interaction is modelled in a flexible manner, using a Gaussian process formulation. Since the proposed approach is based on a statistical model, it allows the natural inclusion of replicates, handles missing data and uneven concentration grids, and provides uncertainty quantification around the results. The model is implemented in the Stan programming language providing a computationally efficient sampler, a fast approximation of the posterior through variational inference, and features parallel processing for working with large drug combination screens.


title: Discovery and characterization of Hv1-type proton channels in reef-building corals.

abstract: Voltage-dependent proton-permeable channels are membrane proteins mediating a number of important physiological functions. Here we report the presence of a gene encoding for Hv1 voltage-dependent, proton-permeable channels in two species of reef-building corals. We performed a characterization of their biophysical properties and found that these channels are fast-activating and modulated by the pH gradient in a distinct manner. The biophysical properties of these novel channels make them interesting model systems. We have also developed an allosteric gating model that provides mechanistic insight into the modulation of voltage-dependence by protons. This work also represents the first functional characterization of any ion channel in scleractinian corals. We discuss the implications of the presence of these channels in the membranes of coral cells in the calcification and pH regulation processes and possible consequences of ocean acidification related to the function of these channels.

category: biophysics


title: Maternal age affects equine Day 8 embryo gene expression both in trophoblast and inner cell mass

abstract:
BackgroundBreeding a mare until she is not fertile or even until her death is common in equine industry but the fertility decreases as the mare age increases. Embryo loss due to reduced embryo quality is partly accountable for this observation. Here, the effect of mares age on blastocysts gene expression was explored. Day 8 post-ovulation embryos were collected from multiparous young (YM, 6-year-old, N = 5) and older (OM, > 10-year-old, N = 6) non-nursing Saddlebred mares, inseminated with the semen of one stallion. Pure or inner cell mass (ICM) enriched trophoblast, obtained by embryo bisection, were RNA sequenced. Deconvolution algorithm was used to discriminate gene expression in the ICM from that in the trophoblast. Differential expression was analyzed with embryo sex and diameter as cofactors. Functional annotation and classification of differentially expressed genes and gene set enrichment analysis were also performed.

ResultsMaternal aging did not affect embryo recovery rate, embryo diameter nor total RNA quantity. In both compartments, the expression of genes involved in mitochondria and protein metabolism were disturbed by maternal age, although more genes were affected in the ICM. Mitosis, signaling and adhesion pathways and embryo development were decreased in the ICM of embryos from old mares. In trophoblast, ion movement pathways were affected.

ConclusionsThis is the first study showing that maternal age affects gene expression in the equine blastocyst, demonstrating significant effects as early as 10 years of age. These perturbations may affect further embryo development and contribute to decreased fertility due to aging.

category: physiology


title: Field microenvironments regulate crop diel transcript and metabolite rhythms

abstract:
O_LIMost research in plant chronobiology was done in laboratory conditions. However, they usually fail to mimic natural conditions and their slight fluctuations, highlighting or obfuscating rhythmicity. High-density crops, such as sugarcane (Saccharum hybrid), generate field microenvironments with specific light and temperature due to mutual shading.
C_LIO_LIWe measured the metabolic and transcriptional rhythms in the leaves of 4-month-old (4 mo) and 9 mo sugarcane grown in the field. Most of the assayed rhythms in 9 mo sugarcane peaked >1 h later than in 4 mo sugarcane, including rhythms of the circadian clock gene, LATE ELONGATED HYPOCOTYL (LHY).
C_LIO_LIWe hypothesized that older sugarcane perceives dawn later than younger sugarcane due to self-shading. As a test, we measured LHY rhythms in plants on the east and the west side of a field. We also tested if a wooden wall built between lines of sugarcane changed their rhythms. The LHY peak was delayed in the plants in the west of the field or beyond the wall; both shaded at dawn.
C_LIO_LIWe conclude that plants in the same field may have different phases due to field microenvironments, impacting important agronomical traits, such as flowering time, stalk weight and number.
C_LI

category: plant biology


title: The ORGAN SIZE (ORG) locus contributes to isometric gigantism in domesticated tomato

abstract:
Gigantism is a key component of the domestication syndrome, a suite of traits that differentiates crops from their wild relatives. Allometric gigantism is strongly marked in horticultural crops, causing disproportionate increases in the size of edible parts such as stems, leaves or fruits. Tomato (Solanum lycopersicum) has attracted attention as a model for fruit gigantism, and many genes have been described controlling this trait. However, the genetic basis of a corresponding increase in size of vegetative organs contributing to isometric gigantism, has remained relatively unexplored. Here, we identified a 0.4 Mbp region on chromosome 7 in introgression lines (ILs) from the wild species Solanum pennellii in two different tomato genetic backgrounds (cv. M82 and cv. Micro-Tom) that controls vegetative and reproductive organ size in tomato. The locus, named ORGAN SIZE (ORG), was fine-mapped using genotype-by-sequencing. A survey of literature revealed that ORG overlaps with previously mapped QTLs controlling tomato fruit weight during domestication. Alleles from the wild species led to reduced cell number in different organs, which was partially compensated by greater cell expansion in leaves but not in fruits. The result was a proportional reduction in leaf, flower and fruit size in the ILs harbouring the wild alleles. These findings suggest that selection for large fruit during domestication also tends to select for increases in leaf size by influencing cell division. Since leaf size is relevant for both source-sink balance and crop adaptation to different environments, the discovery of ORG could allow fine-tuning of these parameters.

One sentence summaryA locus that controls isometric size increase in vegetative and reproductive organs of tomato through changes in cell division


title: Drought resilience of long term dry-farmed grapevines ('Vitis vinifera' L.)

abstract: We explored the long-term drought resilience of field-grown unirrigated (or dry-grown) grapevines of pre-clonal origin from shallow (SR) and deep (DR) soils representing low and high soil water availability, respectively, in a warm, Mediterranean climate. Despite lower soil moisture available to SR vines, both deep and shallow-rooted vines had similar vine water status, based on measurements of midday stem water potential ({Psi}s), and leaf net photosynthesis (An). Due to the lower stomatal conductance (gs), SR had higher intrinsic water use efficiency (WUEi) than DR, however the carbon isotope ratio ({delta}13C) of the fruit at harvest was similar between the two groups. Our observations suggest a degree of drought adaptation in the SR vines resulting from multi-decadal cyclical droughts. Overall, we demonstrate that pre-clonal Cabernet Sauvignon grapevines dry-grown in shallow soils have an enhanced resilience to drought compared to dry-grown vines in deep soils. This study has implications for selection of crop genetic material in a changing climate.


title: Class II LBD genes ZmLBD5 and ZmLBD33 regulate gibberellin and abscisic acid biosynthesis

abstract: Lateral organ boundaries domain (LBD) proteins are plant-specific transcription factors. Class I LBD members are widely reported to be pivotal for organ development, however, the role of class II members is unknown in cereal crops. Class II LBD proteins are distinguished from class I by the lack of a Gly-Ala-Ser (GAS) peptide and leucine-zipper-like coiled-coil domain, which is thought to be essential for protein dimerization. In this study, ZmLBD5 and ZmLBD33 form homo- and hetero-dimers, like class I members. At seedling stage, ZmLBD5 promoted biomass accumulation (shoot dry weight and root dry weight), root development (root length, root number, and root volume), and organ expansion (leaf area), while ZmLBD33 repressed these processes and display a dwarf phenotype. Both ZmLBD5 and ZmLBD33 displayed negative roles in drought tolerance mainly by increasing stomatal density and stomatal aperture. RNA sequencing, gene ontology enrichment analysis, and transient luciferase expression assays indicated that ZmLBD5 and ZmLBD33 are mainly involved in the regulation of the TPS-KS-GA2ox gene module, which comprises key enzymatic genes upstream of GA and ABA biosynthesis. GA1 content increased in ZmLBD5-overexpressing seedlings, while GA3 and abscisic acid content decreased in both transgenic seedlings. Consequently, exogenous GA1 or GA3 undoubtedly rescued the dwarf phenotype of ZmLBD33-overexpressing plants, with GA1 performing better. The study of ZmLBD5 and ZmLBD33 sheds light on the function of the class II LBD gene family in maize.


title: Developing a Petri dish test to detect resistance to key herbicides in Lolium rigidum

abstract: Overreliance on herbicides for weed control is conducive to the evolution of herbicide resistance. Annual ryegrass (Lolium rigidum Gaud.) is a species that is prone to evolve resistance to a wide range of herbicide modes of action. Rapid detection of herbicide-resistant weed populations in the field can aid farmers to optimize the use of herbicides for their control. The feasibility of a portable agar-based test to rapidly and reliably detect annual ryegrass resistance to key herbicides such as clethodim, glyphosate, pyroxasulfone and trifluralin on-farm was investigated. The three research phases of this study show that: a) easy-to-interpret results are obtained with non-dormant seed from well-characterised susceptible and resistant populations, and resistance is detected as effectively as with traditional dose-response pot-based resistance assays. However, the test may not be suitable for portable use on-farm because of b) the low stability of some herbicides such as trifluralin and clethodim in agar and c) the tendency of seed dormancy in freshly-harvested seeds to confound the results. The agar-based test is best used as a research tool as a complement to confirm results obtained in traditional pot-based resistance screenings. Comprehensive agar test and / or whole-plant resistance tests by herbicide application at the recommended label rate (whole plants grown in pots) are the current benchmark for proactive in- and off-season resistance testing and should be promoted more widely to allow early detection of resistance, optimization of herbicide technology use and deploy appropriate weed management interventions.


title: ShapoGraphy: a glyph-oriented visualisation approach for creating pictorial representations of bioimaging data

abstract: Intuitive visualisation of quantitative microscopy data is crucial for interpreting and discovering new patterns in complex bioimage data. Existing visualisation approaches, such as bar charts, scatter plots and heat maps, do not accommodate the complexity of visual information present in microscopy data. Here we develop ShapoGraphy, a first of its kind method accompanied by a user-friendly web-based application for creating interactive quantitative pictorial representations of phenotypic data and facilitating the understanding and analysis of image datasets (www.shapography.com). ShapoGraphy enables the user to create a structure of interest as a set of shapes. Each shape can encode different variables that are mapped to the shape dimensions, colours, symbols, and stroke features. We illustrate the utility of ShapoGraphy using various image data, including high dimensional multiplexed data. Our results show that ShapoGraphy allows a better understanding of cellular phenotypes and relationships between variables. In conclusion, ShopoGraphy supports scientific discovery and communication by providing a wide range of users with a rich vocabulary to create engaging and intuitive representations of diverse data types.

category: systems biology


title: Machine Learning Identifies Ponatinib as a Potent Inhibitor of SARS-CoV2-induced Cytokine Storm

abstract: Although 15-20% of COVID-19 patients experience hyper-inflammation induced by massive cytokine production, cellular triggers of this process and strategies to target them remain poorly understood. Here, we show that the N-terminal domain (NTD) of the spike protein from the SARS-CoV-2 and emerging variants B1.1.7 and B.1.351 substantially induces multiple inflammatory molecules in human monocytes and PBMCs. Further, we identified several protein kinases, including JAK1, EPHA7, IRAK1, MAPK12, and MAP3K8, as essential downstream mediators of NTD-induced cytokine release. Additionally, we found that the FDA-approved, multi-kinase inhibitor Ponatinib is a potent inhibitor of the NTD-mediated cytokine storm. Taken together, we propose that agents targeting multiple kinases required for the SARS-CoV-2-mediated cytokine storm, such as Ponatinib, may represent an attractive therapeutic option for treating moderate to severe COVID-19.


title: Immunoprofiling of HTLV-1-infected individuals shows altered innate cell responsiveness in HAM/TSP patients.

abstract: The Human T-cell Leukemia Virus-1 (HTLV-1)-Associated Myelopathy/Tropical Spastic Paraparesis (HAM/TSP) is a devastating neurodegenerative disease with no effective treatment, which affects an increasing number of people in Brazil. A biological blood factor allowing the prediction of the disease occurrence is so far not available. In this study, we analyzed innate immunity responses at steady state and after blood cell stimulation using an agonist of the toll-like receptor (TLR)7/8-signaling pathway in blood samples from HTLV-1-infected volunteers, including asymptomatic carriers and HAM/TSP patients. We observed a lower responsiveness in dendritic cells to produce IFN. Moreover, we found higher production of IL-12 and Mip-1 by monocytes together with higher levels of IFN{gamma} produced by Natural Killer cells. These deregulations could represent a signature for progression towards HAM/TSP.

category: immunology


title: Invasive grass litter suppresses native species and promotes disease

abstract: Plant litter can alter ecosystems and promote plant invasions by changing resource acquisition, depositing toxins, and transmitting microorganisms to living plants. Transmission of microorganisms from invasive litter to live plants may gain importance as invasive plants accumulate pathogens over time since introduction. It is unclear, however, if invasive plant litter affects native plant communities by promoting disease. Microstegium vimineum is an invasive grass that suppresses native populations, in part through litter production, and has accumulated leaf spot diseases since its introduction to the U.S. In a greenhouse experiment, we evaluated how M. vimineum litter and accumulated pathogens mediated resource competition with the native grass Elymus virginicus. Resource competition reduced biomass of both species and live M. vimineum increased disease incidence on the native species. Microstegium vimineum litter also promoted disease on the native species, suppressed establishment of both species, and reduced biomass of M. vimineum. Nonetheless, interference competition from litter had a stronger negative effect on the native species, increasing the relative abundance of M. vimineum. Altogether, invasive grass litter suppressed both species, ultimately favoring the invasive species in competition, and increased disease incidence on the native species.

category: ecology


title: Evolution of quantitative trait locus hotspots in yeast species

abstract: Dissecting the genetic basis of complex trait remains a real challenge. The budding yeast Saccharomyces cerevisiae has become a model organism for studying quantitative traits, successfully increasing our knowledge in many aspects. However, the exploration of the genotype-phenotype relationship in non-model yeast species could provide a deeper insight into the genetic basis of complex traits. Here, we have studied this relationship in the Lachancea waltii species which diverged from the S. cerevisiae lineage prior to the whole-genome duplication. By performing linkage mapping analyses in this species, we identified 86 quantitative trait loci (QTL) affecting growth fitness in a large number of conditions. The distribution of these loci across the genome has revealed two major QTL hotspots. A first hotspot corresponds to a general fitness QTL, impacting a wide range of conditions. By contrast, the second hotspot highlighted a fitness trade-off with a disadvantageous allele for drug-free conditions which proved to be advantageous in the presence of several drugs. Finally, the comparison of the detected QTL in L. waltii with those which had been previously identified for the same traits in a closely related species, Lachancea kluyveri, clearly revealed the absence of interspecific conservation of these loci. Altogether, our results expand our knowledge on the variation of the QTL landscape across different yeast species.

category: genetics


title: The quantitative genetics of the endemic prevalence of infectious diseases: Indirect Genetic Effects dominate heritable variation and response to selection

abstract:
Infectious diseases have profound effects on life, both in nature and agriculture. Despite the availability of well-established epidemiological theory, however, a quantitative genetic theory of the host population for the endemic prevalence of infectious diseases is almost entirely lacking. While several studies have demonstrated the relevance of the transmission dynamics of infectious diseases for heritable variation and response to selection of the host population, our current theoretical framework of quantitative genetics excludes these dynamics. As a consequence, we do not know which genetic effects of the host population determine the prevalence of an infection, and have no concepts of breeding value and heritable variation for endemic prevalence.

Here we integrate quantitative genetics and epidemiology, and propose a quantitative genetic theory for R0 and for the endemic prevalence of an infectious disease. We first identify the genetic factors that determine the prevalence of an infection, using an approach founded in epidemiological theory. Subsequently we investigate the population level consequences of individual genetic variation, both for R0 and for the endemic prevalence. Next, we present expressions for the breeding value and heritable variation, for both prevalence and individual binary disease status, and show that these parameters depend strongly on the level of the prevalence. Results show that heritable variation for endemic prevalence is substantially greater than currently believed, and increases when prevalence approaches zero, while heritability of individual disease status goes to zero. As a consequence, response of prevalence to selection accelerates considerably when prevalence goes down, in contrast to predictions from classical theory. Finally, we show that most of the heritable variation for the endemic prevalence of an infection is hidden due to indirect genetic effects, suggesting a key role for kin-group selection both in the evolutionary history of current populations and for genetic improvement strategies in animals and plants.


title: The quantitative genetics of the prevalence of infectious diseases: hidden genetic variation due to Indirect Genetic Effects dominates heritable variation and response to selection


title: Calibration-free 3D reconstruction of firefly trajectories from 360-degree cameras

abstract: Over the past few decades, progress in animal tracking techniques, from large migrating mammals to swarming insects, has facilitated significant advances in ecology, behavioural biology, and conservation science. Recently, we developed a technique to record and track flashing fireflies in their natural habitat using pairs of 360-degree cameras. The method, which has the potential to help identify and monitor firefly populations worldwide, was successfully implemented in various natural swarms. However, camera calibration remained tedious and time-consuming. Here, we propose and implement an algorithm that calibrates the cameras directly from the data, requiring minimal user input. We explain the principles of the calibration-free algorithm, and demonstrate the ease and efficiency of its implementation. This method is relatively inexpensive, versatile, and well-suited for automatic processing and the collection of a large dataset of firefly trajectories across species and populations. This calibration-free method paves the way to citizen science efforts for monitoring and conservation of firefly populations.

category: animal behavior and cognition


title: State-dependent egocentric and allocentric heading representation in the monarch butterfly brain

abstract: For navigation, animals use a robust internal compass. Compass navigation is especially crucial for long-distance migrating animals like monarch butterflies, which use a sun compass to navigate every fall over 4,000 km to their overwintering sites. The central complex, a brain region equipped with sun-compass neurons, is proposed to control the butterflys heading. Although the activity of central-complex neurons exhibits a locomotor-dependent modulation in many insects, the consequences of such modulations for the coding of heading remain unexplored. Here, we developed tetrode recordings from tethered flying monarch butterflies to reveal how flight modulates heading representation. We found that during flight, heading-direction neurons change their tuning, transforming the central-complex network to function as a global compass. This compass coding is characterized by the dominance of steering feedback and allows for robust heading representation even under unreliable visual scenarios, an ideal strategy for maintaining a migratory heading over enormous distances.

category: neuroscience


title: Flight-induced compass representation in the monarch butterfly heading network


title: Novel pre-clinical model for CDKL5 Deficiency Disorder

abstract: Cyclin-dependent kinase-like-5 (CDKL5) Deficiency Disorder (CDD) is a severe X-linked neurodegenerative disease characterized by early-onset epileptic seizures, low muscle tone, progressive intellectual disability, severe motor function and visual impairment. CDD affects approximately 1 in 60,000 live births with many patients dying by early adulthood. For many patients, quality of life is significantly reduced due to the severity of their neurological symptoms and functional impairment. There are no effective therapies for CDD with current treatments focusing on improving symptoms rather than addressing the underlying causes of the disorder. Zebrafish offer a number of unique advantages for high-throughput pre-clinical evaluation of potential therapies for human neurological diseases including CDD. In particular, the large number of zebrafish that can be produced, together with the possibilities for in vivo imaging and genetic manipulation, allows for the detailed assessment of disease pathogenesis and therapeutic discovery. We have characterised a loss of function zebrafish model for CDD, containing a nonsense mutation in cdkl5. cdkl5 mutant zebrafish display defects in neuronal patterning, microcephaly, and reduced muscle function caused by impaired muscle innervation. This study provides a powerful vertebrate model to investigate CDD disease pathophysiology and allow high-throughput screening for effective therapies.


title: An open source statistical and data processing toolbox for wide-field optical imaging in mice

abstract: Wide-field optical imaging (WOI) produces concurrent hemodynamic and cell-specific calcium recordings across the entire cerebral cortex. There have been multiple studies using WOI to image mouse models with various environmental or genetic manipulations to understand various diseases. Despite the obvious utility of pursuing mouse WOI alongside human functional magnetic resonance imaging (fMRI), and the multitude of analysis toolboxes in the fMRI literature, there is not an available open-source, user-friendly data processing and statistical analysis toolbox for WOI data. Here, we present our MATLAB toolbox for pre-processing WOI data, as described and adapted to combine processing techniques from multiple WOI groups. Additionally, we provide multiple data analysis packages and translate two commonly used statistical approaches from the fMRI literature to the WOI data. To illustrate the utility, we demonstrate the ability of the processing and analysis framework to detect a well-established deficit in a mouse model of stroke. Additionally, we evaluate resting state data in healthy mice.


title: Sex dependent glial-specific changes in the chromatin accessibility landscape in late-onset Alzheimer's disease brains

abstract:
In the post-GWAS era, there is an unmet need to decode the underpinning genetic etiologies of late-onset Alzheimers disease (LOAD) and translate the associations to causation. Toward that goal, we conducted ATAC-seq profiling using neuronal nuclear protein (NeuN) sorted-nuclei from 40 frozen brain tissues to determine LOAD-specific changes in chromatin accessibility landscape in a cell-type specific manner. We identified 211 LOAD-specific differential chromatin accessibility sites in neuronal-nuclei, four of which overlapped with LOAD-GWAS regions ({+/-}100kb of SNP). While the non-neuronal nuclei did not show LOAD-specific differences, stratification by sex identified 842 LOAD-specific chromatin accessibility sites in females. Seven of these sex-dependent sites in the non-neuronal samples overlapped LOAD-GWAS regions including APOE. LOAD loci were functionally validated using single-nuclei RNA-seq datasets. In conclusion, using brain sorted-nuclei enabled the identification of sex-dependent cell type-specific LOAD alterations in chromatin structure. These findings enhance the interpretation of LOAD-GWAS discoveries, provide potential pathomechanisms, and suggest novel LOAD-loci. Furthermore, our results convey mechanistic insights into sex differences in LOAD risk and clinicopathology.

GRAPHICAL ABSTRACT O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY


title: Radio-pathomic maps of cell density identify glioma invasion beyond traditional MR imaging defined margins

abstract: Current MRI signatures of brain cancer often fail to identify regions of hypercellularity beyond the contrast enhancing region. Therefore, this study used autopsy tissue samples aligned to clinical MRIs in order to quantify the relationship between intensity values and cellularity, as well as to develop a radio-pathomic model to predict cellularity using MRI data. This study used 93 samples collected at autopsy from 44 brain cancer patients. Tissue samples were processed, stained for hematoxylin and eosin (HE) and digitized for nuclei segmentation and cell density calculation. Pre- and post-gadolinium contrast T1-weighted images (T1, T1C), T2 fluid-attenuated inversion recovery (FLAIR) images, and apparent diffusion coefficient (ADC) images calculated from diffusion imaging were collected from each patients final acquisition prior to death. In-house software was used to align tissue samples to the FLAIR image via manually defined control points. Mixed effect models were used to assess the relationship between single image intensity and cellularity for each image. An ensemble learner was trained to predict cellularity using 5 by 5 voxel tiles from each image, employing a 2/3-1/3 train-test split for validation. Single image analyses found subtle associations between image intensity and cellularity, with a less pronounced relationship within GBM patients. The radio-pathomic model was able to accurately predict cellularity in the test set (RMSE = 1015 cells/mm2) and identified regions of hypercellularity beyond the contrast enhancing region. We concluded that a radio-pathomic model for cellularity is able to identify regions of hypercellular tumor beyond traditional imaging signatures.


title: Characterization of IL-22BP expression during Crohn's disease shows lack of evidence for IL-22BP production by T cells

abstract:
Background & aimsIL-22 binding protein (IL-22BP) is a soluble and specific inhibitor of IL-22, a cytokine with known protective actions on intestinal epithelial cells during inflammation. Although eosinophils and mononuclear phagocytes (MNP) were shown to be the producers of IL-22BP in the intestine lamina propria (LP), it has recently been proposed that CD4+ T cells represent an additional source of IL-22BP in the gut during Crohns disease (CD). In this study we sought to confirm these findings and to assess IL-22BP secretion levels.

MethodsWe investigated IL-22BP cellular sources in CD gut samples using qPCR and ELISA on FACS-sorted LP and mesenteric lymph nodes (MLN) cell subsets. We also evaluated IL-22BP levels in ex-vivo culture of intestinal biopsies.

ResultsMNP (HLA DR+ CD11c+ cells) and eosinophils isolated from LP CD tissues expressed IL22RA2, while the expression measured in the CD4+ and CD8+ T cells fractions was undetectable or 100-1000 times lower than in MNP. In MLN, IL22RA2 expression in T cells was either undetectable of 1000-fold lower than in MNPs without differences between naive and non-naive subsets. IL22RA2 expression was undetectable after ex vivo activation of both CD4+ and CD8+ T cells from LP or MLNs and IL-22BP was not detected in their supernatant, either activated or not. LP eosinophils appeared capable of secreting IL-22BP but not DCs likely due to in vitro activation as confirmed with monocyte-derived DCs. We also identified higher production of IL-22BP from ileum as compared to colon biopsies and demonstrated that IL-22BP levels correlated with those of eotaxins but not with TNF and IL-6. Finally, high ex vivo production of IL-22BP in mucosa biopsies from CD patients was only observed in smokers.

ConclusionWe confirmed that eosinophils and MNPs are the major sources of IL-22BP in the gut during CD and found no clear evidence for IL-22BP expression by T cells. This work also provides new insights on factors regulating intestinal IL-22BP levels.


title: morse: an R-package in support of Environmental Risk Assessment

abstract:
Package morse is devoted to the analysis of experimental data collected from standard toxicity tests. It provides ready-to-use functions to visualize a data set and to estimate several toxicity indices to be further used in support of environmental risk assessment in full compliance with regulatory requirements. Such toxicity indices are indeed classical requested by standardized regulatory guidelines on which national agencies base their evaluation of applications for marketing authorisation of chemical active substances.

Package morse can be used to get estimates of LCx (x% Lethal Concentration) or ECx (x% Effective Concentration) by fitting standard exposure-response models on toxicity test data. Risk indicator estimates as well as model parameters are provided along with the quantification of their uncertainty. Package morse can also be used to get estimates of the NEC (No Effect Concentration) by fitting a Toxicokinetic-Toxicodynamic (TKTD) model (namely GUTS models, that is General Unified Threshold models of Survival). Using GUTS models also allow to get estimates of LC(x,t) (whatever x and t) and LP(x,t), this later being defined by EFSA as the x% multiplication factor leading to an additional reduction of x% in survival at the end of the exposure profile. Above all, GUTS models can be used on data collected under time-variable exposure profiles.

This paper illustrates a typical use of morse with survival data collected over time and at different increasing exposure concentrations, analysed with the reduced version of GUTS models based on the stochastic death hypothesis (namely, the GUTS-RED-SD model). This example can be followed step-by-step to analyse any new data set, as long as the data set format is respected.


title: Uncertainty in population estimates: a meta-analysis for petrels

abstract:
O_LIPopulation estimates are commonly generated and used in conservation science. All estimates carry inherent uncertainty, but little attention has been given to when and how this uncertainty limits their use. This requires an understanding of the specific purposes for which population estimates are intended, an assessment of the level of uncertainty each purpose can tolerate, and information on current uncertainty.
C_LIO_LIWe conducted a review and meta-analysis for a widespread group of seabirds, the petrels, to better understand how and why population estimates are being used. Globally petrels are highly threatened, and aspects of their ecology make them difficult to survey, introducing high levels of uncertainty into population estimates.
C_LIO_LIWe found that by far the most common intended use of population estimates was to inform status and trend assessments, while less common uses were trialling methods to improve estimates, and assessing threat impacts and conservation outcomes.
C_LIO_LIThe mean coefficient of variation for published estimates was 0.17 (SD = 0.14), with no evidence that uncertainty has been reduced through time. As a consequence of this high uncertainty, when we simulated declines equivalent to thresholds commonly used to trigger management, only 5% of studies could detect significant differences between population estimates collected 10 years apart for populations declining at a rate of 30% over three generations.
C_LIO_LIReporting of uncertainty was variable with no dispersion statistics reported with 38% of population estimates and most not reporting key underlying parameters: nest numbers/density and nest occupancy. We also found no correlation between population estimates and either island size, body size or species threat status--potential predictors of uncertainty.
C_LIO_LISynthesis and applications--Key recommendations for managers are to be mindful of uncertainty in past population estimates if aiming to collect contemporary estimates for comparison, to report uncertainty clearly for new estimates, and to give careful consideration to whether a proposed estimate is likely to achieve the requisite level of certainty for the investment in its generation to be warranted. We recommend a practitioner-based Value of Information assessment to confirm where there is value in reducing uncertainty.
C_LI


title: Integrating spatial, phylogenetic, and threat assessment data from frogs and lizards to identify areas for conservation priorities in Peninsular Malaysia

abstract:
Malaysia is recognized as a megadiverse country and biodiversity hotspot, which necessitates sufficient levels of habitat protection and effective conservation management. However, conservation planning in Malaysia has hitherto relied largely on species distribution data without taking into account the rich evolutionary history of taxa. This represents the first study that integrates spatial and evolutionary approaches to identify important centers of diversity, endemism, and bioregionalization that can be earmarked for conservation priorities in Peninsular Malaysia. Using georeferenced species occurrences, comprehensive phylogenies, and threat assessments of frogs and lizards, we employed a spatial phylogenetics framework that incorporates various diversity metrics including weighted endemism, phylogenetic diversity, phylogenetic endemism, and evolutionary distinctiveness and global endangerment. Ten areas of high conservation value were identified via the intersection of these metrics--northern Perlis, Langkawi Geopark, southern Bintang range, Cameron Highlands, Frasers Hill, Benom-Krau complex, Selangor-Genting complex, Endau-Rompin National Park, Seribuat Archipelago (Tioman and Pemanggil Islands), and southern Johor. Of these, Cameron Highlands requires the highest conservation priority based on severe environmental degradation, inadequately protected areas, and high numbers of endangered and evolutionary distinct species. Other areas, especially in the northwestern (states of Kedah and Penang) and northeastern regions (states of Kelantan) were not only identified as areas of high conservation value but also areas of biogeographic importance. Taken together, frogs and lizards demonstrate distinct east-west and north-south patterns of bioregionalization that are largely modulated by mountain ranges.

Article Impact StatementThe first study to use a spatial phylogenetic approach to identify areas for conservation priorities in Malaysia


title: Investigating a trade-off between the quality of nest grown feathers and pace of development in an altricial bird.

abstract: Life history theory provides a framework for understanding how trade-offs generate negative trait associations. Among nestling birds, developmental rate, risk of predation, and lifespan covary, but some associations are only found within species while others are only observed between species. A recent comparative study suggests that allocation trade-offs may be alleviated by disinvestment in ephemeral traits, such as nest-grown feathers, that are quickly replaced. However, direct resource allocation trade-offs cannot be inferred from inter-specific trait-associations without complementary intra-specific studies. Here, we asked whether there is evidence for a within-species allocation trade-off between feather quality and developmental speed in tree swallows (Tachycineta bicolor). Consistent with the idea that ephemeral traits are deprioritized, nest-grown feathers had lower barb density than adult feathers. However, despite substantial variation in fledging age among nestlings, there was no evidence for a negative association between developmental pace and feather quality. Furthermore, accounting for differences in resource availability by considering provisioning rate and a nest predation treatment did not reveal a trade-off that was masked by variation in resources. Our results are most consistent with the idea that the inter-specific association between development and feather quality arises from adaptive specialization, rather than from a direct allocation trade-off.


title: Detecting seabird responses to invasive species eradication

abstract: Maximising survey efficiency can help reduce the trade-off between spending limited conservation resources on evaluating performance of past interventions and directing those resources towards future interventions. Seabird responses to island eradications are often poorly evaluated owing to financial, logistical and methodological challenges associated with remote field work and species ecology. We surveyed an assemblage of threatened seabirds following the worlds largest island eradication of multiple invasive species, testing multiple survey designs and outputs. We compared the outcomes of two important choices made during survey design: 1) whether to use unbiased or targeted surveys; and 2) implementing design-based or model-based analyses. An unbiased whole-island stratified randomised survey design performed well in terms of confidence in the final population estimates for widespread species, but poorly for localised recolonising species. For widespread species, model-based analyses resulted in slightly lower population estimates with narrower confidence intervals than traditional design-based approaches but failed to capture the realised niches of recolonising species, resulting in population estimates three orders of magnitude higher than current best estimates. We conclude that a multi-method approach to survey design best captures the size and distribution of recovering populations when the study system is ecologically diverse--importantly our results suggest there is no single strategy for efficient surveys of diverse seabird communities following large island invasive species eradications.


title: Differing ecological responses of seabirds to invasive species eradication

abstract: The impact of invasive species at seabird breeding islands causes a breakdown of important ecological functions such as prey consumption and nutrient transfer, and elevates extinction risk in impacted taxa. Eradicating invasive species from islands can result in substantial short-term recovery of seabird populations and consequently the prevalence of eradication programs as conservation tools is increasing. However, as the scale and complexity of eradications has increased, quantitative data on rates of recovery, especially from larger islands, remain limited. Furthermore, the mechanisms that govern recovery are poorly understood, limiting our ability to forecast outcomes and therefore prioritise effectively. Here, using the worlds largest multi-species vertebrate eradication from Macquarie Island as a case study, we show how responses to invasive species and their eradication differ. Species with broad realised niches whose breeding phenology minimizes time on land and corresponds with summer resource abundance remained extant alongside invasive species while more habitat-specific species present in winter were extirpated. Following eradication, immigration and flexibility to colonise under-utilised optimal habitat appears to be boosting population growth in recolonising species, whereas established populations appear to be tethered to refugial habitats by the influence of philopatry, and their recovery is slower as a result. Unpicking these differential responses and the mechanisms behind them provides valuable information to help predict responses in other systems as future eradications are planned.


title: Rapid, but limited, zooplankton adaptation to simultaneous warming and acidification

abstract: Predicting the response of marine metazoans to climate change is hampered by a lack of studies on evolutionary adaptation, particularly to combined ocean warming and acidification (OWA). We provide evidence for rapid adaptation to OWA in the foundational copepod species, Acartia tonsa, by assessing changes in population fitness based on a comprehensive suite of life-history traits, using an orthogonal experimental design of nominal temperature (18{degrees}C, 22{degrees}C) and pCO2 (400, 2000 atm) for 25 generations (~1 year). Egg production and hatching success initially decreased under OWA, resulting in a 56% reduction in fitness. However, both traits recovered by the third generation and average fitness was reduced thereafter by only 9%. Antagonistic interactions between warming and acidification in later generations decreased survival, thereby limiting full fitness recovery. Our results suggest such interactions constrain evolutionary rescue and add complexity to predictions of the responses of metazoan populations to climate change.

category: evolutionary biology


title: Portrait of a genus: the genetic diversity of Zea

abstract: Maize is a globally valuable commodity and one of the most extensively studied genetic model organisms. However, we know surprisingly little about the extent and potential utility of the genetic variation found in the wild relatives of maize. Here, we characterize a high-density genomic variation map from ~700 genomes encompassing maize and all wild taxa of the genus Zea, identifying over 65 million single nucleotide polymorphisms (SNPs), 8 million Insertion/Deletion (InDel) polymorphisms, and over one thousand novel inversions. The variation map reveals evidence of selection within taxa displaying novel adaptations such as perenniality and regrowth. We focus in detail on evidence of convergent adaptation in highland teosinte and temperate maize. This study not only indicates the key role of hormone related pathways in highland adaptation and flowering time related pathways in high latitude adaptation, but also identifies significant overlap in the genes underlying adaptations to both environments. To show how this data can identify useful genetic variants, we generated and characterized novel mutant alleles for two flowering time candidate genes. This work provides the most extensive sampling to date of the genetic diversity inherent in the genus Zea, resolving questions on evolution and identifying adaptive variants for direct use in modern breeding.


title: The Circadian Phase Response Curve to Light: Conservation across Seasons and Anchorage to Sunset

abstract: Phototherapy outcomes are dependent on the precision by which the magnitude and direction of lights circadian phase-shifting effects can be predicted. Such predictions are largely based on photic phase-response curves (PRCs) generated from animals housed under seasonally agnostic equatorial photoperiods with alternating 12-hour segments of light and darkness. Most of the human population, however, lives at northerly latitudes (20-50{degrees} N of the Equator) where seasonal variations in the light-dark schedule are pronounced. Here, we address this disconnect by constructing the first high-resolution seasonal atlas for light-induced circadian phase-resetting. Testing the light responses of nearly 4,000 Drosophila at 120 timepoints across 5 seasonally relevant photoperiods (i.e., LD 8:16, 10:14, 12:12, 14:10, and 16:8; 24 hourly intervals surveyed in each), we determined that many aspects of the circadian PRC waveform are conserved with increasing daylength. Surprisingly though, irrespective of LD schedule, the start of the PRCs always remained anchored to the timing of subjective sunset, creating a differential overlap of the advance zone with the morning hours after subjective sunrise that was maximized under summer photoperiods and minimized under winter photoperiods. These data suggest that circadian photosensitivity is effectively extinguished by the early winter morning and out of optimal phase alignment with the wake schedules of many individuals (which revolve around the timing of sunrise regardless of season). They raise the possibility that phototherapy protocols for conditions such as seasonal depression might be improved with programmed light exposure during the final hours of sleep.


title: Automatic structural analysis of bioinspired percolating network materials using graph theory

abstract:
Mimicking numerous biological membranes and nanofiber-based tissues, there are multiple materials that are structured as percolating nanoscale networks (PPNs). They reveal unique combination of properties and the family of PNN-based composites and nanoporous materials is rapidly expanding. Their technological significance and the necessity of their structural design require a unifying approach for their structural description. However, their complex aperiodic architectures are difficult to describe using traditional methods that are tailored for crystals. A related problem is the lack of computational tools that enable one to capture and enumerate the patterns of stochastically branching fibrils that are typical for these composites. Here, we describe a conceptual methodology and a computational package, StructuralGT, to automatically produce a graph theoretical (GT) description of PNNs from various micrographs. Using nanoscale networks formed by aramid nanofibers (ANFs) as examples, we demonstrate structural analysis of PNNs with 13 GT parameters. Unlike qualitative assessments of physical features employed previously, StructuralGT allows quantitative description of the complex structural attributes of PNNs enumerating the networks morphology, connectivity, and transfer patterns. Accurate conversion and analysis of micrographs is possible for various levels of noise, contrast, focus, and magnification while a dedicated graphical user interface provides accessibility and clarity. The GT parameters are expected to be correlated to material properties of PNNs (e.g. ion transport, conductivity, stiffness) and utilized by machine learning tools for effectual materials design.

Table of Content

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category: bioengineering


title: Immersive virtual prism adaptation therapy with depth sensing camera: A feasibility study with functional near infrared spectroscopy in healthy adults

abstract: Unilateral spatial neglect (USN) is common after stroke and associated with poor functional recovery. Prism adaptation (PA) is one of the most supported modality able to ameliorate USN but underapplied due to several issues. Using immersive virtual reality and depth-sensing camera, we developed the virtual prism adaptation therapy (VPAT) to overcome the limitations in conventional PA. In this study, we investigated whether VPAT can induce behavioral adaptations and which cortical area is most significantly activated. Fourteen healthy subjects participated in this study. The experiment consisted of four sequential phases (pre-VAPT, VPAT-10{degrees}, VPAT-20{degrees}, and post-VPAT) with functional near-infrared spectroscopy recordings. Each phase consisted of alternating target pointing and resting (or clicking) blocks. To find out the most significantly activated area during pointing in different phases (VPAT-10{degrees}, VPAT-20{degrees}, and Post-VPAT) in contrast to pointing during the pre-VPAT phase, we analyzed changes in oxyhemoglobin concentration during pointing. The pointing errors of the virtual hand deviated to the right-side during early pointing blocks in the VPAT-10{degrees} and VPAT-20{degrees} phases. There was a left-side deviation of the real hand to the target in the post-VPAT phase. The most significantly activated channels were all located in the right hemisphere, and possible corresponding cortical areas included the dorsolateral prefrontal cortex and frontal eye field. In conclusion, VPAT may induce behavioral adaptation with modulation of the dorsal attentional network. Future clinical trials using multiple sessions of a high degree of rightward deviation VPAT over a more extended period are required in stroke patients with unilateral spatial neglect.


title: PsiNorm: a scalable normalization for single-cell RNA-seq data

abstract:
Single-cell RNA sequencing (scRNA-seq) enables transcriptome-wide gene expression measurements at single-cell resolution providing a comprehensive view of the compositions and dynamics of tissue and organism development. The evolution of scRNA-seq protocols has led to a dramatic increase of cells throughput, exacerbating many of the computational and statistical issues that previously arose for bulk sequencing. In particular, with scRNA-seq data all the analyses steps, including normalization, have become computationally intensive, both in terms of memory usage and computational time. In this perspective, new accurate methods able to scale efficiently are desirable.

Here we propose PsiNorm, a between-sample normalization method based on the power-law Pareto distribution parameter estimate. Here we show that the Pareto distribution well resembles scRNA-seq data, independently of sequencing depths and technology. Motivated by this result, we implement PsiNorm, a simple and highly scalable normalization method. We benchmark PsiNorm with other seven methods in terms of cluster identification, concordance and computational resources required. We demonstrate that PsiNorm is among the top performing methods showing a good trade-off between accuracy and scalability. Moreover PsiNorm does not need a reference, a characteristic that makes it useful in supervised classification settings, in which new out-of-sample data need to be normalized.

PsiNorm is available as an R package available at https://github.com/MatteoBlla/PsiNorm


title: Sequence specificity in DNA binding is determined by association rather than dissociation

abstract:
Sequence-specific binding of proteins to DNA is essential for accessing genetic information. Here, we derive a simple equation for target-site recognition, which uncovers a previously unrecognized coupling between the macroscopic association and dissociation rates of the searching protein. Importantly, this relationship makes it possible to recover the relevant microscopic rates from experimentally determined macroscopic ones. We directly test the equation by observing the binding and unbinding of individual lac repressor (LacI) molecules during target search. We find that LacI dissociates from different target sequences with essentially identical microscopic dissociation rates. Instead, sequence specificity is determined by the efficiency with which the protein recognizes different targets, effectively reducing its risk of being retained on a non-target sequence. Our theoretical framework also accounts for the coupling between off-target binding and unbinding of the catalytically inactive Cas9 (dCas9), showing that the binding pathway can be obtained from macroscopic data.

One Sentence SummaryAssociation and dissociation rates are anti-correlated for reactions that include a nonspecific probing step.


title: Spectroscopic glimpses of the transition state of ATP hydrolysis trapped in a bacterial DnaB helicase

abstract: The ATP hydrolysis transition state of motor proteins is a weakly populated protein state that can be stabilized and investigated by replacing ATP with chemical mimics. We present atomic-level structural and dynamic insights on a state created by ADP aluminum fluoride binding to the bacterial DnaB helicase from Helicobacter pylori. We determined the positioning of the metal ion cofactor within the active site using electron paramagnetic resonance, and identified the protein protons coordinating to the phosphate groups of ADP and DNA using proton-detected 31P,1H solid-state nuclear magnetic resonance spectroscopy at fast magic-angle spinning > 100 kHz, as well as temperature-dependent proton chemical-shift values to prove their engagements in hydrogen bonds. 19F and 27Al MAS NMR spectra reveal a highly mobile, fast-rotating aluminum fluoride unit pointing to the capture of a late ATP hydrolysis translation state in which the phosphoryl unit is already detached from the arginine and lysine fingers.


title: Real-time object locator for cryo-EM data collection--- You only navigate EM once ---

abstract: In cryo-electron microscopy (cryo-EM) data collection, locating a target object is the most error-prone. Here, we present a machine learning-based approach with a real-time object locator named yoneoLocr using YOLO, a well-known object detection system. Implementation showed its effectiveness in rapidly and precisely locating carbon holes in single particle cryo-EM and for locating crystals and evaluating electron diffraction (ED) patterns in automated cryo-electron crystallography (cryo-EX) data collection.


title: The causal role of transcranial alternating current stimulation at alpha frequency in boosting visual perceptual learning

abstract:
Extensive training improves our ability to perceive visual contents around us, a phenomenon known as visual perceptual learning (VPL). Numerous studies have been conducted to understand the mechanisms of VPL, while the neural oscillatory mechanisms underpinning VPL has yet to be elucidated. To this end, we adopted transcranial alternating current stimulation (tACS), a neuromodulatory technique that can alter ongoing brain rhythms in a frequency-specific manner by applying external weak electric fields, to stimulate targeted cortical areas in human subjects while they performed an orientation discrimination learning task. Five groups of subjects undertook five daily training sessions to execute the task. Four groups received occipital tACS stimulation at 10 Hz (alpha band), 20 Hz (beta band), 40 Hz (gamma band), or sham 10 Hz (sham), and one group was stimulated at the sensorimotor regions by 10 Hz tACS. Compared with the sham stimulation, occipital tACS at 10 Hz, but not at 20 Hz or 40 Hz, increased both the learning rate and performance improvement. However, when 10 Hz tACS was delivered to the sensorimotor areas, the modulatory effects of tACS were absent, suggesting that tACS modulated the orientation discrimination learning in a frequency- and location-specific manner. Moreover, the tACS-induced enhancement lasted at least two months after the termination of training. Our findings provide strong evidence for the causal role of alpha oscillations in VPL and shed new light on the design of effective neuromodulation protocols that might facilitate rehabilitation for patients with neuro-ophthalmological disorders.

Significance StatementPerformance of visual tasks can be enhanced substantially by training, which is known as visual perceptual learning (VPL). However, little is known about the neural oscillatory mechanisms underlying VPL. To probe the causal link between a given oscillatory frequency band and VPL, transcranial alternating current stimulation (tACS) was applied while subjects performed an orientation discrimination learning task. Our results revealed that tACS modulates VPL in a frequency- and location-specific manner. Specifically, only training coupled with 10 Hz tACS over the occipital cortex speeded up the learning process and amplified the performance gain. Our findings demonstrate the causal role of alpha oscillations in VPL, and provide insight into developing more effective and efficient remediation protocols for clinical applications, e.g., amblyopia.


title: Quantitative mapping of cerebral oxygen metabolism using breath-hold calibrated fMRI

abstract: Magnetic resonance imaging (MRI) offers the possibility to non-invasively map the rate of cerebral metabolic oxygen consumption (CMRO2), which is essential for understanding and monitoring neural function in both health and disease. Existing methods of mapping CMRO2, based on respiratory modulation of arterial spin labelling (ASL) and blood oxygen level dependent (BOLD) signals, require lengthy acquisitions and independent modulation of both arterial oxygen and carbon dioxide levels. Here, we present a new simplified method for mapping the rate of cerebral oxygen metabolism that can be performed using a simple breath-holding paradigm. The method incorporates flow-diffusion modelling of oxygen transport and physiological constraints to create a non-linear mapping between the maximum BOLD signal, M, baseline blood flow (CBF0), and CMRO2. A gradient boosted decision tree is used to learn this mapping directly from simulated MRI data. Modelling studies demonstrate that the proposed method is robust to variation in cerebral physiology and metabolism. This new gas-free methodology offers a rapid and pragmatic alternative to existing dual-calibrated methods, removing the need for specialist respiratory equipment and long acquisition times. In-vivo testing of the method, using an 8-minute 45 second protocol of repeated breath-holding, was performed on 15 healthy volunteers, producing quantitative maps of cerebral blood flow (CBF), oxygen extraction fraction (OEF), and CMRO2.


title: STOPPING A CONTINUOUS MOVEMENT: A NOVEL APPROACH TO INVESTIGATING MOTOR CONTROL

abstract: Flexible, adaptive behavior is critically dependent on inhibitory control. For example, if you suddenly notice you are about to step on a tack and would prefer not to, the ability to halt your ongoing movement is critical. To address limitations in existing approaches for studying your ability to rapidly terminate your movement ("stopping"), we developed a novel stop task. This task requires termination of ongoing motor programs, provides a direct measure of SSRT, and allows for comparison of the same behavior (stopping) in conditions that elicit either prepared or reactive inhibitory control. Here, we present and evaluate our novel Continuous Movement Stop Task (CMST). We examined several versions of the task in a total of 49 participants. Our data reveal that the CMST is effectively able to dissociate stopping behavior between the planned and unplanned conditions. Additionally, within the subset of participants for which we measured speed, we found that participants initiated stopping (with respect to the stop signal) significantly earlier on planned stop compared to unplanned stop trials. Finally, participants took longer to arrive at full motor arrest (i.e. SSRT) following stop initiation on planned than on unplanned stop trials. This novel task design will enable a more precise quantification of stopping behavior and, in conjunction with neuroscientific methods, could provide more rigorous characterization of brain networks underlying stopping.


title: In vivo engineered B cells retain memory and secrete high titers of anti-HIV antibodies in mice

abstract:
As a potential single-shot HIV therapy, transplanted engineered B cells allow robust secretion of broadly neutralizing antibodies (bNAbs). However, ex vivo engineering of autologous B cells is expensive and requires specialized facilities, while allogeneic B cell therapy necessitates MHC compatibility. Here, we develop in vivo B cell engineering, by injecting two adeno associated viral vectors, one coding for saCas9 and another coding for a bNAb. Following immunizations, we demonstrate memory retention and bNAb secretion at neutralizing titers. We observed minimal CRISPR/Cas9 off-target cleavage, using unbiased CHANGE-Seq analysis, while on-target cleavage at undesired tissues is reduced by expressing saCas9 from a B cell specific promoter. In vivo B cell engineering is thus a safe, potent and scalable method for expressing desired antibodies against HIV and beyond.

One sentence summaryB cells can be engineered in vivo to robustly secrete anti-HIV bNAbs in a safe, durable and scalable manner.


title: Transient demographic approaches can drastically expand the toolbox of coral reef science

abstract: Coral communities are threatened by an increasing plethora of abiotic and biotic disturbances. Preventing the ensuing loss of coral coverage and diversity calls for a mechanistic understanding of resilience across coral species and populations that is currently lacking in coral reef science. Assessments into the dynamics of coral populations typically focus on their long-term (i.e. asymptotic) characteristics, tacitly assuming stable environments in which populations can attain their long-term characteristics. Instead, we argue that greater focus is needed on investigating the transient (i.e. short-term) dynamics of coral populations to describe and predict their characteristics and trajectories within unstable environments. Applying transient demographic approaches to the evaluation and forecasting of the responses of coral populations to disturbance holds promise for expediting our capacity to predict and manage the resilience of coral populations, species, and communities.


title: Assessing bivalve phylogeny using Deep Learning and Computer Vision approaches

abstract: Phylogenetic analyses using morphological data currently require hand-crafted character matrices, limiting the number of taxa that can be included. Here I explore how Deep Learning and Computer Vision approaches typically applied to image classification tasks, may be used to infer phylogenetic relationships among bivalves. A convolutional neural network (CNN) was trained on thousands of images showing species of 75 bivalve families. The predictions of the CNN on a large number of bivalve images are then interpreted as an indication of how similar these bivalves are to each other, are averaged by the families to which the species belonged, and visualized in a cluster diagram. In this cluster diagram, significantly more families clustered with members of their subclasses than expected by chance, confirming the feasibility of the approach. To address the issue of convergent evolution, two further CNNs were trained, on the same images but grouped by the orders and subclasses to which the species belonged. Combining predictions for the same images but on different taxonomic levels improved the inferred phylogenetic relationships also of families that the CNNs had not been trained on. Finally, this combined tree is merged with five published phylogenetic trees into a supertree, representing the largest single phylogeny of the Bivalvia to date, encompassing 128 families, including six exclusively fossil families and nine extant families for which presently no molecular data are available. Issues inherent to the approach and suggestions for future directions are discussed.


title: The impact of incongruence and exogenous gene fragments on estimates of the eukaryote root

abstract: Phylogenomics uses multiple genetic loci to reconstruct evolutionary trees, under the stipulation that all combined loci share a common phylogenetic history, i.e., they are congruent. Congruence is primarily evaluated via single-gene trees, but these trees invariably lack sufficient signal to resolve deep nodes making it difficult to assess congruence at these levels. Two methods were developed to systematically assess congruence in multi-locus data. Protocol 1 uses gene jackknifing to measure deviation from a central mean to identify taxon-specific incongruencies in the form of persistent outliers. Protocol_2 assesses congruence at the sub-gene level using a sliding window. Both protocols were tested on a controversial data set of 76 mitochondrial proteins previously used in various combinations to assess the eukaryote root. Protocol_1 showed a concentration of outliers in under-sampled taxa, including the pivotal taxon Discoba. Further analysis of Discoba using Protocol_2 detected a surprising number of apparently exogenous gene fragments, some of which overlap with Protocol_1 outliers and others that do not. Phylogenetic analyses of the full data using the static LG-gamma evolutionary model support a neozoan-excavate root for eukaryotes (Discoba sister), which rises to 99-100% bootstrap support with data masked according to either Protocol_1 or Protocol_2. In contrast, site-heterogeneous (mixture) models perform inconsistently with these data, yielding all three possible roots depending on presence/absence/type of masking and/or extent of missing data. The neozoan-excavate root places Amorphea (including animals and fungi) and Diaphoretickes (including plants) as more closely related to each other than either is to Discoba (Jakobida, Heterolobosea, and Euglenozoa), regardless of the presence/absence of additional taxa.


title: Honeybee Queen mandibular pheromone induces starvation in Drosophila melanogaster, implying a role for nutrition signalling in the evolution of eusociality.

abstract:
Eusocial insect societies are defined by the reproductive division of labour, a social structure that is generally enforced by the reproductive dominant or  queen. Reproductive dominance is maintained through behavioural dominance in some species as well as production of queen pheromones in others, or a mixture of both. Queen mandibular pheromone (QMP) is produced by honeybee (Apis mellifera) queens and has been characterised chemically. How QMP acts to repress worker reproduction, and how it has evolved this activity, remains less well understood. Surprisingly, QMP is capable of repressing reproduction in non-target arthropods which have not co-evolved with QMP, are never exposed to QMP in nature, and are up to 530 million years diverged from the honeybee.

Here we show that, in Drosophila melanogaster, QMP treatment mimics nutrient limiting conditions, leading to disrupted reproduction. Exposure to QMP induces an increase in food consumption, consistent with that observed in D. melanogaster in response to starvation conditions. This response induces the activation of two checkpoints within the ovary that inhibit oogenesis. The first is the 2a/b ovarian checkpoint in the germarium, which reduces the flow of presumptive oocytes. A stage 9 ovarian checkpoint is also activated, causing degradation of oocytes. The magnitude of activation of both checkpoints is indistinguishable between QMP treated and starved individuals.

As QMP seems to trigger a starvation response in an insect highly diverged from honeybees, we propose that QMP originally evolved by co-opting nutrition signalling pathways to regulate reproduction, a key step in the evolution of eusociality.


title: Naïve individuals promote collective exploration in homing pigeons

abstract: Group-living animals that rely on stable foraging or migratory routes can develop behavioural traditions to pass route information down to inexperienced individuals. Striking a balance between exploitation of social information and exploration for better alternatives is essential to prevent the spread of maladaptive traditions. We investigated this balance during cumulative route development in the homing pigeon Columba livia. We quantified information transfer within pairs of birds in a transmission-chain experiment and determined how birds with different levels of experience contributed to the exploration- exploitation trade-off. Newly introduced naive individuals were initially more likely to initiate exploration than experienced birds, but the pair soon settled into a pattern of alternating leadership with both birds contributing equally. Experimental pairs showed an oscillating pattern of exploration over generations that might facilitate the discovery of more efficient routes. Our results introduce a new perspective on the roles of leadership and information pooling in the context of collective learning.


title: Lipid mediator profile of burn wound healing: Acellular cod fish skin grafts promote the formation of EPA and DHA derived lipid mediators during the first seven days

abstract:
The use of acellular fish skin grafts (FSG) for the treatment of burn wounds is becoming more common due to its beneficial wound healing properties. In our previous study we demonstarted that FSG is a scaffold biomaterial that is rich in eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) conjugated to phosphatidylcholines. Here we investigated whether EPA and DHA derived lipid mediators are influenced during the healing of burn wounds treated with FSG. Deep partial and full thickness burn wounds (DPT and FT respectively) were created on Yorkshire pigs (n=4). DPT were treated with either FSG or fetal bovine dermis while FT were treated either with FSG or cadaver skin initially and followed by a split thickness skin graft. Punch biopsies were collected on days 7, 14, 21, 28 and 60 and analysed in respect of changes to approximately 45 derivatives of EPA, DHA, arachidonic acid (AA), and linoleic acid (LA) employing UPLC-MS/MS methodology. Several EPA and DHA derivatives, including 18-HEPE and 17-HDHA, were significantly higher on day 7 in the DPT when treated with FSG. A similar but non-significant trend was observed for the FT. In addition, prostaglandin F2 and its 15-keto derivative (AA pathway) as well as 13-HODE and 13-HOTrE (LA pathway) were significantly lower in the FSG treated FT. The results suggest that the use of FSG in burn wound treatment can alter the formation of EPA and DHA mono hydroxylated lipid mediators in comparison to other grafts of mammalian origin. The differences observed during the first seven days after treatment indicates that FSG affects the early stages of wound healing.

HighlightsO_LIThis is the first study to investigate whether omega-3 rich biomaterial such as fish skin graft can affect the lipidome of burn wound healing
C_LIO_LIThe study monitors the formation of lipid mediators during 60 days of burn wound healing
C_LIO_LIThis is the first study to show an increase in the formation of mono-hydroxylated derivatives of EPA and DHA after seven days of treatment with fish skin graft
C_LIO_LIThe study showed significantly decreased formation of lipid mediators involved in pain modulation in wounds treated with fish skin graft
C_LI

category: biochemistry


title: Microvasculature-on-a-Chip: Bridging the interstitial blood-lymph interface via mechanobiological stimuli

abstract: After decades of simply being referred to as the bodys sewage system, the lymphatic system has recently been recognized as a key player in numerous physiological and pathological processes. As an essential site of immune cell interactions, the lymphatic system is a potential target for next-generation drug delivery approaches in treatments for cancer, infections, and inflammatory diseases. However, the lack of cell-based assays capable of recapitulating the required biological complexity combined with unreliable in vivo animal models currently hamper scientific progress in lymph-targeted drug delivery. To gain more in-depth insight into the blood-lymph interface, we established an advanced chip-based microvascular model to study mechanical stimulations importance on lymphatic sprout formation. Our microvascular models key feature is the co-cultivation of spatially separated 3D blood and lymphatic vessels under controlled, unidirectional interstitial fluid flow while allowing signaling molecule exchange similar to the in vivo situation. We demonstrate that our microphysiological model recreates biomimetic interstitial fluid flow, mimicking the route of fluid in vivo, where shear stress within blood vessels pushes fluid into the interstitial space, which is subsequently transported to the nearby lymphatic capillaries. Results of our cell culture optimization study clearly show an increased vessel sprouting number, length, and morphological characteristics under dynamic cultivation conditions and physiological relevant mechanobiological stimulation. For the first time, a microvascular on-chip system incorporating microcapillaries of both blood and lymphatic origin in vitro recapitulates the interstitial blood-lymph interface.


title: Transfer RNA-derived non-coding RNAs (tncRNAs): Uncovering hidden regulators of transcriptional regulatory circuits in plants

abstract:
The lateral emergence of distinct classes of non-coding RNAs has led to better insights into the eukaryotic regulatory networks. Among them, the existence of transfer RNA (tRNA)-derived non-coding RNAs (tncRNAs) demands their exploration in the plant kingdom. Here, we have designed a methodology to uncover the bigger picture of tncRNAome in plants. Using this, we have identified diverse tncRNAs of length 14-50 nt in ~2500 small RNA sequencing (sRNA-seq) samples of six major angiosperms, and further studied their various features including length, codon-usage, cleavage pattern, and modified tRNA nucleosides. Codon-dependent generation of tncRNAs indicates that the process is highly specific rather than being mere random tRNA degradation. Analysis for nucleotide composition of tncRNA cleavage positions indicates that they are generated through precise endoribonucleolytic machinery. Certain tRNA nucleoside modifications on tncRNAs were found to be conserved across the plants, and hence may influence tRNA cleavage, as well as tncRNA functions. Pathway enrichment analysis revealed that common tncRNA targets were majorly involved in the metabolic and developmental processes of plants. Also, many tRFs were found to be associated with transposable elements. Distinct tissue-specific tncRNA clusters indicate their role in plant development under normal physiological conditions. Furthermore, the identification of a significant number of differentially expressed tncRNAs under several abiotic and biotic stresses highlights their probable role as gene expression modulators during various stress conditions. Thus, this study will be beneficial to investigate the emerging role of tncRNAs as prospective biomarkers in plant development and stress.

HighlightsO_LIComputational pipeline for accurate identification of genuine transfer RNA-derived non-coding RNAs (tncRNAs) using small RNA sequencing (sRNA-seq) datasets.
C_LIO_LISix major tncRNA classes of length ranging from 14 to 50 nt were identified in ~2,500 sRNA-seq datasets in six different angiosperms.
C_LIO_LItRNA nucleoside modifications may affect tncRNA cleavage in plants.
C_LIO_LIConserved tncRNAs target transcripts are involved in plant growth, development, and metabolism.
C_LIO_LItncRNAs are expressed in a tissue-dependent, and stress-specific manner in plants.
C_LI


title: SMaSH: A scalable, general marker gene identification framework for single-cell RNA sequencing and Spatial Transcriptomics

abstract: Spatial transcriptomics is revolutionising the study of single-cell RNA and tissue-wide cell heterogeneity, but few robust methods connecting spatially resolved cells to so-called marker genes from single-cell RNA sequencing, which generate significant insight gleaned from spatial methods, exist. Here we present SMaSH, a general computational framework for extracting key marker genes from single-cell RNA sequencing data for spatial transcriptomics approaches. SMaSH extracts robust and biologically well-motivated marker genes, which characterise the given data-set better than existing and limited computational approaches for global marker gene calculation.


title: Missing Value Imputation using XGboost for Label-Free Mass Spectrometry-Based Proteomics Data

abstract: The label-free mass spectrometry-based proteomics data inevitably suffer from the problem of missing values. The existence of missing values prevents the downstream analyses which need a complete data matrix. Our motivation is to introduce the state-of-art machine learning algorithm XGboost to realize a method of imputation which can improve the accuracy of imputation. But in practical, XGboost has many parameters need to be tuned to deliver on its potential high performance. Although cross validation may find the best parameters, it is much time-consuming. Alternatively, we empirically determined the parameters to two kinds of base learners of XGboost. To explore the robustness and performance of XGboost based imputation with predetermined parameters, we conducted tests on three benchmark datasets. As a comparative, six common imputation methods were also experimented in terms of normalized root mean squared error and Pearson correlation coefficient. The comparative experimental results indicated that the XGboost based imputation method using the linear base learner is competitive to or out-performs its competitors, including the random forest based imputation, by achieving smaller imputation errors and better structure preservation under the empirical parameters for the three benchmark datasets.


title: Structure and Stability of the designer protein WRAP-T and its permutants

abstract: {beta}-Propeller proteins are common natural disc-like pseudo-symmetric proteins that contain multiple repeats ( blades) each consisting of a 4-stranded anti-parallel {beta}-sheet. So far, 4- to 12-bladed {beta}-propellers have been discovered in nature showing large functional and sequential variation. Using computational design approaches, we created perfectly symmetric {beta}-propellers out of natural pseudo-symmetric templates. These proteins are useful tools to study protein evolution of this very diverse fold. While the 7-bladed architecture is the most common, no symmetric 7-bladed monomer has been created and characterized so far. Here we describe such a engineered protein, based on a highly symmetric natural template, and test the effects of circular permutation on its stability. Geometrical analysis of this protein and other artificial symmetrical proteins reveals no systematic constraint that could be used to help in engineering of this fold, and suggests sequence constraints unique to each {beta}-propeller sub-family.


title: Conformational clamping by a membrane ligand activates the EphA2 receptor

abstract: The EphA2 receptor is a promising drug target for cancer treatment, since EphA2 activation can inhibit metastasis and tumor progression. It has been recently described that the TYPE7 peptide activates EphA2 using a novel mechanism that involves binding to the single transmembrane domain of the receptor. TYPE7 is a conditional transmembrane (TM) ligand, which only inserts into membranes at neutral pH in the presence of the TM region of EphA2. However, how membrane interactions can activate EphA2 is not known. We systematically altered the sequence of TYPE7 to identify the binding motif used to activate EphA2. With the resulting six peptides, we performed biophysical and cell migration assays that identified a new potent peptide variant. We also performed a mutational screen that determined the helical interface that mediates dimerization of the TM domain of EphA2 in cells. These results, together with molecular dynamic simulations, allowed to elucidate the molecular mechanism that TYPE7 uses to activate EphA2, where the membrane peptide acts as a molecular clamp that wraps around the TM dimer of the receptor. We propose that this binding mode stabilizes the active conformation of EphA2. Our data, additionally, provide clues into the properties that TM ligands need to have in order to achieve activation of membrane receptors.


title: DIA-based Proteomics Identifies IDH2 as a Targetable Regulator of Acquired Drug Resistance in Chronic Myeloid Leukemia

abstract: Drug resistance is a critical obstacle to effective treatment in patients with chronic myeloid leukemia (CML). To understand the underlying resistance mechanisms in response to imatinib (IMA) and adriamycin (ADR), the parental K562 cells were treated with low doses of IMA or ADR for two months to generate derivative cells with mild, intermediate and severe resistance to the drugs as defined by their increasing resistance index (RI). PulseDIA-based quantitative proteomics was then employed to reveal the proteome changes in these resistant cells. In total, 7,082 proteotypic proteins from 98,232 peptides were identified and quantified from the dataset using four DIA software tools including OpenSWATH, Spectronaut, DIA-NN, and EncyclopeDIA. Sirtuin Signaling Pathway was found to be significantly enriched in both ADR- and IMA-resistant K562 cells. In particular, IDH2 was identified as a potential drug target correlated with the drug resistance phenotype, and its inhibition by the antagonist AGI-6780 reversed the acquired resistance in K562 cells to either ADR or IMA. Together, our study has implicated IDH2 as a potential target that can be therapeutically leveraged to alleviate the drug resistance in K562 cells when treated with IMA and ADR.

category: cancer biology


title: Raman imaging and statistical methods for analysis various type of human brain tumor

abstract: Spectroscopic methods provide information on the spatial localization of biochemical components based on the analysis of vibrational spectra. Raman spectroscopy and Raman imaging can be used to analyze various types of human brain tissue. The objective of this study is employment of Raman spectroscopy and Raman imaging to evaluate the Raman biomarkers to distinguish tumor types. We have demonstrated that bands characteristic for carotenoids (1156 cm-1, 1520 cm-1), proteins (1004 cm-1), fatty acids (1444 cm-1, 1655 cm-1) and cytochrome (1585 cm-1) can be used as universal biomarkers to distinguish aggressiveness in human brain tumor. The sensitivity and specificity obtained from PLS-DA have been over 85%. Only for pituitary adenoma the specificity is lower and takes equal 46%. The presented results confirm the potential applications of vibrational spectroscopy methods in oncological diagnostics.


title: Motor unit recruitment patterns of the quadriceps differ between continuous high- and low-torque isometric knee extension to momentary failure

abstract: The size principle is a theory of motor unit (MU) recruitment that suggests MUs are recruited in an orderly manner from the smallest (lower threshold) to the largest (higher threshold) MUs. A consequence of this biophysical theory is that, for isometric contractions, recruitment is dependent on the intensity of actual effort required to meet task demands. This concept has been supported by modelling work demonstrating that, in tasks performed to momentary failure, full MU recruitment will have occurred upon reaching failure irrespective of the force requirements of the task. However, in vivo studies examining this are limited. Therefore, the aim of the current study was to examine MU recruitment of the quadriceps under both higher- and lower-torque (70% and 30% of MVC, respectively) isometric knee extension, performed to momentary failure. Specifically, we compared surface electromyography (sEMG) frequency characteristics, determined by wavelet analysis, across the two continuous isometric knee extension tasks to identify potential differences in recruitment patterns. A convenience sample of 10 recreationally active adult males (height: 179.6{+/-}6.0 cm; mass: 76.8{+/-}7.3 kg; age: 26{+/-}7 years) with previous resistance training experience (6{+/-}3 years) were recruited. Using a within-session, repeated-measures, randomised crossover design participants performed the knee extension tasks whilst sEMG was collected from the vastus medialis (VM), rectus femoris (RF) and vastus lateralis (VL). Myoelectric signals were decomposed into intensities as a function of time and frequency using an EMG-specific wavelet transformation. Our first analysis compared the mean frequency at momentary failure; second, we investigated the effects of load on relative changes in wavelet intensities; finally, we quantified the degree of wavelet similarity over time. Wavelet-based calculation of the mean signal frequency appeared to show similar mean frequency characteristics occurring when reaching momentary failure. However, individual wavelets revealed that different changes in frequency components occurred between the two tasks, suggesting that patterns of recruitment differed. Low-torque conditions resulted in an increase in intensity of all frequency components across the trials for each muscle whereas high-torque conditions resulted in a wider range of frequency components contained within the myoelectric signals at the beginning of the trials. However, as the low-torque trial neared momentary failure there was an increased agreement between conditions across wavelets. Our results corroborate modelling studies as well as recent biopsy evidence, suggesting overall MU recruitment may largely be similar for isometric tasks performed to momentary failure with the highest threshold MUs likely recruited, despite being achieved with differences in the pattern of recruitment over time utilised.


title: Emotion Recognition in a Multi-Componential Framework: The Role of Physiology

abstract: Emotions are rich and complex experiences involving various behavioral and physiological responses. While many empirical studies have focused on discrete and dimensional representations of emotions, these representations do not fully reconcile with recent neuroscience studies that increasingly suggest a multi-process mechanism underlying emotional experience. Moreover, the latter view accords with psychological theories that consider emotions as multicomponent phenomena, such as appraisal theories. Although there is no complete consensus on the specific components of emotions and fundamental principles defining their organization, the Component Process Model (CPM) is well established framework describing an emotion as a dynamic process with five major highly interrelated components: cognitive appraisal, expression, motivation, physiology and feeling. Yet, few studies have systematically investigated a range of discrete emotions through this full multi-componential view. In the present study, we therefore elicited various emotions during movie watching and measured their manifestation across these components. Our primary goal was to investigate the relationship between physiological measures and the theoretically defined components of emotions. In addition, we also investigated whether discrete emotions could be predicted from information provided by the multicomponent response patterns, as well as the specific contributions of each component in such predictions. Results suggest that physiological features are interrelated to all other components of emotion, but the least significant predictors for emotion classification. Overall, emotion prediction was significantly higher when classifiers were trained with all five components. The findings therefore support a description of emotion as a dynamic multicomponent process, in which the emergence of a conscious feeling state requires the integration of all the components.


title: Caregiving quality modulates neuroendocrine and immunological markers in young children in foster care who have experienced early adversity

abstract:
BackgroundEarly adversity is believed to alter the bodys stress response systems, putting children at increased risk for somatic and mental health problems. However, it remains unclear whether such alterations normalize under improved caregiving experiences. Thus, the goal of the present study was to investigate i) whether children in foster care show endocrine and immunological alterations relative to children living with their biological families, ii) whether these alterations change over time spent with the foster family and iii) whether the alterations are modulated by current caregiving experiences.

MethodsA total of 94 children in foster care and 157 biological children, aged two to seven years, took part in a longitudinal study with three assessments conducted over a 12-month study period. At the initial assessment, children lived for an average of 18 months with their current foster families. Childrens cortisol, dehydroepiandrosterone (DHEA) and progesterone concentrations and cortisol/DHEA ratios were measured in scalp hair and childrens secretory immunoglobulin A (sIgA) levels in saliva. Caregiving quality was assessed based on caregiver-reports and observational measures of caregiver-child interactions.

ResultsChildren in foster care had lower cortisol/DHEA ratios and higher progesterone concentrations than biological children, while no group differences were found for cortisol, DHEA or sIgA. Time spent with the current foster family did not significantly influence the childs endocrine or immunological markers. Importantly, caregiving quality modulated cortisol/DHEA ratios and sIgA concentrations: children in foster care of lower caregiving quality had lower cortisol/DHEA ratios than children in foster care of higher caregiving quality and showed decreasing, rather than increasing, sIgA concentrations across the study period.

ConclusionsOur results indicate that caregiving quality in the foster family may have an important modulating effect on selected indicators of the childs stress response and could thereby mitigate the possible consequences of early childhood adversity.


title: Complex effects of kinase localization revealed by compartment-specific regulation of protein kinase A activity

abstract: Kinase activity in signaling networks frequently depends on regulatory subunits that can both inhibit activity by interacting with the catalytic subunits and target the kinase to distinct molecular partners and subcellular compartments. Here, using a new synthetic molecular interaction system, we show that translocation of a regulatory subunit of the protein kinase A (PKA-R) to the plasma membrane has a paradoxical effect on the membrane kinase activity. It can both enhance it at lower translocation levels, even in the absence of signaling inputs, and inhibit it at higher translocation levels, suggesting its role as a linker that can both couple and decouple signaling processes in a concentration-dependent manner. We further demonstrate that superposition of gradients of PKA-R abundance across single cells can control the directionality of cell migration, reversing it at high enough input levels. Thus complex in vivo patterns of PKA-R localization can drive complex phenotypes, including cell migration.


title: A neural circuit linking two sugar sensors regulates satiety-dependent fructose drive in Drosophila.

abstract: Ingestion of certain sugars leads to activation of fructose sensors within the brain of flies, which then sustain or terminate feeding behavior depending on internal state. Here, we describe a three-part neural circuit that links satiety with fructose sensing. We show that AB-FBl8 neurons of the Fan-shaped body display oscillatory calcium activity when hemolymph glycemia is high, and that these oscillations require synaptic input from SLP-AB neurons projecting from the protocerebrum to the asymmetric body. Suppression of activity in this circuit, either by starvation or genetic silencing, promotes specific drive for fructose ingestion. Moreover, neuropeptidergic signaling by tachykinin bridges fan-shaped body activity and Gr43a-mediated fructose sensing. Together, our results demonstrate how a three-layer neural circuit links the detection of two sugars to impart precise satiety-dependent control over feeding behavior.


title: Image-based deep learning reveals the responses of human motor neurons to stress and ALS

abstract: Although morphological attributes of cells and their substructures are recognized readouts of physiological or pathophysiological states, these have been relatively understudied in amyotrophic lateral sclerosis (ALS) research. In this study we integrate multichannel fluorescence high-content microscopy data with deep-learning imaging methods to reveal - directly from unsegmented images - novel neurite-associated morphological perturbations associated with (ALS-causing) VCP-mutant human motor neurons (MNs). Surprisingly, we reveal that previously unrecognized disease-relevant information is withheld in broadly used and often considered  generic biological markers of nuclei (DAPI) and neurons ({beta}III-tubulin). Additionally, we identify changes within the information content of ALS-related RNA binding protein (RBP) immunofluorescence imaging that is captured in VCP-mutant MN cultures. Furthermore, by analyzing MN cultures exposed to different extrinsic stressors, we show that heat stress recapitulates key aspects of ALS. Our study therefore reveals disease-relevant information contained in a range of both generic and more specific fluorescent markers, and establishes the use of image-based deep learning methods for rapid, automated and unbiased testing of biological hypotheses.