Miracle-dz/UniFAR-FTUs huggingface dataset:
Big Data Reproducibility: Applications in Brain Imaging and Genomics

Reproducibility, the ability to replicate analytical ﬁndings, is a prerequisite for both scientiﬁc discovery and clinical utility. Troublingly, we are in the midst of a reproducibility crisis, in which many investigations fail to replicate. Although many believe that these failings are due to misunderstanding or misapplication of statistical inference (e.g., p-values or the dichotomization of “statistically signiﬁcant”), we believe the shortcomings arise much earlier in the data science workﬂow, at the level of measurement, including data acquisition and reconstruction. A key to reproducibility is that multiple measurements of the same item (e.g., experimental sample or clinical participant) are similar to one another, while they are dissimilar from other items. The intra-class correlation coefﬁcient ( ICC ) quantiﬁes reproducibility in this way, but only for univariate (one dimensional) data, while relying on Gaussian assumptions for validity. In contrast, big data is multivariate (high-dimensional), non-Gaussian, and often non-Euclidean (including text, images, speech, and networks), rendering ICC inadequate. We propose a novel statistic, discriminability , which quantiﬁes the degree to which individual samples are similar to one another, without restricting the data to be univariate, Gaussian, or even Euclidean. We then introduce the possibility of optimizing experimental design via increasing discriminability. We prove that optimizing discriminability yields an improved ability to use the data for subsequent inference tasks, without specifying the inference task a priori . We then apply this approach three different datasets: a brain imaging dataset built by the “Consortium for Reliability and reproducibility” which consists of 28 disparate magnetic resonance imaging datasets, and two genomics datasets. Discriminability is the only statistic that, by optimizing according to it, improves performance on all subsequent inference tasks for each dataset, despite that they were not considered in the optimization. We therefore suggest that designing experiments and analyses to optimize discriminability may be a crucial step in solving the reproducibility crisis.
Genome-wide association study of plasma lipids

There is continuous interest in the genetic determinants of plasma triglycerides (TGs) and phospholipids and their role in the etiology of cardiovascular disease (CVD). Here, we report the results of a Dutch genome wide association study (GWAS) of an in-house developed lipidomics platform, focusing on 90 plasma lipids. Lipids were assessed by liquid chromatography mass spectrometry in participants from the Leiden Longevity Study, the Netherlands Twin Register and the Erasmus Rucphen Family (ERF) study and meta-analysed, resulting in a sample size of 5537 participants. In addition, we performed genetic correlation analyses between the 90 plasma lipids and markers of metabolic health, as well as vascular pathology and CVD combining our GWAS results with publicly available GWAS outputs. We replicated previously known associations between 34 lipids and 10 lipid quantitative trait loci (lipQTL) (GCKR, APOA1, FADS1, SGPP1,TMEM229B, LIPC, PDXDC1, CETP, CERS4 and SPTLC3) with metabolome-wide (P < 1.61 × 10−9) significance. Moreover, we report 6 novel phospholipid-related and 5 triglyceride (TG)-related loci: SGGP1 (SM21:0), SPTLC3 (SM21:0 and SM25:1), FADS1 (LPCO16:1, PC38:2, PEO36:5, PEO38:5, TG56:5, TG56:6, and TG56:7), TMEM229 (LPCO16:1), GCKR (TG50:2), and APOA1 (TG54:4). In addition, we report suggestively significant (P < 5 × 10−8) associations mapping to eleven novel lipQTLs, three of which are supported by mining previous GWAS data: MAU (PC34:4), LDLR (SM16:0), and MLXIPL (TG48:1 and TG50:1)). The other loci failed to replicate. Genetic correlation analysis indicated that one specific sphingomyelin, SM22:0, shared common genetic background with CVD. Levels of SM22:0 also positively associated with carotid artery intima-media thickness in the ERF study, and this observation was independent of LDL-C level. Our findings yield higher resolution of plasma lipid species and new insights in the biology of circulating phosholipids and their relation to CVD risk.
On-site integrated production of cellulases and β-glucosidases by Trichoderma reesei Rut C30 using steam-pretreated sugarcane bagasse

The high cost of commercial cellulases still hampers the economic competitiveness of the production of fuels and chemicals from lignocellulosic biomasses. This cost may be decreased by the on-site production of cellulases with the integrated use of the lignocellulosic biomass as carbon source. This integrated approach was evaluated in the present study whereby steam-pretreated sugarcane bagasse (SPSB) was used as carbon source for the production of cellulases by Trichoderma reesei Rut C30 and the produced enzymes were subsequently used for SPSB hydrolysis. An enzyme preparation with a high cellulase activity, of 1.93 FPU/mL, was obtained, and a significant β-glucosidase activity was achieved in buffered media, indicating the importance of pH control during enzyme production. The hydrolysis of SPSB with the laboratory-made mixture resulted in a glucose yield of 80%, which was equivalent to those observed for control experiments using commercial enzymes. Even though the supplementation of this mixture with external β-glucosidase from Aspergillus awamori was found to increase the initial hydrolysis rates, it had no impact on the final hydrolysis yield. It was shown that SPSB is a promising carbon source for the production of cellulases and β-glucosidases by T. reesei Rut C30 and that the enzyme preparation obtained is effective for the hydrolysis of SPSB, supporting the on-site integrated approach to decrease the cost of the enzymatic hydrolysis of lignocellulosic biomass.
Improving replicability in single-cell RNA-Seq cell type discovery with Dune

Single-cell transcriptome sequencing (scRNA-Seq) has allowed many new types of investigations at unprecedented and unique levels of resolution. Among the primary goals of scRNA-Seq is the classification of cells into potentially novel cell types. Many approaches build on the existing clustering literature to develop tools specific to single-cell applications. However, almost all of these methods rely on heuristics or user-supplied parameters to control the number of clusters identified. This affects both the resolution of the clusters within the original dataset as well as their replicability across datasets. While many recommendations exist to select these tuning parameters, most of them are quite ad hoc. In general, there is little assurance that any given set of parameters will represent an optimal choice in the ever-present trade-off between cluster resolution and replicability. For instance, it may be the case that another set of parameters will result in more clusters that are also more replicable, or in fewer clusters that are also less replicable. Here, we propose a new method called Dune for optimizing the trade-off between the resolution of the clusters and their replicability across datasets. Our method takes as input a set of clustering results on a single dataset, derived from any set of clustering algorithms and associated tuning parameters, and iteratively merges clusters within partitions in order to maximize their concordance between partitions. As demonstrated on a variety of scRNA-Seq datasets from different platforms, Dune outperforms existing techniques, that rely on hierarchical merging for reducing the number of clusters, in terms of replicability of the resultant merged clusters. It provides an objective approach for identifying replicable consensus clusters most likely to represent common biological features across multiple datasets.
Ecological Representations

Cognitive science has three main motivations for claiming that cognition requires representation; the need for intentional access to the world, poverty of perceptual access to that world, and the need to support ‘higher-order’ cognition. In addition to these motivations, all representational systems must address two major problems: symbol grounding and system-detectable error. Here we argue that James J Gibson’s ecological information fits the basic definition of a representation, solves both problems and immediately addresses the first two motivations. We then develop an argument (begun in Golonka, 2015) that informational representations and the resulting neural representations can also support ‘higher-order’ cognition and provides an ecological framework for understanding neural activity. Ecological psychology can be a complete theory of cognition, and the key is the way that information represents the world.
Distinct functions of tissue-resident and circulating memory Th2 cells in allergic airway disease

Memory CD4+ T helper type 2 (Th2) cells are critical in driving allergic asthma pathogenesis, yet the mechanisms whereby tissue-resident memory Th2 cells (Th2 Trm) and circulating memory Th2 cells collaborate in vivo remain unclear. Here, using a house dust mite (HDM) model of allergic asthma and parabiosis, we demonstrate that Th2 Trm and circulating memory Th2 cells perform non-redundant functions in vivo. Upon HDM re-challenge, circulating memory Th2 cells trafficked into the lung parenchyma and ignited perivascular inflammation to promote eosinophil and CD4+ T cell recruitment. In contrast, Th2 Trm proliferated near airways and promoted mucus metaplasia, airway hyper-responsiveness, and airway eosinophil activation. Transcriptional analysis revealed that Th2 Trm and circulating memory Th2 cells share a core Th2 gene signature, but also exhibit distinct transcriptional profiles. Specifically, Th2 Trm express a tissue adaptation signature, including genes involved in regulating and interacting with extracellular matrix. Our findings demonstrate that Th2 Trm and circulating memory Th2 cells are functionally and transcriptionally distinct subsets with unique roles in promoting allergic airway disease. SUMMARY How memory Th2 cell subsets orchestrate allergic airway inflammation remains unclear. Rahimi et al. use a murine model of allergic asthma and parabiosis to demonstrate that tissue-resident and circulating memory Th2 cells are functionally distinct subsets with unique roles in promoting allergic airway disease.
Dual Energy X-ray Absorptiometry (DEXA) as a longitudinal outcome measure of cancer-related muscle wasting in mice

Introduction Pancreatic ductal adenocarcinoma (PDAC) is notorious for its associated skeletal muscle wasting (SMW) and mortality. Currently, the relationships between PDAC, SMW, and survival are poorly understood. Thus, there is a great need for a faithful small animal model with a quantitative longitudinal outcome measure that recapitulates clinical PDAC, to define SMW onset and assess progression. Therefore, we aimed to validate dual energy X-ray absorptiometry (DEXA) as a longitudinal outcome of lean body mass, and demonstrate its utility to quantify SMW in the KCKO murine model of PDAC. Methods In vivo body composition of: 1) untreated mice at 5, 8, 12, 18, and 22 weeks of age (n=4), and 2) a cohort of mice with (n=20) and without PDAC (n=10), was determined via DEXA, and lean mass of the lower hind limbs was predicted via a region of interest analysis by two independent observers. Total body weight was determined. Tibialis anterior (TA) muscles were weighed and processed for histomorphometry immediately post-mortem. Statistical differences between groups were assessed using t-tests and ANOVA. Linear regression models and correlation analysis were used to measure the association between TA and DEXA mass, and reproducibility of DEXA was quantified via the intraclass correlation coefficient (ICC). Results Lean mass in growing untreated mice determined by DEXA correlated with TA mass (r2 = 0.94; p <0.0001) and body weight (r2 = 0.89; p <0.0001). DEXA measurements were highly reproducible between observers (ICC = 0.95; 95% CI: 0.89-0.98). DEXA and TA mass also correlated in the PDAC cohort (r2 = 0.76; p <0.0001). Significant SMW in tumor-bearing mice was detected within 38 days of implantation by DEXA, TA mass, and histomorphometry. Conclusions DEXA is a longitudinal outcome measure of lower limb lean mass in mice. The KCKO syngeneic model is a bona fide model of PDAC-associated SMW that can be quantified with longitudinal DEXA.
Physiological variation reflects bioclimatic differences in the Drosophila americana species complex

Disentangling the selective factors shaping adaptive trait variation is an important but challenging task. Many studies—especially in Drosophila—have documented trait variation along latitudinal or altitudinal clines, but frequently lack resolution about specific environmental gradients that could be causal selective agents, and often do not investigate covariation between traits simultaneously. Here we examined variation in multiple macroecological factors across geographic space and their associations with variation in three physiological traits (desiccation resistance, UV resistance, and pigmentation) at both population and species scales, to address the role of abiotic environment in shaping trait variation.Using environmental data from collection locations of three North American Drosophila species—D. americana americana, D. americana texana and D. novamexicana—we identified two primary axes of macroecological variation; these differentiated species habitats and were strongly loaded for precipitation and moisture variables. In nine focal populations (three per species) assayed for each trait, we detected significant species-level variation for both desiccation resistance and pigmentation, but not for UV resistance. Species-level trait variation was consistent with differential natural selection imposed by variation in habitat water availability, although patterns of variation differed between desiccation resistance and pigmentation, and we found little evidence for pleiotropy between traits.Our multi-faceted approach enabled us to identify potential agents of natural selection and examine how they might influence the evolution of multiple traits at different evolutionary scales. Our findings highlight that environmental factors influence functional trait variation in ways that can be complex, and point to the importance of studies that examine these relationships at both population- and species-levels.
Functional delineation of tissue-resident CD8+ T cell heterogeneity during infection and cancer

Unremitting defense against diverse pathogens and malignancies requires a dynamic and durable immune response. Tissue-resident memory CD8+ T cells (Trm) afford robust protection against infection and cancer progression through continuous surveillance of non-lymphoid tissues. Here, we provide insight into how Trm confer potent and persistent immunity through partitioning of distinct cellular subsets differing in longevity, effector function, and multipotency. Antigen-specific CD8+ T cells localized to the epithelium of the small intestine are primarily comprised of a shorter-lived effector population most prominent early following both acute viral and bacterial infections, and a longer-lived Id3hi Trm population that subsequently accumulates at later memory timepoints. We define regulatory gene-programs driving these distinct Trm states, and further clarify roles for Blimp1, T-bet, Id2, and Id3 in supporting and maintaining intestinal Trm heterogeneity during infection. Further, through single-cell RNAseq analysis we demonstrate that tumor-infiltrating lymphocytes broadly differentiate into discrete populations of short-lived and long-lived Trm-like subsets, which share qualities with terminally-exhausted and progenitor-exhausted cells, respectively. As the clinical relevance of Trm continues to widen from acute infections to settings of chronic inflammation and malignancy, clarification of the spectrum of phenotypic and functional states exhibited by CD8+ T cells that reside in non-lymphoid tissues will provide a framework for understanding their regulation and identity in diverse pathophysiological contexts.
Molecular mechanism of regulation of the purine salvage enzyme XPRT by the alarmones pppGpp, ppGpp, and pGpp

The alarmones pppGpp and ppGpp mediate starvation response and maintain purine homeostasis to protect bacterial species. Xanthine phosphoribosyltransferase (XPRT) is a purine salvage enzyme that produces the nucleotide XMP from PRPP and xanthine. Combining structural, biochemical and genetic analyses, we show that pppGpp and ppGpp, as well as a third putative alarmone pGpp, all directly interact with XPRT and inhibit XPRT activity by competing with its substrate PRPP. Structural analysis reveals that ppGpp binds the PRPP binding motif within the XPRT active site. This motif is present in another (p)ppGpp target, the purine salvage enzyme HPRT, suggesting evolutionary conservation in different enzymes. However, XPRT oligomeric interaction is distinct from HPRT in that XPRT forms a symmetric dimer with two (p)ppGpp binding sites at the dimer interface. This results in two distinct regulatory features. First, XPRT cooperatively binds (p)ppGpp with a Hill coefficient of 2. Also, XPRT displays differential regulation by the alarmones as it is potently inhibited by both ppGpp and pGpp, but only modestly by pppGpp. Lastly, we demonstrate that the alarmones are necessary for protecting GTP homeostasis against excess environmental xanthine in Bacillus subtilis, suggesting that regulation of XPRT is key for regulating the purine salvage pathway.
Fidgetin-like 2 is a novel negative regulator of axonal growth and can be targeted to promote functional nerve regeneration after injury

The microtubule (MT) cytoskeleton plays a critical role in axon growth and guidance. Here, we identify the MT severing enzyme fidgetin-like 2 (FL2) as a negative regulator of axonal regeneration and a potential therapeutic target for promoting neural regeneration after injury. Genetic knockout of FL2 in cultured adult dorsal root ganglion (DRG) neurons resulted in longer axons and attenuated growth cone retraction in response to inhibitory molecules. Given the axonal growth-promoting effects of FL2 depletion in vitro, we tested whether the enzyme could be targeted to promote regeneration in a rodent model of peripheral nerve injury. In the model used in our experiments, the cavernous nerves (CN) are either crushed or transected, mimicking nerve injury caused by radical prostatectomy (RP). As with patients, CN injury results in erectile dysfunction, for which there are presently poor treatment options. At the time of injury, FL2-siRNA or control-siRNA was applied to the site using nanoparticles or chondroitin sulfate microgels as delivery agents. Treatment significantly enhanced functional nerve recovery, as determined by cavernosometry (measurements of corporal blood pressure in response to electrostimulation of the nerve). Remarkably, following complete bilateral nerve transection, visible and functional nerve regeneration was observed in 7 out of 8 animals treated with FL2-siRNA. In contrast, no control-siRNA treated animals showed regeneration. These observations suggest a novel therapeutic approach to treat peripheral nerve injury, particularly injuries resulting from surgical procedures such as RP, where treatments depleting FL2 could be applied locally at the time of injury.
Hypercluster: a python package and SnakeMake pipeline for flexible, parallelized 5 unsupervised clustering optimization

28 Unsupervised clustering is a common and exceptionally useful tool for large 29 biological datasets. However, clustering requires upfront algorithm and hyperparameter 30 selection, which can introduce bias into the final clustering labels. It is therefore 31 advisable to obtain a range of clustering results from multiple models and 32 hyperparameters, which can be cumbersome and slow. To streamline this process, we 33 present hypercluster, a python package and SnakeMake pipeline for flexible and 34 parallelized clustering evaluation and selection. Hypercluster is available on bioconda;
In plants distal regulatory sequences overlap with unmethylated rather than low-methylated regions, in contrast to mammals

Background DNA methylation is an important factor in the regulation of gene expression and genome stability. High DNA methylation levels are associated with transcriptional repression. In mammalian systems, unmethylated, low methylated and fully methylated regions (UMRs, LMRs, and FMRs, respectively) can be distinguished. UMRs are associated with proximal regulatory regions, while LMRs are associated with distal regulatory regions. Although DNA methylation is mainly limited to the CG context in mammals, while it occurs in CG, CHG and CHH contexts in plants, UMRs and LMRs were expected to occupy similar genomic sequences in both mammals and plants. Results This study investigated major model and crop plants such as Arabidopsis thaliana, tomato (Solanum lycopersicum), rice (Oryza sativa) and maize (Zea mays), and shows that plant genomes can also be subdivided in UMRs, LMRs and FMRs, but that LMRs are mainly present in the CHG context rather than the CG context. Strikingly, the identified CHG LMRs were enriched in transposable elements rather than regulatory regions. Maize candidate regulatory regions overlapped with UMRs. LMRs were enriched for heterochromatic histone modifications and depleted for DNase accessibility and H3K9 acetylation. CHG LMRs form a distinct, abundant cluster of loci, indicating they have a different role than FMRs. Conclusions Both mammalian and plant genomes can be segmented in three distinct classes of loci, UMRs, LMRs and FMRs, indicating similar underlying mechanisms. Unlike in mammals, distal regulatory sequences in plants appear to overlap with UMRs instead of LMRs. Our data indicate that LMRs in plants have a different function than those in mammals.
Evaluating institutional open access performance: Methodology, challenges and assessment

Open Access to research outputs is becoming rapidly more important to the global research community and society. Changes are driven by funder mandates, institutional policy, grass-roots advocacy and culture change. It has been challenging to provide a robust, transparent and updateable analysis of progress towards open access that can inform these interventions, particularly at the institutional level. Here we propose a minimum reporting standard and present a large-scale analysis of open access progress across 1,207 institutions world-wide that shows substantial progress being made. The analysis detects responses that coincide with policy and funding interventions. Among the striking results are the high performance of Latin American and African universities, particularly for gold open access, whereas overall open access levels in Europe and North America are driven by repository-mediated access. We present a top-100 of global universities with the world’s leading institutions achieving around 80% open access for 2017 publications.
Extended amygdala-parabrachial circuits alter threat assessment to regulate feeding

An animal’s evolutionary success depends on the ability to seek and consume foods while avoiding environmental threats. However, how evolutionarily conserved threat detection circuits modulate feeding is unknown. In mammals, feeding and threat assessment are strongly influenced by the parabrachial nucleus (PBN), a structure that responds to threats and inhibits feeding. Here, we report that the PBN receives dense inputs from the bed nucleus of the stria terminalis (BNST), an extended amygdala structure that encodes affective information. Using a series of complementary approaches, we identify opposing BNST-PBN circuits that modulate a genetically-defined population of PBN neurons to control feeding. This previously unrecognized neural circuit integrates threat assessment with the intrinsic drive to eat.