bluuebunny/crossref_metadata_2025_split huggingface dataset:
Demuxafy: Improvement in droplet assignment by integrating multiple single-cell demultiplexing and doublet detection methods
Authors: Neavin Drew , Senabouth Anne , Hang Lee Jimmy Tsz , Ripoll Aida ,   sc-eQTLGen Consortium, Franke Lude , Prabhakar Shyam , Ye Chun Jimmie , McCarthy Davis J. , Melé Marta , Hemberg Martin , Powell Joseph E. 
Published: March 2022

AbstractRecent innovations in droplet-based single-cell RNA-sequencing (scRNA-seq) have provided the technology necessary to investigate biological questions at cellular resolution. With the ability to assay thousands of cells in a single capture, pooling cells from multiple individuals has become a common strategy. Droplets can subsequently be assigned to a specific individual by leveraging their inherent genetic differences, and numerous computational methods have been developed to address this problem. However, another challenge implicit with droplet-based scRNA-seq is the occurrence of doublets - droplets containing two or more cells. The inaccurate assignment of cells to individuals or failure to remove doublets contribute unwanted noise to the data and result in erroneous scientific conclusions. Therefore, it is essential to assign cells to individuals and remove doublets accurately. We present a new framework to improve individual singlet classification and doublet removal through a multi-method intersectional approach.We developed a framework to evaluate the enhancement in donor assignment and doublet removal through the consensus intersection of multiple demultiplexing and doublet detecting methods. The accuracy was assessed using scRNA-seq data of ∼1.4 million peripheral blood mononucleated cells from 1,034 unrelated individuals and ∼90,000 fibroblast cells from 81 unrelated individuals. We show that our approach significantly improves droplet assignment by separating singlets from doublets and classifying the correct individual compared to any single method. We show that the best combination of techniques varies under different biological and experimental conditions, and we present a framework to optimise cell assignment for a given experiment. We offer Demuxafy (https://demultiplexing-doublet-detecting-docs.readthedocs.io/en/latest/index.html) - a framework built-in Singularity to provide clear, consistent documentation of each method and additional tools to simplify and improve demultiplexing and doublet removal. Our results indicate that leveraging multiple demultiplexing and doublet detecting methods improves accuracy and, consequently, downstream analyses in multiplexed scRNA-seq experiments.
The impact of SNP density on quantitative genetic analyses of body size traits in a wild population of Soay sheep
Authors: James Caelinn , Pemberton Josephine M. , Navarro Pau , Knott Sara 
Published: March 2022

AbstractUnderstanding the genetic architecture underpinning quantitative traits in wild populations is pivotal to understanding the processes behind trait evolution. The ‘animal model’ is a popular method for estimating quantitative genetic parameters such as heritability and genetic correlation and involves fitting an estimate of relatedness between individuals in the study population. Genotypes at genome-wide markers can be used to estimate relatedness; however, relatedness estimates vary with marker density, potentially affecting results. Increasing density of markers is also expected to increase the power to detect quantitative trait loci (QTL). In order to understand how the density of genetic markers affects the results of quantitative genetic analyses, we estimated heritability and performed genome-wide association studies (GWAS) on five body size traits in an unmanaged population of Soay sheep using two different SNP densities: a dataset of 37,037 genotyped SNPs, and an imputed dataset of 417,373 SNPs. Heritability estimates did not differ between the two SNP densities, but the high-density imputed SNP dataset revealed four new SNP-trait associations that were not found with the lower density dataset, as well as confirming all previously-found QTL. We also demonstrated that fitting fixed and random effects in the same step as performing GWAS is a more powerful approach than pre-correcting for covariates in a separate model.
Emergence of integrated information at macro timescales in real neural recordings
Authors: Leung A , Tsuchiya N 
Published: March 2022

AbstractHow a system generates conscious experience remains an elusive question. One approach towards answering this is to consider the information available in the system from the perspective of the system itself. Integrated information theory (IIT) proposes a measure to capture this, integrated information (Φ). While Φ can be computed at any spatiotemporal scale, IIT posits that it be applied at the scale at which the measure is maximised. Importantly, Φ should emerge to be maximal not at the smallest spatiotemporal scale, but at some macro scale where system elements or timesteps are grouped into larger elements or timesteps. Emergence in this sense has been demonstrated in artificial binary systems, but it remains unclear whether it occurs in real neural recordings which are generally continuous and noisy. Here we first utilise a computational model to confirm that Φ becomes maximal at the temporal scales underlying its generative mechanisms. Second, we search for emergence in local field potentials from the fly brain recorded during wakefulness and anaesthesia, finding that normalised Φ (wake/anaesthesia), but not raw Φ values, peaks at 5 ms. Lastly, we extend our model to investigate why raw Φ values themselves did not peak. This work extends the application of Φ to simple artificial systems consisting of logic gates towards searching for emergence of a macro spatiotemporal scale in real neural systems.
Predictability and Stability Testing to Assess Clinical Decision Instrument Performance for Children After Blunt Torso Trauma
Authors: Kornblith Aaron E. , Singh Chandan , Devlin Gabriel , Addo Newton , Streck Christian J. , Holmes James F. , Kuppermann Nathan , Grupp-Phelan Jacqueline , Fineman Jeffrey , Butte Atul J. , Yu Bin 
Published: March 2022

ABSTRACTObjectiveThe Pediatric Emergency Care Applied Research Network (PECARN) has developed a clinical-decision instrument (CDI) to identify children at very low risk of intra-abdominal injury. However, the CDI has not been externally validated. We sought to vet the PECARN CDI with the Predictability Computability Stability (PCS) data science framework, potentially increasing its chance of a successful external validation.Materials & MethodsWe performed a secondary analysis of two prospectively collected datasets: PECARN (12,044 children from 20 emergency departments) and an independent external validation dataset from the Pediatric Surgical Research Collaborative (PedSRC; 2,188 children from 14 emergency departments). We used PCS to reanalyze the original PECARN CDI along with new interpretable PCS CDIs we developed using the PECARN dataset. External validation was then measured on the PedSRC dataset.ResultsThree predictor variables (abdominal wall trauma, Glasgow Coma Scale Score <14, and abdominal tenderness) were found to be stable. Using only these variables, we developed a PCS CDI which had a lower sensitivity than the original PECARN CDI on internal PECARN validation but performed the same on external PedSRC validation (sensitivity 96.8% and specificity 44%).ConclusionThe PCS data science framework vetted the PECARN CDI and its constituent predictor variables prior to external validation. In this case, the PECARN CDI with 7 predictors, and our PCS-based CDI with 3 stable predictors, had identical performance on independent external validation. This suggests that both CDIs will generalize well to new populations, offering a potential strategy to increase the chance of a successful (costly) prospective validation.
Genetic overlap between mood instability and alcohol-related phenotypes suggests shared biological underpinnings
Authors: Icick Romain , Shadrin Alexey , Holen Børge , Karadag Naz , Lin Aihua , Hindley Guy , O’Connell Kevin , Frei Oleksandr , Bahrami Shahram , Høegh Margrethe Collier , Cheng Weiqiu , Fan Chun C. , Djurovic Srdjan , Dale Anders M. , Lagerberg Trine Vik , Smeland Olav B. , Andreassen Ole A. 
Published: March 2022

ABSTRACTAlcohol use disorder (AUD) is a pervasive and devastating mental illness with high comorbidity rates with other mental disorders. We aimed to characterize the sharedvs. unique polygenicity of AUD, alcohol consumption (AC) and mood instability (MOOD), a relevant transdiagnostic factor, using large genome-wide association studies (GWASs) data. We hypothesize that cross-analyzing these phenotypes would shed light on their unique and shared polygenicity, increase our knowledge regarding the genetic basis of the comorbidity between AUD and mood disorders, and boost discovery for jointly-associated loci. Summary statistics for MOOD, AC and AUD GWASs (Ns =363,705; 200,680 and 200,004; respectively) were analysed to characterize the cross-phenotype associations between MOOD and AC, MOOD and AUD and AC and AUD, respectively. To do so, we used a newly-established pipeline that combines (i) the bivariate causal mixture model (MiXeR) to quantify the cross-phenotype polygenic overlap and (ii) the conjunctional false discovery rate (conjFDR) to discover specific jointly-associated genomic loci. These loci were functionally characterized and mapped to genes and biological functions. We also performed validation in independent samples and phenotypic analyses. MOOD was highly polygenic (10,400 single nucleotide polymorphisms, SNPs) compared to AC and AUD (4,900 SNPs, SD =600 and 4,300 SNPs, SD =2,000; respectively). The polygenic overlap of MOOD and AC was much larger than that of MOOD and AUD (98%vs. 49%) and genetic correlation was opposite (−0.2vs. 0.23), which was confirmed in independent samples. MOOD&AUD causal SNPs were significantly enriched for brain genes, conversely to MOOD&AC. Among 38 loci identified in the joint analysis, sixteen were novel for MOOD, AC and AUD. Similarly distinct patterns were evidenced for SNP localization, function and previous GWAS associations outside of the phenotypes that were currently studied. MOOD, AC and AUD were also strongly associated at the phenotypic level. Overall, using multilevel polygenic quantification, joint loci discovery and functional annotation methods, we evidenced that the polygenic overlap between MOOD and AC/AUD implicated shared biological underpinnings but clearly distinct functional patterns between MOOD&AC and MOOD&AUD. Using the MOOD endophenotype, the current study suggests new mechanisms for the comorbidity of AUD with mood disorders.
Spectral imaging enables contrast agent-free real-time ischemia monitoring in laparoscopic surgery
Authors: Ayala Leonardo , Adler Tim J. , Seidlitz Silvia , Wirkert Sebastian , Engels Christina , Seitel Alexander , Sellner Jan , Aksenov Alexey , Bodenbach Matthias , Bader Pia , Baron Sebastian , Vemuri Anant , Wiesenfarth Manuel , Schreck Nicholas , Mindroc Diana , Tizabi Minu , Pirmann Sebastian , Everitt Brittaney , Kopp-Schneider Annette , Teber Dogu , Maier-Hein Lena 
Published: March 2022

ABSTRACTLaparoscopic surgery has evolved as a key technique for cancer diagnosis and therapy. While characterization of the tissue perfusion is crucial in various procedures, such as partial nephrectomy, doing so by means of visual inspection remains highly challenging. Spectral imaging takes advantage of the fact that different tissue components have unique optical properties to recover relevant information on tissue function such as ischemia. However, clinical success stories for advancing laparoscopic surgery with spectral imaging are lacking to date. To address this bottleneck, we developed the first laparoscopic real-time multispectral imaging (MSI) system featuring a compact and lightweight multispectral camera and the possibility to complement the conventional RGB (Red, Green, and Blue) surgical view of the patient with functional information at a video rate of 25 Hz. To account for the high inter-patient variability of human tissue, we phrase the problem of ischemia detection as an out-of-distribution (OoD) detection problem that does not rely on data from any other patient. Using an ensemble of invertible neural networks (INNs) as a core component, our algorithm computes the likelihood of ischemia based on a short (several seconds) video sequence acquired at the beginning of each surgery. A first-in-human trial performed on 10 patients undergoing partial nephrectomy demonstrates the feasibility of our approach for fully-automatic live ischemia monitoring during laparoscopic surgery. Compared to the clinical state-of-the-art approach based on indocyanine green (ICG) fluorescence, the proposed MSI-based method does not require the injection of a contrast agent and is repeatable if the wrong segment has been clamped. Spectral imaging combined with advanced deep learning-based analysis tools could thus evolve as an important tool for fast, efficient, reliable and safe functional imaging in minimally invasive surgery.
Molecular profiling of XPO1 inhibitor and gemcitabine-nab-paclitaxel combination in cellular and LSL-Kras G12D/+; Trp53 fl/+; Pdx1-Cre (KPC) pancreatic cancer model
Authors: Uddin Md. Hafiz , Aboukameel Amro , Li Yiwei , Khan Husain Yar , Sexton Rachel E. , Bannoura Sahar , Dyson Gregory , Al-Hallak Mohammad Najeeb , Mzannar Yosef , Mohamed Amr , Landesman Yosef , Kim Steve , Beydoun Rafic , Mohammad Ramzi M. , Shields Anthony F. , Azmi Asfar S. 
Published: March 2022

AbstractThe majority of pancreatic ductal adenocarcinoma (PDAC) patients experience disease progression while on treatment with gemcitabine and nab-Paclitaxel (GemPac) treatment indicating the need for more effective combinations for this recalcitrant disease.Earlier we showed that nuclear exporter protein exportin 1 (XPO1) is a valid therapeutic target in PDAC and the selective inhibitor of nuclear export (SINE) selinexor (Sel), synergistically enhances the efficacy of GemPac in pancreatic cancer cells, spheroids, patient derived tumors and had promising activity in a phase I study in patients with PDAC. Here we investigated the mechanisms of synergy by molecular profiling of Sel or Sel-GemPac treated PDAC cells,in vitroand by utilizing genetically modified LSL-Kras G12D/+; Trp53 fl/+; Pdx1-Cre (KPC) mouse model.In KPC model, Sel given with GemPac at a sub-MTD dose enhanced the survival compared to controls (p< 0.05). Molecular analysis of residual KPC tumors showed re-organization of tumor stromal architecture, suppression of proliferation and nuclear retention of tumor suppressors. Single cell nuclear RNA sequencing (snRNAseq) revealed significant loss of cellular clusters in the Sel-GemPac treated mice including CD44 stem cell population. RNA-seq, Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) analysis showed inhibition of several tumor promoting molecules.Prioritized RNA-seq identified molecules were validated inin vitroor in the PDAC patient samples through siRNA mediated silencing, quantitative gene expression, cytotoxicity assays and confirmed their role in observed synergy. Sel or Sel-GemPac caused broad penetration in PDAC supporting signaling networks.
Repeat Detector: versatile sizing of expanded tandem repeats and identification of interrupted alleles from targeted DNA sequencing
Authors: Taylor Alysha S. , Barros Dinis , Gobet Nastassia , Schuepbach Thierry , McAllister Branduff , Aeschbach Lorene , Randall Emma L. , Trofimenko Evgeniya , Heuchan Eleanor R. , Barszcz Paula , Ciosi Marc , Morgan Joanne , Hafford-Tear Nathaniel J. , Davidson Alice E. , Massey Thomas H. , Monckton Darren G. , Jones Lesley ,   REGISTRY Investigators of the European Huntington’s disease network, Xenarios Ioannis , Dion Vincent 
Published: March 2022

AbstractTargeted DNA sequencing approaches will improve how the size of short tandem repeats is measured for diagnostic tests and pre-clinical studies. The expansion of these sequences causes dozens of disorders, with longer tracts generally leading to a more severe disease. Interrupted alleles are sometimes present within repeats and can alter disease manifestation. Determining repeat size mosaicism and identifying interruptions in targeted sequencing datasets remains a major challenge. This is in part because standard alignment tools are ill-suited for repetitive and unstable sequences. To address this, we have developed Repeat Detector (RD), a deterministic profile weighting algorithm for counting repeats in targeted sequencing data. We tested RD using blood-derived DNA samples from Huntington’s disease and Fuchs endothelial corneal dystrophy patients sequenced using either Illumina MiSeq or Pacific Biosciences single-molecule, real-time sequencing platforms. RD was highly accurate in determining repeat sizes of 609 blood-derived samples from Huntington’s disease individuals and did not require prior knowledge of the flanking sequences. Furthermore, RD can be used to identify alleles with interruptions and provide a measure of repeat instability within an individual. RD is therefore highly versatile and may find applications in the diagnosis of expanded repeat disorders and the development of novel therapies.
mPPases create a conserved anionic membrane fingerprint as identified via multi-scale simulations
Authors: Holmes Alexandra O. M. , Goldman Adrian , Kalli Antreas C. 
Published: March 2022

AbstractMembrane-integral pyrophosphatases (mPPases) are membrane-bound enzymes responsible for hydrolysing inorganic pyrophosphate and translocating a cation across the membrane. Their function is essential for the infectivity of clinically relevant protozoan parasites and plant maturation. Recent developments have indicated that their mechanism is more complicated than previously thought and that the membrane environment may be important for their function. In this work, we use multiscale molecular dynamics simulations to demonstrate for the first time that mPPases form specific anionic lipid interactions at 4 sites at the distal and interfacial regions of the protein. These interactions are conserved in simulations of the mPPases from Thermotoga maritima, Vigna radiata and Clostridium leptum and characterised by interactions with positive residues on helices 1, 2, 3 and 4 for the distal site, or 9, 10, 13 and 14 for the interfacial site. Due to the importance of these helices in protein stability and function, these lipid interactions may play a crucial role in the mPPase mechanism and enable future structural and functional studies.Author summaryIn this work we have been able to demonstrate conservation of lipid-interaction sites on proteins from distinct species that deviated from their evolutionary common ancestors a long time ago, as in the case of the membrane-integral pyrophosphatases from a thermophilic bacteria species and a plant species studied here. This retention of a common lipid interaction profile or “fingerprint” and our ability to predict this for other proteins in this family may indicate that they are more integral to protein function than previously thought. By identifying lipid interactions that may act to stabilise the protein structure, these properties could be exploited to gain protein structures, and the interfacial site’s potential involvement in inter-subunit communication may be useful for further investigation of the catalytic cycle of this clinically relevant membrane protein family.
Multiple carotenoid-based signals are enhanced despite poor body condition in urban male and female Northern Cardinals (Cardinalis cardinalis)
Authors: Baldassarre Daniel T. , Bedell Haley S. , Drzewiecki Kristie M. , Goodman Brooke D. , Mills Mya L. , Ramos Denis A. 
Published: March 2022

ABSTRACTIf humans aim to sustainably coexist with wildlife, we must understand how our activity impacts the communication systems of urban animal populations. We know much about the effects of anthropogenic noise on bird song, but relatively little about how avian visual signals are affected by urbanization. One way such an effect may occur if urbanization alters the food available to species with color based on carotenoids, which they must obtain from their diet. Over three years, we compared a comprehensive suite of visual signals in male and female Northern Cardinals (Cardinalis cardinals) in a rural and an urban population. We predicted that urban birds would have enhanced carotenoid-based signals as they likely have access to more carotenoids from invasive plants, especially honeysuckle (Lonicera spp.), that thrive in cities. We used reflectance spectrometry, digital image analyses, and avian visual models to quantify hue, saturation, and brightness of chest (male), underwing (female), and bill (male and female) signals. Compared to rural males, urban males had redder chest feathers in one year and redder bills in every year. Urban females had more saturated underwing color than rural females in every year. These color differences were sufficient to be distinguished by the avian visual system. Urbanization did not affect female bill color. Interestingly, urban birds had significantly reduced mass-related body condition compared to rural birds. These results show that both male and female urban birds can display enhanced carotenoid-based signals despite being in relatively poor condition. The consequences of this color enhancement are unknown, but it could affect the information content of the signals and the dynamics of the social and mating systems. These results stand in stark contrast to the predominant trend in birds of decreased color in urban areas and highlight the complex and varied potential effects of urbanization on animal communication.