bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence and risk factors of unsuppressed viral load among pregnant and breastfeeding women in sub-Saharan Africa: analysis from population-based surveys
Authors: Schrubbe Leah A. , Stöckl Heidi , Hatcher Abigail M. , Marston Milly , Kuchukhidze Salome , Calvert Clara
Published: December 2022

Objective:

To examine the prevalence of viral suppression and risk factors for unsuppressed viral load among pregnant and breastfeeding women living with HIV (WLH).

Design:

Pooled analysis among pregnant and breastfeeding WLH from Population-Based HIV Impact Assessment (PHIA) cross-sectional surveys from 10 sub-Saharan African countries.

Methods:

Questionnaires included sociodemographic, relationship-related, and HIV-related items, while blood tests examined HIV serostatus and viral load (data collected 2015–2018). The weighted prevalence of viral suppression was calculated. Logistic regression was used to examine risk factors for unsuppressed viral load (≥1000 copies/ml).

Results:

Of 1685 pregnant or breastfeeding WLH with viral load results, 63.8% (95% confidence interval (CI): 60.8–66.7%) were virally suppressed at the study visit. Among all included women, adolescence (adjusted odds ratio (aOR): 4.85, 95% CI: 2.58–9.14, P < 0.001) and nondisclosure of HIV status to partner (aOR: 1.48, 95% CI: 1.02–2.14, P = 0.04) were associated with unsuppressed viral load. Among only partnered women, adolescence (aOR: 7.95, 95% CI: 3.32–19.06, P < 0.001), and lack of paid employment (aOR: 0.67, 95% CI: 0.47–0.94, P = 0.02) were associated with unsuppressed viral load. Examining only women on ART, nondisclosure of HIV status to partner (aOR: 1.85, 95% CI: 1.19–2.88, P = 0.006) was associated with unsuppressed viral load.

Conclusion:

Viral suppression among pregnant and breastfeeding WLH in sub-Saharan Africa remains suboptimal. Relationship dynamics around nondisclosure of HIV-positive status to partners was an important risk factor for unsuppressed viral load. Improving HIV care via sensitive discussions around partner dynamics in pregnant and breastfeeding women could improve maternal HIV outcomes and prevention of mother-to-child transmission of HIV (PMTCT).
Minimal theory of 3D vision: new approach to visual scale and visual shape
Authors: Linton Paul
Published: December 2022

Since Kepler and Descartes in the early-1600s, vision science has been committed to a triangulation model of stereo vision. But in the early-1800s, we realized that disparities are responsible for stereo vision. And we have spent the past 200 years trying to shoe-horn disparities back into the triangulation account. The first part of this article argues that this is a mistake, and that stereo vision is a solution to a different problem: the eradication of rivalry between the two retinal images, rather than the triangulation of objects in space. This leads to a ‘minimal theory of 3D vision’, where 3D vision is no longer tied to estimating the scale, shape, and direction of objects in the world. The second part of this article then asks whether the other aspects of 3D vision, which go beyond stereo vision, really operate at the same level of visual experience as stereo vision? I argue they do not. Whilst we want a theory of real-world 3D vision, the literature risks giving us a theory of picture perception instead. And I argue for a two-stage theory, where our purely internal ‘minimal’ 3D percept (from stereo vision) is linked to the world through cognition.

This article is part of a discussion meeting issue ‘New approaches to 3D vision’.
Prevalence of Hepatitis B Virus Surface Antigen (HBsAg) among the Out-patients in a Tertiary Institution in Nigeria.
Authors: Olayiwola John Olusola , LANLEHIN Folake Comfort
Published: December 2022

Hepatitis B virus (HBV) infection is considered to be the ninth leading cause of death and is one of the major public health problems in the world. The prevalence of hepatitis in Nigeria has been rated to be 8.3%. Hence, this study investigate the prevalence of hepatitis B virus infection in a tertiary institution in Oyo State. Informed consent were obtained from the out-patients attending institution clinics. The design was a cross-sectional study and questionnaires were administered to investigate their knowledge and attitude towards safer practices against the spread of HBV. The seroprevalence of the participants were examined with LabAcon rapid kit with 98.2% - 100% and 97.2% - 99.8 for specificity and sensitivity respectively. The population distribution was observed to 45 (90%) female and 5 (10%) male. The prevalence of the HBsAg was found to be 10%. The prevalence of HBsAg among female participants was 11.1%. The relationship between knowledge of HBV infection and sex was insignificant (0.546) however the relationship between knowledge of HBV infection and age was significant (0.004). The occurrence of HBV infection is still area of concern because of the possibility of the virus to spread. This spread could better be curtailed based on regular awareness about the infection.
An amino acid transporter AAT1 plays a pivotal role in chloroquine resistance evolution in malaria parasites
Authors: Amambua-Ngwa Alfred , Button-Simons Katrina A. , Li Xue , Kumar Sudhir , Brenneman Katelyn Vendrely , Ferrari Marco , Checkley Lisa A. , Haile Meseret T. , Shoue Douglas A. , McDew-White Marina , Tindall Sarah M. , Reyes Ann , Delgado Elizabeth , Dalhoff Haley , Larbalestier James K. , Amato Roberto , Pearson Richard D. , Taylor Alexander B. , Nosten François H. , D’Alessandro Umberto , Kwiatkowski Dominic , Cheeseman Ian H. , Kappe Stefan H. I. , Avery Simon V. , Conway David J. , Vaughan Ashley M. , Ferdig Michael T. , Anderson Timothy J. C.
Published: December 2022

Malaria parasites break down host hemoglobin into peptides and amino acids in the digestive vacuole for export to the parasite cytoplasm for growth: interrupting this process is central to the mode of action of several antimalarial drugs. Mutations in the chloroquine (CQ) resistance transporter,pfcrt, located in the digestive vacuole membrane, confer CQ resistance inPlasmodium falciparum, but typically affect parasite fitness. However, the role of other parasite loci in the evolution of CQ resistance is unclear. Here we use a combination of population genomics, genetic crosses and gene editing to demonstrate that a second vacuolar transporter plays a key role in both resistance and compensatory evolution. Longitudinal genomic analyses of the Gambian parasites revealed temporal signatures of selection on an amino acid transporter (pfaat1)S258Lvariant which increased from 0-87% in frequency between 1984 and 2014 in parallel withpfcrt1K76T. Parasite genetic crosses then identified a chromosome 6 quantitative trait locus containingpfaat1that is selected by CQ treatment. Gene editing demonstrated thatpfaat1S258Lpotentiates CQ-resistance but at a cost of reduced fitness, whilepfaat1F313S, a common Southeast Asian polymorphism, reduces CQ-resistance while restoring fitness. Our analyses reveal hidden complexity in CQ-resistance evolution, suggesting thatpfaat1may underlie regional differences in the dynamics of resistance evolution, and modulate parasite resistance or fitness by manipulating the balance between both amino acid and drug transport.
Meiotic and mitotic aneuploidies drive arrest of in vitro fertilized human preimplantation embryos
Authors: McCoy Rajiv C. , Summers Michael C. , McCollin Abeo , Ottolini Christian S. , Ahuja Kamal , Handyside Alan H.
Published: December 2022

The high incidence of aneuploidy in early human development, arising either from errors in meiosis or postzygotic mitosis, is the primary cause of pregnancy loss, miscarriage, and still birth following natural conception as well asin vitrofertilization (IVF). Preimplantation genetic testing for aneuploidy (PGT-A) has confirmed the prevalence of meiotic and mitotic aneuploidies among blastocyst-stage IVF embryos that are candidates for transfer. However, only about half of normally fertilized embryos develop to the blastocyst stagein vitro, while the others arrest at cleavage to late morula or early blastocyst stages. To achieve a more complete view of the impacts of aneuploidy, we applied a validated method of PGT-A to a large series (n = 909) of arrested embryos and trophectoderm biopsies. We then correlated observed aneuploidies with abnormalities of the first two cleavage divisions using time lapse imaging (n = 843). The combined incidence of meiotic and mitotic aneuploidies was strongly associated with blastocyst morphological grading, with the proportion ranging from 20% to 90% for the highest to lowest grades, respectively. In contrast, the incidence of aneuploidy among arrested embryos was exceptionally high (94%), dominated by mitotic aneuploidies affecting multiple chromosomes. In turn, these mitotic aneuploidies were strongly associated with abnormal cleavage divisions, such that 51% of abnormally dividing embryos possessed mitotic aneuploidies compared to only 23% of normally dividing embryos. We conclude that the combination of meiotic and mitotic aneuploidies drives arrest of human embryosin vitro, as development increasingly relies on embryonic gene expression at the blastocyst stage.
The Global Environment Facility approach for allocating biodiversity funding to countries
Authors: Mcowen Chris , Burgess Neil D. , Ash Neville , Baquero Andrea , Fonseca Gustavo , Harfoot Mike , Hilton-Taylor Craig , Kapos Val , Ravilious Corinna , Sayor Catherine , Tallowin Oliver , Teelucksingh Sonja Sabita , Weatherdon Lauren , Wyatt Sarah
Published: December 2022

Biodiversity is not evenly distributed across the globe and some areas have greater potential to contribute to biodiversity conservation than others. Whilst there are multiple ways to determine priority areas for conservation, for a global institution like the Global Environment Facility (GEF), the funding mechanism for the Convention on Biological Diversity and the largest multilateral source of funding for developing countries focused on enhancing biodiversity outcomes and promoting sustainable use, it is important to fund the top-ranked countries whilst also ensuring that all eligible countries are able to undertake some biodiversity conservation actions in accordance with the Convention. To this end, the GEF uses the System for Transparent Allocation of Resources (STAR) to allocate funding in separate funding rounds to eligible countries. This country focus means that all prioritization analyses need to be undertaken within that political framework, while also considering the intrinsic patterns in biodiversity that don’t respect national borders. We present the 2018 update of the biodiversity component of GEF-STAR, investigate how the weighting system affects the ranking of countries. We show that top ranked and bottom ranked countries are robust to changes in the weighting of analytical elements, but the weighting can significantly alter the importance of middle ranking countries, affecting their funding allocation. This analysis has been used by the GEF, along with other data, to allocate over $1 billion in biodiversity funding (GEF-7 = $1.2 billion) to improve country and global prospects for conservation. However, this large funding allocation for conservation needs to be set against the vastly larger funding flows that decrease natural values around the world, and the need for systems level change remains evident across the entire planet.
IIIandMe: An Algorithm for Chromosome-scale Haplotype Determination Using Genome-wide Variants of Three Haploid Reproductive Cells
Authors: Qu Han , Li Ruidong , Yu Lei , Chen Weiming , Feng Yuanfa , Jia Qiong , Traband Ryan , Wang Xuesong , Wang Shibo , He Luoxian , Wang Zixian , Qu Meng , Ferrante Sergio Pietro , Zhu Jianguo , Zhong Weide , Roose Mikeal , Jia Zhenyu
Published: December 2022

Our recent algorithm,Hapi, infers chromosome-scale haplotypes using genomic data of a small number of single gametes. Its advanced version,IIIandMe, is proposed here to achieve comparable phasing accuracy with as few as three gametes, pushing the analysis to its limit. The new method is validated with simulation and a citrus gamete dataset. The rapid advances in genotyping technologies promise a broad application ofIIIandMein disclosing important genetic information.
Use of clustering to improve estimation of epidemic model parameters under a Bayesian hierarchical framework
Authors: Alahakoon Punya , McCaw James M. , Taylor Peter G.
Published: December 2022

We study infectious disease outbreaks that have evolved in isolation without the influence of one another. If stochastic effects are identified within each outbreak, it is necessary to model the dynamics with stochastic epidemic models. However, the accuracy of the estimated model parameters depends on several factors including the statistical inference methodologies that are used. One approach to making inferences from multiple outbreak data is the use of a Bayesian hierarchical model. This statistical framework allows simultaneous inference for multiple outbreaks and the estimation of model parameters at a group level. A hierarchical model will generally provide improved estimates; however, we show that this is not always true when the variability among model parameter values of the outbreaks is high. We further show that subsets of outbreaks with similar parameter values can be identified prior to a hierarchical analysis using common clustering algorithms such as k-means. When hierarchical analyses are carried out for these pre-identified subsets of outbreaks, parameter estimates are improved compared to those estimated under a hierarchical analysis for the complete set of outbreaks. We have applied our estimation framework within a simulation-based experiment using synthetic data generated from stochasticSIRSmodels. The framework is generalizable to other biological data.
dgram2dmap: Extraction, visualisation and formatting of distance constraints from AlphaFold distograms
Authors: Wallner Björn , Amunts Alexey , Naschberger Andreas , Nystedt Björn , Mirabello Claudio
Published: December 2022

Distograms are data structures output by AlphaFold, along with the predicted 3D coordinates of the target protein, that encode predictions about Euclidean distances between pairs of amino acids. Although distograms are often overlooked, they do provide information that is to some extent complementary to that of the final 3D model. Here, we introduce dgram2dmap, a simple tool to convert distograms into distance maps that can be visualised and used in external tools for further downstream analyses. dgram2dmap runs within seconds to minutes, is open source and available on GitHub:https://github.com/clami66/dgram2dmap.
The function of environmentally acquired perfume blends in male orchid bees
Authors: Henske Jonas , Saleh Nicholas W. , Chouvenc Thomas , Ramírez Santiago R. , Eltz Thomas
Published: December 2022

Perfume making by male orchid bees is a remarkable behavior giving rise to an entire pollination syndrome in the neotropics. Male orchid bees concoct and store perfume mixtures in specialized hind-leg pockets using volatiles acquired from multiple environmental sources, including orchids. However, the precise function and ultimate causes of this behavior have remained elusive. We supplemented maleEuglossa dilemmareared from trap-nests with perfume loads harvested from wild conspecifics. In dual-choice experiments, males supplemented with perfumes mated with more females, and sired more offspring, than untreated, equal-aged, control males. Our results demonstrate that male-acquired perfumes function as chemical signals emitted during courtship and received by females when selecting mates. Sexual selection might be a key agent shaping the evolution of perfume signaling.

One-Sentence Summary

The possession of exogenous volatiles increase male mating success and paternity in orchid bees.
Cell composition inference and identification of layer-specific transcriptional profiles with POLARIS
Authors: Chen Jiawen , Luo Tianyou , Jiang Minzhi , Liu Jiandong , Gupta Gaorav P , Li Yun
Published: December 2022

Spatial transcriptomics (ST) technology, providing spatially resolved transcriptional profiles, facilitates advanced understanding of key biological processes related to health and disease. Sequencing-based ST technologies provide whole-transcriptome profiles, but are limited by the non-single cell level resolution. Lack of knowledge in the number of cells or cell type composition at each spot can lead to invalid downstream analysis, which is a critical issue recognized in ST data analysis. Methods developed, however, tend to under-utilize histological images, which conceptually provide important and complementary information including anatomical structure and distribution of cells. To fill in the gaps, we present POLARIS, a versatile ST analysis method that can perform cell type deconvolution, identify anatomical or functional layer-wise differentially expressed (LDE) genes and enable cell composition inference from histology images. Applied to four tissues, POLARIS demonstrates high deconvolution accuracy, accurately predicts cell composition solely from images, and identifies LDE genes that are biologically relevant and meaningful.
Statistical inference reveals the role of length, breathing, and nucleotide identity in V(D)J nucleotide trimming
Authors: Russell Magdalena L , Simon Noah , Bradley Philip , Matsen Frederick A
Published: December 2022

To appropriately defend against a wide array of pathogens, humans somatically generate highly diverse repertoires of B cell and T cell receptors (BCRs and TCRs) through a random process called V(D)J recombination. Receptor diversity is achieved during this process through both the combinatorial assembly of V(D)J-genes and the junctional deletion and insertion of nucleotides. While the Artemis protein is often regarded as the main nuclease involved in V(D)J recombination, the exact mechanism of nucleotide trimming is not understood. Using a previously-published TCRβrepertoire sequencing data set, we have designed a flexible probabilistic model of nucleotide trimming that allows us to explore various mechanistically-interpretable sequence-level features. We show that local sequence context and the capacity for sequence-breathing, together, can most accurately predict the trimming probabilities of a given V-gene sequence. This model suggests that double-stranded DNA needs to be able to “breathe” for trimming to occur, and provides evidence of a sequence motif that appears to get preferentially trimmed, independent of breathing. Further, we find that the inferred mechanistic coefficients from this model provide accurate prediction for V- and J-gene sequences from other adaptive immune receptor loci. These results refine our understanding of how the Artemis nuclease may function to trim nucleotides during V(D)J recombination and provide another step towards understanding how V(D)J recombination generates diverse receptors and supports a powerful, unique immune response in healthy humans.
Identification of a covert evolutionary pathway between two protein folds
Authors: Chakravarty Devlina , Sreenivasan Shwetha , Swint-Kruse Liskin , Porter Lauren L.
Published: December 2022

Although homologous protein sequences are expected to adopt similar structures, some amino acid substitutions can interconvert α-helices and β-sheets. Such fold switching may have occurred over evolutionary history, but supporting evidence has been limited by the: (1) abundance and diversity of sequenced genes, (2) quantity of experimentally determined protein structures, and (3) assumptions underlying the statistical methods used to infer homology. Here, we overcame these barriers by applying multiple statistical methods to a family of ~600,000 bacterial response regulator proteins. We found that their homologous DNA-binding subunits assume divergent structures: helix-turn-helix versus α-helix+β-sheet (winged helix). Phylogenetic analyses, ancestral sequence reconstruction, and AlphaFold2 models indicated that amino acid substitutions facilitated a switch from helix-turn-helix into winged helix. This structural transformation likely expanded DNA-binding specificity. Our approach uncovers an evolutionary pathway between two protein folds and provides methodology to identify secondary structure switching in other protein families.
Signatures of adaptive decreased virulence of deformed wing virus in an isolated population of wild honey bees (Apis mellifera)
Authors: Ray Allyson M. , Gordon Emma C. , Seeley Thomas D. , Rasgon Jason L. , Grozinger Christina M.
Published: December 2022

Understanding the ecological and evolutionary processes that drive host-pathogen interactions is critical for combating epidemics and conserving species. TheVarroa destructormite and deformed wing virus (DWV) are two synergistic threats to Western honey bee (Apis mellifera) populations across the globe. Distinct honey bee populations have been found to self-sustain despiteVarroainfestations, including colonies within the Arnot Forest outside Ithaca, NY, USA. We hypothesized that in these honey bee populations, DWV has been selected to produce an avirulent infection phenotype, allowing for the persistence of both host and disease-causing agents. To investigate this, we assessed the presence and titer of viruses in bees from the Arnot Forest and managed apiaries, and assessed genomic variation and virulence differences between DWV isolates. Across groups, we found viral abundance was similar, but viral genotypes were distinct. We also found that infections with viral isolates from the Arnot Forest resulted in higher survival and lower rates of symptomatic deformed wings, compared to analogous isolates from managed colonies, providing preliminary evidence to support the hypothesis of adaptive decreased viral virulence. Overall, this multi-level investigation of virus genotype and phenotype across different contexts reveals critical insight into global bee health and the ecological and evolutionary processes that drive host-pathogen interactions.
Single cell guided deconvolution of bulk transcriptomics recapitulates differentiation stages of acute myeloid leukemia and predicts drug response
Authors: Karakaslar E Onur , Severens Jeppe , Sánchez-López Elena , van Veelen Peter A , Zlei Mihaela , van Dongen Jacques JM , Otte Annemarie M. , Halkes Constantijn JM , van Balen Peter , Veelken Hendrik , Reinders Marcel JT , Griffioen Marieke , van den Akker Erik B
Published: December 2022

The diagnostic spectrum for AML patients is increasingly based on genetic abnormalities due to their prognostic and predictive value. However, information on the AML blast phenotype regarding their maturational arrest has started to regain importance due to its predictive power on drug responses. Here, we deconvolute 1350 bulk RNA-seq samples from five independent AML cohorts on a single-cell healthy BM reference and demonstrate that the morphological differentiation stage (FAB classification) could be faithfully reconstituted using estimated cell compositions (ECCs). Moreover, we show that the ECCs reliably predictex-vivodrug resistances as demonstrated for Venetoclax, aBCL-2inhibitor, resistance specifically in AML with CD14+ monocyte phenotype. We further validate these predictions using in-house proteomics data by showing thatBCL-2protein abundance is split into two distinct clusters for NPM1-mutated AML at the extremes of CD14+ monocyte percentages, which could be crucial for the Venetoclax dosing for these patients. Our results suggest that Venetoclax resistance predictions can also be extended to AML without recurrent genetic abnormalities (NOS), and possibly to MDS-related AML and secondary AML. Collectively, we propose a framework for allowing a joint mutation and maturation stage modeling that could be used as a blueprint for testing sensitivity for new agents across the various subtypes of AML.
3D multiplexed tissue imaging reconstruction and optimized region-of-interest (ROI) selection through deep learning model of channels embedding
Authors: Burlingame Erik , Ternes Luke , Lin Jia-Ren , Chen Yu-An , Kim Eun Na , Gray Joe W. , Santagata Sandro , Sorger Peter K. , Chang Young Hwan
Published: December 2022

Tissue-based sampling and diagnosis are defined as the extraction of information from certain limited spaces and its diagnostic significance of a certain object. Pathologists deal with issues related to tumor heterogeneity since analyzing a single sample does not necessarily capture a representative depiction of cancer, and a tissue biopsy usually only presents a small fraction of the tumor. Many multiplex tissue imaging platforms (MTIs) make the assumption that tissue microarrays (TMAs) containing small core samples of 2-dimensional (2D) tissue sections are a good approximation of bulk tumors although tumors are not 2D. However, emerging whole slide imaging (WSI) or 3D tumor atlases that employ MTIs like cyclic immunofluorescence (CyCIF) strongly challenge this assumption. In spite of the additional insight gathered by measuring the tumor microenvironment in WSI or 3D, it can be prohibitively expensive and time-consuming to process tens or hundreds of tissue sections with CyCIF. Even when resources are not limited, the criteria for region-of-interest (ROI) selection in tissues for downstream analysis remain largely qualitative and subjective as stratified sampling requires the knowledge of objects and evaluates their features. Despite the fact TMAs fail to adequately approximate whole tissue features, a theoretical subsampling of tissue exists that can best represent the tumor in the whole slide image. To address these challenges, we propose deep learning approaches to learn multi-modal image translation tasks from two aspects: 1) generative modeling approach to reconstruct 3D CyCIF representation and 2) co-embedding CyCIF image and Hematoxylin and Eosin (H&E) section to learn multi-modal mappings by a cross-domain translation for minimum representative ROI selection. We demonstrate that generative modeling enables a 3D virtual CyCIF reconstruction of a colorectal cancer specimen given a small subset of the imaging data at training time. By co-embedding histology and MTI features, we propose a simple convex optimization for objective ROI selection. We demonstrate the potential application of ROI selection and the efficiency of its performance with respect to cellular heterogeneity.
Demographic impacts of low- and high-intensity fire in a riparian savanna bird: implications for ecological fire management
Authors: Teunissen Niki , McAlpine Hamish , Cameron Skye F. , Murphy Brett P. , Peters Anne
Published: December 2022

Climate change is driving changes in fire frequency and intensity, making it more urgent for conservation managers to understand how species and ecosystems respond to fire. In tropical monsoonal savannas – Earth’s most fire-prone landscapes – ecological fire management aims to prevent intense wildfires late in the dry season through prescribed low-intensity fire early in the dry season. Riparian habitats embedded within tropical savannas represent critical refuges for biodiversity, yet are particularly sensitive to fire. Better understanding of the impact of fire – including prescribed burns – on riparian habitats is therefore key, but requires long-term detailed post-fire monitoring of species’ demographic rates, as effects may persist and/or be delayed.

Here, we quantify the multi-year impacts of prescribed low-intensity and high-intensity fire on the density, survival, reproduction and dispersal of the threatened western purple-crowned fairy-wren (Malurus coronatus coronatus), in an exceptionally well-studied individually-marked population.

Following low-intensity fire, bird density was reduced in the burnt compared to adjacent unburnt riparian habitat for at least 2.5 years. This was a result of reduced breeding success and recruitment for two years immediately following the fire, rather than mortality of adults or dispersal away from burnt habitat.

In contrast, a high-intensity fire (in a year with low rainfall) resulted in a sharp decline in population density 2-8 months after the fire, with no signs of recovery after 2.5 years. The decline in density was due to post-fire adult mortality, rather than dispersal. Breeding success of the (few) remaining individuals was low but not detectably lower than in unburnt areas, likely because breeding success was poor overall due to prevailing dry conditions.

Hence, even if there is no or very low mortality during fire, and no movement of birds away from burnt areas post-fire, both low- and high-intensity fire in the riparian zone result in reduced population density. However, the mechanism by which this occurs, and recovery time, differs with fire intensity. To minimise the impacts of fire on riparian zones in tropical savannas, we suggest employing low-intensity prescribed burns shortly after the breeding season in years with good rainfall.
Phantasus: web-application for visual and interactive gene expression analysis
Authors: Kleverov Maksim , Zenkova Daria , Kamenev Vladislav , Sablina Margarita , Artyomov Maxim N. , Sergushichev Alexey A.
Published: December 2022

Transcriptomic profiling became a standard approach to quantify a cell state, which led to accumulation of huge amount of public gene expression datasets. However, both reuse of these datasets or analysis of newly generated ones requires a significant technical expertise. Here we present Phantasus – a user-friendly web-application for interactive gene expression analysis which provide a streamlined access to more than 84000 public gene expression datasets, as well as allows analysis of user-uploaded datasets. Phantasus integrates an intuitive and highly interactive JavaScript-based heatmap interface with an ability to run sophisticated R-based analysis methods. Overall Phantasus allows to go all the way from loading, normalizing and filtering data to doing differential gene expression and downstream analysis. Phantasus can be accessed on-line athttps://ctlab.itmo.ru/phantasusorhttps://artyomovlab.wustl.edu/phantasusor can be installed locally from Bioconductor (https://bioconductor.org/packages/phantasus). Phantasus source code is available athttps://github.com/ctlab/phantasusunder MIT licence.
Transfer Learning for Neuroimaging via Re-use of Deep Neural Network Features
Authors: Holderrieth Peter , Smith Stephen , Peng Han
Published: December 2022

A major problem in the application of machine learning to neuroimaging is the technological variability of MRI scanners and differences in the subject populations across studies. Transfer learning (TL) attempts to alleviate this problem. TL refers to a family of methods which acquire knowledge from related tasks to improve generalization in the tasks of interest. In this work, we pre-train a deep neural network on UK Biobank MRI data on age and sex prediction, and study the predictions of the network on three small MRI data sets. We find that the neural networks can extract meaningful features from unseen data sets under the necessary but also sufficient condition that the network was pre-trained to predict the label of interest (e.g. pre-trained on age prediction if age prediction is the task of interest). Based on this, we propose a transfer learning pipeline which relies on the re-use of deep neural network features across data sets for the same tasks. We find that our method outperforms classical regression methods and training a network from scratch. In particular, we improve state-of-the-art results on age and sex prediction. Our transfer learning method may therefore provide a simple and efficient pipeline to achieve high performance on small MRI data sets.
NIT: an open-source tool for information theoretic analysis of neural population data
Authors: Maffulli Roberto , Casal Miguel A. , Celotto Marco , Zucca Stefano , Safaai Houman , Fellin Tommaso , Panzeri Stefano
Published: December 2022

Information theory provides a popular and principled framework for the analysis of neural data. It allows to uncover in an assumption-free way how neurons encode and transmit information, capturing both linear and non-linear coding mechanisms and including the information carried by interactions of any order. To facilitate its application, here we present Neuroscience Information Toolbox (NIT), a new toolbox for the accurate information theoretical analysis of neural data. NIT contains widely used tools such as limited sampling bias corrections and discretization of neural probabilities for the calculation of stimulus coding in low-dimensional representation of neural activity (e.g. Local Field Potentials or the activity of small neural population).Importantly, it adds a range of recent tools for quantifying information encoding by large populations of neurons or brain areas, for the directed transmission of information between neurons or areas, and for the calculation of Partial Information Decompositions to quantify the behavioral relevance of neural information and the synergy and redundancy among neurons and brain areas. Further, because information theoretic algorithms have been previously validated mainly with electrophysiological recordings, here we used realistic simulations and analysis of real data to study how to optimally apply information theory to the analysis of two-photon calcium imaging data, which are particularly challenging due to their lower signal-to-noise and temporal resolution. We also included algorithms (based on parametric and non-parametric copulas) to compute robustly information specifically with analog signals such as calcium traces. We provide indications on how to best process calcium imaging traces and to apply NIT depending on the type of calcium indicator, imaging frame rate and firing rate levels. In sum, NIT provides a toolbox for the comprehensive and effective information theoretic analysis of all kinds of neural data, including calcium imaging.
Site-directed placement of three-dimensional DNA origami
Authors: Martynenko Irina , Erber Elisabeth , Ruider Veronika , Dass Mihir , Posnjak Gregor , Yin Xin , Altpeter Philipp , Liedl Tim
Published: December 2022

Assembling hybrid substrates with nanometer-scale precision and molecular addressability enables advances in such distant fields as material research and biosensing. As such, the combination of lithographic methods with 2D DNA origami self-assembly [1–4] has led, among others, to the development of photonic crystal cavity arrays [2] and the exploration of sensing nanoarrays where molecular devices are patterned on the sub-micron scale [5–7]. Here we extend this concept to the third dimension through mounting 3D DNA origami onto nano-patterned substrates followed by silicification [8, 9] to provide mechanical and chemical stability. Our versatile and scalable method relying on self-assembly at ambient temperatures offers the potential to 3D-position any inorganic and organic components that are compatible with DNA architectures [10–13]. This way, complex and 3D-patterend surfaces designed on the molecular level while reaching macroscopic dimensions could supersede energy-intensive manufacturing steps in substrate processing.
Using machine learning to detect coronaviruses potentially infectious to humans
Authors: Gonzalez-Isunza Georgina , Jawaid M. Zaki , Liu Pengyu , Cox Daniel L. , Vazquez Mariel , Arsuaga Javier
Published: December 2022

Establishing the host range for novel viruses remains a challenge. Here, we address the challenge of identifying non-human animal coronaviruses that may infect humans by creating an artificial neural network model that learns from the binding of the spike protein of alpha and beta coronaviruses to their host receptor. The proposed method produces a human-Binding Potential (h-BiP) score that distinguishes, with high accuracy, the binding potential among human coronaviruses. Two viruses, previously unknown to bind human receptors, were identified: Bat coronavirus BtCoV/133/2005 (a MERS related virus) andRhinolophus affiniscoronavirus isolate LYRa3 a SARS related virus. We further analyze the binding properties of these viruses using molecular dynamics. To test whether this model can be used for surveillance of novel coronaviruses, we re-trained the model on a set that excludes SARS-COV-2 viral sequences. The results predict the binding of SARS-CoV-2 with a human receptor, indicating that machine learning methods are an excellent tool for the prediction of host expansion events.
Efficacy and safety of emapalumab in macrophage activation syndrome
Authors: De Benedetti Fabrizio , Grom Alexei A , Brogan Paul , Bracaglia Claudia , Pardeo Manuela , Marucci Giulia , Eleftheriou Despina , Papadopoulou Charalampia , Schulert Grant S , Quartier Pierre , Antón Jordi , Laveille Christian , Frederiksen Rikke , Asnaghi Veronica , Ballabio Maria , Jacqmin Philippe , de Min Cristina
Published: December 2022

Objectives

Macrophage activation syndrome (MAS) is a severe, life-threatening complication of systemic juvenile idiopathic arthritis (sJIA) and adult onset Still’s disease (AOSD). The objective of this study was to confirm the adequacy of an emapalumab dosing regimen in relation to interferon-γ (IFNγ) activity by assessing efficacy and safety. The efficacy outcome was MAS remission by week 8, based on clinical and laboratory criteria.

Methods

We studied emapalumab, a human anti–IFNγ antibody, administered with background glucocorticoids, in a prospective open-label, single-group trial involving patients who had MAS secondary to sJIA or AOSD and had previously failed high-dose glucocorticoids. The study foresaw 4-week treatment that could be shortened or prolonged based on investigator’s assessment of response. Patients could enter a long-term (12 months) follow-up study.

Results

Fourteen patients received emapalumab. All patients completed the trial, entered the long-term follow-up and were alive at the end of the follow-up. The investigated dosing regimen, based on an initial loading dose followed by maintenance doses, was appropriate, as shown by rapid neutralisation of IFNγ activity, demonstrated by prompt decrease in serum C-X-C motif chemokine ligand 9 (CXCL9) levels. By week 8, remission of MAS was achieved in 13 of the 14 patients at a median time of 25 days. Viral infections and positive viral tests were observed during the trial and during the long-term follow-up.

Conclusions

Neutralisation of IFNγ with emapalumab was efficacious in inducing remission of MAS secondary to sJIA or AOSD in patients who had failed high-dose glucocorticoids.

KEY MESSAGES

What is already known on this topic?

Macrophage activation syndrome (MAS) is a severe and potentially life-threatening complication of systemic juvenile idiopathic arthritis and adult-onset Still’s disease. There are no therapeutic options that have been prospectively investigated in MAS. Data in animal models andex vivodata from humans with MAS led to the hypothesis that interferon-γ (IFNγ) has a pathogenic role in MAS.

What does this study add?

This open-label multicentre trial using emapalumab, an anti–IFNγ antibody, in patients who have failed to respond to high-dose glucocorticoids, demonstrates that IFNγ has a pathogenic role in MAS and that its neutralisation leads to MAS remission.

How might this affect research, clinical practice or policy?

The results of this study show that neutralisation of IFNγ with emapalumab is a therapeutic option for patients with severe MAS who have failed standard of care with high-dose glucocorticoids.
PaleoProPhyler: a reproducible pipeline for phylogenetic inference using ancient proteins
Authors: Patramanis Ioannis , Ramos-Madrigal Jazmín , Cappellini Enrico , Racimo Fernando
Published: December 2022

Ancient proteins from fossilized or semi-fossilized remains can yield phylogenetic information at broad temporal horizons, in some cases even millions of years into the past. In recent years, peptides extracted from archaic hominins and long-extinct mega-fauna have enabled unprecedented insights into their evolutionary history. In contrast to the field of ancient DNA - where several computational methods exist to process and analyze sequencing data - few tools exist for handling ancient protein sequence data. Instead, most studies rely on loosely combined custom scripts, which makes it difficult to reproduce results or share methodologies across research groups. Here, we present PaleoProPhyler: a new fully reproducible pipeline for aligning ancient peptide data and subsequently performing phylogenetic analyses. The pipeline can not only process various forms of proteomic data, but also easily harness genetic data in different formats (CRAM, BAM, VCF) and translate it, allowing the user to create reference panels for phyloproteomic analyses. We describe the various steps of the pipeline and its many functionalities, and provide some examples of how to use it. PaleoProPhyler allows researchers with little bioinformatics experience to efficiently analyze palaeoproteomic sequences, so as to derive insights from this valuable source of evolutionary data.
Anomalous diffusion ofE. coliunder microfluidic confinement and chemical gradient
Authors: Raza Md Ramiz , George Jijo Easo , Kumari Savita , Mitra Mithun K , Paul Debjani
Published: December 2022

We report a two-layer microfluidic device to study the combined effect of confinement and chemical gradient on the motility of wild typeE. coli. We track individualE. coliin 50μmand 10μmwide channels, with a channel height of 2.5μm, to generate quasi-2D conditions. We find that contrary to expectations, bacterial trajectories are super-diffusive even in absence of a chemical (glucose) gradient. The superdiffusive behaviour becomes more pronounced on introduction of a chemical gradient or on strengthening the lateral confinement. Runlength distributions for weak confinement in absence of chemical gradients follow an exponential distribution. Both confinement and chemoattraction induce deviations from this behaviour, with the runlength distributions approaching a power-law form under these conditions. Both confinement and chemoattraction suppress large angle tumbles as well. Our results suggest that wild-typeE. colimodulates both its runs and tumbles in a similar manner under physical confinement and chemical gradient.
Characterisation of a TatA/TatB binding site on the TatC component of theEscherichia colitwin arginine translocase
Authors: Severi Emmanuele , Batista Mariana Bunoro , Lannoy Adelie , Stansfeld Phillip J. , Palmer Tracy
Published: December 2022

The twin arginine transport (Tat) pathway exports folded proteins across the cytoplasmic membranes of prokaryotes and the thylakoid membranes of chloroplasts. InEscherichia coliand other Gram-negative bacteria, the Tat machinery comprises TatA, TatB and TatC components. A Tat receptor complex, formed from all three proteins, binds Tat substrates, which triggers receptor organisation and recruitment of further TatA molecules to form the active Tat translocon. The polytopic membrane protein TatC forms the core of the Tat receptor and harbours two binding sites for the sequence-related TatA and TatB proteins. A ‘polar’ cluster binding site, formed by TatC transmembrane helices (TMH) 5 and 6 is occupied by TatB in the resting receptor and exchanges for TatA during receptor activation. The second binding site, lying further along TMH6 is occupied by TatA in the resting state, but its functional relevance is unclear. Here we have probed the role of this second binding site through a programme of random and targeted mutagenesis. Characterisation of three stably produced TatC variants, P221R, M222R and L225P, each of which is inactive for protein transport, demonstrated that the substitutions did not affect assembly of the Tat receptor. Moreover, the substitutions that we analysed did not abolish TatA or TatB binding to either binding site. Using targeted mutagenesis we introduced bulky substitutions into the TatA binding site. Molecular dynamics simulations and crosslinking analysis indicated that TatA binding at this site was substantially reduced by these amino acid changes, however TatC retrained function. While it is not clear whether TatA binding at the TMH6 site is essential for Tat activity, the isolation of inactivating substitutions indicate that this region of the protein has a critical function.
The impact of narcissism, self-confidence and auditor’s characteristics on audit report readability
Authors: Salehi Mahdi , Dalwai Tamanna , Arianpoor Arash
Published: December 2022

Purpose

The present study aims to assess the impact of narcissism, self-confidence and auditor's characteristics on audit report readability for companies listed on the Tehran Stock Exchange.

Design/methodology/approach

The study’s statistical population comprises firms listed on the Tehran Stock Exchange. The present research used a systematic elimination method, and 1,162 firm-year observations were obtained for seven years from 2012 to 2018. Three variables including auditor tenure, audit fee and audit specialization are used for measuring auditing features. The Fog index is used as a proxy for measuring audit report readability. In addition, in this paper, four regressions, including fixed effects, random effects, pooled and T+1, are used to estimate reliable coefficients.

Findings

The findings show a negative and significant relationship between auditor’s characteristics (tenure, fee and specialization) and audit report readability. Moreover, the variables of the auditor’s narcissism, self-confidence and mandatory auditor change have a positive and significant association with audit report readability. This study lends support to the theories of personality disorder and behavioral decision.

Originality/value

Since narcissism and self-confidence are two characteristics that shape an individual’s character and personality, some involved behavioral factors in auditors’ characteristics contribute to their decisions. The effects of these should be detected to enhance the decision-making process. The said factors significantly impact audit report readability. Hence, this paper attempts to assess the effect of the said factors on audit report readability.
Understanding and preserving Indigenous agricultural knowledge: a suggested way forward for future research
Authors: Radcliffe Chris , Parissi Cesidio
Published: December 2022

Purpose

Indigenous farmers have, for centuries, applied practices which maintained resilient and sustainable landscapes. Thus, understanding and preserving the agricultural knowledge of Indigenous farmers may enhance the knowledge base of sustainable agriculture. The purpose of this paper is to review current research in the fields of Indigenous knowledge and sustainability to present a research approach which enables a cohesive global way forward for future research projects seeking to understand and preserve Indigenous agricultural knowledge.

Design/methodology/approach

This study applied thematic analysis to review 57 research studies in the field of Indigenous knowledge and sustainability. Key themes were identified from four overarching criteria: research methodology, data input, output and outcomes.

Findings

The findings revealed a range of commonalities among the 57 research studies reviewed. This study proposes the research should continue to seek to understand and preserve Indigenous knowledge, however, research needs to go beyond simply documenting Indigenous knowledge. The way forward requires research of Indigenous agricultural knowledge to establish databases, digital repositories (including oral, video, visual) and online repositories with globally shared access, whilst acknowledging and acting in partnership with Indigenous farmers and their communities.

Originality/value

To the best of the authors’ knowledge, this is an original study which has practical implications for enhancing research outcomes with regard to preservation of Indigenous knowledge. The findings of this study may be used to influence research policy formulation and implementation.