bluuebunny/crossref_metadata_2025 huggingface dataset:
Macroscopic label-free biomedical imaging with shortwave infrared Raman scattering
Authors: Arús Bernardo A. , Yiu Joycelyn , Lingg Jakob G. P. , Hofmann Anja , Fumo Amy R. , Ji Honglei , Jethwa Carolin , Park Roy K. , Henderson James , Mishra Kanuj , Mukha Iuliia , Stiel Andre C. , Santovito Donato , Weber Christian , Reeps Christian , Rohm Maria , Bartelt Alexander , Valdez Tulio A. , Chmyrov Andriy , Bruns Oliver T.
Published: June 2024

Shortwave infrared (SWIR) imaging provides enhanced tissue penetration and reduced autofluorescence in clinical and pre-clinical applications. However, existing applications often lack the ability to probe chemical composition and molecular specificity without the need for contrast agents. Here, we present a SWIR imaging approach that visualizes spontaneous Raman scattering with remarkable chemical contrast deep within tissue across large fields of view. Our results demonstrate that Raman scattering overcomes autofluorescence as the predominant source of endogenous tissue background at illumination wavelengths as short as 892 nm. We highlight the versatility of SWIR Raman imaging throughin vivomonitoring of whole-body tissue composition dynamics and non-invasive detection of fatty liver disease in mice, and identification of calcification and lipids in unfixed human atherosclerotic plaques. Moreover, our approach facilitates the visualization of nerves embedded in fatty tissue, a major advancement for surgical applications. With a simple wide-field setup orthogonal to fluorescence, SWIR Raman imaging holds promise for rapid adoption by clinicians and biologists. This technique opens new possibilities for contrast agent-free visualization of pathophysiology in whole animals and intraoperative imaging in humans.

Graphical abstract
Cross-modality representation and multi-sample integration of spatially resolved omics data
Authors: Li Zhen , Cui Xuejian , Chen Xiaoyang , Gao Zijing , Liu Yuyao , Pan Yan , Chen Shengquan , Lv Hairong , Zhai Lei , Jiang Rui
Published: June 2024

Spatially resolved sequencing technologies have revolutionized our understanding of biological regulatory processes within the microenvironment by accessing the states of genomic regions, genes and proteins as well as spatial coordinates of cells. However, discrepancies between different modalities and samples hinder the analysis of spatial omics data, necessitating the development of advanced computational methods. In this article, we propose PRESENT, an effective and scalable contrastive learning framework, for the cross-modality representation and multi-sample integration of spatial multi-omics, epigenomics and transcriptomics data. Through comprehensive experiments on spatial datasets, PRESENT demonstrates superior performance across various species, tissues, and technologies. Specifically, PRESENT effectively integrates spatial dependency and omics information simultaneously, facilitating the detection of spatially functional domains and the exploration of biological regulatory mechanisms. Furthermore, PRESENT can be extended for the integrative analysis of tissue samples across different dissected regions or developmental stages, promoting the identification of hierarchical structures from systematic and spatiotemporal perspectives.
SAMPLE: an R package to estimate sampling effort for species’ occurrence rates
Authors: Bravo Henrique , Ben Chehida Yacine , van der Meij Sancia E.T.
Published: June 2024

Species’ occurrence rates are the backbone of many ecological studies. Sampling of species occurrence, however, can come with challenges and might prove more difficult than anticipated. Logistical difficulties, limited funds or time, elusiveness or rarity of species and difficult sampling environments are all examples of scenarios that might contribute to (undesired) small sample sizes. In order to help circumvent some of these difficulties and uncertainties, we presentSAMPLE, anRpackage that aims to inform the user whether the amount of sampling conducted is enough to accurately estimate the occurrence rate of species. We use a simulation approach to help verify the accuracy of the package and to help guide the user in choosing the most appropriate values for the available parameters. Moreover, we provide a real data set where we usedSAMPLEto estimate the occurrence rate of various coral-dwelling species on their hosts and the minimum number of samples required for an accurate estimation. This provided example data set includes closely related host species, single or multiple symbionts on a single host coral taxon, and data points obtained from different depths to illustrate how occurrence rates can vary depending on the provided input. Due to its simplicity and easiness of use, this package allows for users to run it whilst in the field to estimate if sampling is sufficient or if the sampling approach needs to be adapted for a particular species. We hope that this package proves itself useful to users that need to estimate occurrence or prevalence rates of species and do not always have the possibility to obtain large sample sizes.
Proteolytic Performance is Dependent on Binding Efficiency, Processivity and Turnover: Single Protease Insights
Authors: Sørensen Emily Winther , Reinhold Freya Björk , Faber Andreas , Bender Steen , Kaestel-Hansen Jacob , de Sparra Lundin Jeannette , Voutyritsa Errika , Hedegaard Per , Christensen Sune M. , Hatzakis Nikos S.
Published: June 2024

Proteases are essential enzymes for a plethora of biological processes and biotechnological applications, e.g., within the dairy, pharmaceutical, and detergent industries. Decoding the molecular level mechanisms that drive protease performance is key to designing improved biosolutions. However, direct dynamic assessment of the fundamental partial reactions of substrate binding and activity has proven a challenge with conventional ensemble approaches. We developed a single-molecule (SM) assay for the direct and parallel recording of the stochastic binding interaction of Savinase, a serine-type protease broadly employed in biotechnology, with casein synchronously with monitoring proteolytic degradation of the substrate. SM recordings enabled us to determine how the overall activity of Savinase and two mutants relies on binding efficiency, enzymatic turnover and activity per binding event. Analysis of residence times revealed three characteristic binding states. Mutations were found to dominantly alter the likelihood of sampling the long lived state, with lifetimes longer than 30 seconds, indicating this state contributes to overall activity and supporting a level of processivity for Savinase. This observation challenges conventional expectations, as the protease has no characterized substrate binding site, or binding domain, aside from the active site. These insights, inaccessible through conventional assays, offer new perspectives for engineering proteases with improved hydrolytic performance.
Prediction of gene cluster function based on transcriptional regulatory networks uncovers a novel locus required for desferrioxamine B biosynthesis
Authors: Augustijn Hannah E. , Reitz Zachary L. , Zhang Le , Boot Jeanine A. , Elsayed Somayah S. , Challis Gregory L. , Medema Marnix H. , van Wezel Gilles P.
Published: June 2024

Bacteria produce a plethora of natural products that are in clinical, agricultural and biotechnological use. Genome mining revealed millions of biosynthetic gene clusters (BGCs) that encode their biosynthesis, and the major challenge is to predict the bioactivities of the molecules these BGCs specify, and how to elicit their expression. Here, we present an innovative strategy whereby we harness the power of regulatory networks combined with global gene expression patterns to predict BGC functions. Studying the regulon of iron master regulator DmdR1 inStreptomyces coelicolorcombined with co-expression data and large-scale comparative genome analysis identified the noveldesJGHgene cluster. Mutational and metabolomics analysis showed thatdesJGHis required for biosynthesis of the clinical drug desferrioxamine B. DesJGH thereby dictate the balance between the structurally distinct desferrioxamines B and E. We propose regulation-based genome mining as a promising approach to functionally prioritize BGCs to accelerate the discovery of novel bioactive molecules.
Tuning the stability of DNA tetrahedra with base-stacking interactions
Authors: Punnoose Jibin Abraham , Cole Dadrian , Melfi Tristan , Morya Vinod , Madhanagopal Bharath Raj , Chen Alan A. , Vangaveti Sweta , Chandrasekaran Arun Richard , Halvorsen Ken
Published: June 2024

DNA nanotechnology relies on programmable anchoring of regions of single-stranded DNA through base pair hybridization to create nanoscale objects such as polyhedra, tubes, sheets, and other desired shapes. Recent work from our lab measured the energetics of base-stacking interactions and suggested that terminal stacking interactions between two adjacent strands could be an additional design parameter for DNA nanotechnology. Here, we explore that idea by creating DNA tetrahedra held together with sticky ends that contain identical base pairing interactions but different terminal stacking interactions. Testing all 16 possible combinations, we found that the melting temperature of DNA tetrahedra varied by up to 10 °C from altering a single base stack in the design. These results can inform stacking design to control DNA tetrahedra stability in a substantial and predictable way. To that end, we show that a 4 bp sticky end with weak terminal stacking does not form stable tetrahedra, while strengthening the stacks confers high stability with a 46.8 ± 1.2 °C melting temperature, comparable to a 6 bp sticky end with weak stacking (49.7 ± 2.9 °C). The results likely apply to other types of DNA nanostructures and suggest that terminal stacking interactions play an integral role in formation and stability of DNA nanostructures.
Monitoring macrophage polarization with gene expression reporters and bioluminescence phasor analysis
Authors: Tedeschi Giulia , Navarro Mariana X. , Scipioni Lorenzo , Sondhi Tanvi K. , Prescher Jennifer A. , Digman Michelle A.
Published: June 2024

Macrophages exhibit a spectrum of behaviors upon activation and are generally classified as one of two types: inflammatory (M1) or anti-inflammatory (M2). Tracking these phenotypes in living cells can provide insight into immune function, but remains a challenging pursuit. Existing methods are mostly limited to static readouts or difficult to employ for multiplexed imaging in complex 3D environments while maintaining cellular resolution. We aimed to fill this void using bioluminescent technologies. Here we report genetically engineered luciferase reporters for long-term monitoring of macrophage polarization via spectral phasor analysis. M1- and M2-specific promoters were used to drive the expression of bioluminescent enzymes in macrophage cell lines. The readouts were multiplexed and discernable in both 2D and 3D formats with single cell resolution in living samples. Collectively, this work expands the toolbox of methods for monitoring macrophage polarization and provides a blueprint for monitoring other multifaceted networks in heterogeneous environments.
Generalization of the Packing Parameter for Quantifying the Morphology of Peptide Amphiphile Micelles
Authors: Kruse Luke E. , Ulery Bret D. , Hammond Karl D.
Published: June 2024

We present a quantitative means for classifying the shape of molecular dynamics simulated peptide amphiphile micelles (PAMs) that is both consistent with existing metrics and extendable to estimating shape-dependent free energy contributions. The presented framework not only outlines an approach for characterizing the shape of simulated PAMs but also presents expressions that can readily be applied to quantify the shape of particles from experimental techniques where aspect ratios are measured. The generalization of the packing parameter introduces a characteristic length that, when applied to simulated PAMs, functions intuitively as an effective radius for a PAM whose core is a perfect sphere or an infinite cylinder. The presented shape assignment scheme is used to develop a model for the free energy penalty associated with packing the tails of the amphiphiles into a core whose shape is modeled by an ellipsoid. Good agreement with previous models and scaling behaviors is observed and the importance of accounting for the shape and size dependence of the core is illustrated.

TOC Graphic
Evaluation of Machine Learning Models for Aqueous Solubility Prediction in Drug Discovery
Authors: Xue Nian , Zhang Yuzhu , Liu Sensen
Published: June 2024

Determining the aqueous solubility of the chemical compound is of great importancein-silicodrug discovery. However, correctly and rapidly predicting the aqueous solubility remains a challenging task. This paper explores and evaluates the predictability of multiple machine learning models in the aqueous solubility of compounds. Specifically, we apply a series of machine learning algorithms, including Random Forest, XG-Boost, LightGBM, and CatBoost, on a well-established aqueous solubility dataset (i. e., the Huuskonen dataset) of over 1200 compounds. Experimental results show that even traditional machine learning algorithms can achieve satisfactory performance with high accuracy. In addition, our investigation goes beyond mere prediction accuracy, delving into the interpretability of models to identify key features and understand the molecular properties that influence the predicted outcomes. This study sheds light on the ability to use machine learning approaches to predict compound solubility, significantly shortening the time that researchers spend on new drug discovery.
Atrioventricular nodal reentrant tachycardia onset, sustainability, and spontaneous termination in rabbit atrioventricular node model with autonomic nervous system control
Authors: Ryzhii Maxim , Ryzhii Elena
Published: June 2024

Atrioventricular nodal reentrant tachycardia (AVNRT) is one of the most common types of paroxysmal supraventricular tachycardia. The autonomic nervous system (ANS) activity is known to affect sudden episodes of AVNRT, but the detailed underlying mechanism is not fully understood. In this work, we update our recent compact multifunctional model of the rabbit atrioventricular node (AV) with ANS control to simulate AVNRT. The refractoriness of model cells is modulated by one ANS coefficient, causing a change in the effective refractory periods, conduction delays, and intrinsic frequency of pacemaker cells. Using the model, we examine the onset, sustainability, and spontaneous termination of typical slow-fast and atypical fast-slow forms of AVNRT under ANS modulation. The conditions for the onset and sustainability of AVNRT can occur independently of each other in various combinations. Differences in the effective refractory periods of the slow and fast pathways of the AV node during anterograde and retrograde conduction determine the form of AVNRT. For the first time, the possibility of identifying hidden processes occurring inside the AV node using a computer model is shown, allowing us to come closer to understanding the role of ANS control during AVNRT. The results obtained are consistent with clinical and experimental data and represent a new tool for studying the electrophysiological mechanisms of this type of arrhythmia.
Exome Sequencing of 963 Chinese Families Identifies Novel Epilepsy Candidate Genes
Authors: Ma Yu , Su Ke , Zhou Mingshan , Liu Yihan , Lu Guangqin , Wang Jie , Li Chengjie , Wang Tianqi , Li Yingfeng , Zhang Qi , Guan Xia , Han Xiong , Li Wenling , Ren Rongna , Zhong Min , Ding Ding , Jiang Yonghui , Peng Gang , Wang Yi , Wu Qihui , Fan Shaohua
Published: June 2024

Epilepsy, a prevalent neurodevelopmental disorder in children, is often accompanied by detrimental psychological consequences and other comorbidities. We performed exome sequencing on 963 patient-parent trios, revealing differences in genetic epidemiology between Chinese and European epilepsy cohorts. The diagnostic yield for known epilepsy genes was 40%. Pathogenic variants were most commonly found in SCN1A, KCNQ2, and DEPDC5. Additionally, we identified 15 novel monogenic epilepsy candidates in at least two patients diagnosed with developmental and epileptic encephalopathy, non-acquired focal epilepsy, or genetic generalized epilepsy, includingADCY2, BCAR3, CDC45, CHRNG, CRTC2, CSMD1, CSMD2, KDM6B, KIF1B, PLEKHM3, PPP4R1, RASGRP2, SGSM2, SYNE1, andZFHX3. Aside fromADCY2, which was implicated in the GABAergic synapse pathway based on KEGG analysis, these candidates do not belong to known epilepsy pathways. Local field potential recordings in zebrafish and calcium imaging experiments validated associations for 11 of these genes, excluding those unsuitable for functional analyses. Furthermore, we found thatCRTC2overexpression leads to hippocampal neuronal hyperactivity using multi-electrode arrays and electrophysiology. We have documented the first-line medications prescribed for patients harboring variants in the novel candidate genes. This study expands our understanding of the genetic underpinnings of epilepsy and provides opportunities for early diagnosis and personalized medicine approaches.
TransferGWAS of T1-weighted Brain MRI Data from the UK Biobank
Authors: Rakowski Alexander , Monti Remo , Lippert Christoph
Published: June 2024

Genome-wide association studies (GWAS) traditionally analyze single traits, e.g., disease diagnoses or biomarkers. Nowadays, large-scale cohorts such as the UK Biobank (UKB) collect imaging data with sample sizes large enough to perform genetic association testing. Typical approaches to GWAS on high-dimensional modalities extract predefined features from the data, e.g., volumes of regions of interest. This limits the scope of such studies to predefined traits and can ignore novel patterns present in the data. TransferGWAS employs deep neural networks (DNNs) to extract low-dimensional representations of imaging data for GWAS, eliminating the need for predefined biomarkers. Here, we apply transferGWAS on brain MRI data from the UKB. We encoded 36, 311 T1-weighted brain magnetic resonance imaging (MRI) scans using DNN models trained on MRI scans from the Alzheimer’s Disease Neuroimaging Initiative, and on natural images from the ImageNet dataset, and performed a multivariate GWAS on the resulting features. Furthermore, we fitted polygenic scores (PGS) of the deep features and computed genetic correlations between them and a range of selected phenotypes. We identified 289 independent loci, associated mostly with bone density, brain, or cardiovascular traits, and 14 regions having no previously reported associations. We evaluated the PGS in a multi-PGS setting, improving predictions of several traits. By examining clusters of genetic correlations, we found novel links between diffusion MRI traits and type 2 diabetes.

1

Author Summary

Genome-wide association studies are a popular framework for identifying regions in the genome influencing a trait of interest. At the same time, the growing sample sizes of medical imaging datasets allow for their incorporation into such studies. However, due to high dimensionalities of imaging modalities, association testing cannot be performed directly on the raw data. Instead, one would extract a set of measurements from the images, typically using predefined algorithms, which has several drawbacks - it requires specialized software, which might not be available for new or less popular modalities, and can ignore features in the data, if they have not yet been defined. An alternative approach is to extract the features using pretrained deep neural network models, which are well suited for complex high-dimensional data and have the potential to uncover patterns not easily discoverable by manual human analysis. Here, we extracted deep feature representations of brain MRI scans from the UK Biobank, and performed a genome-wide association study on them. Besides identifying genetic regions with previously reported associations with brain phenotypes, we found novel regions, as well as ones related to several other traits such as bone mineral density or cardiovascular traits.
Role of type I hypersensitivity reaction in the development of overall and uncomplicated acute appendicitis: a systematic review and meta-analysis
Authors: Montero Javier Arredondo , Jiménez María Rico , Riveros Blanca Paola Pérez , Atuan Rafael Fernández , Pakkasjärvi Niklas , Krishnan Nellai , Delgado-Miguel Carlos , Anand Sachit
Published: June 2024

Background

This systematic review aimed to analyze the potential etiopathogenic role of a type I hypersensitivity reaction in the development of overall acute appendicitis (AA), non-complicated acute appendicitis (NCAA), and complicated acute appendicitis (CAA).

Methods

This review was prospectively registered in PROSPERO (CRD42024516547). We included both prospective and retrospective original clinical studies that examined the role of immunoallergic processes in the development of acute appendicitis (AA). A comprehensive search was conducted in PubMed, Web of Science, Scopus, and OVID, using the following search terms and keywords: (allergy OR allergic OR immunoallergy OR immunoallergic OR immunomediated) AND (appendicitis OR appendectomy) AND (IgE OR “IgE-mediated” OR hypersensitivity OR “type I”). Two independent reviewers meticulously selected the articles and extracted relevant data. The methodological quality of the studies was rigorously assessed using the Newcastle-Ottawa index. A synthesis of the results, a standardization of the metrics, and seven random-effect meta-analyses were performed.

Results

This review included nineteen studies. A random-effects meta-analysis including six articles (6370 patients with NCAA and 2000 patients with CAA) showed that patients with any documented history of IgE-mediated allergy had a lower risk of developing CAA (OR 0.52, 95%CI [0.38-0.72], p<0.0001). The random-effect meta-analysis for serum Interleukin-9 (NCAA vs. CAA) included two articles (177 patients with NCAA and 101 patients with CAA) and resulted in a significant mean difference [95% CI] of –0.38 [-0.67,-0.08] pg/mL (p=0.01). The random-effect meta-analysis for serum Interleukin-13 (NCAA vs. CAA) included two articles (177 patients with NCAA and 101 patients with CAA) and resulted in a significant mean difference [95% CI] of –11.32 [-13.90,-8.75] pg/mL (p=<0.00001). The random-effect meta-analysis for total eosinophil count (NCAA vs. CAA) included three articles (455 NCAA and 303 CAA) and resulted in a significant mean difference [95% CI] of –0.06 [-0.09,-0.04] eosinophils x 109/L (p=<0.00001).

Conclusions

The present study demonstrates an association between a type I hypersensitivity reaction and the development of NCAA. Additionally, our meta-analytic model shows significantly higher levels of eosinophils peripheral blood in patients with NCAA than in patients with CAA. These findings suggest a potential immunoallergic mediation in the development of NCAA. Future prospective studies must validate these findings since these patients may benefit from specific therapeutic targets.

Funding

None

Registration

PROSPERO (CRD42024516547).
LT4SG@SMM4H’24: Tweets Classification for Digital Epidemiology of Childhood Health Outcomes Using Pre-Trained Language Models
Authors: Athukoralage Dasun , Atapattu Thushari , Thilakaratne Menasha , Falkner Katrina
Published: June 2024

This paper presents our approaches for the SMM4H’24 Shared Task 5 on the binary classification of English tweets reporting children’s medical disorders. Our first approach involves fine-tuning a single RoBERTa-large model, while the second approach entails ensembling the results of three fine-tuned BERTweet-large models. We demonstrate that although both approaches exhibit identical performance on validation data, the BERTweet-large ensemble excels on test data. Our best-performing system achieves an F1-score of 0.938 on test data, out-performing the benchmark classifier by 1.18%.
Artificial cells with all-aqueous droplet-in-droplet structures for spatially separated transcription and translation
Authors: Tomohara Kanji , Minagawa Yoshihiro , Noji Hiroyuki
Published: June 2024

The design of functional artificial cells involves compartmentalizing biochemical processes to mimic cellular organization. To emulate the complex chemical systems in biological cells, it is necessary to incorporate an increasing number of cellular functions into single compartments. Artificial organelles that spatially segregate reactions inside artificial cells will be beneficial in this context by rectifying biochemical pathways. In our study, we developed artificial cells featuring all-aqueous droplet-in-droplet structures that separate transcription and translation processes, mimicking the nucleus and cytosol in eukaryotic cells. This droplet-in-droplet architecture utilizes intrinsically disordered protein (IDP) to form coacervate droplets for the inner compartments, and aqueous two-phase systems (ATPS) for the outer compartments, with the outer interfaces stabilized by colloidal emulsifiers. The inner droplet was designed to enrich DNA and RNA polymerase to conduct transcription, which was coupled to translation at the outer droplet, realizing the cascade reaction mediated by mRNA. We also demonstrate that these processes proceed independently within each artificial cell compartment, maintaining the correspondence between genotype and phenotype. The modular configuration of these artificial organelles could be extended to other enzymatic reactions. Coupled with the ease of manufacturing these artificial cells, which only requires simple agitation in an all-aqueous mixture, this approach provides a practical and accessible tool for exploring complex systems of artificial organelles within large ensembles of artificial cells.
Mimosaspecies endemic to acidic soils in central Brazil are nodulated by a high diversity ofParaburkholderiagenotypes, but widespread species are nodulated byParaburkholderia,CupriavidusorRhizobiumdepending on soil characteristics
Authors: Rouws Luc , Barauna Alexandre , Beukes Chrizelle , Rouws Janaina R. C. , de Faria Sergio Miana , Gross Eduardo , dos Reis Junior Fabio Bueno , Simon Marcelo F. , Maluk Marta , Odee David W. , Fordeyn Stephanie , Kenicer Gregory , Young J. Peter W. , Reis Veronica M. , Zilli Jerri , James Euan K.
Published: June 2024

Neotropical Beta-rhizobia have a particular affinity to the large legume (Fabaceae) genusMimosaand some of its relatives in the tribe Mimosae of the Caesalpinioideae subfamily. However, little is still known about the ecology of this interaction, especially the relationship between the rhizobia of “widespread” pan-tropicalMimosaspecies likeM. pudicaand the rhizobia that nodulate endemicMimosaspecies that are very restricted in their habitats. The objective of this study was to examine the microsymbionts ofMimosaspp. and some other mimosoids in climates ranging from tropical to subtropical, humid to semi-arid, with varied soil characteristics and altitudes, with the aim of testing the hypothesis that widespread species have more cosmopolitan symbiont preferences than endemic ones. Nodules were sampled from more than 40Mimosaspp. and related taxa in eleven Brazilian states, many endemics or biome-restricted, but particular attention was paid to sample nodules from the widespread speciesM. pudicaat all locations. TheMimosasymbionts comprised 19 potential 16S rRNA andrecAgroups at the species level, with 16 belonging to the genusParaburkholderia, including six lineages that may represent new species. The remaining genotypes consisted of 14 strains in two lineages ofCupriavidusthat were mainly isolated fromM. pudicagrowing at low altitudes, plus a single lineage ofRhizobiumalso fromM. pudica. It is concluded that a high diversity ofParaburkholderiastrains dominate as symbionts ofMimosain the acidic soils of its main center of radiation in Central Brazil but thatCupriavidusandRhizobiumcomprise a significant minority of symbionts of widespreadMimosaspp., especiallyM. pudica, in lowland or disturbed areas with less acidic soils.Mimosasymbiont diversity is thus driven either by edapho-climatic characteristics for widespread species and/or by co-evolution of the symbiotic partners for endemic species.
LEVERAGING CITIZEN SCIENCE TO ASSESS RICHNESS, DIVERSITY, AND ABUNDANCE IN ANT COMMUNITIES
Authors: Szewczyk Tim M. , Lavanchy Guillaume , Freitag Anne , Dépraz Aline , Avril Amaury , Broennimann Olivier , Guisan Antoine , Bertelsmeier Cleo , Schwander Tanja
Published: June 2024

Abstract

Citizen science is a key resource in overcoming the logistical challenges of monitoring biodiversity. While datasets collected by groups of volunteers typically have biases, recent methodological and technological advances provide approaches for accounting for such biases, particularly in the context of modelling species distributions and diversity. Specifically, data integration techniques allow for the combination of scientifically collected datasets with haphazardly sampled presence-only datasets created by most citizen science initiatives. Here, we use a hierarchical Bayesian framework to integrate a set of ant presences collected by citizen scientists in the Vaud canton (Switzerland) with ant colony density data collected concurrently in the same region following a scientific sampling design. The community-level Poisson point process model included species-specific responses to the local (1.2 m2) and regional (1 km2) environment, with the presence-only samples incorporated at the regional scale to predict local and regional ant communities. At the regional scale, species richness followed a hump-shaped pattern and peaked near 1000 m while abundance increased with elevation. Low elevation and montane ant communities were composed of distinct species assemblages. At the local scale, the link between elevation and richness, diversity, and abundance was weak. At low elevations, local plots varied both in total abundance and species composition, while at higher elevations, the species composition was less variable. The citizen science dataset showed a general tendency toward under-representation of certain species, and heavy spatial sampling bias. Nonetheless, the inclusion of the citizen science data improved predictions of local communities, and also reduced susceptibility to over-fitting. Additionally, the citizen science dataset included many rare species not detected in the structured abundance dataset. The model described here illustrates a framework for capitalizing on the efforts of citizen scientists to better understand the patterns and distribution of biodiversity.
Contribution of the Type 3 Secretion System to immunogenicity of a liveYersinia pseudotuberculosisplague vaccine
Authors: Derbise Anne , Guillas Chloé , Rivera Hebert Echenique , Carniel Elisabeth , Gerke Chris , Cerdá Javier Pizarro , Demeure Christian E.
Published: June 2024

The causative agent of plague,Yersinia pestis, remains a treat for public health worldwide. In the perspective to develop effective and safe vaccines, we present here a derived version of ourY. pseudotuberculosisVTnF1 live attenuated vaccine candidate that lacks the pYV virulence plasmid coding for the Type 3 Secretion system (T3SS) and no antibiotic resistance cassettes. This strain, called VpYV-, was safe for immunodeficient mice, and thus can be considered as deeply attenuated. It still has tropism for lymphatic tissues (Peyer’s patches, Mesenteric lymph nodes) but hardly reaches the spleen and liver. It elicits IgG to the F1 antigen as efficiently as VTnF1 but less directed to other Yersinia antigens. A single oral dose induced 100% protection against bubonic and pneumonic forms of plague, but this protection decreased faster with time than that of VTnF1. In the same line, VpYV-was 30% less protective against a F1-negativeY. pestis, revealing that the tools encoded by pYV are mandatory to obtain a large spectrum protection. Finally, VTnF1 like theY. pestisvaccine EV76 can induce protection against co-infectedY. pestisrelying on ‘host iron nutritional immunity”, indicating a potential use as therapeutics of recent infection. In contrast VpYV-failed to do so, revealing an importance of the T3SS in this mechanism. Overall, VpYV- and its parental strain VTnF1 offer a choice between more attenuation and safety or vaccine performances. They give an alternative and may represent useful tools to prevent and treatY. pestisinfection in healthy or immunosuppressed individuals.
Echinocandins have an alternative mode of action on biomimetic membranes that is not directly related to the functioning of (1,3) beta-glucan synthase
Authors: Malykhina Anna I. , Efimova Svetlana S. , Vodopyanova Ekaterina V. , Grammatikova Natalia E. , Tevyashova Anna N. , Shchekotikhin Andrey E. , Ostroumova Olga S.
Published: June 2024

Echinocandins, one of five main classes of antifungal agents, are FDA-approved drugs for therapy of invasive candidiasis and aspergillosis. The exact mechanisms of echinocandins action are still under debates, in particular the role of target cell membranes in their function. In present study we analyzed the molecular mechanisms of action of echinocandins (anidulafungin, caspofungin, and micafungin) on the sterol-enriched lipid bilayers mimicking fungal and mammalian membranes. Calcein release assay and molecular dynamics simulations demonstrated the relation of the membrane permeability and echinocandin type. Moreover, we have shown for the first time the ability of echinocandins to form ion-permeable pores in sterol-containing membranes. Differential scanning microcalorimetry of the gel-to-liquid-crystalline lipid phase transition and confocal fluorescent microscopy of lipid domains revealed the ability of echinocandins to enhance phase segregation in membrane. Thus, echinocandins might affect the (1,3) beta-glucan synthase functioning by alteration in lipid microenvironment of target protein and cellular membrane permeability via formation of ion-selective leakage channels. We also found that small natural molecule, phloretin, potentiated the pore-forming activity of micafungin in the ergosterol-containing bilayers and significantly reduced the minimum inhibitory concentration of micafungin against fluconazole-resistantCandida albicans, C. tropicalis, andC.krusei.
Nitrous Oxide Formation and Consumption in Thawing Permafrost: A Microcosm Study
Authors: Sun Yanchen , Wu Xiaofen , Zanina Oksana G. , Rivkina Elizaveta M. , Lloyd Karen G. , Loeffler Frank E. , Vishnivetskaya Tatiana A.
Published: June 2024

Nitrous oxide (N2O) emissions contribute to stratospheric ozone depletion and global warming. Climate warming causes permafrost thawing and decomposition of the dormant nitrogenous compounds, releasing N2O; however, understanding of the microbial formation and consumption of N2O in permafrost is still limited. Permafrost soils collected at two depths (5.4 m and 16.9 m) from the East Siberian Sea coast of Russia were used to establish microcosms assessing N2O formation and consumption in the presence of either nitrate (NO3-, 1 mM) or N2O (1 mM), respectively, during incubation at 4 and 20°C. Rapid N2O formation was observed in NO3--amended microcosms, but N2O consumption was slow and incomplete over a 1-year incubation period in all microcosms. Twenty-six quality-filtered metagenome-assembled genomes (MAGs) harboring genes involved in the reduction of NO3-and/or N2O were recovered from 16 metagenomes obtained from duplicate NO3-- and N2O-amended microcosms. None of the MAGs carried a complete set of genes to perform canonical denitrification (i.e., NO3-→N2) indicating N2O formation and consumption is likely driven by non-denitrifying bacteria. While coastal permafrost microbiomes harbornosZgenes, activity monitored in the microcosms indicates N2O formation exceeds N2O consumption, emphasizing the need for integrated approaches to assess and predict N turnover in thawing permafrost.
Minimizing command timing volatility is a key factor in skilled actions
Authors: Takagi Atsushi , Ito Sho , Gomi Hiroaki
Published: June 2024

Variability between movements prevents the best athletes from making a perfect shot every time. While fluctuations in the amplitude of neural sensory inputs and motor outputs are thought to be primarily responsible, they only account for a fraction of the observed variability. Here, we propose that a significant portion of the variability is due to imprecisely timed motor commands. This command timing volatility theory best explained the three peaks observed in the force variability’s time-series in discrete reaching movements and during periodic force control. Furthermore, we show how the timing volatility in the non-dominant arm’s muscles is larger than in the dominant arm, then develop a variability index that estimates the arm’s timing volatility via its variability during circle tracing. The difference in the variability index between the left and right hands accurately predicts the Edinburgh Quotient, suggesting a relationship between handedness and the command timing volatility of the left- and right-hands. Lastly, we constructed a simulation of reaching movements made by an arm controlled by muscles whose command timing was made incrementally more volatile. As timing volatility increased, aiming became less precise and movements jerkier. Such impairments during reaching are reported in patients with different neuronal diseases that damage any brain regions critical to motor timing, suggesting that essential aspects of these symptoms may be caused by excessive timing volatility. Our theory provides a unifying computational perspective of movement variability in healthy and diseased individuals that is essential to understanding the control of movements.
Retrieving Nonlinear Features from Noisy Quantum States
Authors: Zhao Benchi , Jing Mingrui , Zhang Lei , Zhao Xuanqiang , Chen Yu-Ao , Wang Kun , Wang Xin
Published: June 2024

Accurately estimating high-order moments of quantum states is an elementary precondition for many crucial tasks in quantum computing, such as entanglement spectroscopy, entropy estimation, spectrum estimation, and predicting nonlinear features from quantum states. But in reality, inevitable quantum noise prevents us from accessing the desired value. In this paper, we address this issue by systematically analyzing the feasibility and efficiency of extracting high-order moments from noisy states. We first show that there exists a quantum protocol capable of accomplishing this task if and only if the underlying noise channel is invertible. We then establish a method for deriving protocols that attain optimal sample complexity using quantum operations and classical postprocessing only. Our protocols, in contrast to conventional ones, incur lower overheads and avoid sampling different quantum operations due to a novel technique called the “‘observable shift method,” making the protocols strong candidates for practical use on current quantum devices. The proposed method also indicates the power of entangled protocols in retrieving high-order information, whereas in the existing methods, entanglement does not help. We further construct the protocol for large quantum systems to retrieve the depolarizing channels, making the proposed method scalable. Our work contributes to a deeper understanding of how quantum noise could affect high-order information extraction and provides guidance on how to tackle it.

Published by the American Physical Society
2024
Can high-speed railway promote enterprise ambidextrous innovation: a quasi-natural experiment in China
Authors: Li Xing , Zhang Guiyang , Zheng Fangyuan , Qi Yong , Lu Chang
Published: June 2024

Purpose

Well-constructed transportation infrastructure may effectively decrease barriers to the flow of innovative human resources and inventive elements, accelerating enterprise innovation activities. This study will explore how HSR helps enterprises achieve ambidextrous innovation, including the mediating mechanism of absorbed slack resources, innovative talents, and the heterogeneous effects of management shareholding ratio and financing constraints.

Design/methodology/approach

Based on resource dependence theory and social network theory, this study employs a quasi-natural experiment of China’s high-speed railway and builds a multi-time point DID model to investigate its influence on enterprise ambidextrous innovation.

Findings

Results suggest that the HSR positively influences both exploitative and exploratory innovation, and the influence is more substantial on exploitative innovation. Further analysis finds two influencing channels through which HSR influences enterprise ambidextrous innovation: providing redundant resources and attracting innovative talents. Heterogeneity analysis indicates that HSR has a more significant positive effect on exploratory innovation for enterprises with high management shareholding. In the low financing constraint group, the HSR opening has a more significant impact on ambidextrous innovation.

Practical implications

In ambidextrous innovation, enterprises should rationalize the allocation of resources, attach importance to the innovative talent introduction, and choose differentiated paths based on intrinsic characteristics. Meanwhile, the government should actively improve the HSR routes and continuously improve the innovative environment.

Originality/value

This study enriches the theoretical research framework of HSR and ambidextrous innovation by identifying the channel mechanisms and boundary conditions through which HSR affects ambidextrous innovation and expands the consequences of HSR and the antecedents of ambidextrous.
Beyond the academic curriculum: embedding a career management program to improve the employability of business students
Authors: Chieng Fayrene , Goi Chai Lee , Ho Jie Min , Yip Ka Yii
Published: June 2024

Purpose

The purpose of this paper is to evaluate the effectiveness of a career management program embedded within a business module, with a specific focus on enhancing the employability of students.

Design/methodology/approach

The study involved five one-hour workshops based on the DOTS model, covering aspects like resume writing and professional communication. Surveys, using a structured questionnaire and a Likert scale, measured participants' perceived employability. The pre-survey included demographic details, while the post-survey evaluated the effectiveness of the Career development learning workshop. Incentives and QR codes were employed to boost participation, and data were collected at the semester's start and end, with responses linked through students' phone numbers.

Findings

The results confirmed a positive connection between the perceived effectiveness of skill programs and students' employability. Integration of career management into the curriculum cultivates a heightened professional mindset and boosts employability. Validation through a paired-samples t-test demonstrates a substantial increase in perceived employability after program participation, affirming the program's role in fostering psychosocial empowerment and elevating students' confidence in job seeking.

Originality/value

This pioneering research integrates a career management program into a business module, addressing employability challenges in Industry 4.0. It provides empirical evidence of the program's positive impact on students' perceived employability.
Exploring the effect of enterprise risk management for ESG risks towards green growth
Authors: Shah Syed Quaid Ali , Lai Fong-Woon , Shad Muhammad Kashif , Hamad Salaheldin , Ellili Nejla Ould Daoud
Published: June 2024

Purpose

Despite the growing emphasis on sustainability and the need to manage environmental, social, and governance (ESG) risks, the direct relationship between enterprise risk management (ERM) and green growth (GG) has not been investigated. This study seeks to fill this gap by examining the effect of ERM on the GG of oil and gas (O&G) companies in Malaysia.

Design/methodology/approach

The study used panel data regression models to analyze panel data from 2012 to 2021. For computing GG, we adapted the Organization for Economic Cooperation and Development’s (OECD) GG framework. ERM is computed using COSO and WBCSD guidelines for ESG-related risks. Weighted content analysis is used to measure ERM and GG

Findings

The findings derived from the content and descriptive statistics analyses indicate a consistent and ongoing rise in the adoption of ERM practices over time. However, some companies are still in the initial stages of incorporating ERM to address ESG risks. The study’s findings unequivocally establish a substantial and positive relationship between ERM and GG. ERM drives GG by significantly influencing its environmental and resource productivity dimensions. The study further reveals that the impact of ERM on economic opportunities and policy responses, as well as the natural asset base, is statistically significant, albeit with relatively lower coefficient values.

Practical implications

To enhance the legitimacy of organizations and foster positive stakeholder relationships, regulators, governments, and policymakers should actively promote the adoption of ERM standards that specifically address ESG risks, as outlined by COSO and WBCSD. This strategic alignment with risk management practices will ultimately contribute to improving green growth for organizations.

Originality/value

To the best of the authors' knowledge, this is the first study examining ERM’s effect on GG. The study adds to the existing literature by focusing on ERM’s role in a company’s GG. It clarifies ERM’s significant effect on diminishing emerging ESG risks and advancing GG
Exploring the motives for using social networks for professional development by Spanish teachers
Authors: Marcelo-Martínez Paula , Yot-Domínguez Carmen , Mosquera Gende Ingrid
Published: June 2024

Purpose

Social networks (SNs) play a significant role as environments supporting teacher professional development. The purpose of this to analyze the motivation and participation roles that Spanish teachers have when participating in SNs for their professional development in three professional stages: preservice teachers, beginning teachers and experienced teachers.

Design/methodology/approach

The study uses a mixed-method approach, combining two validated surveys, one applied to 217 preservice teachers and other to 68 beginning teachers and 384 experienced teachers, with 15 interviews. A qualitative exploratory sequential strategy has been followed along with an ex post facto quantitative survey-type study of a descriptive and inferential nature.

Findings

Preservice and beginning teachers use SNs to access materials and resources with which to learn, presenting an observer and passive role in their interaction on SNs. Experienced teachers log in to learn about experiences but begin to participate more actively in SNs for searching for specific resources, establishing contacts with other teachers, contributing with their own educational materials and helping other teachers with their doubts or even forming their own communities.

Originality/value

These findings help understand how the evolution in teacher expertise accompanies the level of involvement in their social network interactions. The results allow us to better understand how different levels of teaching experience influence the way Spanish teachers access and participate in SNs, in some cases consuming and in others producing digital content.