bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Visually Simulated Self-Motion on Predicting Object Motion
Authors: Jörges Björn , Harris Laurence R.
Published: November 2023

To interact successfully with moving objects in our environment we need to be able to predict their behavior. Predicting the position of a moving object requires an estimate of its velocity. When flow parsing during self-motion is incomplete – that is, when some of the retinal motion created by self-motion is incorrectly attributed to object motion – object velocity estimates become biased. Further, the process of flow parsing should add noise and lead to object velocity judgements being more variable during selfmotion. Biases and lowered precision in velocity estimation should then translate to biases and lowered precision in motion extrapolation. We investigated this relationship between self-motion, velocity estimation and motion extrapolation with two tasks performed in a realistic virtual reality (VR) environment: first, participants were shown a ball moving laterally which disappeared after a certain time. They then indicated by button press when they thought the ball would have hit a target rectangle positioned in the environment. While the ball was visible, participants sometimes experienced simultaneous visual lateral self-motion in either the same or in the opposite direction of the ball. The second task was a two-interval forced choice task in which participants judged which of two motions was faster: in one interval they saw the same ball they observed in the first task while in the other they saw a ball cloud whose speed was controlled by a PEST staircase. While observing the single ball, they were again moved visually either in the same or opposite direction as the ball or they remained static. We found the expected biases in estimated time-to-contact, while for the speed estimation task, this was only the case when the ball and observer were moving in opposite directions. Our hypotheses regarding precision were largely unsupported by the data. Overall, we draw several conclusions from this experiment: first, incomplete flow parsing can affect motion prediction. Further, it suggests that time-to-contact estimation and speed judgements are determined by partially different mechanisms. Finally, and perhaps most strikingly, there appear to be certain compensatory mechanisms at play that allow for much higher-than-expected precision when observers are experiencing self-motion – even when self-motion is simulated only visually.
Influence of Nursing Explanation Skills on Incident Occurrence
Authors: Fujimoto Manabu , Shimamura Mika , Yuki Fumiko
Published: November 2023

Objectives

A routine nursing task is providing explanations to patients, their families, and other healthcare professionals. Inaccurate explanations can adversely affect the quality of healthcare and patient safety. Despite the significance of good explanatory skills in nursing, supporting empirical data are limited. Therefore, this study aimed to develop a psychological scale and investigate the impact of explanatory skills on incidents.

Methods

In the preliminary investigation, responses obtained from experienced nurses were analyzed to compile 87 scale items. Study 1 involved an online explanatory skills survey with a sample of 1,000 nursing professionals. Study 2 comprised a field survey involving 159 nursing staff members working in a comprehensive hospital.

Results

Nine sub-skills were identified and categorized under two factors: “compassion” and “mental model sharing.” Seven of these sub-skills were found to be shared, and the remaining two were specific to interactions with patients/families or healthcare professionals. Clinical ladder progression was associated with both compassion and mental model sharing, whereas years of practical experience was only related to mental model sharing. Furthermore, compassion was identified as a factor that increased the probability of the occurrence of various incidents through interactional failures. In contrast, mental model sharing enhanced the probability of severe incidents stemming from judgmental failures and minor incidents from conceptual failures.

Conclusions

This study developed a psychological scale to measure nursing professionals’ explanation skills in communication with patients, their families, and other medical staff. It elucidated their impact on incident occurrence through miscommunication. The findings need to be practically verified through fieldwork in nursing education.
Polygenic burden of short tandem repeat expansions promote risk for Alzheimer’s disease
Authors: Guo Michael H. , Lee Wan-Ping , Vardarajan Badri , Schellenberg Gerard D. , Phillips-Cremins Jennifer
Published: November 2023

Studies of the genetics of Alzheimer’s disease (AD) have largely focused on single nucleotide variants and short insertions/deletions. However, most of the disease heritability has yet to be uncovered, suggesting that there is substantial genetic risk conferred by other forms of genetic variation. There are over one million short tandem repeats (STRs) in the genome, and their link to AD risk has not been assessed. As pathogenic expansions of STR cause over 30 neurologic diseases, it is important to ascertain whether STRs may also be implicated in AD risk. Here, we genotyped 321,742 polymorphic STR tracts genome-wide using PCR-free whole genome sequencing data from 2,981 individuals (1,489 AD case and 1,492 control individuals). We implemented an approach to identify STR expansions as STRs with tract lengths that are outliers from the population. We then tested for differences in aggregate burden of expansions in case versus control individuals. AD patients had a 1.19-fold increase of STR expansions compared to healthy elderly controls (p=8.27×10−3, two-sided Mann Whitney test). Individuals carrying > 30 STR expansions had 3.62-fold higher odds of having AD and had more severe AD neuropathology. AD STR expansions were highly enriched within active promoters in post-mortem hippocampal brain tissues and particularly within SINE-VNTR-Alu (SVA) retrotransposons. Together, these results demonstrate that expanded STRs within active promoter regions of the genome promote risk of AD.
Fecal microbiota transplantation from individual with bipolar disorder and healthy control elicits distinct behaviors and metabolite profiles in mice
Authors: Bukowski-Thall Grace , Fellendorf Frederike T. , Gorkiewicz Sarah , Ip Kenny Chi Kin , Schmidt Laura , Durdevic Marija , Habisch Hansjörg , Mörkl Sabrina , Wagner-Skacel Jolana , Bengesser Susanne A. , Lenger Melanie , Dalkner Nina , Gorkiewicz Gregor , Högenauer Christoph , Madl Tobias , Moissl-Eichinger Christine , Farzi Aitak , Reininghaus Eva Z.
Published: November 2023

Bipolar disorder (BD) is a chronic mood disorder characterized by recurrent episodes of depression and (hypo-) mania. The gut microbiome is a potential avenue through which metabolic signaling, inflammatory pathways, environmental factors, and genetics influence BD pathogenesis via the gut-brain axis. Fecal microbiota transplantation (FMT) is a powerful translational tool for investigating the connections between the gut microbiome and BD, and there is evidence FMT can transfer affective symptoms of BD from humans to mice. In this study, we compared the behavior, gut-brain metabolomic profiles, and inflammatory marker expression in two groups of adult female C57BL/6J mice, one receiving FMT from a human donor with BD in a mixed episode ( HAM-D = 20, YMRS = 14) and another receiving FMT from a mentally healthy weight and age-matched control donor without BD (HAM-D and YMRS = 0). Here, we demonstrate that mice receiving FMT from individuals with BD had an increased abundance of Bacteroidota and decreased abundances ofParabacteroides merdaeandAkkermansia muciniphilaassociated with altered levels of fecal metabolites, short-chain fatty acids, and related gut hormone expression relative to mice receiving control donor FMT. BD mice also exhibited differential regulation of several metabolites and inflammatory markers in the amygdala, with glycine being the most prominently affected. Furthermore, BD mice displayed increased anxiety-like behavior and decreased sociability, indicating that aspects of the behavioral phenotype of BD are transferable from humans to mice via FMT. Taken together, these findings implicate gut-brain signaling in the physiological and behavioral changes observed in our BD-FMT mouse model.
Diving into bacterial dormancy: emergence of osmotically stable wall-less forms in an aquatic environment
Authors: Carvalho Filipe , Carreaux Alexis , Sartori-Rupp Anna , Tachon Stéphane , Gazi Anastasia D. , Courtin Pascal , Nicolas Pierre , Dubois-Brissonnet Florence , Barbotin Aurélien , Desgranges Emma , Gloux Karine , Schouler Catherine , Carballido-López Rut , Chapot-Chartier Marie-Pierre , Milohanic Eliane , Bierne Hélène , Pagliuso Alessandro
Published: November 2023

Bacteria can respond to environmental stresses by entering a dormant state, called viable but non-culturable (VBNC) state, in which they no longer grow in routine culture media. VBNC pathogens pose thus a significant risk for human and animal health as they are not detected by standard growth-based techniques and can “wake up” back into a vegetative and virulent state. Although hundreds of species were reported to become VBNC in response to different stresses, the molecular mechanisms governing this phenotypic switch remain largely elusive.

Here, we characterized the VBNC state transition process in the Gram-positive pathogenListeria monocytogenesin response to nutritional deprivation. By combining fluorescence microscopy, cryo-electron tomography and analytical biochemistry, we found that starvation in mineral water drivesL. monocytogenesinto a VBNC state via a mechanism of cell wall (CW) shedding that generates osmotically stable CW-deficient (CWD) coccoid forms. This phenomenon occurs in multipleL. monocytogenesstrains and in otherListeriaspecies, suggesting it may be a stress-adapting process transversal to theListeriagenus. Transcriptomic and gene-targeted approaches revealed the stress response regulator SigB and the autolysin NamA as major moderators of CW loss and VBNC state transition. Finally, we show that this CWD dormant state is transient as VBNCListeriarevert back to a walled, vegetative and virulent state after passage in embryonated eggs.

Our findings provide unprecedented detail on the mechanisms governing the transition to a VBNC state, and reveal that dormant CWD bacterial forms can naturally arise in aquatic environments without osmotic stabilization. This may represent an alternative strategy for bacterial survival in oligotrophic conditions, which can potentially generate public health-threatening reservoirs of undetectable pathogens.
Guidelines for Performing Ribosome Profiling in Plants Including Structural Analysis of rRNA Fragments
Authors: Ting Michael K. Y. , Gao Yang , Barahimipour Rouhollah , Ghandour Rabea , Liu Jinghan , Martinez-Seidel Federico , Smirnova Julia , Gotsmann Vincent Leon , Fischer Axel , Haydon Michael J. , Willmund Felix , Zoschke Reimo
Published: November 2023

Ribosome profiling (or Ribo-seq) is a technique that provides genome-wide information on the translational landscape (translatome). Across different plant studies, variable methodological setups have been described which raises questions about the general comparability of data that were generated from diverging methodologies. Furthermore, a common problem when performing Ribo-seq are abundant rRNA fragments that are wastefully incorporated into the libraries and dramatically reduce sequencing depth. To remove these rRNA contaminants, it is common to perform preliminary trials to identify these fragments because they are thought to vary depending on nuclease treatment, tissue source, and plant species. Here, we compile valuable insights gathered over years of generating Ribo-seq datasets from different species and experimental setups. We highlight which technical steps are important for maintaining cross experiment comparability and describe a highly efficient approach for rRNA removal. Furthermore, we provide evidence that many rRNA fragments are structurally preserved over diverse nuclease regimes, as well as across plant species. Using a recently published cryo-electron microscopy (cryo-EM) structure of the tobacco 80S ribosome, we show that the most abundant rRNA fragments are spatially derived from the solvent-exposed surface of the ribosome. The guidelines presented here shall aid newcomers in establishing ribosome profiling in new plant species and provide insights that will help in customizing the methodology for individual research goals.
Progression of herpesvirus infection remodels mitochondrial organization and metabolism
Authors: Leclerc Simon , Gupta Alka , Ruokolainen Visa , Chen Jian-Hua , Kunnas Kari , Ekman Axel A. , Niskanen Henri , Belevich Ilya , Vihinen Helena , Turkki Paula , Perez-Berna Ana J. , Kapishnikov Sergey , Mäntylä Elina , Harkiolaki Maria , Dufour Eric , Hytönen Vesa , Pereiro Eva , McEnroe Tony , Fahy Kenneth , Kaikkonen Minna U. , Jokitalo Eija , Larabell Carolyn A. , Weinhardt Venera , Mattola Salla , Aho Vesa , Vihinen-Ranta Maija
Published: November 2023

Viruses target mitochondria to promote their replication, and infection-induced stress during the progression of infection leads to the regulation of antiviral defenses and mitochondrial metabolism which are opposed by counteracting viral factors. The precise structural and functional changes that underlie how mitochondria react to the infection remain largely unclear. Here we show extensive transcriptional remodeling of protein-encoding host genes involved in the respiratory chain, apoptosis, and structural organization of mitochondria as herpes simplex virus type 1 lytic infection proceeds from early to late stages of infection. High-resolution microscopy and interaction analyses unveiled infection-induced emergence of rough, thin, and elongated mitochondria relocalized at the perinuclear area, a significant increase in the number and clustering of ER-mitochondria contact sites, and thickening and shortening of mitochondrial cristae. Finally, metabolic analyses demonstrated that reactivation of ATP production is accompanied by increased mitochondrial Ca2+content and proton leakage as the infection proceeds. Overall, the significant structural and functional changes in the mitochondria triggered by the viral invasion are tightly connected to the progression of the virus infection.
The meditative brain: State and trait changes in harmonic complexity for long-term mindfulness meditators
Authors: Atasoy Selen , Escrichs Anira , Stark Eloise , Terry Kendra G. M. , Camara Estela , Sanjuan Ana , Chandaria Shamil , Deco Gustavo , Kringelbach Morten L.
Published: November 2023

Meditation is an ancient practice that is shown to yield benefits for cognition, emotion regulation and human flourishing. In the last two decades, there has been a surge of interest in extracting the neural correlates of meditation, in particular of mindfulness meditation. Yet, these efforts have been mostly limited to the analysis of certain regions or networks of interest and a clear understanding of meditation-induced changes in the whole-brain dynamics has been lacking. Here, we investigate meditation-induced changes in brain dynamics using a novel connectome-specific harmonic decomposition method. Specifically, utilising the connectome harmonics as brain states - elementary building blocks of complex brain dynamics - we study the immediate (state) and long-term (trait) effects of mindfulness meditation in terms of the energy, power and complexity of the repertoire of these harmonic brain states. Our results reveal increased power, energy and complexity of the connectome harmonic repertoire and demonstrate that meditation alters brain dynamics in a frequency selective manner. Remarkably, the frequency-specific alterations observed in meditation are reversed in resting state in group-wise comparison revealing for the first time the long-term (trait) changes induced by meditation. These findings also provide evidence for the entropic brain hypothesis in meditation and provide a novel understanding of state and trait changes in brain dynamics induced by mindfulness meditation revealing the unique connectome harmonic signatures of the meditative brain.
The Advanced BRain Imaging on ageing and Memory (ABRIM) data collection: Study protocol and rationale
Authors: Jansen Michelle G. , Zwiers Marcel P. , Marques Jose P. , Chan Kwok-Shing , Amelink Jitse S. , Altgassen Mareike , Oosterman Joukje M. , Norris David G.
Published: November 2023

To understand the neurocognitive mechanisms that underlie heterogeneity in cognitive ageing, recent scientific efforts have led to a growing public availability of imaging cohort data. The Advanced BRain Imaging on ageing and Memory (ABRIM) project aims to add to these existing datasets by taking an adult lifespan approach to provide a cross-sectional, normative database with a particular focus on connectivity, myelinization and iron content of the brain in concurrence with cognitive functioning, mechanisms of reserve, and sleep-wake rhythms. ABRIM freely shares MRI and behavioural data from 295 participants between 18-80 years, stratified by age decade and sex (median age 52, IQR 36-66, 53.20% females). The ABRIM MRI collection consists of both the raw and pre-processed structural and functional MRI data to facilitate data usage among both expert and non-expert users. The ABRIM behavioural collection includes measures of cognitive functioning (i.e., global cognition, processing speed, executive functions, and memory), proxy measures of cognitive reserve (e.g., educational attainment, verbal intelligence, and occupational complexity), and various self-reported questionnaires (e.g., on depressive symptoms, pain, and the use of memory strategies in daily life and during a memory task). In a sub-sample (n= 120), we recorded sleep-wake rhythms with an actigraphy device for a period of 7 consecutive days. Here, we provide an in-depth description of our study protocol, pre-processing pipelines, and data availability. ABRIM provides a cross-sectional database on healthy participants throughout the adult lifespan, including numerous parameters relevant to improve our understanding of cognitive ageing. Therefore, ABRIM enables researchers to model the advanced imaging parameters and cognitive topologies as a function of age, identify the normal range of values of such parameters, and to further investigate the diverse mechanisms of reserve and resilience.
New sensitive tools to characterize meta-metabolome response to short- and long-term cobalt exposure in dynamic river biofilm communities
Authors: Colas Simon , Marie Benjamin , Morin Soizic , Milhe-Poutingon Mathieu , Foucault Pierre , Chalvin Siann , Gelber Clémentine , Baldoni-Andrey Patrick , Gurieff Nicholas , Fortin Claude , Faucheur Séverine Le
Published: November 2023

Untargeted metabolomics is a non-a priorianalysis of biomolecules that characterizes the metabolome variations induced by short- and long-term exposures to stressors. Even if the metabolite annotation remains lacunar due to database gaps, the global metabolomic fingerprint allows for trend analyses of dose-response curves for hundreds of cellular metabolites. The combination of untargeted metabolomic features and benchmark-dose (BMD) calculations then makes it possible to determine concentration range inducing defense responses (CRIDeR) and concentration range inducing damage responses (CRIDaR). To develop this approach in a context of time-dependent microbial community changes, mature river biofilms were exposed for 1 month to four cobalt (Co) concentrations (background concentration, 1 x 10-7, 5 x 10-7and 1 x 10-6M) in an open system of artificial streams. The meta-metabolomic response of biofilms was compared against a multitude of biological parameters (including bioaccumulation, biomass, chlorophyllacontent, composition and structure of prokaryotic and eukaryotic communities) monitored at set exposure times (from 1 hour to 28 days). Cobalt exposure induced extremely rapid responses of the meta-metabolome, with time range inducing defense responses (TRIDeR) of around ten seconds, and time range inducing damage responses (TRIDaR) of several hours. Even in biofilms whose structure had been altered by Co bioaccumulation (reduced biomass, chlorophyllacontents and changes in the composition and diversity of prokaryotic and eukaryotic communities), CRIDeRs with similar initiation thresholds (1.41 ± 0.77 x 10-10M Co2+added in the exposure medium) were set up at the meta-metabolome level at every time point. In contrast, the CRIDaR initiation thresholds increased by 10 times in long-term Co exposed biofilms. The present study demonstrates that defense and damage responses of biofilm meta-metabolome exposed to Co are rapidly and sustainably impacted, even within tolerant and resistant microbial communities.

Graphical abstract

Highlights

Prokaryotic community structures were impacted after 1 h of exposure to Co

Biofilm meta-metabolome was impacted after 36 s of exposure to Co

Biofilm meta-metabolome response was faster than changes in biofilm communities

Short- and long-term exposed biofilms have similar CRIDeR initiation thresholds

Long-term exposed biofilms have higher CRIDaR initiation thresholds
Generation and characterization of a novel mouse model of Becker Muscular Dystrophy with a deletion of exons 52 to 55
Authors: Perillat Lucie O. M. , Wong Tatianna W. Y. , Maino Eleonora , Ahmed Abdalla , Scott Ori , Hyatt Elzbieta , Delgado-Olguin Paul , Ivakine Evgueni A. , Cohn Ronald D.
Published: November 2023

Becker Muscular Dystrophy (BMD) is a rare X-linked recessive neuromuscular disorder caused by in-frame deletions in theDMDgene that result in the production of a truncated, yet functional, dystrophin protein. BMD is often considered a milder form of Duchenne Muscular Dystrophy, in which mutations typically result in the disruption of the reading frame and the malfunction or loss of dystrophin. The consequences of BMD-causing in-frame deletions on the organism are more difficult to predict, especially in regard to long-term prognosis. Here, we employed CRISPR-Cas9 technology to generate a newDmddel52-55 mouse model by deleting exons 52-55, resulting in a typical BMD-like in-frame deletion. To delineate the long-term effects of this deletion, we studied these mice over 52 weeks. Our results suggest that a truncated dystrophin is sufficient to maintain wildtype-like muscle and heart functions in young mice. However, the truncated protein appears insufficient to maintain normal muscle homeostasis and protect against exercise-induced damage at 52 weeks. To further delineate the effects of the exons 52-55 in-frame deletion, we performed RNA-Seq pre– and post-exercise and identified several differentially expressed pathways that could explain the abnormal muscle phenotype observed at 52 weeks in the BMD model.

Summary Statement

We generated and characterized the long-term effects of a Becker Muscular Dystrophy-like in-frame deletion of exon 52 to 55 in mice.
An enterococcal phage protein broadly inhibits type IV restriction enzymes involved in antiphage defense
Authors: Bullen Nathan P. , Johnson Cydney N. , Andersen Shelby E. , Arya Garima , Marotta Sonia R. , Lee Yan-Jiun , Weigele Peter R. , Whitney John C. , Duerkop Breck A.
Published: November 2023

The prevalence of multidrug resistant (MDR) bacterial infections continues to rise as the development of antibiotics needed to combat these infections remains stagnant. MDR enterococci are a major contributor to this crisis. A potential therapeutic approach for combating MDR enterococci is bacteriophage (phage) therapy, which uses lytic viruses to infect and kill pathogenic bacteria. While phages that lyse some strains of MDR enterococci have been identified, other strains display high levels of resistance and the mechanisms underlying this resistance are poorly defined. Here, we use a CRISPR interference (CRISPRi) screen to identify a genetic locus found on a mobilizable plasmid fromEnterococcus faecalisinvolved in phage resistance. This locus encodes a putative serine recombinase followed by a Type IV restriction enzyme (TIV-RE) that we show restricts the replication of phage phi47 inE. faecalis. We further find that phi47 evolves to overcome restriction by acquiring a missense mutation in a TIV-RE inhibitor protein. We show that this inhibitor, termed type IV restriction inhibiting factor A (tifA), binds and inactivates diverse TIV-REs. Overall, our findings advance our understanding of phage defense in drug-resistantE. faecalisand provide mechanistic insight into how phages evolve to overcome antiphage defense systems.
Hierarchical annotation of eQTLs enables identification of genes with cell-type divergent regulation
Authors: Przytycki Pawel F. , Pollard Katherine S.
Published: November 2023

While context-type-specific regulation of genes is largely determined by cis-regulatory regions, attempts to identify cell-type specific eQTLs are complicated by the nested nature of cell types. We present a network-based model for hierarchical annotation of bulk-derived eQTLs to levels of a cell type tree using single cell chromatin accessibility data and no clustering of cells into discrete cell types. Using our model, we annotated bulk-derived eQTLs from the developing brain with high specificity to levels of a cell-type hierarchy. The increased annotation power provided by the hierarchical model allowed for sensitive detection of genes with multiple distinct non-coding elements regulating their expression in different cell types, which we validated in single-cell multiome data and reporter assays. Overall, we find that incorporating the hierarchical organization of cell types provides a powerful way to account for the relationships between cell types in complex tissues.
Drug Response Prediction and Biomarker Discovery Using Multi-Modal Deep Learning
Authors: Taj Farzan , Stein Lincoln D.
Published: November 2023

A major challenge in cancer care is that patients with similar demographics, tumor types, and medical histories can respond quite differently to the same drug regimens. This difference is largely explained by genetic and other molecular variabilities among the patients and their cancers. Efforts in the pharmacogenomics field are underway to understand better the relationship between the genome of the patient’s healthy and tumor cells and their response to therapy. To advance this goal, research groups and consortia have undertaken large-scale systematic screening of panels of drugs across multiple cancer cell lines that have been molecularly profiled by genomics, proteomics, and similar techniques. These large data drug screening sets have been applied to the problem of drug response prediction (DRP), the challenge of predicting the response of a previously untested drug/cell-line combination. Although deep learning algorithms outperform traditional methods, there are still many challenges in DRP that ultimately result in these models’ low generalizability and hampers their clinical application. In this paper, we describe a novel algorithm that addresses the major shortcomings of current DRP methods by combining multiple cell line characterization data, addressing drug response data skewness, and improving chemical compound representation. The result is an open-source, Python-based, command-line program available athttps://github.com/LincolnSteinLab/MMDRP.
PanScreen: A Comprehensive Approach to Off-Target Liability Assessment
Authors: Sellner Manuel S. , Lill Markus A. , Smieško Martin
Published: November 2023

Drug development projects are getting increasingly more expensive while their success rate is stagnating. Safety issues attributed to off-target binding represent a major reason for the failure of new drugs. Besides desired on-target binding, small molecules may interact with off-targets, triggering adverse effects. Therefore, the development of novel methods for early recognition of such issues that are resource-efficient and cost-effective becomes vital. Here, we introduce PanScreen, an online platform for the automated assessment of off-target liabilities. PanScreen combines structure-based modeling techniques with state-of-the-art deep learning methods to not only predict accurate binding affinities but also give insight into potential modes of action. We show that the predictions are approaching experimental accuracy found in public datasets and that the same technology can also be used for other research areas, such as drug repurposing. Such fast and inexpensive methods allow researchers to test not only drug candidates, but all small molecules that might come into contact with a human organism for potential safety concerns very early in the development process. PanScreen is publicly available atwww.panscreen.ch.
Mixed Waste Contamination Selects for a Mobile Genetic Element Population Enriched in Multiple Heavy Metal Resistance Genes
Authors: Goff Jennifer L. , Lui Lauren M. , Nielsen Torben N. , Poole Farris L. , Smith Heidi J. , Walker Kathleen F. , Hazen Terry C. , Fields Matthew W. , Arkin Adam P. , Adams Michael W. W.
Published: November 2023

Mobile genetic elements (MGEs) like plasmids, viruses, and transposable elements can provide fitness benefits to their hosts for survival in the presence of environmental stressors. Heavy metal resistance genes (HMRGs) are frequently observed on MGEs, suggesting that MGEs may be an important driver of adaptive evolution in environments contaminated with heavy metals. Here, we report the meta-mobilome of the heavy metal contaminated regions of the Oak Ridge Reservation (ORR) subsurface. This meta-mobilome was compared to one derived from samples collected from unimpacted regions of the ORR subsurface. We assembled 1,615 unique circularized DNA elements that we propose to be MGEs. The circular elements from the highly contaminated subsurface were enriched in HMRG clusters relative to those from the nearby unimpacted regions. Additionally, we found that these HMRGs were associated with Gamma and Betaproteobacteria hosts in the contaminated subsurface and potentially facilitate the persistence and dominance of these taxa in this region. Finally, the HMRGs were associated with conjugative elements, suggesting their potential for future lateral transfer. We demonstrate how our understanding of MGE ecology, evolution, and function can be enhanced through the genomic context provided by completed MGE assemblies.
Guide RNA structure design enables combinatorial CRISPRa programs for biosynthetic profiling
Authors: Fontana Jason , Sparkman-Yager David , Faulkner Ian , Cardiff Ryan , Kiattisewee Cholpisit , Walls Aria , Primo Tommy G. , Kinnunen Patrick C. , Martin Hector Garcia , Zalatan Jesse G. , Carothers James M.
Published: November 2023

Engineering bacterial metabolism to efficiently produce chemicals and materials from multi-step pathways requires optimizing multi-gene expression programs to achieve enzyme balance. CRISPR-Cas transcriptional control systems are emerging as important metabolic engineering tools for programming multi-gene expression regulation. However, poor predictability of guide RNA folding can disrupt enzyme balance through unreliable expression control. We devised a set of computational parameters that can describe guide RNA folding, and we expect them to be broadly applicable across CRISPR-Cas9 systems. Here, we correlate efficacy of modified guide RNAs (scRNAs) for CRISPR activation (CRISPRa) inE. coliwith a kinetic parameter describing folding rate into the active structure. This parameter also enables forward design of new scRNAs, with no observed failures in our screen. We use CRISPRa target sequences from this set to design a system of three synthetic promoters that can orthogonally activate and tune expression of chosen outputs over a >35-fold dynamic range. Independent activation tuning allows experimental exploration of a three-dimensional expression design spaceviaa 64-member combinatorial triple-scRNA library. We apply these CRISPRa programs to two biosynthetic pathways, demonstrating production of valuable pteridine and human milk oligosaccharide products inE. coli. Profiling these design spaces indicated expression combinations producing up to 2.3-fold higher titer than that produced by maximal expression. Mapping production can also identify bottlenecks as targets for pathway redesign, improving titer of the oligosaccharide lacto-N-tetraose by 6-fold. Aided by computational scRNA efficacy prediction, the combinatorial CRISPRa strategy enables effective optimization of multi-step metabolic pathways. More broadly, the guide RNA design rules uncovered here may enable the routine design of effective multi-guide programs for a wide range of model- and data-driven applications of CRISPR gene regulation in bacterial hosts.
The similarities in microbial and chemical patterns of fermentation in two open environments were promoted by using 150-year-old Nukadoko as starters
Authors: Yamaguchi Marin , Imai Kota , Chen Dominique , Seong Young ah , Jo Kazuhiro , Ito Kohei
Published: November 2023

Nukadoko, a fermented rice bran employed in traditional Japanese pickling, uses lactic acid bacteria to ferment vegetables. Here, we report the microbial and chemical data of a mixture of matured 150-year-old nukadoko and commercially available rice bran placed in two open environments over 29 days. Across the two environments,Loigolactobacilluswas identified as the dominant microbial genera in the later stages of fermentation in nukadoko. The period of increase in the relative abundance ofLoigolactobacilluscorrelated with a decrease in pH and Oxidation-Reduction Potential (ORP) values. While the two environments showed a difference in the rate of change in microbial diversity, they shared the common process through whichLoigolactobacillusoutcompeted adventitious bacteria in nukadoko, as indicated by the alpha and beta diversity index. Thus, the similarities in microbial and chemical data across two open environments during fermentation using starters indicate that starters contribute to the stability of fermentation in open environments.
Perceptual constancy for an odour is acquired through changes in primary sensory neurons
Authors: Conway Mark , Oncul Merve , Allen Kate , Johnston Jamie
Published: November 2023

The ability to consistently recognise an object despite sensory input that varies with environmental conditions and/or distance from the object is termed perceptual constancy. This is not an innate ability, rather it develops early in life and is likely dependent upon experience (1,2). The neural mechanisms underpinning the development of perceptual constancy are poorly understood. We have taken advantage of the olfactory system of mice and show that when mice are naïve to an odour a perceptual shift occurs with increasing concentration. The perceptual shift coincides with a rapid reduction in activity of a single olfactory receptor channel that is most sensitive to the odour. This drop in activity is not a property of circuit interactions within the olfactory bulb, rather it is due to a sensitivity miss-match of olfactory receptor neurons within the nose. We show that after forming an association of this odour with food, the sensitivity of the receptor channel is matched to the odour object, preventing transmission failure and promoting perceptual stability. These data show that plasticity of the primary sensory organ enables learning of perceptual constancy.
Programming Probiotics: Diet-responsive gene expression and colonization control in engineeredS. boulardii
Authors: Durmusoglu Deniz , Haller Daniel J. , Al’Abri Ibrahim S. , Day Katie , Sands Carmen , Clark Andrew , San-Miguel Adriana , Vazquez-Uribe Ruben , Sommer Morten O. A. , Crook Nathan C.
Published: November 2023

Saccharomyces boulardii(Sb) is an emerging probiotic chassis for delivering biomolecules to the mammalian gut, offering unique advantages as the only eukaryotic probiotic. However, precise control over gene expression and gut residence time inSbhave remained challenging. To address this, we developed five ligand-responsive gene expression systems and repaired galactose metabolism inSb, enabling inducible gene expression in this strain. Engineering these systems allowed us to construct AND logic gates, control the surface display of proteins, and turn on protein production in the mouse gut in response to a dietary sugar. Additionally, repairing galactose metabolism expandedSb’s habitat within the intestines and resulted in galactose-responsive control over gut residence time. This work opens new avenues for precise dosing of therapeutics bySbvia control over itsin vivogene expression levels and localization within the gastrointestinal tract.
Combining evolution and protein language models for an interpretable cancer driver mutation prediction with D2Deep
Authors: Tzavella Konstantina , Diaz Adrian , Olsen Catharina , Vranken Wim
Published: November 2023

The mutations driving cancer are being increasingly exposed through tumor-specific genomic data. However, differentiating between cancer-causing driver mutations and random passenger mutations remains challenging. State-of-the-art homology-based predictors contain built-in biases and are often ill-suited to the intricacies of cancer biology. Protein Language Models have successfully addressed various biological problems but have not yet been tested on the challenging task of cancer driver mutation prediction at large scale. Additionally, they often fail to offer result interpretation, hindering their effective use in clinical settings. The AI-based D2Deep method we introduce here addresses these challenges by combining two powerful elements: i) a non-specialized protein language model that captures the makeup of all protein sequences and ii) protein-specific evolutionary information that encompasses functional requirements for a particular protein. D2Deep relies exclusively on sequence information, outperforms state-of-the-art predictors and captures intricate epistatic changes throughout the protein caused by mutations. These epistatic changes correlate with known mutations in the clinical setting and can be used for the interpretation of results. The model is trained on a balanced, somatic training set and so effectively mitigates biases related to hotspot mutations compared to state-of-the-art techniques. The versatility of D2Deep is illustrated by its performance on non-cancer mutation prediction, where most variants still lack known consequences. D2Deep predictions and confidence scores are available viahttps://tumorscope.be/d2deepto help with clinical interpretation and mutation prioritization.
Remedial education program for Syrian refugees: ensuring their learning during a protracted crisis
Authors: Komatsu Taro , Ghalawinji-Yamamoto Kaoru , Iwama Yukari , Hattori Sayo
Published: November 2023

Purpose

The purpose of this paper is to explore how vulnerable refugee children's education can be supported in the first asylum country during a long-term, complex crisis. More specifically, the authors examine the impact of a remedial education (RE) program on academically challenged Syrian refugees' sustained learning and well-being in Jordan during a protracted emergency.

Design/methodology/approach

Using the 2012 United Nations human security framework, the authors analyze the quantitative results of program evaluation, supplemented by qualitative surveys and stakeholder interviews that asked about the aspirations of refugee children and their guardians, their school experience and the refugee–host community relationship.

Findings

The authors' data suggest that the program enhanced targeted Syrians' protection and empowerment. Their increased sense of safety and improved academic performance and learning motivation were likely owing to child-friendly classroom management and pedagogies that facilitated interactive and differentiated learning. Their human security was further strengthened when they learned with Jordanian children who experienced similar academic challenges and with teachers sympathetic to their plight. Meanwhile, a human security framework calls for humanitarian agencies' strategic engagement with local partners to ensure refugees' learning continuity.

Originality/value

Refugee education studies in first asylum countries are rare. Even rarer are studies focusing on academically low-achieving refugees with full consideration of the protracted and complex nature of a crisis. This study suggests effective measures to increase their human security while calling for humanitarian aid organizations to use long-term thinking.
Blended learning classroom model: a new extended teaching approach for new normal
Authors: Inprasitha Maitree
Published: November 2023

Purpose

The purpose of this research is to explore how and to what extent the Blended Learning Classroom (BLC) model enhances students’ learning experience. The creation of the BLC model was to provide different learning approaches to overcome the challenges in the new normal regarding how we could manage the Thailand Lesson Study Incorporated Open Approach (TLSOA) model to maximize students’ independent learning.

Design/methodology/approach

The researcher employed a participatory observation research design for 178 participants consisting of directors and teachers from 62 schools using a purposive sampling technique. Data were collected using the stimulated recall technique that allowed the participants to reflect and discuss what was happening while they were applying the BLC model.

Findings

A total of 84.9 percent of participants agreed and strongly agreed with the benefits of implementing the BLC model. The results revealed that Lesson Study (LS) teams created the problem situations substantially by emphasizing across-subject. The qualitative findings revealed that there are three valuable insights in terms of the strengths, challenges and effectiveness of implementing the BLC model.

Research limitations/implications

These discussions are limited to a study representative of 62 out of 274 project schools.

Practical implications

The successful implementation of the BLC model requires effective planning, ongoing support for teachers and a suitable infrastructure to ensure access to technology.

Originality/value

This research adds new insight to the scarce amount of literature on students’ active, interactive and self-regulated learning in a BL environment.
Financial distress prediction in private firms: developing a model for troubled debt restructuring
Authors: Mehmood Asad , De Luca Francesco
Published: November 2023

Purpose

This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

Design/methodology/approach

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

Findings

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

Research limitations/implications

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

Practical implications

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

Originality/value

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.
How electronic word of mouth (eWOM) shapes consumer social media shopping
Authors: Beck Brittany , Moore Koskie Melanie , Locander William
Published: November 2023

Purpose

This study aims to contribute to the ongoing discussion of how consumers approach shopping directly via social media by explicating decisions related to trust on social media and how various types of electronic word of mouth (eWOM; ratings and reviews, recommendations and referrals and social media communities) contribute to these decisions.

Design/methodology/approach

A total of 198 respondents with experience shopping directly via social media were instructed to select the platform on which they had the most shopping experience (Facebook, Instagram, TikTok, Pinterest, etc.) to answer relevant survey questions. Structural equation modeling (SEM) was used for analyzing the results.

Findings

Findings reveal that eWOM provided by strong ties (recommendations and referrals; social media communities) is superior to weak ties (ratings and reviews). Surprisingly, ratings and reviews do not significantly relate to trust in the retailer, suggesting that this information may be necessary but not sufficient for trusting retailers on social media.

Originality/value

This research distinguishes trust decisions related to shopping on social media and clarifies how each type of eWOM uniquely influences trust in the retailer by using tie strength theory.