bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding technology-related prescribing errors for system optimisation: the Technology-Related Error Mechanism (TREM) classification
Authors: Raban Magdalena Z. , Merchant Alison , Fitzpatrick Erin , Baysari Melissa T. , Li Ling , Gates Peter J. , Westbrook Johanna I.
Published: September 2024

Objectives

Technology-related prescribing errors curtail the positive impacts of computerised provider order entry (CPOE) on medication safety. Understanding how technology-related errors occur can inform CPOE optimisation. Previously, we developed a classification of the underlying mechanisms of technology-related errors using prescribing error data from two adult hospitals. Our objective was to update the classification using paediatric prescribing error data, and to assess the reliability with which reviewers could independently apply the classification.

Materials and Methods

Using data on 1696 prescribing errors identified by chart review in 2016 and 2017 at a tertiary paediatric hospital, we identified errors that were technology-related. These errors were investigated to classify their underlying mechanisms using our previously developed classification, and new categories were added based on the data. A two-step process was used to identify and classify technology-related errors involving review of the error in the CPOE and simulating the error in the CPOE testing environment.

Results

The Technology-Related Error Mechanism (TREM) classification comprises seven categories and 19 subcategories. The seven categories are: 1) errors due to incorrect system configuration or system malfunction, 2) prescribing on the wrong patient record, 3) selection errors, 4) construction errors, 5) editing errors, 6) errors that occur when using workflows that differ from a paper-based system 7) contributing factor: use of hybrid systems.

Conclusion

Technology-related errors remain a critical issue for CPOE. The updated TREM classification provides a systematic means of assessing and monitoring technology-related errors to inform and prioritise system improvements, and has now been updated for the paediatric setting.

What is already known on this topic

Technology-related errors occur frequently in computerised provider order entry (CPOE).

Technology-related errors can be addressed by CPOE modifications; however, an understanding of how the errors occurred is required.

What this study adds

This study presents a method for classifying how technology-related errors occur, the Technology-Related Error Mechanism (TREM) classification.

How this study might affect research, practice or policy

Using the TREM classification can aid system managers in identifying areas for CPOE optimisation to deliver improved patient safety outcomes.
Comparison of the prevalence and associated factors of chronic kidney disease diagnosed by serum creatinine or cystatin C among young people living with HIV in Uganda
Authors: Nasuuna Esther M , Tomlinson Laurie A , Kalyesubula Robert , Chikwari Chido Dziva , Castelnuovo Barbara , Manabe Yukari C , Nakanjako Damalie , Weiss Helen A.
Published: September 2024

Introduction

Young people living with HIV (YPLHIV) are at increased risk of developing chronic kidney disease (CKD) which is associated with high mortality and morbidity. Early diagnosis is important to halt progression. We aimed to estimate the prevalence and factors associated with CKD among YPLHIV in Kampala, Uganda, and to compare serum creatinine and cystatin C for early diagnosis of CKD in this population.

Methods

A cross-sectional study with YPLHIV aged 10 to 24 years was conducted in seven HIV clinics. Participants provided a urine and blood sample to measure urinary albumin, proteinuria, serum creatinine and cystatin C levels at baseline and after three months. The estimated glomerular filtration rate (eGFR) was calculated using CKDEPI 2021, Cockroft-Gault and bedside Schwartz equations using creatinine or cystatin C. The albumin creatinine ratio (ACR) and proteinuria were measured. CKD was defined as either eGFR <60ml/min/1.73m2or <90ml/min/1.73m2or ACR above 30mg/g on two separate occasions. Univariable and multivariable logistic regression were used to estimate adjusted odds ratios (aOR) and 95% confidence intervals (CI) for factors associated with CKD.

Results

A total of 500 participants were enrolled. Most were female (56%; n=280) and aged 10 to 17 years (66.9%; n=335). CKD prevalence ranged from 0-23% depending on the criteria, equation and biomarker used. Cystatin C-based equations estimated higher prevalence of CKD compared to creatinine-based ones. Prevalence of ACR above 30mg/g was 10.1% and of proteinuria 29%. Factors independently associated with CKD were age (aOR=1.42; 95% CI:1.30-1.51) and male sex (aOR=3.02; 95% CI:1.68-5.43).

Conclusion

CKD prevalence among YPLHIV varied substantially depending on definitions used and the current definition would likely lead to missed cases of CKD among YPLHIV. Estimating equations should be validated against measured GFR in YPLHIV and the optimal definition of CKD in this vulnerable population should be revised to optimise detection and opportunities for reducing disease progression.
Dengue nowcasting in Brazil by combining official surveillance data and Google Trends information
Authors: Xiao Yang , Soares Guilherme , Bastos Leonardo , Izbicki Rafael , Moraga Paula
Published: September 2024

Dengue is a mosquito-borne viral disease that poses significant public health challenges in tropical and sub-tropical regions worldwide. Surveillance systems are essential for dengue prevention and control. However, traditional systems often rely on delayed data, limiting their effectiveness. To address this, nowcasting methods are needed to estimate underreported cases, enabling more timely decision-making. This study evaluates the value of using Google Trends indices of dengue-related keywords to complement official dengue data for nowcasting dengue in Brazil, a country frequently affected by this disease. We compare various nowcasting approaches that incorporate autoregressive features from official dengue cases, Google Trends data, and a combination of both, using a naive approach as a baseline. The performance of these methods is evaluated by nowcasting weekly dengue cases from March to June 2024 across Brazilian states. Error measures and 95% coverage probabilities reveal that models incorporating Google Trends data enhance the accuracy of weekly nowcasts across states and offer valuable insights into dengue activity levels. To support real-time decision-making, we also present Dengue Tracker, a website that displays weekly dengue nowcasts and trends to inform both decision-makers and the public, improving situational awareness of dengue activity. In conclusion, the study demonstrates the value of digital data sources in enhancing dengue nowcasting, and emphasizes the value of integrating alternative data streams into traditional surveillance systems for better-informed decision-making.

Author summary

Dengue is a mosquito-borne viral disease that poses significant public health challenges in tropical and sub-tropical regions worldwide. Surveillance systems are crucial for dengue prevention and control. Unfortunately, traditional systems often rely on delayed data, limiting their effectiveness. To address this, nowcasting methods are needed to estimate underreported cases, enabling more timely decision-making. This study evaluates how Google Trends indices of dengue-related keywords can complement official dengue data to improve nowcasting of dengue in Brazil, a country frequently affected by this disease. We compare the performance of various nowcasting approaches that incorporate Google Trends data with other approaches that rely solely on official reported cases data, assessing their accuracy and uncertainty in nowcasting weekly dengue cases from March to June 2024 across Brazilian states. To support real-time decision-making, we also present Dengue Tracker, a website that displays weekly dengue nowcasts offering valuable insights into dengue activity levels. The study demonstrates the potential of digital data sources in enhancing traditional surveillance systems for better-informed decision-making.
Beyond Words: Non-verbal auditory cognitive impairments in Alzheimer’s Disease dementia
Authors: Lad Meher , Deasy Charlotte , Plack Christopher J , Taylor John-Paul , Griffiths Timothy D
Published: September 2024

Background

Verbal speech-in-noise (SIN) measures are impaired in early Alzheimer’s disease (AD) but may be confounded by linguistic and cultural factors. We investigated whether non-verbal auditory memory could predict cognitive impairment in AD.

Methods

We evaluated 158 cognitively healthy individuals, 26 with mild cognitive impairment (MCI), and 28 with AD dementia using the Addenbrooke’s Cognitive Examination (ACE-III), pure-tone audiometry, verbal SIN tests, and non-verbal auditory memory tests for basic sound features. Group differences were assessed adjusting for age, sex, and education. Logistic regression and receiver operating characteristic (ROC) analyses compared model fit of verbal and non-verbal auditory variables.

Results

All auditory cognition measures were significantly associated with cognition. Non-verbal measures provided a better fit to diagnosis than verbal measures (AIC difference >10), although ROC analyses showed no significant differences between models.

Conclusions

Non-verbal auditory measures are effective measures in distinguishing between cognitively healthy, MCI, and AD dementia individuals.
Childhood Adversity and Adolescent Epigenetic Age Acceleration: The Role of Adolescent Sleep Health
Authors: DiMarzio Karissa , Rojo-Wissar Darlynn M. , Hernandez Valencia Evelyn , Ver Pault Mikayla , Denherder Shane , Lopez Adamari , Lerch Jena , Metrailer Georgette , Merrill Sarah M. , Highlander April , Parent Justin
Published: September 2024

Study Objectives

We investigated how a dimension of early life adversity (ELA) capturing threat in the home relates to later epigenetic age acceleration in adolescence through sleep (duration, efficiency, and timing), to empirically test theoretical models suggesting the importance of sleep as a key mechanism linking ELA with poor health outcomes, and to expand the limited literature on sleep and epigenetic aging among youth.

Methods

We utilized data from 861 participants from the Future of Families and Child Wellbeing Study (FFCWS) who participated in the actigraphy sub study at age 15. Sleep variables used were average total sleep time (TST), sleep efficiency (SE), and sleep onset timing. Home threat was determined at ages 3, 5, and 9 from parent reports on the Child Conflict Tactics Scale (CTS-PC), and epigenetic aging was measured through DNA methylation analyses of saliva samples collected at age 15.

Results

Higher levels of childhood home threat exposure were associated with less adolescent TST, lower SE, and later sleep onset timing. Adolescent SE and timing were associated with a faster pace of aging and epigenetic age acceleration. Sleep efficiency and timing mediated the link between childhood home threat exposure and adolescent epigenetic aging.

Conclusions

Epigenetic embedding of childhood threat exposure in the home may occur through adversity-related sleep disturbances in adolescence. Findings warrant greater attention to pediatric sleep health in theoretical models of biological embedding of adversity and point to the examination of improving sleep health as a potential way to prevent adversity-related epigenetic age acceleration.

Statement of Significance

This study brings together two largely disparate bodies of literature on early life adversity and epigenetics and sleep and epigenetics. Findings advance knowledge on how adversity impacts specific aspects of sleep (duration, efficiency, and timing), and biological aging, offering potential pathways for mitigating long-term health risks associated with childhood adversity.
High levels of IsoDGR-modified fibronectin are associated with higher levels of macrophages and other rupture-prone plaque characteristics in patients undergoing carotid endarterectomy
Authors: Motsak Tetiana , Mol Barend M. , K.R. Hoekstra Joost , Osorio Zuluaga Valentina , Rumpff-Derksen Saskia , Paspali-Strik Ioanna , Cam Ngan Sofon , Pasterkamp Gerard , de Borst Gert J. , Kwan Sze Siu , De Kleijn Dominique
Published: September 2024

Objective: Deamidation of the NGR (Asn-Gly-Arg) motif to the isoDGR (isoAsp-Gly-Arg) motif in fibronectin (IsoDGR-fibronectin) enhances in vitro monocyte and endothelial cell activation. Blocking isoDGR reduces macrophage influx in murine tissues. Although macrophage influx is an important feature of human plaque destabilization, the role for plasma and plaque isoDGR-fibronectin in macrophage influx in the atherosclerotic plaque and thereby increasing plaque vulnerability has not been investigated in large human cohorts. Design: IsoDGR-fibronectin levels in plasma and plaques were measured in carotid endarterectomy (CEA) patients from the Athero Express biobank cohort and associated with macrophage and other vulnerable plaque characteristics in the carotid plaque of the same patient. Methods: Levels of isoDGR-fibronectin were measured using an ELISA. Carotid plaque characteristics were visualized with immunohistochemistry staining and scored semi-quantitatively. Baseline characteristics were analysed with Pearson`s Chi-squared test and Mann-Whitney U-test when applicable. Univariate and multivariate logistics regression analyses were used to identify associations with adverse plaque characteristics. Results: Plasma isoDGR-fibronectin was measured in 730 CEA patients. Patients with moderate/heavy plaque macrophage staining had higher levels of isoDGR-fibronectin than patients with no/minor macrophage staining (multivariate OR 1.40 (95%CI 1.04-1.90, p=0.028)). Of the 730 CEA patients, 348 had plaque samples available for isoDGR-fibronectin measurements. In the multivariate analysis, higher plaque levels of isoDGR-fibronectin were associated with moderate/high plaque macrophage staining (OR 1.22 (95%CI 1.00-1.56, p=0.049)), >40% fat in plaque (OR 1.1.44 (95% CI 1.14-1.86, p=0.004)) and intraplaque haemorrhage (OR 1.38 (95% 1.12-1.72, p=0.003)). Conclusion: In this large human cohort study high plasma and plaque levels of isoDGR-fibronectin were associated with more plaque macrophages and other adverse plaque characteristics. This suggests the involvement of isoDGR-fibronectin in human plaque destabilization that may lead to new potential treatment modalities.
CV.eDNA: A hybrid approach to invertebrate biomonitoring using computer vision and DNA metabarcoding
Authors: Blair Jarrett D. , Weiser Michael D. , Siler Cameron , Kaspari Michael , Smith Sierra N. , McLaughlin Jessica F. , Marshall Katie E.
Published: September 2024

Automated invertebrate classification using computer vision has shown significant potential to improve specimen processing efficiency. However, challenges such as invertebrate diversity and morphological similarity among taxa can make it difficult to infer fine-scale taxonomic classifications using computer vision. As a result, many invertebrate computer vision models are forced to make classifications at coarser levels, such as at family or order.

Here we propose a novel modular method to combine computer vision and bulk DNA metabarcoding specimen processing pipelines to improve the accuracy and taxonomic granularity of individual specimen classifications. To improve specimen classification accuracy, our methods use multimodal fusion models that combine image data with DNA-based assemblage data. To refine the taxonomic granularity of the model’s classifications, our methods cross-references the classifications with DNA metabarcoding detections from bulk samples. We demonstrated these methods using a continental-scale, invertebrate bycatch dataset collected by the National Ecological Observatory Network. We also introduce the CV.eDNA R package, which aims to assist practitioners looking to implement our methods.

Using our methods, we reached a classification accuracy of 79.6% across the 17 taxa using real DNA assemblage data, and 83.6% when the assemblage data was “error-free”, resulting in a 2.2% and 6.2% increase in accuracy when compared to a model trained using only images. After cross-referencing with the DNA metabarcoding detections, we improved taxonomic granularity in up to 72.2% of classifications, with up to 5.7% reaching species-level.

By providing computer vision models with coincident DNA assemblage data, and refining individual classifications using DNA metabarcoding detections, our methods the potential to greatly expand the capabilities of biological computer vision classifiers. Our methods allow computer vision classifiers to infer taxonomically fine-grained classifications when it would otherwise be difficult or impossible due to challenges of morphologic similarity or data scarcity. These methods are not limited to terrestrial invertebrates and could be applied in any instance where image and DNA metabarcoding data are concurrently collected.
Spatiotemporal structure and substates in facial expressions and speech movements
Authors: Cuve Hélio Clemente José , Sowden-Carvalho Sophie , Cook Jennifer
Published: September 2024

Ranging from overt emotion displays to the understated eyebrow raise accompanying speech, facial expressions are indispensable cues in social interaction. Yet, how these inherently dynamic cues contribute to emotion signalling remains only partially understood. One overlooked factor is how facial actions combine and recombine over time to produce nuanced expressions. Moreover, although most face-to-face interactions naturally involve speech, its contribution to facial emotion signalling has been largely neglected. Building on motor control principles and employing a novel data-driven pipeline - combining spatiotemporal dimensionality reduction, dynamic feature extraction, classification and clustering - we investigated the structure and function of facial dynamics in bothExpression onlyandEmotive speechsignals. We show that a few fundamental spatiotemporal patterns reliably differentiated between specific emotion dynamics such as happy, sad and angry as well as betweenExpression onlyandEmotive speechsignals. Furthermore, these spatiotemporal components exhibit meaningful substates, which reflect transient dynamics that are diagnostic of emotion content. This underlying spatiotemporal structure represents an efficient encoding strategy, optimising the transmission and perception of emotion and non-emotion facial signals. These findings have implications for understanding normative and “atypical” face-to-face signalling and can inform the design of expressive emotive capabilities in artificial social agents. Moreover, our data-driven pipeline can be extended to study broader aspects of multimodal social signalling.

Significance Statement

In face-to-face interactions, facial movements convey both emotional and speech-related information, yet their complex dynamic signalling remains only partly understood. This study explores how facial movements evolve over time, integrate emotional and speech cues. Using advanced techniques to measure and analyse moment-to-moment changes in dozens of facial muscles we identified fundamental movement patterns that differentiate emotional signals. These dynamic patterns enable both isolated emotional signalling and simultaneous emotion cues during speech. These findings can inform understanding of typical and atypical face-to-face interactions abilities and enhance the design of human-like facial expressions in social robots and virtual agents. We also contribute a novel data-driven pipeline for analysing facial dynamics, applicable to broader facets of multimodal social communication.
Convergent evolution of somatic escape variants inSERPINA1in the liver in alpha-1 anti-trypsin deficiency
Authors: Brzozowska Natalia , Wu Lily YD , Khodzhaeva Vera , Griffiths William J , Duckworth Adam , Jung Hyunchul , Coorens Tim H H , Hooks Yvette , Chambers Joseph E , Campbell Peter J , Marciniak Stefan J , Hoare Matthew
Published: September 2024

Somatic variants accumulate in non-malignant tissues with age1,2. Functional variants leading to clonal advantage of hepatocytes accumulate in the liver from patients with acquired chronic liver disease (CLD)3–5. Whether these somatic variants are common to CLD from differing aetiologies is unknown. We analysed somatic variants in the liver from patients with genetic CLD from alpha-1 anti-trypsin (A1AT) deficiency or haemochromatosis. We show that somatic variants inSERPINA1, the gene encoding A1AT, are strongly selected for in A1AT deficiency, with evidence of convergent evolution. Acquired variants cluster at the 3’ end ofSERPINA1leading to C-terminal missense or truncation variants of A1AT.In vitro,C-terminal truncation variants abrogate disease-associated A1AT polymerisation and retention in the endoplasmic reticulum, supporting the C-terminal domain swap mechanism. Therefore, somatic escape variants from a deleterious germline variant are selected for in A1AT deficiency, suggesting adaptive functional somatic variants are disease-specific in CLD and point to disease-associated mechanisms.
Idiosyncratic choice bias and feedback-induced bias differ in their long-term dynamics
Authors: Lebovich Lior , Kaplan Lea , Hansel David , Loewenstein Yonatan
Published: September 2024

A well-known observation in repeated-choice experiments is that a tendency to prefer one response over the others emerges if the feedback consistently favors that response. Choice bias, a tendency to prefer one response over the others, however, is not restricted to biased-feedback settings and is also observed when the feedback is unbiased. In fact, participant-specific choice bias, known as idiosyncratic choice bias (ICB), is common even in symmetrical experimental settings in which feedback is completely absent. Here we ask whether feedback-induced bias and ICB share a common mechanism. Specifically, we ask whether ICBs reflect idiosyncrasies in choice-feedback associationspriorto the measurement of the ICB. To address this question, we compare the long-term dynamics of ICBs with feedback-induced biases. We show that while feedback effectively induced choice preferences, its effect is transient and diminished within several weeks. By contrast, we show that ICBs remained stable for at least 22 months. These results indicate that different mechanisms underlie the idiosyncratic and feedback-induced biases.
Standardizing marine habitat modelling practices to enhance inter-comparability across biological observations
Authors: Schickele Alexandre , Clerc Corentin , Benedetti Fabio , De Angelis Daniele , Hofmann-Elizondo Urs , Münnich Matthias , Irisson Jean-Olivier , Vogt Meike
Published: September 2024

In recent years, the volume of accessible marine pelagic observations has increased exponentially and now incorporates a wealth of new data types, including information derived from metagenomics and quantitative imaging. This calls for standardized modelling protocol across taxonomically harmonized observations, to better predict biogeographic patterns in space and time, and thus investigate marine ecosystem structure and functioning on a macroecological scale. In this context, we introduce CEPHALOPOD (Comprehensive Ensemble Pipeline for Habitat modelling Across Large-scale Ocean Pelagic Observation Datasets), a standardized and flexible framework to perform multi-species marine habitat modelling across data types and data sources. We built this new framework on observational data from federating initiatives such as AtlantECO, OBIS, GBIF, associated with already existing statistical and machine learning methods that enable to extract and model information from heterogeneous, scarce, and biased field observations. Here, we first document our statistical ensemble modelling approach and then assess its strength and limitations with a virtual ecologist approach. We show how our framework performs in reproducing a range of distributions from biased field samples. Then, we illustrate its performance and comparability across data types by investigating the global diversity patterns of coccolithophores from both abundance and metagenomic data. Our modelling framework serves as a foundation for the consistent generation of Essential Biodiversity and Ocean Variables (EBVs and EOVs) and carries the potential to significantly advance our comprehension of biodiversity and marine ecosystems functioning. Finally, it provides an unprecedented opportunity to foster collaborations in the field of marine science, sustainable ecological practices, and, ultimately, contribute to the preservation of global marine biodiversity.
Ongoing activation of visual cortex and superior colliculus in therd10mouse model of retinitis pigmentosa
Authors: Rüland Thomas , Doerenkamp Kerstin , Graff Peter Severin , Wetz Sophie , Jain Anoushka , Nabbefeld Gerion , Gehlen Jana , Gilissen Sara RJ , Arckens Lutgarde , Musall Simon , Müller Frank , Kampa Björn M.
Published: September 2024

Efforts in vision restoration have been focused on a condition called Retinitis Pigmentosa, where photoreceptors in the retina degenerate while the rest of the visual pathway remain mostly intact. Retinal implants that replace the phototransduction process by stimulating retinal ganglion cells have shown promising but limited results in patients so far. Apart from technical limitations, cross-modal plasticity of visual areas might contribute to this problem. We therefore investigated if the primary visual cortex (V1) of therd10mouse model for retinal degeneration became more sensitive to auditory or tactile sensory inputs, potentially hindering retinal stimulation. After reaching complete blindness confirmed by the lack of optomotor responses, activity in visual cortex and superior colliculus (SC) was recorded using Neuropixels probes. While we could not find any significant differences in tactile or auditory responses compared to wildtype mice, the local field potential revealed distinct oscillatory events (0.5 – 6 Hz) in V1 and SC resembling previously observed aberrant activity in the retina of rd10 mice. Further absence of cross-modal plasticity was confirmed by a lacking increase inzif268expression in V1 after tactile stimulation. We therefore propose that aberrant retinal activity is transmitted to higher visual areas where it prevents cross-modal changes.
ERVcancer: a web resource designed for querying activation of human endogenous retroviruses across major cancer types
Authors: Lei Xiaoyun , Mao Song , Li Yinshuang , Huang Shi , Li Jinchen , Du Wei , Kuang Chunmei , Yuan Kai
Published: September 2024

Human endogenous retroviruses (HERVs) compose approximately 8% of the human genome, co-opted into the dynamic regulatory network of cellular potency in early embryonic development. In recent studies, resurgent HERVs’ transcriptional activity has been frequently observed in many types of human cancers, suggesting their potential functions in the occurrence and progression of malignancy. However, a web resource dedicated to querying the relationship between activation of HERVs and cancer development is lacking. Here, we have constructed a database to explore the sequence information, expression profiles, survival prognosis, and genetic interactions of HERVs in diverse cancer types. Our database currently incorporates RNA sequencing (RNA-seq) data of 580 HERVs across 16246 samples, comprising 151 early embryonic data from the Gene Expression Omnibus (GEO) database, 8051 human adult tissues’ data from the Genotype-Tissue Expression (GTEx) project, 932 cancer cell lines’ data from the Cancer Cell Line Encyclopedia (CCLE) project, 6478 tumoral and 634 normal tissue samples’ data from The Cancer Genome Atlas (TCGA) project. The primary goal is to provide an easily accessible and user-friendly database for professionals in the fields of bioinformatics, pathology, pharmacology, and related areas, enabling them to efficiently screen the activity of HERVs of interest in normal and cancerous tissues and evaluate the clinical relevance. The ERVcancer database is available athttp://kyuanlab.com/ervcancer/.
Sociability genetically separable from social hierarchy in amniotes
Authors: Lin Xin , Dai Guangyi , Zhou Sumei , Li Yangyang , Pan Yi-Hsuan , Li Haipeng
Published: September 2024

The emergence of social structure and organization is essential for the evolution of amniotes, including human beings. Sociability and social hierarchy are two key features to form a social group. However, it remains unknown whether sociability and social hierarchy are genetically separable. In this study, we examined the social hierarchy, social and social novelty preference of PAS1 (placental-accelerated sequence 1) knock-out and knock-in mice. PAS1 is a social enhancer that modulates social hierarchy. We found that PAS1 knock-out mice lack social hierarchy while wallaby/chicken PAS1 knock-in mice establish stable social ranks. Moreover, social and social novelty preference was observed in all PAS1-mutated mice. PAS1 knock-in mice have stronger preference to interact with other mice than wild-type mice (C57BL/6). No aggressive alteration was found in PAS1-mutated mice. Overall, our results showed that PAS1 is an indispensable regulatory element in the formation of social hierarchy while PAS1 regulates one of pathways modulating sociability. Therefore, sociability is genetically separable from social hierarchy in amniotes, providing insights into how social structure and organization evolved.

Highlights

PAS1, a social enhancer, is indispensable for amniotes to establish social hierarchy.

PAS1 modulates sociability in amniotes.

Sociability and social hierarchy are regulated differently in amniotes.

The frequency of PAS1 allele was not rare when social hierarchy first appeared.
Di-HAMP domains of a cytoplasmic chemoreceptor modulate nucleoid array formation and downstream signalling
Authors: Jazleena Panikkaveetil Jawaharlal , Das Apurba , Guiseppi Annick , Debard Fabian , Sharma Jaya , Yaikhomba Mutum , Mignot Tam , Mauriello Emilia MF , Gayathri Pananghat
Published: September 2024

In bacterial chemosensing, environmental cues are typically sensed by bacterial transmembrane receptors known as methyl accepting chemotaxis proteins (MCPs). MCPs form highly organized arrays using the bacterial membrane as a scaffold, which amplify the signals and transduce them into a cellular response. The FrzCD cytoplasmic receptor from Myxococcus xanthus is unique due to its ability to bind DNA and use the nucleoid as a scaffold to form arrays. In this study, we identified two HAMP (histidine kinase, adenylyl cyclase, MCP and phosphatase) domains located between the DNA binding and signaling domains of FrzCD. In vitro experiments demonstrate that these HAMP domains restrict FrzCD to a dimeric form in solution and modulate FrzCD's affinity for DNA, whereas the signaling domain stabilizes higher-order oligomeric assemblies upon DNA binding. Through fluorescence microscopy and analyses on Myxococcus social behavior, we demonstrate that the impact of FrzCD HAMP domains on DNA binding and oligomerization significantly influences group motility and development. Our results suggest that HAMP domains might have roles not only in signal transduction but also in the plasticity of chemosensory arrays. These observations illustrate mechanisms of regulation of a DNA-bound cytoplasmic array formed by a diffusible MCP.
Microbial populations hardly ever grow logistically and never sublinearly
Authors: Camacho-Mateu José , Lampo Aniello , Castro Mario , Cuesta José A.
Published: September 2024

We investigate the growth dynamics of microbial populations, challenging the conventional logistic model. By analyzing empirical data from various biomes, we demonstrate that microbial growth is better described by a generalized logistic model, theθ-logistic model. This accounts for different growth mechanisms and environmental fluctuations, leading to a generalized gamma distribution of abundance fluctuations. Our findings reveal that microbial growth is never sublinear, so they cannot endorse—at least in the microbial world—the recent proposal of this mechanism as a stability enhancer of highly diverse communities. These results have significant implications for understanding macroecological patterns and the stability of microbial ecosystems.
β-Glucan Reprograms Neutrophils to Induce Disease Tolerance Against Influenza A Virus
Authors: Khan Nargis , Chevre Raphael , Sun Sarah , Sadeghi Mina , Pernet Erwan , Herrero Andrea , Grant Alexander , Downey Jeffrey , Barreiro Luis B. , Yipp Bryan G , Soehnlein Oliver , Divangahi Maziar
Published: September 2024

ABSTRACT

Disease tolerance is an evolutionarily conserved host defence strategy that preserves tissue integrity and physiology without affecting pathogen load. Unlike host resistance, the mechanisms underlying disease tolerance remain poorly understood. In the present study, we investigated whether an adjuvant (β-glucan) can reprogram innate immunity to provide protection against Influenza A virus (IAV) infection. Here we observe that β-glucan treatment reduced the morbidity and mortality against IAV infection, independent of host resistance (viral load). Increased survival of β-glucan treated mice against IAV is associated with the accumulation of neutrophils via RoRγt+T cells in the lung tissue. Using gain-and-loss-of-function approaches, we demonstrate that β- glucan reprogrammed neutrophils are essential for promoting disease tolerance, limiting pulmonary tissue damage, and enhancing survival against IAV infection. β-glucan treatment promotes granulopoiesis in a type 1 interferon-dependent manner that leads to the generation of a unique subset of neutrophils, which are less mature with higher mitochondrial mass utilizing mitochondrial oxidative (OXPHOS) metabolism. Collectively, our data indicate that β-glucan reprograms hematopoietic stem cells (HSCs) to generate neutrophils with a novel “regulatory” function, which is required for promoting disease tolerance and maintaining lung tissue integrity against viral infection.
Mesoscale Explorer - Visual Exploration of Large-Scale Molecular Models
Authors: Rose Alexander , Sehnal David , Goodsell David S. , Autin Ludovic
Published: September 2024

The advent of cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET), coupled with computational modeling, has enabled the creation of integrative 3D models of viruses, bacteria, and cellular organelles. These models, composed of thousands of macromolecules and billions of atoms, have historically posed significant challenges for manipulation and visualization without specialized molecular graphics tools and hardware. With the recent advancements in GPU rendering power and web browser capabilities, it is now feasible to render interactively large molecular scenes directly on the web. In this work, we introduceMesoscale Explorer, a web application built using theMol*framework, dedicated to the visualization of large-scale molecular models ranging from viruses to cell organelles.Mesoscale Explorerprovides unprecedented access and insight into the molecular fabric of life, enhancing perception, streamlining exploration, and simplifying visualization of diverse data types, showcasing the intricate details of these models with unparalleled clarity.

Statement:Mesoscale Explorerleverages advanced GPU rendering and web technologies to facilitate and democratize the interactive 3D visualization of large-scale molecular models from viruses to cellular organelles composed of millions of atoms.Mesoscale Explorerenables broader exploration and deeper understanding of the complex structure of these large molecular landscapes.
Reversible and effective cell cycle synchronization method for studying stage-specific investigations
Authors: Chen Yu-Lin , Reddy Syon , Suzuki Aussie
Published: September 2024

The cell cycle is a crucial process for cell proliferation, differentiation, and development. Numerous genes and proteins play pivotal roles at specific cell cycle stages to regulate these events precisely. Studying the stage-specific functions of the cell cycle requires accumulating cell populations at the desired cell cycle stage. Cell synchronization, achieved through the use of cell cycle kinase and protein inhibitors, is often employed for this purpose. However, suboptimal concentrations of these inhibitors can result in reduced efficiency, irreversibility, and undesirable cell cycle defects. In this study, we have optimized effective and reversible techniques to synchronize the cell cycle at each stage in human RPE1 cells, utilizing both fixed high-precision cell cycle identification methods and high-temporal live-cell imaging. These reproducible synchronization methods are invaluable for investigating the regulatory mechanisms specific to each cell cycle stage.
KegAlign: Optimizing pairwise alignments with diagonal partitioning
Authors: Gulhan A. Burak , Burhans Richard , Harris Robert , Kandemir Mahmut , Haeussler Maximilian , Nekrutenko Anton
Published: September 2024

Our ability to generate sequencing data and assemble it into high quality complete genomes has rapidly advanced in recent years. These data promise to advance our understanding of organismal biology and answer longstanding evolutionary questions. Multiple genome alignment is a key tool in this quest. It is also the area which is lagging: today we can generate genomes faster than we can construct and update multiple alignments containing them. The bottleneck is in considerable computational time required to generate accurate pairwise alignments between divergent genomes, an unavoidable precursor to multiple alignments. This step is typically performed with lastZ, a very sensitive and yet equally slow tool. Here we describe an optimized GPU-enabled pairwise aligner KegAlign. It incorporates a new parallelization strategy, diagonal partitioning, with the latest features of modern GPUs. With KegAlign a typical human/mouse alignment can be computed in under 6 hours on a machine containing a single NVidia A100 GPU and 80 CPU cores without the need for any pre-partitioning of input sequences: a ∼150× improvement over lastZ. While other pairwise aligners can complete this task in a fraction of that time, none achieves the sensitivity of KegAlign’s main alignment engine, lastZ, and thus may not be suitable for comparing divergent genomes. In addition to providing the source code and a Conda package for KegAlign we also provide a Galaxy workflow that can be readily used by anyone.
Histamine interferes with the early visual processing in mice
Authors: Tripodi Matteo , Asari Hiroki
Published: September 2024

Sensory processing is dynamically modulated by an animal’s behavior and internal states. Growing evidence suggests that such modulation starts from early stages, even at the retina, but the underlying mechanisms remain elusive. Combining pharmacological and chemogenetic tools with single-unit extracellular recordings in awake head-fixed mice, here we identified that the visual responses of retinal ganglion cells and the lateral geniculate nucleus were both made weaker and slower by histaminergic projections from the tuberomammillary nucleus of the posterior hypothalamus. The observed changes in the visual responses were, however, not directly linked with histaminergic modulation of pupil dynamics or locomotion behavior. Our computational modelling analysis instead suggests neuronal circuit effects, such as gain modulation via the histamine H1 receptors in the retina. As nocturnal animals, facilitation of visual processing at low histamine level is ethologically beneficial for mice to respond faster to visual threats when animals are less active during daytime.
Discovery of interpretable patterning rules by integrating mechanistic modeling and deep learning
Authors: Lu Jia , Luo Nan , Liu Sizhe , Sahu Kinshuk , Maddamsetti Rohan , Baig Yasa , You Lingchong
Published: September 2024

Predictive programming of self-organized pattern formation using living cells is challenging in major part due to the difficulty in navigating through the high-dimensional design space effectively. The emergence and characteristics of patterns are highly sensitive to both system and environmental parameters. Often, the optimal conditions able to generate patterns represent a small fraction of the possible design space. Furthermore, the experimental generation and quantification of patterns is typically labor intensive and low throughput, making it impractical to optimize pattern formation solely based on trials and errors. To this end, simulations using a well-formulated mechanistic model can facilitate the identification of optimal experimental conditions for pattern formation. However, even a moderately complex system can make these simulations computationally prohibitive when applied to a large parameter space. In this study, we demonstrate how integrating mechanistic modeling with machine learning can significantly accelerate the exploration of design space for patterning circuits and aid in deriving human-interpretable design rules. We apply this strategy to program self-organized ring patterns inPseudomonas aeruginosausing a synthetic gene circuit. Our approach involved training a neural network with simulated data to predict pattern formation 10 million times faster than the mechanistic model. This neural network was then used to predict pattern formation across a vast array of parameter combinations, far exceeding the size of the training dataset and what was computationally feasible using the mechanistic model alone. By doing so, we identified many parameter combinations able to generate desirable patterns, which still represent an extremely small fraction of explored parametric space. We next used the mechanistic model to validate top candidates and identify coarse-grained rules for patterning. We experimentally demonstrated the generation and control of patterning guided by the learned rules. Our work highlights the effectiveness in integrating mechanistic modeling and machine learning for rational engineering of complex dynamics in living cells.
Scattering-Based Super-Resolution Optical Fluctuation Imaging
Authors: Yudovich Shimon , Posnjak Gregor , Shani Lior , Teblum Eti , Liedl Tim , Enderlein Jörg , Weiss Shimon
Published: September 2024

Super-resolution optical imaging has become a prominent tool in life and material sciences, allowing one to decipher structures at increasingly greater spatial detail. Among the utilized techniques in this field, super-resolution optical fluctuation imaging (SOFI) has proved to be a valuable approach. A major advantage of SOFI is its less restrictive requirements for generating super-resolved images of neighboring nanostructures or molecules, as it only assumes that the detected fluctuating light from neighboring emitters is statistically uncorrelated, but not necessarily separated in time. While most optical super-resolution microscopies depend on signals obtained from fluorescence, they are limited by photobleaching and phototoxicity. An alternative source for optical signals can be acquired by detecting the light scattered from molecules or nanoparticles. However, the application of coherent scattering-based imaging modalities for super-resolution imaging has been considerably limited compared to fluorescence-based modalities. Here, we develop scattering-based super-resolution optical fluctuation imaging (sSOFI), where we utilize the rotation of anisotropic particles as a source of fluctuating optical signals. We discuss the differences in the application of SOFI algorithms for coherent and incoherent imaging modalities, and utilize interference microscopy to demonstrate super-resolution imaging of rotating nanoparticle dimers. We present a theoretical analysis of the relevant model systems, and discuss the possible effects of cusp artifacts and electrodynamic coupling between nearby nano-scatterers. Finally, we apply sSOFI as a label-free novelty filter that highlights regions with higher activity of biomolecules and demonstrate its use by imaging membrane protrusions of live cells. Overall, the development of optical super-resolution approaches for coherent scattering-based imaging modalities, as described here, could potentially allow for the investigation of biological processes at temporal resolutions and acquisition durations previously inaccessible in fluorescence-based imaging.
Domestic freezer storage: a solution for preserving stool microbiota integrity for at-home collection
Authors: Momo Cabrera Paula , Bokulich Nicholas A. , Zimmermann Petra
Published: September 2024

The gut microbiome is crucial for host health. Early childhood is a critical period for the development of a healthy gut microbiome, but it is particularly sensitive to external influences. Recent research has focused on using advanced techniques like shotgun metagenome sequencing to identify key microbial signatures and disruptions linked to disease. For accurate microbiome analysis, samples need to be collected and stored under specific conditions to preserve microbial integrity and composition, with -80°C storage considered the gold standard for stabilization.

This study investigates the effect of domestic freezer storage on the microbial composition of stool samples from 20 children under 4 years with the use of shotgun metagenomic sequencing. Fresh stool samples were aliquoted into sterile tubes, with one aliquot stored at 4°C and analyzed within 24 hours, while others were frozen in domestic freezers (below -18°C) and analyzed after 1 week, 2 months, and 6 months. Assessments of contig assembly quality, microbial diversity, and antimicrobial resistance genes revealed no significant degradation or variation in microbial composition.

Importance

Most previous studies on sample storage have used amplicon sequencing, which limits relevance to metagenome sequencing, in which contig quality and functional gene detection are additional concerns. Moreover, the effects of domestic freezer storage for at-home stool collection on microbiome profiles, contig quality, and antimicrobial resistance gene profiles have not been tested previously.

Our findings suggest that stool samples stored in domestic freezers for up to six months maintain the integrity of metagenomic data. These findings indicate that domestic freezer storage does not compromise the integrity or reproducibility of metagenomic data, offering a reliable and accessible alternative for temporary sample storage. This approach enhances the feasibility of large-scale at-home stool collection and citizen science projects, even those focused on the more easily perturbed early life microbiome. This advancement enables more inclusive research into the gut microbiome, enhancing our understanding of its role in human health.