bluuebunny/crossref_metadata_2025 huggingface dataset:
Chronic demyelination of rabbit lesions is attributable to failed oligodendrocyte progenitor cell repopulation
Authors: Cooper James J. M. , Polanco Jessie J. , Saraswat Darpan , Peirick Jennifer , Seidl Anna , Li Yi , Ma Dan , Sim Fraser J.
Published: January 2022

The failure of remyelination in the human CNS contributes to axonal injury and disease progression in multiple sclerosis (MS). In contrast to regions of chronic demyelination in the human brain, remyelination in murine models is preceded by abundant oligodendrocyte progenitor cell (OPC) repopulation, such that OPC density within regions of demyelination far exceeds that of normal white matter. As such, we hypothesized that efficient OPC repopulation was a prerequisite of successful remyelination, and that increased lesion volume may contribute to the failure of OPC repopulation in human brain. In this study, we characterized the pattern of OPC activation and proliferation following induction of lysolecithin-induced chronic demyelination in adult rabbits. The density of OPCs never exceeded that of normal white matter and oligodendrocyte density did not recover even at 6 months post-injection. Rabbit OPC recruitment in large lesions was further characterized by chronic Sox2 expression in OPCs located in the lesion core and upregulation of quiescence-associated Prrx1 mRNA at the lesion border. Surprisingly, when small rabbit lesions of equivalent size to mouse were induced, they too exhibited reduced OPC repopulation. However, small lesions were distinct from large lesions as they displayed an almost complete lack of OPC proliferation following demyelination. These differences in the response to demyelination suggest that both volume dependent and species-specific mechanisms are critical in the regulation of OPC proliferation and lesion repopulation and suggest that alternate models will be necessary to fully understand the mechanisms that contribute to failed remyelination in MS.

Main Points

- Chronic demyelination in the rabbit CNS was associated with reduced OPC repopulation.

- Quiescent OPCs accumulated around the edge of rabbit lesions.

- OPC and oligodendrocyte repopulation was reduced in rabbit regardless of lesion volume.
Computational Model of Heterogeneity in Melanoma: Designing Therapies and Predicting Outcomes
Authors: Hodgkinson Arran , Trucu Dumitru , Lacroix Matthieu , Le Cam Laurent , Radulescu Ovidiu
Published: January 2022

Cutaneous melanoma is a highly invasive tumor and, despite the development of recent therapies, most patients with advanced metastatic melanoma have a poor clinical outcome. The most frequent mutations in melanoma affect the BRAF oncogene, a protein kinase of the MAPK signaling pathway. Therapies targeting both BRAF and MEK are effective for only 50% of patients and, almost systematically, generate drug resistance. Genetic and non-genetic mechanisms associated with the strong heterogeneity and plasticity of melanoma cells have been suggested to favor drug resistance but are still poorly understood. Recently, we have introduced a novel mathematical formalism allowing the representation of the relation between tumor heterogeneity and drug resistance and proposed several models for the development of resistance of melanoma treated with BRAF/MEK inhibitors. In this paper, we further investigate this relationship by using a new computational model that copes with multiple cell states identified by single cell mRNA sequencing data in melanoma treated with BRAF/MEK inhibitors. We use this model to predict the outcome of different therapeutic strategies. The reference therapy, referred to as “continuous” consists in applying one drug (or several drugs) without disruption. In “combination therapy”, several drugs are used sequentially. In “adaptive therapy” drug application is interrupted when the tumor size is below a lower threshold and resumed when the size goes over an upper threshold. We show that, counter-intuitively, the optimal protocol in combination therapy of BRAF/MEK inhibitors with a hypothetical drug targeting cell states that develop later during the tumor response to kinase inhibitors, is to treat first with this hypothetical drug. Also, even though there is little difference in the timing of emergence of the resistance between continuous and adaptive therapies, the spatial distribution of the different melanoma subpopulations is more zonated in the case of adaptive therapy.
DelaySSAToolkit.jl: stochastic simulation of reaction systems with time delays in Julia
Authors: Fu Xiaoming , Zhou Xinyi , Gu Dongyang , Cao Zhixing , Grima Ramon
Published: January 2022

DelaySSAToolkit.jl is a Julia package for modelling reaction systems with non-Markovian dynamics, specifically those with time delays. These delays implicitly capture multiple intermediate reaction steps and hence serve as an effective model reduction technique for complex systems in biology, chemistry, ecology and genetics. The package implements a variety of exact formulations of the delay stochastic simulation algorithm.

Contact

xmfu@ecust.edu.cn, zcao@ecust.edu.cn, or ramon.grima@ed.ac.uk

Availability and Implementation

The source code and documentation of DelaySSAToolkit.jl are available at https://github.com/palmtree2013/DelaySSAToolkit.jl.
Coherence of Terrestrial Vertebrate Species Richness with External Drivers Across Scales and Taxonomic Groups
Authors: O’Malley Conor P. B. , Roberts Gareth G. , Mannion Philip D. , Hackel Jan , Wang Yanghua
Published: January 2022

Aim

Understanding connections between environment and biodiversity is crucial for conservation, identifying causes of ecosystem stress, and predicting population responses to changing environments. Explaining biodiversity requires an understanding of how species richness and environment co-vary across scales. Here, we identify scales and locations at which biodiversity is generated and correlates with environment.

Location

Full latitudinal range per continent.

Time period

Present-day.

Major taxa studied

Terrestrial vertebrates: all mammals, carnivorans, bats, songbirds, humming-birds, amphibians.

Methods

We describe the use of wavelet power spectra, cross-power and coherence for identifying scale-dependent trends across Earth’s surface. Spectra reveal scale- and location-dependent coherence between species richness and topography (E), mean annual precipitation (Pn), temperature (Tm) and annual temperature range (∆T).

Results

>97% of species richness of taxa studied is generated at large scales, i.e. wavelengths 103km, with 30–69% generated at scales 104km. At these scales, richness tends to be highly coherent and anti-correlated withEand ∆T, and positively correlated withPnandTm. Coherence between carnivoran richness and ∆Tis low across scales, implying insensitivity to seasonal temperature variations. Conversely, amphibian richness is strongly anti-correlated with ∆Tat large scales. At scales 103km, examined taxa, except carnivorans, show highest richness within the tropics. Terrestrial plateaux exhibit high coherence between carnivorans andEat scales∼103km, consistent with contribution of large-scale tectonic processes to biodiversity. Results are similar across different continents and for global latitudinal averages. Spectral admittance permits derivation of rules-of-thumb relating long-wavelength environmental and species richness trends.

Main conclusions

Sensitivities of mammal, bird and amphibian populations to environment are highly scale-dependent. At large scales, carnivoran richness is largely independent of temperature and precipitation, whereas amphibian richness correlates strongly with precipitation and temperature, and anti-correlates with temperature range. These results pave the way for spectral-based calibration of models that predict biodiversity response to climate change scenarios.
Time-resolved parameterization of aperiodic and periodic brain activity
Authors: Wilson Luc E. , da Silva Castanheira Jason , Baillet Sylvain
Published: January 2022

Macroscopic neural dynamics comprise both aperiodic and periodic signal components. Recent advances in parameterizing neural power spectra offer practical tools for evaluating these features separately. Although neural signals vary dynamically and express non-stationarity in relation to ongoing behaviour and perception, current methods yield static spectral decompositions. Here, we introduce Spectral Parameterization Resolved in Time (SPRiNT) as a novel method for decomposing complex neural dynamics into periodic and aperiodic spectral elements in a time- resolved manner. First, we demonstrate with naturalistic synthetic data SPRiNT’s capacity to reliably recover time-varying spectral features. We emphasize SPRiNT’s specific strengths compared to other time-frequency parameterization approaches based on wavelets. Second, we use SPRiNT to illustrate how aperiodic spectral features fluctuate across time in empirical resting-state electroencephalography data (n = 178), and relate the observed changes in aperiodic parameters over time to participants’ demographics and behaviour. Lastly, we use SPRiNT to demonstrate how aperiodic dynamics relate to movement behaviour in intracranial recordings in rodents. We foresee SPRiNT responding to growing neuroscientific interests in the parameterization of time-varying neural power spectra and advancing the quantitation of complex neural dynamics at the natural time scales of behaviour.

Significance Statement

The new method and reported findings address a growing interest in neuroscience for research tools that can reliably decompose brain activity at the mesoscopic scale into interpretable components. We show that the new approach proposed is capable of tracking transient, dynamic spectral (aperiodic and periodic) components across time, both in synthetic data and in in vivo experimental data. We anticipate that this novel technique, SPRiNT, will enable new neuroscience inquiries that reconcile multifaceted neural dynamics with complex behaviour.
chromMAGMA: regulatory element-centric interrogation of risk variants
Authors: Nameki Robbin , Shetty Anamay , Dareng Eileen , Tyrer Jonathan , Lin Xianzhi ,   the Ovarian Cancer Association Consortium, Pharoah Paul , Corona Rosario I. , Kar Siddhartha , Lawrenson Kate
Published: January 2022

Genome-wide association studies (GWASs) have identified thousands of genetic variants associated with common polygenic traits. The candidate causal risk variants reside almost exclusively in noncoding regions of the genome and the underlying mechanisms remain elusive for most. Innovative approaches are necessary to understand their biological function. Multimarker analysis of genomic annotation (MAGMA) is a widely used program that nominates candidate risk genes by mapping single-nucleotide polymorphism (SNP) summary statistics from genome-wide association studies to gene bodies. We augmented MAGMA into chromatin-MAGMA (chromMAGMA), a novel method to nominate candidate risk genes based on the presence of risk variants within noncoding regulatory elements (REs). We applied chromMAGMA to a genetic susceptibility dataset for epithelial ovarian cancer (EOC), a rare gynecologic malignancy characterized by high mortality. Disease-specific RE landscapes were defined using H3K27ac chromatin immunoprecipitation-sequence data. This identified 155 unique candidate EOC risk genes across five EOC histotypes; 83% (105/127) of high-grade serous ovarian cancer risk genes had not previously been implicated in this EOC histotype. Risk genes nominated by chromMAGMA converged on mRNA splicing and transcriptional dysregulation pathways. chromMAGMA is a pipeline that nominates candidate risk genes through a gene regulation-focused approach and helps interpret the biological mechanism of noncoding risk variants in complex diseases.
Transcriptional mapping of the macaque retina and RPE-choroid reveals conserved inter-tissue transcription drivers and signaling pathways
Authors: Mungale Ameera , McGaughey David M. , Zhang Congxiao , Yousaf Sairah , Liu James , Brooks Brian P. , Maminishkis Arvydas , Fufa Temesgen D. , Hufnagel Robert B.
Published: January 2022

Purpose

The macula and fovea comprise a highly sensitive visual detection tissue that is susceptible to common disease processes like age-related macular degeneration (AMD). Our understanding of the molecular determinants of high acuity vision remains unclear, as few model organisms possess a human-like fovea. We explore transcription factor networks and receptor-ligand interactions to elucidate tissue interactions in the macula and peripheral retina and concomitant changes in the underlying retinal pigment epithelium (RPE)/choroid.

Methods

Poly-A selected, 100 bp paired-end RNA-sequencing (RNA-seq) was performed across the macular/foveal, perimacular, and temporal peripheral regions of the neural retina and RPE/choroid tissues of four adult Rhesus macaque eyes to characterize region- and tissue-specific gene expression. RNA-seq reads were mapped to both the macaque and human genomes for maximum alignment and analyzed for differential expression and Gene Ontology (GO) enrichment.

Results

Comparison of the neural retina and RPE/choroid tissues indicated distinct, contiguously changing gene expression profiles from fovea through perimacula to periphery. Top GO enrichment of differentially expressed genes in the RPE/choroid included cell junction organization and epithelial cell development. Expression of transcriptional regulators and various disease-associated genes show distinct location-specific preference and retina-RPE/choroid tissue-tissue interactions.

Conclusions

Regional gene expression changes in the macaque retina and RPE/choroid is greater than that found in previously published transcriptome analysis of the human retina and RPE/choroid. Further, conservation of human macula-specific transcription factor profiles and gene expression in macaque tissues suggest a conservation of programs required for retina and RPE/choroid function and disease susceptibility.
FAME: Fragment-based Conditional Molecular Generation for Phenotypic Drug Discovery
Authors: Pham Thai-Hoang , Xie Lei , Zhang Ping
Published: January 2022

De novo molecular design is a key challenge in drug discovery due to the complexity of chemical space. With the availability of molecular datasets and advances in machine learning, many deep generative models are proposed for generating novel molecules with desired properties. However, most of the existing models focus only on molecular distribution learning and target-based molecular design, thereby hindering their potentials in real-world applications. In drug discovery, phenotypic molecular design has advantages over target-based molecular design, especially in first-in-class drug discovery. In this work, we propose the first deep graph generative model (FAME) targeting phenotypic molecular design, in particular gene expression-based molecular design. FAME leverages a conditional variational autoencoder framework to learn the conditional distribution generating molecules from gene expression profiles. However, this distribution is difficult to learn due to the complexity of the molecular space and the noisy phenomenon in gene expression data. To tackle these issues, a gene expression denoising (GED) model that employs contrastive objective function is first proposed to reduce noise from gene expression data. FAME is then designed to treat molecules as the sequences of fragments and learn to generate these fragments in autoregressive manner. By leveraging this fragment-based generation strategy and the denoised gene expression profiles, FAME can generate novel molecules with a high validity rate and desired biological activity. The experimental results show that FAME outperforms existing methods including both SMILES-based and graph-based deep generative models for phenotypic molecular design. Furthermore, the effective mechanism for reducing noise in gene expression data proposed in our study can be applied to omics data modeling in general for facilitating phenotypic drug discovery.
Brain-optimized neural networks learn non-hierarchical models of representation in human visual cortex
Authors: St-Yves Ghislain , Allen Emily J. , Wu Yihan , Kay Kendrick , Naselaris Thomas
Published: January 2022

Deep neural networks (DNNs) trained to perform visual tasks learn representations that align with the hierarchy of visual areas in the primate brain. This finding has been taken to imply that the primate visual system forms representations by passing them through a hierarchical sequence of brain areas, just as DNNs form representations by passing them through a hierarchical sequence of layers. To test the validity of this assumption, we optimized DNNs not to perform visual tasks but to directly predict brain activity in human visual areas V1–V4. Using a massive sampling of human brain activity, we constructed brain-optimized networks that predict brain activity even more accurately than task-optimized networks. We show that brain-optimized networks can learn representations that diverge from those formed in a strict hierarchy. Brain-optimized networks do not need to align representations in V1–V4 with layer depth; moreover, they are able to accurately model anterior brain areas (e.g., V4) without computing intermediary representations associated with posterior brain areas (e.g., V1). Our results challenge the view that human visual areas V1–V4 act—like the early layers of a DNN—as a serial pre-processing sequence for higher areas, and suggest they may subserve their own independent functions.
Evaluating the Phytotoxicity of Methanolic Extracts of Parthenium hysterophorus L. on Selected Crops and Weeds
Authors: Khairul Bashar H.M. , Juraimi Abdul Shukor , Ahmad-Hamdani Muhammad Saiful , Uddin Md Kamal , Asib Norhayu , Anwar Md. Parvez , Rahaman Ferdoushi , Haque Mohammad Amdadul , Hossain Akbar
Published: January 2022

Herbicides made from natural molecules may be a good environmentally friendly alternative to synthetic chemical herbicides for weed control. As a result, this investigation was carried out to ascertain the phytotoxicity of Parthenium hysterophorus L. as well as to identify its phenolic components. Germination of seeds and development of seedlings of Vigna subterranea (L.) Verdc, Raphanus sativus (L.) Domin, Cucurbita maxima Duchesne., Cucumis sativus L., Solanum lycopersicum L., Capsicum frutescens L., Zea mays L., Abelmoschus esculentus (L.) Moench, Daucus carota L., Digitaria sanguinalis (L.) Scop and Eleusine indica (L.) Gaertn were investigated using P. hysterophorus leaf, stem, and flower methanol extracts. Six concentrations (25, 50, 75, 100, and 150 g L−1) were comparison to the control (distilled water). The concentration of extracts increased, the rate of the seed sprouting and seedling growth decreased. EC50 values showed that the extraction of leaf of P. hysterophorus (811) was phytotoxic in comparison to the stem (1554) and flower (1109) extract. According to PCA analysis, Raphanus sativus, Solanum lycopersicum, Capsicum frutescens, Abelmoschus esculentus, Daucus carota, Digitaria sanguinalis, and Eleusine indica were all very susceptible to allelochemicals. A LC-MS analysis revealed that the P. hysterophorus leaf extract contained 7 phenolic compounds that were responsible for inhibition. These studies also revealed that the leaf of P. hysterophorus is a major source of phytotoxicity, which could be valuable in the future for developing a natural herbicide.
Cardiovascular Risk Models in Chronic Kidney Disease: A Systematic Review and External Validation of Models
Authors: Major Rupert W , Grant Robert , Shepherd David , Medcalf James F , Jesus-Silva Jorge , Gray Laura J , Brunskill Nigel J
Published: January 2022

Background and Objectives

Risk factors for cardiovascular disease in chronic kidney disease differ to the general population due to the increased role of inflammation, calcification and arteriosclerosis. Over 350 cardiovascular risk models (“models”) exist in the general population but most have not undergone testing (“external validation”) in other populations, such as cohorts with chronic kidney disease. We aimed to update a previous systematic review of models in chronic kidney disease and then perform external validation of these and general population models in a chronic kidney disease cohort.

Design, Setting, Participants and Measurements

We searched Medline up to 26th August 2020 for models in chronic kidney disease. We performed external validation of models using a primary care chronic kidney disease cohort of 17,248 individuals with 2,072 (12.0%) cardiovascular events, 5,108 (29.6%) deaths and a median follow-up of 5.0 years. Model discrimination and calibration was assessed and where appropriate models were re-calibrated. Multiple imputation was used to account for missing data.

Results

Seven chronic kidney disease specific models were identified. These models and three general population models underwent external validation. All models had worse discrimination of events than in their original cohorts, particularly in the chronic kidney disease specific models. General population models were miscalibrated and overpredicted risk. The major contributor to this was the high competing risk of death from non-cardiovascular causes.

Conclusions

Existing chronic kidney disease cardiovascular risk models performed poorly in external validation. General population cardiovascular disease risk models should be interpreted with caution in individuals with chronic kidney disease as they may overestimate risk due to the competing risk of death. Further development of models to include simultaneous risk prediction for cardiovascular and non-cardiovascular disease risk is required.
Mortality risks associated with empirical antibiotic activity in E. coli bacteraemia: an analysis of electronic health records
Authors: Yoon Chang Ho , Bartlett Sean , Stoesser Nicole , Pouwels Koen B. , Jones Nicola , Crook Derrick W. , Peto Tim E.A. , Walker A. Sarah , Eyre David W.
Published: January 2022

Background

Reported bacteraemia outcomes following inactive empirical antibiotics (as judged by in vitro testing) are conflicting, potentially reflecting heterogeneous effects of species, minimum inhibitory concentration (MIC) breakpoints defining resistance/susceptibility, and times to rescue therapy.

Methods

We investigated adult inpatients with Escherichia coli bacteraemia at Oxford University Hospitals, UK, from 04-February-2014 to 30-June-2021 receiving empirical amoxicillin-clavulanate with/without other antibiotics. We analysed 30-day all-cause mortality from index blood culture using Cox models by in vitro amoxicillin-clavulanate susceptibility (activity) using the EUCAST resistance breakpoint (>8/2mg/L), categorical MIC, and a higher resistance breakpoint (>32/2mg/L), adjusting for other antibiotic activity and multiple confounders including comorbidities, vital signs, and blood tests.

Results

1720 E. coli bacteraemias (1626 patients) were treated with empirical amoxicillin-clavulanate. 30-day mortality was 193/1400 (14%) [any active baseline therapy] and 52/320 (16%) [inactive baseline therapy] (p=0.17). With EUCAST breakpoints, there was no evidence that mortality differed for inactive vs. active amoxicillin-clavulanate (adjusted HR, aHR=1.27 [95%CI 0.83-1.93;p=0.28]), nor of an association with other antibiotic activity (p>0.18). Considering categorical amoxicillin-clavulanate MIC, MICs>32/2 were associated with mortality (aHR=1.85 vs. MIC=2/2 [0.99-3.73;p=0.054]). Using the higher resistance breakpoint, MICs>32/2 were independently associated with higher mortality (aHR=1.82 [1.07-3.10;p=0.027]), as were MICs>32/2 with active baseline aminoglycoside (aHR=2.34 [1.40-3.89;p=0.001), but not MICs>32/2 with active baseline non-aminoglycoside antibiotic(s) (aHR=0.87 [0.40-1.89;p=0.72).

Conclusions

EUCAST-defined amoxicillin-clavulanate resistance was not associated with increased mortality, but a higher resistance breakpoint was. Additional active baseline non-aminoglycoside antibiotics prevented amoxicillin-clavulanate resistance-associated mortality, but active baseline aminoglycosides did not. Granular phenotyping and comparison with clinical outcomes may improve AMR breakpoints.

In patients with E. coli bacteraemia, high-level resistance to baseline empirical amoxicillin-clavulanate (minimum inhibitory concentration >32/2 mg/L) was associated with increased 30-day mortality, which was not compensated for by single-dose aminoglycosides.
SUSTAINED BENEFICIAL EFFECTS OF VACCINATION ON THE CASE FATALITY RATE FOR COVID-19 INFECTIONS
Authors: Murata Glen H. , Murata Allison E. , Perkins Douglas J. , Campbell Heather M. , Mao Jenny T. , Wagner Brent , Mcmahon Benjamin H. , Hagedorn Curt H.
Published: January 2022

Objective

To evaluate the benefits of vaccination on the case fatality rate (CFR) for COVID-19 infections.

Design

Multivariate modeling of data from electronic medical records

Setting

130 medical centers of the United States Department of Veterans Affairs

Participants

339,772 patients with COVID-19 confirmed by nucleic acid amplification testing as of September 30, 2021

Methods

The primary outcome was death within 60 days of the diagnosis. Patients were considered vaccinated if they had completed a full series >= 14 days prior to diagnosis. Cases presenting in July - September of 2021 were considered to have the delta variant. Logistic regression was used to derive adjusted odds ratios (OR) for vaccination and infection with delta versus earlier variants. Models were adjusted for demographic traits, standard comorbidity indices, selected clinical terms, and 3 novel parameters representing all prior diagnoses, all prior vital signs/ baseline laboratory tests, and current outpatient treatment. Patients with a delta infection were divided into 8 cohorts based upon the time from vaccination to diagnosis (in 4-week blocks). A common model was used to estimate the odds of death associated with vaccination for each cohort relative that of all unvaccinated patients.

Results

9.1% of subjects had been fully vaccinated, and 21.5% were presumed to have the delta variant. 18,120 patients (5.33%) died within 60 days of their diagnoses. The adjusted OR for delta infection was 1.87 +/- 0.05 which corresponds to a relative risk of 1.78. The overall adjusted OR for prior vaccination was 0.280 +/- 0.011 corresponding to a relative risk of 0.291. The study of vaccine cohorts with a delta infection showed that the raw CFR rose steadily after 10-14 weeks. However, the OR for vaccination remained stable for 10-34 weeks.

Conclusions

Our study confirms that delta is substantially more lethal than earlier variants and that vaccination is an effective means of preventing COVID death. After adjusting for major selection biases, we found no evidence that the benefits of vaccination on CFR declined over 34 weeks.
Universal guide for skull extraction and custom-fitting of implants to continuous and discontinuous skulls
Authors: Ahmed Zurna , Agha Naubahar , Trunk Attila , Berger Michael , Gail Alexander
Published: January 2022

Intracranial neurophysiological recordings require chronic implants to provide transcranial access to the brain. Especially in larger animals, which participate in experiments over extended periods of time, implants should match the skull curvature to promote osseointegration and avoid tissue and bacterial ingress over time. Proposed CAD methods for designing implants to date have focused on naïve animals with continuous and even skull surfaces and calculate Boolean differences between implant and skull surface to fit the implant to the skull curvature. However, custom-fitting by calculating the difference fails, if a discontinuous skull surface needs to be matched. Also, the difference method does not allow designs with constant material thickness along the skull curvature, e.g. to allow fixed screw lengths. We present a universal step-by-step guide for custom-fitting implants which overcomes these limitations. It is suited for unusual skull conditions, like surface discontinuities or irregularities and includes virtual bending as a process to match skull surfaces while maintaining implant thickness. We demonstrate its applicability for a wide spectrum of scenarios, ranging from complex-shaped single-pieced implants to detailed multi-component implant systems built on even or discontinuous skull. The guide uses only a few software tools and the final virtual product can be manufactured using CNC milling or 3D printing. A detailed description of this process is available on GitHub including step-by-step video instructions suitable for users without any prior knowledge in CAD programming. We report the experience with these implants over several years in 11 rhesus monkeys.

Significance Statement

Chronic implants are essential for intracranial neurophysiological recordings. In this study we show how to custom-design and –fit such implants for rhesus monkeys (Macacca mulatta). Different to existing approaches, our procedure is not limited to even skull surfaces but can be applied to discontinuous or irregular surfaces. It furthermore presents a description of virtual implant bending to match the skull curvature while maintaining implant thickness. The final virtual product can be manufactured using CNC milling or 3D printing. In contrast to previous studies, this guide is suited for users without any prior expertise in CAD programming using our step-by-step video instructions.
The spatial scale of adaptation in a native annual plant and its implications for responses to climate change
Authors: Gorton Amanda J. , Benning John W. , Tiffin Peter , Moeller David A.
Published: January 2022

Spatial patterns of adaptation provide important insights into agents of selection and expected responses of populations to climate change. Robust inference into the spatial scale of adaptation can be gained through reciprocal transplant experiments that combine multiple source populations and common gardens. Here we examine the spatial scale of local adaptation of the North American annual plant common ragweed, Ambrosia artemisiifolia, using data from four common gardens with 22 source populations sampled from across a ∼1200 km latitudinal gradient within the native range. We found evidence of local adaptation at the northernmost common garden, but maladaptation at the two southern gardens, where more southern source populations outperformed local populations. Overall, the spatial scale of adaptation was large — at the three gardens where distance between source populations and gardens explained variation in fitness, it took an average of 820 km for fitness to decline to 50% of its predicted maximum. Taken together, these results suggest that climate change has already caused maladaptation, especially across the southern portion of the range, and may result in northward range contraction over time.
Glaucoma and Alzheimer: Neurodegenerative disorders show an adrenergic dysbalance
Authors: Hohberger Bettina , Prüss Harald , Mardin Christian , Lämmer Robert , Müller Johannes , Wallukat Gerd
Published: January 2022

Glaucoma disease is characterized by an increased intraocular pressure (IOP), glaucomatous alterations of the optic disc and corresponding visual field defects. Even lowering the main risk factor IOP until an individual target level does not prevent this neurodegenerative disorder from proceeding. Several autoimmune mechanisms were discovered, partly showing a functionality. One of these autoimmune phenomena targets the ß2 adrenergic receptor (ß2-AR; i.e. agonistic autoantibodies; ß2-agAAb) and is linked to the elevated IOP and an impaired retinal microcirculation. As neurodegenerative disorder, Alzheimer’s Disease (AD) is postulated to share a common molecular mechanism with glaucoma. In the present study we investigated autoimmune phenomena targeting the ß2-AR in patients with AD. Sera of the patients were analyzed in a rat cardiomyocyte bioassay for the presence of functional autoantibodies against ß2-AR. In addition, different species of amyloid beta (Aß) monomers were tested (Aß1-14, Aß10-25, Aβ10-37 Aß1-40, Aß1-42, Aβ28-40, and [Pyr]-Aß3-42). Our results demonstrate that none of the short-chain Aß (Aß1-14, Aß10-25, or Aβ28-40) showed any agonistic or inhibitory effect on ß2-AR. Contrary, long-chain [Pyr]-Aß3-42, representing a major neurogenic plaque component, exerted an activation that was blocked by the ß2-AR antagonist ICI118.551 indicating that the effect was realized via the ß2-AR. Moreover, the long chain Aß1-40, Aβ1-42, and Aβ10-37 yet not the short-chain Aß peptides prevented the clenbuterol induced desensitization of the ß2-AR. In addition, we identified functional autoantibodies in the sera of AD patients, activating the ß2-AR like the ß2-agAAb found in patients with glaucoma. As autoimmune mechanisms were reportedly involved in the pathogenesis of glaucoma and Alzheimer’s Disease, we postulate that overstimulation of the ß2-AR pathway can induce an adrenergic overdrive, that may play an important role in the multifactorial interplay of neurodegenerative disorders.
A reference single-cell regulomic and transcriptomic map of cynomolgus monkeys
Authors: Qu Jiao , Yang Fa , Zhu Tao , Wang Yingshuo , Fang Wen , Ding Yan , Zhao Xue , Qi Xianjia , Xie Qiangmin , Xu Qiang , Xie Yicheng , Sun Yang , Chen Dijun
Published: January 2022

Non-human primates (NHP) are attractive laboratory animal models that accurately reflect both developmental and pathological features of humans. Here we present a compendium of cell types from the cynomolgus monkey Macaca fascicularis (denoted as ‘Monkey Atlas’) using both single-cell chromatin accessibility (scATAC-seq) and RNA sequencing (scRNA-seq) data at the organism-wide level. The integrated cell map enables in-depth dissection and comparison of molecular dynamics, cell-type composition and cellular heterogeneity across multiple tissues and organs. Using single-cell transcriptomic data, we inferred pseudotime cell trajectories and cell-cell communications to uncover key molecular signatures underlying their cellular processes. Furthermore, we identified various cell-specific cis-regulatory elements and constructed organ-specific gene regulatory networks at the single-cell level. Finally, we performed a comparative analysis of single-cell landscapes among mouse, cynomolgus monkey and human, and we showed that cynomolgus monkey has significantly higher degree of cell-type similarity to human than mouse. Taken together, our study provides a valuable resource for NHP cell biology.
Context-aware knowledge selection and reliable model recommendation with ACCORDION
Authors: Ahmed Yasmine , Telmer Cheryl A. , Zhou Gaoxiang , Miskov-Zivanov Natasa
Published: January 2022

New discoveries and knowledge are summarized in thousands of published papers per year per scientific domain, making it incomprehensible for scientists to account for all available knowledge relevant for their studies. In this paper, we present ACCORDION (ACCelerating andOptimizing modelRecommenDatIONs), a novel methodology and an expert system that retrieves and selects relevant knowledge from literature and databases to recommend models with correct structure and accurate behavior, enabling mechanistic explanations and predictions, and advancing understanding. ACCORDION introduces an approach that integrates knowledge retrieval, graph algorithms, clustering, simulation, and formal analysis. Here, we focus on biological systems, although the proposed methodology is applicable in other domains. We used ACCORDION in nine benchmark case studies and compared its performance with other previously published tools. We show that ACCORDION is:comprehensive, retrieving relevant knowledge from a range of literature sources; veryeffective, reducing the error of the initial baseline model by more than 80%, recommending models that closely recapitulate desired behavior, and outperforming previously published tools;selective, recommending only the most relevant, context-specific, and useful subset (15-20%) of candidate knowledge in literature;diverse, accounting for several distinct criteria to recommend more than one solution, thus enabling alternative explanations or intervention directions.
Look-up and look-down neurons in the mouse visual thalamus during freely moving exploration
Authors: Orlowska-Feuer Patrycja , Ebrahimi Aghileh S. , Zippo Antonio G. , Petersen Rasmus S. , Lucas Robert J. , Storchi Riccardo
Published: January 2022

The traditional view that visuomotor integration is a property of higher brain centres has recently been challenged by the discovery in head-fixed rodents that locomotion increases neuronal activity throughout the early visual system (including the retina). Any appreciation of the importance of this behavioural modulation of visual inputs must encompass a comprehensive understanding of the range of behaviours engaged by this mechanism. This information is unavailable from head-fixed preparations in which head and body postures are fundamentally constrained and dissociated from their natural coupling with visual experience.

We addressed this deficit by recording spiking activity from the primary visual thalamus during freely moving exploration, while simultaneously applying frame-by-frame quantification of postures and movements to robust 3D reconstructions of head and body. We found that postures associated with the animal looking up/down affected activity in >50% neurons. The extent of this effect was comparable to that induced by locomotion. Moreover, the two effects were largely independent and jointly modulated neuronal activity. Thus, while most units were excited by locomotion, some expressed highest firing when the animal was looking up (“look up” neurons) while others when the animal was looking down (“look-down” neurons). These results were observed in the dark, thus representing a genuine behavioural modulation, and were amplified in a lit arena.

These findings define the influence of natural exploratory behaviour on activity in the early visual system and reveal the importance of up/down postures in gating neuronal activity in the primary visual thalamus.
The relaxin receptor RXFP1 signals through a mechanism of autoinhibition
Authors: Erlandson Sarah C. , Rawson Shaun , Osei-Owusu James , Brock Kelly P. , Liu Xinyue , Paulo Joao A. , Mintseris Julian , Gygi Steven P. , Marks Debora S. , Cong Xiaojing , Kruse Andrew C.
Published: January 2022

The relaxin family peptide receptor 1 (RXFP1) is the receptor for relaxin-2, an important regulator of reproductive and cardiovascular physiology. RXFP1 is a multi-domain G protein-coupled receptor (GPCR) with an ectodomain consisting of an LDLa module and leucine-rich repeats. The mechanism of RXFP1 signal transduction is clearly distinct from that of other GPCRs, but remains very poorly understood. Here, we present the cryo-electron microscopy structure of active-state human RXFP1, bound to a single-chain version of the endogenous agonist relaxin-2 and to the heterotrimeric Gs protein. Evolutionary coupling analysis and structure-guided functional experiments reveal that RXFP1 signals through a mechanism of autoinhibition, wherein the receptor’s extracellular loop 2 occupies the orthosteric site in the active state but is inhibited by the ectodomain in the absence of relaxin-2. Our results explain how an unusual GPCR family functions, providing a path to rational drug development targeting the relaxin receptors.
Inflammasome-mediated glucose limitation induces antibiotic tolerance in Staphylococcus aureus
Authors: Beam Jenna E. , Wagner Nikki J. , Lu Kuan-Yi , Rowe Sarah E. , Conlon Brian P.
Published: January 2022

Staphylococcus aureus is a leading human pathogen that frequently causes relapsing infections. Host-pathogen interactions have been shown to have substantial impacts on antibiotic susceptibility and the formation of antibiotic tolerant cells. In this study, we interrogate how a major S. aureus virulence factor, α-toxin, interacts with macrophages to alter the microenvironment of the pathogen, thereby influencing its susceptibility to antibiotics. We find α-toxin-mediated activation of the NLRP3 inflammasome induces antibiotic tolerance in the host cell cytoplasm. Induction of antibiotic tolerance is driven by increased glycolysis in the host cells, resulting in glucose limitation and ATP depletion in S. aureus. Additionally, inhibition of NLRP3 activation improves antibiotic efficacy in vitro and in vivo. Our findings identify interactions between S. aureus and the host that result in metabolic crosstalk that can determine the outcome of antimicrobial therapy.
Multi-curve fitting and tubulin-lattice signal removal for structure determination of large microtubule-based motors
Authors: Chai Pengxin , Rao Qinhui , Zhang Kai
Published: January 2022

Revealing high-resolution structures of microtubule-associated proteins (MAPs) is critical for understanding their fundamental roles in various cellular activities, such as cell motility and intracellular cargo transport. Nevertheless, large molecular motors that dynamically bind and release microtubule networks are challenging for cryo-electron microscopy (cryo-EM). Traditional structure determination of MAPs bound to microtubules needs alignment information from the reconstruction of microtubules, which cannot be readily applied to large MAPs without a fixed binding pattern. Here, we developed a comprehensive approach to estimate the microtubule networks (multicurve fitting), model the tubulin-lattice signals, and remove them (tubulin-lattice subtraction) from the raw cryo-EM micrographs. The approach does not require an ordered binding pattern of MAPs on microtubules, nor does it need a reconstruction of the microtubules. We demonstrated the capability of our approach using the reconstituted outer-arm dynein bound to microtubule doublets. In addition, we applied our multi-curve fitting approach to other biological filaments and achieved accurate estimations. Our work provides a new tool to determine high-resolution structures of large MAPs bound to curved microtubule networks.
Beyond vaccination: A Cross-Sectional Study of the importance of Behavioral and Native Factors on COVID-19 Infection and Severity
Authors: Aouissi Hani Amir , Ababsa Mostefa , Leveau Carlos M. , Petrisor Alexandru-Ionut , Słomka Artur , Kechebar Mohamed Seif Allah , Yasuhara Jun , Epelboin Loïc , Ohmagari Norio
Published: January 2022

The COVID-19 pandemic has a major impact on a global scale. Understanding the innate and lifestyle-related factors influencing the rate and severity of COVID-19 is important for making evidence-based recommendations. This cross-sectional study aimed at establishing a potential relationship between human characteristics and vulnerability/resistance to SARS-CoV-2. We hypothesize that the impact of virus is not the same due to cultural and ethnic differences. A cross-sectional study was performed using an online questionnaire. The methodology included a development of a multi-language survey, expert evaluation and data analysis. Data was collected using a 13-item pre-tested questionnaire based on a literature review. Data was statistically analyzed using the logistic regression. For a total of 1125 respondents, 332 (29.5%) were COVID-19 positive, among them 130 (11.5%) required home-based treatment, and 14 (1.2%) intensive care. The significant factors included age, physical activity and health status all found to have a significant influence on the infection (p < 0.05). The severity of infection was associated with preventive measures and tobacco (p < 0.05). This suggests the importance of behavioral factors compared to innate ones. Apparently, the individual behavior is mainly responsible for the spread of the virus. Adopting a healthy lifestyle and scrupulously observing preventive measures including vaccination would greatly limit the probability of infection and prevent the development of severe COVID-19.
Predicting missing links in global host–parasite networks
Authors: Farrell Maxwell J. , Elmasri Mohamad , Stephens David A. , Davies T. Jonathan
Published: January 2022

1. Parasites that infect multiple species cause major health burdens globally, but for many, the full suite of susceptible hosts is unknown. Predicting undocumented host–parasite associations will help expand knowledge of parasite host specificities, promote the development of theory in disease ecology and evolution, and support surveillance of multi‐host infectious diseases. The analysis of global species interaction networks allows for leveraging of information across taxa, but link prediction at this scale is often limited by extreme network sparsity and lack of comparable trait data across species.

2. Here we use recently developed methods to predict missing links in global mammal‐parasite networks using readily available data: network properties and evolutionary relationships among hosts. We demonstrate how these link predictions can efficiently guide the collection of species interaction data and increase the completeness of global species interaction networks.

3. We amalgamate a global mammal host–parasite interaction network (>29,000 interactions) and apply a hierarchical Bayesian approach for link prediction that leverages information on network structure and scaled phylogenetic distances among hosts. We use these predictions to guide targeted literature searches of the most likely yet undocumented interactions, and identify empirical evidence supporting many of the top ‘missing’ links.

4. We find that link prediction in global host–parasite networks can successfully predict parasites of humans, domesticated animals and endangered wildlife, representing a combination of published interactions missing from existing global databases, and potential but currently undocumented associations.

5. Our study provides further insight into the use of phylogenies for predicting host–parasite interactions, and highlights the utility of iterated prediction and targeted search to efficiently guide the collection of information on host–parasite interactions. These data are critical for understanding the evolution of host specificity, and may be used to support disease surveillance through a process of predicting missing links, and targeting research towards the most likely undocumented interactions.
‘We are happy to tell you the sisimol stories (small stories)’: Reframing what counts as conservation work in the Arnavon Islands, Solomon Islands
Authors: Fidali Kristina L. , Larder Nicolette
Published: January 2022

Funders and governments alike increasingly understand the importance of women's inclusion in environmental conservation and natural resource management across the Pacific region. Despite this recognition, the weight of evidence suggests that entrenched gender inequalities continue to create barriers for women's engagement in conservation management and related projects like those for climate change adaptation. Against the dominant narrative that women are always marginal in environmental management in the Pacific, we draw on the small stories provided by women in communities around the Arnavon Islands in the Solomon Islands to show that in fact women are deeply engaged in conservation efforts and environmental care. Building on the concept of emplaced sustainability, we reframe what counts as the work of environmental conservation to include the mundane, small and everyday activities undertaken by women. Rather than marginal, the collective mundane and everyday work of women takes place alongside the ‘important’ or ‘big’ work of conservation in the region and we argue that both kinds of labouring matter for sustaining ecological livelihoods.