bluuebunny/crossref_metadata_2025 huggingface dataset:
A Buprenorphine depot formulation provides effective sustained post-surgical analgesia for 72h in mouse femoral fracture models
Authors: Wolter Angelique , Bucher Christian H. , Kurmies Sebastian , Schreiner Viktoria , Konietschke Frank , Hohlbaum Katharina , Klopfleisch Robert , Löhning Max , Thöne-Reineke Christa , Buttgereit Frank , Huwyler Jörg , Jirkof Paulin , Rapp Anna E. , Lang Annemarie
Published: July 2022

Adequate pain management is essential for ethical and scientific reasons in animal experiments and should completely cover the period of expected pain without the need for frequent re-application. However, current depot formulations of Buprenorphine are only available in the USA and have limited duration of action. Recently, a new microparticulate Buprenorphine formulation (BUP-Depot) for sustained release has been developed as an alternative product within Europe. Pharmacokinetics indicate a potential effectiveness for about 72h. Here, we investigated whether the administration of the BUP-Depot ensures continuous and sufficient analgesia in two mouse femoral fracture models and could therefore serve as a potent alternative to the application of Tramadol via drinking water. Both protocols were examined for analgesic effectiveness, side effects on experimental readout, and effects on fracture healing outcomes in male and female C57BL/6N mice. The BUP-Depot provided effective analgesia for 72h, comparable to the effectiveness of Tramadol in drinking water. Fracture healing outcome was not different between analgesic regimes. The availability of a Buprenorphine depot formulation for laboratory animals in Europe would be a beneficial addition for extended pain relief in mice, thereby increasing animal welfare.
Outline and divergence time of subkingdom Mucoromyceta: two new phyla, five new orders, six new families and seventy-three new species
Authors: Zhao Heng , Dai Yu-Cheng , Liu Xiao-Yong
Published: July 2022

Zygomycetes are phylogenetically early diverged, ecologically diverse, industrially valuable, agriculturally beneficial, and clinically pathogenic fungi. Although new phyla and subphyla have been constantly established to accommodate specific members and a subkingdom, Mucoromyceta, was erected to unite core zygomycetous fungi, their phylogenetic relationships have not been well resolved. Taking account of the information of monophyly and divergence time estimated from ITS and LSU rDNA sequences, the present study updates the classification framework of the subkingdom Mucoromyceta from the phylum down to the generic rank: six phyla (including two new phyla Endogonomycota and Umbelopsidomycota), eight classes, 15 orders (including five new orders Claroideoglomerales, Cunninghamellales, Lentamycetales, Phycomycetales and Syncephalastrales), 41 families (including six new families Circinellaceae, Gongronellaceae, Protomycocladaceae, Rhizomucoraceae, Syzygitaceae and Thermomucoraceae), and 121 genera. The taxonomic hierarchy was calibrated with estimated divergence times: phyla 810–639 Mya, classes 651–585 Mya, orders 570–400 Mya, and families 488–107 Mya. Along with this outline, 71 genera are annotated and 73 new species are described. In addition, three new combinations are proposed. In this paper, we update the taxonomic backbone of the subkingdom Mucoromyceta and reinforce its phylogeny. We also contribute numerous new taxa and enrich the diversity of Mucoromyceta.
Clinical utility of fluid biomarkers in the evaluation of cognitive impairment: a systematic review and meta-analysis
Authors: Hazan Jemma , Wing Michelle , Liu Kathy , Reeves Suzanne , Howard Robert
Published: July 2022

Background

The analytical and clinical validity of fluid biomarkers, measured typically in cerebrospinal (CSF) serum or plasma, has been extensively researched in dementia. Further work is needed to assess the ability of these biomarkers to improve diagnosis, management, and health outcomes in the clinical setting

Objectives

To assess the added value and clinical utility of fluid biomarkers in the diagnostic assessment of cognitively impaired patients under evaluation for Alzheimer’s disease (AD).

Methods

Systematic literature searches of Medline, EMBASE, PsycINFO, Web of Science research databases were conducted on 17th December 2022. Data from relevant studies were extracted and independently screened for quality using a tool for bias. Clinical utility was measured by clinicians’ changes in diagnosis, diagnostic confidence, and patient management (when available), after their examination of patients’ fluid biomarkers. Cost-effectiveness was assessed by consideration of additional cost per patient and quality-adjusted life years (QALY).

Results

Searches identified 18 studies comprising 2199 patient participants and 599 clinicians. The meta-analysis revealed that clinicians’ use of fluid biomarkers resulted in a pooled percentage change in diagnosis of 25% (95% CI: 14–37), an increase in diagnostic confidence of 14% (95% CI: 9–18) and a pooled proportion of patients whose management changed of 31% (95% CI 12–50). CSF biomarkers were deemed cost effective, particularly in memory services, where pre-test AD prevalence is higher compared to a primary care setting.

Conclusions

Fluid biomarkers can be a helpful additional diagnostic tool for clinicians assessing patients with cognitive impairment. In particular, CSF biomarkers consistently improved clinicians’ confidence in diagnosing AD and influenced on diagnostic change and patient management. Further research is needed to study the clinical utility of blood-based biomarkers in the clinical setting.
Cross-sectional evolution of pain management policies and practices in Portuguese pediatric emergency departments
Authors: Garrido André , Manuel Ana Rute , Araújo Ricardo , Mascarenhas Inês , Almeida Helena , Abadesso Clara
Published: July 2022

The prevalence of pediatric pain, either related to the child’s hospital visit or as a result of diagnostic and/or therapeutical interventions, is of primordial importance in pediatric emergency departments (PEDs).

In this study, we evaluate the evolution of pain assessment and management in Portuguese PEDs through eleven years. To this end, we prepared a questionnaire addressed to head physicians of 45 the Portuguese PEDs in 2007 and compared the responses to those provided in 2018, where we also posed these questions to nurse managers.

Pain assessment in Portuguese PEDs has significantly improved, namely with establishment of local protocols and widespread use of pain scales. However, effective adoption of pain management remains insufficient, as mild to moderate pain is still far from being universally treated. Nonetheless, there seems to be an adequate treatment of severe pain and respective common use of opioids, but correct practices were not generally adopted when specific types of pain were analyzed. Procedural sedation and use of non-pharmacological techniques has significantly increased, but are not yet universally practiced. These inadequacies are reflected by the staff’s perception that pain management remains suboptimal, and more training is needed, effectively urging for a nationwide plan and better knowledge translation of correct pediatric pain management.
Chemotherapy use and outcomes in patients with stage III or IV small-cell lung cancer in relation to age: An analysis of the English Systemic Anti-Cancer Treatment (SACT) dataset
Authors: Pilleron S. , Morris EJA. , Dodwell D. , Franks K.N.
Published: July 2022

Introduction

Survival from small cell lung cancer (SCLC) is poor and there has been little progress in treatment. There is little evidence on outcomes in patients aged 75+. We described patterns of chemotherapy use and outcomes using the national Systemic Anti-Cancer Treatment dataset in patients with stage III or IV SCLC in relation to age.

Method

We included 7,966 SCLC (67.6% stage IV) diagnosed between 2014-17 in England, treated with chemotherapy and followed up through 2017. Patterns of chemotherapy use, 30- and 90-mortality rates, 6-,12-month and median overall survival (OS) from the start of the first chemotherapy cycle were compared between those below and above the age of 75. OS was estimated using Kaplan Meier estimator and modeled using a flexible hazard regression model.

Results

Older patients were 6-7 times less likely to receive curative treatment than younger patients regardless of stage. There were more frequent adjustments of treatment and dose reduction (stage III) in older than younger patients but no age-related differences in reduction of doses (stage IV), treatment delayed or stopped earlier than planned. Although 30-day mortality rates were similar across age groups in stage III SCLC (∼4%), older patients had higher early mortality and poorer OS than younger peers. In both stages, 6 and 12-month OS by age decreased around the age of 70-75 and were worse in patients with performance status scores ≥2.

Conclusion

This study offers a snapshot of chemotherapy use and outcomes in advanced SCLC, notably in older patients, in the pre-immunotherapy era.
A systematic review of dengue outbreak prediction models: current scenario and future directions
Authors: Leung Xing Yu , Islam Rakibul M. , Adhami Mohammadmehdi , Ilic Dragan , McDonald Lara , Palawaththa Shanika , Diug Basia , Munshi Saif U. , Karim M.D. Nazmul
Published: July 2022

Dengue is among the fastest-spreading vector-borne infectious disease, with outbreaks often overwhelm the health system and result in huge morbidity and mortality in its endemic populations in the absence of an efficient warning system. A large number of prediction models are currently in use globally. As such, this study aimed to systematically review the published literature that used quantitative models to predict dengue outbreaks and provide insights about the current practices. A systematic search was undertaken, using the Ovid MEDLINE, EMBASE, Scopus and Web of Science databases for published citations, without time or geographical restrictions. Study selection, data extraction and management process were devised in accordance with the ‘Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies’ (‘CHARMS’) framework. A total of 78 models were included in the review from 51 studies. Most models sourced climate (89.7%) and climate change (82.4%) data from agency reports and only 59.0% of the models adjusted for reporting time lag. All included models used climate predictors; 65.4% of them were built with only climate factors. Climate factors were used in combination with climate change factors (10.3%), both climate change and demographic factors (10.3%), vector factors (5.1%), and demographic factors (5.1%). Machine learning techniques were used for 38.5% of the models. Of these, random forest (20.0%), neural networks (23.3%) and ensemble models (13.3%) were notable. Among the statistical (61.5%) models, linear regression (20.8%), Poisson regression (18.8%), generalized additive models (16.7%) and time series/autoregressive models (18.8%) were notable. Around 24.4% of the models reported no validation at all and only 6.4% reported external validation. The reporting of methodology and model performance measures were inadequate in many of the existing prediction models. This review collates plausible predictors and methodological approaches, which will contribute to robust modelling in diverse settings and populations.
Fromcereusto anthrax and back again: The role of the PlcR regulator in the “cross-over” strainBacillus cereusG9241
Authors: Manoharan Shathviga , Taylor-Joyce Grace , Brooker Thomas A. , Hernandez-Rodriguez Carmen Sara , Hapeshi Alexia , Baldwin Victoria , Baillie Les , Oyston Petra C. F. , Waterfield Nicholas R.
Published: July 2022

Bacillus cereusG9241 was isolated from a Louisiana welder suffering from an anthrax-like infection. The organism carries two transcriptional regulators that have previously been proposed to be incompatible with each other: the pleiotropic transcriptional regulator PlcR found in most members of theBacillus cereusgroup but truncated in allBacillus anthracisisolates, and the anthrax toxin regulator AtxA found in allB. anthracisstrains and a fewB. cereussensu stricto strains. Here we report cytotoxic and haemolytic activity of cell freeB. cereusG9241 culture supernatants cultured at 25 °C to various eukaryotic cells. However, this is not observed at the mammalian infection relevant temperature 37 °C, behaving much like the supernatants generated byB. anthracis. Using a combination of genetic and proteomic approaches to understand this unique phenotype, we identified several PlcR-regulated toxins to be secreted highly at 25 °C compared to 37 °C. Furthermore, we demonstrate that differential expression of the protease involved in processing the PlcR quorum sensing activator molecule PapR appears to be the limiting step for the production of PlcR-regulated toxins at 37 °C, giving rise to the temperature-dependent haemolytic and cytotoxic activity of the culture supernatants. This study provides an insight on howB. cereusG9241 is able to ‘switch’ betweenB. cereusandB. anthracis–like phenotypes in a temperature-dependent manner, potentially accommodating the activities of both PlcR and AtxA.
An integrated ‘omics approach highlights the role of epigenetic events to explain and predict response to neoadjuvant chemotherapy and bevacizumab
Authors: Fleischer Thomas , Haugen Mads Haugland , Ankill Jørgen , Silwal-Pandit Laxmi , Børresen-Dale Anne-Lise , Hedenfalk Ingrid , Hatschek Thomas , Tost Jörg , Engebraaten Olav , Kristensen Vessela N.
Published: July 2022

Here we present an integrated ‘omics approach for DNA methylation profiling using copy number alteration, gene expression and proteomic data to predict response to therapy and to pinpoint response-related epigenetic events. Fresh frozen tumor biopsies taken before, during and after treatment from patients receiving neoadjuvant chemotherapy with or without the anti-angiogenic drug bevacizumab were subjected to molecular profiling. Our previous studies have shown that administration of bevacizumab in addition to chemotherapy (combination treatment) may confer improved response for patients; here we report that DNA methylation at enhancer CpGs related to cell cycle regulation can predict response to chemotherapy and bevacizumab for ER positive patients with high fidelity (AUC=0.874), and we validate this observation in an independent patient cohort with similar treatment regimen (AUC=0.762). When combining the DNA methylation score with a previously reported proteomic score (ViRP), the prediction accuracy further improved in the validation cohort (AUC=0.784). We also show that tumors receiving the combination treatment underwent more extensive epigenetic alterations than tumors receiving only chemotherapy. Finally, we performed an integrative emQTL analysis on alterations in DNA methylation and gene expression levels, showing that the epigenetic alterations that occur during treatment are different between responders and non-responders and that these differences may be explained by the proliferation-EMT axis through the activity of the transcription factor GRHL2. Taken together, these results illustrate the clinical benefit of the addition of bevacizumab to chemotherapy if administered to the correct patients.
Diversity and task-dependence of task representations in V1 during freely-moving decisions
Authors: Zhang Anqi , Zador Anthony M.
Published: July 2022

Neurons in primary visual cortex (area V1) are strongly driven by both sensory stimuli and non-sensory events. However, although the representation of sensory stimuli has been well characterized, much less is known about the representation of non-sensory events. Here, we characterize the specificity and organization of non-sensory representations in rat V1 during a freely-moving visual decision task. We find that single neurons encode diverse combinations of task features simultaneously and across task epochs. Despite heterogeneity at the level of single neuron response patterns, both visual and non-visual task variables could be reliably decoded from small neural populations (5-40 units) throughout a trial. Interestingly, in animals trained to make an auditory decision following passive observation of a visual stimulus, some but not all task features could also be decoded from V1 activity. Our results support the view that even in V1— the earliest stage of the cortical hierarchy—bottom-up sensory information is combined with top-down non-sensory information in a task-dependent manner.
XDec Simplex Map of Breast Cancer Cell States Enables Precise Modeling and Targeting of Breast Cancer
Authors: Murillo Oscar D. , Petrosyan Varduhi , LaPlante Emily L. , Dobrolecki Lacey E. , Lewis Michael T. , Milosavljevic Aleksandar
Published: July 2022

The characterization of cancer cell states within the tumor microenvironment is a key to understanding tumor biology and an important step toward the development of precision therapies. To reconstruct this information from bulk RNA-seq profiles, we developed the XDec Simplex Mapping (XDec-SM) approach, a reference-optional deconvolution method that leverages single-cell information, when such information is available, to map tumors and the states of constituent cells onto a biologically interpretable, low-dimensional space. When applied to breast tumors in The Cancer Genome Atlas (TCGA), XDec-SM infers the identity of constituent cell types and their proportions. XDec-SM also infers cancer cells states within individual tumors that associate with DNA methylation patterns, driver somatic mutations, pathway activation and metabolic coupling between stromal and breast cancer cells. By projecting tumors, cancer cell lines, and PDX models onto the same map, we identify both in vitro and in vivo models with matching cancer cell states. Map position is also predictive of therapy response, thus opening the prospects for precision therapy informed by experiments in model systems matched to tumors in vivo by cancer cell state.
Neural Correlates of Statistical Learning in Developmental Dyslexia: An Electroencephalography Study
Authors: Daikoku Tatsuya , Jentschke Sebastian , Tsogli Vera , Bergström Kirstin , Lachmann Thomas , Ahissar Merav , Koelsch Stefan
Published: July 2022

The human brain extracts statistical regularities from the surrounding environment in a process referred to as statistical learning. Recent behavioural evidence suggests that developmental dyslexia affects statistical learning. However, surprisingly few neurophysiological studies have assessed how developmental dyslexia affects the neural processing underlying statistical learning. In this study, we used electroencephalography to explore the neural correlates of an important aspect of statistical learning – sensitivity to transitional probabilities – in individuals with developmental dyslexia. Adults diagnosed with developmental dyslexia (n = 17) and controls (n = 19) were exposed to a continuous stream of sound triplets in which a few triplet endings were location deviants (i.e., were presented from an unexpected speaker direction) or statistical deviants (i.e., had a low transitional probability given the triplet’s first two sounds). Location deviants elicited a large location mismatch negativity (MMN), which was larger in controls than dyslexics. Statistical deviants elicited a small, yet significant statistical MMN (sMMN) in controls, whereas the dyslexic individuals did not exhibit a statistical MMN. These results suggest that the neural mechanisms underlying statistical learning are impaired in developmental dyslexia.

Significance statement

We assessed the neural correlates of statistical learning in individuals with developmental dyslexia. Statistical deviants, namely word endings with a low transitional probability (as compared to high probability transitions) elicited a small, yet significant statistical MMN in controls, whereas the dyslexic individuals did not exhibit a statistical MMN. Location deviants elicited a MMN, which was larger in controls than dyslexics. These results suggest that the neural mechanisms underlying statistical learning are impaired in developmental dyslexia.
Introducing Mouffet, a unified framework to make model creation easier and more reproducible
Authors: Christin Sylvain , Lecomte Nicolas
Published: July 2022

Biological and ecological models are being increasingly used to explain the natural world. Model creation is an iterative process requiring two steps: training and evaluating the models. However, this process can become complex when multiple models are trained and evaluated at the same time. Besides, development steps can be lost, reducing the reproducibility of model creation.

We introduce Mouffet, an open-source Python framework that aims to make model creation easier, more robust, and more reproducible. It provides a set of configuration files and high-level Python interfaces that help managing data, training, and evaluating models. To improve reproducibility, every step of the model creation process, including the options used, are saved.

Mouffet introduces the notion of scenarios that allow users to define multiple training or evaluation tasks in a single configuration file. This not only facilitates model creation but enables users to define experimental plans to study the effect of selected parameters on training or evaluation.

While initially developed for deep learning models, Mouffet is independent of the implementation of the models. Therefore, it could be successfully used to compare different modelling approaches. Besides, its ease of use makes it a choice tool for ecologists, even when not familiar with complex model creation.
Coherent pathway enrichment estimation by modeling inter-pathway dependencies using regularized regression
Authors: Jablonski Kim Philipp , Beerenwinkel Niko
Published: July 2022

Gene set enrichment methods are a common tool to improve the interpretability of gene lists as obtained, for example, from differential gene expression analyses. They are based on computing whether dysregulated genes are located in certain biological pathways more often than expected by chance. Gene set enrichment tools rely on pre-existing pathway databases such as KEGG, Reactome, or the Gene Ontology. These databases are increasing in size and in the number of redundancies between pathways, which complicates the statistical enrichment computation. Here, we address this problem and develop a novel gene set enrichment method, calledpareg, which is based on a regularized generalized linear model and directly incorporates dependencies between gene sets related to certain biological functions, for example, due to shared genes, in the enrichment computation. We show thatparegis more robust to noise than competing methods. Additionally, we demonstrate the ability of our method to recover known pathways as well as to suggest novel treatment targets in an exploratory analysis using breast cancer samples from TCGA.paregis freely available as an R package on Bioconductor (https://bioconductor.org/packages/release/bioc/html/pareg.html) as well as onhttps://github.com/cbg-ethz/pareg. The GitHub repository also contains the Snakemake workflows needed to reproduce all results presented here.
Multi-modal profiling of peripheral blood cells across the human lifespan reveals distinct immune cell signatures of aging and longevity
Authors: Karagiannis Tanya T. , Dowrey Todd W. , Villacorta-Martin Carlos , Montano Monty , Reed Eric , Andersen Stacy L. , Perls Thomas T. , Monti Stefano , Murphy George J. , Sebastiani Paola
Published: July 2022

Age-related changes in immune cell composition and functionality are associated with multimorbidity and mortality. However, many centenarians delay the onset of aging-related disease suggesting the presence of elite immunity that remains highly functional at extreme old age. To identify immune-specific patterns of aging and extreme human longevity, we analyzed novel single cell profiles from the peripheral blood mononuclear cells (PBMCs) of 7 centenarians (mean age 106) and publicly available single cell RNA-sequencing (scRNA-seq) datasets that included an additional 7 centenarians as well as 52 people at younger ages (20-89 years). The analysis confirmed known shifts in the ratio of lymphocytes to myeloid cells, and noncytotoxic to cytotoxic cell distributions with aging, but also identified significant shifts from CD4+T cell to B cell populations in centenarians suggesting a history of exposure to natural and environmental immunogens. Our transcriptional analysis identified cell type signaturesspecificto exceptional longevity that included genes with age-related changes (e.g., increased expression ofSTK17A, a gene known to be involved in DNA damage response)as well as genes expressed uniquely in centenarians’ PBMCs (e.g.,S100A4, part of the S100 protein family studied in age-related disease and connected to longevity and metabolic regulation). Collectively, these data suggest that centenarians harbor unique, highly functional immune systems that have successfully adapted to a history of insults allowing for the achievement of exceptional longevity.
MC profiling: a novel approach to analyze DNA methylation heterogeneity from bulk bisulfite sequencing data
Authors: De Riso Giulia , Sarnataro Antonella , Scala Giovanni , Cuomo Mariella , Della Monica Rosa , Amente Stefano , Chiariotti Lorenzo , Miele Gennaro , Cocozza Sergio
Published: July 2022

DNA methylation is an epigenetic mark implicated in crucial biological processes. Most of the knowledge about DNA methylation is based on bulk experiments, in which DNA methylation of genomic regions is reported as average methylation. However, average methylation does not inform on how methylated cytosines are distributed in each single DNA molecule.

Here, we propose Methylation Class (MC) profiling as a genome-wide approach to the study of DNA methylation heterogeneity from bulk bisulfite sequencing experiments. The proposed approach is built on the concept of MCs, groups of DNA molecules sharing the same number of methylated cytosines. The relative abundances of MCs from sequencing reads incorporates the information on the average methylation, and directly informs on the methylation level of each molecule.

By applying our approach to publicly available bisulfite-sequencing datasets, we individuated cell-to-cell differences as the prevalent contributor to methylation heterogeneity. Moreover, we individuated signatures of loci undergoing imprinting and X-inactivation, and highlighted differences between the two processes. When applying MC profiling to compare different conditions, we identified methylation changes occurring in regions with almost constant average methylation.

Altogether, our results indicate that MC profiling can provide useful insights on the epigenetic status and its evolution at multiple genomic regions.
Evaluation of epigenetic age acceleration scores and their associations with CVD related phenotypes in a population cohort
Authors: Chervova Olga , Chernysheva Elizabeth , Panteleeva Kseniia , Widayati Tyas Arum , Hrbkova Natalie , Schneider Jadesada , Maximov Vladimir , Ryabikov Andrew , Tillmann Taavi , Pikhart Hynek , Bobak Martin , Voloshin Vitaly , Malyutina Sofia , Beck Stephan
Published: July 2022

We evaluated associations between nine epigenetic age acceleration (EAA) scores and 18 cardio-metabolic phenotypes using an Eastern European ageing population cohort richly annotated for a diverse set of phenotypes (subsample, n = 306; aged 45-69 years). This was implemented by splitting the data into groups with positive and negative EAAs. We observed strong association between all epigenetic age acceleration scores and sex, suggesting that any analysis of EAAs should be adjusted by sex. We found that some sex-adjusted EAA scores were significantly associated with several phenotypes such as blood levels of gamma-glutamyl transferase and low-density lipoprotein, smoking status, annual alcohol consumption, multiple carotid plaques, and incident coronary heart disease status (not necessarily the same phenotypes for different EAAs). We demonstrated that even after adjusting EAAs for sex, EAA-phenotype associations remain sex-specific, which should be taken into account in any downstream analysis involving EAAs. The obtained results suggest that in some EAA-phenotype associations, negative EAA scores (i.e. epigenetic age below chronological age) indicated more harmful phenotype values, which is counter-intuitive. Among all considered epigenetic clocks, GrimAge was significantly associated with more phenotypes than any other EA scores in this Russian sample.
A deep learning and graph-based approach to characterise the immunological landscape and spatial architecture of colon cancer tissue
Authors: Parreno-Centeno Mario , Malagoli Tagliazucchi Guidantonio , Withnell Eloise , Pan Shi , Secrier Maria
Published: July 2022

Tumour immunity is key for the prognosis and treatment of colon adenocarcinoma, but its characterisation remains cumbersome and expensive, requiring sequencing or other complex assays. Detecting tumour-infiltrating lymphocytes in haematoxylin and eosin (H&E) slides of cancer tissue would provide a cost-effective alternative to support clinicians in treatment decisions, but inter- and intra-observer variability can arise even amongst experienced pathologists. Furthermore, the compounded effect of other cells in the tumour microenvironment is challenging to quantify but could yield useful additional biomarkers. We combined RNA sequencing, digital pathology and deep learning through the InceptionV3 architecture to develop a fully automated computer vision model that detects prognostic tumour immunity levels in H&E slides of colon adenocarcinoma with an area under the curve (AUC) of 82%. Amongst tumour infiltrating T cell subsets, we demonstrate that CD8+ effector memory T cell patterns are most recognisable algorithmically with an average AUC of 83%. We subsequently applied nuclear segmentation and classification via HoVer-Net to derive complex cell-cell interaction graphs, which we queried efficiently through a bespoke Neo4J graph database. This uncovered stromal barriers and lymphocyte triplets that could act as structural hallmarks of low immunity tumours with poor prognosis. Our integrated deep learning and graph-based workflow provides evidence for the feasibility of automated detection of complex immune cytotoxicity patterns within H&E-stained colon cancer slides, which could inform new cellular biomarkers and support treatment management of this disease in the future.
Electrical stimulation of temporal and limbic circuitry produces distinct responses in human ventral temporal cortex
Authors: Huang Harvey , Gregg Nicholas M. , Valencia Gabriela Ojeda , Brinkmann Benjamin H. , Lundstrom Brian N. , Worrell Gregory A. , Miller Kai J. , Hermes Dora
Published: July 2022

The human ventral temporal cortex (VTC) is highly connected to integrate visual perceptual inputs with feedback from cognitive and emotional networks. In this study, we used electrical brain stimulation to understand how different inputs from multiple brain regions drive unique electrophysiological responses in the VTC.

We recorded intracranial EEG data in 6 patients implanted with intracranial electrodes for epilepsy surgery evaluation. Pairs of electrodes were stimulated with single pulse electrical stimulation, and corticocortical evoked potential (CCEP) responses were measured at electrodes in the collateral sulcus and lateral occipitotemporal sulcus of the VTC. Using a novel unsupervised machine learning method, we uncovered 2 to 4 distinct response shapes, termed basis profile curves (BPCs), at each recording electrode in the 11 to 500 ms post-stimulation interval.

CCEPs of unique shape and high amplitude were elicited following stimulation of several regions and classified into a set of four consensus BPCs across subjects. One of the consensus BPCs was primarily elicited by stimulation of the hippocampus; another by stimulation of the amygdala; a third by stimulation of lateral cortical sites, such as the middle temporal gyrus; and the final one by stimulation of multiple distributed sites. Stimulation also produced sustained high frequency power decreases and low frequency power increases that spanned multiple BPC categories.

Characterizing distinct shapes in stimulation responses provides a novel description of connectivity to the VTC and reveals significant differences in input from cortical and limbic structures.

SIGNIFICANCE STATEMENT

Disentangling the numerous input influences on highly connected areas in the brain is a critical step toward understanding how different brain networks work together to produce function. Single pulse electrical stimulation is an effective tool to accomplish this goal because the shapes and amplitudes of signals recorded from electrodes are informative of the synaptic physiology of the stimulation-driven inputs. We focused on targets in the ventral temporal cortex because it is an area strongly implicated in visual object perception. By using a data-driven clustering algorithm, we identified anatomical regions with distinct input connectivity profiles to the ventral temporal cortex. Examining high frequency power changes revealed possible modulation of excitability at the recording site induced by electrical stimulation of connected regions.
In vivoAntidiarrheal activities of the hydro alcoholic extracts ofSchinus molleL. (Anarcardiaceae) leaf in mice
Authors: Mengistu Getnet , Hailay Kidan , Misganaw Desye , Andualem Abel , Belayneh Yaschilal Muche
Published: July 2022

Background

diarrhea is the second leading cause of death among children under five globally next to pneumonia and it kills around 760, 000 children every year in the world. The available synthetic drugs to treat diarrhea have limited safety and efficacy. Thus, people are still dependent on the herbal remedies for managing diarrhea.

Objective

To evaluate in vivo antidiarrheal activities of the hydro-alcoholic leaf extracts ofSchinus molleL. (Anacardiaceae) in mice.

Methods

The 80% methanol leaf extract was prepared by successive maceration technique. The antidiarrheal activity of the extract was evaluated using castor oil induced diarrhea, enteropooling and small intestine transit models. The test groups received various doses (100, 200 and 400 mg/kg) of the extract, whereas positive controls received Loperamide (3 mg/kg) and negative controls received vehicle (distilled water, 10 ml/kg). Data were analysed using one-way ANOVA followed by Tukey’s posthoc test.

Result

In the castor oil induced diarrheal model, the 80% methanol extract delayed onset of defecation and reduced the number and weight of feces at all tested doses significantly as compared to the negative control. In the enteropooling test, the 80ME significantly (P<0.001) reduced the weight and volume of intestinal fluid at all tested doses when compared to negative control. Results from the charcoal meal test revealed that the extracts produced a significant anti-motility effect at all tested doses as compared to negative control.

Conclusion

This study confirmed the antidiarrheal activity of the hydro-alcoholic extract and the highest test dose produced the maximum antidiarrheal activity in all models
FAVA: High-quality functional association networks inferred from scRNA-seq and proteomics data
Authors: Koutrouli Mikaela , Líndez Pau Piera , Nastou Katerina , Bouwmeester Robbin , Rasmussen Simon , Martens Lennart , Jensen Lars Juhl
Published: July 2022

Protein networks are commonly used for understanding how proteins interact. However, they are typically biased by data availability, favoring well-studied proteins with more interactions. To uncover functions of understudied proteins, we must use data that are not affected by this literature bias, such as single-cell RNA-seq and proteomics. Due to data sparseness and redundancy, co-expression analysis becomes complex. To address this, we have developed FAVA (Functional Associations using Variational Autoencoders), which compresses high-dimensional data into a low-dimensional space. FAVA infers networks from high-dimensional omics data with much higher accuracy than existing methods, across a diverse collection of real as well as simulated datasets. FAVA can process large datasets with over 0.5 million conditions and has predicted 4,210 interactions between 1,039 understudied proteins. Our findings showcase FAVA’s capability to offer novel perspectives on protein interactions. FAVA functions within the scverse ecosystem, employing AnnData as its input source.
Metabolic differences and differentially expressed genes between C57BL/6J and C57BL/6N mice substrains
Authors: Nemoto Shino , Kubota Tetsuya
Published: July 2022

C57BL/6J (B6J) and C57BL/6N (B6N) mice are the most frequently used substrains in C57BL/6 (B6) inbred mice, serving as physiological models for in vivo studies and as background strains to build transgenic mice. However, little attention has been paid to the phenotypic differences between B6J and B6N mice, and they have often been attributed to mutations in the nicotinamide nucleotide transhydrogenase (Nnt) gene, which was found only in B6J. Nevertheless, phenotypic differences between the two that cannot be explained by Nnt mutations alone, especially in metabolic traits, indicate the presence of genetic variants associated with metabolism other than Nnt. We aimed to identify these genetic differences between B6J and B6N mice. Our results provide insights into differentially expressed genes (DEGs) in adipose tissues, skeletal muscle, liver, hypothalamus, and hippocampus, and phenotypic differences in metabolic traits between B6J and B6N. B6J mice had significantly lower body weight than B6N mice, regardless of a normal or high-fat diet. Blood insulin levels in B6J mice were significantly lower than those in B6N mice and glucose levels during dietary obesity were higher in B6J mice. Metabolic assessments revealed greater physical activity, less food intake, and higher energy expenditure in B6J mice than in B6N mice. Among the DEGs that were highly expressed in B6J mice compared to B6N mice, three genes—insulin degrading enzyme, adenylosuccinate synthase 2, and ectonucleotide triphosphate diphosphohydrolase 4—and the DEGs that had lower expression in B6J mice compared to B6N mice—Nnt, WD repeat and FYVE domain containing 1, and dynein light chain Tctex-type 1—were overlapped in all seven tissues. Our study provides insights into DEGs between B6J and B6N, which will be useful for substrain selection for mouse experiments, avoiding erroneous experimental results, and reviewing the results of studies that have used B6J, B6N, or mixed substrains.
How to entrain a selected neuronal rhythm but not others: open-loop dithered brain stimulation for selective entrainment
Authors: Duchet Benoit , Sermon James J. , Weerasinghe Gihan , Denison Timothy , Bogacz Rafal
Published: July 2022

While brain stimulation therapies such as deep brain stimulation for Parkinson’s disease can be effective, they have yet to reach their full potential across neurological disorders. Entraining neuronal rhythms using rhythmic brain stimulation has been suggested as a new therapeutic mechanism to restore neurotypical behavior in conditions such as chronic pain, depression, and Alzheimer’s disease. However, theoretical and experimental evidence indicate that brain stimulation can also entrain neuronal rhythms at sub- and super-harmonics, far from the stimulation frequency. Crucially, these counterintuitive effects can be harmful to patients, for example by triggering debilitating involuntary movements in Parkinson’s disease. We therefore propose a principled approach to selectively promote rhythms close to the stimulation frequency, while avoiding potential harmful effects by preventing entrainment at sub- and super-harmonics. Our open-loop approach to selective entrainment, dithered stimulation, consists in adding white noise to the stimulation period. We theoretically establish the ability of dithered stimulation to selectively entrain a given brain rhythm, and verify its efficacy in simulations of uncoupled neural oscillators, and networks of coupled neural oscillators. Furthermore, we show that dithered stimulation can be implemented in neurostimulators with limited capabilities by toggling within a finite set of stimulation frequencies. Likely implementable across a variety of existing brain stimulation devices, dithering-based selective entrainment has potential to enable new brain stimulation therapies, as well as new neuroscientific research exploiting its ability to modulate higher-order entrainment.
A minimum effective dose for (transcranial) alternating current stimulation
Authors: Alekseichuk Ivan , Wischnewski Miles , Opitz Alexander
Published: July 2022

Transcranial alternating current stimulation (tACS) is a popular method for non-invasive neuromodulation in human research and therapy. However, what constitutes an effective dose in tACS applications is still a matter of investigation and debate. Here, we examined available literature data regarding the effects of alternating current (AC)-induced electric fields on cellular-level neural activity. The literature search identified 16 relevant experimental reports that utilized brain slices, anesthetized rodents, and awake/behaving animal models. We implemented a probabilistic meta-analysis to estimate the minimum effective dose (MED) required for inducing detectable significant neural changes with AC stimulation. The results showed that AC stimulation at 0.3 mV/mm in awake/behaving mammals leads to an 80% probability of inducing minimum neural effects. A similar level of effectiveness in brain slices and anesthetized mammals required 0.7 mV/mm. In conclusion, (transcranial) alternating current stimulation is significantly more effective in awake than in anesthetized brains. The proposed dose targets can serve as a practical guideline for tACS in humans.
Jointly Modeling Species Niche and Phylogenetic Model in a Bayesian Hierarchical Framework
Authors: McHugh Sean W , Espíndola Anahí , White Emma , Uyeda Josef
Published: July 2022

When studying how species will respond to climatic change, a common goal is to predict how species distributions change through time. Environmental niche models (ENMs) are commonly used to estimate a species’ environmental niche from observed patterns of occurrence and environmental predictors. However, species distributions are often shaped by non-environmental factors–including biotic interactions and dispersal barriers—truncating niche estimates. Though a truncated niche estimate may accurately predict present-day species distribution within the sampled area, this accuracy decreases when predicting occurrence at different places and under different environmental conditions. Modeling niche in a phylogenetic framework leverages a clade’s shared evolutionary history to pull species estimates closer towards phylogenetic conserved values and farther away from species specific biases. We propose a new Bayesian model of phylogenetic niche estimation implemented in R calledBePhyNE(Bayesian environmental Phylogenetic Niche Estimation). Under our model, species ENM parameters are transformed into biologically interpretable continuous parameters of environmental niche optimum, breadth, and tolerance evolving as a multivariate Brownian motion. Through simulation analyses, we demonstrate model accuracy and precision that improve as phylogeny size increases. We also demonstrate our model on eastern United States Plethodontid salamanders and recover accurate estimates of species niche, even when species occurrence data is lacking and entirely informed by the evolutionary model. Our model demonstrates a novel framework where niche changes can be studied forwards and backwards through time to understand ancestral ranges, patterns of environmental specialization, and estimate niches of data-deficient species.
The DynaSig-ML Python package: automated learning of biomolecular dynamics-function relationships
Authors: Mailhot Olivier , Major François , Najmanovich Rafael
Published: July 2022

The DynaSig-ML (“Dynamical Signatures - Machine Learning”) Python package allows the efficient, user-friendly exploration of 3D dynamics-function relationships in biomolecules, using datasets of experimental measures from large numbers of sequence variants. The DynaSig-ML package is built around the Elastic Network Contact Model (ENCoM), the first and only sequence-sensitive coarse-grained NMA model, which is used to generate the input Dynamical Signatures. Starting fromin silicomutated structures, the whole pipeline can be run with just a few lines of Python and modest computational resources. The compute-intensive steps can also easily be parallelized in the case of either large biomolecules or vast amounts of sequence variants. As an example application, we use the DynaSig-ML package to predict the evolutionary fitness of the bacterial enzyme VIM-2 lactamase from deep mutational scan data.

Availability and implementation

DynaSig-ML is open source software available athttps://github.com/gregorpatof/dynasigml_package

Contact

rafael.najmanovich@umontreal.ca
Epidermal threads reveal the origin of hagfish slime
Authors: Zeng Yu , Plachetzki David , Nieders Kristen , Campbell Hannah , Cartee Marissa , Guillen Kennedy , Fudge Douglas
Published: July 2022

Fiber-reinforced soft materials possess high flexibility with high strength but are rare in nature. Hagfishes can produce a tough, fibrous slime within a fraction of a second by ejecting two cellular products, mucus and threads, into seawater. With thousands of silk-like threads, the slime is highly effective in defending against large predators. However, the evolutionary origin of hagfish slime remains unresolved, with the presence of another, putatively homologous thread in the epidermis providing circumstantial evidence for an epidermal origin. Here, we investigated the epidermal threads produced in hagfish skin. We found that these threads average ∼2 mm in length and ∼0.5 μm in diameter, or ∼80 times shorter and ∼4 times thinner than the slime threads, characterizing the second longest intracellular fiber. The entire hagfish body is covered by a dense layer of epidermal thread cells, with each square millimeter of skin storing a total of ∼96 cm threads. Experimentally induced damage to a hagfish’s skin caused the release of threads, which together with mucus, formed an adhesive epidermal slime that is more fibrous and less dilute than the defensive slime. Transcriptome analyses further revealed that the epidermal threads are ancestral to the slime threads, with duplication and diversification of thread genes in parallel with the evolution of slime glands. These results support an epidermal origin of hagfish slime and slime glands, as driven by predator selection for stronger and more voluminous slime.