bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling the biomechanics of cells on microcarriers in a stirred-tank bioreactor
Authors: Camphuijsen Jaro , Rivera Fernando J. Cantarero , Potter Greg , Clark Chris , Chen Jiajia , Kahan Simon , Aguilar Boris
Published: September 2022

Highly productive and efficient growth of biomass in bioreactors is an essential bioprocess outcome in many industrial applications. In the nascent cultivated meat industry, large-scale biomass creation will be critical given the size of demand in the conventional meat and seafood sectors. However, there are many challenges that must be overcome before cultivated meat and seafood become commercially viable including cost reductions of cell culture media, bioprocess design innovation and optimization, and scaling up in the longer term. Computational modelling and simulation can help to address many of these challenges, and can be a far cheaper and faster alternative to performing physical experiments. Computer modelling can also help researchers pinpoint system interactions that matter, and guide researchers to identify those parameters that should be changed in later designs for eventual optimization. In this work, a computational model that combines agent-based modeling and computational fluid dynamics was developed to study biomass growth as a function of the operative conditions of stirred-tank bioreactors. The focus was to analyze how the mechanical stress induced by rotor speed can influence the growth of cells attached to spherical microcarriers. The computer simulation results reproduced observations from physical experiments that high rotor speeds reduce cell growth rates and induce cell death under the high mechanical stresses induced at these stir speeds. Moreover, the results suggest that modeling both cell death and cell quiescence are required to recapitulate these observations from physical experiments. These simulation outcomes are the first step towards more comprehensive models that, in combination with experimental observations, will improve our knowledge of biomass production in bioreactors for cultivated meat and other industries.
Community-driven shark monitoring for informed decision making: A case study from Fiji
Authors: Ward-Paige CA , Sykes H , Osgood GJ , Brunnschweiler J
Published: September 2022

Context

Globally, more than 121 million people enjoy nature-based marine tourism, making it one of the largest marine industries. Ocean degradation threatens this industry and management has not kept pace to ensure long-term sustainability. In response, some individuals within the industry are taking it upon themselves to monitor the ocean and provide the data needed to assist management decisions. Fiji is one such place.

Aims

Between 2012 and 2016, 39 Fijian dive operators, in collaboration with eOceans, conducted the Great Fiji Shark Count (GFSC) to document sharks on their dives.

Methods

Using 146,304 shark observations from 30,668 dives, we document spatial and temporal patterns of eleven shark species at 592 sites.

Key results

Sharks were observed on 13,846 dives (45% of recorded dives) at 441 (74%) sites. Generally, our results matched those from other, more limited surveys, including from BRUVs. We found high variability in shark presence, species richness, and relative abundance through space and time. One trend was surprising: the most common species, Whitetip Reef Shark, decreased over the study period at eastern sites and increased at western sites — the cause is currently unknown.

Conclusions

Our results can guide management and conservation needs, future scientific questions, and provide a baseline for future assessments.

Implications

This study demonstrates the value of longitudinal observation data that includes absences for describing marine fauna, and confirms the capacity of stakeholders to document the ocean. It also points the direction for broadscale participatory science methodologies to track the ocean.
A genome-scale atlas reveals complex interplay of transcription and translation in an archaeon
Authors: Lorenzetti Alan P. R. , Kusebauch Ulrike , Zaramela Lívia S. , Wu Wei-Ju , de Almeida João P. P. , Turkarslan Serdar , de Lomana Adrián L. G. , Gomes-Filho José V. , Vêncio Ricardo Z. N. , Moritz Robert L. , Koide Tie , Baliga Nitin S.
Published: September 2022

The scale of post-transcriptional regulation and the implications of its interplay with other forms of regulation on environmental acclimation is underexplored for organisms of the domain Archaea. Here, we have investigated the scale of post-transcriptional regulation in the extremely halophilic archaeon Halobacterium salinarum NRC-1 by integrating transcriptome-wide locations of transcript processing sites (TPS) and SmAP1 binding, genome-wide locations of antisense RNAs (asRNAs), and consequences of RNase_2099C knockout on differential expression of all genes. This integrated analysis has discovered that 54% of all protein-coding genes in the genome of this haloarchaeon are likely targeted by multiple mechanisms for putative post-transcriptional processing and regulation, with about 20% of genes likely regulated by combinatorial schemes involving SmAP1, asRNAs, and RNase_2099C. Comparative analysis of mRNA levels (RNA-Seq) and protein levels (SWATH-MS) for 2,579 genes over four phases of batch culture growth in complex medium has generated additional evidence for conditional post-transcriptional regulation of 7% of all protein-coding genes. We demonstrate that post-transcriptional regulation may act to fine-tune specialized and rapid acclimation to stressful environments, e.g., as a switch to turn on gas vesicle biogenesis to promote vertical relocation in anoxic conditions and to modulate frequency of transposition by IS elements of the IS200/IS605, IS4, and ISH3 families. Findings from this study are provided as an atlas in a public web resource (https://halodata.systemsbiology.net).

IMPORTANCE

While the transcriptional regulation landscape of archaea has been extensively investigated, we currently have limited knowledge about post-transcriptional regulation and its driving mechanisms in this domain of life. In this study, we collected and integrated omics data from multiple sources and technologies to infer post-transcriptionally regulated genes and the putative mechanisms modulating their expression at the protein level in Halobacterium salinarum NRC-1. The results suggest that post-transcriptional regulation may drive environmental acclimation by regulating hallmark biological processes. To foster discoveries by other research groups interested in the topic, we extended our integrated data to the public in the form of an interactive atlas (https://halodata.systemsbiology.net).
Statistical inference of the rates of cell proliferation and phenotypic switching in cancer
Authors: Gunnarsson Einar Bjarki , Foo Jasmine , Leder Kevin
Published: September 2022

Recent evidence suggests that nongenetic (epigenetic) mechanisms play an important role at all stages of cancer evolution. In many cancers, these mechanisms have been observed to induce dynamic switching between two or more cell states, which commonly show differential responses to drug treatments. To understand how these cancers evolve over time, and how they respond to treatment, we need to understand the state-dependent rates of cell proliferation and phenotypic switching. In this work, we propose a rigorous statistical framework for estimating these parameters, using data from commonly performed cell line experiments, where phenotypes are sorted and expanded in culture. The framework explicitly models the stochastic dynamics of cell division, cell death and phenotypic switching, and it provides likelihood-based confidence intervals for the model parameters. The input data can be either the fraction of cells or the number of cells in each state at one or more time points. Through a combination of theoretical analysis and numerical simulations, we show that when cell fraction data is used, the rates of switching may be the only parameters that can be estimated accurately. On the other hand, using cell number data enables accurate estimation of the net division rate for each phenotype, and it can even enable estimation of the state-dependent rates of cell division and cell death. We conclude by applying our framework to a publicly available dataset.
Therapeutic Potential of Blocking GAPDH Nitrosylation with CGP3466b in Experimental Autoimmune Encephalomyelitis
Authors: Godfrey Wesley H. , Hwang Soonmyung , Gharibani Payam , Abramson Efrat , Kornberg Michael D.
Published: September 2022

Multiple sclerosis (MS) is a neuroinflammatory disease of the central nervous system (CNS). Although classically considered a demyelinating disease, neuroaxonal injury occurs in both the acute and chronic phases and represents a pathologic substrate of disability not targeted by current therapies. Nitric oxide (NO) generated by CNS macrophages and microglia contributes to neuroaxonal injury in all phases of MS, but candidate therapies that prevent NO-mediated injury have not been identified. Here, we demonstrate that the multifunctional protein glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is robustly nitrosylated in the CNS in the experimental autoimmune encephalomyelitis (EAE) mouse model of MS. GAPDH nitrosylation is blocked in vivo with daily administration of CGP3466b, a CNS-penetrant compound with an established safety profile in humans. Consistent with the known role of nitrosylated GAPDH (SNO-GAPDH) in neuronal cell death, blockade of SNO-GAPDH with CGP3466b attenuates neurologic disability and reduces axonal injury in EAE independent of effects on the immune system. Our findings suggest that SNO-GAPDH contributes to neuroaxonal injury during neuroinflammation and identify CGP3466b as a candidate neuroprotective therapy in MS.
Excitation creates a distributed pattern of cortical suppression due to varied recurrent input
Authors: O’Rawe Jonathan F , Zhou Zhishang , Li Anna J , LaFosse Paul K , Goldbach Hannah C , Histed Mark H
Published: September 2022

Dense local, recurrent connections are a major feature of cortical circuits, yet how they affect neurons’ responses is unclear, with some studies reporting weak recurrent effects, some amplification, and others showing instead local suppression. Here, we show that optogenetic input to mouse V1 excitatory neurons generates salt-and-pepper patterns of both excitation and suppression. Responses in individual neurons are not strongly predicted by that neuron’s direct input. A balanced-state network model reconciles a set of diverse observations: the observed dynamics, suppressed responses, decoupling of input and output, and long tail of excited responses. The model shows recurrent excitatory-excitatory connections are strong and also variable across neurons. Together, these results demonstrate that excitatory recurrent connections can have major effects on cortical computations, by shaping and changing neurons’ responses to input.
Toward a generalizable deep CNN for neural drive estimation across muscles and participants
Authors: Wen Yue , Kim Sangjoon J. , Avrillon Simon , Levine Jackson T. , Hug François , Pons José L.
Published: September 2022

High-density electromyography (HD-EMG) decomposition algorithms are used to identify individual motor unit spike trains, which collectively constitute the neural code of movements, to predict motor intent. This approach has advanced from offline to online decomposition, from isometric to dynamic contractions, leading to a wide range of neural-machine interface applications. However, current online methods need offline retraining when applied to the same muscle on a different day or to a different person, which limits their applications in a real-time neural-machine interface. We proposed a deep convolutional neural network (CNN) framework for neural drive estimation, which captures general spatiotemporal properties of motor unit action potentials to generalize its application without retraining to HD-EMG data recorded in separate sessions, muscles, and participants. We recorded HD-EMG signals from the vastus medialis and vastus lateralis muscles while participants performed isometric contractions during two sessions separated by approximately 20 months. We identified motor unit spike trains from HD-EMG signals using a blind source separation (BSS) method, and then used the cumulative spike train (CST) of these motor units and the HD-EMG signals to train and validate the deep CNN. On average, the correlation coefficients between CST from BSS and that from deep CNN were 0.977±0.007 for leave-one-out across-sessions-and-muscles validation and 0.985±0.005 for leave-one-out across-participants validation. When trained with more than four datasets, the performance of deep CNN saturated at 0.979±0.001 for cross validations across muscles, sessions, and participants. Therefore, we can conclude that the deep CNN is generalizable across the afore-mentioned conditions without retraining. We could potentially generate a robust deep CNN to estimate neural drive to muscles for neural-machine interfaces.
Lysyl oxidase-dependent subendothelial matrix stiffening promotes RAGE-mediated retinal endothelial activation in diabetes
Authors: Chandrakumar Sathishkumar , Tierno Irene Santiago , Agarwal Mahesh , Matisioudis Nikolaos , Kern Timothy S. , Ghosh Kaustabh
Published: September 2022

Endothelial cell (EC) activation is a crucial determinant of retinal vascular inflammation associated with diabetic retinopathy (DR), a major microvascular complication of diabetes. We previously showed that, similar to abnormal biochemical factors, aberrant mechanical cues in the form of lysyl oxidase (LOX)-dependent subendothelial matrix stiffening also contribute significantly to retinal EC activation in diabetes. Yet, how LOX is itself regulated and precisely how it mechanically controls retinal EC activation in diabetes is poorly understood. Here we show that high glucose-induced LOX upregulation in human retinal ECs (HRECs) is mediated by proinflammatory RAGE (receptor for advanced glycation end products/AGEs). HRECs treated with methylglyoxal (MGO), an active precursor to the AGE MG-H1, exhibited LOX upregulation that was blocked by a RAGE inhibitor, thus confirming the ability of RAGE to promote LOX expression. Crucially, as a downstream effector of RAGE, LOX was found to mediate both the proinflammatory and matrix remodeling effects of MGO/RAGE, primarily through its ability to crosslink/stiffen matrix. Finally, using decellularized HREC-derived matrices and a mouse model of diabetes, we demonstrate that LOX-dependent matrix stiffening feeds back to enhance RAGE, thereby achieving its autoregulation and proinflammatory effects. These fresh insights into the regulation and proinflammatory role of LOX-dependent mechanical cues may help identify new therapeutic targets to block AGE/RAGE signaling in DR.
From sequence to function through structure: deep learning for protein design
Authors: Ferruz Noelia , Heinzinger Michael , Akdel Mehmet , Goncearenco Alexander , Naef Luca , Dallago Christian
Published: September 2022

The process of designing biomolecules, in particular proteins, is witnessing a rapid change in available tooling and approaches, moving from design through physicochemical force fields, to producing plausible, complex sequences fast via end-to-end differentiable statistical models. To achieve conditional and controllable protein design, researchers at the interface of artificial intelligence and biology leverage advances in natural language processing (NLP) and computer vision techniques, coupled with advances in computing hardware to learn patterns from growing biological databases, curated annotations thereof, or both. Once learned, these patterns can be leveraged to provide novel insights into mechanistic biology and the design of biomolecules. However, navigating and understanding the practical applications for the many recent protein design tools is complex. To facilitate this, we 1) document recent advances in deep learning (DL) assisted protein design from the last three years, 2) present a practical pipeline that allows to go from de novo-generated sequences to their predicted properties and web-powered visualization within minutes, and 3) leverage it to suggest a generated protein sequence which might be used to engineer a biosynthetic gene cluster to produce a molecular glue-like compound. Lastly, we discuss challenges and highlight opportunities for the protein design field.

Availability

pLM generated and UniRef50 sampled sequence sets and predictions are available at http://data.bioembeddings.com/public/design. Code-base and Notebooks for analysis are available at https://github.com/hefeda/PGP. An online version of Table 1 can be found at https://github.com/hefeda/design_tools.
On quality thresholds for the clustering of molecular structures
Authors: Daura Xavier , Conchillo-Solé Oscar
Published: September 2022

It has been recently suggested that diametral (so-called quality) similarity thresholds are superior to radial ones for the clustering of molecular three-dimensional structures. 1 The argument has been made for two clustering algorithms available in various software packages for the analysis of molecular structures from ensembles generated by computer simulations, attributed to Daura et al. 2,3 (radial threshold) and Heyer et al. 4 (diametral threshold). Here, we compare these two algorithms using the root-mean-squared-difference between the Cartesian coordinates of selected atoms as pairwise similarity metric. We discuss formally the relation between these two methods and illustrate their behavior with two examples, a set of points in two dimensions and the coordinates of the tau polypeptide along a trajectory extracted from a replica-exchange molecular-dynamics simulation. 1,5 We show that the two methods produce equally-sized clusters as long as adequate choices are made for the respective thresholds. The real issue is not whether the threshold is radial or diametral, but how to choose in either case a threshold value that is physically meaningful. We will argue that, when clustering molecular structures with the RMSD as metric, the simplest best guess for a threshold is actually radial in nature.
Decoding spatiotemporal gene expression of the developing human spinal cord and implications for ependymoma origin
Authors: Li Xiaofei , Andrusivova Zaneta , Czarnewski Paulo , Langseth Christoffer Mattsson , Andersson Alma , Liu Yang , Gyllborg Daniel , Braun Emelie , Larsson Ludvig , Hu Lijuan , Alekseenko Zhanna , Lee Hower , Avenel Christophe , Kallner Helena Kopp , Åkesson Elisabet , Adameyko Igor , Nilsson Mats , Linnarsson Sten , Lundeberg Joakim , Sundström Erik
Published: September 2022

The human spinal cord contains diverse cell types, governed by a series of spatiotemporal events for tissue assembly and functions. However, the spatiotemporal regulation of cell fate specification in the human developing spinal cord remains largely unknown. Single-cell RNA sequencing and spatial transcriptomics techniques have advanced the understanding of human organ development considerably. By performing integrated analysis of single-cell and spatial multi-omics methods, we created a comprehensive developmental cell atlas of the first trimester human spinal cord. Our data revealed that the cell fate commitment of neural progenitor cells and their spatial positioning are spatiotemporally regulated by specific gene sets. Beyond this resource, we unexpectedly discovered unique events in human spinal cord development compared to rodents, including earlier quiescence of active neural stem cells, different regulation of stem cell differentiation, and distinct spatiotemporal genetic regulations of cell fate choices. In addition, using our atlas we identified specific gene expression in cancer stem cells in ependymomas. Thus, we demonstrate spatiotemporal genetic regulation of human spinal cord development as well as its potential to understand novel disease mechanisms and to inspire new therapies.
Accumulated metagenomic studies reveal recent migration, whole genome evolution, and undiscovered diversity of orthomyxoviruses
Authors: Dudas Gytis , Batson Joshua
Published: September 2022

Metagenomic studies have uncovered many novel viruses by looking beyond hosts of public health or economic interest. However, the resulting viral genomes are often incomplete, and analyses largely characterize the distribution of viruses over their dynamics. Here, we integrate accumulated data from metagenomic studies to reveal geographic and evolutionary dynamics in a case study ofOrthomyxoviridae, the RNA virus family that includes influenza virus. First, we use sequences of the orthomyxovirid Wǔhàn mosquito virus 6 to track the migrations of its host. We then look at orthomyxovirus genome evolution, finding gene gain and loss across members of the family, especially in the surface proteins responsible for cell and host tropism. We find that the surface protein of Wǔhàn mosquito virus 6 exhibits accelerated non-synonymous evolution suggestive of antigenic evolutioni.e. vertebrate infection, and belongs to a wider quaranjavirid group bearing highly diverged surface proteins. Finally we quantify the progress of orthomyxovirus discovery and forecast that many divergedOrthomyxoviridaemembers remain to be found. We argue that continued metagenomic studies will be fruitful for understanding the dynamics, evolution, ecology of viruses and their hosts, regardless of whether novel viruses are identified or not, as long as study designs allowing for the resolution of complete viral genomes are employed.

0.1

Importance

The number of known virus species has increased dramatically through metagenomic studies, which search genetic material sampled from a host for non-host genes. Here, we focus on an important viral family that includes influenza viruses, theOrthomyxoviridae, with over a hundred recently discovered viruses infecting hosts from humans to fish. We find one virus called Wǔhàn mosquito virus 6, discovered in mosquitoes in China, has spread across the globe very recently. Surface proteins used to enter cells show signs of rapid evolution in Wǔhàn mosquito virus 6 and its relatives which suggests an ability to infect vertebrate animals. We compute the rate at which new orthomyxovirus species discovered add evolutionary history to the tree of life, predict that many viruses remain to be discovered, and discuss what appropriately designed future studies can teach us about how diseases cross between continents and species.
Cell-intrinsic ceramides determine T cell function during melanoma progression
Authors: Hose Matthias , Günther Anne , Naser Eyad , Schumacher Fabian , Schönberger Tina , Falkenstein Julia , Papadamakis Athanassios , Kleuser Burkhard , Becker Katrin Anne , Gulbins Erich , Haimovitz-Friedman Adriana , Buer Jan , Westendorf Astrid M. , Hansen Wiebke
Published: September 2022

Acid sphingomyelinase (Asm) and acid ceramidase (Ac) are parts of the sphingolipid metabolism. Asm hydrolyzes sphingomyelin to ceramide, which is further metabolized to sphingosine by Ac. Ceramide generates ceramide-enriched platforms that are involved in receptor clustering within cellular membranes. However, the impact of cell-intrinsic ceramide on T cell function is not well characterized. By using T cell-specific Asm- or Ac-deficient mice, with reduced or elevated ceramide levels in T cells, we identified ceramide to play a crucial role in T cell function in vitro and in vivo. T cell-specific ablation of Asm in Asmflox/flox/CD4cre mice resulted in enhanced tumor progression associated with impaired T cell responses, whereas Acflox/flox/CD4cre mice showed reduced tumor growth rates and elevated T cell activation compared to the respective controls upon tumor transplantation. Further in vitro analysis revealed that decreased ceramide content supports CD4+ regulatory T cell differentiation and interferes with cytotoxic activity of CD8+ T cells. In contrast, elevated ceramide concentration in CD8+ T cells from Acflox/flox/CD4cre mice was associated with enhanced cytotoxic activity. Strikingly, ceramide co-localized with the T cell receptor (TCR) and CD3 in the membrane of stimulated T cells and phosphorylation of TCR signaling molecules was elevated in Ac-deficient T cells. Hence, our results indicate that modulation of ceramide levels, by interfering with the Asm or Ac activity has an effect on T cell differentiation and function and might therefore represent a novel therapeutic strategy for the treatment of T cell-dependent diseases such as tumorigenesis.
Refining Embedding-Based Binding Predictions by Leveraging AlphaFold2 Structures
Authors: Endres Leopold , Olenyi Tobias , Erckert Kyra , Weißenow Konstantin , Rost Burkhard , Littmann Maria
Published: September 2022

Background

Identifying residues in a protein involved in ligand binding is important for understanding its function. bindEmbed21DL is a Machine Learning method which predicts protein-ligand binding on a per-residue level using embeddings derived from the protein Language Model (pLM) ProtT5. This method relies solely on sequences, making it easily applicable to all proteins. However, highly reliable protein structures are now accessible through the AlphaFold Protein Structure Database or can be predicted using AlphaFold2 and ColabFold, allowing the incorporation of structural information into such sequence-based predictors.

Results

Here, we propose bindAdjust which leverages predicted distance maps to adjust the binding probabilities of bindEmbed21DL to subsequently boost performance. bindAdjust raises the recall of bindEmbed21DL from 47±2% to 53±2% at a precision of 50% for small molecule binding. For binding to metal ions and nucleic acids, bindAdjust serves as a filter to identify good predictions focusing on the binding site rather than isolated residues. Further investigation of two examples shows that bindAdjust is in fact able to add binding predictions which are not close in sequence but close in structure, extending the binding residue predictions of bindEmbed21DL to larger binding stretches or binding sites.

Conclusion

Due to its simplicity and speed, the algorithm of bindAdjust can easily refine binding predictions also from other tools than bindEmbed21DL and, in fact, could be applied to any protein prediction task.
Consequences of life-cycle complexity to the potential for evolutionary branching
Authors: Vasconcelos Paula , Saltini Marco , Rueffler Claus
Published: September 2022

Complex life-cycles – that is, organismal development that unfolds across ecological niches – are pervasive in nature. In this work we set out to investigate the effects of complex life-cycles on the potential for diversification via evolutionary branching. We did this by analyzing a mathematical model of a consumer with two life-stages, each of which is characterized by a specific feeding efficiency trait that undergoes evolutionary change in response to ecological conditions such as resource competition. We find (i) that life-cycle complexity can favor diversification when compared to simple life-cycles, as there is a larger potential for evolutionary branching in the trait of the life-stage that has a higher population density; (ii) that evolution favors character displacement to minimize intra-stage resource competition; and (iii) that under certain parameters more than one evolutionary branching event can occur.
A Machine Learning and Bioinformatic Analysis Reveals an Associated between Cell Surface Receptor Transcript Levels with Drug Response of Breast Cancer Cells and the Drug Off-Target Effects
Authors: Sinkala Musalula , Naran Krupa , Ramamurthy Dharanidharan , Mungra Neelakshi , Martin Darren , Barth Stefan
Published: September 2022

Breast cancer is characterised by varied responses to different anticancer therapies, which may provoke several different off-target effects. We hypothesise that for drugs that target cell surface receptors (CSRs), the different responses of tumours and the adverse events produced by these drugs may be attributed to variations in the transcriptional landscapes of CSRs in both breast tumours and healthy tissues. Here, we use data from various sources to compare the CSR transcriptional landscapes of breast tumours and a range of different non-diseased human tissues. We demonstrate an association between the responses to drug perturbation of breast cancer cell lines and the transcription levels of their targeted CSRs. Furthermore, we reveal important differences in the CSR transcriptional landscapes of primary breast tumour subtypes and the CSR transcriptional landscapes of breast cancer cell lines, which will likely impact the accuracy of drug response predictions. Finally, applying clinical trial data, we expose a link between the expression levels of CSR genes in healthy tissues and adverse reactions of patients to anticancer drugs. Altogether, this approach allows for the isolation of the most suitable CSR target(s) among the expressed transcripts, solely based on the measured dose-responses of cell lines to small molecules, the CSR transcriptional landscape in health patient tissues, and reported adverse responses of patients to drugs targeting CSRs.
Decoy effect in shoaling decision making in zebrafish
Authors: Singh Abhishek , Kumari Kajal , Kalra Sanya , Pal Shubhi , Rajaraman Bittu Kaveri
Published: September 2022

The decoy effect, a bias in choice between two options when a third, inferior option is introduced, has been observed across various organisms, from slime molds to humans. In this study, we investigated whether zebrafish (Danio rerio), a widely used biological model organism, exhibit the decoy effect in their shoaling group choices, specifically examining this effect by varying only shoal size. Using spatial trajectory analysis of freely swimming zebrafish interacting with conspecifics in adjacent display tanks, we tested how shoaling decisions varied between dichotomous (two-option) and trichotomous (three-option) choice sets. Our experiments compared preferences for 4 versus 2 and 6 versus 3 shoal sizes, with a single fish serving as a decoy in the trichotomous sets. The results revealed sex-specific differences in the decoy effect: males exhibited a shift in preference only in the Trichotomous-first condition, where prior exposure to the decoy led to a significant preference for the larger shoal. In contrast, females displayed the decoy effect exclusively in the Dichotomous-first condition, shifting from a significant preference for the larger shoal to showing no clear preference in the presence of the decoy. Notably, our findings demonstrate that the decoy effect can occur even when studied unidimensionally, with both sex and the order of presentation influencing zebrafish shoaling preferences. These results offer new insights into decision-making processes and highlight the importance of considering order effects in studies of choice behavior, with potential methodological implications for research in other species.
A circulating biomarker of facioscapulohumeral muscular dystrophy clinical severity, valid in skeletal muscle and blood
Authors: Banerji Christopher R. S. , Greco Anna , Joosten Leo A. B. , van Engelen Baziel , Zammit Peter S.
Published: September 2022

Facioscapulohumeral muscular dystrophy (FSHD) is incurable. DUX4 mis-expression is believed to underlie FSHD pathogenesis, alongside PAX7 target gene repression, yet clinical trials lack robust biomarkers of severity. FSHD entails fatty replacement of muscle, accelerated by inflammation, we thus performed RNA-sequencing on both an MRI guided inflamed (TIRM+) and non-inflamed (TIRM-) muscle biopsies from clinically-characterised FSHD patients, alongside peripheral blood mononucleated cells (PBMCs). PAX7 target gene repression in TIRM-muscle associates with severity. DUX4 target gene biomarkers associate with lower limb fat fraction and D4Z4 repeat length, but not severity. PAX7 target gene repression in muscle correlates with levels in matched PBMCs. A refined biomarker computed in PBMCs associates with severity in FSHD patients, and also validates as a classifier of severity in an independent set of 54 FSHD patient blood samples. In summary, we present a minimally-invasive, circulating, transcriptomic biomarker of FSHD clinical severity valid in muscle and blood.
Salinomycin disturbs Golgi apparatus function and specifically affects cells in epithelial-to-mesenchymal transition
Authors: Marjanović Marko , Dražić Ana-Matea Mikecin , Mioč Marija , Kliček Filip , Novokmet Mislav , Lauc Gordan , Kralj Marijeta
Published: September 2022

Epithelial-to-mesenchymal transition (EMT) gives rise to cells with properties similar to cancer stem cells (CSCs). Targeting the EMT program to selectively eliminate CSCs is a promising way to improve cancer therapy. Salinomycin (Sal), a K+/H+ ionophore, was identified as highly selective towards CSC-like cells, but its mechanism of action and selectivity remains elusive. Here we show that Sal, similarly to monensin and nigericin, disturbs the function of the Golgi apparatus (GA). Sal alters the expression of GA-related genes and leads to marked changes in GA morphology, particularly in cells that underwent EMT. Moreover, GA disturbing agents severely affect protein post-translational modifications including protein processing, glycosylation and secretion. We discover that the alterations induced by GA disturbing agents specifically affect the viability of EMT cells. Collectively, our work identifies a new vulnerability related to the EMT, suggesting that targeting the GA is a novel therapeutic approach against CSCs.
Modelling human endurance: Power laws vs critical power
Authors: Drake Jonah , Finke Axel , Ferguson Richard
Published: September 2022

Thepower–duration relationshipdescribes the time to exhaustion for exercise at different intensities. It is generally believed to be a “fundamental bioenergetic property of living systems” that this relationship is hyperbolic. Indeed, thehyperbolic(a.k.a.critical-power) model which formalises this belief is the dominant tool for describing and predicting high-intensity exercise performance, e.g. in cycling, running, rowing, or swimming. However, the hyperbolic model is now the focus of two heated debates in the literature because: (a) it unrealistically represents efforts that are short (< 2 minutes) or long (> 15 minutes); (b) it contradicts widely-used performance predictors such as the so-calledfunctional threshold power(FTP) in cycling. We contribute to both debates by demonstrating that the power–duration relationship is more adequately represented by an alternative,power-lawmodel. In particular, we show that the often observed good fit of the hyperbolic model between 2 and 15 minutes should not be taken as proof that the power–duration relationship is hyperbolic. Rather, in this range, a hyperbolic function just happens to approximate a power law fairly well. We also prove mathematical results which suggest that the power-law model is a safer tool for pace selection than the hyperbolic model and that the former better models fatigue than the latter. Finally, we use the power-law model to shed light on popular performance predictors in cycling, running and rowing such as FTP and Jack Daniels’“VDOT” calculator.
CRTC-1 balances histone trimethylation and acetylation to promote longevity
Authors: Silva-García Carlos G. , Láscarez-Lagunas Laura I. , Papsdorf Katharina , Heintz Caroline , Prabhakar Aditi , Morrow Christopher S. , Torres Lourdes Pajuelo , Sharma Arpit , Liu Jihe , Colaiácovo Monica P. , Brunet Anne , Mair William B.
Published: September 2022

Loss of function during ageing is accompanied by transcriptional drift, altering gene expression and contributing to a variety of age-related diseases. CREB-regulated transcriptional coactivators (CRTCs) have emerged as key regulators of gene expression that might be targeted to promote longevity. Here, we define the role of theCaenorhabditis elegansCRTC-1 in the epigenetic regulation of longevity. Endogenous CRTC-1 binds chromatin factors, including components of the COMPASS complex, which trimethylates lysine 4 on histone H3 (H3K4me3). CRISPR editing of endogenous CRTC-1 reveals that the CREB-binding domain in neurons is specifically required for H3K4me3-dependent longevity. However, this effect is independent of CREB but instead acts via the transcription factor AP-1. Strikingly, CRTC-1 also mediates global histone acetylation levels, and this acetylation is essential for H3K4me3-dependent longevity. Indeed, overexpression of an acetyltransferase enzyme is sufficient to promote longevity in wild-type worms. CRTCs, therefore, link energetics to longevity by critically fine-tuning histone acetylation and methylation to promote healthy ageing.
A Camera-Assisted Pathology Microscope to Capture the Lost Data in Clinical Glass Slide Diagnosis
Authors: Ashman Kimberly , Cooper Max S. , Zhuge Huimin , Fox Sharon E. , Epstein Jonathan I. , Wenk Carola , Summa Brian , Brown J. Quincy
Published: September 2022

Digital pathology, or the practice of acquiring, managing, and interpreting high-resolution digital images from glass pathology slides, holds much promise in precision medicine, potentially transforming diagnosis and prognosis based on computational image biomarkers derived from digital tissue images. However, for all its promise, digital imaging in pathology has not yet become an integral part of the clinical workflow as it has in radiology due to high cost, workflow disruptions, burdensome data sizes and IT requirements, and additional dedicated personnel requirements. Consequently, pathology retains the 150-year-old analog workflow, and the vast majority of slides used in clinical diagnosis are never digitized. Furthermore, there is a missed opportunity to capture the image information and associated data on search processes that led to the clinical diagnosis, which could serve as the foundation for computational clinical decision support. This paper describes an approach for slide digitization during clinical review using a camera attached to a standard brightfield pathology microscope. While a pathologist reviews a glass slide using the eyepiece oculars, the continuously running camera digitizes a complete record of the slide review, resulting in multi-resolution slide images and spatiotemporal saliency maps of the slide review. Unlike other approaches, the pathologist does not stop to review the video stream or monitor the acquisition of video frames but performs the diagnostic review at the microscope using the standard clinical protocol. This hybrid analog-digital approach combines the benefits of digital slide analysis, including annotation, computation, and the ability to confirm the completeness and quality of the glass slide review with the ease of using the microscope for primary diagnosis. Furthermore, a record of the pathologist’s attention during the review, including their search path, magnification level, and dwell times at each location on the slide, is obtained. In the future, this approach could enable the development and application of new and emerging computational decision-support algorithms in real-time to provide feedback to the pathologist, reduce diagnostic errors, and improve disease diagnosis and prognosis.
STAT3 cooperates with the core transcriptional regulatory circuitry to drive MYC expression and oncogenesis in anaplastic large cell lymphoma
Authors: Prutsch Nicole , He Shuning , Berezovskaya Alla , Durbin Adam D. , Dharia Neekesh V. , Stegmaier Kimberly , Matthews Jamie D. , Hare Lucy , Turner Suzanne D. , Kenner Lukas , Merkel Olaf , Young Richard A. , Abraham Brian J. , Look A. Thomas , Zimmerman Mark W.
Published: September 2022

Anaplastic large cell lymphoma (ALCL) is an aggressive, CD30+ T-cell lymphoma of children and adults. ALK fusion transcripts or mutations in the JAK-STAT pathway are observed in most ALCL tumors, but the mechanisms underlying tumorigenesis are not fully understood. Here we show that dysregulated STAT3, together with a core transcriptional regulatory circuit consisting of BATF3–IRF4– IKZF1, co-occupies gene enhancers to establish an oncogenic transcription program and maintain the malignant state of ALCL. Critical downstream targets of this network in ALCL cells include the proto-oncogene MYC, which requires active STAT3 to facilitate high levels of MYC transcription. The activity of this auto-regulatory transcription loop is reinforced by MYC binding to the enhancer regions associated with STAT3 and each of the core regulatory transcription factors. These findings provide new insights for understanding how dysregulated signaling pathways hijack cell-type-specific transcriptional machinery to drive tumorigenesis and create therapeutic vulnerabilities in genetically defined tumors.
Enhancer Reprogramming in Melanoma Immune Checkpoint Therapy Resistance
Authors: Maitituoheti Mayinuer , Shi Alvin , Tang Ming , Ho Li-Lun , Terranova Christopher , Galani Kyriaki , Keung Emily Z. , Creasy Caitlin A. , Wu Manrong , Chen Jiajia , Chen Nana , Singh Anand K. , Chaudhri Apoorvi , Anvar Nazanin E. , Tarantino Giuseppe , Yang Jiekun , Sarkar Sharmistha , Jiang Shan , Malke Jared , Haydu Lauren , Burton Elizabeth , Davies Michael A. , Gershenwald Jeffrey E. , Hwu Patrick , Lazar Alexander , Cheah Jaime H. , Soule Christian K. , Levine Stuart S. , Bernatchez Chantale , Saladi Srinivas V. , Liu David , Wargo Jennifer , Boland Genevieve M. , Kellis Manolis , Rai Kunal
Published: September 2022

Immune checkpoint blockade (ICB) therapy has improved long-term survival for patients with advanced melanoma. However, there is critical need to identify potential biomarkers of response and actionable strategies to improve response rates. Through generation and analysis of 148 chromatin modification maps for 36 melanoma samples from patients treated with anti-PD- 1, we identified significant enrichment of active enhancer states in non-responders at baseline. Analysis of an independent cohort of 20 samples identified a set of 437 enhancers that predicted response to anti-PD-1 therapy (Area Under the Curve of 0.8417). The activated non-responder enhancers marked a group of key regulators of several pathways in melanoma cells (including c- MET, TGFβ, EMT and AKT) that are known to mediate resistance to ICB therapy and several checkpoint receptors in T cells. Epigenetic editing experiments implicated involvement of c-MET enhancers in the modulation of immune response. Finally, inhibition of enhancers and repression of these pathways using bromodomain inhibitors along with anti-PD-1 therapy significantly decreased melanoma tumor burden and increased T-cell infiltration. Together, these findings identify a potential enhancer-based biomarker of resistance to anti-PD-1 and suggest enhancer blockade in combination with ICB as a potential strategy to improve responses.
Drug-Drug Interaction Extraction from Biomedical Text using Relation BioBERT with BLSTM
Authors: KafiKang Maryam , Hendawi Abdeltawab
Published: September 2022

Drug-drug interactions (DDIs) happen when two or more drugs interact. DDIs may change the effect of drugs in the body which can induce adverse effects and severe diseases for patients. As a result, detecting the interaction between drugs is essential. In the last years, many new DDIs have been found and added to the medical datasets with the rise in the number of discovered drugs. On the other hand, since a lot of this information is still in Biomedical articles and sources, there is a need for a method to extract DDIs information. However, despite the development of many techniques, attaining good prediction accuracy is the main issue. This paper proposes a deep learning approach that: 1) uses the power of Relation BioBERT (R-BioBERT) to detect and classify the DDIs and 2) employs the Bidirectional Long-Short Term Memory (BLSTM) to further increase the prediction quality. Not only does this paper study whether the two drugs have an interaction or not, but it also studies specific types of interactions between drugs. The paper also provides that using BLSTM can significantly increase the F-scores compared to the baseline model on the famous SemEval 2013, TAC 2018, and TAC 2019 DDI Extraction datasets.
A two-compartment system for subfreezing temperatures preservation of large volumes of organic matter in an isochoric system
Authors: Năstase Gabriel , Botea Florin , Beșchea George-Andrei , Câmpean Ștefan-Ioan , Barcu Alexandru , Popescu Irinel , Rubinsky Boris , Șerban Alexandru
Published: September 2022

This is a technology paper on the design of and test results from an 11-liter isochoric (constant volume) chamber, for the preservation of large, organs in a supercooled state. Details of the design are given, as well as a proof that the chamber is isochoric. Five repeats show that in this large chamber, ice nucleation of steam distilled water occurs at – 2 °C within less than 12 hours, in all the repeats. An examination of the experimental results suggests that the ice nucleation starts on the inner walls of the isochoric chamber. A new two compartment isochoric chamber was designed to reduces the probability of ice nucleation on the walls of the chamber. In the two-compartment system, the biological matter and the preservation fluid are introduced in a sealed low-density polyethylene bag, and placed in the center of the isochoric chamber, in such a way that the bag does not touch the walls. The space between the inner walls of the isochoric chamber and the outer walls of the bag are filled with a fluid with a composition that does not freeze at the storage temperature. Three repeat experiments with steam distilled water and with in vitro pig liver show that with this technique, the system remained supercooled, without any ice nucleation for the duration of the experiments. Experiments were voluntary terminated at 48 hours of supercooling. This new technology may hold promise for long term preservation of large biological organs in a supercooled state, without the use of any chemical additives.