bluuebunny/crossref_metadata_2025 huggingface dataset:
Logistic resource limitation model for quasi real-time measured subjective cognitive load predicts Hill function of hemoglobin-oxygen saturation
Authors: Fürstenau Norbert
Published: January 2024

Cognitive processing and memory resources invested in task execution determine mental workload (MWL) that is quantified through objective physiological measures such as heart rate and variability, EEG, and hemoglobin oxygen (HbO2) saturation, and subjective methods like periodic quasi-real-time “instantaneous self-assessment” (ISA) with discrete five- or seven-level WL-scales. Previously published results of human-in-the-loop (HITL) air-traffic control simulations with highly trained domain experts provided initial evidence for logistic and power law functional dependencies between subjective MWL self-assessment reports and simultaneously monitored task load and simulation variables (e.g. communication and traffic load). Here we show that a biased “Logistic Resource Limitation” (LRL) model for regression based parameter estimates of subjective self-reports through combination with a logistic task load function leads to a cognitive power law with parametric correspondence to the classical Hill function that quantifies HbO2saturation. Hill function saturation exponent and equilibrium dissociation constant turned out to show surprising agreement with corresponding estimates of the power law parameters derived from the LRL-model applied to published independent data sets from the three different HITL-simulation experiments. Our results suggest the hypothesis that under certain conditions quasi real-time subjective (behavioral) reporting of cognitive load due to task execution might represent the output of an interoceptive HbO2saturation sensor that measures resource limitation of neural energy supply. From the HbO2- saturation perspective, our results might provide an additional aspect to the “selfish brain” theory for cortical energy supply as derived by A. Peters et al. based on a logistic Glucose push–pull supply chain model. However, more focused experiments are required including direct (e.g. fNIR based) measurements of HbO2-saturation to further support (or falsify) our conclusions.

Author Summary

Measurements of mental workload of domain experts under cognitive task requirements by human-in-the-loop simulation experiments utilize subjective and objective methods and measures. Standard data analysis is mostly limited to linear statistical methods such as variance and regression analysis for quantifying load differences under different task requirements. Based on nonlinear resource limitation models with asymptotic saturation limits we derive here a cognitive power law for the dependency of real-time subjective work- vs. objective task load. The focused analysis of three previously published independent datasets revealed an unexpected formal and quantitative equivalence with the classical Hill-function of blood-oxygen saturation. Our results suggest the hypothesis of a close quantitative relationship between subjective load reports and an interoceptive senor for cortical energy resources.
Beyond comparison: Brillouin microscopy and AFM-based indentation reveal divergent insights into the mechanical profile of the murine retina
Authors: Möllmert Stephanie , Gutmann Marcus , Müller Paul , Kim Kyoohyun , Salvador Jana Bachir , Aif Serhii , Meinel Lorenz , Guck Jochen
Published: January 2024

Mechanical tissue properties increasingly serve as pivotal phenotypic characteristics that are subject to change during development or pathological progression. The quantification of such material properties often relies on physical contact between a load-applying probe and an exposed sample surface. For most tissues, these requirements necessitate animal sacrifice, tissue dissection and sectioning. These invasive procedures bear the risk of yielding mechanical properties that do not portray the physiological mechanical state of a tissue within a functioning organism. Brillouin microscopy has emerged as a non-invasive, optical technique that allows to assess mechanical cell and tissue properties with high spatio-temporal resolution. In optically transparent specimens, this technique does not require animal sacrifice, tissue dissection or sectioning. However, the extent to which results obtained from Brillouin microscopy allow to infer conclusions about potential results obtained with a contact-based technique, andvice versa, is unclear. Potential sources for discrepancies include the varying characteristic temporal and spatial scales, the directionality of measurement, environmental factors, and mechanical moduli probed. In this work, we addressed those aspects by quantifying the mechanical properties of acutely dissected murine retinal tissues using Brillouin microscopy and atomic force microscopy (AFM)-based indentation measurements. Our results show a distinct mechanical profile of the retinal layers with respect to the Brillouin frequency shift, the Brillouin linewidth and the apparent Young’s modulus. Contrary to previous reports, our findings do not support a simple correlative relationship between Brillouin frequency shift and apparent Young’s modulus. Additionally, the divergent sensitivity of Brillouin microscopy and AFM-indentation measurements to cross-linking or changespost mortemunderscores the dangers of assuming both methods can be generally used interchangeably. In conclusion, our study advocates for viewing Brillouin microscopy and AFM-based indentation measurements as complementary tools, discouraging direct comparisonsa prioriand suggesting their combined use for a more comprehensive understanding of tissue mechanical properties.
Sex-biased migration and demographic history of the big European fireflyLampyris noctiluca
Authors: Catalán Ana , Gygax Daniel , Candolin Ulrika , Tusso Sergio , Duchen Pablo , Höhna Sebastian
Published: January 2024

Differential dispersion between the sexes can impact population structure and connectivity between populations, which in turn, can have an effect on the evolvability capability of a species. Here we explored the demographic history of the big European firefly,Lampyris noctiluca, which exhibits female neoteny.L. noctilucadistribution extends throughout Europe, but nothing is known on how its colonization processes. To investigate this, we produced the firstLampyrisgenome (653Mb), including an IsoSeq annotation and the identification of the X chromosome. We collected 115 individuals from six populations ofL. noctiluca(Finland to Italy) and generated whole genome re-sequencing for each individual. We inferred several population expansions and bottlenecks throughout the Pleistocene that correlate with glaciation events. Surprisingly, we uncovered strong population structure and low gene-flow. We reject a stepwise, south to north, colonization history scenario and instead uncovered a complex demographic history with a putative eastern European origin. Analyzing the evolutionary history of the mitochondrial genome as well as X-linked and autosomal loci, we found evidence of a maternal colonialization of Germany, putatively from a western European population, followed by male-only migration from south of the Alps (Italy). Overall, investigating the demographic history and colonization patterns of a species should form part of an integrative approach of biodiversity research. Our results provide evidence of sex-biased migration which is important to consider for demographic, biogeographic and species delimitation studies.
Single-cell RNA-seq based elucidation of the antidepressant hyperforin biosynthesisde novoin St. John’s wort
Authors: Wu Song , Morotti Ana Luisa Malaco , Yang Jun , Wang Ertao , Tatsis Evangelos C.
Published: January 2024

Hyperforin is the compound responsible for the effectiveness of St. John’s wort (Hypericum perforatum) as an antidepressant, but its biosynthesis remains unknown. Gene discovery based on co-expression analysis of bulk RNA-sequencing data or genome mining failed to discover the missing steps in hyperforin biosynthesis. Here we sequenced the tetraploidH. perforatumgenome. By single-cell RNA-seq, we identified a distinct type of cells, Hyper cells, wherein hyperforin biosynthesisde novotakes place. Through pathway reconstitution in yeast and tobacco, we identify and characterize four transmembrane prenyltransferases to resolve hyperforin biosynthesis. The hyperforin polycyclic scaffold is created by a reaction cascade involving an irregular isoprenoid coupling and a tandem cyclization. Our findings reveal how and where hyperforin is biosynthesized that enables synthetic-biology reconstitution of the complete pathway. These results deepen our comprehension of specialized metabolism at the cellular level, and we anticipate acceleration of pathway elucidation in plant metabolism.
An analysis of semaphorin-mediated cellular interactions in theC. elegansepidermis using the IR-LEGO single-cell gene induction system
Authors: Suzuki Motoshi , Takagi Shin
Published: January 2024

One of the major functions of the semaphorin signaling system is the regulation of cell shape. In the nematodeC. elegans, membrane-bound semaphorins SMP-1/2 (SMPs) regulate the morphology of epidermal cells via their receptor plexin, PLX-1. In the larval male tail of the SMPs/PLX-1 signaling mutants, the border between two epidermal cells, R1.p and R2.p, is displaced anteriorly, resulting in the anterior displacement of the anterior most ray, ray 1, in the adult male. To elucidate how the intercellular signaling mediated by SMPs regulates the position of the intercellular border, we performed mosaic gene expression analyses by using IR-LEGO (InfraRedLaserEvokedGeneOperator). We show that PLX-1 expressed in R1.p and SMP-1 expressed in R2.p is required for proper positioning of ray 1. The result suggests that SMPs signaling promotes extension, rather than retraction, of R1.p. This is in contrast to a previous finding that SMPs mediate inhibition of cell-extension of vulval precursor cells, another group of epidermal cells ofC. elegans,indicating the context-dependence of cell shape control via the semaphorin signaling system.
Polarity-JaM: An image analysis toolbox for cell polarity, junction and morphology quantification
Authors: Giese Wolfgang , Albrecht Jan Philipp , Oppenheim Olya , Akmeriç Emir Bora , Kraxner Julia , Schmidt Deborah , Harrington Kyle , Gerhardt Holger
Published: January 2024

Cell polarity involves the asymmetric distribution of cellular components such as signaling molecules and organelles within a cell, asymmetries of a cell”s shape as well as contacts with neighbouring cells. Gradients and mechanical forces often act as global cues that bias cell polarity and orientation, and polarity is coordinated by communication between adjacent cells.

Advances in fluorescence microscopy combined with deep learning algorithms for image segmentation open up a wealth of possibilities to understand cell polarity behaviour in health and disease. We have therefore developed the open-source package Polarity-JaM, which offers versatile methods for performing reproducible exploratory image analysis. Multi-channel single cell segmentation is performed using a flexible and userfriendly interface to state-of-the-art deep learning algorithms. Interpretable single-cell features are automatically extracted, including cell and organelle orientation, cell-cell contact morphology, signaling molecule gradients, as well as collective orientation, tissue-wide size and shape variation. Circular statistics of cell polarity, including polarity indices, confidence intervals, and circular correlation analysis, can be computed using our web application. We have developed data graphs for comprehensive visualisation of key statistical measures and suggest the use of an adapted polarity index when the expected polarisation direction or the direction of a global cue is knowna priori.

The focus of our analysis is on fluorescence image data from endothelial cells (ECs) and their polarisation behaviour. ECs line the inside of blood vessels and are essential for vessel formation and repair, as well as for various cardiovascular diseases, cancer, and inflammation. However, the general architecture of the software will allow it to be applied to other cell types and image modalities. The package is built in in Python, allowing researchers to seamlessly integrate Polarity-JaM into their image and data analysis workflows, seehttps://polarityjam. readthedocs.io. In addition, a web application for statistical analysis, available atwww.polarityjam.com, and a Napari plugin are available, each with a graphical user interface to facilitate exploratory analysis.
Inferring internal states across mice and monkeys using facial features
Authors: Tlaie Alejandro , El Hay Muad Y. Abd , Mert Berkutay , Taylor Robert , Ferracci Pierre-Antoine , Shapcott Katharine , Glukhova Mina , Pillow Jonathan W , Havenith Martha N , Schölvinck Marieke L
Published: January 2024

Animal behaviour is shaped to a large degree by internal cognitive states, but it is unknown whether these states are similar across species. To address this question, here we develop a virtual reality setup in which male mice and macaques engage in the same naturalistic visual foraging task. We exploit the richness of a wide range of facial features extracted from video recordings during the task, to train a Markov-Switching Linear Regression (MSLR). By doing so, we identify, on a singletrial basis, a set of internal states that reliably predicts when the animals are going to react to the presented stimuli. Even though the model is trained purely on reaction times, it can also predict task outcome, supporting the behavioural relevance of the inferred states. The relationship of the identified states to task performance is comparable between mice and monkeys. Furthermore, each state corresponds to a characteristic pattern of facial features that partially overlaps between species, highlighting the importance of facial expressions as manifestations of internal cognitive states across species.
PHOSPHATE-INDUCED 1 and its paralogs positively regulate cellulose biosynthesis in Arabidopsis
Authors: Yu Fugen , Wang Qiang , Qiu Jieren , Liao Yonghui , Wang Xin , Cao Tianjun , Zhang Jiao , Yin Shan , Zhuang Zhong , Chen Xiaolin , Jiang Haojie , Lu Shan
Published: January 2024

Cellulose is not only the most abundant biopolymer on Earth but also an essential multi-purpose resource, primarily synthesized by cellulose synthase complexes (CSCs) located on plasma membrane in vascular plants. Although insights into the functions of CSCs have been provided by the identification of cellulose synthase catalytic subunits, our understanding of the regulation of CSC activity remains limited. In this study, combining molecular and genetic methods, we demonstrated that both PHI-1 and its paralogs residing in the plasma membrane are involved in the cellulose biosynthesis regulation as a positive regulatory component of CSCs by feeding developmental and environmental cues into their activities in Arabidopsis (Arabidopsis thaliana). Our finding reveals a mechanism for how plants regulate cellulose synthesis in response to developmental and environmental signals, and thus improves the likelihood that cellulose biosynthesis could be feasibly adapted for sustainable purposes.
Spatiotemporal Modeling of Mitochondrial Network Architecture
Authors: Holt Keaton , Winter Julius , Manley Suliana , Koslover Elena F.
Published: January 2024

In many cell types, mitochondria undergo extensive fusion and fission to form dynamic, responsive network structures that contribute to a number of homeostatic, metabolic, and signaling functions. The relationship between the dynamic interactions of individual mitochondrial units and the cell-scale network architecture remains an open area of study. In this work, we use coarse-grained simulations and approximate analytic models to establish how the network morphology is governed by local mechanical and kinetic parameters. The transition between fragmented structures and extensive networks is controlled by local fusion-to-fission ratios, network density, and geometric constraints. Similar fusion rate constants are found to account for the very different structures formed by mammalian networks (poised at the percolation transition) and well-connected budding yeast networks. Over a broad parameter range, the simulated network structures can be described by effective mean-field association constants that exhibit a non-linear dependence on the microscopic non-equilibrium fusion, fission, and transport rates. Intermediate fusion rates are shown to result in the highest rates of network remodeling, with mammalian mitochondrial networks situated in a regime of high turnover. Our modeling framework helps to elucidate how local parameters that govern mitochondrial interactions give rise to spatially resolved dynamic network structures at the cellular scale.
Predicting the DNA binding specificity of mutated transcription factors using family-level biophysically interpretable machine learning
Authors: Liu Shaoxun , Gomez-Alcala Pilar , Leemans Christ , Glassford William J. , Mann Richard S. , Bussemaker Harmen J.
Published: January 2024

Sequence-specific interactions of transcription factors (TFs) with genomic DNA underlie many cellular processes. High-throughputin vitrobinding assays coupled with computational analysis have made it possible to accurately define such sequence recognition in a biophysically interpretable yet mechanism-agonistic way for individual TFs. The fact that such sequence-to-affinity models are now available for hundreds of TFs provides new avenues for predicting how the DNA binding specificity of a TF changes when its protein sequence is mutated. To this end, we developed an analytical framework based on a tetrahedron embedding that can be applied at the level of a given structural TF family. Using bHLH as a test case, we demonstrate that we can systematically map dependencies between the protein sequence of a TF and base preference within the DNA binding site. We also develop a regression approach to predict the quantitative energetic impact of mutations in the DNA binding domain of a TF on its DNA binding specificity, and perform SELEX-seq assays on mutated TFs to experimentally validate our results. Our results point to the feasibility of predicting the functional impact of disease mutations and allelic variation in the cell-wide TF repertoire by leveraging high-quality functional information across sets of homologous wild-type proteins.

SIGNIFICANCE STATEMENT

Transcription factors (TFs) are DNA binding proteins that play a key role in gene expression control. Genetic mutations in the protein sequence of TFs are increasingly found to be associated with disease. Being able to predict the functional impact of such mutations in terms the quantitative changes in DNA sequence preference they cause is therefore highly useful. TFs come in families that are structurally similar but vary in terms of their sequence and function. In this study, we show that by jointly analyzing high-throughput DNA binding data for the basic helix-loop-helix (bHLH) family of transcription factors, we can successfully build a model that predicts the impact of TF protein sequence mutations.
Impact of the COVID-19 Pandemic on Undergraduate Research in the Department of Biology at Western University: Effect on project types, learning outcomes, and student perceptions
Authors: Chaplin Ava , Kohalmi Susanne , Simon Anne
Published: January 2024

Undergraduate research is a high impact practice that offers numerous benefits to students, academic institutions, and the wider scientific community. Unfortunately, undergraduate research has faced restrictions due to the COVID-19 pandemic. This study aimed to assess how the COVID-19 pandemic has impacted: (1) the number and types of undergraduate research projects performed in the Department of Biology at the University of Western Ontario, and (2) the satisfaction-levels and perceived learning outcomes of students performing these projects. This study also aimed to incorporate a ‘One Health’ framework through an emphasis on stakeholder involvement and the need for future action.

A survey of 33 students who completed an undergraduate research project in the Department of Biology in the 2020/2021 academic year, and 68 students who completed an undergraduate research project in the 5 years prior was conducted. In keeping with the One Health approach, key stakeholders were identified, and a stakeholder map was constructed.

The number of projects performed did not change dramatically despite COVID-19 restrictions. However, a shift towards dry research was observed with 87.9% of students in the 2020/2021 academic year conducting dry research, compared to 16.4% of students in the 5 years prior. Students who conducted research in the 2020/2021 academic year indicated lower overall levels of satisfaction and enjoyment, though their perceived learning outcomes were consistent with students who completed their projects in the 5 years prior. 53 key stakeholders from academia, government, industry, media, and the public were identified.

Students provided invaluable feedback on their undergraduate research experiences that can be used to improve the quality of undergraduate research courses in the Department of Biology in the future. Findings may be of use to other departments and educational institutions that are seeking to improve their own undergraduate research courses amidst the COVID-19 pandemic or looking to incorporate experiential-based learning techniques into existing online courses.
Studying the cellular basis of small bowel enteropathy using high-parameter flow cytometry in mouse models of primary antibody deficiency
Authors: Mohammed Ahmed D. , Ball Ryan A.W. , Jolly Amy , Nagarkatti Prakash , Nagarkatti Mitzi , Kubinak Jason L.
Published: January 2024

Background

Primary immunodeficiencies are heritable defects in immune system function. Antibody deficiency is the most common form of primary immunodeficiency in humans, can be caused by abnormalities in both the development and activation of B cells, and may result from B-cell-intrinsic defects or defective responses by other cells relevant to humoral immunity. Inflammatory gastrointestinal complications are commonly observed in antibody-deficient patients, but the underlying immune mechanisms driving this are largely undefined.

Methods

In this study, several mouse strains reflecting a spectrum of primary antibody deficiency (IgA-/-, Aicda-/-, CD19-/-and JH-/-) were used to generate a functional small-bowel-specific cellular atlas using a novel high-parameter flow cytometry approach that allows for the enumeration of 59 unique cell subsets. Using this cellular atlas, we generated a direct and quantifiable estimate of immune dysregulation. This estimate was then used to identify specific immune factors most predictive of the severity of inflammatory disease of the small bowel (small bowel enteropathy).

Results

Results from our experiments indicate that the severity of primary antibody deficiency positively correlates with the degree of immune dysregulation that can be expected to develop in an individual. In the SI of mice, immune dysregulation is primarily explained by defective homeostatic responses in T cell and invariant natural killer-like T (iNKT) cell subsets. These defects are strongly correlated with abnormalities in the balance between protein (MHCII-mediated) versus lipid (CD1d-mediated) antigen presentation by intestinal epithelial cells (IECs) and intestinal stem cells (ISCs), respectively.

Conclusions

Multivariate statistical approaches can be used to obtain quantifiable estimates of immune dysregulation based on high-parameter flow cytometry readouts of immune function. Using one such estimate, we reveal a previously unrecognized tradeoff between iNKT cell activation and type 1 immunity that underlies disease in the small bowel. The balance between protein/lipid antigen presentation by ISCs may play a crucial role in regulating this balance and thereby suppressing inflammatory disease in the small bowel.
Harnessing Stress: balancing the Burden of Slightly-Deleterious Variants by a Handicap
Authors: Shamanskiy Victor , Popadin Konstantin
Published: January 2024

Numerous empirical studies have revealed epistatic interactions among deleterious variants. In this paper, we assume such interactions are widespread and analyze the resulting shift in mutational burden and average population fitness following the introduction of a strong and universal stress (hereafter “handicap”). We demonstrate that organisms with a low burden of slightly-deleterious variants (SDVs) are more likely to survive exposure to a handicap, whether genetic or environmental, leading to a purifying effect on the population. We further discuss the potential applications of harnessing such interactions for evolutionary and population studies as well as for population management.
Realistic time-lags and litter dynamics alter predictions of plant–soil feedback across generations
Authors: Ou Suzanne X. , Kandlikar Gaurav S. , Warren Magdalena L. , Ke Po-Ju
Published: January 2024

Plant–soil feedback is a critical process in natural plant communities. However, it remains unclear whether greenhouse-measured microbial effects manifest in natural systems with temporally separated growing seasons as classic experiments often overlook seasonal time lags and litter dynamics.

We modified the classic two-phase experiment to study plant–soil feedback for three Californian annual plant species. Our response phase used soil inoculum obtained either immediately after plant conditioning, after a six-month dry period with the conditioning plant removed, or after a dry period with the litter of the conditioning plant. We characterized soil bacterial and fungal communities in different treatments and employed recent advancement in plant–soil feedback theory to predict plant coexistence.

Temporal delays and the presence of litter caused distinct responses in the fungal and bacterial communities, resulting in divergent microbial compositions at the end of the response phases. The delayed response treatments also affected microbially mediated stabilization, fitness differences, and invasion growth rates differently across species pairs, influencing predictions of plant coexistence.

Our study highlights that the interplay between seasonal delays and litter dynamics prevents the direct extrapolation of plant–soil feedback measurements across multiple seasons, emphasizing the necessity of considering natural history when predicting microbially mediated plant coexistence.
High variability in the attractiveness of municipally-planted decorative plants to pollinators
Authors: Czaczkes Tomer J. , Breuss Carsten , Kurze Christoph
Published: January 2024

Insect populations are declining globally. A major driver of this decline is land use change, including urbanisation. However, urban environments can also offer a wide range of floral resources to pollinators, through ornamental plantings, but these can vary widely in their attractiveness to insects. Often, the largest single planter of ornamental plants in an urban area is the municipality. Here we evaluated the decorative plantings carried out by the city municipality of Regensburg, Germany, by systematically surveying insect visitations on different plant types in late summer, when forage is often limited for pollinators. We found a 130-fold increase from the least to the most attractive plants, and high variation in which insect groups were attracted to which plants. While honey bees, which are not conservation concern, were the most common insect visitors, some decorative plants attracted a very large proportion of wild bees, flies, and wasps. Our results demonstrate that there is great scope for increasing the supply of urban forage to pollinators in general, and specific groups in particular, without requiring new decorative plant types to be sourced or planted. We argue that providing local evidence-based guidance to municipalities offers a quick and potentially cost-neutral method for supporting urban insect populations.
Skewness enables stabilising effect of hierarchy in complex competition networks
Authors: Koch Franziska , Neutel Anje-Margriet , Barnes David K.A. , Allhoff Korinna T.
Published: January 2024

1

In observed ecological networks of interference-competition, hierarchy has been shown to generate asymmetric patterns of interaction strengths which enhance system stability. However, it remains unknown whether this stabilising effect of competitive hierarchies depends on the distribution of link strengths. Here, we analysed the relationship between interaction strength distributions, patterning, and system stability. We found that the interaction strengths within 30 observed encrusting, marine bryozoan networks were characterised by a high level of skewness, with many weak and few strong links. We showed that this distribution of link strengths is necessary for the stabilising effect of hierarchy, as skewness enables a patterning that strongly reduces the weight of short and long feedback loops. The stabilising effect of hierarchy did not appear in systems with uniform or normal distributions of interaction strengths. This has important ecological implications, since theoretical studies using random matrices often assume normal or uniform distributions. Since skewed interaction strengths are a common feature of ecological networks, including trophic and mutualistic systems, such theoretical approaches might overlook stabilising mechanisms present in living systems.
AdhE spirosome length in enterohaemorrhagicEscherichia coliis correlated with enzymatic directionality and is perturbed by salicylidene acylhydrazide binding
Authors: Serrano Ester , Tyler Arwen I. I. , Soroor Mostafa , Floria Iris , Kapur Nikil , Roe Andrew J. , Byron Olwyn
Published: January 2024

Antibiotics are contraindicated for the treatment of infection enterohemorrhagicEscherichia coli(EHEC), a human pathogen that causes diarrhea or hemorrhagic colitis in humans which can progress to hemolytic uremic syndrome (HUS). As an alternative to the use of antibiotics, previous studies developed the salicylidene acylhydrazides (SA), a family of anti-virulence compounds capable of blocking expression of the type three secretion system (T3SS), thereby reducing bacterial infections. Here we validate AdhE as the anti-virulence protein target of the SA compound ME0054. AdhE is a bidirectional enzyme able to catalyse the conversion of acetyl-CoA to ethanol andvice versa. AdhE oligomerises forming helicoidal filaments heterogeneous in length called spirosomes. In this work, we show that it is possible to partially fractionate AdhE spirosomes using size exclusion chromatography (SEC) and to characterise the spirosome oligomers present in each fraction with biophysical techniques such as small angle X-ray scattering (SAXS) and sedimentation velocity analytical ultracentrifugation (SV-AUC). Also, we observe that short spirosomes are more efficient in the reverse reaction whereas the spirosome length has no impact on the forward reaction. Therefore, for first time, we reveal that AdhE spirosome formation is necessary to regulate the direction of its enzymatic reactions. In addition, we show that ME0054 disrupts AdhE spirosomes, thereby enhancing the conversion of ethanol to acetyl-CoA. Importantly, SV-AUC data show that ME0054 binds to the AdhE filaments. Finally, time-resolved (TR) SAXS allowed us to follow the kinetics of spirosome disruption produced by ME0054, confirming its effectiveness at biologically relevant temperatures and timescales.

SIGNIFICANCE STATEMENT

There is an urgent need to develop alternative strategies to combat bacterial infections. Salicylidene acylhydrazides (SA) are able to reduce expression of the bacterial type three secretion system (T3SS), used by many pathogens to manipulate host eukaryotic cells, including our pathogen of interest: enterohaemorrhagicE. coli(EHEC). The mechanism underpinning these compounds is a mystery. Here we show how the SA compound ME0054, by disrupting AdhE spirosomes, enhances metabolic conversion of ethanol to acetyl-CoA. This finding is consistent with the phenotype observed in an EHEC AdhE mutant: alterations in acetate levels and changes in T3SS expression. Our work establishes a crucial mechanistic link between the binding of the SA compound to a key target protein and changes in bacterial metabolism.
Restoring O-glycosylation and expression of MUC2 limits progression of colorectal cancer
Authors: Yang Yian , Yin Yuesong , Xu Wei , Kang Yan , Chen Jiawei , Zou Yanfeng , Xiao Zhigang , Li Zheng , Cao Peiguo
Published: January 2024

This study investigated the molecular mechanisms underlying the regulation of MUC2 expression and O-glycosylation modification in colorectal cancer. In addition, the potential of rosiglitazone to inhibit colorectal cancer by improving MUC2 glycosylation to protect intestinal barrier function was explored. In vitro, lectin staining combined with Co-IP assay was used to detect glycosyltransferases regulating MUC2 O-glycosylation. ChIP and Luciferase experiments were used to verify the transcription factors regulating MUC2 expression level. Samples from CRC patients were used to detect differences in multimolecular expression. The AOM/DSS mouse model was used to validate the effect of rosiglitazone on inhibiting colorectal cancer progression. Our results showed that B3GNT6 acts as a glycosyltransferase to enhance the O-glycosylation level of MUC2 and maintain protein stability to resist degradation by StcE secreting from pathogenic bacteria. Furthermore, KLF4 directly promotes the transcription of B3GNT6 and MUC2, which are regulated by PPARg. Rosiglitazone activated PPARg-KLF4-B3GNT6 axis which increased the expression level and glycosylation of MUC2 and further improved the intestinal mucosal barrier function to delay the development of colorectal cancer in mice. These data suggest that O-glycosylation and expression of MUC2 is key to the maintenance of functional intestinal mucosa and rosiglitazone is a potential colorectal cancer therapeutic agent.
A transcription network underlies the dual genomic coordination of mitochondrial biogenesis
Authors: Zhang Fan , Lee Annie , Freitas Anna , Herb Jake , Wang Zongheng , Gupta Snigdha , Chen Zhe , Xu Hong
Published: January 2024

Mitochondrial biogenesis requires the expression of genes encoded by both the nuclear and mitochondrial genomes. However, aside from a handful transcriptional factors regulating specific subsets of mitochondrial genes, the overall architecture of the transcriptional control of mitochondrial biogenesis remains to be elucidated. The mechanisms coordinating these two genomes are largely unknown. We performed a targeted RNAi screen in developing eyes with reduced mitochondrial DNA content, anticipating a synergistic disruption of tissue development due to impaired mitochondrial biogenesis and mtDNA deficiency. Among 638 transcription factors annotated in Drosophila genome, 77 were identified as potential regulators of mitochondrial biogenesis. Utilizing published ChIP-seq data of positive hits, we constructed a regulatory network revealing the logic of the transcription regulation of mitochondrial biogenesis. Multiple transcription factors in core layers had extensive connections, collectively governing the expression of nearly all mitochondrial genes, whereas factors sitting on the top layer may respond to cellular cues to modulate mitochondrial biogenesis through the underlying network. CG1603, a core component of the network, was found to be indispensable for the expression of most nuclear mitochondrial genes, including those required for mtDNA maintenance and gene expression, thus coordinating nuclear genome and mtDNA activities in mitochondrial biogenies. Additional genetics analyses validated YL-1, a transcription factor upstream of CG1603 in the network, as a regulator controlling CG1603 expression and mitochondrial biogenesis.
Synthetic Histology Images for Training AI Models: A Novel Approach to Improve Prostate Cancer Diagnosis
Authors: Van Booven Derek J , Chen Cheng-Bang , Kryvenko Oleksander , Punnen Sanoj , Sandoval Victor , Malpani Sheetal , Noman Ahmed , Ismael Farhan , Briseño Andres , Wang Yujie , Arora Himanshu
Published: January 2024

Prostate cancer (PCa) poses significant challenges for timely diagnosis and prognosis, leading to high mortality rates and increased disease risk and treatment costs. Recent advancements in machine learning and digital imagery offer promising potential for developing automated and objective assessment pipelines that can reduce human capital and resource costs. However, the reliance of AI models on large amounts of clinical data for training presents a significant challenge, as this data is often biased, lacking diversity, and not readily available. Here we aim to address this limitation by employing customized generative adversarial network (GAN) models to produce high-quality synthetic images of different PCa grades (radical prostatectomy (RP)) and needle biopsies, which were customized to account for the granularity associated with each Gleason grade. The generated images were subjected to multiple rounds of benchmarking, quantifications and quality control assessment before being used to train an AI model (EfficientNet) for grading digital histology images of adenocarcinoma specimens (RP sections) and needle biopsies obtained from the PANDA challenge repository. Validation was performed using the AI model trained with synthetic data to grade digital histology from the cancer genome atlas (TCGA) (RP sections) and needle biopsy data from Radboud University Medical Center and Karolinska Institute. Results demonstrated that the AI model trained with a combination of image patches derived from original and enhanced synthetic images outperformed the model trained with original digital histology images. Together, this study demonstrates the potential of customized GAN models to generate a large cohort of synthetic data that can train AI models to effectively grade PCa specimens. This approach could potentially eliminate the need for extensive clinical data for training any AI model in the domain of digital imagery, leading to cost and time-effective diagnosis and prognosis.
Unlocking genome-based prediction and selection in conifers: the key role of within-family prediction accuracy
Authors: Papin Victor , Gorjanc Gregor , Pocrnic Ivan , Bouffier Laurent , Sanchez Leopoldo
Published: January 2024

Context

Genomic selection is a promising approach for forest tree breeding. However, its advantage in terms of prediction accuracy over conventional pedigree-based methods is unclear and within-family accuracy is rarely assessed.

Aims

We used an pedigree-based model (ABLUP) with corrected pedigree data as a baseline reference for assessing the prediction accuracy of genome-based model (GBLUP) at the global and within-family levels in maritime pine (Pinus pinasterAit).

Methods

We sampled 39 full-sib families, each comprising 10 to 40 individuals, to constitute an experimental population of 833 individuals. A stochastic simulation model was also developed to explore other scenarios of heritability, training set size and tagging density.

Results

Prediction accuracies with GBLUP and ABLUP were similar and accuracy with GBLUP within-family was on average zero with large variation between families. Simulations revealed that the number of individuals in the training set was the principal factor limiting GBLUP accuracy in our study and likely in many forest tree breeding programmes. Accurate within-family prediction is possible if 40-65 individuals per full-sib family are included in the genomic training set, from a total of 1600-2000 individuals in the training set.

Conclusion

Such conditions lead to a significant advantage of GBLUP over ABLUP in terms of prediction accuracy and more clearly justify the switch to genome-based prediction and selection in forest trees.
Morphological and genetic analysis of inflorescence and flower development in hemp (Cannabis sativaL.)
Authors: Shi Jiaqi , Schilling Susanne , Melzer Rainer
Published: January 2024

Hemp (Cannabis sativa) is one of the oldest cultivated crops, and its myriad of uses have fascinated humans for millennia. In contemporary agriculture, the seeds are used for high-quality oil, human food, and nutritional supplements. From female inflorescences, secondary compounds (cannabinoids, terpenes, and flavonoids) are isolated that are implicated to have a wide range of medicinal applications. These elements provide hemp with significant market and research value and emphasise the need to thoroughly understand reproductive development in hemp.

Here, we present a detailed morphological and molecular analysis of hemp inflorescence and flower development of the cultivar ‘FINOLA’. Hemp is unusual among flowering plants as it is dioecious, i.e. develops male and female plants. We define eight landmark events in male and female flower development and show that developmental differences between male and female plants extend beyond floral morphology, additionally comprising inflorescence structure as well as flowering time. Further, we demonstrate that the time of activation of key reproductive developmental regulators is significantly different in male and female hemp plants. Our comparison of male and female hemp plants shows that developmental pathways diverge very early, already at the two-leaf stage, laying a basis for further exploration into the genetics of sex determination ofC. sativa.
In SilicoStudy of the Early Stages of Aggregation ofβ-Sheet Forming Antimicrobial Peptide GL13K
Authors: Hamidabad Mohammadreza Niknam , Watson Natalya A. , Wright Lindsay N. , Mansbach R.A.
Published: January 2024

Antimicrobial peptides (AMPs) are of growing interest as potential candidates for antibiotics to which antimicrobial resistance increases slowly. In this article, we perform the firstin silicostudy of the syntheticβsheet-forming AMP GL13K. Through atomistic simulations of single and multipeptide systems under different charge conditions, we are able to shine a light on the short timescales of early aggregation. We find that isolated peptide conformations are primarily dictated by sequence rather than charge, whereas changing charge has a significant impact on the conformational free energy landscape of multi-peptide systems. We demonstrate that the lack of charge-charge repulsion is a sufficient minimal model for experimentally observed aggregation. Overall, our work explores the molecular biophysical underpinnings of the first stages of aggregation of a unique AMP, laying necessary groundwork for its further development as an antibiotic candidate.
Immunotherapy and Cannabis: A Harmful Drug Interaction or Reefer Madness?
Authors: Piper Brian J. , Tian Maria , Saini Pragosh , Higazy Ahmad , Graham Jason , Carbe Christian J. , Bordonaro Michael
Published: January 2024

A retrospective (N=140) and a prospective (N=102) observational Israeli study by Bar-Sela and colleagues about cannabis potentially adversely impacting the response to immunotherapy have together been cited 191 times including by clinical practice guidelines. There have also been reports on PubPeer outlining unverifiable information in their statistics and numerous discrepancies calculating percentages. This report attempted to replicate the data-analysis including non-parametric statistics. Table 1 of the corrected prospective report contained 22 p-values but only one (4.5%) could be verified, despite the authors being transparent about the N and statistics employed. Cannabis users were significantly (p < .0025) younger than non-users but this was not reported in the retrospective report. There were also errors in percentage calculations (e.g. 13/34 reported as 22.0% instead of 38.2%). Overall, these observational investigations, and especially the prospective, appear to contain gross inaccuracies which could impact the statistical decisions (i.e. significant findings reported as non-significant or vice-versa). Although it is mechanistically plausible that cannabis could have immunosuppressive effects which inhibit the response to immuno-therapy, these two reports should be viewed cautiously. Larger prospective studies of this purported drug interaction that account for potential confounds (e.g. greater nicotine smoking among cannabis users) may be warranted. 198 / 200 words

Simple Summary

Two Israeli studies about medical marijuana potentially interfering with immunotherapies like nivolumab for cancer treatment have received substantial attention. However, there have been anonymous but detailed concerns about these reports on PubPeer. This team attempted to verify the data-analysis and statistics of these two reports and the published correction. Many findings including some that could impact the statistical conclusions could not be verified. Of the 22 statistical tests on Table 1 of the prospective report, six could not be repeated using the same statistics and with the provided N. The p-value on 15 corresponded with that of a different statistical test than was listed in the methods. Re-analysis also identified some previously unreported significant differences (e.g. age) between cannabis users and non-users at baseline. Further study of the safety of immunotherapy and cannabis combination may be warranted using patient groups that have been matched on key demographic and medical variables. 150 / 150 words

Graphical abstract
A Systematic Review and Meta-analysis for Association of Celiac Disease and Thyroid Disorders
Authors: Norouzi Zahra , Hasani Fatemeh , Besharat Sima , Shirzad-Aski Hesamaddin , Ghorbani Somayeh , Mohammadi Masoud , Yadegari Anahita , Kalhori Ali
Published: January 2024

It is probable that people who have celiac disease (CD) are more likely to have thyroid disorders. A comprehensive systematic review and meta-analysis were conducted to assess the link between thyroid disorders and CD. Articles were selected from PubMed, Web of Science, Scopus, Ovid, Embase, Cochrane, ProQuest, and Wiley from February 2022 and earlier. A meta-analysis was conducted to evaluate the outcomes, using odds ratios (ORs) and corresponding 95% confidence intervals (95% CIs). The meta-analysis comprised 31 articles with 3310256 participants including 101253 individuals with thyroid disorders. Overall, the frequency of thyroid disease was notably higher in patients with CD compared to the control groups (OR: 3.06, 95% CI: 2.51 – 3.72, P<0.001). The findings of our meta-analysis support the notion that patients with CD are more likely to have autoimmune thyroid disease (ATD) and other thyroid disorders than the control group, thus indicating that regular screening for thyroid disease is necessary for CD patients. Further cohort research is required to investigate the relationship between thyroid disorders and CD.