bluuebunny/crossref_metadata_2025 huggingface dataset:
Structural basis for the access and binding of resolvin D1 (RvD1) to formyl peptide receptor 2 (FPR2/ALX), a class A GPCR
Authors: Mun Brian , Obi Peter , Szlenk Christopher T. , Natesan Senthil
Published: September 2024

Inflammation is essential to the body’s defense against tissue injury and microbial invasion. However, uncontrolled inflammation is highly detrimental and can result in chronic inflammatory diseases such as asthma, cancer, obesity, and diabetes. An increasing body of evidence suggests that specialized pro-resolving lipid mediators (SPMs), such as resolvins, are actively involved in critical cellular events that drive the resolution of inflammation and a return to homeostasis. An imbalance caused by insufficient SPMs can result in the unsuccessful resolution of inflammation. The D-series resolvins (metabolites of docosahexaenoic acid), such as resolvin D1 (RvD1) and resolvin D2 (RvD2), carry out their pro-resolving functions by directly binding to class A G protein-coupled receptors FPR2/ALXR and GPR32, and GPR18, respectively. We recently demonstrated that RvD1 and RvD2 preferentially partition and accumulate at the polar headgroup regions of the membrane. However, the mechanistic detail of how RvD1 gains access to the FPR2 binding site from a surrounding membrane environment remains unknown. In this study, we used classical MD and well-tempered metadynamics simulations to examine the structural basis for the access and binding of RvD1 to its target receptor from aqueous and membrane environments. The results offer valuable insights into the access path, potential binding pose, and key residue interactions essential for the access and binding of RvD1 to FPR2/ALXR and may help in identifying small molecule therapeutics as a possible treatment for inflammatory disorders.
The ECOLOPES PLANT MODEL : a high-resolution model to simulate plant community dynamics in cities and other human-dominated and managed environments
Authors: Joschinski Jens , Boulangeat Isabelle , Calbi Mariasole , Hauck Thomas E. , Vogler Verena , Mimet Anne
Published: September 2024

Cities and urbanized areas have become an important habitat for organisms. Although nature can provide multiple ecosystem services to humans, urban planning and architecture often do not adequately consider the ecological needs of species. In ECOLOPES we envision buildings, and in particular building envelopes, to be a joint habitat for humans, plants, animals and microbiota as equally relevant stakeholders. A centerpiece of the planning and design tools that ECOLOPES provides is a joint soil-plant-animal community model. We present the first prototype of the ECOLOPES PLANT (community) MODEL that responds to 3-dimensional (building) geometry and management, show potential applications as a stand-alone model, and discuss its technical and conceptual limitations that are yet to be overcome.
SeaMoon: Prediction of molecular motions based on language models
Authors: Lombard Valentin , Timsit Dan , Grudinin Sergei , Laine Elodie
Published: September 2024

How protein move and deform determines their interactions with the environment and is thus of utmost importance for cellular functioning. Following the revolution in single protein 3D structure prediction, researchers have focused on repurposing or developing deep learning models for sampling alternative protein conformations. In this work, we explored whether continuous compact representations of protein motions could be predicted directly from protein sequences, without exploiting nor sampling protein structures. Our approach, called SeaMoon, leverages protein Language Model (pLM) embeddings as input to a lightweight (∼1M trainable parameters) convolutional neural network. SeaMoon achieves a success rate of up to 40% when assessed against∼1 000 collections of experimental conformations exhibiting a wide range of motions. SeaMoon capture motions not accessible to the normal mode analysis, an unsupervised physics-based method relying solely on a protein structure’s 3D geometry, and generalises to proteins that do not have any detectable sequence similarity to the training set. SeaMoon is easily retrainable with novel or updated pLMs.
Evolving properties of biological materials captured via needle-based cavity expansion method
Authors: Varner Hannah M. , Naghibzadeh S. Kiana , Spaeth Katie C. , Klein Abigail , Cohen Tal
Published: September 2024

Background

The mechanical properties of biological tissues change over time and with disease progression. Quantifying these mechanical properties can thus be instrumental for medical diagnosis and for evaluation of tissue viability for transplant. However, soft and biological materials are exceptionally challenging to mechanically characterize using conventional testing methods, which are hindered by limitations of sample size, fixturing capabilities, and sample preparation.

Objective

We hypothesize that Volume Controlled Cavity Expansion (VCCE) is well-suited to capture subtle mechanical differences in biological tissue. The objective of this work is therefore twofold: first, we seek to quantify how stiffness of liver and gelatin evolve with age. In achieving this understanding, we aim to demonstrate the precision of VCCE in measuring subtle changes in the mechanical properties of biological tissues.

Methods

Performing VCCE tests over 15 days in samples of gelatin and liver (porcine and bovine), we track the evolving pressure-volume response and deformation limits of the materials.

Results

In both materials, we observed time-dependent variation of the stiffness and fracture thresholds. In gelatin VCCE repeatably captured stiffening over time, which was correlated with a higher fracture stress. This was in contrast to observations in bovine liver, where stiffening corresponded to a lower fracture stress. Porcine liver initially stiffened, then reversed this trend and relaxed.

Conclusion

Through this work we show that liver and gelatin stiffen with age, and that this trend is measurable via VCCE. These results highlight the utility of VCCE and call attention to the need for a new class of mechanism based constitutive models that are capable of capturing variations in material over time with a minimal number of parameters.
Robust and highly efficient transformation method for a minimal Mycoplasma cell
Authors: Mizutani Masaki , Glass John I , Fukatsu Takema , Suzuki Yo , Kakizawa Shigeyuki
Published: September 2024

Mycoplasmas have been widely investigated for their pathogenicity, as well as for genomics and synthetic biology. Conventionally, transformation of mycoplasmas was not highly efficient, and due to the low transformation efficiency, large amounts of DNA and recipient cells were required for that purpose. Here we report a robust and highly efficient transformation method for the minimal cell JCVI-syn3B, which was created through streamlining of the genome ofMycoplasma mycoides. When the growth states of JCVI-syn3B were examined in detail by focusing on such factors as pH, color, absorbance, CFU, and transformation efficiency, we found that the growth phase after the lag phase can be divided into three distinct phases, of which the highest transformation efficiency was observed during the early-exponential growth phase. Notably, we attained the transformation efficiency up to 4.4 × 10-2transformants per cell per μg plasmid DNA. We developed a method to obtain several hundred to several thousand transformants with less than 0.2 mL of cultured cells and 10 ng of plasmid DNA. Moreover, we established a transformation method using frozen stock of transformation-ready cells. These procedures and information could simplify and enhance the transformation process of minimal cells, facilitating advanced genetic engineering and biological research using minimal cells.

IMPORTANCE

Mycoplasmas are parasitic and pathogenic bacteria for many animals. They are also useful bacteria to understand cellular process of life and for bioengineering because of their simple metabolism, small genomes and cultivability. Genetic manipulation is crucial for these purposes, but transformation efficiency in mycoplasmas is typically quite low. Here we report a highly efficient transformation method for the minimal genome mycoplasma JCVI-syn3B. Using this method, transformants can be obtainable only 10 nanograms of plasmid DNA, which is around one-thousandth amount required for traditional mycoplasma transformations. Moreover, we established a convenient method using frozen stocks of transformation-ready cells. These improved methods play a crucial role in further studies using minimal cells.
Opioids Diminish the Placebo Antidepressant Response: A Post Hoc Analysis of a Randomized Controlled Ketamine Trial
Authors: Lii Theresa R. , Flohr Josephine R. , Okada Robin L. , Cianfichi Lisa J. , Hack Laura M. , Schatzberg Alan F. , Heifets Boris D.
Published: September 2024

Background

The endogenous opioid system is thought to play a role in the placebo antidepressant response. A recent trial comparing the rapid antidepressant effects of ketamine versus placebo in surgical patients, some of whom were on chronic opioid therapy, revealed a substantial placebo effect. This finding provided an opportunity to test the hypothesis that opioid agonist exposure interacts with placebo antidepressant responses.

Methods

Thispost hocanalysis utilized data from a previously reported randomized, anesthesia-blinded, placebo-controlled trial of intravenous ketamine in depressed patients undergoing routine surgery. Mixed-effects models were used to determine whether baseline opioid use influenced antidepressant responses to the trial interventions, as measured by the Montgomery-Åsberg Depression Rating Scale (MADRS) over 1 to 14 days post-treatment.

Results

In the placebo arm, baseline opioid use was associated with a 10-point increase (95% CI: 0.81–19.4) in MADRS scores across all post-treatment time points, indicating worse depression in this subgroup. In an alternative model using percent change in MADRS scores, the difference between opioid users and non-users was 38.4% (95% CI: 8.59–68.2), with opioid users experiencing less improvement. For ketamine-treated participants, baseline opioid use did not significantly impact MADRS scores or the percent change in MADRS scores. Pain intensity was not a significant predictor of MADRS outcomes, and the correlation between post-treatment MADRS scores and pain intensity was negligible (R=0.12).

Limitations

This analysis was unregistered and conducted on a small sample; the findings need to be confirmed by prospective controlled studies.

Conclusions

Opioid use at baseline attenuated the placebo antidepressant response independently of pain in depressed patients who received the study treatment under general anesthesia for routine surgery. The antidepressant response was preserved in opioid users who received intravenous ketamine.
Non-invasive epidermal proteome assessment-based diagnosis and molecular subclassification of psoriasis and eczematous dermatitis
Authors: Murphy Michael J. , Chen Gloria , Edemobi Princess , Junejo Muhammad H. , Wride A. Mitchel , Spaulding Sarah L. , Wang Yiwei , Cohen Jeffrey M. , Damsky William
Published: September 2024

Background

Immunologic heterogeneity is known to exist within both eczematous dermatitis and psoriasis; however, selection of molecularly targeted therapies for individual patients generally does assess for or incorporate such information about patient-specific immune changes.

Objective

We sought to develop a rapid, non-invasive method for obtaining and analyzing epidermal protein biomarkers from skin and utilize this methodology to dissect immunologic heterogeneity in both psoriasis and eczematous dermatitis.

Methods

We optimize and evaluate detergent-based immune profiling system (DIPS) which utilizes a combination of two detergents to solubilize full-thickness epidermis when applied to the skin with an applicator. Downstream proteomic profiling of this material allows high-throughput immunologic characterization of immune biomarkers.

Results

DIPS was performed on 43 patients with psoriasis and 27 patients with eczematous dermatitis. This approach was found to be painless, nonscarring, and enabled rapid turnaround from sample collection to data output. We used this approach to accurately differentiate psoriasis and eczema using a limited set of proteins and to identify cases of eczema/psoriasis overlap with non-canonical molecular profiles. Additionally, we measured patient-specific cytokine profiles in eczema that correlated with response to IL-4Rα blockade.

Conclusion

DIPS is a promising new non-invasive cutaneous immune profiling approach that can deconvolute immune heterogeneity amongst patients with both psoriasis and eczematous dermatitis.

Clinical Implication

DIPS has potential applications in both research and day-to-day dermatologic practice and may help personalize diagnosis and medication selection in patients with inflammatory skin diseases.

Capsule summary

Detergent-based immune profiling system (DIPS), a novel non-invasive approach for molecular evaluation of skin disease, is described and evaluated in psoriasis and eczematous dermatitis
Unmasking Neuroendocrine Prostate Cancer with a Machine Learning-Driven 7-Gene Stemness Signature that Predicts Progression
Authors: Sabater Agustina , Sanchis Pablo , Seniuk Rocio , Pascual Gaston , Anselmino Nicolas , Alonso Daniel , Cayol Federico , Vazquez Elba , Marti Marcelo , Cotignola Javier , Toro Ayelen , Labanca Estefania , Bizzotto Juan , Gueron Geraldine
Published: September 2024

Prostate cancer (PCa) poses a significant global health challenge, particularly due to its progression into aggressive forms like neuroendocrine prostate cancer (NEPC). This study developed and validated a stemness-associated gene signature using advanced machine learning techniques, including Random Forest and Lasso regression, applied to large-scale transcriptomic datasets. The resulting 7-gene signature (KMT5C, MEN1, TYMS, IRF5, DNMT3B, CDC25B and DPP4) was validated across independent cohorts and patient-derived xenograft (PDX) models. The signature demonstrated strong prognostic value for progression-free, disease-free, relapse-free, metastasis-free, and overall survival. Importantly, the signature not only identified specific NEPC subtypes, such as large-cell neuroendocrine carcinoma, which is associated with very poor outcomes, but also predicted a poor prognosis for PCa cases that exhibit this molecular signature, even when they were not histopathologically classified as NEPC. This dual prognostic and classifier capability makes the 7-gene signature a robust tool for personalized medicine, providing a valuable resource for predicting disease progression and guiding treatment strategies in PCa management.
Evolutionary uniqueN-glycan-dependent protein quality control system plays pivotal roles in cellular fitness and extracellular vesicle transport inCryptococcus neoformans
Authors: Mota Catia , Kim Kiseung , Son Ye Ji , Thak Eun Jung , Lee Su-Bin , Kim Ju-El , Yoon Jeong-Kee , Kang Min-Ho , Hwang Heeyoun , Bahn Yong-Sun , Alspaugh J. Andrew , Kang Hyun Ah
Published: September 2024

A conservedN-glycan-dependent endoplasmic reticulum protein quality control (ERQC) system has evolved in eukaryotes to ensure accuracy during glycoprotein folding. The human pathogenCryptococcus neoformanspossesses a uniqueN-glycosylation pathway that lacks the glucose addition step to the coreN-glycan precursors in the ER but includes additional basidiomycetes-specific mannosidases. To investigate the molecular features and functions of the ERQC system inC. neoformans,we characterized a set of mutants with deletion of genes coding for the ERQC sensor UDP-glucose:glycoprotein glucosyltransferase (UGG1) and putative α1,2-mannose trimming enzymes (MNS1,MNS101,MNL1, andMNL2). Theugg1Δ,mns1Δ,mns101Δ, andmns1Δ101Δ mutants showed alterations inN-glycan profiles, defective cell surface organization, decreased survival in host cells, and varying degrees of reducedin vivovirulence. Theugg1Δ strain exhibited severely impaired extracellular secretion of capsular polysaccharides and virulence-related enzymes. Comparative transcriptome analysis showed the upregulation of protein folding, proteolysis, and cell wall remodeling genes, which is indicative of induced ER stress inugg1Δ. However, no apparent changes were observed in the expression of genes involved in protein secretion or capsule biosynthesis. Additionally, extracellular vesicle (EV) analysis combined with proteomic analysis showed significant alterations in the number, size distribution, and cargo composition of EVs inugg1Δ. These findings highlight the essential role of the functional ERQC system for cellular fitness under adverse conditions and proper EV-mediated transport of virulence bags, which are crucial for the full fungal pathogenicity ofC. neoformans.
Adaptation to high pressure; insights from the genome of an evolvedEscherichia colistrain with increased piezotolerance
Authors: Allemann Marco N. , Ma Stacey , Sztain Terra , Bartholow Thomas G. , Marshall Ian P.G. , McCammon J. Andrew , Burkart Michael , Allen Eric E. , Bartlett Douglas H. , Marietou Angeliki
Published: September 2024

Pressure is a key environmental parameter that influences the activity and distribution of microbial life on our planet. Despite its key role there is still not a definitive list of essential genes for microbial adaptation to life under increasing pressure. In this study we used a previously characterizedEscherichia colistrain (AN62) evolved to grow at pressure (60 MPa) non-permissive to the parental strain and performed comparative genomics in order to identify the genome-level adaptations that might allowed the observed pressure-adapted phenotype. We identified 18 mutations in total of which 3 mutations were present in both the parental and evolved strain, 3 mutations were only present in the parental strain, and 12 mutations were observed only in the evolved AN62 strain. Among the characterized mutations we observed a point mutation in the acyl carrier protein (acpPV43G). Complementation experiments revealed that the observed V43G mutation in AcpP is responsible for increased levels of cis-vaccenic acid but is not alone responsible for the pressure adapted phenotype. Further molecular dynamics and docking simulations suggested that the V43G mutation promoted stronger binding of the AcpP protein to partner enzymes of the fatty acid biosynthesis pathway involved in fatty acid unsaturation.

Data Summary

Escherichiacoli reads from the parental and evolved strain have been deposited in the Sequence Read Archive (SRA) under accession number RJNA600359. All software used in the bioinformatic analysis is publicly available.

Impact Statement

Pressure is a key environmental parameter. Two-thirds of our planet is covered by oceans with an average depth of 3800m, which means that the majority of the marine life experiences deep sea conditions. Our results offer a list of gene mutations that could contribute to an improved pressure growth phenotype inEscherichia coli, offering a unique insight on the genome level adaptations that might contribute to high pressure adaptation.
Api-TRACE: A System for Honey Bee Tracking in a Constrained Environment to Study Bee Learning Process and the Effect of Lithium on Learning
Authors: Erdem Babur , Ince Ayben , Sevin Sedat , Arslan Okan Can , Gozen Ayse Gul , Giray Tugrul , Alemdar Hande
Published: September 2024

Learning is an adaptive behavior that improves the performance of bees in foraging, dance communication, predator avoidance, and other tasks. Any deficiencies in learning could be detrimental to the long-term survival of the bee colony. Passive avoidance task is a fundamental procedure for investigating learning. We introduce Api-TRACE, a computer vision-aided system to analyze the avoidance assays. Api-TRACE tracks individual bees from the video footage of the assay and detects the moments when they were exposed to a stimulus. The algorithm provides stimulus exposure duration and learning profiles of each individual bee, enabling fast and detailed analysis of the results. Electric shock avoidance assay is one of the most common experimental methods to assess learning. We designed an apparatus for the electric shock avoidance experiments using within-reach hardware and 3D-printed components. We used Api-TRACE and experimental apparatus to investigate the effect of lithium on bee learning success in passive avoidance and reversal learning paradigms through an electric shock avoidance assay. Lithium is a potential chemical for combatingVarroa, a bee (Apis) parasite, and a well-known medication for treating bipolar disorder. It has been known that lithium alters learning in humans and other animals. Before the experiment, we treated the bees with a sucrose solution with 0, 5, 25, and 125 mM LiClad libitum. Our results indicated that a decrement in learning performance emerged with increasing lithium doses in the reversal phase but not in the acquisition of the electric shock avoidance assay.
Dual transposon sequencing (Dual Tn-seq) to probe genome-wide genetic interactions
Authors: Zik Justin J. , Price Morgan N. , Arkin Adam P. , Deutschbauer Adam M. , Sham Lok-To
Published: September 2024

Understanding gene function on a genome-wide scale is a fundamental goal in biology. With the advent of next-generation sequencing, high-throughput methods such as transposon sequencing (Tn- seq) were developed to measure fitness of single deletion mutants en masse. Nevertheless, gene redundancy complicates these approaches, as inactivating genes individually may not produce discernable phenotypes. Here, we report Dual Tn-seq, a technique for simultaneously assaying fitness of a comprehensive pool of double mutants. Dual Tn-seq couples random barcode transposon-site sequencing (RB Tn-seq) with the Cre-loxsystem, allowing us to determine the fitness of ≈68% of all possible double mutant combinations in the human pathogenStreptococcus pneumoniae. Genetic interactions identified from ≈1.4 billion double mutants uncovered new avenues in widely conserved biochemical pathways, exemplified by the discovery of a new CTP synthase and a regulator of peptidoglycan biosynthesis. Since Dual Tn-seq has very few requirements, it can be readily adapted to diverse organisms.
Which perceptual categories do observers experience during multistable perception?
Authors: Skerswetat Jan , Bex Peter J.
Published: September 2024

Multistable perceptual phenomena provide insights into the mind’s dynamic states within a stable external environment and the neural underpinnings of these consciousness changes are often studied with binocular rivalry. Conventional methods to study binocular rivalry suffer from biases and assumptions that limit their ability to describe the continuous nature of this perceptual transitions and to discover what kind of percept was perceived across time. In this study, we propose a novel way to avoid those shortcomings by combining a continuous psychophysical method that estimates introspection during binocular rivalry with machine learning clustering and transition probability analysis. This combination of techniques reveals individual variability and complexity of perceptual experience in 28 normally sighted participants. Also, the analysis of transition probabilities between perceptual categories, i.e., exclusive and different kinds of mixed percepts, suggest that interocular perceptual competition, triggered by low-level stimuli, involves conflict between monocular and binocular neural processing sites rather than mutual inhibition of monocular sites.

Layman abstract

When our brain receives ambiguous information about the world, it changes its interpretation between different alternatives and thereby provides insight into how the mind works. Scientists often use a technique called binocular rivalry, where each eye sees a different image, to provoke an ambiguous visual world that is perceived as ongoing competition among interpretations of the two eyes inputs. Traditional methods for studying binocular rivalry struggle to describe the continuous nature of this fluctuation and to estimate the range of different perceived experiences. We have created a new approach in which participants reproduce their ongoing perceptual experiences combined machine learning analyses of these states. We found that individuals visual experience is more varied and complex than previously thought. Our results suggest that when our eyes see conflicting images, the brain’s effort to make sense of what is seen involves syntheses among both monocular and binocular brain areas, not just competition between monocular areas.
Unsupervised Neural Network-Based Image Stitching Method for Bladder Endoscopy
Authors: Ye Zixing , Shao Chenyu , Zhu Kelei
Published: September 2024

Bladder endoscopy enables the observation of intravesical lesion characteristics, making it an essential tool in urology. Image stitching techniques are commonly employed to expand the field of view of bladder endoscopy. Traditional image stitching methods rely on feature matching. In recent years, deep-learning techniques have garnered significant attention in the field of computer vision. However, the commonly employed supervised learning approaches often require a substantial amount of labeled data, which can be challenging to acquire, especially in the context of medical data. Both feature-based and unreliable supervised methods for cystoscopy image stitching are limited by their quality and the robustness of image stitching. This study proposes an unsupervised neural network-based image stitching method for bladder endoscopy that comprises two modules: an unsupervised alignment network and an unsupervised fusion network. In the unsupervised alignment network, we employed feature convolution, regression networks, and linear transformations to align images. In the unsupervised fusion network, we achieved image fusion from features to pixel by simultaneously eliminating artifacts and enhancing the resolution. Experiments demonstrated our method’s consistent stitching success rate of 98.11% and robust image stitching accuracy at various resolutions. Our method eliminates sutures and flocculent debris from cystoscopy images, presenting good image smoothness while preserving rich textural features. Moreover, our method could successfully stitch challenging scenes such as dim and blurry scenes. Our application of unsupervised deep learning methods in the field of cystoscopy image stitching was successfully validated, laying the foundation for real-time panoramic stitching of bladder endoscopic video images. This advancement provides opportunities for the future development of computer-vision-assisted diagnostic systems for bladder cavities.
Bacterial cell size modulation along the growth curve across nutrient conditions
Authors: Nieto César , Igler Claudia , Singh Abhyudai
Published: September 2024

Under stable growth conditions, bacteria maintain cell size homeostasis through coordinated elongation and division. However, fluctuations in nutrient availability result in dynamic regulation of the target cell size. Using microscopy imaging and mathematical modelling, we examine how bacterial cell volume changes over the growth curve in response to nutrient conditions. We find that two rod-shaped bacteria,Escherichia coliandSalmonella enterica, exhibit similar cell volume distributions in stationary phase cultures irrespective of growth media. Cell resuspension in rich media results in a transient peak with a five-fold increase in cell volume ≈ 2h after resuspension. This maximum cell volume, which depends on nutrient composition, subsequently decreases to the stationary phase cell size. Continuous nutrient supply sustains the maximum volume. In poor nutrient conditions, cell volume shows minimal changes over the growth curve, but a markedly decreased cell width compared to other conditions. The observed cell volume dynamics translate into non-monotonic dynamics in the ratio between biomass (optical density) and cell number (colony-forming units), highlighting their non-linear relationship. Our findings support a heuristic model comparing modulation of cell division relative to growth across nutrient conditions and providing novel insight into the mechanisms of cell size control under dynamic environmental conditions.
Combinatorial responsiveness of single chemosensory neurons to external stimulation of mouse explants revealed by DynamicNeuronTracker
Authors: Noh Jungsik , Wong Wen Mai , Danuser Gaudenz , Meeks Julian P.
Published: September 2024

Calcium fluorescence imaging enables us to investigate how individual neurons of live animals encode sensory input or drive specific behaviors. Extracting and interpreting large-scale neuronal activity from imaging data are crucial steps in harnessing this information. A significant challenge arises from uncorrectable tissue deformation, which disrupts the effectiveness of existing neuron segmentation methods. Here, we propose an open-source software, DynamicNeuronTracker (DyNT), which generates dynamic neuron masks for deforming and/or incompletely registered 3D calcium imaging data using patch-matching iterations. We demonstrate that DyNT accurately tracks densely populated neurons, whereas a widely used static segmentation method often produces erroneous masks. DyNT also includes automated statistical analyses for interpreting neuronal responses to multiple sequential stimuli. We applied DyNT to analyze the responses of pheromone-sensing neurons in mice to controlled stimulation. We found that four bile acids and four sulfated steroids activated 15 subpopulations of sensory neurons with distinct combinatorial response profiles, revealing a strong bias toward detecting sulfated estrogen and pregnanolone.
Adipocyte metabolic state regulates glial phagocytic function
Authors: Alassaf Mroj , Rajan Akhila
Published: September 2024

Obesity and type 2 diabetes are well-established risk factors for neurodegenerative disorders1–4, yet the underlying mechanisms remain poorly understood. The adipocyte-brain axis is crucial for brain function, as adipocytes secrete signaling molecules, including lipids and adipokines, that impinge on neural circuits to regulate feeding and energy expenditure5. Disruptions in the adipocyte-brain axis are associated with neurodegenerative conditions6, but the causal links are not fully understood. Neural debris accumulates with age and injury, and glial phagocytic function is crucial for clearing this debris and maintaining a healthy brain microenvironment7–9. Using adultDrosophila,we investigate how adipocyte metabolism influences glial phagocytic activity in the brain. We demonstrate that a prolonged obesogenic diet increases adipocyte fatty acid oxidation and ketogenesis. Genetic manipulations that mimic obesogenic diet-induced changes in adipocyte lipid and mitochondrial metabolism unexpectedly reduce the expression of the phagocytic receptor Draper inDrosophilamicroglia-like cells in the brain. We identifyApolpp—theDrosophilaequivalent of human apolipoprotein B (ApoB)—as a critical adipocyte-derived signal that regulates glial phagocytosis. Additionally, we show that Lipoprotein Receptor 1 (LpR1), the LDL receptor on phagocytic glia, is required for glial capacity to clear injury-induced neuronal debris. Our findings establish that adipocyte-brain lipoprotein signaling regulates glial phagocytic function, revealing a novel pathway that links adipocyte metabolic disorders with neurodegeneration.

Highlights

Prolonged exposure to an obesogenic diet result in a starvation-like metabolic response in adipose tissue.

Obesogenic diet-induced mitochondrial lipid catabolism in adipose tissue impacts glial phagocytic function.

Adipocyte ApoB is a novel regulator of glial phagocytic function.

LpR1, on ensheathing glia, is required for glial response to axonal injury.

Graphical abstract
MedGraphNet: Leveraging Multi-Relational Graph Neural Networks and Text Knowledge for Biomedical Predictions
Authors: Macaulay Oladimeji , Servilla Michael , Arredondo David , Virupakshappa Kushal , Hu Yue , Tafoya Luis , Zhang Yanfu , Sahu Avinash
Published: September 2024

Genetic, molecular, and environmental factors influence diseases through complex interactions with genes, phenotypes, and drugs. Current methods often fail to integrate diverse multi-relational biological data meaningfully, limiting the discovery of novel risk genes and drugs. To address this, we presentMedGraphNet, a multi-relational Graph Neural Network (GNN) model designed to infer relationships among drugs, genes, diseases, and phenotypes.MedGraphNetinitializes nodes using informative embeddings from existing text knowledge, allowing for robust integration of various data types and improved generalizability. Our results demonstrate thatMedGraphNetmatches and often outperforms traditional single-relation approaches, particularly in scenarios with isolated or sparsely connected nodes. The model shows generalizability to external datasets, achieving high accuracy in identifying disease-gene associations and drug-phenotype relationships. Notably,MedGraphNetaccurately inferred drug side effects without direct training on such data. Using Alzheimer’s disease as a case study,MedGraphNetsuccessfully identified relevant phenotypes, genes, and drugs, corroborated by existing literature. These findings demonstrate the potential of integrating multi-relational data with text knowledge to enhance biomedical predictions and drug repurposing for diseases.MedGraphNetcode is available athttps://github.com/vinash85/MedGraphNet
The evolution and functional significance of the programmed ribosomal frameshift inprfB
Authors: Prince Cassidy R. , Lin Isabella N. , Feaga Heather A.
Published: September 2024

Release Factor 2 (RF2) is one of two peptide release factors that terminate translation in bacteria. InEscherichia coli, the gene encoding RF2,prfB, contains an in-frame premature RF2-specific stop codon. Therefore, a programmed ribosomal frameshift is required to translate full-length RF2. Here, we investigate the diversity ofprfBframeshifting through bioinformatic analyses of >12,000 genomes. We present evidence thatprfBframeshifting autoregulates RF2 levels throughout the bacterial domain since (i) theprfBin-frame stop codon is always TGA or TAA, both of which are recognized by RF2, and never the RF1-specific TAG stop codon, and (ii) species that lack the autoregulatory programmed frameshift likely need higher RF2 levels since, on average, they have significantly higher RF2-specific stop codon usage. Overexpression ofprfBwithout the autoregulatory frameshift motif is toxic toBacillus subtilis, an organism with intermediate RF2-specific stop codon usage. We did not detect the programmed frameshift in any Actinobacteriota. Consistent with this finding, we observed very low frameshift efficiency at theprfBframeshift motif in the ActinobacteriumMycobacterium smegmatis. Our work provides a more complete picture of the evolution of the RF2 programmed frameshifting motif, and its usage to prevent toxic overexpression of RF2.
Dynamic BMP signaling regulates sclerotome induction and lineage diversification in zebrafish
Authors: Xie Linjun , Ma Roger C. , Kocha Katrinka M. , Méndez-Olivos Emilio E. , Huang Peng
Published: September 2024

The sclerotome is an embryonic structure that gives rise to various supportive tissues, including the axial skeleton and connective tissues. Despite its significance, the mechanisms underlying sclerotome induction and diversification during embryonic development remain poorly understood. Sclerotome progenitors exhibit transientbmp4expression and an active response to BMP signaling. Using BMP gain- and loss-of-function tools, we demonstrate that BMP signaling is both necessary and sufficient for sclerotome induction. Furthermore, through mosaic expression of a dominant-negative tool, we show that BMP signaling induces sclerotome fate in a cell-autonomous manner. Interestingly, different populations of sclerotome-derived cells have distinct BMP signaling requirements. Sclerotome-derived notochord-associated cells in the trunk lack BMP response, and sustained BMP signaling inhibits their differentiation into tenocytes. By contrast, sclerotome-derived fin mesenchymal cells in the fin fold require high levels of BMP signaling for proper morphogenesis. Our findings suggest that dynamic regulation of BMP signaling is crucial for the induction of the sclerotome and the subsequent diversification of sclerotome-derived lineages in zebrafish.
From Homogeneity to Heterogeneity: Refining Stochastic Simulations of Gene Regulation
Authors: Chae Seok Joo , Shin Seolah , Lee Seunggyu , Kim Jae Kyoung
Published: September 2024

Cellular processes are intricately controlled through gene regulation, which is significantly influenced by intrinsic noise due to the small number of molecules involved. The Gillespie algorithm, a widely used stochastic simulation method, is pervasively employed to model these systems. However, this algorithm typically assumes that DNA is homogeneously distributed through- out the nucleus, which is not realistic. In this study, we evaluated whether stochastic simulations based on the assumption of spatial homogeneity can accurately capture the dynamics of gene regulation. Our findings indicate that when transcription factors diffuse slowly, these simulations fail to accurately capture gene expression, highlighting the necessity to account for spatial heterogeneity. However, incorporating spatial heterogeneity considerably increases computational time. To address this, we explored various stochastic quasi-steady-state approximations (QSSAs) that simplify the model and reduce simulation time. While both the stochastic total quasi-steady state approximation (stQSSA) and the stochastic low-state quasi-steady-state approximation (slQSSA) reduced simulation time, only the slQSSA provided an accurate model reduction. Our study underscores the importance of utilizing appropriate methods for efficient and accurate stochastic simulations of gene regulatory dynamics, especially when incorporating spatial heterogeneity.
Hebbian induction adds AMPA-labile signaling units to CA3-CA1 synapses in the developing hippocampus
Authors: Abrahamsson Therése , Gustafsson Bengt , Hanse Eric
Published: September 2024

In the 2ndpostnatal week hippocampus, Hebbian-induced long-term potentiation (LTP) of AMPA receptor-mediated transmission in CA3-CA1 synapses is not a genuine potentiation. Instead, it is a de-depression (unsilencing) and temporary stabilization of postsynaptically AMPA-labile synapses silenced by a prior test pulse (0.03 - 0.2 Hz) stimulation. In addition to such an LTP, Hebbian induction at these synapses also results in a labile potentiation that becomes depotentiated by test pulse stimulation, thus appearing as an Hebbian-induced short- term potentiation (STP). Although the induction of this labile potentiation was blocked in the combined presence of N-methyl-D-aspartate (NMDA) and metabotropic glutamate (mGlu) receptor antagonists, the depotentiation was not affected by these drugs. The labile potentiation was not associated with a change in paired-pulse ratio and was, after a depotentiation, fully re-established by a 20 min interruption of test pulse stimulation. These properties are shared with the silencing of previously non-stimulated (naïve) AMPA-labile synapses by such test pulse stimulation. However, the depotentiation following an Hebbian induction is not a re-silencing of naïve AMPA labile synapses since there is no correlation between the magnitudes of depotentiation and preceding silencing of naïve synapses. The present results suggest that Hebbian induction at these neonatal CA3-CA1 synapses, in addition to unsilencing and temporary stabilization of AMPA-labile transmission, creates a labile potentiation based on the insertion/activation of an additional AMPA-labile signaling unit to a pre-existing synapse.
Quantitative in toto live imaging analysis of apical nuclear migration in the mouse telencephalic neuroepithelium
Authors: Shimamura Tsukasa , Miyata Takaki
Published: September 2024

In the embryonic neuroepithelium (NE), neural progenitor cells undergo cell cycle-dependent interkinetic nuclear migration (IKNM) along the apicobasal axis. Extensive IKNM supports increasing cell production rates per unit apical surface, as typically observed in the mammalian telencephalic NE. Apical nucleokinesis during the G2 phase is an essential premitotic event, but its occurrence has not yet been quantitatively analyzed at a large 3D scale with sufficient spatiotemporal resolution. Here, we comprehensively analyzed apically migrating nuclei/somata in reference to their surroundings from embryonic day (E)11 to E13 in the mouse telencephalon. The velocity of apical nucleokinesis decreased, with more frequent nuclear pausing occurring at E12 and E13, whereas the nuclear density in the middle NE zone (20-40 μm deep) increased. This result, together with the results of Shh-mediated overproliferation experiments in which the nuclear density was increased in vivo at E11, suggests that apical nucleokinesis is physically influenced by the surrounding nuclei. Mean square displacement analysis for nuclei being passed by the apically migrating nuclei via horizontal sectioning in toto-recorded movies revealed that the “tissue fluidity” or physical permissiveness of the NE to apical nucleokinesis gradually decreased (E11 > E12 > E13). To further investigate the spatial relationship between preexisting mitoses and subsequent premitotic apical nucleokinesis, the horizontal distribution of mitoses was cumulatively (∼3 hours) analyzed under in toto monitoring. The four-dimensional cumulative apical mitoses presented a “random”, not “clustered” or “regular”, distribution pattern throughout the period examined. These methodologies provide a basis for future comparative studies of interspecies differences.
High
Q
and high gradient performance of the first medium-temperature baking 1.3 GHz cryomodule
Authors: Pan Weimin , Zhai Jiyuan , He Feisi , Ge Rui , Mi Zhenghui , Sha Peng , Jin Song , Han Ruixiong , Wang Qunyao , Lin Haiying , Wang Guangwei , Dai Xuwen , Zhang Zhanjun , Li Mei , Sang Minjing , Sun Liangrui , Ye Rui , Zhao Tongxian , Li Shaopeng , Zhu Keyu , Liu Baiqi , Wang Xiaolong , Yang Xiangchen , Bian Xiaojuan , Zhang Xiangzhen , Ma Huizhou , Zhao Jianbing , Zhang Liang , Zhao Hui , Guo Runbing , Mu Zhihui , Yang Conglai , Zheng Xiaobing , Dong Chao , Zheng Hongjuan , Chang Zhengze , Yang Xiaochen , Huang Tongming , Ma Qiang , Wang Zihan , Liu Ming , Zhou Wenzhong , Chen Senyu
Published: September 2024

The world’s first 1.3 GHz cryomodule containing eight 9-cell superconducting radio-frequency (rf) cavities treated by medium-temperature furnace baking (mid-T bake) was developed at the Institute of High Energy Physics, Chinese Academy of Sciences. The 9-cell cavities in the cryomodule achieved an unprecedented high average intrinsic quality factor (Q0) of 3.8×1010 at 16  MV/m and 3.6×1010 at 21  MV/m in the horizontal test. The cryomodule can operate stably up to a total continuous wave rf voltage greater than 193 MV, with an average cavity usable accelerating gradient of more than 23  MV/m. The results significantly exceed the specifications of Circular Electron Positron Collider and Dalian advanced light source and the other high repetition rate free electron laser facilities [Linac Coherent Light Source II (LCLS-II), LCLS-II-high energy, Shanghai High Repetition Rate X-ray FEL and Extreme Light Facility, Shenzhen Superconducting Soft X-Ray Free Electron Laser, etc.]. There is evidence that the mid-T bake cavity may not require fast cooldown or long processing time in the cryomodule. This paper reviews the cryomodule performance and discusses some important issues in cryomodule assembly and testing.

Published by the American Physical Society
2024
Analytic forms for the
e+e−
annihilation cross sections around a resonance including initial state radiation
Authors: Liu Baoxin , Zhang Zhenyu , Zhou Xiang
Published: September 2024

For the first time, the exact analytic integration of the product between the Kuraev-Fadin radiative function and the Born-level cross section has been achieved for e+e− annihilation near a narrow resonance. The analytic result is in a perfect agreement with the one obtained through direct numerical integration. The extraction of resonance parameters is demonstrated through the unfolding of the initial state radiation effect. The analytic integration significantly accelerates the regression process by more than 160 times compared to numerical integration. Moreover, it facilitates the determination of experimental measurements for physical parameters, such as the two-dimensional confidence region of the branching fraction and the relative phase between the strong and electromagnetic amplitudes, within just one hour instead of one week typically required for numerical integration.

Published by the American Physical Society
2024
Compact dwarfs made of light-quark nuggets
Authors: You Hao-Song , Sun Hao , Li Hong-Bo , Xia Cheng-Jun , Xu Ren-Xin
Published: September 2024

Utilizing an equiparticle model with both linear confinement and leading-order perturbative interactions, we obtain systematically the properties of strangelets and nonstrange quark matter (udQM) nuggets at various baryon (A) and charge (Z) numbers, where the detailed single-quark-energy levels are fixed by solving Dirac equations in mean-field approximation. We then examine the structures of compact dwarfs made of light strangelets or udQM nuggets forming body-centered cubic lattices in a uniform electron background. Despite that the strangelets and udQM nuggets generally become more stable at larger A, the compact dwarfs are still stable since the fusion reactions between those objects do not take place in the presence of a Coulomb barrier, which is similar to the cases of light nuclei in normal white dwarfs. If udQM dwarfs or strangelet dwarfs are covered with normal matter, their masses and radii become larger but do not exceed those of ordinary white dwarfs. Finally, we investigate the radial oscillation frequencies of udQM dwarfs and strangelet dwarfs and find that their frequencies are typically higher than traditional white dwarfs. The stability of compact dwarfs are then analyzed by examining radial oscillation frequencies of the fundamental mode, where compact dwarfs covered by normal matter are still stable.

Published by the American Physical Society
2024
Holographic spin alignment for vector mesons
Authors: Sheng Xin-Li , Zhao Yan-Qing , Li Si-Wen , Becattini Francesco , Hou Defu
Published: September 2024

We develop a general framework for studying the spin alignment ρ00 for flavorless vector mesons by using the gauge/gravity duality. Focusing on the dilepton production through vector meson decay, we derive the relation between production rates at each spin channel and meson’s spectral function in a thermal medium, which can be evaluated by holographic models for a strongly coupled system. As examples, we study ρ00 for J/ψ and ϕ mesons, induced by the relative motion to a thermal background, within the soft-wall model. Spectral functions for J/ψ at T=150  MeV have significant resonance peaks, indicating that c−c¯ can exist as quasistable J/ψ mesons. However, no significant peaks for the ϕ meson are observed at the same temperature, implying that ϕ mesons are melting down at this temperature and spectral functions are interpreted as probabilities of unstable s−s¯ pairs. These pairs are related to free-streaming ϕ mesons by an instantaneous freeze-out assumption, which is performed by sandwiching the in-medium spectral function between the meson’s free-streaming propagators. Then only states with invariant masses closing to the meson’s vacuum mass survive during the freeze-out stage and contribute to final results. We show that ρ00 in the helicity frame for J/ψ and ϕ mesons have positive and negative deviations from 1/3 at T=150  MeV, respectively, which consequently leads to different properties for their global spin alignments.

Published by the American Physical Society
2024